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def request(flow): real_github_token = 'REPLACE_ME!' auth_header = flow.request.headers.get('Authorization') if auth_header: flow.request.headers['Authorization'] = auth_header.replace('__GITHUB_TOKEN_PLACEHOLDER__', real_github_token) def response(flow): recording_proxy = 'http://host.docker.internal:8080' link_header = flow.response.headers.get('Link') if link_header: flow.response.headers['Link'] = link_header.replace('https://api.github.com', recording_proxy) flow.response.content = flow.response.content.replace(b'https://api.github.com', recording_proxy.encode('ascii'))
def request(flow): real_github_token = 'REPLACE_ME!' auth_header = flow.request.headers.get('Authorization') if auth_header: flow.request.headers['Authorization'] = auth_header.replace('__GITHUB_TOKEN_PLACEHOLDER__', real_github_token) def response(flow): recording_proxy = 'http://host.docker.internal:8080' link_header = flow.response.headers.get('Link') if link_header: flow.response.headers['Link'] = link_header.replace('https://api.github.com', recording_proxy) flow.response.content = flow.response.content.replace(b'https://api.github.com', recording_proxy.encode('ascii'))
class TokenMeta: """This class holds some meta data about a token from the text held by a Doc object. This allows to create a Token object when needed. """ def __init__(self, text: str, space_after: bool): """Initializes a TokenMeta object Args: text (str): The token's text. space_after (bool): Whether the token is followed by a single white space (True) or not (False). """ self.text = text self.space_after = space_after # A dictionary to hold custom attributes self.attributes: Dict[str, List[str]] = dict()
class Tokenmeta: """This class holds some meta data about a token from the text held by a Doc object. This allows to create a Token object when needed. """ def __init__(self, text: str, space_after: bool): """Initializes a TokenMeta object Args: text (str): The token's text. space_after (bool): Whether the token is followed by a single white space (True) or not (False). """ self.text = text self.space_after = space_after self.attributes: Dict[str, List[str]] = dict()
TimesTable = int(input("Please Choose A Times Table To Be Quizzed On;\n1)One Times Tables\n2)Two Times Tables\n3)Three Times Tables\n4)Four Times Tables\n5)Five Times Tables\n6)Six Times Tables\n7)Seven Times Tables\n8)Eight Times Tables\n9)Nine Times Tables\n10)Ten Times Tables\n11)Eleven Times Tables\n12)Twelve Times Tables\nPlease Choose One To Start: ")) No1 = 1 ans = 0 for x in range (12): ans = No1 * TimesTable print("\n",No1,"x",TimesTable,"=",ans) No1 = No1 + 1
times_table = int(input('Please Choose A Times Table To Be Quizzed On;\n1)One Times Tables\n2)Two Times Tables\n3)Three Times Tables\n4)Four Times Tables\n5)Five Times Tables\n6)Six Times Tables\n7)Seven Times Tables\n8)Eight Times Tables\n9)Nine Times Tables\n10)Ten Times Tables\n11)Eleven Times Tables\n12)Twelve Times Tables\nPlease Choose One To Start: ')) no1 = 1 ans = 0 for x in range(12): ans = No1 * TimesTable print('\n', No1, 'x', TimesTable, '=', ans) no1 = No1 + 1
nums = (input("")).split() n = int(nums[0]) m = int(nums[1]) l= int(nums[2]) list1 = [] for i in range(n): request = (input("")).split() request[1] = float(request[1]) request[2] = int(request[2]) request[3] = int(request[3]) request.append(i) list1.append(request) list1.sort() list1 = sorted(list1, key=lambda a_entry: a_entry[1]) taken = [] for i in range(m+1): taken.append(False) if(l==1): for i in range(n): if(list1[i][2]==1): if(list1[i][3]==-1): list1[i][2]=0 continue if(list1[i][3]>m): list1[i][3]=-1 elif(list1[i][3]!=0): taken[list1[i][3]]=True index = 1 for i in range(n): if(list1[i][2]==0): if(index>m): list1[i][3]=-1 continue if(list1[i][3]!=0): check =True while(taken[index]): index+=1 if(index>m): check =False break if(check): taken[index]=True list1[i][3]=index index+=1 else: list1[i][3] = -1 else: index = 1 for i in range(n): if(list1[i][3]==-1): list1[i][2] = 0 if(index>m): list1[i][3]=-1 elif(list1[i][3]!=0): list1[i][3]=index index+=1 # print(list1) for i in range(n): print(list1[i][0]+" " + str(list1[i][1])+" " + str(list1[i][2])+" " + str(list1[i][3])) # lst1 = sorted(lst, key=lambda a_entry: a_entry[1]) # print(lst1)
nums = input('').split() n = int(nums[0]) m = int(nums[1]) l = int(nums[2]) list1 = [] for i in range(n): request = input('').split() request[1] = float(request[1]) request[2] = int(request[2]) request[3] = int(request[3]) request.append(i) list1.append(request) list1.sort() list1 = sorted(list1, key=lambda a_entry: a_entry[1]) taken = [] for i in range(m + 1): taken.append(False) if l == 1: for i in range(n): if list1[i][2] == 1: if list1[i][3] == -1: list1[i][2] = 0 continue if list1[i][3] > m: list1[i][3] = -1 elif list1[i][3] != 0: taken[list1[i][3]] = True index = 1 for i in range(n): if list1[i][2] == 0: if index > m: list1[i][3] = -1 continue if list1[i][3] != 0: check = True while taken[index]: index += 1 if index > m: check = False break if check: taken[index] = True list1[i][3] = index index += 1 else: list1[i][3] = -1 else: index = 1 for i in range(n): if list1[i][3] == -1: list1[i][2] = 0 if index > m: list1[i][3] = -1 elif list1[i][3] != 0: list1[i][3] = index index += 1 for i in range(n): print(list1[i][0] + ' ' + str(list1[i][1]) + ' ' + str(list1[i][2]) + ' ' + str(list1[i][3]))
""" Settings, As for the database, look for ../sql_orm/database.py """ #DEBUG/TEST MODE: This allows HTTP connection instead of HTTPS TEST_MODE = True API_PORT = 8000 # These are used only if the TEST_MODE is disabled SSL_CERT_LOCATION = "path" SSL_KEY_LOCATION = "path" SSL_CA_LOCATION = "path" # JWT access settings: Secret key is randomly generated on the first instance and saved to the database (see main) # The algorithm HS256 should not be changed!! Token expiration should be the same on every server ALGORITHM = "HS256" ACCESS_TOKEN_EXPIRE_MINUTES = 30 # How often the server checks for expired ssh authkeys CLEANING_LADY_INTERVAL_SECONDS = 60 # SSH For this particular server! Please refer to what you can actually do: If you are using sish, please use the # version on github.com/santomet as it is currently the one that supports blocking different ports than the ones allowed PORT_LIST = list(range(9000, 9101)) SSH_AUTH_KEYS_FILE_PATH = "/opt/INSTALL/sish/deploy/pubkeys/authorized_keys" SSH_PORT = "2222" SSH_SERVER = "" # If kept empty, agents will use the same IP/DOMAIN that they use to connect the API SSH_SERVER_PUBLIC_FINGERPRINT = "ssh-ed25519 AAAAC3NzaC1lZDI1NTE5AAAAIADBJiJyOZq7Goad/J4IQZaCx70cUjVcMSoIWyzBlKtc" SSH_SERVER_USERNAME = "" # A classic SSH server needs this, SISH does not
""" Settings, As for the database, look for ../sql_orm/database.py """ test_mode = True api_port = 8000 ssl_cert_location = 'path' ssl_key_location = 'path' ssl_ca_location = 'path' algorithm = 'HS256' access_token_expire_minutes = 30 cleaning_lady_interval_seconds = 60 port_list = list(range(9000, 9101)) ssh_auth_keys_file_path = '/opt/INSTALL/sish/deploy/pubkeys/authorized_keys' ssh_port = '2222' ssh_server = '' ssh_server_public_fingerprint = 'ssh-ed25519 AAAAC3NzaC1lZDI1NTE5AAAAIADBJiJyOZq7Goad/J4IQZaCx70cUjVcMSoIWyzBlKtc' ssh_server_username = ''
capitals = ["Amsterdam", "Andorra la Vella", "Athens", "Berlin", "Bratislava", "Brussels", "Dublin", "Helsinki", "Lisbon", "Ljubljana", "Luxembourg", "Madrid", "Monaco", "Nicosia", "Paris", "Riga", "Rome", "San Marino", "Tallinn", "Valletta", "Vatican City", "Vienna", "Vilnius"] # len_cities = len(capitals) # print("length of capital arrays = ",len_cities) countries = ["Netherlands", "Andorra", "Greece", "Germany", "Slovakia", "Belgium", "Ireland", "Finland", "Portugal", "Slovenia", "Luxembourg", "Spain", "Monaco", "Cyprus", "France", "Latvia", "Italy", "San Marino", "Estonia", "Malta", "Vatican City", "Austria", "Lithuania"] # print(capitals.index("Berlin")) print("Rules: All countries and capitals have to be capitalized!\n" "If no correct answers apply enter 'none'\n") capitals_input = input("Name a capital city of a eurozone country: ") if capitals_input in capitals: print("Well done!") countries_input = input(f"Which country is {capitals_input} the capital of? ") if countries_input in countries: if capitals.index(capitals_input) == countries.index(countries_input): print("That's correct") neighbors = { "Netherlands": ["Germany", "Belgium"], "Andorra": ["Spain", "France"], "Greece": ["none"], "Germany": ["France", "Austria", "Netherlands", "Belgium", "Luxembourg"], "Slovakia": ["Austria"], "Belgium": ["Netherlands", "Luxembourg", "Germany", "France"], "Ireland": ["none"], "Finland": ["none"], "Portugal": ["Spain"], "Slovenia": ["Austria", "Italy"], "Luxembourg": ["Belgium", "Germany", "France"], "Spain": ["Portugal", "Andorra", "France"], "Monaco": ["France"], "Cyprus": ["none"], "France": ["Germany", "Spain", "Andorra", "Italy", "Luxembourg", "Monaco", "Belgium"], "Latvia": ["Estonia", "Lithuania"], "Italy": ["San Marino", "Vatican City", "France", "Slovenia", "Austria"], "San Marino": ["Italy"], "Estonia": ["Latvia"], "Malta": ["none"], "Vatican City": ["Italy"], "Austria": ["Italy", "Slovenia", "Slovakia", "Germany"], "Lithuania": ["Latvia"], } neighbor_input = input(f"Can you name any of {countries_input}'s neighboring countries that also use the " f"Euro? (excluding maritime borders) ") if neighbor_input in (neighbors[countries_input]): print("That is correct!") capitals_input_2 = input(f"Do you also know {neighbor_input}'s capital? ") if capitals_input_2 in capitals: if capitals.index(capitals_input_2) == countries.index(neighbor_input): print("Well done!") else: print("That's not the capital.") else: print("That's not a neighboring country!") else: print("Wrong country!") else: print("Country is not on the list!") elif capitals_input == str("no"): print("haiyaaa, why not?") else: print("Wrong!")
capitals = ['Amsterdam', 'Andorra la Vella', 'Athens', 'Berlin', 'Bratislava', 'Brussels', 'Dublin', 'Helsinki', 'Lisbon', 'Ljubljana', 'Luxembourg', 'Madrid', 'Monaco', 'Nicosia', 'Paris', 'Riga', 'Rome', 'San Marino', 'Tallinn', 'Valletta', 'Vatican City', 'Vienna', 'Vilnius'] countries = ['Netherlands', 'Andorra', 'Greece', 'Germany', 'Slovakia', 'Belgium', 'Ireland', 'Finland', 'Portugal', 'Slovenia', 'Luxembourg', 'Spain', 'Monaco', 'Cyprus', 'France', 'Latvia', 'Italy', 'San Marino', 'Estonia', 'Malta', 'Vatican City', 'Austria', 'Lithuania'] print("Rules: All countries and capitals have to be capitalized!\nIf no correct answers apply enter 'none'\n") capitals_input = input('Name a capital city of a eurozone country: ') if capitals_input in capitals: print('Well done!') countries_input = input(f'Which country is {capitals_input} the capital of? ') if countries_input in countries: if capitals.index(capitals_input) == countries.index(countries_input): print("That's correct") neighbors = {'Netherlands': ['Germany', 'Belgium'], 'Andorra': ['Spain', 'France'], 'Greece': ['none'], 'Germany': ['France', 'Austria', 'Netherlands', 'Belgium', 'Luxembourg'], 'Slovakia': ['Austria'], 'Belgium': ['Netherlands', 'Luxembourg', 'Germany', 'France'], 'Ireland': ['none'], 'Finland': ['none'], 'Portugal': ['Spain'], 'Slovenia': ['Austria', 'Italy'], 'Luxembourg': ['Belgium', 'Germany', 'France'], 'Spain': ['Portugal', 'Andorra', 'France'], 'Monaco': ['France'], 'Cyprus': ['none'], 'France': ['Germany', 'Spain', 'Andorra', 'Italy', 'Luxembourg', 'Monaco', 'Belgium'], 'Latvia': ['Estonia', 'Lithuania'], 'Italy': ['San Marino', 'Vatican City', 'France', 'Slovenia', 'Austria'], 'San Marino': ['Italy'], 'Estonia': ['Latvia'], 'Malta': ['none'], 'Vatican City': ['Italy'], 'Austria': ['Italy', 'Slovenia', 'Slovakia', 'Germany'], 'Lithuania': ['Latvia']} neighbor_input = input(f"Can you name any of {countries_input}'s neighboring countries that also use the Euro? (excluding maritime borders) ") if neighbor_input in neighbors[countries_input]: print('That is correct!') capitals_input_2 = input(f"Do you also know {neighbor_input}'s capital? ") if capitals_input_2 in capitals: if capitals.index(capitals_input_2) == countries.index(neighbor_input): print('Well done!') else: print("That's not the capital.") else: print("That's not a neighboring country!") else: print('Wrong country!') else: print('Country is not on the list!') elif capitals_input == str('no'): print('haiyaaa, why not?') else: print('Wrong!')
CONFIG = { 'http': { 'port': 3000 }, 'authentication': { 'salt_rounds': 12, 'secret': '!!! CHANGE ME !!!', 'issuer': 'example.com', 'token_expiry': '24h', 'admin_primary_email': 'admin@localhost', 'admin_default_password': 'admin' }, 'authorization': { 'default_roles': ['user:read', 'user:write', 'public:read'], 'approved_roles': ['posts:write', 'comment:write'] } }
config = {'http': {'port': 3000}, 'authentication': {'salt_rounds': 12, 'secret': '!!! CHANGE ME !!!', 'issuer': 'example.com', 'token_expiry': '24h', 'admin_primary_email': 'admin@localhost', 'admin_default_password': 'admin'}, 'authorization': {'default_roles': ['user:read', 'user:write', 'public:read'], 'approved_roles': ['posts:write', 'comment:write']}}
#!/usr/bin/env python # encoding: utf-8 """ unique_path_ii.py Created by Shengwei on 2014-07-28. """ # https://oj.leetcode.com/problems/unique-paths-ii/ # tags: medium, matrix, path, dp """ Follow up for "Unique Paths": Now consider if some obstacles are added to the grids. How many unique paths would there be? An obstacle and empty space is marked as 1 and 0 respectively in the grid. For example, There is one obstacle in the middle of a 3x3 grid as illustrated below. [ [0,0,0], [0,1,0], [0,0,0] ] The total number of unique paths is 2. Note: m and n will be at most 100. """ # Improvoment: only need O(min(m,n)) space class Solution: # @param obstacleGrid, a list of lists of integers # @return an integer def uniquePathsWithObstacles(self, obstacleGrid): m, n = len(obstacleGrid), len(obstacleGrid[0]) matrix = [[0] * n for _ in range(m - 1)] last_row = [0] * n for index in range(-1, -n - 1, -1): if obstacleGrid[-1][index]: break last_row[index] = 1 matrix.append(last_row) for i in range(-2, -m - 1, -1): for j in range(-1, -n - 1, -1): if obstacleGrid[i][j]: continue down = right = 0 if i + 1 < 0: down = matrix[i + 1][j] if j + 1 < 0: right = matrix[i][j + 1] matrix[i][j] = down + right return matrix[0][0]
""" unique_path_ii.py Created by Shengwei on 2014-07-28. """ '\nFollow up for "Unique Paths":\n\nNow consider if some obstacles are added to the grids. How many unique paths would there be?\n\nAn obstacle and empty space is marked as 1 and 0 respectively in the grid.\n\nFor example,\nThere is one obstacle in the middle of a 3x3 grid as illustrated below.\n\n[\n [0,0,0],\n [0,1,0],\n [0,0,0]\n]\nThe total number of unique paths is 2.\n\nNote: m and n will be at most 100.\n' class Solution: def unique_paths_with_obstacles(self, obstacleGrid): (m, n) = (len(obstacleGrid), len(obstacleGrid[0])) matrix = [[0] * n for _ in range(m - 1)] last_row = [0] * n for index in range(-1, -n - 1, -1): if obstacleGrid[-1][index]: break last_row[index] = 1 matrix.append(last_row) for i in range(-2, -m - 1, -1): for j in range(-1, -n - 1, -1): if obstacleGrid[i][j]: continue down = right = 0 if i + 1 < 0: down = matrix[i + 1][j] if j + 1 < 0: right = matrix[i][j + 1] matrix[i][j] = down + right return matrix[0][0]
class FilePath: regex = '[0-9]{4}' def to_python(self, value): return int(value)
class Filepath: regex = '[0-9]{4}' def to_python(self, value): return int(value)
# Time: O(n) # Space: O(1) class Solution(object): def sumZero(self, n): """ :type n: int :rtype: List[int] """ return [i for i in range(-(n//2), n//2+1) if not (i == 0 and n%2 == 0)]
class Solution(object): def sum_zero(self, n): """ :type n: int :rtype: List[int] """ return [i for i in range(-(n // 2), n // 2 + 1) if not (i == 0 and n % 2 == 0)]
test = {'name': 'q7', 'points': 8, 'suites': [{'cases': [{'code': '>>> t = Tree (1 , [ Tree (2) , Tree (1 , [ ' 'Tree (2 , [ Tree (3 , [ Tree (0)])])])])\n' '\n' '>>> longest_seq( t) # 1 -> 2 -> 3\n' '3\n' '\n' '>>> t = Tree (1)\n' '\n' '>>> longest_seq( t)\n' '1\n'}], 'scored': True, 'setup': 'from q7 import *', 'type': 'doctest'}]}
test = {'name': 'q7', 'points': 8, 'suites': [{'cases': [{'code': '>>> t = Tree (1 , [ Tree (2) , Tree (1 , [ Tree (2 , [ Tree (3 , [ Tree (0)])])])])\n\n>>> longest_seq( t) # 1 -> 2 -> 3\n3\n\n>>> t = Tree (1)\n\n>>> longest_seq( t)\n1\n'}], 'scored': True, 'setup': 'from q7 import *', 'type': 'doctest'}]}
x = [input() for x in range(10)] m = 0 m_index = 0 for i in range(0,10,2): if int(x[i]) > m: m = int(x[i]) m_index = i print(f"a maioe nota foi de {x[m_index+1]} com {x[m_index]} pontos")
x = [input() for x in range(10)] m = 0 m_index = 0 for i in range(0, 10, 2): if int(x[i]) > m: m = int(x[i]) m_index = i print(f'a maioe nota foi de {x[m_index + 1]} com {x[m_index]} pontos')
""" There are two sorted arrays nums1 and nums2 of size m and n respectively. Find the median of the two sorted arrays. The overall run time complexity should be O(log (m+n)). You may assume nums1 and nums2 cannot be both empty. Example 1: nums1 = [1, 3] nums2 = [2] The median is 2.0 Example 2: nums1 = [1, 2] nums2 = [3, 4] The median is (2 + 3)/2 = 2.5 """ #Difficulty: Hard #2085 / 2085 test cases passed. #Runtime: 84 ms #Memory Usage: 14.1 MB #Runtime: 84 ms, faster than 97.56% of Python3 online submissions for Median of Two Sorted Arrays. #Memory Usage: 14.1 MB, less than 5.71% of Python3 online submissions for Median of Two Sorted Arrays. class Solution: #def findMedianSortedArrays(self, nums1: List[int], nums2: List[int]) -> float: def findMedianSortedArrays(nums1, nums2): n = sorted(nums1+nums2) return (n[(len(n)//2)-1]+n[len(n)//2])/2 if len(n)%2 == 0 else n[len(n)//2] #Tests nums1 = [1, 2] nums2 = [3, 4] print(Solution.findMedianSortedArrays(nums1, nums2),'2,5')
""" There are two sorted arrays nums1 and nums2 of size m and n respectively. Find the median of the two sorted arrays. The overall run time complexity should be O(log (m+n)). You may assume nums1 and nums2 cannot be both empty. Example 1: nums1 = [1, 3] nums2 = [2] The median is 2.0 Example 2: nums1 = [1, 2] nums2 = [3, 4] The median is (2 + 3)/2 = 2.5 """ class Solution: def find_median_sorted_arrays(nums1, nums2): n = sorted(nums1 + nums2) return (n[len(n) // 2 - 1] + n[len(n) // 2]) / 2 if len(n) % 2 == 0 else n[len(n) // 2] nums1 = [1, 2] nums2 = [3, 4] print(Solution.findMedianSortedArrays(nums1, nums2), '2,5')
class Commands: def __init__(self, arguments_commandline: list): commands_allowed = ['compile', 'clean'] if len(arguments_commandline) > 1: command = arguments_commandline[1] if not command in commands_allowed: raise Exception("You give an invalid command") self.arguments_commandline = arguments_commandline def is_command_given(self): return len(self.arguments_commandline) > 1 def get_command_given(self): return self.arguments_commandline[1]
class Commands: def __init__(self, arguments_commandline: list): commands_allowed = ['compile', 'clean'] if len(arguments_commandline) > 1: command = arguments_commandline[1] if not command in commands_allowed: raise exception('You give an invalid command') self.arguments_commandline = arguments_commandline def is_command_given(self): return len(self.arguments_commandline) > 1 def get_command_given(self): return self.arguments_commandline[1]
""" Base information for using R in BuildPacks. Keeping this in r.py would lead to cyclic imports. """ # Via https://rstudio.com/products/rstudio/download-server/debian-ubuntu/ RSTUDIO_URL = "https://download2.rstudio.org/server/bionic/amd64/rstudio-server-1.2.5001-amd64.deb" # This is MD5, because that is what RStudio download page provides! RSTUDIO_CHECKSUM = "d33881b9ab786c09556c410e7dc477de" # Via https://www.rstudio.com/products/shiny/download-server/ SHINY_URL = "https://download3.rstudio.org/ubuntu-14.04/x86_64/shiny-server-1.5.12.933-amd64.deb" SHINY_CHECKSUM = "9aeef6613e7f58f21c97a4600921340e" # Version of MRAN to pull devtools from. DEVTOOLS_VERSION = "2018-02-01" # IRKernel version - specified as a tag in the IRKernel repository IRKERNEL_VERSION = "1.0.2" def rstudio_base_scripts(): """Base steps to install RStudio and shiny-server.""" return [ ( "root", # Install RStudio! r""" curl --silent --location --fail {rstudio_url} > /tmp/rstudio.deb && \ echo '{rstudio_checksum} /tmp/rstudio.deb' | md5sum -c - && \ apt-get update && \ apt install -y /tmp/rstudio.deb && \ rm /tmp/rstudio.deb && \ apt-get -qq purge && \ apt-get -qq clean && \ rm -rf /var/lib/apt/lists/* """.format( rstudio_url=RSTUDIO_URL, rstudio_checksum=RSTUDIO_CHECKSUM ), ), ( "root", # Install Shiny Server! r""" curl --silent --location --fail {url} > {deb} && \ echo '{checksum} {deb}' | md5sum -c - && \ dpkg -i {deb} && \ rm {deb} """.format( url=SHINY_URL, checksum=SHINY_CHECKSUM, deb="/tmp/shiny.deb" ), ), ( "${NB_USER}", # Install nbrsessionproxy r""" pip install --no-cache-dir jupyter-server-proxy==1.3.2 && \ pip install --no-cache-dir https://github.com/jupyterhub/jupyter-rsession-proxy/archive/d5efed5455870556fc414f30871d0feca675a4b4.zip && \ jupyter serverextension enable jupyter_server_proxy --sys-prefix && \ jupyter nbextension install --py jupyter_server_proxy --sys-prefix && \ jupyter nbextension enable --py jupyter_server_proxy --sys-prefix """, ), ( # Not all of these locations are configurable; so we make sure # they exist and have the correct permissions "root", r""" install -o ${NB_USER} -g ${NB_USER} -d /var/log/shiny-server && \ install -o ${NB_USER} -g ${NB_USER} -d /var/lib/shiny-server && \ install -o ${NB_USER} -g ${NB_USER} /dev/null /var/log/shiny-server.log && \ install -o ${NB_USER} -g ${NB_USER} /dev/null /var/run/shiny-server.pid """, ), ]
""" Base information for using R in BuildPacks. Keeping this in r.py would lead to cyclic imports. """ rstudio_url = 'https://download2.rstudio.org/server/bionic/amd64/rstudio-server-1.2.5001-amd64.deb' rstudio_checksum = 'd33881b9ab786c09556c410e7dc477de' shiny_url = 'https://download3.rstudio.org/ubuntu-14.04/x86_64/shiny-server-1.5.12.933-amd64.deb' shiny_checksum = '9aeef6613e7f58f21c97a4600921340e' devtools_version = '2018-02-01' irkernel_version = '1.0.2' def rstudio_base_scripts(): """Base steps to install RStudio and shiny-server.""" return [('root', "\n curl --silent --location --fail {rstudio_url} > /tmp/rstudio.deb && \\\n echo '{rstudio_checksum} /tmp/rstudio.deb' | md5sum -c - && \\\n apt-get update && \\\n apt install -y /tmp/rstudio.deb && \\\n rm /tmp/rstudio.deb && \\\n apt-get -qq purge && \\\n apt-get -qq clean && \\\n rm -rf /var/lib/apt/lists/*\n ".format(rstudio_url=RSTUDIO_URL, rstudio_checksum=RSTUDIO_CHECKSUM)), ('root', "\n curl --silent --location --fail {url} > {deb} && \\\n echo '{checksum} {deb}' | md5sum -c - && \\\n dpkg -i {deb} && \\\n rm {deb}\n ".format(url=SHINY_URL, checksum=SHINY_CHECKSUM, deb='/tmp/shiny.deb')), ('${NB_USER}', '\n pip install --no-cache-dir jupyter-server-proxy==1.3.2 && \\\n pip install --no-cache-dir https://github.com/jupyterhub/jupyter-rsession-proxy/archive/d5efed5455870556fc414f30871d0feca675a4b4.zip && \\\n jupyter serverextension enable jupyter_server_proxy --sys-prefix && \\\n jupyter nbextension install --py jupyter_server_proxy --sys-prefix && \\\n jupyter nbextension enable --py jupyter_server_proxy --sys-prefix\n '), ('root', '\n install -o ${NB_USER} -g ${NB_USER} -d /var/log/shiny-server && \\\n install -o ${NB_USER} -g ${NB_USER} -d /var/lib/shiny-server && \\\n install -o ${NB_USER} -g ${NB_USER} /dev/null /var/log/shiny-server.log && \\\n install -o ${NB_USER} -g ${NB_USER} /dev/null /var/run/shiny-server.pid\n ')]
def _map_int(*args): """Convert each element to an int""" return list(map(_int, _flatten(args)))
def _map_int(*args): """Convert each element to an int""" return list(map(_int, _flatten(args)))
class MyClass(object): """This is a test class.""" # Python has no real concept of private elements. """Default class initializer""" # Every method, included in the class definition passes the object in question as its first parameter. # The word 'self' is used for this parameter (usage of self is actually by convention). def __init__(self, prop1 = None): self.prop1 = prop1 def getProp1(self): return self.prop1 def setProp1(self, value): self.prop1 = value @property def prop2(self): """A profoundly important string.""" return self._prop2 @prop2.setter def prop2(self, value): self._prop2 = value def myFunc(self, param1): """This is a test function.""" print(param1) class MyDerivedClass(MyClass): def extraMethod(): print('Child Class!') instance1 = MyClass() instance1.myFunc('Message') print(instance1.getProp1()) instance1.prop2 = "String!" instance2 = MyDerivedClass("First Value") print(instance2.getProp1()) instance2.setProp1('New Value') print(instance2.getProp1()) # Python uses the C3 linearization algorithm to determine the order in which to resolve class attributes, # including methods. This is known as the Method Resolution Order (MRO). # As as a result, it supports multiple inheritance.
class Myclass(object): """This is a test class.""" 'Default class initializer' def __init__(self, prop1=None): self.prop1 = prop1 def get_prop1(self): return self.prop1 def set_prop1(self, value): self.prop1 = value @property def prop2(self): """A profoundly important string.""" return self._prop2 @prop2.setter def prop2(self, value): self._prop2 = value def my_func(self, param1): """This is a test function.""" print(param1) class Myderivedclass(MyClass): def extra_method(): print('Child Class!') instance1 = my_class() instance1.myFunc('Message') print(instance1.getProp1()) instance1.prop2 = 'String!' instance2 = my_derived_class('First Value') print(instance2.getProp1()) instance2.setProp1('New Value') print(instance2.getProp1())
class ResourceVersionStatus(Enum,IComparable,IFormattable,IConvertible): """ An enum indicating whether a resource is current or out of date. enum ResourceVersionStatus,values: Current (0),OutOfDate (1),Unknown (2) """ def __eq__(self,*args): """ x.__eq__(y) <==> x==yx.__eq__(y) <==> x==yx.__eq__(y) <==> x==y """ pass def __format__(self,*args): """ __format__(formattable: IFormattable,format: str) -> str """ pass def __ge__(self,*args): pass def __gt__(self,*args): pass def __init__(self,*args): """ x.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signature """ pass def __le__(self,*args): pass def __lt__(self,*args): pass def __ne__(self,*args): pass def __reduce_ex__(self,*args): pass def __str__(self,*args): pass Current=None OutOfDate=None Unknown=None value__=None
class Resourceversionstatus(Enum, IComparable, IFormattable, IConvertible): """ An enum indicating whether a resource is current or out of date. enum ResourceVersionStatus,values: Current (0),OutOfDate (1),Unknown (2) """ def __eq__(self, *args): """ x.__eq__(y) <==> x==yx.__eq__(y) <==> x==yx.__eq__(y) <==> x==y """ pass def __format__(self, *args): """ __format__(formattable: IFormattable,format: str) -> str """ pass def __ge__(self, *args): pass def __gt__(self, *args): pass def __init__(self, *args): """ x.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signature """ pass def __le__(self, *args): pass def __lt__(self, *args): pass def __ne__(self, *args): pass def __reduce_ex__(self, *args): pass def __str__(self, *args): pass current = None out_of_date = None unknown = None value__ = None
size(200, 400) path = BezierPath() path.polygon((80, 28), (50, 146), (146, 152), (172, 78)) with savedState(): clipPath(path) scale(200/512) image("../images/drawbot.png", (0, 0)) translate(0, 200) with savedState(): scale(200/512) image("../images/drawbot.png", (0, 0))
size(200, 400) path = bezier_path() path.polygon((80, 28), (50, 146), (146, 152), (172, 78)) with saved_state(): clip_path(path) scale(200 / 512) image('../images/drawbot.png', (0, 0)) translate(0, 200) with saved_state(): scale(200 / 512) image('../images/drawbot.png', (0, 0))
with open("input.txt", "r") as input_file: lines = input_file.readlines() reports = [int(line, 2) for line in lines] counts = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] for report in reports: i = 0 num_of_bits = len(counts) while i < num_of_bits: counts[num_of_bits-1-i] += report >> i & 1 i += 1 gamma_string = "" epsilon_string = "" for count in counts: if count > len(lines) / 2: gamma_string += "1" epsilon_string += "0" else: gamma_string += "0" epsilon_string += "1" gamma = int(gamma_string, 2) epsilon = int(epsilon_string, 2) power = gamma * epsilon print(gamma, bin(epsilon), power)
with open('input.txt', 'r') as input_file: lines = input_file.readlines() reports = [int(line, 2) for line in lines] counts = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] for report in reports: i = 0 num_of_bits = len(counts) while i < num_of_bits: counts[num_of_bits - 1 - i] += report >> i & 1 i += 1 gamma_string = '' epsilon_string = '' for count in counts: if count > len(lines) / 2: gamma_string += '1' epsilon_string += '0' else: gamma_string += '0' epsilon_string += '1' gamma = int(gamma_string, 2) epsilon = int(epsilon_string, 2) power = gamma * epsilon print(gamma, bin(epsilon), power)
''' Determine whether an integer is a palindrome. Do this without extra space. Could negative integers be palindromes? (ie, -1) If you are thinking of converting the integer to string, note the restriction of using extra space. You could also try reversing an integer. However, if you have solved the problem "Reverse Integer", you know that the reversed integer might overflow. How would you handle such case? There is a more generic way of solving this problem. ''' class Solution(object): def isPalindrome(self, x): """ :type x: int :rtype: bool """ if x < 0: return False div = 1 while x / div >= 10: div *= 10 while x > 0: l = x // div r = x % 10 if l != r: return False x %= div x //= 10 div /= 100 return True if __name__ == "__main__": assert Solution().isPalindrome(123) == False assert Solution().isPalindrome(12321) == True assert Solution().isPalindrome(-121) == False
""" Determine whether an integer is a palindrome. Do this without extra space. Could negative integers be palindromes? (ie, -1) If you are thinking of converting the integer to string, note the restriction of using extra space. You could also try reversing an integer. However, if you have solved the problem "Reverse Integer", you know that the reversed integer might overflow. How would you handle such case? There is a more generic way of solving this problem. """ class Solution(object): def is_palindrome(self, x): """ :type x: int :rtype: bool """ if x < 0: return False div = 1 while x / div >= 10: div *= 10 while x > 0: l = x // div r = x % 10 if l != r: return False x %= div x //= 10 div /= 100 return True if __name__ == '__main__': assert solution().isPalindrome(123) == False assert solution().isPalindrome(12321) == True assert solution().isPalindrome(-121) == False
class Template: model_owner = "model_owner" detail_view = "detail_view" detail_view_u = "detail_view_u" detail_view_d = "detail_view_d" detail_view_ud = "detail_view_ud" all_objects_view = "all_objects_view" filter_objects_view = "filter_objects_view" user_register_view = "user_register_view" user_profile_view = "user_profile_view" user_profile_detail_view = "user_profile_detail_view"
class Template: model_owner = 'model_owner' detail_view = 'detail_view' detail_view_u = 'detail_view_u' detail_view_d = 'detail_view_d' detail_view_ud = 'detail_view_ud' all_objects_view = 'all_objects_view' filter_objects_view = 'filter_objects_view' user_register_view = 'user_register_view' user_profile_view = 'user_profile_view' user_profile_detail_view = 'user_profile_detail_view'
#Write a function called num_factors. num_factors should #have one parameter, an integer. num_factors should count #how many factors the number has and return that count as #an integer # #A number is a factor of another number if it divides #evenly into that number. For example, 3 is a factor of 6, #but 4 is not. As such, all factors will be less than the #number itself. # #Do not count 1 or the number itself in your factor count. #For example, 6 should have 2 factors: 2 and 3. Do not #count 1 and 6. You may assume the number will be less than #1000. #Add your code here! def num_factors( num ): count = 0 for i in range(2,num): if num % i == 0: count += 1 return count #Below are some lines of code that will test your function. #You can change the value of the variable(s) to test your #function with different inputs. # #If your function works correctly, this will originally #print: 0, 2, 0, 6, 6, each on their own line. print(num_factors(5)) print(num_factors(6)) print(num_factors(97)) print(num_factors(105)) print(num_factors(999))
def num_factors(num): count = 0 for i in range(2, num): if num % i == 0: count += 1 return count print(num_factors(5)) print(num_factors(6)) print(num_factors(97)) print(num_factors(105)) print(num_factors(999))
#!/usr/bin/env python3 # -*- coding: utf-8 -*- def apply_fn_to_list_items_in_dict(dictionary, fn, **kwargs): """ Given a dictionary with items that are lists, applies the given function to each item in each list and return an updated version of the dictionary. :param dictionary: the dictionary to update. :param fn: the function to apply. :param **kwargs: variable keyworded arguments to run fn with :returns: an updated version of the dictionary. """ updated_dictionary = {} for key, items in dictionary.items(): updated_items = [] for item in items: updated_item = fn(item, **kwargs) updated_items.append(updated_item) updated_dictionary[key] = updated_items return updated_dictionary
def apply_fn_to_list_items_in_dict(dictionary, fn, **kwargs): """ Given a dictionary with items that are lists, applies the given function to each item in each list and return an updated version of the dictionary. :param dictionary: the dictionary to update. :param fn: the function to apply. :param **kwargs: variable keyworded arguments to run fn with :returns: an updated version of the dictionary. """ updated_dictionary = {} for (key, items) in dictionary.items(): updated_items = [] for item in items: updated_item = fn(item, **kwargs) updated_items.append(updated_item) updated_dictionary[key] = updated_items return updated_dictionary
# # Created on Sat Apr 25 2020 # # Title: Leetcode - Jump Game # # Author: Vatsal Mistry # Web: mistryvatsal.github.io # # Approach will be to traverse array in reverse, maintain last_optimum_pos # and check whether last_optimum_pos is at the 0 index class Solution: def canJump(self, nums): N = len(nums) last_optimum_pos = N-1 for i in range(N-1, -1, -1): if (i + nums[i]) >= last_optimum_pos: last_optimum_pos = i return (last_optimum_pos == 0)
class Solution: def can_jump(self, nums): n = len(nums) last_optimum_pos = N - 1 for i in range(N - 1, -1, -1): if i + nums[i] >= last_optimum_pos: last_optimum_pos = i return last_optimum_pos == 0
while True: n = int(input()) if n == 0: break ans = 0 for i in range(n): flag = True s = input() for j in range(len(s)): if s[j] == ' ' and ans <= j: flag = False ans = j break if flag and ans < len(s): ans = len(s) print(ans+1)
while True: n = int(input()) if n == 0: break ans = 0 for i in range(n): flag = True s = input() for j in range(len(s)): if s[j] == ' ' and ans <= j: flag = False ans = j break if flag and ans < len(s): ans = len(s) print(ans + 1)
""" Calculating the factors of an integer - a number that evenly divides a larger number """ # # def is_factor(a, b): # if b % a == 0: # return True # else: # return False # # # print(is_factor(2, 1)) """ Find the factors of an integer """ # # # def factors(n): # # for i in range(1, n +1): # if n % i == 0: # print(i) # # factors(6) # """ # Generate a multiplication table # """ # # # def multi_table(n): # for i in range(11): # result = n * i; # print(f"{n} x {i} = {result}") # # # num1 = input("Enter base number: ") # # if not num1.isnumeric(): # print("invalid integer") # else: # num1 = int(num1) # multi_table(num1) # print(f"{0.12345:.3f}") # 1 + 2 + 3 + 4 + 5 = 15 # def summation(num): # total = 0 # # for i in range(1, num + 1): # total = total + i # # return total # sort vs sorted vs reversed # sort - sorts the list (mutates the list) # sorted - returns a sorted list of the specified iterable object # reversed - returns a reversed iterator object # def descending_order(num): # return int("".join(reversed(str(num)))) # # convert string to jaden case # def toJadenCase(string): # return " ".join(word.capitalize() for word in string.split()) def find_next_square(sq): root = math.sqrt(sq) return (root + 1) ** 2 if root.is_integer() else -1
""" Calculating the factors of an integer - a number that evenly divides a larger number """ '\n Find the factors of an integer\n' def find_next_square(sq): root = math.sqrt(sq) return (root + 1) ** 2 if root.is_integer() else -1
# Shopping Options # https://aonecode.com/amazon-online-assessment-shopping-options def getNumberOfOptions(priceOfJeans, priceOfShoes, priceOfSkirts, priceOfTops, dollars): if not priceOfJeans or not priceOfShoes or not priceOfSkirts or not priceOfTops: return 0 js = [] for i in range(len(priceOfJeans)): for j in range(len(priceOfShoes)): js.append(priceOfJeans[i] + priceOfShoes[j]) st = [] for i in range(len(priceOfSkirts)): for j in range(len(priceOfTops)): st.append(priceOfSkirts[i] + priceOfTops[j]) js.sort() st.sort() res = 0 left, right = 0, len(st) - 1 while left < len(js) and right >= 0: if js[left] + st[right] <= dollars: res += right - 0 + 1 left += 1 else: # js[left] + st[right] > dollars right -= 1 return res
def get_number_of_options(priceOfJeans, priceOfShoes, priceOfSkirts, priceOfTops, dollars): if not priceOfJeans or not priceOfShoes or (not priceOfSkirts) or (not priceOfTops): return 0 js = [] for i in range(len(priceOfJeans)): for j in range(len(priceOfShoes)): js.append(priceOfJeans[i] + priceOfShoes[j]) st = [] for i in range(len(priceOfSkirts)): for j in range(len(priceOfTops)): st.append(priceOfSkirts[i] + priceOfTops[j]) js.sort() st.sort() res = 0 (left, right) = (0, len(st) - 1) while left < len(js) and right >= 0: if js[left] + st[right] <= dollars: res += right - 0 + 1 left += 1 else: right -= 1 return res
""" core functionality """ def another_func(a, b): """ just a test Parameters ---------- a : int an input b : float another input See also -------- {{ cookiecutter.project_slug }}.{{ cookiecutter.project_slug }}.a_function """ pass
""" core functionality """ def another_func(a, b): """ just a test Parameters ---------- a : int an input b : float another input See also -------- {{ cookiecutter.project_slug }}.{{ cookiecutter.project_slug }}.a_function """ pass
_base_ = [ '_base_/datasets/cxr14_bs16.py', '_base_/models/resnet50_cxr14.py', '_base_/schedules/cxr14_bs16_ep20.py', '_base_/default_runtime.py' ]
_base_ = ['_base_/datasets/cxr14_bs16.py', '_base_/models/resnet50_cxr14.py', '_base_/schedules/cxr14_bs16_ep20.py', '_base_/default_runtime.py']
#encoding:utf-8 # Write here subreddit name. Like this one for /r/BigAnimeTiddies. subreddit = 'BigAnimeTiddies' # This is for your public telegram channel. t_channel = '@r_BigAnimeTiddies' def send_post(submission, r2t): return r2t.send_simple(submission)
subreddit = 'BigAnimeTiddies' t_channel = '@r_BigAnimeTiddies' def send_post(submission, r2t): return r2t.send_simple(submission)
def rest(): i01.setHeadSpeed(1.0,1.0) i01.setHandSpeed("right", 1.0, 1.0, 1.0, 1.0, 1.0, 1.0) i01.setArmSpeed("right", 1.0, 1.0, 1.0, 1.0) #atach i01.head.neck.attach() i01.head.rothead.attach() i01.rightHand.attach() i01.rightArm.shoulder.attach() i01.rightArm.omoplate.attach() i01.rightArm.bicep.attach() leftneckServo.attach(right, 13) rightneckServo.attach(right, 12) sleep(0.5) #r.arm i01.moveArm("right",0,90,30,10) #head i01.head.neck.moveTo(75) i01.head.rothead.moveTo(88) #r.hand i01.moveHand("right",2,2,2,2,2,88) #roll neck delta = 20 neckMoveTo(restPos,delta) sleep(7) leftneckServo.detach() rightneckServo.detach() i01.detach()
def rest(): i01.setHeadSpeed(1.0, 1.0) i01.setHandSpeed('right', 1.0, 1.0, 1.0, 1.0, 1.0, 1.0) i01.setArmSpeed('right', 1.0, 1.0, 1.0, 1.0) i01.head.neck.attach() i01.head.rothead.attach() i01.rightHand.attach() i01.rightArm.shoulder.attach() i01.rightArm.omoplate.attach() i01.rightArm.bicep.attach() leftneckServo.attach(right, 13) rightneckServo.attach(right, 12) sleep(0.5) i01.moveArm('right', 0, 90, 30, 10) i01.head.neck.moveTo(75) i01.head.rothead.moveTo(88) i01.moveHand('right', 2, 2, 2, 2, 2, 88) delta = 20 neck_move_to(restPos, delta) sleep(7) leftneckServo.detach() rightneckServo.detach() i01.detach()
""" Implementation of a binary Min Heap, represented by an array. """ class MinHeap(): def __init__(self): self.array = [] self.root = None self.size = 0 def parent(heap, i): """ Returns the index of the parent of a given node. """ if i == 0: return 0 return heap.array[(i-1)//2] def left(heap, i): """ Returns the left child of a given node. """ return heap.array[2*i + 1] def right(heap, i): """ Returns the right child of a given node. """ return heap.array[2*i + 2] def return_smallest(heap): """ Returns the smallest value from a correct MinHeap. """ return heap.root def heapify(heap): #TODO pass def insert(heap): #TODO pass
""" Implementation of a binary Min Heap, represented by an array. """ class Minheap: def __init__(self): self.array = [] self.root = None self.size = 0 def parent(heap, i): """ Returns the index of the parent of a given node. """ if i == 0: return 0 return heap.array[(i - 1) // 2] def left(heap, i): """ Returns the left child of a given node. """ return heap.array[2 * i + 1] def right(heap, i): """ Returns the right child of a given node. """ return heap.array[2 * i + 2] def return_smallest(heap): """ Returns the smallest value from a correct MinHeap. """ return heap.root def heapify(heap): pass def insert(heap): pass
#!/usr/bin/python3 for i in range(-10,-100,-30): print(i) print(i)
for i in range(-10, -100, -30): print(i) print(i)
def test_index(client): r = client.get("/") assert r.status_code == 200 def test_paper_page(client): r = client.get("/paper/1812.35598") assert r.status_code == 200
def test_index(client): r = client.get('/') assert r.status_code == 200 def test_paper_page(client): r = client.get('/paper/1812.35598') assert r.status_code == 200
# -*- coding: utf-8 -*- # Licensed under a 3-clause BSD style license, see LICENSE. """ Submodule for useful exceptions =============================== .. note:: not meant for user code in general, though possible. """ # Definition of handy colours for printing _default = "\x1b[00m" _green = "\x1b[01;32m" _red = "\x1b[01;31m" class InvalidOperationError(Exception): """Exception class for meaningless operations.""" def __init__(self, *args, **kwargs): Exception.__init__(self, *args, **kwargs) def __str__(self): """String representation.""" return _red + self.message + _default class SkhepTypeError(Exception): """Exception class for non-instantiable classes.""" def __init__(self, name): Exception.__init__(self, name) self.message = "'{0}' is an abstract base class. Instantiate one of its subclasses instead.".format( name ) def __str__(self): """String representation.""" return _red + self.message + _default
""" Submodule for useful exceptions =============================== .. note:: not meant for user code in general, though possible. """ _default = '\x1b[00m' _green = '\x1b[01;32m' _red = '\x1b[01;31m' class Invalidoperationerror(Exception): """Exception class for meaningless operations.""" def __init__(self, *args, **kwargs): Exception.__init__(self, *args, **kwargs) def __str__(self): """String representation.""" return _red + self.message + _default class Skheptypeerror(Exception): """Exception class for non-instantiable classes.""" def __init__(self, name): Exception.__init__(self, name) self.message = "'{0}' is an abstract base class. Instantiate one of its subclasses instead.".format(name) def __str__(self): """String representation.""" return _red + self.message + _default
class Node: def __init__(self, data=None): self.__data=data self.__next=None @property def data(self): return self.__data @data.setter def data(self, data): self.__data=data @property def next(self): return self.__next @next.setter def next(self, n): self.__next = n class LStack: def __init__(self): self.top=None def empty(self): if self.top is None: return True else: return False def push(self, data): New_node = Node(data) New_node.next = self.top self.top = New_node def pop(self): if self.empty(): return temp = self.top.data self.top = self.top.next return temp def peek(self): if self.empty(): return return self.top.data if __name__ =="__main__": s = LStack() s.push(1) s.push(2) s.push(3) s.push(4) s.push(5) while not s.empty(): print(s.pop(), end=" ")
class Node: def __init__(self, data=None): self.__data = data self.__next = None @property def data(self): return self.__data @data.setter def data(self, data): self.__data = data @property def next(self): return self.__next @next.setter def next(self, n): self.__next = n class Lstack: def __init__(self): self.top = None def empty(self): if self.top is None: return True else: return False def push(self, data): new_node = node(data) New_node.next = self.top self.top = New_node def pop(self): if self.empty(): return temp = self.top.data self.top = self.top.next return temp def peek(self): if self.empty(): return return self.top.data if __name__ == '__main__': s = l_stack() s.push(1) s.push(2) s.push(3) s.push(4) s.push(5) while not s.empty(): print(s.pop(), end=' ')
def pkgs_raw(packages): pkgs_raw_str = "" for package in packages: pkgs_raw_str += str(package) + "\n" print(pkgs_raw_str) def pkgs_traits(packages, traits_to_print): pkgs_traits_str = "" for package in packages: pkgs_traits_str += "\n" for trait in traits_to_print: if trait in package: pkgs_traits_str += "%s: %s\n" % (trait, package[trait]) print(pkgs_traits_str)
def pkgs_raw(packages): pkgs_raw_str = '' for package in packages: pkgs_raw_str += str(package) + '\n' print(pkgs_raw_str) def pkgs_traits(packages, traits_to_print): pkgs_traits_str = '' for package in packages: pkgs_traits_str += '\n' for trait in traits_to_print: if trait in package: pkgs_traits_str += '%s: %s\n' % (trait, package[trait]) print(pkgs_traits_str)
webgui = Runtime.create("webgui","WebGui") # if you don't want the browser to # autostart to homepage # # webgui.autoStartBrowser(false) # set a different port number to listen to # default is 8888 # webgui.setPort(7777) # on startup the webgui will look for a "resources" # directory (may change in the future) # static html files can be placed here and accessed through # the webgui service # starts the websocket server # and attempts to autostart browser webgui.startService();
webgui = Runtime.create('webgui', 'WebGui') webgui.startService()
class Solution: max_time = 0 def numOfMinutes(self, n: int, headID: int, manager: List[int], informTime: List[int]) -> int: global max_time max_time=0 def dfs(adj,node,path_sum): global max_time if adj.get(node)==None: max_time=max(max_time,path_sum) return else: for i in adj[node]: dfs(adj,i,path_sum+informTime[node]) adj={} for i in range(len(manager)): if adj.get(manager[i])!=None: adj[manager[i]].append(i) else: adj[manager[i]]=[i] max_path=0 dfs(adj,headID,0) return max_time
class Solution: max_time = 0 def num_of_minutes(self, n: int, headID: int, manager: List[int], informTime: List[int]) -> int: global max_time max_time = 0 def dfs(adj, node, path_sum): global max_time if adj.get(node) == None: max_time = max(max_time, path_sum) return else: for i in adj[node]: dfs(adj, i, path_sum + informTime[node]) adj = {} for i in range(len(manager)): if adj.get(manager[i]) != None: adj[manager[i]].append(i) else: adj[manager[i]] = [i] max_path = 0 dfs(adj, headID, 0) return max_time
def z_inicial(lista): cont=0 if len(lista) == 0: return else: for i in range(len(lista)): if lista[i][0] == "z" or lista[i][0] == "Z": cont+=1 return cont lista=input().split() print(z_inicial(lista))
def z_inicial(lista): cont = 0 if len(lista) == 0: return else: for i in range(len(lista)): if lista[i][0] == 'z' or lista[i][0] == 'Z': cont += 1 return cont lista = input().split() print(z_inicial(lista))
""" pyexcel_io.constants ~~~~~~~~~~~~~~~~~~~ Constants appeared in pyexcel :copyright: (c) 2014-2017 by Onni Software Ltd. :license: New BSD License """ # flake8: noqa DEFAULT_NAME = 'pyexcel' DEFAULT_SHEET_NAME = '%s_sheet1' % DEFAULT_NAME MESSAGE_INVALID_PARAMETERS = "Invalid parameters" MESSAGE_ERROR_02 = "No content, file name. Nothing is given" MESSAGE_ERROR_03 = "cannot handle unknown content" MESSAGE_WRONG_IO_INSTANCE = "Wrong io instance is passed for your file format." MESSAGE_CANNOT_WRITE_STREAM_FORMATTER = "Cannot write content of file type %s to stream" MESSAGE_CANNOT_READ_STREAM_FORMATTER = "Cannot read content of file type %s from stream" MESSAGE_CANNOT_WRITE_FILE_TYPE_FORMATTER = "Cannot write content of file type %s to file %s" MESSAGE_CANNOT_READ_FILE_TYPE_FORMATTER = "Cannot read content of file type %s from file %s" MESSAGE_LOADING_FORMATTER = "The plugin for file type %s is not installed. Please install %s" MESSAGE_EMPTY_ARRAY = "One empty row is found" MESSAGE_IGNORE_ROW = "One row is ignored" MESSAGE_DB_EXCEPTION = """ Warning: Bulk insertion got below exception. Trying to do it one by one slowly.""" FILE_FORMAT_CSV = 'csv' FILE_FORMAT_TSV = 'tsv' FILE_FORMAT_CSVZ = 'csvz' FILE_FORMAT_TSVZ = 'tsvz' FILE_FORMAT_ODS = 'ods' FILE_FORMAT_XLS = 'xls' FILE_FORMAT_XLSX = 'xlsx' FILE_FORMAT_XLSM = 'xlsm' DB_SQL = 'sql' DB_DJANGO = 'django' KEYWORD_TSV_DIALECT = 'excel-tab' KEYWORD_LINE_TERMINATOR = 'lineterminator' SKIP_DATA = -1 TAKE_DATA = 0 STOP_ITERATION = 1
""" pyexcel_io.constants ~~~~~~~~~~~~~~~~~~~ Constants appeared in pyexcel :copyright: (c) 2014-2017 by Onni Software Ltd. :license: New BSD License """ default_name = 'pyexcel' default_sheet_name = '%s_sheet1' % DEFAULT_NAME message_invalid_parameters = 'Invalid parameters' message_error_02 = 'No content, file name. Nothing is given' message_error_03 = 'cannot handle unknown content' message_wrong_io_instance = 'Wrong io instance is passed for your file format.' message_cannot_write_stream_formatter = 'Cannot write content of file type %s to stream' message_cannot_read_stream_formatter = 'Cannot read content of file type %s from stream' message_cannot_write_file_type_formatter = 'Cannot write content of file type %s to file %s' message_cannot_read_file_type_formatter = 'Cannot read content of file type %s from file %s' message_loading_formatter = 'The plugin for file type %s is not installed. Please install %s' message_empty_array = 'One empty row is found' message_ignore_row = 'One row is ignored' message_db_exception = '\nWarning: Bulk insertion got below exception. Trying to do it one by one slowly.' file_format_csv = 'csv' file_format_tsv = 'tsv' file_format_csvz = 'csvz' file_format_tsvz = 'tsvz' file_format_ods = 'ods' file_format_xls = 'xls' file_format_xlsx = 'xlsx' file_format_xlsm = 'xlsm' db_sql = 'sql' db_django = 'django' keyword_tsv_dialect = 'excel-tab' keyword_line_terminator = 'lineterminator' skip_data = -1 take_data = 0 stop_iteration = 1
''' Problem # 3 Write a program that takes the salary and grade from user. It then adds 50% bonus if the grade is greater tha 15. It adds 25% bonus if the grade is 15 or less and then it should display the salary Pseudocode 1. Start 2. Take the salary and grade from the user 3. If the grade is greater than 15 then 1. Calculate the bonus using the formula 50 / 100 * salary # can also use 1.5 4. Otherwise do the following 1. Caculate the bonus using the formula 25 / 100 * salary # can also use 1.25 5. Calculate the total salary using salary = salary + bonus. 6. Display the total salary 7. End # I need to create three variables: # 1. Salary needs to be a floating point number # 2. grade needs to be a interger # 3. bonus should be a floating point number Main | Real Salary | Real bonus | Interger grade | Input Salary | Input bonus | False | True ____if grade > 15__________________________ | | Bonus = 25/100 * salary bonus = 50/100 * salary |_______________________ 0 _____________| | salary = salary + bonus | Output"Your total salary is"salary and bonus | End ''' salary = float(input("please enter the salary: ")) grade = int(input("please enter your grade: ")) if grade > 15: bonus = 50 / 100 * salary else: bonus = 25 / 100 * salary salary += bonus # salary = salary + bonus print("Your total salary is", salary) # please enter the salary: 50000 # please enter your grade: 18 # Your total salary is 75000.0
""" Problem # 3 Write a program that takes the salary and grade from user. It then adds 50% bonus if the grade is greater tha 15. It adds 25% bonus if the grade is 15 or less and then it should display the salary Pseudocode 1. Start 2. Take the salary and grade from the user 3. If the grade is greater than 15 then 1. Calculate the bonus using the formula 50 / 100 * salary # can also use 1.5 4. Otherwise do the following 1. Caculate the bonus using the formula 25 / 100 * salary # can also use 1.25 5. Calculate the total salary using salary = salary + bonus. 6. Display the total salary 7. End # I need to create three variables: # 1. Salary needs to be a floating point number # 2. grade needs to be a interger # 3. bonus should be a floating point number Main | Real Salary | Real bonus | Interger grade | Input Salary | Input bonus | False | True ____if grade > 15__________________________ | | Bonus = 25/100 * salary bonus = 50/100 * salary |_______________________ 0 _____________| | salary = salary + bonus | Output"Your total salary is"salary and bonus | End """ salary = float(input('please enter the salary: ')) grade = int(input('please enter your grade: ')) if grade > 15: bonus = 50 / 100 * salary else: bonus = 25 / 100 * salary salary += bonus print('Your total salary is', salary)
## 1. Overview ## f = open("movie_metadata.csv", 'r') movie_metadata = f.read() movie_metadata = movie_metadata.split('\n') movie_data = [] for element in movie_metadata: row = element.split(',') movie_data.append(row) print(movie_data[:5]) ## 3. Writing Our Own Functions ## def first_elts(nested_lists): list_heads = [] for n_list in nested_lists: list_heads.append(n_list[0]) return list_heads movie_names = first_elts(movie_data) print(movie_names) ## 4. Functions with Multiple Return Paths ## def is_usa(movie): origin_idx = 6 return True if movie[origin_idx] == "USA" else False wonder_woman = ['Wonder Woman','Patty Jenkins','Color',141,'Gal Gadot','English','USA',2017] wonder_woman_usa = is_usa(wonder_woman) ## 5. Functions with Multiple Arguments ## wonder_woman = ['Wonder Woman','Patty Jenkins','Color',141,'Gal Gadot','English','USA',2017] def is_usa(input_lst): if input_lst[6] == "USA": return True else: return False def index_equals_str(input_lst, index, input_str): return input_lst[index] == input_str wonder_woman_in_color = index_equals_str(wonder_woman, 2, "Color") ## 6. Optional Arguments ## def index_equals_str(input_lst,index,input_str): if input_lst[index] == input_str: return True else: return False def counter(input_lst,header_row = False): num_elt = 0 if header_row == True: input_lst = input_lst[1:len(input_lst)] for each in input_lst: num_elt = num_elt + 1 return num_elt def feature_counter(input_lst, index, input_str, header_row=False): num_feature = 0 if header_row == True: input_lst = input_lst[1:] for row in input_lst: num_feature += 1 if row[index] == input_str else 0 return num_feature num_of_us_movies = feature_counter(movie_data, 6, "USA", True) ## 7. Calling a Function inside another Function ## def feature_counter(input_lst, index, input_str, header_row = False): num_elt = 0 if header_row == True: input_lst = input_lst[1:] for each in input_lst: if each[index] == input_str: num_elt += 1 return num_elt def summary_statistics(input_lst): input_lst = input_lst[1:] num_japan_films = feature_counter(input_lst, 6, "Japan") num_color_films = feature_counter(input_lst, 2, "Color") num_films_in_english = feature_counter(input_lst, 5, "English") summary_dict = {"japan_films": num_japan_films, "color_films": num_color_films, "films_in_english": num_films_in_english} return summary_dict summary = summary_statistics(movie_data)
f = open('movie_metadata.csv', 'r') movie_metadata = f.read() movie_metadata = movie_metadata.split('\n') movie_data = [] for element in movie_metadata: row = element.split(',') movie_data.append(row) print(movie_data[:5]) def first_elts(nested_lists): list_heads = [] for n_list in nested_lists: list_heads.append(n_list[0]) return list_heads movie_names = first_elts(movie_data) print(movie_names) def is_usa(movie): origin_idx = 6 return True if movie[origin_idx] == 'USA' else False wonder_woman = ['Wonder Woman', 'Patty Jenkins', 'Color', 141, 'Gal Gadot', 'English', 'USA', 2017] wonder_woman_usa = is_usa(wonder_woman) wonder_woman = ['Wonder Woman', 'Patty Jenkins', 'Color', 141, 'Gal Gadot', 'English', 'USA', 2017] def is_usa(input_lst): if input_lst[6] == 'USA': return True else: return False def index_equals_str(input_lst, index, input_str): return input_lst[index] == input_str wonder_woman_in_color = index_equals_str(wonder_woman, 2, 'Color') def index_equals_str(input_lst, index, input_str): if input_lst[index] == input_str: return True else: return False def counter(input_lst, header_row=False): num_elt = 0 if header_row == True: input_lst = input_lst[1:len(input_lst)] for each in input_lst: num_elt = num_elt + 1 return num_elt def feature_counter(input_lst, index, input_str, header_row=False): num_feature = 0 if header_row == True: input_lst = input_lst[1:] for row in input_lst: num_feature += 1 if row[index] == input_str else 0 return num_feature num_of_us_movies = feature_counter(movie_data, 6, 'USA', True) def feature_counter(input_lst, index, input_str, header_row=False): num_elt = 0 if header_row == True: input_lst = input_lst[1:] for each in input_lst: if each[index] == input_str: num_elt += 1 return num_elt def summary_statistics(input_lst): input_lst = input_lst[1:] num_japan_films = feature_counter(input_lst, 6, 'Japan') num_color_films = feature_counter(input_lst, 2, 'Color') num_films_in_english = feature_counter(input_lst, 5, 'English') summary_dict = {'japan_films': num_japan_films, 'color_films': num_color_films, 'films_in_english': num_films_in_english} return summary_dict summary = summary_statistics(movie_data)
# -*- coding: utf-8 -*- # # Copyright (c) 2017 Hewlett Packard Enterprise Development LP # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. Manifest = { 'Name': 'temp_sensor_status_transition_monitor', 'Description': 'Network Analytics Agent Script to monitor' 'status transitions of all temperature sensors', 'Version': '1.0', 'Author': 'Aruba Networks' } class Policy(NAE): def __init__(self): self.variables['sensors_list'] = '' uri1 = '/rest/v1/system/subsystems/*/*/temp_sensors/*?' \ 'attributes=status' self.m1 = Monitor(uri1, 'Sensor Status') # MONITOR NORMAL STATE TRANSITIONS # Normal -> Min self.r1 = Rule('Sensor Status - Normal -> Min') self.r1.condition( 'transition {} from "normal" to "min"', [self.m1]) self.r1.action(self.sensor_status_action_normal) # Normal -> Max self.r2 = Rule('Sensor Status - Normal -> Max') self.r2.condition( 'transition {} from "normal" to "max"', [self.m1]) self.r2.action(self.sensor_status_action_normal) # Low Critical -> Min self.r3 = Rule('Sensor Status - Low Critical -> Min') self.r3.condition( 'transition {} from "low_critical" to "min"', [self.m1]) self.r3.action(self.sensor_status_action_normal) # Critical -> Max self.r4 = Rule('Sensor Status - Critical -> Max') self.r4.condition( 'transition {} from "critical" to "max"', [self.m1]) self.r4.action(self.sensor_status_action_normal) # Fault -> Uninitialized self.r5 = Rule('Sensor Status - Fault -> Uninitialized') self.r5.condition( 'transition {} from "fault" to "uninitialized"', [self.m1]) self.r5.action(self.sensor_status_action_normal) # Fault -> Normal self.r6 = Rule('Sensor Status - Fault -> Normal') self.r6.condition( 'transition {} from "fault" to "normal"', [self.m1]) self.r6.action(self.sensor_status_action_normal) # Fault -> Min self.r7 = Rule('Sensor Status - Fault -> Min') self.r7.condition( 'transition {} from "fault" to "min"', [self.m1]) self.r7.action(self.sensor_status_action_normal) # Fault -> Max self.r8 = Rule('Sensor Status - Fault -> Max') self.r8.condition( 'transition {} from "fault" to "max"', [self.m1]) self.r8.action(self.sensor_status_action_normal) # MONITOR CRITICAL STATE TRANSITIONS # Min -> Low Critical self.r9 = Rule('Sensor Status - Min -> Low Critical') self.r9.condition( 'transition {} from "min" to "low_critical"', [self.m1]) self.r9.action(self.sensor_status_action_critical) # Max -> Critical self.r10 = Rule('Sensor Status - Max -> Critical') self.r10.condition( 'transition {} from "max" to "critical"', [self.m1]) self.r10.action(self.sensor_status_action_critical) # Critical -> Emergency self.r11 = Rule( 'Sensor Status - Critical -> Emergency') self.r11.condition( 'transition {} from "critical" to "emergency"', [self.m1]) self.r11.action(self.sensor_status_action_critical) # Emergency -> Critical self.r12 = Rule('Sensor Status - Emergency -> Critical') self.r12.condition( 'transition {} from "emergency" to "critical"', [self.m1]) self.r12.action(self.sensor_status_action_critical) # Uninitialized -> Fault self.r13 = Rule('Sensor Status - Uninitialized -> Fault') self.r13.condition( 'transition {} from "uninitialized" to "fault"', [self.m1]) self.r13.action(self.sensor_status_action_critical) # Normal -> Fault self.r14 = Rule('Sensor Status - Normal -> Fault') self.r14.condition( 'transition {} from "normal" to "fault"', [self.m1]) self.r14.action(self.sensor_status_action_critical) # Min -> Fault self.r15 = Rule('Sensor Status - Min -> Fault') self.r15.condition( 'transition {} from "min" to "fault"', [self.m1]) self.r15.action(self.sensor_status_action_critical) # Low Critical -> Fault self.r16 = Rule('Sensor Status - Low Critical -> Fault') self.r16.condition( 'transition {} from "low_critical" to "fault"', [self.m1]) self.r16.action(self.sensor_status_action_critical) # Max -> Fault self.r17 = Rule('Sensor Status - Max -> Fault') self.r17.condition( 'transition {} from "max" to "fault"', [self.m1]) self.r17.action(self.sensor_status_action_critical) # Critical -> Fault self.r18 = Rule('Sensor Status - Critical -> Fault') self.r18.condition( 'transition {} from "critical" to "fault"', [self.m1]) self.r18.action(self.sensor_status_action_critical) # Emergency -> Fault self.r19 = Rule('Sensor Status - Emergency -> Fault') self.r19.condition( 'transition {} from "emergency" to "fault"', [self.m1]) self.r19.action(self.sensor_status_action_critical) # Fault -> Emergency self.r20 = Rule('Sensor Status - Fault -> Emergency') self.r20.condition( 'transition {} from "fault" to "emergency"', [self.m1]) self.r20.action(self.sensor_status_action_critical) # Fault -> Critical self.r21 = Rule('Sensor Status - Fault -> Critical') self.r21.condition( 'transition {} from "fault" to "critical"', [self.m1]) self.r21.action(self.sensor_status_action_critical) # Fault -> Low Critical self.r22 = Rule('Sensor Status - Fault -> Low Critical') self.r22.condition( 'transition {} from "fault" to "low_critical"', [self.m1]) self.r22.action(self.sensor_status_action_critical) def sensor_status_action_critical(self, event): self.logger.debug('********CRITICAL********') self.logger.debug('LABEL = ' + event['labels'] + 'VALUE = ' + event['value']) label = str(event['labels']) labelsplit = label.split(",") readsensor = labelsplit[1] readsensorsplit = readsensor.split("=") sensorname = str(readsensorsplit[1]) self.logger.debug('Sensor Name= ' + sensorname) if self.variables['sensors_list'] != '': findsensor = self.variables['sensors_list'] istrue = findsensor.find(sensorname) if istrue == -1: sensors_list = sensorname + self.variables['sensors_list'] self.variables['sensors_list'] = sensors_list self.logger.debug('list of sensors : ' + self.variables['sensors_list']) self.setactions(sensorname) else: ActionSyslog('Sensor: ' + sensorname + ' is in Critical state') ActionCLI('show environment temperature') else: self.variables['sensors_list'] = sensorname self.logger.debug('list of sensors:' + self.variables['sensors_list']) self.setactions(sensorname) def setactions(self, sensorname): self.logger.debug('+++ CALLBACK: SENSOR STATUS - CRITICAL!') self.set_alert_level(AlertLevel.CRITICAL) ActionSyslog('Sensor: ' + sensorname + ' is in Critical state') ActionCLI('show environment temperature') def sensor_status_action_normal(self, event): if self.get_alert_level() is not None: if self.variables['sensors_list'] == '': self.set_policy_status_normal() else: print('********NORMAL********') label = str(event['labels']) labelsplit = label.split(",") readsensor = labelsplit[1] readsensorsplit = readsensor.split("=") sensorname = str(readsensorsplit[1]) ''' delete all Sensor Name's which moved back to Normal state from Critical state ''' index = 0 length = len(sensorname) findsensor = self.variables['sensors_list'] index = findsensor.find(sensorname) if index != -1: # index = string.find(str, substr) findsensor = findsensor[ 0:index] + findsensor[ index + length:] self.variables['sensors_list'] = findsensor self.logger.debug('Sensor name deleted: ' + sensorname) self.logger.debug('Current Sensors list: ' + self.variables['sensors_list']) ActionSyslog('Sensor ' + sensorname + ' is back to Normal') if self.variables['sensors_list'] == '': self.set_policy_status_normal() def set_policy_status_normal(self): self.remove_alert_level() ActionSyslog('All Sensors are Normal')
manifest = {'Name': 'temp_sensor_status_transition_monitor', 'Description': 'Network Analytics Agent Script to monitorstatus transitions of all temperature sensors', 'Version': '1.0', 'Author': 'Aruba Networks'} class Policy(NAE): def __init__(self): self.variables['sensors_list'] = '' uri1 = '/rest/v1/system/subsystems/*/*/temp_sensors/*?attributes=status' self.m1 = monitor(uri1, 'Sensor Status') self.r1 = rule('Sensor Status - Normal -> Min') self.r1.condition('transition {} from "normal" to "min"', [self.m1]) self.r1.action(self.sensor_status_action_normal) self.r2 = rule('Sensor Status - Normal -> Max') self.r2.condition('transition {} from "normal" to "max"', [self.m1]) self.r2.action(self.sensor_status_action_normal) self.r3 = rule('Sensor Status - Low Critical -> Min') self.r3.condition('transition {} from "low_critical" to "min"', [self.m1]) self.r3.action(self.sensor_status_action_normal) self.r4 = rule('Sensor Status - Critical -> Max') self.r4.condition('transition {} from "critical" to "max"', [self.m1]) self.r4.action(self.sensor_status_action_normal) self.r5 = rule('Sensor Status - Fault -> Uninitialized') self.r5.condition('transition {} from "fault" to "uninitialized"', [self.m1]) self.r5.action(self.sensor_status_action_normal) self.r6 = rule('Sensor Status - Fault -> Normal') self.r6.condition('transition {} from "fault" to "normal"', [self.m1]) self.r6.action(self.sensor_status_action_normal) self.r7 = rule('Sensor Status - Fault -> Min') self.r7.condition('transition {} from "fault" to "min"', [self.m1]) self.r7.action(self.sensor_status_action_normal) self.r8 = rule('Sensor Status - Fault -> Max') self.r8.condition('transition {} from "fault" to "max"', [self.m1]) self.r8.action(self.sensor_status_action_normal) self.r9 = rule('Sensor Status - Min -> Low Critical') self.r9.condition('transition {} from "min" to "low_critical"', [self.m1]) self.r9.action(self.sensor_status_action_critical) self.r10 = rule('Sensor Status - Max -> Critical') self.r10.condition('transition {} from "max" to "critical"', [self.m1]) self.r10.action(self.sensor_status_action_critical) self.r11 = rule('Sensor Status - Critical -> Emergency') self.r11.condition('transition {} from "critical" to "emergency"', [self.m1]) self.r11.action(self.sensor_status_action_critical) self.r12 = rule('Sensor Status - Emergency -> Critical') self.r12.condition('transition {} from "emergency" to "critical"', [self.m1]) self.r12.action(self.sensor_status_action_critical) self.r13 = rule('Sensor Status - Uninitialized -> Fault') self.r13.condition('transition {} from "uninitialized" to "fault"', [self.m1]) self.r13.action(self.sensor_status_action_critical) self.r14 = rule('Sensor Status - Normal -> Fault') self.r14.condition('transition {} from "normal" to "fault"', [self.m1]) self.r14.action(self.sensor_status_action_critical) self.r15 = rule('Sensor Status - Min -> Fault') self.r15.condition('transition {} from "min" to "fault"', [self.m1]) self.r15.action(self.sensor_status_action_critical) self.r16 = rule('Sensor Status - Low Critical -> Fault') self.r16.condition('transition {} from "low_critical" to "fault"', [self.m1]) self.r16.action(self.sensor_status_action_critical) self.r17 = rule('Sensor Status - Max -> Fault') self.r17.condition('transition {} from "max" to "fault"', [self.m1]) self.r17.action(self.sensor_status_action_critical) self.r18 = rule('Sensor Status - Critical -> Fault') self.r18.condition('transition {} from "critical" to "fault"', [self.m1]) self.r18.action(self.sensor_status_action_critical) self.r19 = rule('Sensor Status - Emergency -> Fault') self.r19.condition('transition {} from "emergency" to "fault"', [self.m1]) self.r19.action(self.sensor_status_action_critical) self.r20 = rule('Sensor Status - Fault -> Emergency') self.r20.condition('transition {} from "fault" to "emergency"', [self.m1]) self.r20.action(self.sensor_status_action_critical) self.r21 = rule('Sensor Status - Fault -> Critical') self.r21.condition('transition {} from "fault" to "critical"', [self.m1]) self.r21.action(self.sensor_status_action_critical) self.r22 = rule('Sensor Status - Fault -> Low Critical') self.r22.condition('transition {} from "fault" to "low_critical"', [self.m1]) self.r22.action(self.sensor_status_action_critical) def sensor_status_action_critical(self, event): self.logger.debug('********CRITICAL********') self.logger.debug('LABEL = ' + event['labels'] + 'VALUE = ' + event['value']) label = str(event['labels']) labelsplit = label.split(',') readsensor = labelsplit[1] readsensorsplit = readsensor.split('=') sensorname = str(readsensorsplit[1]) self.logger.debug('Sensor Name= ' + sensorname) if self.variables['sensors_list'] != '': findsensor = self.variables['sensors_list'] istrue = findsensor.find(sensorname) if istrue == -1: sensors_list = sensorname + self.variables['sensors_list'] self.variables['sensors_list'] = sensors_list self.logger.debug('list of sensors : ' + self.variables['sensors_list']) self.setactions(sensorname) else: action_syslog('Sensor: ' + sensorname + ' is in Critical state') action_cli('show environment temperature') else: self.variables['sensors_list'] = sensorname self.logger.debug('list of sensors:' + self.variables['sensors_list']) self.setactions(sensorname) def setactions(self, sensorname): self.logger.debug('+++ CALLBACK: SENSOR STATUS - CRITICAL!') self.set_alert_level(AlertLevel.CRITICAL) action_syslog('Sensor: ' + sensorname + ' is in Critical state') action_cli('show environment temperature') def sensor_status_action_normal(self, event): if self.get_alert_level() is not None: if self.variables['sensors_list'] == '': self.set_policy_status_normal() else: print('********NORMAL********') label = str(event['labels']) labelsplit = label.split(',') readsensor = labelsplit[1] readsensorsplit = readsensor.split('=') sensorname = str(readsensorsplit[1]) "\n delete all Sensor Name's which moved back to\n Normal state from Critical state\n " index = 0 length = len(sensorname) findsensor = self.variables['sensors_list'] index = findsensor.find(sensorname) if index != -1: findsensor = findsensor[0:index] + findsensor[index + length:] self.variables['sensors_list'] = findsensor self.logger.debug('Sensor name deleted: ' + sensorname) self.logger.debug('Current Sensors list: ' + self.variables['sensors_list']) action_syslog('Sensor ' + sensorname + ' is back to Normal') if self.variables['sensors_list'] == '': self.set_policy_status_normal() def set_policy_status_normal(self): self.remove_alert_level() action_syslog('All Sensors are Normal')
#gwang_01.py j = 0 for i in range (1000): if (i % 3) == 0 or (i%5) == 0: j+=i j
j = 0 for i in range(1000): if i % 3 == 0 or i % 5 == 0: j += i j
dp = [0 for i in range(301)];stair = [0 for i in range(301)] n = int(input()) for i in range(n): stair[i] = int(input()) dp[0] = stair[0];dp[1] = stair[0]+stair[1];dp[2] = max(stair[0]+stair[2],stair[1]+stair[2]) for i in range(3,n): dp[i] = max(dp[i-2]+stair[i],dp[i-3]+stair[i-1]+stair[i]) print(dp[n-1])
dp = [0 for i in range(301)] stair = [0 for i in range(301)] n = int(input()) for i in range(n): stair[i] = int(input()) dp[0] = stair[0] dp[1] = stair[0] + stair[1] dp[2] = max(stair[0] + stair[2], stair[1] + stair[2]) for i in range(3, n): dp[i] = max(dp[i - 2] + stair[i], dp[i - 3] + stair[i - 1] + stair[i]) print(dp[n - 1])
#!/usr/bin/env python3 # # Advent of Code 2017 - Day 2 # INPUTFILE = 'input.txt' def load_input(infile): lines = [] with open(infile, 'r') as fp: for line in fp: line = line.strip() if line: lines.append(line) return lines def checksum(sheet): result = 0 for row in sheet.splitlines(): vals = [int(item.strip()) for item in row.strip().split()] result += max(vals) - min(vals) return result def checksum2(sheet): result = 0 def row_value(items): for i, a in enumerate(items[:-1]): for b in items[i+1:]: if a % b == 0: return a // b raise ValueError("No divisible pair found in {}".format(items)) for row in sheet.splitlines(): vals = sorted([int(item.strip()) for item in row.strip().split()], reverse=True) result += row_value(vals) return result # PART 1 def example(): sheet = """ 5 1 9 5 7 5 3 2 4 6 8 """ expected = 18 result = checksum(sheet) print("result = {} (expected {})".format(result, expected)) assert result == expected print('= ' * 32) def part1(lines): result = checksum("\n".join(lines)) print("checksum = {}".format(result)) print('= ' * 32) # PART 2 def example2(): sheet = """5 9 2 8 9 4 7 3 3 8 6 5 """ expected = 9 result = checksum2(sheet) print("result = {} (expected {})".format(result, expected)) assert result == expected print('= ' * 32) def part2(lines): result = checksum2("\n".join(lines)) print("checksum2 = {}".format(result)) print('= ' * 32) if __name__ == '__main__': example() input = load_input(INPUTFILE) part1(input) example2() part2(input)
inputfile = 'input.txt' def load_input(infile): lines = [] with open(infile, 'r') as fp: for line in fp: line = line.strip() if line: lines.append(line) return lines def checksum(sheet): result = 0 for row in sheet.splitlines(): vals = [int(item.strip()) for item in row.strip().split()] result += max(vals) - min(vals) return result def checksum2(sheet): result = 0 def row_value(items): for (i, a) in enumerate(items[:-1]): for b in items[i + 1:]: if a % b == 0: return a // b raise value_error('No divisible pair found in {}'.format(items)) for row in sheet.splitlines(): vals = sorted([int(item.strip()) for item in row.strip().split()], reverse=True) result += row_value(vals) return result def example(): sheet = ' 5 1 9 5\n7 5 3\n2 4 6 8\n' expected = 18 result = checksum(sheet) print('result = {} (expected {})'.format(result, expected)) assert result == expected print('= ' * 32) def part1(lines): result = checksum('\n'.join(lines)) print('checksum = {}'.format(result)) print('= ' * 32) def example2(): sheet = '5 9 2 8\n9 4 7 3\n3 8 6 5\n' expected = 9 result = checksum2(sheet) print('result = {} (expected {})'.format(result, expected)) assert result == expected print('= ' * 32) def part2(lines): result = checksum2('\n'.join(lines)) print('checksum2 = {}'.format(result)) print('= ' * 32) if __name__ == '__main__': example() input = load_input(INPUTFILE) part1(input) example2() part2(input)
def read_only_properties(*args): def class_rebuilder(cls): def __setattr__(self, key, value): if key in args and key in self.__dict__: raise AttributeError("Can't modify %s" % key) else: super().__setattr__(key, value) cls.__setattr__ = __setattr__ return cls return class_rebuilder
def read_only_properties(*args): def class_rebuilder(cls): def __setattr__(self, key, value): if key in args and key in self.__dict__: raise attribute_error("Can't modify %s" % key) else: super().__setattr__(key, value) cls.__setattr__ = __setattr__ return cls return class_rebuilder
# Copyright (c) 2013 The Chromium Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. { 'variables': { 'chromium_code': 1, }, 'targets': [ { 'target_name': 'gfx_geometry', 'type': '<(component)', 'dependencies': [ '<(DEPTH)/base/base.gyp:base', ], 'defines': [ 'GFX_IMPLEMENTATION', ], 'sources': [ 'geometry/box_f.cc', 'geometry/box_f.h', 'geometry/cubic_bezier.h', 'geometry/cubic_bezier.cc', 'geometry/insets.cc', 'geometry/insets.h', 'geometry/insets_base.h', 'geometry/insets_f.cc', 'geometry/insets_f.h', 'geometry/matrix3_f.cc', 'geometry/matrix3_f.h', 'geometry/point.cc', 'geometry/point.h', 'geometry/point3_f.cc', 'geometry/point3_f.h', 'geometry/point_conversions.cc', 'geometry/point_conversions.h', 'geometry/point_f.cc', 'geometry/point_f.h', 'geometry/quad_f.cc', 'geometry/quad_f.h', 'geometry/rect.cc', 'geometry/rect.h', 'geometry/rect_conversions.cc', 'geometry/rect_conversions.h', 'geometry/rect_f.cc', 'geometry/rect_f.h', 'geometry/r_tree.h', 'geometry/r_tree_base.cc', 'geometry/r_tree_base.h', 'geometry/safe_integer_conversions.h', 'geometry/scroll_offset.cc', 'geometry/scroll_offset.h', 'geometry/size.cc', 'geometry/size.h', 'geometry/size_conversions.cc', 'geometry/size_conversions.h', 'geometry/size_f.cc', 'geometry/size_f.h', 'geometry/vector2d.cc', 'geometry/vector2d.h', 'geometry/vector2d_conversions.cc', 'geometry/vector2d_conversions.h', 'geometry/vector2d_f.cc', 'geometry/vector2d_f.h', 'geometry/vector3d_f.cc', 'geometry/vector3d_f.h', ], # TODO(jdduke): Revisit optimization after gauging benefit, crbug/419051. 'includes': [ '../../build/android/increase_size_for_speed.gypi', ], }, { 'target_name': 'gfx', 'type': '<(component)', 'dependencies': [ '<(DEPTH)/base/base.gyp:base', '<(DEPTH)/base/base.gyp:base_i18n', '<(DEPTH)/base/base.gyp:base_static', '<(DEPTH)/base/third_party/dynamic_annotations/dynamic_annotations.gyp:dynamic_annotations', '<(DEPTH)/skia/skia.gyp:skia', '<(DEPTH)/third_party/harfbuzz-ng/harfbuzz.gyp:harfbuzz-ng', '<(DEPTH)/third_party/icu/icu.gyp:icui18n', '<(DEPTH)/third_party/icu/icu.gyp:icuuc', '<(DEPTH)/third_party/libpng/libpng.gyp:libpng', '<(DEPTH)/third_party/zlib/zlib.gyp:zlib', 'gfx_geometry', ], # text_elider.h includes ICU headers. 'export_dependent_settings': [ '<(DEPTH)/skia/skia.gyp:skia', '<(DEPTH)/third_party/icu/icu.gyp:icui18n', '<(DEPTH)/third_party/icu/icu.gyp:icuuc', ], 'defines': [ 'GFX_IMPLEMENTATION', ], 'include_dirs': [ '<(DEPTH)/third_party/icu/source/common' ], 'sources': [ 'android/device_display_info.cc', 'android/device_display_info.h', 'android/gfx_jni_registrar.cc', 'android/gfx_jni_registrar.h', 'android/java_bitmap.cc', 'android/java_bitmap.h', 'android/shared_device_display_info.cc', 'android/shared_device_display_info.h', 'android/view_configuration.cc', 'android/view_configuration.h', 'animation/animation.cc', 'animation/animation.h', 'animation/animation_container.cc', 'animation/animation_container.h', 'animation/animation_container_element.h', 'animation/animation_container_observer.h', 'animation/animation_delegate.h', 'animation/linear_animation.cc', 'animation/linear_animation.h', 'animation/multi_animation.cc', 'animation/multi_animation.h', 'animation/slide_animation.cc', 'animation/slide_animation.h', 'animation/throb_animation.cc', 'animation/throb_animation.h', 'animation/tween.cc', 'animation/tween.h', 'break_list.h', 'canvas.cc', 'canvas.h', 'canvas_notimplemented.cc', 'canvas_paint_mac.h', 'canvas_paint_mac.mm', 'canvas_paint_win.cc', 'canvas_paint_win.h', 'canvas_skia.cc', 'canvas_skia_paint.h', 'codec/jpeg_codec.cc', 'codec/jpeg_codec.h', 'codec/png_codec.cc', 'codec/png_codec.h', 'color_utils.cc', 'color_utils.h', 'display.cc', 'display.h', 'display_change_notifier.cc', 'display_change_notifier.h', 'display_observer.cc', 'display_observer.h', 'font.cc', 'font.h', 'font_fallback.h', 'font_fallback_linux.cc', 'font_fallback_mac.cc', 'font_fallback_win.cc', 'font_fallback_win.h', 'font_list.cc', 'font_list.h', 'font_list_impl.cc', 'font_list_impl.h', 'font_render_params.cc', 'font_render_params.h', 'font_render_params_android.cc', 'font_render_params_linux.cc', 'font_render_params_mac.cc', 'font_render_params_win.cc', 'frame_time.h', 'gfx_export.h', 'gfx_paths.cc', 'gfx_paths.h', 'gpu_memory_buffer.cc', 'gpu_memory_buffer.h', 'image/canvas_image_source.cc', 'image/canvas_image_source.h', 'image/image.cc', 'image/image.h', 'image/image_family.cc', 'image/image_family.h', 'image/image_ios.mm', 'image/image_mac.mm', 'image/image_png_rep.cc', 'image/image_png_rep.h', 'image/image_skia.cc', 'image/image_skia.h', 'image/image_skia_operations.cc', 'image/image_skia_operations.h', 'image/image_skia_rep.cc', 'image/image_skia_rep.h', 'image/image_skia_source.h', 'image/image_skia_util_ios.h', 'image/image_skia_util_ios.mm', 'image/image_skia_util_mac.h', 'image/image_skia_util_mac.mm', 'image/image_util.cc', 'image/image_util.h', 'image/image_util_ios.mm', 'interpolated_transform.cc', 'interpolated_transform.h', 'linux_font_delegate.cc', 'linux_font_delegate.h', 'mac/coordinate_conversion.h', 'mac/coordinate_conversion.mm', 'mac/scoped_ns_disable_screen_updates.h', 'native_widget_types.h', 'nine_image_painter.cc', 'nine_image_painter.h', 'overlay_transform.h', 'pango_util.cc', 'pango_util.h', 'path.cc', 'path.h', 'path_aura.cc', 'path_win.cc', 'path_win.h', 'path_x11.cc', 'path_x11.h', 'platform_font.h', 'platform_font_android.cc', 'platform_font_ios.h', 'platform_font_ios.mm', 'platform_font_mac.h', 'platform_font_mac.mm', 'platform_font_ozone.cc', 'platform_font_pango.cc', 'platform_font_pango.h', 'platform_font_win.cc', 'platform_font_win.h', 'range/range.cc', 'range/range.h', 'range/range_mac.mm', 'range/range_win.cc', 'render_text.cc', 'render_text.h', 'render_text_harfbuzz.cc', 'render_text_harfbuzz.h', 'render_text_mac.cc', 'render_text_mac.h', 'render_text_ozone.cc', 'render_text_pango.cc', 'render_text_pango.h', 'render_text_win.cc', 'render_text_win.h', 'scoped_canvas.h', 'scoped_cg_context_save_gstate_mac.h', 'scoped_ns_graphics_context_save_gstate_mac.h', 'scoped_ns_graphics_context_save_gstate_mac.mm', 'screen.cc', 'screen.h', 'screen_android.cc', 'screen_aura.cc', 'screen_ios.mm', 'screen_mac.mm', 'screen_win.cc', 'screen_win.h', 'scrollbar_size.cc', 'scrollbar_size.h', 'selection_model.cc', 'selection_model.h', 'sequential_id_generator.cc', 'sequential_id_generator.h', 'shadow_value.cc', 'shadow_value.h', 'skbitmap_operations.cc', 'skbitmap_operations.h', 'skia_util.cc', 'skia_util.h', 'switches.cc', 'switches.h', 'sys_color_change_listener.cc', 'sys_color_change_listener.h', 'text_constants.h', 'text_elider.cc', 'text_elider.h', 'text_utils.cc', 'text_utils.h', 'text_utils_android.cc', 'text_utils_ios.mm', 'text_utils_skia.cc', 'transform.cc', 'transform.h', 'transform_util.cc', 'transform_util.h', 'ui_gfx_exports.cc', 'utf16_indexing.cc', 'utf16_indexing.h', 'vsync_provider.h', 'win/direct_write.cc', 'win/direct_write.h', 'win/dpi.cc', 'win/dpi.h', 'win/hwnd_util.cc', 'win/hwnd_util.h', 'win/scoped_set_map_mode.h', 'win/singleton_hwnd.cc', 'win/singleton_hwnd.h', 'win/window_impl.cc', 'win/window_impl.h', ], 'includes': [ '../../build/android/increase_size_for_speed.gypi', ], 'conditions': [ ['OS=="ios"', { 'dependencies': [ '<(DEPTH)/ui/ios/ui_ios.gyp:ui_ios', ], # iOS only uses a subset of UI. 'sources/': [ ['exclude', '^codec/jpeg_codec\\.cc$'], ], }, { 'dependencies': [ '<(libjpeg_gyp_path):libjpeg', ], }], # TODO(asvitkine): Switch all platforms to use canvas_skia.cc. # http://crbug.com/105550 ['use_canvas_skia==1', { 'sources!': [ 'canvas_notimplemented.cc', ], }, { # use_canvas_skia!=1 'sources!': [ 'canvas_skia.cc', ], }], ['OS=="win"', { 'sources': [ 'gdi_util.cc', 'gdi_util.h', 'icon_util.cc', 'icon_util.h', ], # TODO(jschuh): C4267: http://crbug.com/167187 size_t -> int # C4324 is structure was padded due to __declspec(align()), which is # uninteresting. 'msvs_disabled_warnings': [ 4267, 4324 ], }], ['OS=="android"', { 'sources!': [ 'animation/throb_animation.cc', 'display_observer.cc', 'selection_model.cc', ], 'dependencies': [ 'gfx_jni_headers', ], 'link_settings': { 'libraries': [ '-landroid', '-ljnigraphics', ], }, }], ['use_aura==0 and toolkit_views==0', { 'sources!': [ 'nine_image_painter.cc', 'nine_image_painter.h', ], }], ['OS=="android" and use_aura==0', { 'sources!': [ 'path.cc', ], }], ['OS=="android" and use_aura==1', { 'sources!': [ 'screen_android.cc', ], }], ['OS=="android" and android_webview_build==0', { 'dependencies': [ '<(DEPTH)/base/base.gyp:base_java', ], }], ['OS=="android" or OS=="ios"', { 'sources!': [ 'render_text.cc', 'render_text.h', 'render_text_harfbuzz.cc', 'render_text_harfbuzz.h', 'text_utils_skia.cc', ], }], ['use_x11==1', { 'dependencies': [ '../../build/linux/system.gyp:x11', 'x/gfx_x11.gyp:gfx_x11', ], }], ['use_pango==1', { 'dependencies': [ '<(DEPTH)/build/linux/system.gyp:pangocairo', ], 'sources!': [ 'platform_font_ozone.cc', 'render_text_ozone.cc', ], }], ['desktop_linux==1 or chromeos==1', { 'dependencies': [ # font_render_params_linux.cc uses fontconfig '<(DEPTH)/build/linux/system.gyp:fontconfig', ], }], ], 'target_conditions': [ # Need 'target_conditions' to override default filename_rules to include # the file on iOS. ['OS == "ios"', { 'sources/': [ ['include', '^scoped_cg_context_save_gstate_mac\\.h$'], ], }], ], }, { 'target_name': 'gfx_test_support', 'type': 'static_library', 'sources': [ 'image/image_unittest_util.cc', 'image/image_unittest_util.h', 'image/image_unittest_util_ios.mm', 'image/image_unittest_util_mac.mm', 'test/fontconfig_util_linux.cc', 'test/fontconfig_util_linux.h', 'test/gfx_util.cc', 'test/gfx_util.h', 'test/ui_cocoa_test_helper.h', 'test/ui_cocoa_test_helper.mm', ], 'dependencies': [ '../../base/base.gyp:base', '../../skia/skia.gyp:skia', '../../testing/gtest.gyp:gtest', ], 'conditions': [ ['OS == "mac"', { 'link_settings': { 'libraries': [ '$(SDKROOT)/System/Library/Frameworks/AppKit.framework', ], }, }], ['OS=="ios"', { # The cocoa files don't apply to iOS. 'sources/': [ ['exclude', 'cocoa'] ], }], ['OS=="linux"', { 'dependencies': [ '../../build/linux/system.gyp:fontconfig', ], }], ], }, ], 'conditions': [ ['OS=="android"' , { 'targets': [ { 'target_name': 'gfx_jni_headers', 'type': 'none', 'sources': [ '../android/java/src/org/chromium/ui/gfx/BitmapHelper.java', '../android/java/src/org/chromium/ui/gfx/DeviceDisplayInfo.java', '../android/java/src/org/chromium/ui/gfx/ViewConfigurationHelper.java', ], 'variables': { 'jni_gen_package': 'ui/gfx', }, 'includes': [ '../../build/jni_generator.gypi' ], }, ], }], ], }
{'variables': {'chromium_code': 1}, 'targets': [{'target_name': 'gfx_geometry', 'type': '<(component)', 'dependencies': ['<(DEPTH)/base/base.gyp:base'], 'defines': ['GFX_IMPLEMENTATION'], 'sources': ['geometry/box_f.cc', 'geometry/box_f.h', 'geometry/cubic_bezier.h', 'geometry/cubic_bezier.cc', 'geometry/insets.cc', 'geometry/insets.h', 'geometry/insets_base.h', 'geometry/insets_f.cc', 'geometry/insets_f.h', 'geometry/matrix3_f.cc', 'geometry/matrix3_f.h', 'geometry/point.cc', 'geometry/point.h', 'geometry/point3_f.cc', 'geometry/point3_f.h', 'geometry/point_conversions.cc', 'geometry/point_conversions.h', 'geometry/point_f.cc', 'geometry/point_f.h', 'geometry/quad_f.cc', 'geometry/quad_f.h', 'geometry/rect.cc', 'geometry/rect.h', 'geometry/rect_conversions.cc', 'geometry/rect_conversions.h', 'geometry/rect_f.cc', 'geometry/rect_f.h', 'geometry/r_tree.h', 'geometry/r_tree_base.cc', 'geometry/r_tree_base.h', 'geometry/safe_integer_conversions.h', 'geometry/scroll_offset.cc', 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'animation/slide_animation.cc', 'animation/slide_animation.h', 'animation/throb_animation.cc', 'animation/throb_animation.h', 'animation/tween.cc', 'animation/tween.h', 'break_list.h', 'canvas.cc', 'canvas.h', 'canvas_notimplemented.cc', 'canvas_paint_mac.h', 'canvas_paint_mac.mm', 'canvas_paint_win.cc', 'canvas_paint_win.h', 'canvas_skia.cc', 'canvas_skia_paint.h', 'codec/jpeg_codec.cc', 'codec/jpeg_codec.h', 'codec/png_codec.cc', 'codec/png_codec.h', 'color_utils.cc', 'color_utils.h', 'display.cc', 'display.h', 'display_change_notifier.cc', 'display_change_notifier.h', 'display_observer.cc', 'display_observer.h', 'font.cc', 'font.h', 'font_fallback.h', 'font_fallback_linux.cc', 'font_fallback_mac.cc', 'font_fallback_win.cc', 'font_fallback_win.h', 'font_list.cc', 'font_list.h', 'font_list_impl.cc', 'font_list_impl.h', 'font_render_params.cc', 'font_render_params.h', 'font_render_params_android.cc', 'font_render_params_linux.cc', 'font_render_params_mac.cc', 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'screen_android.cc', 'screen_aura.cc', 'screen_ios.mm', 'screen_mac.mm', 'screen_win.cc', 'screen_win.h', 'scrollbar_size.cc', 'scrollbar_size.h', 'selection_model.cc', 'selection_model.h', 'sequential_id_generator.cc', 'sequential_id_generator.h', 'shadow_value.cc', 'shadow_value.h', 'skbitmap_operations.cc', 'skbitmap_operations.h', 'skia_util.cc', 'skia_util.h', 'switches.cc', 'switches.h', 'sys_color_change_listener.cc', 'sys_color_change_listener.h', 'text_constants.h', 'text_elider.cc', 'text_elider.h', 'text_utils.cc', 'text_utils.h', 'text_utils_android.cc', 'text_utils_ios.mm', 'text_utils_skia.cc', 'transform.cc', 'transform.h', 'transform_util.cc', 'transform_util.h', 'ui_gfx_exports.cc', 'utf16_indexing.cc', 'utf16_indexing.h', 'vsync_provider.h', 'win/direct_write.cc', 'win/direct_write.h', 'win/dpi.cc', 'win/dpi.h', 'win/hwnd_util.cc', 'win/hwnd_util.h', 'win/scoped_set_map_mode.h', 'win/singleton_hwnd.cc', 'win/singleton_hwnd.h', 'win/window_impl.cc', 'win/window_impl.h'], 'includes': ['../../build/android/increase_size_for_speed.gypi'], 'conditions': [['OS=="ios"', {'dependencies': ['<(DEPTH)/ui/ios/ui_ios.gyp:ui_ios'], 'sources/': [['exclude', '^codec/jpeg_codec\\.cc$']]}, {'dependencies': ['<(libjpeg_gyp_path):libjpeg']}], ['use_canvas_skia==1', {'sources!': ['canvas_notimplemented.cc']}, {'sources!': ['canvas_skia.cc']}], ['OS=="win"', {'sources': ['gdi_util.cc', 'gdi_util.h', 'icon_util.cc', 'icon_util.h'], 'msvs_disabled_warnings': [4267, 4324]}], ['OS=="android"', {'sources!': ['animation/throb_animation.cc', 'display_observer.cc', 'selection_model.cc'], 'dependencies': ['gfx_jni_headers'], 'link_settings': {'libraries': ['-landroid', '-ljnigraphics']}}], ['use_aura==0 and toolkit_views==0', {'sources!': ['nine_image_painter.cc', 'nine_image_painter.h']}], ['OS=="android" and use_aura==0', {'sources!': ['path.cc']}], ['OS=="android" and use_aura==1', {'sources!': ['screen_android.cc']}], ['OS=="android" and android_webview_build==0', {'dependencies': ['<(DEPTH)/base/base.gyp:base_java']}], ['OS=="android" or OS=="ios"', {'sources!': ['render_text.cc', 'render_text.h', 'render_text_harfbuzz.cc', 'render_text_harfbuzz.h', 'text_utils_skia.cc']}], ['use_x11==1', {'dependencies': ['../../build/linux/system.gyp:x11', 'x/gfx_x11.gyp:gfx_x11']}], ['use_pango==1', {'dependencies': ['<(DEPTH)/build/linux/system.gyp:pangocairo'], 'sources!': ['platform_font_ozone.cc', 'render_text_ozone.cc']}], ['desktop_linux==1 or chromeos==1', {'dependencies': ['<(DEPTH)/build/linux/system.gyp:fontconfig']}]], 'target_conditions': [['OS == "ios"', {'sources/': [['include', '^scoped_cg_context_save_gstate_mac\\.h$']]}]]}, {'target_name': 'gfx_test_support', 'type': 'static_library', 'sources': ['image/image_unittest_util.cc', 'image/image_unittest_util.h', 'image/image_unittest_util_ios.mm', 'image/image_unittest_util_mac.mm', 'test/fontconfig_util_linux.cc', 'test/fontconfig_util_linux.h', 'test/gfx_util.cc', 'test/gfx_util.h', 'test/ui_cocoa_test_helper.h', 'test/ui_cocoa_test_helper.mm'], 'dependencies': ['../../base/base.gyp:base', '../../skia/skia.gyp:skia', '../../testing/gtest.gyp:gtest'], 'conditions': [['OS == "mac"', {'link_settings': {'libraries': ['$(SDKROOT)/System/Library/Frameworks/AppKit.framework']}}], ['OS=="ios"', {'sources/': [['exclude', 'cocoa']]}], ['OS=="linux"', {'dependencies': ['../../build/linux/system.gyp:fontconfig']}]]}], 'conditions': [['OS=="android"', {'targets': [{'target_name': 'gfx_jni_headers', 'type': 'none', 'sources': ['../android/java/src/org/chromium/ui/gfx/BitmapHelper.java', '../android/java/src/org/chromium/ui/gfx/DeviceDisplayInfo.java', '../android/java/src/org/chromium/ui/gfx/ViewConfigurationHelper.java'], 'variables': {'jni_gen_package': 'ui/gfx'}, 'includes': ['../../build/jni_generator.gypi']}]}]]}
class Solution(object): def reformatNumber(self, number): """ :type number: str :rtype: str """ number = number.replace('-' ,'').replace(' ', '') ans = [] for i in range(0, len(number), 3): ans.append(number[i:i+3]) if len(ans) >= 2 and len(ans[-1]) == 1: ans[-1] = ans[-2][2] + ans[-1] ans[-2] = ans[-2][:2] return '-'.join(ans) number = "1-23-45 6" res = Solution().reformatNumber(number) print(res)
class Solution(object): def reformat_number(self, number): """ :type number: str :rtype: str """ number = number.replace('-', '').replace(' ', '') ans = [] for i in range(0, len(number), 3): ans.append(number[i:i + 3]) if len(ans) >= 2 and len(ans[-1]) == 1: ans[-1] = ans[-2][2] + ans[-1] ans[-2] = ans[-2][:2] return '-'.join(ans) number = '1-23-45 6' res = solution().reformatNumber(number) print(res)
class BaseError(Exception): """Base package error.""" class InvalidModelInputError(BaseError): """Model input contains an error."""
class Baseerror(Exception): """Base package error.""" class Invalidmodelinputerror(BaseError): """Model input contains an error."""
#!/usr/bin/env python3 # ex6: String and Text # Assign the string with 10 replacing the formatting character to variable 'x' x = "There are %d types of people." % 10 # Assign the string with "binary" to variable 'binary' binary = "binary" # Assign the string with "don't" to variable 'do_not' do_not = "don't" # Assign the string with 'binary' and 'do_not' replacing the # formatting character to variable 'y' y = "Those who know %s and those who %s." % (binary, do_not) # Two strings inside of a string # Print "There are 10 types of people." print(x) # Print "Those who know binary and those who don't." print(y) # Print "I said 'There are 10 types of people.'" print("I said %r." % x) # One string inside of a string # Print "I also said: 'Those who know binary and those who don't.'." print("I also said: '%s'." % y) # One string inside of a string # Assign boolean False to variable 'hilarious' hilarious = False # Assign the string with an unevaluated formatting character to 'joke_evaluation' joke_evaluation = "Isn't that joke so funny?! %r" # Print "Isn't that joke so funny?! False" print(joke_evaluation % hilarious) # One string inside of a string # Assign string to 'w' w = "This is the left side of..." # Assign string to 'e' e = "a string with a right side." # Print "This is the left side of...a string with a right side." print(w + e) # Concatenate two strings with + operator
x = 'There are %d types of people.' % 10 binary = 'binary' do_not = "don't" y = 'Those who know %s and those who %s.' % (binary, do_not) print(x) print(y) print('I said %r.' % x) print("I also said: '%s'." % y) hilarious = False joke_evaluation = "Isn't that joke so funny?! %r" print(joke_evaluation % hilarious) w = 'This is the left side of...' e = 'a string with a right side.' print(w + e)
class QolsysException(Exception): pass class QolsysGwConfigIncomplete(QolsysException): pass class QolsysGwConfigError(QolsysException): pass class UnableToParseEventException(QolsysException): pass class UnknownQolsysControlException(QolsysException): pass class UnknownQolsysEventException(QolsysException): pass class UnknownQolsysSensorException(QolsysException): pass class MissingUserCodeException(QolsysException): pass class InvalidUserCodeException(QolsysException): pass
class Qolsysexception(Exception): pass class Qolsysgwconfigincomplete(QolsysException): pass class Qolsysgwconfigerror(QolsysException): pass class Unabletoparseeventexception(QolsysException): pass class Unknownqolsyscontrolexception(QolsysException): pass class Unknownqolsyseventexception(QolsysException): pass class Unknownqolsyssensorexception(QolsysException): pass class Missingusercodeexception(QolsysException): pass class Invalidusercodeexception(QolsysException): pass
## 3. Read the File Into a String ## f = open("dq_unisex_names.csv", 'r') names = f.read(); ## 4. Convert the String to a List ## f = open('dq_unisex_names.csv', 'r') names = f.read() names_list = names.split('\n') first_five = names_list[0:5] print(first_five) ## 5. Convert the List of Strings to a List of Lists ## f = open('dq_unisex_names.csv', 'r') names = f.read() names_list = names.split('\n') nested_list = [] for name in names_list: nested_list.append(name.split(',')) print(nested_list[0:5]) ## 6. Convert Numerical Values ## print(nested_list[0:5]) numerical_list = [] for ele in nested_list: numerical_list.append([ele[0], float(ele[1])]) ## 7. Filter the List ## # The last value is ~100 people numerical_list[len(numerical_list)-1] thousand_or_greater = [] for ele in numerical_list: if ele[1] >= 1000: thousand_or_greater.append(ele[0]) print(thousand_or_greater[0:10])
f = open('dq_unisex_names.csv', 'r') names = f.read() f = open('dq_unisex_names.csv', 'r') names = f.read() names_list = names.split('\n') first_five = names_list[0:5] print(first_five) f = open('dq_unisex_names.csv', 'r') names = f.read() names_list = names.split('\n') nested_list = [] for name in names_list: nested_list.append(name.split(',')) print(nested_list[0:5]) print(nested_list[0:5]) numerical_list = [] for ele in nested_list: numerical_list.append([ele[0], float(ele[1])]) numerical_list[len(numerical_list) - 1] thousand_or_greater = [] for ele in numerical_list: if ele[1] >= 1000: thousand_or_greater.append(ele[0]) print(thousand_or_greater[0:10])
def main(): x_coords = [] x_lines = ["side 1 G", "side 1 5", "side 1 10", "side 1 15", "side 1 20", "side 1 25", "side 1 30", "side 1 35", "side 1 40", "side 1 45", "50", "side 2 45", "side 2 40", "side 2 35", "side 2 30", "side 2 25", "side 2 20", "side 2 15", "side 2 10", "side 2 5", "side 2 G"] for i, line in enumerate(x_lines): if i < 10: if i > 0: x_coords += ["{0} outside the {1}".format(x, line) for x in range(4, 0, -1)] x_coords.append("on the {0}".format(line)) x_coords += ["{0} inside the {1}".format(x, line) for x in range(1, 4)] elif i == 10: x_coords += ["{0} outside the {1} on side 1".format(x, line) for x in range(4, 0, -1)] x_coords.append("on the {0}".format(line)) x_coords += ["{0} outside the {1} on side 2".format(x, line) for x in range(1, 5)] else: x_coords += ["{0} inside the {1}".format(x, line) for x in range(3, 0, -1)] x_coords.append("on the {0}".format(line)) if i + 1 < len(x_lines): x_coords += ["{0} outside the {1}".format(x, line) for x in range(1, 5)] y_coords = [] y_coords.append("on the front sideline") y_coords += ["{0} behind the front sideline".format(x) for x in range(1, 50)] y_coords += ["{0} in front of the front hash".format(x) for x in range(50, 0, -1)] y_coords.append("on the front hash") y_coords += ["{0} behind the front hash".format(x) for x in range(1, 50)] y_coords += ["{0} in front of the back hash".format(x) for x in range(50, 0, -1)] y_coords.append("on the back hash") y_coords += ["{0} behind the back hash".format(x) for x in range(1, 50)] y_coords += ["{0} in front of the back sideline".format(x) for x in range(50, 0, -1)] y_coords.append("on the back sideline") output = "" for x in x_coords: for y in y_coords: output += "{0}, {1}. \n".format(x, y) with open("output.txt", "w") as out: out.write(output) # Press the green button in the gutter to run the script. if __name__ == '__main__': main() # See PyCharm help at https://www.jetbrains.com/help/pycharm/
def main(): x_coords = [] x_lines = ['side 1 G', 'side 1 5', 'side 1 10', 'side 1 15', 'side 1 20', 'side 1 25', 'side 1 30', 'side 1 35', 'side 1 40', 'side 1 45', '50', 'side 2 45', 'side 2 40', 'side 2 35', 'side 2 30', 'side 2 25', 'side 2 20', 'side 2 15', 'side 2 10', 'side 2 5', 'side 2 G'] for (i, line) in enumerate(x_lines): if i < 10: if i > 0: x_coords += ['{0} outside the {1}'.format(x, line) for x in range(4, 0, -1)] x_coords.append('on the {0}'.format(line)) x_coords += ['{0} inside the {1}'.format(x, line) for x in range(1, 4)] elif i == 10: x_coords += ['{0} outside the {1} on side 1'.format(x, line) for x in range(4, 0, -1)] x_coords.append('on the {0}'.format(line)) x_coords += ['{0} outside the {1} on side 2'.format(x, line) for x in range(1, 5)] else: x_coords += ['{0} inside the {1}'.format(x, line) for x in range(3, 0, -1)] x_coords.append('on the {0}'.format(line)) if i + 1 < len(x_lines): x_coords += ['{0} outside the {1}'.format(x, line) for x in range(1, 5)] y_coords = [] y_coords.append('on the front sideline') y_coords += ['{0} behind the front sideline'.format(x) for x in range(1, 50)] y_coords += ['{0} in front of the front hash'.format(x) for x in range(50, 0, -1)] y_coords.append('on the front hash') y_coords += ['{0} behind the front hash'.format(x) for x in range(1, 50)] y_coords += ['{0} in front of the back hash'.format(x) for x in range(50, 0, -1)] y_coords.append('on the back hash') y_coords += ['{0} behind the back hash'.format(x) for x in range(1, 50)] y_coords += ['{0} in front of the back sideline'.format(x) for x in range(50, 0, -1)] y_coords.append('on the back sideline') output = '' for x in x_coords: for y in y_coords: output += '{0}, {1}. \n'.format(x, y) with open('output.txt', 'w') as out: out.write(output) if __name__ == '__main__': main()
def main(): arr = [] while True: arr.append(1) if len(arr) >= 10: break return None if __name__ == "__main__": main()
def main(): arr = [] while True: arr.append(1) if len(arr) >= 10: break return None if __name__ == '__main__': main()
""" Shared constants. Only put things here if they are used in more than one module. Otherwise just define them in the module where they are used. """ EASYCRON_IPS = ["198.27.83.222", "192.99.21.124", "167.114.64.88", "167.114.64.21"]
""" Shared constants. Only put things here if they are used in more than one module. Otherwise just define them in the module where they are used. """ easycron_ips = ['198.27.83.222', '192.99.21.124', '167.114.64.88', '167.114.64.21']
''' Given an array of meeting time intervals consisting of start and end times [[s1,e1],[s2,e2],...] (si < ei), find the minimum number of conference rooms required. Example 1: Input: [[0, 30],[5, 10],[15, 20]] Output: 2 Example 2: Input: [[7,10],[2,4]] Output: 1 ''' # Definition for an interval. # class Interval(object): # def __init__(self, s=0, e=0): # self.start = s # self.end = e class Solution(object): def minMeetingRooms(self, intervals): """ :type intervals: List[Interval] :rtype: int """ start = [x.start for x in intervals] end = [x.end for x in intervals] start.sort() end.sort() res = 0 idx = 0 for i in xrange(len(start)): if start[i] < end[idx]: res += 1 else: idx += 1 return res # Definition for an interval. # class Interval(object): # def __init__(self, s=0, e=0): # self.start = s # self.end = e class Solution(object): def minMeetingRooms(self, intervals): """ :type intervals: List[Interval] :rtype: int """ start = sorted([x.start for x in intervals]) end = sorted([x.end for x in intervals]) res = 0 tmp = 0 i = 0 j = 0 while i < len(start): if j < len(end): if start[i] < end[j]: if tmp > 0: tmp -= 1 else: res += 1 i += 1 else: tmp += 1 j += 1 else: if tmp > 0: tmp -= 1 else: res += 1 i += 1 return res
""" Given an array of meeting time intervals consisting of start and end times [[s1,e1],[s2,e2],...] (si < ei), find the minimum number of conference rooms required. Example 1: Input: [[0, 30],[5, 10],[15, 20]] Output: 2 Example 2: Input: [[7,10],[2,4]] Output: 1 """ class Solution(object): def min_meeting_rooms(self, intervals): """ :type intervals: List[Interval] :rtype: int """ start = [x.start for x in intervals] end = [x.end for x in intervals] start.sort() end.sort() res = 0 idx = 0 for i in xrange(len(start)): if start[i] < end[idx]: res += 1 else: idx += 1 return res class Solution(object): def min_meeting_rooms(self, intervals): """ :type intervals: List[Interval] :rtype: int """ start = sorted([x.start for x in intervals]) end = sorted([x.end for x in intervals]) res = 0 tmp = 0 i = 0 j = 0 while i < len(start): if j < len(end): if start[i] < end[j]: if tmp > 0: tmp -= 1 else: res += 1 i += 1 else: tmp += 1 j += 1 else: if tmp > 0: tmp -= 1 else: res += 1 i += 1 return res
enums = { 'AcpAmplitudeCorrectionType': { 'values': [ { 'documentation': { 'description': ' All the frequency bins in the spectrum are compensated with a single external attenuation value that corresponds to the RF center frequency.' }, 'name': 'RF_CENTER_FREQUENCY', 'value': 0 }, { 'documentation': { 'description': ' An individual frequency bin in the spectrum is compensated with the external attenuation value corresponding to that frequency.' }, 'name': 'SPECTRUM_FREQUENCY_BIN', 'value': 1 } ] }, 'AcpAveragingEnabled': { 'values': [ { 'documentation': { 'description': ' The measurement is performed on a single acquisition.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' The ACP measurement uses the RFMXSPECAN_ATTR_ACP_AVERAGING_COUNT attribute as the number of acquisitions over which the ACP measurement is averaged. ' }, 'name': 'TRUE', 'value': 1 } ] }, 'AcpAveragingType': { 'values': [ { 'documentation': { 'description': ' The power spectrum is linearly averaged. RMS averaging reduces signal fluctuations but not the noise floor. ' }, 'name': 'RMS', 'value': 0 }, { 'documentation': { 'description': ' The power spectrum is averaged in a logarithmic scale.' }, 'name': 'LOG', 'value': 1 }, { 'documentation': { 'description': ' The square root of the power spectrum is averaged.' }, 'name': 'SCALAR', 'value': 2 }, { 'documentation': { 'description': ' The peak power in the spectrum at each frequency bin is retained from one acquisition to the next.' }, 'name': 'MAXIMUM', 'value': 3 }, { 'documentation': { 'description': ' The least power in the spectrum at each frequency bin is retained from one acquisition to the next. ' }, 'name': 'MINIMUM', 'value': 4 } ] }, 'AcpCarrierMode': { 'values': [ { 'documentation': { 'description': ' The carrier power is not considered as part of the total carrier power.' }, 'name': 'PASSIVE', 'value': 0 }, { 'documentation': { 'description': ' The carrier power is considered as part of the total carrier power.' }, 'name': 'ACTIVE', 'value': 1 } ] }, 'AcpCarrierRrcFilterEnabled': { 'values': [ { 'documentation': { 'description': ' The channel power of the acquired carrier channel is measured directly.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' The measurement applies the RRC filter on the acquired carrier channel before measuring the carrier channel power.' }, 'name': 'TRUE', 'value': 1 } ] }, 'AcpFftOverlapMode': { 'values': [ { 'documentation': { 'description': ' Disables the overlap between the chunks.' }, 'name': 'DISABLED', 'value': 0 }, { 'documentation': { 'description': ' Measurement sets the overlap based on the value you have set for the RFMXSPECAN_ATTR_ACP_FFT_WINDOW attribute. When you set the RFMXSPECAN_ATTR_ACP_FFT_WINDOW attribute to any value other than RFMXSPECAN_VAL_ACP_FFT_WINDOW_NONE, the number of overlapped samples between consecutive chunks is set to 50% of the value of the RFMXSPECAN_ATTR_ACP_SEQUENTIAL_FFT_SIZE attribute. When you set the RFMXSPECAN_ATTR_ACP_FFT_WINDOW attribute to RFMXSPECAN_VAL_ACP_FFT_WINDOW_NONE, the chunks are not overlapped and the overlap is set to 0%.' }, 'name': 'AUTOMATIC', 'value': 1 }, { 'documentation': { 'description': ' Measurement uses the overlap that you specify in the RFMXSPECAN_ATTR_ACP_FFT_OVERLAP attribute.' }, 'name': 'USER_DEFINED', 'value': 2 } ] }, 'AcpFftWindow': { 'values': [ { 'documentation': { 'description': ' Analyzes transients for which duration is shorter than the window length. You can also use this window type to separate two tones with frequencies close to each other but with almost equal amplitudes.' }, 'name': 'NONE', 'value': 0 }, { 'documentation': { 'description': ' Measures single-tone amplitudes accurately.' }, 'name': 'FLAT_TOP', 'value': 1 }, { 'documentation': { 'description': ' Analyzes transients for which duration is longer than the window length. You can also use this window type to provide better frequency resolution for noise measurements.' }, 'name': 'HANNING', 'value': 2 }, { 'documentation': { 'description': ' Analyzes closely-spaced sine waves.' }, 'name': 'HAMMING', 'value': 3 }, { 'documentation': { 'description': ' Provides a good balance of spectral leakage, frequency resolution, and amplitude attenuation. Hence, this windowing is useful for time-frequency analysis.' }, 'name': 'GAUSSIAN', 'value': 4 }, { 'documentation': { 'description': ' Analyzes single tone because it has a low maximum side lobe level and a high side lobe roll-off rate. ' }, 'name': 'BLACKMAN', 'value': 5 }, { 'documentation': { 'description': ' Useful as a good general purpose window, having side lobe rejection greater than 90 dB and having a moderately wide main lobe. ' }, 'name': 'BLACKMAN_HARRIS', 'value': 6 }, { 'documentation': { 'description': ' Separates two tones with frequencies close to each other but with widely-differing amplitudes.' }, 'name': 'KAISER_BESSEL', 'value': 7 } ] }, 'AcpIFOutputPowerOffsetAuto': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'AcpMeasurementMethod': { 'values': [ { 'documentation': { 'description': ' The ACP measurement acquires the spectrum using the same signal analyzer setting across frequency bands. Use this method when measurement speed is desirable over higher dynamic range. ' }, 'name': 'NORMAL', 'value': 0 }, { 'documentation': { 'description': ' The ACP measurement acquires the spectrum using the hardware-specific optimizations for different frequency bands. Use this method to get the best dynamic range.\n\n Supported devices: PXIe-5665/5668' }, 'name': 'DYNAMIC_RANGE', 'value': 1 }, { 'documentation': { 'description': ' The ACP measurement acquires I/Q samples for a duration specified by the RFMXSPECAN_ATTR_ACP_SWEEP_TIME_INTERVAL attribute. These samples are divided into smaller chunks. The size of each chunk is defined by the RFMXSPECAN_ATTR_ACP_SEQUENTIAL_FFT_SIZE attribute. The overlap between the chunks is defined by the RFMXSPECAN_ATTR_ACP_FFT_OVERLAP_MODE attribute. FFT is computed on each of these chunks. The resultant FFTs are averaged to get the spectrum and is used to compute ACP. If the total acquired samples is not an integer multiple of the FFT size, the remaining samples at the end of acquisition are not used for the measurement. Use this method to optimize ACP measurement speed. Accuracy of the results may be reduced when using this measurement method.' }, 'name': 'SEQUENTIAL_FFT', 'value': 2 } ] }, 'AcpMeasurementMode': { 'values': [ { 'documentation': { 'description': ' ACP measurement is performed on the acquired signal. ' }, 'name': 'MEASURE', 'value': 0 }, { 'documentation': { 'description': ' Manual noise calibration of the signal analyzer is performed for the ACP measurement.' }, 'name': 'CALIBRATE_NOISE_FLOOR', 'value': 1 } ] }, 'AcpNoiseCalibrationAveragingAuto': { 'values': [ { 'documentation': { 'description': ' RFmx uses the averages that you set for the RFMXSPECAN_ATTR_ACP_NOISE_CALIBRATION_AVERAGING_COUNT attribute.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' When you set the RFMXSPECAN_ATTR_ACP_MEASUREMENT_METHOD attribute to RFMXSPECAN_VAL_ACP_MEASUREMENT_METHOD_NORMAL, RFmx uses a noise calibration averaging count of 32. When you set the RFMXSPECAN_ATTR_ACP_MEASUREMENT_METHOD attribute to RFMXSPECAN_VAL_ACP_MEASUREMENT_METHOD_DYNAMIC_RANGE and the sweep time is less than 5 ms, RFmx uses a noise calibration averaging count of 15. When you set the RFMXSPECAN_ATTR_ACP_MEASUREMENT_METHOD attribute to RFMXSPECAN_VAL_ACP_MEASUREMENT_METHOD_DYNAMIC_RANGE and the sweep time is greater than or equal to 5 ms, RFmx uses a noise calibration averaging count of 5.' }, 'name': 'TRUE', 'value': 1 } ] }, 'AcpNoiseCalibrationDataValid': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'AcpNoiseCalibrationMode': { 'values': [ { 'documentation': { 'description': ' When you set the RFMXSPECAN_ATTR_ACP_MEASUREMENT_MODE attribute to RFMXSPECAN_VAL_ACP_MEASUREMENT_MODE_CALIBRATE_NOISE_FLOOR, you can initiate instrument noise calibration for the ACP measurement manually. When you set the RFMXSPECAN_ATTR_ACP_MEASUREMENT_MODE attribute to RFMXSPECAN_VAL_ACP_MEASUREMENT_MODE_MEASURE, you can initiate the ACP measurement manually.' }, 'name': 'MANUAL', 'value': 0 }, { 'documentation': { 'description': ' When you set the RFMXSPECAN_ATTR_ACP_NOISE_COMPENSATION_ENABLED to RFMXSPECAN_VAL_ACP_NOISE_COMPENSATION_ENABLED_TRUE, RFmx sets the Input Isolation Enabled attribute to Enabled and calibrates the instrument noise in the current state of the instrument. RFmx then resets the Input Isolation Enabled attribute and performs the ACP measurement, including compensation for noise of the instrument. RFmx skips noise calibration in this mode if valid noise calibration data is already cached. When you set the RFMXSPECAN_ATTR_ACP_NOISE_COMPENSATION_ENABLED attribute to RFMXSPECAN_VAL_ACP_NOISE_COMPENSATION_ENABLED_FALSE, RFmx does not calibrate instrument noise and only performs the ACP measurement without compensating for noise of the instrument.' }, 'name': 'AUTO', 'value': 1 } ] }, 'AcpNoiseCompensationEnabled': { 'values': [ { 'documentation': { 'description': ' Disables noise compensation.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' Enables noise compensation.' }, 'name': 'TRUE', 'value': 1 } ] }, 'AcpNoiseCompensationType': { 'values': [ { 'documentation': { 'description': ' Compensates for noise from the analyzer and the 50-ohm termination. The measured power values are in excess of the thermal noise floor.' }, 'name': 'ANALYZER_AND_TERMINATION', 'value': 0 }, { 'documentation': { 'description': ' Compensates for the analyzer noise only.' }, 'name': 'ANALYZER_ONLY', 'value': 1 } ] }, 'AcpOffsetEnabled': { 'values': [ { 'documentation': { 'description': ' Disables the offset channel for ACP measurement.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' Enables the offset channel for ACP measurement.' }, 'name': 'TRUE', 'value': 1 } ] }, 'AcpOffsetFrequencyDefinition': { 'values': [ { 'documentation': { 'description': ' The offset frequency is defined from the center of the closest carrier to the center of the offset channel.' }, 'name': 'CARRIER_CENTER_TO_OFFSET_CENTER', 'value': 0 }, { 'documentation': { 'description': ' The offset frequency is defined from the center of the closest carrier to the nearest edge of the offset channel.' }, 'name': 'CARRIER_CENTER_TO_OFFSET_EDGE', 'value': 1 } ] }, 'AcpOffsetPowerReferenceCarrier': { 'values': [ { 'documentation': { 'description': ' The measurement uses the power measured in the carrier closest to the offset channel center frequency, as the power reference.' }, 'name': 'CLOSEST', 'value': 0 }, { 'documentation': { 'description': ' The measurement uses the highest power measured among all the active carriers as the power reference.' }, 'name': 'HIGHEST', 'value': 1 }, { 'documentation': { 'description': ' The measurement uses the sum of powers measured in all the active carriers as the power reference.' }, 'name': 'COMPOSITE', 'value': 2 }, { 'documentation': { 'description': ' The measurement uses the power measured in the carrier that has an index specified by the RFMXSPECAN_ATTR_ACP_OFFSET_POWER_REFERENCE_SPECIFIC attribute, as the power reference.' }, 'name': 'SPECIFIC', 'value': 3 } ] }, 'AcpOffsetRrcFilterEnabled': { 'values': [ { 'documentation': { 'description': ' The channel power of the acquired offset channel is measured directly.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' The measurement applies the RRC filter on the acquired offset channel before measuring the offset channel power.' }, 'name': 'TRUE', 'value': 1 } ] }, 'AcpOffsetSideband': { 'values': [ { 'documentation': { 'description': ' Configures a lower offset segment to the left of the leftmost carrier. ' }, 'name': 'NEGATIVE', 'value': 0 }, { 'documentation': { 'description': ' Configures an upper offset segment to the right of the rightmost carrier. ' }, 'name': 'POSITIVE', 'value': 1 }, { 'documentation': { 'description': ' Configures both negative and positive offset segments.' }, 'name': 'BOTH', 'value': 2 } ] }, 'AcpPowerUnits': { 'values': [ { 'documentation': { 'description': ' The absolute powers are reported in dBm.' }, 'name': 'DBM', 'value': 0 }, { 'documentation': { 'description': ' The absolute powers are reported in dBm/Hz.' }, 'name': 'DBM_PER_HZ', 'value': 1 } ] }, 'AcpRbwAutoBandwidth': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'AcpRbwFilterBandwidthDefinition': { 'values': [ { 'documentation': { 'description': ' Defines the RBW in terms of the 3dB bandwidth of the RBW filter. When you set the RFMXSPECAN_ATTR_ACP_RBW_FILTER_TYPE attribute to RFMXSPECAN_VAL_ACP_RBW_FILTER_TYPE_FFT_BASED, RBW is the 3dB bandwidth of the window specified by the RFMXSPECAN_ATTR_ACP_FFT_WINDOW attribute.' }, 'name': '3_DB', 'value': 0 }, { 'documentation': { 'description': ' Defines the RBW in terms of the bin width of the spectrum computed using FFT when you set the RFMXSPECAN_ATTR_ACP_RBW_FILTER_TYPE attribute to FFT Based.' }, 'name': 'BIN_WIDTH', 'value': 2 } ] }, 'AcpRbwFilterType': { 'values': [ { 'documentation': { 'description': ' No RBW filtering is performed.' }, 'name': 'FFT_BASED', 'value': 0 }, { 'documentation': { 'description': ' An RBW filter with a Gaussian response is applied.' }, 'name': 'GAUSSIAN', 'value': 1 }, { 'documentation': { 'description': ' An RBW filter with a flat response is applied.' }, 'name': 'FLAT', 'value': 2 } ] }, 'AcpSweepTimeAuto': { 'values': [ { 'documentation': { 'description': ' The measurement uses the sweep time that you specify in the RFMXSPECAN_ATTR_ACP_SWEEP_TIME_INTERVAL attribute.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' The measurement calculates the sweep time based on the value of the RFMXSPECAN_ATTR_ACP_RBW_FILTER_BANDWIDTH attribute.' }, 'name': 'TRUE', 'value': 1 } ] }, 'AmpmAMToAMCurveFitType': { 'values': [ { 'name': 'LEAST_SQUARE', 'value': 0 }, { 'name': 'LEAST_ABSOLUTE_RESIDUAL', 'value': 1 }, { 'name': 'BISQUARE', 'value': 2 } ] }, 'AmpmAMToAMEnabled': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'AmpmAMToPMCurveFitType': { 'values': [ { 'name': 'LEAST_SQUARE', 'value': 0 }, { 'name': 'LEAST_ABSOLUTE_RESIDUAL', 'value': 1 }, { 'name': 'BISQUARE', 'value': 2 } ] }, 'AmpmAMToPMEnabled': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'AmpmAutoCarrierDetectionEnabled': { 'values': [ { 'documentation': { 'description': ' Disables auto detection of carrier offset and carrier bandwidth.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' Enables auto detection of carrier offset and carrier bandwidth.' }, 'name': 'TRUE', 'value': 1 } ] }, 'AmpmAveragingEnabled': { 'values': [ { 'documentation': { 'description': ' The measurement is performed on a single acquisition.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' The AMPM measurement uses the RFMXSPECAN_ATTR_AMPM_AVERAGING_COUNT attribute as the number of acquisitions over which the signal for the AMPM measurement is averaged.' }, 'name': 'TRUE', 'value': 1 } ] }, 'AmpmCompressionPointEnabled': { 'values': [ { 'documentation': { 'description': ' Disables computation of compression points.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' Enables computation of compression points.' }, 'name': 'TRUE', 'value': 1 } ] }, 'AmpmCompressionPointGainReference': { 'values': [ { 'documentation': { 'description': ' Measurement computes the gain reference to be used for compression point calculation. The computed gain reference is also returned as RFMXSPECAN_ATTR_AMPM_RESULTS_MEAN_LINEAR_GAIN result.' }, 'name': 'AUTO', 'value': 0 }, { 'documentation': { 'description': ' Measurement uses the gain corresponding to the reference power that you specify for the RFMXSPECAN_ATTR_AMPM_COMPRESSION_POINT_GAIN_REFERENCE_POWER attribute as gain reference. The reference power can be configured as either input or output power based on the value of the RFMXSPECAN_ATTR_AMPM_REFERENCE_POWER_TYPE attribute.' }, 'name': 'REFERENCE_POWER', 'value': 1 } ] }, 'AmpmEqualizerMode': { 'values': [ { 'documentation': { 'description': ' Equalization is not performed.' }, 'name': 'OFF', 'value': 0 }, { 'documentation': { 'description': ' The equalizer is turned on to compensate for the effect of the channel.' }, 'name': 'TRAIN', 'value': 1 } ] }, 'AmpmEvmEnabled': { 'values': [ { 'documentation': { 'description': ' Disables EVM computation. NaN is returned as Mean RMS EVM.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' Enables EVM computation.' }, 'name': 'TRUE', 'value': 1 } ] }, 'AmpmFrequencyOffsetCorrectionEnabled': { 'values': [ { 'documentation': { 'description': ' The measurement does not perform frequency offset correction.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' The measurement computes and corrects any frequency offset between the reference and the acquired waveforms.' }, 'name': 'TRUE', 'value': 1 } ] }, 'AmpmIQOriginOffsetCorrectionEnabled': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'AmpmMeasurementSampleRateMode': { 'values': [ { 'documentation': { 'description': ' The acquisition sample rate is defined by the value of the RFMXSPECAN_ATTR_AMPM_MEASUREMENT_SAMPLE_RATE attribute.' }, 'name': 'USER', 'value': 0 }, { 'documentation': { 'description': ' The acquisition sample rate is set to match the sample rate of the reference waveform.' }, 'name': 'REFERENCE_WAVEFORM', 'value': 1 } ] }, 'AmpmReferencePowerType': { 'values': [ { 'documentation': { 'description': ' The instantaneous powers at the input port of device under test (DUT) forms the x-axis of AM to AM and AM to PM traces.' }, 'name': 'INPUT', 'value': 0 }, { 'documentation': { 'description': ' The instantaneous powers at the output port of DUT forms the x-axis of AM to AM and AM to PM traces.' }, 'name': 'OUTPUT', 'value': 1 } ] }, 'AmpmReferenceWaveformIdleDurationPresent': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'AmpmSignalType': { 'values': [ { 'documentation': { 'description': ' The reference waveform is a cellular or connectivity standard signal.' }, 'name': 'MODULATED', 'value': 0 }, { 'documentation': { 'description': ' The reference waveform is a continuous signal comprising of one or more tones.' }, 'name': 'TONES', 'value': 1 } ] }, 'AmpmSynchronizationMethod': { 'values': [ { 'documentation': { 'description': ' Synchronizes the acquired and reference waveforms assuming that sample rate is sufficient to prevent aliasing in intermediate operations. This method is recommended when the measurement sampling rate is high.' }, 'name': 'DIRECT', 'value': 1 }, { 'documentation': { 'description': ' Synchronizes the acquired and reference waveforms while ascertaining that intermediate operations are not impacted by aliasing. This method is recommended for non-contiguous carriers separated by a large gap, and/or when the measurement sampling rate is low. Refer to AMPM concept help for more information.' }, 'name': 'ALIAS_PROTECTED', 'value': 2 } ] }, 'AmpmThresholdEnabled': { 'values': [ { 'documentation': { 'description': ' All samples are considered for the AMPM measurement.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' Samples above the threshold level specified in the RFMXSPECAN_ATTR_AMPM_THRESHOLD_LEVEL attribute are considered for the AMPM measurement.' }, 'name': 'TRUE', 'value': 1 } ] }, 'AmpmThresholdType': { 'values': [ { 'documentation': { 'description': ' The threshold is relative to the peak power of the acquired samples.' }, 'name': 'RELATIVE', 'value': 0 }, { 'documentation': { 'description': ' The threshold is the absolute power, in dBm.' }, 'name': 'ABSOLUTE', 'value': 1 } ] }, 'Boolean': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'CcdfRbwFilterType': { 'values': [ { 'documentation': { 'description': ' The measurement does not use any RBW filtering.' }, 'name': 'NONE', 'value': 5 }, { 'documentation': { 'description': ' The RBW filter has a Gaussian response.' }, 'name': 'GAUSSIAN', 'value': 1 }, { 'documentation': { 'description': ' The RBW filter has a flat response.' }, 'name': 'FLAT', 'value': 2 }, { 'documentation': { 'description': ' The RRC filter with the roll-off specified by the RFMXSPECAN_ATTR_CCDF_RBW_FILTER_RRC_ALPHA attribute is used as the RBW filter.' }, 'name': 'RRC', 'value': 6 } ] }, 'CcdfThresholdEnabled': { 'values': [ { 'documentation': { 'description': ' All samples are considered for the CCDF measurement.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' The samples above the threshold level specified in the RFMXSPECAN_ATTR_CCDF_THRESHOLD_LEVEL attribute are considered for the CCDF measurement.' }, 'name': 'TRUE', 'value': 1 } ] }, 'CcdfThresholdType': { 'values': [ { 'documentation': { 'description': ' The threshold is relative to the peak power of the acquired samples.' }, 'name': 'RELATIVE', 'value': 0 }, { 'documentation': { 'description': ' The threshold is the absolute power, in dBm.' }, 'name': 'ABSOLUTE', 'value': 1 } ] }, 'ChpAmplitudeCorrectionType': { 'values': [ { 'documentation': { 'description': ' All the frequency bins in the spectrum are compensated with a single external attenuation value that corresponds to the RF center frequency.' }, 'name': 'RF_CENTER_FREQUENCY', 'value': 0 }, { 'documentation': { 'description': ' An individual frequency bin in the spectrum is compensated with the external attenuation value corresponding to that frequency.' }, 'name': 'SPECTRUM_FREQUENCY_BIN', 'value': 1 } ] }, 'ChpAveragingEnabled': { 'values': [ { 'documentation': { 'description': ' The measurement is performed on a single acquisition.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' The CHP measurement uses the RFMXSPECAN_ATTR_CHP_AVERAGING_COUNT attribute as the number of acquisitions over which the CHP measurement is averaged.' }, 'name': 'TRUE', 'value': 1 } ] }, 'ChpAveragingType': { 'values': [ { 'documentation': { 'description': ' The power spectrum is linearly averaged. RMS averaging reduces signal fluctuations but not the noise floor. ' }, 'name': 'RMS', 'value': 0 }, { 'documentation': { 'description': ' The power spectrum is averaged in a logarithmic scale.' }, 'name': 'LOG', 'value': 1 }, { 'documentation': { 'description': ' The square root of the power spectrum is averaged.' }, 'name': 'SCALAR', 'value': 2 }, { 'documentation': { 'description': ' The peak power in the spectrum at each frequency bin is retained from one acquisition to the next.' }, 'name': 'MAXIMUM', 'value': 3 }, { 'documentation': { 'description': ' The least power in the spectrum at each frequency bin is retained from one acquisition to the next. ' }, 'name': 'MINIMUM', 'value': 4 } ] }, 'ChpCarrierRrcFilterEnabled': { 'values': [ { 'documentation': { 'description': ' The channel power of the acquired channel is measured directly.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' The measurement applies the RRC filter on the acquired channel before measuring the channel power.' }, 'name': 'TRUE', 'value': 1 } ] }, 'ChpFftWindow': { 'values': [ { 'documentation': { 'description': ' Analyzes transients for which duration is shorter than the window length. You can also use this window type to separate two tones with frequencies close to each other but with almost equal amplitudes. ' }, 'name': 'NONE', 'value': 0 }, { 'documentation': { 'description': ' Measures single-tone amplitudes accurately.' }, 'name': 'FLAT_TOP', 'value': 1 }, { 'documentation': { 'description': ' Analyzes transients for which duration is longer than the window length. You can also use this window type to provide better frequency resolution for noise measurements.' }, 'name': 'HANNING', 'value': 2 }, { 'documentation': { 'description': ' Analyzes closely-spaced sine waves.' }, 'name': 'HAMMING', 'value': 3 }, { 'documentation': { 'description': ' Provides a good balance of spectral leakage, frequency resolution, and amplitude attenuation. Hence, this windowing is useful for time-frequency analysis.' }, 'name': 'GAUSSIAN', 'value': 4 }, { 'documentation': { 'description': ' Analyzes single tone because it has a low maximum side lobe level and a high side lobe roll-off rate. ' }, 'name': 'BLACKMAN', 'value': 5 }, { 'documentation': { 'description': ' Useful as a good general purpose window, having side lobe rejection greater than 90 dB and having a moderately wide main lobe. ' }, 'name': 'BLACKMAN_HARRIS', 'value': 6 }, { 'documentation': { 'description': ' Separates two tones with frequencies close to each other but with widely-differing amplitudes. ' }, 'name': 'KAISER_BESSEL', 'value': 7 } ] }, 'ChpMeasurementMode': { 'values': [ { 'documentation': { 'description': ' CHP measurement is performed on the acquired signal.' }, 'name': 'MEASURE', 'value': 0 }, { 'documentation': { 'description': ' Manual noise calibration of the signal analyzer is performed for the CHP measurement.' }, 'name': 'CALIBRATE_NOISE_FLOOR', 'value': 1 } ] }, 'ChpNoiseCalibrationAveragingAuto': { 'values': [ { 'documentation': { 'description': ' RFmx uses the averages that you set for the RFMXSPECAN_ATTR_CHP_NOISE_CALIBRATION_AVERAGING_COUNT attribute. ' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' RFmx uses a noise calibration averaging count of 32.' }, 'name': 'TRUE', 'value': 1 } ] }, 'ChpNoiseCalibrationDataValid': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'ChpNoiseCalibrationMode': { 'values': [ { 'documentation': { 'description': ' When you set the RFMXSPECAN_ATTR_CHP_MEASUREMENT_MODE attribute to RFMXSPECAN_VAL_CHP_MEASUREMENT_MODE_CALIBRATE_NOISE_FLOOR, you can initiate instrument noise calibration for the CHP measurement manually. When you set the RFMXSPECAN_ATTR_CHP_MEASUREMENT_MODE attribute to RFMXSPECAN_VAL_CHP_MEASUREMENT_MODE_MEASURE, you can initiate the CHP measurement manually.' }, 'name': 'MANUAL', 'value': 0 }, { 'documentation': { 'description': ' When you set the RFMXSPECAN_ATTR_CHP_NOISE_COMPENSATION_ENABLED attribute to RFMXSPECAN_VAL_CHP_NOISE_COMPENSATION_ENABLED_TRUE, RFmx sets Input Isolation Enabled to Enabled and calibrates the intrument noise in the current state of the instrument. RFmx then resets the Input Isolation Enabled attribute and performs the CHP measurement, including compensation for noise of the instrument. RFmx skips noise calibration in this mode if valid noise calibration data is already cached. When you set the RFMXSPECAN_ATTR_CHP_NOISE_COMPENSATION_ENABLED attribute to RFMXSPECAN_VAL_CHP_NOISE_COMPENSATION_ENABLED_FALSE, RFmx does not calibrate instrument noise and performs only the CHP measurement without compensating for the noise contribution of the instrument.' }, 'name': 'AUTO', 'value': 1 } ] }, 'ChpNoiseCompensationEnabled': { 'values': [ { 'documentation': { 'description': ' Disables noise compensation.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' Enables noise compensation.' }, 'name': 'TRUE', 'value': 1 } ] }, 'ChpNoiseCompensationType': { 'values': [ { 'documentation': { 'description': ' Compensates for noise from the analyzer and the 50 ohm termination. The measured power values are in excess of the thermal noise floor.' }, 'name': 'ANALYZER_AND_TERMINATION', 'value': 0 }, { 'documentation': { 'description': ' Compensates for the analyzer noise only.' }, 'name': 'ANALYZER_ONLY', 'value': 1 } ] }, 'ChpRbwAutoBandwidth': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'ChpRbwFilterBandwidthDefinition': { 'values': [ { 'documentation': { 'description': ' Defines the RBW in terms of the 3 dB bandwidth of the RBW filter. When you set the RFMXSPECAN_ATTR_CHP_RBW_FILTER_TYPE attribute to RFMXSPECAN_VAL_CHP_RBW_FILTER_TYPE_FFT_BASED, RBW is the 3 dB bandwidth of the window specified by the RFMXSPECAN_ATTR_CHP_FFT_WINDOW attribute.' }, 'name': '3_DB', 'value': 0 }, { 'documentation': { 'description': ' Defines the RBW in terms of the spectrum bin width computed using an FFT when you set the RFMXSPECAN_ATTR_CHP_RBW_FILTER_TYPE attribute to FFT Based.' }, 'name': 'BIN_WIDTH', 'value': 2 } ] }, 'ChpRbwFilterType': { 'values': [ { 'documentation': { 'description': ' No RBW filtering is performed.' }, 'name': 'FFT_BASED', 'value': 0 }, { 'documentation': { 'description': ' An RBW filter with a Gaussian response is applied.' }, 'name': 'GAUSSIAN', 'value': 1 }, { 'documentation': { 'description': ' An RBW filter with a flat response is applied. ' }, 'name': 'FLAT', 'value': 2 } ] }, 'ChpSweepTimeAuto': { 'values': [ { 'documentation': { 'description': ' The measurement uses the sweep time that you specify in the RFMXSPECAN_ATTR_CHP_SWEEP_TIME_INTERVAL attribute. ' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' The measurement calculates the sweep time based on the value of the RFMXSPECAN_ATTR_CHP_RBW_FILTER_BANDWIDTH attribute.' }, 'name': 'TRUE', 'value': 1 } ] }, 'DigitalEdgeTriggerEdge': { 'values': [ { 'documentation': { 'description': ' The trigger asserts on the rising edge of the signal.' }, 'name': 'RISING_EDGE', 'value': 0 }, { 'documentation': { 'description': ' The trigger asserts on the falling edge of the signal.' }, 'name': 'FALLING_EDGE', 'value': 1 } ] }, 'DigitalEdgeTriggerSource': { 'generate-mappings': True, 'values': [ { 'documentation': { 'description': ' The trigger is received on PFI 0.' }, 'name': 'PFI0', 'value': 'PFI0' }, { 'documentation': { 'description': ' The trigger is received on PFI 1.' }, 'name': 'PFI1', 'value': 'PFI1' }, { 'documentation': { 'description': ' The trigger is received on PXI trigger line 0.' }, 'name': 'PXI_TRIG0', 'value': 'PXI_Trig0' }, { 'documentation': { 'description': ' The trigger is received on PXI trigger line 1.' }, 'name': 'PXI_TRIG1', 'value': 'PXI_Trig1' }, { 'documentation': { 'description': ' The trigger is received on PXI trigger line 2.' }, 'name': 'PXI_TRIG2', 'value': 'PXI_Trig2' }, { 'documentation': { 'description': ' The trigger is received on PXI trigger line 3.' }, 'name': 'PXI_TRIG3', 'value': 'PXI_Trig3' }, { 'documentation': { 'description': ' The trigger is received on PXI trigger line 4.' }, 'name': 'PXI_TRIG4', 'value': 'PXI_Trig4' }, { 'documentation': { 'description': ' The trigger is received on PXI trigger line 5.' }, 'name': 'PXI_TRIG5', 'value': 'PXI_Trig5' }, { 'documentation': { 'description': ' The trigger is received on PXI trigger line 6.' }, 'name': 'PXI_TRIG6', 'value': 'PXI_Trig6' }, { 'documentation': { 'description': ' The trigger is received on PXI trigger line 7.' }, 'name': 'PXI_TRIG7', 'value': 'PXI_Trig7' }, { 'documentation': { 'description': ' The trigger is received on the PXI star trigger line. ' }, 'name': 'PXI_STAR', 'value': 'PXI_STAR' }, { 'documentation': { 'description': ' The trigger is received on the PXIe DStar B trigger line. ' }, 'name': 'PXIE_DSTARB', 'value': 'PXIe_DStarB' }, { 'documentation': { 'description': ' The trigger is received from the timer event.' }, 'name': 'TIMER_EVENT', 'value': 'TimerEvent' } ] }, 'DpdApplyDpdCfrEnabled': { 'values': [ { 'documentation': { 'description': ' Disables CFR. The maximum increase in PAPR, after pre-distortion, is limited to 6 dB.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' Enables CFR.' }, 'name': 'TRUE', 'value': 1 } ] }, 'DpdApplyDpdCfrMethod': { 'values': [ { 'documentation': { 'description': ' Hard clips the signal such that the target PAPR is achieved.' }, 'name': 'CLIPPING', 'value': 0 }, { 'documentation': { 'description': ' Scales the peaks in the signal using weighted window function to get smooth peaks and achieve the target PAPR.' }, 'name': 'PEAK_WINDOWING', 'value': 1 }, { 'documentation': { 'description': ' Scales the peaks using modified sigmoid transfer function to get smooth peaks and achieve the target PAPR. This method does not support the filter operation.' }, 'name': 'SIGMOID', 'value': 2 } ] }, 'DpdApplyDpdCfrTargetPaprType': { 'values': [ { 'documentation': { 'description': ' Sets the target PAPR for pre-distorted waveform equal to the PAPR of input waveform.' }, 'name': 'INPUT_PAPR', 'value': 0 }, { 'documentation': { 'description': ' Sets the target PAPR equal to the value that you set for the Apply DPD CFR Target PAPR attribute.' }, 'name': 'CUSTOM', 'value': 1 } ] }, 'DpdApplyDpdCfrWindowType': { 'values': [ { 'documentation': { 'description': ' Uses the flat top window function to scale peaks.' }, 'name': 'FLAT_TOP', 'value': 1 }, { 'documentation': { 'description': ' Uses the Hanning window function to scale peaks.' }, 'name': 'HANNING', 'value': 2 }, { 'documentation': { 'description': ' Uses the Hamming window function to scale peaks.' }, 'name': 'HAMMING', 'value': 3 }, { 'documentation': { 'description': ' Uses the Gaussian window function to scale peaks.' }, 'name': 'GAUSSIAN', 'value': 4 }, { 'documentation': { 'description': ' Uses the Blackman window function to scale peaks.' }, 'name': 'BLACKMAN', 'value': 5 }, { 'documentation': { 'description': ' Uses the Blackman-Harris window function to scale peaks.' }, 'name': 'BLACKMAN_HARRIS', 'value': 6 }, { 'documentation': { 'description': ' Uses the Kaiser-Bessel window function to scale peaks.' }, 'name': 'KAISER_BESSEL', 'value': 7 } ] }, 'DpdApplyDpdConfigurationInput': { 'values': [ { 'documentation': { 'description': ' Uses the computed DPD polynomial or lookup table for applying DPD on an input waveform using the same RFmx session handle. The configuration parameters for applying DPD such as the RFMXSPECAN_ATTR_DPD_DUT_AVERAGE_INPUT_POWER, RFMXSPECAN_ATTR_DPD_MODEL, RFMXSPECAN_ATTR_DPD_MEASUREMENT_SAMPLE_RATE, DPD polynomial, and lookup table are obtained from the DPD measurement configuration. ' }, 'name': 'MEASUREMENT', 'value': 0 }, { 'documentation': { 'description': ' Applies DPD by using a computed DPD polynomial or lookup table on an input waveform. You must set the configuration parameters for applying DPD such as the RFMXSPECAN_ATTR_DPD_APPLY_DPD_USER_DUT_AVERAGE_INPUT_POWER, RFMXSPECAN_ATTR_DPD_APPLY_DPD_USER_DPD_MODEL, RFMXSPECAN_ATTR_DPD_APPLY_DPD_USER_MEASUREMENT_SAMPLE_RATE, DPD polynomial, and lookup table. ' }, 'name': 'USER', 'value': 1 } ] }, 'DpdApplyDpdIdleDurationPresent': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'DpdApplyDpdLookupTableCorrectionType': { 'values': [ { 'documentation': { 'description': ' The measurement predistorts the magnitude and phase of the input waveform.' }, 'name': 'MAGNITUDE_AND_PHASE', 'value': 0 }, { 'documentation': { 'description': ' The measurement predistorts only the magnitude of the input waveform.' }, 'name': 'MAGNITUDE_ONLY', 'value': 1 }, { 'documentation': { 'description': ' The measurement predistorts only the phase of the input waveform.' }, 'name': 'PHASE_ONLY', 'value': 2 } ] }, 'DpdApplyDpdMemoryModelCorrectionType': { 'values': [ { 'documentation': { 'description': ' The measurement predistorts the magnitude and phase of the input waveform.' }, 'name': 'MAGNITUDE_AND_PHASE', 'value': 0 }, { 'documentation': { 'description': ' The measurement predistorts only the magnitude of the input waveform.' }, 'name': 'MAGNITUDE_ONLY', 'value': 1 }, { 'documentation': { 'description': ' The measurement predistorts only the phase of the input waveform.' }, 'name': 'PHASE_ONLY', 'value': 2 } ] }, 'DpdApplyDpdUserDpdModel': { 'values': [ { 'documentation': { 'description': ' This model computes the complex gain coefficients applied to linearize systems with negligible memory effects.' }, 'name': 'LOOKUP_TABLE', 'value': 0 }, { 'documentation': { 'description': ' This model computes the memory polynomial predistortion coefficients used to linearize systems with moderate memory effects.' }, 'name': 'MEMORY_POLYNOMIAL', 'value': 1 }, { 'documentation': { 'description': ' This model computes the generalized memory polynomial predistortion coefficients used to linearize systems with significant memory effects.' }, 'name': 'GENERALIZED_MEMORY_POLYNOMIAL', 'value': 2 } ] }, 'DpdApplyDpdUserLookupTableType': { 'values': [ { 'documentation': { 'description': ' Input powers in the LUT are specified in dBm.' }, 'name': 'LOG', 'value': 0 }, { 'documentation': { 'description': ' Input powers in the LUT are specified in watts.' }, 'name': 'LINEAR', 'value': 1 } ] }, 'DpdAutoCarrierDetectionEnabled': { 'values': [ { 'documentation': { 'description': ' Disables auto detection of carrier offset and carrier bandwidth.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' Enables auto detection of carrier offset and carrier bandwidth.' }, 'name': 'TRUE', 'value': 1 } ] }, 'DpdAveragingEnabled': { 'values': [ { 'documentation': { 'description': ' The measurement is performed on a single acquisition.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' The DPD measurement uses the RFMXSPECAN_ATTR_DPD_AVERAGING_COUNT attribute as the number of acquisitions over which the signal for the DPD measurement is averaged. ' }, 'name': 'TRUE', 'value': 1 } ] }, 'DpdFrequencyOffsetCorrectionEnabled': { 'values': [ { 'documentation': { 'description': ' The measurement computes and corrects any frequency offset between the reference and the acquired waveforms.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' The measurement does not perform frequency offset correction.' }, 'name': 'TRUE', 'value': 1 } ] }, 'DpdIQOriginOffsetCorrectionEnabled': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'DpdIterativeDpdEnabled': { 'values': [ { 'documentation': { 'description': ' RFmx computes the DPD Results DPD Polynomial without considering the value of the DPD Previous DPD Polynomial.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' RFmx computes the DPD Results DPD Polynomial based on the value of the DPD Previous DPD Polynomial.' }, 'name': 'TRUE', 'value': 1 } ] }, 'DpdLookupTableAMToAMCurveFitType': { 'values': [ { 'name': 'LEAST_SQUARE', 'value': 0 }, { 'name': 'LEAST_ABSOLUTE_RESIDUAL', 'value': 1 }, { 'name': 'BISQUARE', 'value': 2 } ] }, 'DpdLookupTableAMToPMCurveFitType': { 'values': [ { 'name': 'LEAST_SQUARE', 'value': 0 }, { 'name': 'LEAST_ABSOLUTE_RESIDUAL', 'value': 1 }, { 'name': 'BISQUARE', 'value': 2 } ] }, 'DpdLookupTableThresholdEnabled': { 'values': [ { 'documentation': { 'description': ' All samples are considered for the DPD measurement.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' Only samples above the threshold level which you specify in the RFMXSPECAN_ATTR_DPD_LOOKUP_TABLE_THRESHOLD_LEVEL attribute are considered for the DPD measurement.' }, 'name': 'TRUE', 'value': 1 } ] }, 'DpdLookupTableThresholdType': { 'values': [ { 'documentation': { 'description': ' The threshold is relative to the peak power of the acquired samples.' }, 'name': 'RELATIVE', 'value': 0 }, { 'documentation': { 'description': ' The threshold is the absolute power, in dBm.' }, 'name': 'ABSOLUTE', 'value': 1 } ] }, 'DpdLookupTableType': { 'values': [ { 'documentation': { 'description': ' Input powers in the LUT are specified in dBm.' }, 'name': 'LOG', 'value': 0 }, { 'documentation': { 'description': ' Input powers in the LUT are specified in watts.' }, 'name': 'LINEAR', 'value': 1 } ] }, 'DpdMeasurementSampleRateMode': { 'values': [ { 'documentation': { 'description': ' The acquisition sample rate is defined by the value of the RFMXSPECAN_ATTR_DPD_MEASUREMENT_SAMPLE_RATE attribute.' }, 'name': 'USER', 'value': 0 }, { 'documentation': { 'description': ' The acquisition sample rate is set to match the sample rate of the reference waveform.' }, 'name': 'REFERENCE_WAVEFORM', 'value': 1 } ] }, 'DpdModel': { 'values': [ { 'documentation': { 'description': ' This model computes the complex gain coefficients applied when performing digital predistortion to linearize systems with negligible memory effects.' }, 'name': 'LOOKUP_TABLE', 'value': 0 }, { 'documentation': { 'description': ' This model computes the memory polynomial predistortion coefficients used to linearize systems with moderate memory effects.' }, 'name': 'MEMORY_POLYNOMIAL', 'value': 1 }, { 'documentation': { 'description': ' This model computes the generalized memory polynomial predistortion coefficients used to linearize systems with significant memory effects.' }, 'name': 'GENERALIZED_MEMORY_POLYNOMIAL', 'value': 2 } ] }, 'DpdNmseEnabled': { 'values': [ { 'documentation': { 'description': ' Disables NMSE computation. NaN is returned as NMSE.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' Enables NMSE computation.' }, 'name': 'TRUE', 'value': 1 } ] }, 'DpdPreDpdCfrEnabled': { 'values': [ { 'documentation': { 'description': ' Disables the CFR. The RFmxSpecAn_DPDApplyPreDPDSignalConditioning function returns an error when the CFR is disabled.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' Enables the CFR.' }, 'name': 'TRUE', 'value': 1 } ] }, 'DpdPreDpdCfrFilterEnabled': { 'values': [ { 'documentation': { 'description': ' Disables the filter operation when performing CFR.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' Enables filter operation when performing CFR. Filter operation is not supported when you set the RFMXSPECAN_ATTR_DPD_PRE_DPD_CFR_METHOD attribute to RFMXSPECAN_VAL_DPD_PRE_DPD_CFR_METHOD_SIGMOID.' }, 'name': 'TRUE', 'value': 1 } ] }, 'DpdPreDpdCfrMethod': { 'values': [ { 'documentation': { 'description': ' Hard clips the signal such that the target PAPR is achieved.' }, 'name': 'CLIPPING', 'value': 0 }, { 'documentation': { 'description': ' Scales the peaks in the signal using weighted window function to get smooth peaks and achieve the target PAPR.' }, 'name': 'PEAK_WINDOWING', 'value': 1 }, { 'documentation': { 'description': ' Scales the peaks using modified sigmoid transfer function to get smooth peaks and achieve the target PAPR. This method does not support the filter operation.' }, 'name': 'SIGMOID', 'value': 2 } ] }, 'DpdPreDpdCfrWindowType': { 'values': [ { 'documentation': { 'description': ' Uses the flat top window function to scale peaks.' }, 'name': 'FLAT_TOP', 'value': 1 }, { 'documentation': { 'description': ' Uses the Hanning window function to scale peaks.' }, 'name': 'HANNING', 'value': 2 }, { 'documentation': { 'description': ' Uses the Hamming window function to scale peaks.' }, 'name': 'HAMMING', 'value': 3 }, { 'documentation': { 'description': ' Uses the Gaussian window function to scale peaks.' }, 'name': 'GAUSSIAN', 'value': 4 }, { 'documentation': { 'description': ' Uses the Blackman window function to scale peaks.' }, 'name': 'BLACKMAN', 'value': 5 }, { 'documentation': { 'description': ' Uses the Blackman-Harris window function to scale peaks.' }, 'name': 'BLACKMAN_HARRIS', 'value': 6 }, { 'documentation': { 'description': ' Uses the Kaiser-Bessel window function to scale peaks.' }, 'name': 'KAISER_BESSEL', 'value': 7 } ] }, 'DpdReferenceWaveformIdleDurationPresent': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'DpdSignalType': { 'values': [ { 'documentation': { 'description': ' The reference waveform is a cellular or connectivity standard signal.' }, 'name': 'MODULATED', 'value': 0 }, { 'documentation': { 'description': ' The reference waveform is a continuous signal comprising one or more tones.' }, 'name': 'TONES', 'value': 1 } ] }, 'DpdSynchronizationMethod': { 'values': [ { 'documentation': { 'description': ' Synchronizes the acquired and reference waveforms assuming that sample rate is sufficient to prevent aliasing in intermediate operations. This method is recommended when measurement sampling rate is high.' }, 'name': 'DIRECT', 'value': 1 }, { 'documentation': { 'description': ' Synchronizes the acquired and reference waveforms while ascertaining that intermediate operations are not impacted by aliasing. This method is recommended for non-contiguous carriers separated by a large gap, and/or when measurement sampling rate is low. Refer to DPD concept help for more information.' }, 'name': 'ALIAS_PROTECTED', 'value': 2 } ] }, 'DpdTargetGainType': { 'values': [ { 'documentation': { 'description': ' The DPD polynomial or lookup table is computed by assuming that the linearized gain expected from the DUT after applying DPD on the input waveform is equal to the average power gain provided by the DUT without DPD.' }, 'name': 'AVERAGE_GAIN', 'value': 0 }, { 'documentation': { 'description': ' The DPD polynomial or lookup table is computed by assuming that the linearized gain expected from the DUT after applying DPD on the input waveform is equal to the gain provided by the DUT, without DPD, to the parts of the reference waveform that do not drive the DUT into non-linear gain-expansion or compression regions of its input-output characteristics.\n\n The measurement computes the linear region gain as the average gain experienced by the parts of the reference waveform that are below a threshold which is computed as shown in the following equation:\n\n Linear region threshold (dBm) = Max {-25, Min {reference waveform power} + 6, DUT Average Input Power -15}' }, 'name': 'LINEAR_REGION_GAIN', 'value': 1 }, { 'documentation': { 'description': ' The DPD polynomial or lookup table is computed by assuming that the linearized gain expected from the DUT after applying DPD on the input waveform is equal to the average power gain provided by the DUT, without DPD, to all the samples of the reference waveform for which the magnitude is greater than the peak power in the reference waveform (dBm) - 0.5dB.' }, 'name': 'PEAK_INPUT_POWER_GAIN', 'value': 2 } ] }, 'FcntAveragingEnabled': { 'values': [ { 'documentation': { 'description': ' The measurement is performed on a single acquisition.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' The FCnt measurement uses the RFMXSPECAN_ATTR_FCNT_AVERAGING_COUNT attribute as the number of acquisitions over which the FCnt measurement is averaged. ' }, 'name': 'TRUE', 'value': 1 } ] }, 'FcntAveragingType': { 'values': [ { 'documentation': { 'description': ' The mean of the instantaneous signal phase difference over multiple acquisitions is used for the frequency measurement. ' }, 'name': 'MEAN', 'value': 6 }, { 'documentation': { 'description': ' The maximum instantaneous signal phase difference over multiple acquisitions is used for the frequency measurement. ' }, 'name': 'MAXIMUM', 'value': 3 }, { 'documentation': { 'description': ' The minimum instantaneous signal phase difference over multiple acquisitions is used for the frequency measurement. ' }, 'name': 'MINIMUM', 'value': 4 }, { 'documentation': { 'description': ' The maximum instantaneous signal phase difference over multiple acquisitions is used for the frequency measurement. The sign of the phase difference is ignored to find the maximum instantaneous value.' }, 'name': 'MINMAX', 'value': 7 } ] }, 'FcntRbwFilterType': { 'values': [ { 'documentation': { 'description': ' The measurement does not use any RBW filtering.' }, 'name': 'NONE', 'value': 5 }, { 'documentation': { 'description': ' The RBW filter has a Gaussian response.' }, 'name': 'GAUSSIAN', 'value': 1 }, { 'documentation': { 'description': ' The RBW filter has a flat response.' }, 'name': 'FLAT', 'value': 2 }, { 'documentation': { 'description': ' The RRC filter with the roll-off specified by RFMXSPECAN_ATTR_FCNT_RBW_FILTER_RRC_ALPHA attribute is used as the RBW filter.' }, 'name': 'RRC', 'value': 6 } ] }, 'FcntThresholdEnabled': { 'values': [ { 'documentation': { 'description': ' All samples are considered for the FCnt measurement. ' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' The samples above the threshold level specified in the RFMXSPECAN_ATTR_FCNT_THRESHOLD_LEVEL attribute are considered for the FCnt measurement. ' }, 'name': 'TRUE', 'value': 1 } ] }, 'FcntThresholdType': { 'values': [ { 'documentation': { 'description': ' The threshold is relative to the peak power of the acquired samples.' }, 'name': 'RELATIVE', 'value': 0 }, { 'documentation': { 'description': ' The threshold is the absolute power, in dBm.' }, 'name': 'ABSOLUTE', 'value': 1 } ] }, 'FrequencyReferenceSource': { 'generate-mappings': True, 'values': [ { 'name': 'ONBOARD_CLOCK', 'value': 'OnboardClock' }, { 'name': 'REF_IN', 'value': 'RefIn' }, { 'name': 'PXI_CLK', 'value': 'PXI_Clk' }, { 'name': 'CLK_IN', 'value': 'ClkIn' } ] }, 'HarmAutoHarmonicsSetupEnabled': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'HarmAveragingEnabled': { 'values': [ { 'documentation': { 'description': ' The measurement is performed on a single acquisition.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' The Harmonics measurement uses the RFMXSPECAN_ATTR_HARM_AVERAGING_COUNT attribute as the number of acquisitions over which the Harmonics measurement is averaged.' }, 'name': 'TRUE', 'value': 1 } ] }, 'HarmAveragingType': { 'values': [ { 'documentation': { 'description': ' The power trace is linearly averaged. RMS averaging reduces signal fluctuations but not the noise floor. ' }, 'name': 'RMS', 'value': 0 }, { 'documentation': { 'description': ' The power trace is averaged in a logarithmic scale.' }, 'name': 'LOG', 'value': 1 }, { 'documentation': { 'description': ' The square root of the power trace is averaged.' }, 'name': 'SCALAR', 'value': 2 }, { 'documentation': { 'description': ' The maximum instantaneous power in the power trace is retained from one acquisition to the next.' }, 'name': 'MAXIMUM', 'value': 3 }, { 'documentation': { 'description': ' The minimum instantaneous power in the power trace is retained from one acquisition to the next.' }, 'name': 'MINIMUM', 'value': 4 } ] }, 'HarmHarmonicEnabled': { 'values': [ { 'documentation': { 'description': ' Disables the harmonic for measurement.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' Enables the harmonic for measurement.' }, 'name': 'TRUE', 'value': 1 } ] }, 'HarmMeasurementMethod': { 'values': [ { 'documentation': { 'description': ' The harmonics measurement acquires the signal using the same signal analyzer setting across frequency bands. Use this method when the measurement speed is desirable over higher dynamic range.\n\n Supported devices: PXIe-5644/5645/5646, PXIe-5663/5665/5668' }, 'name': 'TIME_DOMAIN', 'value': 0 }, { 'documentation': { 'description': ' The harmonics measurement acquires the signal using the hardware-specific features, such as the IF filter and IF gain, for different frequency bands. Use this method to get the best dynamic range.\n\n Supported devices: PXIe-5665/5668' }, 'name': 'DYNAMIC_RANGE', 'value': 2 } ] }, 'HarmNoiseCompensationEnabled': { 'values': [ { 'documentation': { 'description': ' Disables compensation of the average harmonic powers for the noise floor of the signal analyzer.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' Enables compensation of the average harmonic powers for the noise floor of the signal analyzer. The noise floor of the signal analyzer is measured for the RF path used by the harmonics measurement and cached for future use. If the signal analyzer or measurement parameters change, noise floors are measured again.\n\n Supported devices: PXIe-5663/5665/5668' }, 'name': 'TRUE', 'value': 1 } ] }, 'HarmRbwFilterType': { 'values': [ { 'name': 'GAUSSIAN', 'value': 1 }, { 'name': 'FLAT', 'value': 2 }, { 'name': 'NONE', 'value': 5 }, { 'name': 'RRC', 'value': 6 } ] }, 'IMAmplitudeCorrectionType': { 'values': [ { 'name': 'RF_CENTER_FREQUENCY', 'value': 0 }, { 'name': 'SPECTRUM_FREQUENCY_BIN', 'value': 1 } ] }, 'IMAutoIntermodsSetupEnabled': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'IMAveragingEnabled': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'IMAveragingType': { 'values': [ { 'name': 'RMS', 'value': 0 }, { 'name': 'LOG', 'value': 1 }, { 'name': 'SCALAR', 'value': 2 }, { 'name': 'MAXIMUM', 'value': 3 }, { 'name': 'MINIMUM', 'value': 4 } ] }, 'IMFftWindow': { 'values': [ { 'name': 'NONE', 'value': 0 }, { 'name': 'FLAT_TOP', 'value': 1 }, { 'name': 'HANNING', 'value': 2 }, { 'name': 'HAMMING', 'value': 3 }, { 'name': 'GAUSSIAN', 'value': 4 }, { 'name': 'BLACKMAN', 'value': 5 }, { 'name': 'BLACKMAN_HARRIS', 'value': 6 }, { 'name': 'KAISER_BESSEL', 'value': 7 } ] }, 'IMFrequencyDefinition': { 'values': [ { 'name': 'RELATIVE', 'value': 0 }, { 'name': 'ABSOLUTE', 'value': 1 } ] }, 'IMIFOutputPowerOffsetAuto': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'IMIntermodEnabled': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'IMIntermodSide': { 'values': [ { 'name': 'LOWER', 'value': 0 }, { 'name': 'UPPER', 'value': 1 }, { 'name': 'BOTH', 'value': 2 } ] }, 'IMLocalPeakSearchEnabled': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'IMMeasurementMethod': { 'values': [ { 'name': 'NORMAL', 'value': 0 }, { 'name': 'DYNAMIC_RANGE', 'value': 1 }, { 'name': 'SEGMENTED', 'value': 2 } ] }, 'IMRbwFilterAutoBandwidth': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'IMRbwFilterType': { 'values': [ { 'name': 'FFT_BASED', 'value': 0 }, { 'name': 'GAUSSIAN', 'value': 1 }, { 'name': 'FLAT', 'value': 2 } ] }, 'IMSweepTimeAuto': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'IQBandwidthAuto': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'IQDeleteRecordOnFetch': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'IQPowerEdgeTriggerLevelType': { 'values': [ { 'name': 'RELATIVE', 'value': 0 }, { 'name': 'ABSOLUTE', 'value': 1 } ] }, 'IQPowerEdgeTriggerSlope': { 'values': [ { 'name': 'RISING_SLOPE', 'value': 0 }, { 'name': 'FALLING_SLOPE', 'value': 1 } ] }, 'LimitedConfigurationChange': { 'values': [ { 'documentation': { 'description': ' This is the normal mode of RFmx operation. All configuration changes in RFmxInstr attributes or in personality attributes will be applied during RFmx Commit.' }, 'name': 'DISABLED', 'value': 0 }, { 'documentation': { 'description': ' Signal configuration and RFmxInstr configuration are locked after the first Commit or Initiate of the named signal configuration. Any configuration change thereafter either in RFmxInstr attributes or personality attributes will not be considered by subsequent RFmx Commits or Initiates of this signal. Use No Change if you have created named signal configurations for all measurement configurations but are setting some RFmxInstr attributes. Refer to the Limitations of the Limited Configuration Change Attribute topic for more details about the limitations of using this mode. ' }, 'name': 'NO_CHANGE', 'value': 1 }, { 'documentation': { 'description': ' Signal configuration, other than center frequency, external attenuation, and RFInstr configuration, is locked after first Commit or Initiate of the named signal configuration. Thereafter, only the Center Frequency and RFMXSPECAN_ATTR_EXTERNAL_ATTENUATION attribute value changes will be considered by subsequent driver Commits or Initiates of this signal. Refer to the Limitations of the Limited Configuration Change Attribute topic for more details about the limitations of using this mode. ' }, 'name': 'FREQUENCY', 'value': 2 }, { 'documentation': { 'description': ' Signal configuration, other than the reference level and RFInstr configuration, is locked after first Commit or Initiate of the named signal configuration. Thereafter only the RFMXSPECAN_ATTR_REFERENCE_LEVEL attribute value change will be considered by subsequent driver Commits or Initiates of this signal. If you have configured this signal to use an IQ Power Edge Trigger, NI recommends that you set the RFMXSPECAN_ATTR_IQ_POWER_EDGE_TRIGGER_LEVEL_TYPE to RFMXSPECAN_VAL_IQ_POWER_EDGE_TRIGGER_LEVEL_TYPE_RELATIVE so that the trigger level is automatically adjusted as you adjust the reference level. Refer to the Limitations of the Limited Configuration Change Attribute topic for more details about the limitations of using this mode. ' }, 'name': 'REFERENCE_LEVEL', 'value': 3 }, { 'documentation': { 'description': ' Signal configuration, other than center frequency, reference level, external attenuation, and RFInstr configuration, is locked after first Commit or Initiate of the named signal configuration. Thereafter only Center Frequency, RFMXSPECAN_ATTR_REFERENCE_LEVEL, and RFMXSPECAN_ATTR_EXTERNAL_ATTENUATION attribute value changes will be considered by subsequent driver Commits or Initiates of this signal. If you have configured this signal to use an IQ Power Edge Trigger, NI recommends you set the RFMXSPECAN_ATTR_IQ_POWER_EDGE_TRIGGER_LEVEL_TYPE to RFMXSPECAN_VAL_IQ_POWER_EDGE_TRIGGER_LEVEL_TYPE_RELATIVE so that the trigger level is automatically adjusted as you adjust the reference level. Refer to the Limitations of the Limited Configuration Change Attribute topic for more details about the limitations of using this mode. ' }, 'name': 'FREQUENCY_AND_REFERENCE_LEVEL', 'value': 4 }, { 'documentation': { 'description': ' Signal configuration, other than Selected Ports, Center frequency, Reference level, External attenuation, and RFInstr configuration, is locked after first Commit or Initiate of the named signal configuration. Thereafter only Selected Ports, Center Frequency, RFMXSPECAN_ATTR_REFERENCE_LEVEL, and RFMXSPECAN_ATTR_EXTERNAL_ATTENUATION attribute value changes will be considered by subsequent driver Commits or Initiates of this signal. If you have configured this signal to use an IQ Power Edge Trigger, NI recommends you set the RFMXSPECAN_ATTR_IQ_POWER_EDGE_TRIGGER_LEVEL_TYPE to RFMXSPECAN_VAL_IQ_POWER_EDGE_TRIGGER_LEVEL_TYPE_RELATIVE so that the trigger level is automatically adjusted as you adjust the reference level. Refer to the Limitations of the Limited Configuration Change Attribute topic for more details about the limitations of using this mode.' }, 'name': 'SELECTED_PORTS_FREQUENCY_AND_REFERENCE_LEVEL', 'value': 5 } ] }, 'MarkerNextPeak': { 'values': [ { 'name': 'NEXT_HIGHEST', 'value': 0 }, { 'name': 'NEXT_LEFT', 'value': 1 }, { 'name': 'NEXT_RIGHT', 'value': 2 } ] }, 'MarkerPeakExcursionEnabled': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'MarkerThresholdEnabled': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'MarkerTrace': { 'values': [ { 'name': 'ACP_SPECTRUM', 'value': 0 }, { 'name': 'CCDF_GAUSSIAN_PROBABILITIES_TRACE', 'value': 1 }, { 'name': 'CCDF_PROBABILITIES_TRACE', 'value': 2 }, { 'name': 'CHP_SPECTRUM', 'value': 3 }, { 'name': 'FCNT_POWER_TRACE', 'value': 4 }, { 'name': 'OBW_SPECTRUM', 'value': 5 }, { 'name': 'SEM_SPECTRUM', 'value': 6 }, { 'name': 'SPECTRUM', 'value': 7 }, { 'name': 'TXP_POWER_TRACE', 'value': 8 } ] }, 'MarkerType': { 'values': [ { 'name': 'OFF', 'value': 0 }, { 'name': 'NORMAL', 'value': 1 }, { 'name': 'DELTA', 'value': 3 } ] }, 'MeasurementTypes': { 'values': [ { 'name': 'ACP', 'value': 1 }, { 'name': 'CCDF', 'value': 2 }, { 'name': 'CHP', 'value': 4 }, { 'name': 'FCNT', 'value': 8 }, { 'name': 'HARMONICS', 'value': 16 }, { 'name': 'OBW', 'value': 32 }, { 'name': 'SEM', 'value': 64 }, { 'name': 'SPECTRUM', 'value': 128 }, { 'name': 'SPUR', 'value': 256 }, { 'name': 'TXP', 'value': 512 }, { 'name': 'AMPM', 'value': 1024 }, { 'name': 'DPD', 'value': 2048 }, { 'name': 'IQ', 'value': 4096 }, { 'name': 'IM', 'value': 8192 }, { 'name': 'NF', 'value': 16384 }, { 'name': 'PHASENOISE', 'value': 32768 }, { 'name': 'PAVT', 'value': 65536 } ] }, 'MechanicalAttenuationAuto': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'NFAveragingEnabled': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'NFCalibrationDataValid': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'NFCalibrationLossCompensationEnabled': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'NFColdSourceMode': { 'values': [ { 'name': 'MEASURE', 'value': 0 }, { 'name': 'CALIBRATE', 'value': 1 } ] }, 'NFDutInputLossCompensationEnabled': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'NFDutOutputLossCompensationEnabled': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'NFDutType': { 'values': [ { 'name': 'AMPLIFIER', 'value': 0 }, { 'name': 'DOWNCONVERTER', 'value': 1 }, { 'name': 'UPCONVERTER', 'value': 2 } ] }, 'NFExternalPreampPresent': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'NFFrequencyConverterFrequencyContext': { 'values': [ { 'name': 'RF', 'value': 0 }, { 'name': 'IF', 'value': 1 } ] }, 'NFFrequencyConverterSideband': { 'values': [ { 'name': 'LSB', 'value': 0 }, { 'name': 'USB', 'value': 1 } ] }, 'NFMeasurementMethod': { 'values': [ { 'name': 'Y_FACTOR', 'value': 0 }, { 'name': 'COLD_SOURCE', 'value': 1 } ] }, 'NFYFactorMode': { 'values': [ { 'name': 'MEASURE', 'value': 0 }, { 'name': 'CALIBRATE', 'value': 1 } ] }, 'NFYFactorNoiseSourceLossCompensationEnabled': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'ObwAmplitudeCorrectionType': { 'values': [ { 'documentation': { 'description': ' All the frequency bins in the spectrum are compensated with a single external attenuation value that corresponds to the RF center frequency.' }, 'name': 'RF_CENTER_FREQUENCY', 'value': 0 }, { 'documentation': { 'description': ' An individual frequency bin in the spectrum is compensated with the external attenuation value corresponding to that frequency.' }, 'name': 'SPECTRUM_FREQUENCY_BIN', 'value': 1 } ] }, 'ObwAveragingEnabled': { 'values': [ { 'documentation': { 'description': ' The measurement is performed on a single acquisition.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' The OBW measurement uses the RFMXSPECAN_ATTR_OBW_AVERAGING_COUNT attribute as the number of acquisitions over which the OBW measurement is averaged.' }, 'name': 'TRUE', 'value': 1 } ] }, 'ObwAveragingType': { 'values': [ { 'documentation': { 'description': ' The power spectrum is linearly averaged. RMS averaging reduces signal fluctuations but not the noise floor. ' }, 'name': 'RMS', 'value': 0 }, { 'documentation': { 'description': ' The power spectrum is averaged in a logarithmic scale.' }, 'name': 'LOG', 'value': 1 }, { 'documentation': { 'description': ' The square root of the power spectrum is averaged.' }, 'name': 'SCALAR', 'value': 2 }, { 'documentation': { 'description': ' The peak power in the spectrum at each frequency bin is retained from one acquisition to the next.' }, 'name': 'MAXIMUM', 'value': 3 }, { 'documentation': { 'description': ' The least power in the spectrum at each frequency bin is retained from one acquisition to the next. ' }, 'name': 'MINIMUM', 'value': 4 } ] }, 'ObwFftWindow': { 'values': [ { 'documentation': { 'description': ' Analyzes transients for which duration is shorter than the window length. You can also use this window type to separate two tones with frequencies close to each other but with almost equal amplitudes. ' }, 'name': 'NONE', 'value': 0 }, { 'documentation': { 'description': ' Measures single-tone amplitudes accurately.' }, 'name': 'FLAT_TOP', 'value': 1 }, { 'documentation': { 'description': ' Analyzes transients for which duration is longer than the window length. You can also use this window type to provide better frequency resolution for noise measurements.' }, 'name': 'HANNING', 'value': 2 }, { 'documentation': { 'description': ' Analyzes closely-spaced sine waves.' }, 'name': 'HAMMING', 'value': 3 }, { 'documentation': { 'description': ' Provides a good balance of spectral leakage, frequency resolution, and amplitude attenuation. Hence, this windowing is useful for time-frequency analysis.' }, 'name': 'GAUSSIAN', 'value': 4 }, { 'documentation': { 'description': ' Analyzes single tone because it has a low maximum side lobe level and a high side lobe roll-off rate. ' }, 'name': 'BLACKMAN', 'value': 5 }, { 'documentation': { 'description': ' Useful as a good general purpose window, having side lobe rejection greater than 90 dB and having a moderately wide main lobe. ' }, 'name': 'BLACKMAN_HARRIS', 'value': 6 }, { 'documentation': { 'description': ' Separates two tones with frequencies close to each other but with widely-differing amplitudes. ' }, 'name': 'KAISER_BESSEL', 'value': 7 } ] }, 'ObwPowerUnits': { 'values': [ { 'documentation': { 'description': ' The absolute powers are reported in dBm.' }, 'name': 'DBM', 'value': 0 }, { 'documentation': { 'description': ' The absolute powers are reported in dBm/Hz.' }, 'name': 'DBM_PER_HZ', 'value': 1 } ] }, 'ObwRbwAutoBandwidth': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'ObwRbwFilterBandwidthDefinition': { 'values': [ { 'documentation': { 'description': ' Defines the RBW in terms of the 3 dB bandwidth of the RBW filter. When you set the RFMXSPECAN_ATTR_OBW_RBW_FILTER_TYPE attribute to RFMXSPECAN_VAL_OBW_RBW_FILTER_TYPE_FFT_BASED, RBW is the 3 dB bandwidth of the window specified by the RFMXSPECAN_ATTR_OBW_FFT_WINDOW attribute.' }, 'name': '3_DB', 'value': 0 }, { 'documentation': { 'description': ' Defines the RBW in terms of the spectrum bin width computed using an FFT when you set the RFMXSPECAN_ATTR_OBW_RBW_FILTER_TYPE attribute to FFT Based.' }, 'name': 'BIN_WIDTH', 'value': 2 } ] }, 'ObwRbwFilterType': { 'values': [ { 'documentation': { 'description': ' No RBW filtering is performed.' }, 'name': 'FFT_BASED', 'value': 0 }, { 'documentation': { 'description': ' The RBW filter has a Gaussian response.' }, 'name': 'GAUSSIAN', 'value': 1 }, { 'documentation': { 'description': ' The RBW filter has a flat response.' }, 'name': 'FLAT', 'value': 2 } ] }, 'ObwSweepTimeAuto': { 'values': [ { 'documentation': { 'description': ' The measurement uses the sweep time that you specify in the RFMXSPECAN_ATTR_OBW_SWEEP_TIME_INTERVAL attribute. ' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' The measurement calculates the sweep time based on the value of the RFMXSPECAN_ATTR_OBW_RBW_FILTER_BANDWIDTH attribute.' }, 'name': 'TRUE', 'value': 1 } ] }, 'PavtFrequencyOffsetCorrectionEnabled': { 'values': [ { 'documentation': { 'description': ' Disables the frequency offset correction.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' Enables the frequency offset correction. The measurement computes and corrects any frequency offset between the reference and the acquired waveforms.' }, 'name': 'TRUE', 'value': 1 } ] }, 'PavtFrequencyTrackingEnabled': { 'values': [ { 'documentation': { 'description': ' Disables the drift correction for the measurement.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' Enables the drift correction. The measurement corrects and reports the frequency offset per segment.' }, 'name': 'TRUE', 'value': 1 } ] }, 'PavtMeasurementIntervalMode': { 'values': [ { 'documentation': { 'description': ' The time offset from the start of segment and the duration over which the measurement is performed is uniform for all segments and is given by the RFMXSPECAN_ATTR_PAVT_MEASUREMENT_OFFSET attribute and the RFMXSPECAN_ATTR_PAVT_MEASUREMENT_LENGTH attribute respectively.' }, 'name': 'UNIFORM', 'value': 0 }, { 'documentation': { 'description': ' The time offset from the start of segment and the duration over which the measurement is performed is configured separately for each segment and is given by the RFMXSPECAN_ATTR_PAVT_SEGMENT_MEASUREMENT_OFFSET attribute and the RFMXSPECAN_ATTR_PAVT_SEGMENT_MEASUREMENT_LENGTH attribute respectively.' }, 'name': 'VARIABLE', 'value': 1 } ] }, 'PavtMeasurementLocationType': { 'values': [ { 'documentation': { 'description': ' The measurement is performed over a single record across multiple segments separated in time. The measurement locations of the segments are specified by the RFMXSPECAN_ATTR_PAVT_SEGMENT_START_TIME attribute. The number of segments is equal to the number of segment start times.' }, 'name': 'TIME', 'value': 0 }, { 'documentation': { 'description': ' The measurement is performed across segments obtained in multiple records, where each record is obtained when a trigger is received. The number of segments is equal to the number of triggers (records).' }, 'name': 'TRIGGER', 'value': 1 } ] }, 'PavtPhaseUnwrapEnabled': { 'values': [ { 'documentation': { 'description': ' Phase measurement results are wrapped within +/-180 degrees.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' Phase measurement results are unwrapped.' }, 'name': 'TRUE', 'value': 1 } ] }, 'PavtSegmentType': { 'values': [ { 'documentation': { 'description': ' Phase and amplitude is measured in this segment.' }, 'name': 'PHASE_AND_AMPLITUDE', 'value': 0 }, { 'documentation': { 'description': ' Amplitude is measured in this segment.' }, 'name': 'AMPLITUDE', 'value': 1 }, { 'documentation': { 'description': ' Frequency error is measured in this segment.' }, 'name': 'FREQUENCY_ERROR_MEASUREMENT', 'value': 2 } ] }, 'PhaseNoiseCancellationEnabled': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'PhaseNoiseFftWindow': { 'values': [ { 'name': 'NONE', 'value': 0 }, { 'name': 'FLAT_TOP', 'value': 1 }, { 'name': 'HANNING', 'value': 2 }, { 'name': 'HAMMING', 'value': 3 }, { 'name': 'GAUSSIAN', 'value': 4 }, { 'name': 'BLACKMAN', 'value': 5 }, { 'name': 'BLACKMAN_HARRIS', 'value': 6 }, { 'name': 'KAISER_BESSEL', 'value': 7 } ] }, 'PhaseNoiseIntegratedNoiseRangeDefinition': { 'values': [ { 'name': 'NONE', 'value': 0 }, { 'name': 'MEASUREMENT', 'value': 1 }, { 'name': 'CUSTOM', 'value': 2 } ] }, 'PhaseNoiseRangeDefinition': { 'values': [ { 'name': 'MANUAL', 'value': 0 }, { 'name': 'AUTO', 'value': 1 } ] }, 'PhaseNoiseSmoothingType': { 'values': [ { 'name': 'NONE', 'value': 0 }, { 'name': 'LINEAR', 'value': 1 }, { 'name': 'LOGARITHMIC', 'value': 2 }, { 'name': 'MEDIAN', 'value': 3 } ] }, 'PhaseNoiseSpurRemovalEnabled': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'RFAttenuationAuto': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'SemAmplitudeCorrectionType': { 'values': [ { 'documentation': { 'description': ' All the frequency bins in the spectrum are compensated with a single external attenuation value that corresponds to the RF center frequency.' }, 'name': 'RF_CENTER_FREQUENCY', 'value': 0 }, { 'documentation': { 'description': ' An individual frequency bin in the spectrum is compensated with the external attenuation value corresponding to that frequency.' }, 'name': 'SPECTRUM_FREQUENCY_BIN', 'value': 1 } ] }, 'SemAveragingEnabled': { 'values': [ { 'documentation': { 'description': ' The measurement is performed on a single acquisition.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' The SEM measurement uses the RFMXSPECAN_ATTR_SEM_AVERAGING_COUNT attribute as the number of acquisitions over which the SEM measurement is averaged.' }, 'name': 'TRUE', 'value': 1 } ] }, 'SemAveragingType': { 'values': [ { 'documentation': { 'description': ' The power spectrum is linearly averaged. RMS averaging reduces signal fluctuations but not the noise floor. ' }, 'name': 'RMS', 'value': 0 }, { 'documentation': { 'description': ' The power spectrum is averaged in a logarithmic scale.' }, 'name': 'LOG', 'value': 1 }, { 'documentation': { 'description': ' The square root of the power spectrum is averaged.' }, 'name': 'SCALAR', 'value': 2 }, { 'documentation': { 'description': ' The peak power in the spectrum at each frequency bin is retained from one acquisition to the next.' }, 'name': 'MAXIMUM', 'value': 3 }, { 'documentation': { 'description': ' The least power in the spectrum at each frequency bin is retained from one acquisition to the next. ' }, 'name': 'MINIMUM', 'value': 4 } ] }, 'SemCarrierEnabled': { 'values': [ { 'documentation': { 'description': ' The carrier power is not considered as part of the total carrier power.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' The carrier power is considered as part of the total carrier power.' }, 'name': 'TRUE', 'value': 1 } ] }, 'SemCarrierRbwAutoBandwidth': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'SemCarrierRbwFilterBandwidthDefinition': { 'values': [ { 'documentation': { 'description': ' Defines the RBW in terms of the 3 dB bandwidth of the RBW filter. When you set the RFMXSPECAN_ATTR_SEM_CARRIER_RBW_FILTER_TYPE attribute to RFMXSPECAN_VAL_SEM_CARRIER_RBW_FILTER_TYPE_FFT_BASED, RBW is the 3 dB bandwidth of the window specified by the RFMXSPECAN_ATTR_SEM_FFT_WINDOW attribute.' }, 'name': '3_DB', 'value': 0 }, { 'documentation': { 'description': ' Defines the RBW in terms of the spectrum bin width computed using an FFT when you set the RFMXSPECAN_ATTR_SEM_CARRIER_RBW_FILTER_TYPE attribute to FFT Based.' }, 'name': 'BIN_WIDTH', 'value': 2 } ] }, 'SemCarrierRbwFilterType': { 'values': [ { 'documentation': { 'description': ' No RBW filtering is performed.' }, 'name': 'FFT_BASED', 'value': 0 }, { 'documentation': { 'description': ' The RBW filter has a Gaussian response.' }, 'name': 'GAUSSIAN', 'value': 1 }, { 'documentation': { 'description': ' The RBW filter has a flat response.' }, 'name': 'FLAT', 'value': 2 } ] }, 'SemCarrierRrcFilterEnabled': { 'values': [ { 'documentation': { 'description': ' The channel power of the acquired carrier channel is measured directly.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' The measurement applies the RRC filter on the acquired carrier channel before measuring the carrier channel power.' }, 'name': 'TRUE', 'value': 1 } ] }, 'SemCompositeMeasurementStatus': { 'values': [ { 'name': 'FAIL', 'value': 0 }, { 'name': 'PASS', 'value': 1 } ] }, 'SemFftWindow': { 'values': [ { 'documentation': { 'description': ' Analyzes transients for which duration is shorter than the window length. You can also use this window type to separate two tones with frequencies close to each other but with almost equal amplitudes. ' }, 'name': 'NONE', 'value': 0 }, { 'documentation': { 'description': ' Measures single-tone amplitudes accurately.' }, 'name': 'FLAT_TOP', 'value': 1 }, { 'documentation': { 'description': ' Analyzes transients for which duration is longer than the window length. You can also use this window type to provide better frequency resolution for noise measurements.' }, 'name': 'HANNING', 'value': 2 }, { 'documentation': { 'description': ' Analyzes closely-spaced sine waves.' }, 'name': 'HAMMING', 'value': 3 }, { 'documentation': { 'description': ' Provides a good balance of spectral leakage, frequency resolution, and amplitude attenuation. Hence, this windowing is useful for time-frequency analysis.' }, 'name': 'GAUSSIAN', 'value': 4 }, { 'documentation': { 'description': ' Analyzes single tone because it has a low maximum side lobe level and a high side lobe roll-off rate. ' }, 'name': 'BLACKMAN', 'value': 5 }, { 'documentation': { 'description': ' Useful as a good general purpose window, having side lobe rejection greater than 90 dB and having a moderately wide main lobe. ' }, 'name': 'BLACKMAN_HARRIS', 'value': 6 }, { 'documentation': { 'description': ' Separates two tones with frequencies close to each other but with widely-differing amplitudes. ' }, 'name': 'KAISER_BESSEL', 'value': 7 } ] }, 'SemLowerOffsetMeasurementStatus': { 'values': [ { 'name': 'FAIL', 'value': 0 }, { 'name': 'PASS', 'value': 1 } ] }, 'SemOffsetAbsoluteLimitMode': { 'values': [ { 'documentation': { 'description': ' The line specified by the RFMXSPECAN_ATTR_SEM_OFFSET_ABSOLUTE_LIMIT_START and RFMXSPECAN_ATTR_SEM_OFFSET_ABSOLUTE_LIMIT_STOP attribute values as the two ends is considered as the mask.' }, 'name': 'MANUAL', 'value': 0 }, { 'documentation': { 'description': ' The two ends of the line are coupled to the value of the RFMXSPECAN_ATTR_SEM_OFFSET_ABSOLUTE_LIMIT_START attribute.' }, 'name': 'COUPLE', 'value': 1 } ] }, 'SemOffsetEnabled': { 'values': [ { 'documentation': { 'description': ' Disables the offset segment for the SEM measurement.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' Enables the offset segment for the SEM measurement.' }, 'name': 'TRUE', 'value': 1 } ] }, 'SemOffsetFrequencyDefinition': { 'values': [ { 'documentation': { 'description': ' The start frequency and stop frequency are defined from the center of the closest carrier channel bandwidth to the center of the offset segment measurement bandwidth.\n\nMeasurement Bandwidth = Resolution Bandwidth * Bandwidth Integral.' }, 'name': 'CARRIER_CENTER_TO_MEASUREMENT_BANDWIDTH_CENTER', 'value': 0 }, { 'documentation': { 'description': ' The start frequency and stop frequency are defined from the center of the closest carrier channel bandwidth to the nearest edge of the offset segment measurement bandwidth.' }, 'name': 'CARRIER_CENTER_TO_MEASUREMENT_BANDWIDTH_EDGE', 'value': 1 }, { 'documentation': { 'description': ' The start frequency and stop frequency are defined from the nearest edge of the closest carrier channel bandwidth to the center of the nearest offset segment measurement bandwidth.' }, 'name': 'CARRIER_EDGE_TO_MEASUREMENT_BANDWIDTH_CENTER', 'value': 2 }, { 'documentation': { 'description': ' The start frequency and stop frequency are defined from the nearest edge of the closest carrier channel bandwidth to the edge of the nearest offset segment measurement bandwidth.' }, 'name': 'CARRIER_EDGE_TO_MEASUREMENT_BANDWIDTH_EDGE', 'value': 3 } ] }, 'SemOffsetLimitFailMask': { 'values': [ { 'documentation': { 'description': ' The measurement fails if the power in the segment exceeds both the absolute and relative masks.' }, 'name': 'ABSOLUTE_AND_RELATIVE', 'value': 0 }, { 'documentation': { 'description': ' The measurement fails if the power in the segment exceeds either the absolute or relative mask.' }, 'name': 'ABSOLUTE_OR_RELATIVE', 'value': 1 }, { 'documentation': { 'description': ' The measurement fails if the power in the segment exceeds the absolute mask.' }, 'name': 'ABSOLUTE', 'value': 2 }, { 'documentation': { 'description': ' The measurement fails if the power in the segment exceeds the relative mask.' }, 'name': 'RELATIVE', 'value': 3 } ] }, 'SemOffsetRbwAutoBandwidth': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'SemOffsetRbwFilterBandwidthDefinition': { 'values': [ { 'documentation': { 'description': ' Defines the RBW in terms of the 3dB bandwidth of the RBW filter. When you set the RFMXSPECAN_ATTR_SEM_OFFSET_RBW_FILTER_TYPE attribute to RFMXSPECAN_VAL_SEM_RBW_FILTER_TYPE_FFT_BASED, RBW is the 3dB bandwidth of the window specified by the RFMXSPECAN_ATTR_SEM_FFT_WINDOW attribute.' }, 'name': '3_DB', 'value': 0 }, { 'documentation': { 'description': ' Defines the RBW in terms of the spectrum bin width computed using FFT when you set the RFMXSPECAN_ATTR_SEM_OFFSET_RBW_FILTER_TYPE attribute to FFT Based.' }, 'name': 'BIN_WIDTH', 'value': 2 } ] }, 'SemOffsetRbwFilterType': { 'values': [ { 'documentation': { 'description': ' No RBW filtering is performed.' }, 'name': 'FFT_BASED', 'value': 0 }, { 'documentation': { 'description': ' The RBW filter has a Gaussian response.' }, 'name': 'GAUSSIAN', 'value': 1 }, { 'documentation': { 'description': ' The RBW filter has a flat response.' }, 'name': 'FLAT', 'value': 2 } ] }, 'SemOffsetRelativeLimitMode': { 'values': [ { 'documentation': { 'description': ' The line specified by the RFMXSPECAN_ATTR_SEM_OFFSET_RELATIVE_LIMIT_START and RFMXSPECAN_ATTR_SEM_OFFSET_RELATIVE_LIMIT_STOP attribute values as the two ends is considered as the mask.' }, 'name': 'MANUAL', 'value': 0 }, { 'documentation': { 'description': ' The two ends of the line are coupled to the value of the RFMXSPECAN_ATTR_SEM_OFFSET_RELATIVE_LIMIT_START attribute.' }, 'name': 'COUPLE', 'value': 1 } ] }, 'SemOffsetSideband': { 'values': [ { 'documentation': { 'description': ' Configures a lower offset segment to the left of the leftmost carrier. ' }, 'name': 'NEGATIVE', 'value': 0 }, { 'documentation': { 'description': ' Configures an upper offset segment to the right of the rightmost carrier. ' }, 'name': 'POSITIVE', 'value': 1 }, { 'documentation': { 'description': ' Configures both negative and positive offset segments.' }, 'name': 'BOTH', 'value': 2 } ] }, 'SemPowerUnits': { 'values': [ { 'documentation': { 'description': ' The absolute powers are reported in dBm.' }, 'name': 'DBM', 'value': 0 }, { 'documentation': { 'description': ' The absolute powers are reported in dBm/Hz.' }, 'name': 'DBM_PER_HZ', 'value': 1 } ] }, 'SemReferenceType': { 'values': [ { 'documentation': { 'description': ' The power reference is the integrated power of the closest carrier.' }, 'name': 'INTEGRATION', 'value': 0 }, { 'documentation': { 'description': ' The power reference is the peak power of the closest carrier.' }, 'name': 'PEAK', 'value': 1 } ] }, 'SemSweepTimeAuto': { 'values': [ { 'documentation': { 'description': ' The measurement uses the sweep time that you specify in the RFMXSPECAN_ATTR_SEM_SWEEP_TIME_INTERVAL attribute.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' The measurement calculates the sweep time based on the value of the RFMXSPECAN_ATTR_SEM_OFFSET_RBW_FILTER_BANDWIDTH and RFMXSPECAN_ATTR_SEM_CARRIER_RBW_FILTER_BANDWIDTH attributes.' }, 'name': 'TRUE', 'value': 1 } ] }, 'SemUpperOffsetMeasurementStatus': { 'values': [ { 'name': 'FAIL', 'value': 0 }, { 'name': 'PASS', 'value': 1 } ] }, 'SpectrumAmplitudeCorrectionType': { 'values': [ { 'documentation': { 'description': ' All the frequency bins in the spectrum are compensated with a single external attenuation value that corresponds to the RF center frequency.' }, 'name': 'RF_CENTER_FREQUENCY', 'value': 0 }, { 'documentation': { 'description': ' An individual frequency bin in the spectrum is compensated with the external attenuation value corresponding to that frequency.' }, 'name': 'SPECTRUM_FREQUENCY_BIN', 'value': 1 } ] }, 'SpectrumAnalysisInput': { 'values': [ { 'documentation': { 'description': ' Measurement analyzes the acquired I+jQ data, resulting generally in a spectrum that is not symmetric around 0 Hz. Spectrum trace result contains both positive and negative frequencies. Since the RMS power of the complex envelope is 3.01 dB higher than that of its equivalent real RF signal, the spectrum trace result of the acquired I+jQ data is scaled by -3.01 dB. ' }, 'name': 'IQ', 'value': 0 }, { 'documentation': { 'description': ' Measurement ignores the Q data from the acquired I+jQ data and analyzes I+j0, resulting in a spectrum that is symmetric around 0 Hz. Spectrum trace result contains positive frequencies only. Spectrum of I+j0 data is scaled by +3.01 dB to account for the power of the negative frequencies that are not returned in the spectrum trace.' }, 'name': 'I_ONLY', 'value': 1 }, { 'documentation': { 'description': ' Measurement ignores the I data from the acquired I+jQ data and analyzes Q+j0, resulting in a spectrum that is symmetric around 0 Hz. Spectrum trace result contains positive frequencies only. Spectrum of Q+j0 data is scaled by +3.01 dB to account for the power of the negative frequencies that are not returned in the spectrum trace.' }, 'name': 'Q_ONLY', 'value': 2 } ] }, 'SpectrumAveragingEnabled': { 'values': [ { 'documentation': { 'description': ' The measurement is performed on a single acquisition.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' The spectrum measurement uses the RFMXSPECAN_ATTR_SPECTRUM_AVERAGING_COUNT attribute as the number of acquisitions over which the spectrum measurement is averaged.' }, 'name': 'TRUE', 'value': 1 } ] }, 'SpectrumAveragingType': { 'values': [ { 'documentation': { 'description': ' The power spectrum is linearly averaged. RMS averaging reduces signal fluctuations but not the noise floor. ' }, 'name': 'RMS', 'value': 0 }, { 'documentation': { 'description': ' The power spectrum is averaged in a logarithmic scale.' }, 'name': 'LOG', 'value': 1 }, { 'documentation': { 'description': ' The square root of the power spectrum is averaged.' }, 'name': 'SCALAR', 'value': 2 }, { 'documentation': { 'description': ' The peak power in the spectrum at each frequency bin is retained from one acquisition to the next.' }, 'name': 'MAXIMUM', 'value': 3 }, { 'documentation': { 'description': ' The least power in the spectrum at each frequency bin is retained from one acquisition to the next. ' }, 'name': 'MINIMUM', 'value': 4 } ] }, 'SpectrumDetectorType': { 'values': [ { 'documentation': { 'description': ' The detector is disabled.' }, 'name': 'NONE', 'value': 0 }, { 'documentation': { 'description': ' The middle sample in the bucket is detected.' }, 'name': 'SAMPLE', 'value': 1 }, { 'documentation': { 'description': ' The maximum value of the samples within the bucket is detected if the signal only rises or if the signal only falls. If the signal, within a bucket, both rises and falls, then the maximum and minimum values of the samples are detected in alternate buckets.' }, 'name': 'NORMAL', 'value': 2 }, { 'documentation': { 'description': ' The maximum value of the samples in the bucket is detected.' }, 'name': 'PEAK', 'value': 3 }, { 'documentation': { 'description': ' The minimum value of the samples in the bucket is detected.' }, 'name': 'NEGATIVE_PEAK', 'value': 4 }, { 'documentation': { 'description': ' The average RMS of all the samples in the bucket is detected.' }, 'name': 'AVERAGE_RMS', 'value': 5 }, { 'documentation': { 'description': ' The average voltage of all the samples in the bucket is detected. ' }, 'name': 'AVERAGE_VOLTAGE', 'value': 6 }, { 'documentation': { 'description': ' The average log of all the samples in the bucket is detected.' }, 'name': 'AVERAGE_LOG', 'value': 7 } ] }, 'SpectrumFftWindow': { 'values': [ { 'documentation': { 'description': ' Analyzes transients for which duration is shorter than the window length. You can also use this window type to separate two tones with frequencies close to each other but with almost equal amplitudes. ' }, 'name': 'NONE', 'value': 0 }, { 'documentation': { 'description': ' Measures single-tone amplitudes accurately.' }, 'name': 'FLAT_TOP', 'value': 1 }, { 'documentation': { 'description': ' Analyzes transients for which duration is longer than the window length. You can also use this window type to provide better frequency resolution for noise measurements.' }, 'name': 'HANNING', 'value': 2 }, { 'documentation': { 'description': ' Analyzes closely-spaced sine waves.' }, 'name': 'HAMMING', 'value': 3 }, { 'documentation': { 'description': ' Provides a good balance of spectral leakage, frequency resolution, and amplitude attenuation. Hence, this windowing is useful for time-frequency analysis.' }, 'name': 'GAUSSIAN', 'value': 4 }, { 'documentation': { 'description': ' Analyzes single tone because it has a low maximum side lobe level and a high side lobe roll-off rate. ' }, 'name': 'BLACKMAN', 'value': 5 }, { 'documentation': { 'description': ' Useful as a good general purpose window, having side lobe rejection greater than 90 dB and having a moderately wide main lobe. ' }, 'name': 'BLACKMAN_HARRIS', 'value': 6 }, { 'documentation': { 'description': ' Separates two tones with frequencies close to each other but with widely-differing amplitudes. ' }, 'name': 'KAISER_BESSEL', 'value': 7 } ] }, 'SpectrumMeasurementMode': { 'values': [ { 'documentation': { 'description': ' Spectrum measurement is performed on the acquired signal. ' }, 'name': 'MEASURE', 'value': 0 }, { 'documentation': { 'description': ' Manual noise calibration of the signal analyzer is performed for the spectrum measurement.' }, 'name': 'CALIBRATE_NOISE_FLOOR', 'value': 1 } ] }, 'SpectrumNoiseCalibrationAveragingAuto': { 'values': [ { 'documentation': { 'description': ' RFmx uses the averages that you set for the RFMXSPECAN_ATTR_SPECTRUM_NOISE_CALIBRATION_AVERAGING_COUNT attribute.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' RFmx uses a noise calibration averaging count of 32.' }, 'name': 'TRUE', 'value': 1 } ] }, 'SpectrumNoiseCalibrationDataValid': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'SpectrumNoiseCalibrationMode': { 'values': [ { 'documentation': { 'description': ' When you set the RFMXSPECAN_ATTR_SPECTRUM_MEASUREMENT_MODE attribute to RFMXSPECAN_VAL_SPECTRUM_MEASUREMENT_MODE_CALIBRATE_NOISE_FLOOR, you can initiate instrument noise calibration for the spectrum measurement manually. When you set the RFMXSPECAN_ATTR_SPECTRUM_MEASUREMENT_MODE attribute to RFMXSPECAN_VAL_SPECTRUM_MEASUREMENT_MODE_MEASURE, you can initiate the spectrum measurement manually.' }, 'name': 'MANUAL', 'value': 0 }, { 'documentation': { 'description': ' When you set the RFMXSPECAN_ATTR_SPECTRUM_NOISE_COMPENSATION_ENABLED attribute to RFMXSPECAN_VAL_SPECTRUM_NOISE_COMPENSATION_ENABLED_TRUE, RFmx sets the Input Isolation Enabled attribute to Enabled and calibrates the intrument noise in the current state of the instrument. RFmx then resets the Input Isolation Enabled attribute and performs the spectrum measurement, including compensation for noise from the instrument. RFmx skips noise calibration in this mode if valid noise calibration data is already cached. When you set the RFMXSPECAN_ATTR_SPECTRUM_NOISE_COMPENSATION_ENABLED attribute to RFMXSPECAN_VAL_SPECTRUM_NOISE_COMPENSATION_ENABLED_FALSE, RFmx does not calibrate instrument noise and performs only the spectrum measurement without compensating for the noise from the instrument.' }, 'name': 'AUTO', 'value': 1 } ] }, 'SpectrumNoiseCompensationEnabled': { 'values': [ { 'documentation': { 'description': ' Disables compensation of the spectrum for the noise floor of the signal analyzer.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' Enables compensation of the spectrum for the noise floor of the signal analyzer. The noise floor of the signal analyzer is measured for the RF path used by the Spectrum measurement and cached for future use. If signal analyzer or measurement parameters change, noise floors are measured again.' }, 'name': 'TRUE', 'value': 1 } ] }, 'SpectrumNoiseCompensationType': { 'values': [ { 'documentation': { 'description': ' Compensates for noise from the analyzer and the 50 ohm termination. The measured power values are in excess of the thermal noise floor.' }, 'name': 'ANALYZER_AND_TERMINATION', 'value': 0 }, { 'documentation': { 'description': ' Compensates for the analyzer noise only.' }, 'name': 'ANALYZER_ONLY', 'value': 1 } ] }, 'SpectrumPowerUnits': { 'values': [ { 'documentation': { 'description': ' The absolute powers are reported in dBm.' }, 'name': 'DBM', 'value': 0 }, { 'documentation': { 'description': ' The absolute powers are reported in dBm/Hz.' }, 'name': 'DBM_PER_HZ', 'value': 1 }, { 'documentation': { 'description': ' The absolute powers are reported in dBW.' }, 'name': 'DBW', 'value': 2 }, { 'documentation': { 'description': ' The absolute powers are reported in dBV.' }, 'name': 'DBV', 'value': 3 }, { 'documentation': { 'description': ' The absolute powers are reported in dBmV.' }, 'name': 'DBMV', 'value': 4 }, { 'documentation': { 'description': ' The absolute powers are reported in dBuV.' }, 'name': 'DBUV', 'value': 5 }, { 'documentation': { 'description': ' The absolute powers are reported in W.' }, 'name': 'WATTS', 'value': 6 }, { 'documentation': { 'description': ' The absolute powers are reported in volts.' }, 'name': 'VOLTS', 'value': 7 }, { 'documentation': { 'description': ' The absolute powers are reported in volts2.' }, 'name': 'VOLTS_SQUARED', 'value': 8 } ] }, 'SpectrumRbwAutoBandwidth': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'SpectrumRbwFilterBandwidthDefinition': { 'values': [ { 'documentation': { 'description': ' Defines the RBW in terms of the 3dB bandwidth of the RBW filter. When you set the RFMXSPECAN_ATTR_SPECTRUM_RBW_FILTER_TYPE attribute to RFMXSPECAN_VAL_SPECTRUM_RBW_FILTER_TYPE_FFT_BASED, RBW is the 3dB bandwidth of the window specified by the RFMXSPECAN_ATTR_SPECTRUM_FFT_WINDOW attribute.' }, 'name': '3_DB', 'value': 0 }, { 'documentation': { 'description': ' Defines the RBW in terms of the 6dB bandwidth of the RBW filter. When you set the RFMXSPECAN_ATTR_SPECTRUM_RBW_FILTER_TYPE attribute to FFT Based, RBW is the 6dB bandwidth of the window specified by the RFMXSPECAN_ATTR_SPECTRUM_FFT_WINDOW attribute.' }, 'name': '6_DB', 'value': 1 }, { 'documentation': { 'description': ' Defines the RBW in terms of the spectrum bin width computed using FFT when you set the RFMXSPECAN_ATTR_SPECTRUM_RBW_FILTER_TYPE attribute to FFT Based.' }, 'name': 'BIN_WIDTH', 'value': 2 }, { 'documentation': { 'description': ' Defines the RBW in terms of the ENBW bandwidth of the RBW filter. When you set the RFMXSPECAN_ATTR_SPECTRUM_RBW_FILTER_TYPE attribute to FFT Based, RBW is the ENBW bandwidth of the window specified by the RFMXSPECAN_ATTR_SPECTRUM_FFT_WINDOW attribute.' }, 'name': 'ENBW', 'value': 3 } ] }, 'SpectrumRbwFilterType': { 'values': [ { 'documentation': { 'description': ' No RBW filtering is performed.' }, 'name': 'FFT_BASED', 'value': 0 }, { 'documentation': { 'description': ' The RBW filter has a Gaussian response.' }, 'name': 'GAUSSIAN', 'value': 1 }, { 'documentation': { 'description': ' The RBW filter has a flat response.' }, 'name': 'FLAT', 'value': 2 } ] }, 'SpectrumSweepTimeAuto': { 'values': [ { 'documentation': { 'description': ' The measurement uses the sweep time that you specify in the RFMXSPECAN_ATTR_SPECTRUM_SWEEP_TIME_INTERVAL attribute. ' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' The measurement calculates the sweep time based on the value of the RFMXSPECAN_ATTR_SPECTRUM_RBW_FILTER_BANDWIDTH attribute.' }, 'name': 'TRUE', 'value': 1 } ] }, 'SpectrumVbwFilterAutoBandwidth': { 'values': [ { 'documentation': { 'description': ' Specify the video bandwidth in the RFMXSPECAN_ATTR_SPECTRUM_VBW_FILTER_BANDWIDTH attribute. The RFMXSPECAN_ATTR_SPECTRUM_VBW_FILTER_VBW_TO_RBW_RATIO attribute is disregarded in this mode.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' Specify video bandwidth in terms of the VBW to RBW ratio. The value of the video bandwidth is then computed by using the RFMXSPECAN_ATTR_SPECTRUM_VBW_FILTER_VBW_TO_RBW_RATIO attribute and the RFMXSPECAN_ATTR_SPECTRUM_RBW_FILTER_BANDWIDTH attribute. The value of the RFMXSPECAN_ATTR_SPECTRUM_VBW_FILTER_BANDWIDTH attribute is disregarded in this mode.' }, 'name': 'TRUE', 'value': 1 } ] }, 'SpurAbsoluteLimitMode': { 'values': [ { 'name': 'MANUAL', 'value': 0 }, { 'name': 'COUPLE', 'value': 1 } ] }, 'SpurAmplitudeCorrectionType': { 'values': [ { 'documentation': { 'description': ' All the frequency bins in the spectrum are compensated with a single external attenuation value that corresponds to the RF center frequency.' }, 'name': 'RF_CENTER_FREQUENCY', 'value': 0 }, { 'documentation': { 'description': ' An individual frequency bin in the spectrum is compensated with the external attenuation value corresponding to that frequency.' }, 'name': 'SPECTRUM_FREQUENCY_BIN', 'value': 1 } ] }, 'SpurAveragingEnabled': { 'values': [ { 'documentation': { 'description': ' The measurement is performed on a single acquisition.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' The Spur measurement uses the RFMXSPECAN_ATTR_SPUR_AVERAGING_COUNT attribute as the number of acquisitions over which the Spur measurement is averaged.' }, 'name': 'TRUE', 'value': 1 } ] }, 'SpurAveragingType': { 'values': [ { 'documentation': { 'description': ' The power spectrum is linearly averaged. RMS averaging reduces signal fluctuations but not the noise floor. ' }, 'name': 'RMS', 'value': 0 }, { 'documentation': { 'description': ' The power spectrum is averaged in a logarithmic scale.' }, 'name': 'LOG', 'value': 1 }, { 'documentation': { 'description': ' The square root of the power spectrum is averaged.' }, 'name': 'SCALAR', 'value': 2 }, { 'documentation': { 'description': ' The peak power in the spectrum at each frequency bin is retained from one acquisition to the next.' }, 'name': 'MAXIMUM', 'value': 3 }, { 'documentation': { 'description': ' The least power in the spectrum at each frequency bin is retained from one acquisition to the next. ' }, 'name': 'MINIMUM', 'value': 4 } ] }, 'SpurFftWindow': { 'values': [ { 'documentation': { 'description': ' Analyzes transients for which duration is shorter than the window length. You can also use this window type to separate two tones with frequencies close to each other but with almost equal amplitudes. ' }, 'name': 'NONE', 'value': 0 }, { 'documentation': { 'description': ' Measures single-tone amplitudes accurately.' }, 'name': 'FLAT_TOP', 'value': 1 }, { 'documentation': { 'description': ' Analyzes transients for which duration is longer than the window length. You can also use this window type to provide better frequency resolution for noise measurements.' }, 'name': 'HANNING', 'value': 2 }, { 'documentation': { 'description': ' Analyzes closely-spaced sine waves.' }, 'name': 'HAMMING', 'value': 3 }, { 'documentation': { 'description': ' Provides a balance of spectral leakage, frequency resolution, and amplitude attenuation. This windowing is useful for time-frequency analysis.' }, 'name': 'GAUSSIAN', 'value': 4 }, { 'documentation': { 'description': ' Analyzes single tone because it has a low maximum side lobe level and a high side lobe roll-off rate. ' }, 'name': 'BLACKMAN', 'value': 5 }, { 'documentation': { 'description': ' Useful as a good general purpose window, having side lobe rejection greater than 90 dB and having a moderately wide main lobe. ' }, 'name': 'BLACKMAN_HARRIS', 'value': 6 }, { 'documentation': { 'description': ' Separates two tones with frequencies close to each other but with widely-differing amplitudes.' }, 'name': 'KAISER_BESSEL', 'value': 7 } ] }, 'SpurMeasurementStatus': { 'values': [ { 'name': 'FAIL', 'value': 0 }, { 'name': 'PASS', 'value': 1 } ] }, 'SpurRangeDetectorType': { 'values': [ { 'documentation': { 'description': ' The detector is disabled.' }, 'name': 'NONE', 'value': 0 }, { 'documentation': { 'description': ' The middle sample in the bucket is detected.' }, 'name': 'SAMPLE', 'value': 1 }, { 'documentation': { 'description': ' The maximum value of the samples within the bucket is detected if the signal only rises or if the signal only falls. If the signal, within a bucket, both rises and falls, then the maximum and minimum values of the samples are detected in alternate buckets.' }, 'name': 'NORMAL', 'value': 2 }, { 'documentation': { 'description': ' The maximum value of the samples in the bucket is detected.' }, 'name': 'PEAK', 'value': 3 }, { 'documentation': { 'description': ' The minimum value of the samples in the bucket is detected.' }, 'name': 'NEGATIVE_PEAK', 'value': 4 }, { 'documentation': { 'description': ' The average RMS of all the samples in the bucket is detected.' }, 'name': 'AVERAGE_RMS', 'value': 5 }, { 'documentation': { 'description': ' The average voltage of all the samples in the bucket is detected. ' }, 'name': 'AVERAGE_VOLTAGE', 'value': 6 }, { 'documentation': { 'description': ' The average log of all the samples in the bucket is detected.' }, 'name': 'AVERAGE_LOG', 'value': 7 } ] }, 'SpurRangeEnabled': { 'values': [ { 'documentation': { 'description': ' Disables the acquisition of the frequency range.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' Enables measurement of Spurs in the frequency range.' }, 'name': 'TRUE', 'value': 1 } ] }, 'SpurRangeStatus': { 'values': [ { 'name': 'FAIL', 'value': 0 }, { 'name': 'PASS', 'value': 1 } ] }, 'SpurRangeVbwFilterAutoBandwidth': { 'values': [ { 'documentation': { 'description': ' Specify the video bandwidth in the RFMXSPECAN_ATTR_SPUR_RANGE_VBW_FILTER_BANDWIDTH attribute. The Spur VBW to RBW Ratio attribute is disregarded in this mode.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' Specify video bandwidth in terms of the VBW to RBW ratio. The value of the video bandwidth is then computed by using the RFMXSPECAN_ATTR_SPUR_RANGE_VBW_FILTER_VBW_TO_RBW_RATIO attribute and the RFMXSPECAN_ATTR_SPUR_RANGE_RBW_FILTER_BANDWIDTH attribute. The value of the RFMXSPECAN_ATTR_SPUR_RANGE_VBW_FILTER_BANDWIDTH attribute is disregarded in this mode.' }, 'name': 'TRUE', 'value': 1 } ] }, 'SpurRbwAutoBandwidth': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'SpurRbwFilterBandwidthDefinition': { 'values': [ { 'name': '3_DB', 'value': 0 }, { 'name': 'BIN_WIDTH', 'value': 2 }, { 'name': 'ENBW', 'value': 3 } ] }, 'SpurRbwFilterType': { 'values': [ { 'name': 'FFT_BASED', 'value': 0 }, { 'name': 'GAUSSIAN', 'value': 1 }, { 'name': 'FLAT', 'value': 2 } ] }, 'SpurSweepTimeAuto': { 'values': [ { 'name': 'FALSE', 'value': 0 }, { 'name': 'TRUE', 'value': 1 } ] }, 'TriggerMinimumQuietTimeMode': { 'values': [ { 'documentation': { 'description': ' The minimum quiet time for triggering is the value of the RFMXSPECAN_ATTR_TRIGGER_MINIMUM_QUIET_TIME_DURATION attribute. ' }, 'name': 'MANUAL', 'value': 0 }, { 'documentation': { 'description': ' The measurement computes the minimum quiet time used for triggering.' }, 'name': 'AUTO', 'value': 1 } ] }, 'TriggerType': { 'values': [ { 'documentation': { 'description': ' No Reference Trigger is configured.' }, 'name': 'NONE', 'value': 0 }, { 'documentation': { 'description': ' The Reference Trigger is not asserted until a digital edge is detected. The source of the digital edge is specified using the RFMXSPECAN_ATTR_DIGITAL_EDGE_TRIGGER_SOURCE attribute.' }, 'name': 'DIGITAL_EDGE', 'value': 1 }, { 'documentation': { 'description': ' The Reference Trigger is asserted when the signal changes past the level specified by the slope (rising or falling), which is configured using the RFMXSPECAN_ATTR_IQ_POWER_EDGE_TRIGGER_SLOPE attribute.' }, 'name': 'IQ_POWER_EDGE', 'value': 2 }, { 'documentation': { 'description': ' The Reference Trigger is not asserted until a software trigger occurs. ' }, 'name': 'SOFTWARE', 'value': 3 } ] }, 'TxpAveragingEnabled': { 'values': [ { 'documentation': { 'description': ' The measurement is performed on a single acquisition.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' The TXP measurement uses the RFMXSPECAN_ATTR_TXP_AVERAGING_COUNT attribute as the number of acquisitions over which the TXP measurement is averaged.' }, 'name': 'TRUE', 'value': 1 } ] }, 'TxpAveragingType': { 'values': [ { 'documentation': { 'description': ' The power trace is linearly averaged.' }, 'name': 'RMS', 'value': 0 }, { 'documentation': { 'description': ' The power trace is averaged in a logarithmic scale.' }, 'name': 'LOG', 'value': 1 }, { 'documentation': { 'description': ' The square root of the power trace is averaged.' }, 'name': 'SCALAR', 'value': 2 }, { 'documentation': { 'description': ' The maximum instantaneous power in the power trace is retained from one acquisition to the next.' }, 'name': 'MAXIMUM', 'value': 3 }, { 'documentation': { 'description': ' The minimum instantaneous power in the power trace is retained from one acquisition to the next.' }, 'name': 'MINIMUM', 'value': 4 } ] }, 'TxpRbwFilterType': { 'values': [ { 'documentation': { 'description': ' The RBW filter has a Gaussian response.' }, 'name': 'NONE', 'value': 1 }, { 'documentation': { 'description': ' The RBW filter has a flat response.' }, 'name': 'GAUSSIAN', 'value': 2 }, { 'documentation': { 'description': ' The measurement does not use any RBW filtering.' }, 'name': 'FLAT', 'value': 5 }, { 'documentation': { 'description': ' The RRC filter with the roll-off specified by the RFMXSPECAN_ATTR_TXP_RBW_FILTER_ALPHA attribute is used as the RBW filter.' }, 'name': 'RRC', 'value': 6 } ] }, 'TxpThresholdEnabled': { 'values': [ { 'documentation': { 'description': ' All the acquired samples are considered for the TXP measurement.' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' The samples above the threshold level specified in the RFMXSPECAN_ATTR_TXP_THRESHOLD_LEVEL attribute are considered for the TXP measurement.' }, 'name': 'TRUE', 'value': 1 } ] }, 'TxpThresholdType': { 'values': [ { 'documentation': { 'description': ' The threshold is relative to the peak power of the acquired samples.' }, 'name': 'RELATIVE', 'value': 0 }, { 'documentation': { 'description': ' The threshold is the absolute power, in dBm.' }, 'name': 'ABSOLUTE', 'value': 1 } ] }, 'TxpVbwFilterAutoBandwidth': { 'values': [ { 'documentation': { 'description': ' Specify the video bandwidth in the RFMXSPECAN_ATTR_TXP_VBW_FILTER_BANDWIDTH attribute. The RFMXSPECAN_ATTR_TXP_VBW_FILTER_VBW_TO_RBW_RATIO attribute is disregarded in this mode. ' }, 'name': 'FALSE', 'value': 0 }, { 'documentation': { 'description': ' Specify video bandwidth in terms of the VBW to RBW ratio. The value of the video bandwidth is then computed by using the RFMXSPECAN_ATTR_TXP_VBW_FILTER_VBW_TO_RBW_RATIO attribute and the RFMXSPECAN_ATTR_TXP_RBW_FILTER_BANDWIDTH attribute. The value of the RFMXSPECAN_ATTR_TXP_VBW_FILTER_BANDWIDTH attribute is disregarded in this mode.' }, 'name': 'TRUE', 'value': 1 } ] } }
enums = {'AcpAmplitudeCorrectionType': {'values': [{'documentation': {'description': ' All the frequency bins in the spectrum are compensated with a single external attenuation value that corresponds to the RF center frequency.'}, 'name': 'RF_CENTER_FREQUENCY', 'value': 0}, {'documentation': {'description': ' An individual frequency bin in the spectrum is compensated with the external attenuation value corresponding to that frequency.'}, 'name': 'SPECTRUM_FREQUENCY_BIN', 'value': 1}]}, 'AcpAveragingEnabled': {'values': [{'documentation': {'description': ' The measurement is performed on a single acquisition.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' The ACP measurement uses the RFMXSPECAN_ATTR_ACP_AVERAGING_COUNT attribute as the number of acquisitions over which the ACP measurement is averaged. '}, 'name': 'TRUE', 'value': 1}]}, 'AcpAveragingType': {'values': [{'documentation': {'description': ' The power spectrum is linearly averaged. RMS averaging reduces signal fluctuations but not the noise floor. '}, 'name': 'RMS', 'value': 0}, {'documentation': {'description': ' The power spectrum is averaged in a logarithmic scale.'}, 'name': 'LOG', 'value': 1}, {'documentation': {'description': ' The square root of the power spectrum is averaged.'}, 'name': 'SCALAR', 'value': 2}, {'documentation': {'description': ' The peak power in the spectrum at each frequency bin is retained from one acquisition to the next.'}, 'name': 'MAXIMUM', 'value': 3}, {'documentation': {'description': ' The least power in the spectrum at each frequency bin is retained from one acquisition to the next. '}, 'name': 'MINIMUM', 'value': 4}]}, 'AcpCarrierMode': {'values': [{'documentation': {'description': ' The carrier power is not considered as part of the total carrier power.'}, 'name': 'PASSIVE', 'value': 0}, {'documentation': {'description': ' The carrier power is considered as part of the total carrier power.'}, 'name': 'ACTIVE', 'value': 1}]}, 'AcpCarrierRrcFilterEnabled': {'values': [{'documentation': {'description': ' The channel power of the acquired carrier channel is measured directly.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' The measurement applies the RRC filter on the acquired carrier channel before measuring the carrier channel power.'}, 'name': 'TRUE', 'value': 1}]}, 'AcpFftOverlapMode': {'values': [{'documentation': {'description': ' Disables the overlap between the chunks.'}, 'name': 'DISABLED', 'value': 0}, {'documentation': {'description': ' Measurement sets the overlap based on the value you have set for the RFMXSPECAN_ATTR_ACP_FFT_WINDOW attribute. When you set the RFMXSPECAN_ATTR_ACP_FFT_WINDOW attribute to any value other than RFMXSPECAN_VAL_ACP_FFT_WINDOW_NONE, the number of overlapped samples between consecutive chunks is set to 50% of the value of the RFMXSPECAN_ATTR_ACP_SEQUENTIAL_FFT_SIZE attribute. When you set the RFMXSPECAN_ATTR_ACP_FFT_WINDOW attribute to RFMXSPECAN_VAL_ACP_FFT_WINDOW_NONE, the chunks are not overlapped and the overlap is set to 0%.'}, 'name': 'AUTOMATIC', 'value': 1}, {'documentation': {'description': ' Measurement uses the overlap that you specify in the RFMXSPECAN_ATTR_ACP_FFT_OVERLAP attribute.'}, 'name': 'USER_DEFINED', 'value': 2}]}, 'AcpFftWindow': {'values': [{'documentation': {'description': ' Analyzes transients for which duration is shorter than the window length. You can also use this window type to separate two tones with frequencies close to each other but with almost equal amplitudes.'}, 'name': 'NONE', 'value': 0}, {'documentation': {'description': ' Measures single-tone amplitudes accurately.'}, 'name': 'FLAT_TOP', 'value': 1}, {'documentation': {'description': ' Analyzes transients for which duration is longer than the window length. You can also use this window type to provide better frequency resolution for noise measurements.'}, 'name': 'HANNING', 'value': 2}, {'documentation': {'description': ' Analyzes closely-spaced sine waves.'}, 'name': 'HAMMING', 'value': 3}, {'documentation': {'description': ' Provides a good balance of spectral leakage, frequency resolution, and amplitude attenuation. Hence, this windowing is useful for time-frequency analysis.'}, 'name': 'GAUSSIAN', 'value': 4}, {'documentation': {'description': ' Analyzes single tone because it has a low maximum side lobe level and a high side lobe roll-off rate. '}, 'name': 'BLACKMAN', 'value': 5}, {'documentation': {'description': ' Useful as a good general purpose window, having side lobe rejection greater than 90 dB and having a moderately wide main lobe. '}, 'name': 'BLACKMAN_HARRIS', 'value': 6}, {'documentation': {'description': ' Separates two tones with frequencies close to each other but with widely-differing amplitudes.'}, 'name': 'KAISER_BESSEL', 'value': 7}]}, 'AcpIFOutputPowerOffsetAuto': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'AcpMeasurementMethod': {'values': [{'documentation': {'description': ' The ACP measurement acquires the spectrum using the same signal analyzer setting across frequency bands. Use this method when measurement speed is desirable over higher dynamic range. '}, 'name': 'NORMAL', 'value': 0}, {'documentation': {'description': ' The ACP measurement acquires the spectrum using the hardware-specific optimizations for different frequency bands. Use this method to get the best dynamic range.\n\n Supported devices: PXIe-5665/5668'}, 'name': 'DYNAMIC_RANGE', 'value': 1}, {'documentation': {'description': ' The ACP measurement acquires I/Q samples for a duration specified by the RFMXSPECAN_ATTR_ACP_SWEEP_TIME_INTERVAL attribute. These samples are divided into smaller chunks. The size of each chunk is defined by the RFMXSPECAN_ATTR_ACP_SEQUENTIAL_FFT_SIZE attribute. The overlap between the chunks is defined by the RFMXSPECAN_ATTR_ACP_FFT_OVERLAP_MODE attribute. FFT is computed on each of these chunks. The resultant FFTs are averaged to get the spectrum and is used to compute ACP. If the total acquired samples is not an integer multiple of the FFT size, the remaining samples at the end of acquisition are not used for the measurement. Use this method to optimize ACP measurement speed. Accuracy of the results may be reduced when using this measurement method.'}, 'name': 'SEQUENTIAL_FFT', 'value': 2}]}, 'AcpMeasurementMode': {'values': [{'documentation': {'description': ' ACP measurement is performed on the acquired signal. '}, 'name': 'MEASURE', 'value': 0}, {'documentation': {'description': ' Manual noise calibration of the signal analyzer is performed for the ACP measurement.'}, 'name': 'CALIBRATE_NOISE_FLOOR', 'value': 1}]}, 'AcpNoiseCalibrationAveragingAuto': {'values': [{'documentation': {'description': ' RFmx uses the averages that you set for the RFMXSPECAN_ATTR_ACP_NOISE_CALIBRATION_AVERAGING_COUNT attribute.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' When you set the RFMXSPECAN_ATTR_ACP_MEASUREMENT_METHOD attribute to RFMXSPECAN_VAL_ACP_MEASUREMENT_METHOD_NORMAL, RFmx uses a noise calibration averaging count of 32. When you set the RFMXSPECAN_ATTR_ACP_MEASUREMENT_METHOD attribute to RFMXSPECAN_VAL_ACP_MEASUREMENT_METHOD_DYNAMIC_RANGE and the sweep time is less than 5 ms, RFmx uses a noise calibration averaging count of 15. When you set the RFMXSPECAN_ATTR_ACP_MEASUREMENT_METHOD attribute to RFMXSPECAN_VAL_ACP_MEASUREMENT_METHOD_DYNAMIC_RANGE and the sweep time is greater than or equal to 5 ms, RFmx uses a noise calibration averaging count of 5.'}, 'name': 'TRUE', 'value': 1}]}, 'AcpNoiseCalibrationDataValid': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'AcpNoiseCalibrationMode': {'values': [{'documentation': {'description': ' When you set the RFMXSPECAN_ATTR_ACP_MEASUREMENT_MODE attribute to RFMXSPECAN_VAL_ACP_MEASUREMENT_MODE_CALIBRATE_NOISE_FLOOR, you can initiate instrument noise calibration for the ACP measurement manually. When you set the RFMXSPECAN_ATTR_ACP_MEASUREMENT_MODE attribute to RFMXSPECAN_VAL_ACP_MEASUREMENT_MODE_MEASURE, you can initiate the ACP measurement manually.'}, 'name': 'MANUAL', 'value': 0}, {'documentation': {'description': ' When you set the RFMXSPECAN_ATTR_ACP_NOISE_COMPENSATION_ENABLED to RFMXSPECAN_VAL_ACP_NOISE_COMPENSATION_ENABLED_TRUE, RFmx sets the Input Isolation Enabled attribute to Enabled and calibrates the instrument noise in the current state of the instrument. RFmx then resets the Input Isolation Enabled attribute and performs the ACP measurement, including compensation for noise of the instrument. RFmx skips noise calibration in this mode if valid noise calibration data is already cached. When you set the RFMXSPECAN_ATTR_ACP_NOISE_COMPENSATION_ENABLED attribute to RFMXSPECAN_VAL_ACP_NOISE_COMPENSATION_ENABLED_FALSE, RFmx does not calibrate instrument noise and only performs the ACP measurement without compensating for noise of the instrument.'}, 'name': 'AUTO', 'value': 1}]}, 'AcpNoiseCompensationEnabled': {'values': [{'documentation': {'description': ' Disables noise compensation.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' Enables noise compensation.'}, 'name': 'TRUE', 'value': 1}]}, 'AcpNoiseCompensationType': {'values': [{'documentation': {'description': ' Compensates for noise from the analyzer and the 50-ohm termination. The measured power values are in excess of the thermal noise floor.'}, 'name': 'ANALYZER_AND_TERMINATION', 'value': 0}, {'documentation': {'description': ' Compensates for the analyzer noise only.'}, 'name': 'ANALYZER_ONLY', 'value': 1}]}, 'AcpOffsetEnabled': {'values': [{'documentation': {'description': ' Disables the offset channel for ACP measurement.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' Enables the offset channel for ACP measurement.'}, 'name': 'TRUE', 'value': 1}]}, 'AcpOffsetFrequencyDefinition': {'values': [{'documentation': {'description': ' The offset frequency is defined from the center of the closest carrier to the center of the offset channel.'}, 'name': 'CARRIER_CENTER_TO_OFFSET_CENTER', 'value': 0}, {'documentation': {'description': ' The offset frequency is defined from the center of the closest carrier to the nearest edge of the offset channel.'}, 'name': 'CARRIER_CENTER_TO_OFFSET_EDGE', 'value': 1}]}, 'AcpOffsetPowerReferenceCarrier': {'values': [{'documentation': {'description': ' The measurement uses the power measured in the carrier closest to the offset channel center frequency, as the power reference.'}, 'name': 'CLOSEST', 'value': 0}, {'documentation': {'description': ' The measurement uses the highest power measured among all the active carriers as the power reference.'}, 'name': 'HIGHEST', 'value': 1}, {'documentation': {'description': ' The measurement uses the sum of powers measured in all the active carriers as the power reference.'}, 'name': 'COMPOSITE', 'value': 2}, {'documentation': {'description': ' The measurement uses the power measured in the carrier that has an index specified by the RFMXSPECAN_ATTR_ACP_OFFSET_POWER_REFERENCE_SPECIFIC attribute, as the power reference.'}, 'name': 'SPECIFIC', 'value': 3}]}, 'AcpOffsetRrcFilterEnabled': {'values': [{'documentation': {'description': ' The channel power of the acquired offset channel is measured directly.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' The measurement applies the RRC filter on the acquired offset channel before measuring the offset channel power.'}, 'name': 'TRUE', 'value': 1}]}, 'AcpOffsetSideband': {'values': [{'documentation': {'description': ' Configures a lower offset segment to the left of the leftmost carrier. '}, 'name': 'NEGATIVE', 'value': 0}, {'documentation': {'description': ' Configures an upper offset segment to the right of the rightmost carrier. '}, 'name': 'POSITIVE', 'value': 1}, {'documentation': {'description': ' Configures both negative and positive offset segments.'}, 'name': 'BOTH', 'value': 2}]}, 'AcpPowerUnits': {'values': [{'documentation': {'description': ' The absolute powers are reported in dBm.'}, 'name': 'DBM', 'value': 0}, {'documentation': {'description': ' The absolute powers are reported in dBm/Hz.'}, 'name': 'DBM_PER_HZ', 'value': 1}]}, 'AcpRbwAutoBandwidth': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'AcpRbwFilterBandwidthDefinition': {'values': [{'documentation': {'description': ' Defines the RBW in terms of the 3dB bandwidth of the RBW filter. When you set the RFMXSPECAN_ATTR_ACP_RBW_FILTER_TYPE attribute to RFMXSPECAN_VAL_ACP_RBW_FILTER_TYPE_FFT_BASED, RBW is the 3dB bandwidth of the window specified by the RFMXSPECAN_ATTR_ACP_FFT_WINDOW attribute.'}, 'name': '3_DB', 'value': 0}, {'documentation': {'description': ' Defines the RBW in terms of the bin width of the spectrum computed using FFT when you set the RFMXSPECAN_ATTR_ACP_RBW_FILTER_TYPE attribute to FFT Based.'}, 'name': 'BIN_WIDTH', 'value': 2}]}, 'AcpRbwFilterType': {'values': [{'documentation': {'description': ' No RBW filtering is performed.'}, 'name': 'FFT_BASED', 'value': 0}, {'documentation': {'description': ' An RBW filter with a Gaussian response is applied.'}, 'name': 'GAUSSIAN', 'value': 1}, {'documentation': {'description': ' An RBW filter with a flat response is applied.'}, 'name': 'FLAT', 'value': 2}]}, 'AcpSweepTimeAuto': {'values': [{'documentation': {'description': ' The measurement uses the sweep time that you specify in the RFMXSPECAN_ATTR_ACP_SWEEP_TIME_INTERVAL attribute.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' The measurement calculates the sweep time based on the value of the RFMXSPECAN_ATTR_ACP_RBW_FILTER_BANDWIDTH attribute.'}, 'name': 'TRUE', 'value': 1}]}, 'AmpmAMToAMCurveFitType': {'values': [{'name': 'LEAST_SQUARE', 'value': 0}, {'name': 'LEAST_ABSOLUTE_RESIDUAL', 'value': 1}, {'name': 'BISQUARE', 'value': 2}]}, 'AmpmAMToAMEnabled': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'AmpmAMToPMCurveFitType': {'values': [{'name': 'LEAST_SQUARE', 'value': 0}, {'name': 'LEAST_ABSOLUTE_RESIDUAL', 'value': 1}, {'name': 'BISQUARE', 'value': 2}]}, 'AmpmAMToPMEnabled': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'AmpmAutoCarrierDetectionEnabled': {'values': [{'documentation': {'description': ' Disables auto detection of carrier offset and carrier bandwidth.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' Enables auto detection of carrier offset and carrier bandwidth.'}, 'name': 'TRUE', 'value': 1}]}, 'AmpmAveragingEnabled': {'values': [{'documentation': {'description': ' The measurement is performed on a single acquisition.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' The AMPM measurement uses the RFMXSPECAN_ATTR_AMPM_AVERAGING_COUNT attribute as the number of acquisitions over which the signal for the AMPM measurement is averaged.'}, 'name': 'TRUE', 'value': 1}]}, 'AmpmCompressionPointEnabled': {'values': [{'documentation': {'description': ' Disables computation of compression points.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' Enables computation of compression points.'}, 'name': 'TRUE', 'value': 1}]}, 'AmpmCompressionPointGainReference': {'values': [{'documentation': {'description': ' Measurement computes the gain reference to be used for compression point calculation. The computed gain reference is also returned as RFMXSPECAN_ATTR_AMPM_RESULTS_MEAN_LINEAR_GAIN result.'}, 'name': 'AUTO', 'value': 0}, {'documentation': {'description': ' Measurement uses the gain corresponding to the reference power that you specify for the RFMXSPECAN_ATTR_AMPM_COMPRESSION_POINT_GAIN_REFERENCE_POWER attribute as gain reference. The reference power can be configured as either input or output power based on the value of the RFMXSPECAN_ATTR_AMPM_REFERENCE_POWER_TYPE attribute.'}, 'name': 'REFERENCE_POWER', 'value': 1}]}, 'AmpmEqualizerMode': {'values': [{'documentation': {'description': ' Equalization is not performed.'}, 'name': 'OFF', 'value': 0}, {'documentation': {'description': ' The equalizer is turned on to compensate for the effect of the channel.'}, 'name': 'TRAIN', 'value': 1}]}, 'AmpmEvmEnabled': {'values': [{'documentation': {'description': ' Disables EVM computation. NaN is returned as Mean RMS EVM.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' Enables EVM computation.'}, 'name': 'TRUE', 'value': 1}]}, 'AmpmFrequencyOffsetCorrectionEnabled': {'values': [{'documentation': {'description': ' The measurement does not perform frequency offset correction.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' The measurement computes and corrects any frequency offset between the reference and the acquired waveforms.'}, 'name': 'TRUE', 'value': 1}]}, 'AmpmIQOriginOffsetCorrectionEnabled': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'AmpmMeasurementSampleRateMode': {'values': [{'documentation': {'description': ' The acquisition sample rate is defined by the value of the RFMXSPECAN_ATTR_AMPM_MEASUREMENT_SAMPLE_RATE attribute.'}, 'name': 'USER', 'value': 0}, {'documentation': {'description': ' The acquisition sample rate is set to match the sample rate of the reference waveform.'}, 'name': 'REFERENCE_WAVEFORM', 'value': 1}]}, 'AmpmReferencePowerType': {'values': [{'documentation': {'description': ' The instantaneous powers at the input port of device under test (DUT) forms the x-axis of AM to AM and AM to PM traces.'}, 'name': 'INPUT', 'value': 0}, {'documentation': {'description': ' The instantaneous powers at the output port of DUT forms the x-axis of AM to AM and AM to PM traces.'}, 'name': 'OUTPUT', 'value': 1}]}, 'AmpmReferenceWaveformIdleDurationPresent': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'AmpmSignalType': {'values': [{'documentation': {'description': ' The reference waveform is a cellular or connectivity standard signal.'}, 'name': 'MODULATED', 'value': 0}, {'documentation': {'description': ' The reference waveform is a continuous signal comprising of one or more tones.'}, 'name': 'TONES', 'value': 1}]}, 'AmpmSynchronizationMethod': {'values': [{'documentation': {'description': ' Synchronizes the acquired and reference waveforms assuming that sample rate is sufficient to prevent aliasing in intermediate operations. This method is recommended when the measurement sampling rate is high.'}, 'name': 'DIRECT', 'value': 1}, {'documentation': {'description': ' Synchronizes the acquired and reference waveforms while ascertaining that intermediate operations are not impacted by aliasing. This method is recommended for non-contiguous carriers separated by a large gap, and/or when the measurement sampling rate is low. Refer to AMPM concept help for more information.'}, 'name': 'ALIAS_PROTECTED', 'value': 2}]}, 'AmpmThresholdEnabled': {'values': [{'documentation': {'description': ' All samples are considered for the AMPM measurement.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' Samples above the threshold level specified in the RFMXSPECAN_ATTR_AMPM_THRESHOLD_LEVEL attribute are considered for the AMPM measurement.'}, 'name': 'TRUE', 'value': 1}]}, 'AmpmThresholdType': {'values': [{'documentation': {'description': ' The threshold is relative to the peak power of the acquired samples.'}, 'name': 'RELATIVE', 'value': 0}, {'documentation': {'description': ' The threshold is the absolute power, in dBm.'}, 'name': 'ABSOLUTE', 'value': 1}]}, 'Boolean': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'CcdfRbwFilterType': {'values': [{'documentation': {'description': ' The measurement does not use any RBW filtering.'}, 'name': 'NONE', 'value': 5}, {'documentation': {'description': ' The RBW filter has a Gaussian response.'}, 'name': 'GAUSSIAN', 'value': 1}, {'documentation': {'description': ' The RBW filter has a flat response.'}, 'name': 'FLAT', 'value': 2}, {'documentation': {'description': ' The RRC filter with the roll-off specified by the RFMXSPECAN_ATTR_CCDF_RBW_FILTER_RRC_ALPHA attribute is used as the RBW filter.'}, 'name': 'RRC', 'value': 6}]}, 'CcdfThresholdEnabled': {'values': [{'documentation': {'description': ' All samples are considered for the CCDF measurement.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' The samples above the threshold level specified in the RFMXSPECAN_ATTR_CCDF_THRESHOLD_LEVEL attribute are considered for the CCDF measurement.'}, 'name': 'TRUE', 'value': 1}]}, 'CcdfThresholdType': {'values': [{'documentation': {'description': ' The threshold is relative to the peak power of the acquired samples.'}, 'name': 'RELATIVE', 'value': 0}, {'documentation': {'description': ' The threshold is the absolute power, in dBm.'}, 'name': 'ABSOLUTE', 'value': 1}]}, 'ChpAmplitudeCorrectionType': {'values': [{'documentation': {'description': ' All the frequency bins in the spectrum are compensated with a single external attenuation value that corresponds to the RF center frequency.'}, 'name': 'RF_CENTER_FREQUENCY', 'value': 0}, {'documentation': {'description': ' An individual frequency bin in the spectrum is compensated with the external attenuation value corresponding to that frequency.'}, 'name': 'SPECTRUM_FREQUENCY_BIN', 'value': 1}]}, 'ChpAveragingEnabled': {'values': [{'documentation': {'description': ' The measurement is performed on a single acquisition.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' The CHP measurement uses the RFMXSPECAN_ATTR_CHP_AVERAGING_COUNT attribute as the number of acquisitions over which the CHP measurement is averaged.'}, 'name': 'TRUE', 'value': 1}]}, 'ChpAveragingType': {'values': [{'documentation': {'description': ' The power spectrum is linearly averaged. RMS averaging reduces signal fluctuations but not the noise floor. '}, 'name': 'RMS', 'value': 0}, {'documentation': {'description': ' The power spectrum is averaged in a logarithmic scale.'}, 'name': 'LOG', 'value': 1}, {'documentation': {'description': ' The square root of the power spectrum is averaged.'}, 'name': 'SCALAR', 'value': 2}, {'documentation': {'description': ' The peak power in the spectrum at each frequency bin is retained from one acquisition to the next.'}, 'name': 'MAXIMUM', 'value': 3}, {'documentation': {'description': ' The least power in the spectrum at each frequency bin is retained from one acquisition to the next. '}, 'name': 'MINIMUM', 'value': 4}]}, 'ChpCarrierRrcFilterEnabled': {'values': [{'documentation': {'description': ' The channel power of the acquired channel is measured directly.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' The measurement applies the RRC filter on the acquired channel before measuring the channel power.'}, 'name': 'TRUE', 'value': 1}]}, 'ChpFftWindow': {'values': [{'documentation': {'description': ' Analyzes transients for which duration is shorter than the window length. You can also use this window type to separate two tones with frequencies close to each other but with almost equal amplitudes. '}, 'name': 'NONE', 'value': 0}, {'documentation': {'description': ' Measures single-tone amplitudes accurately.'}, 'name': 'FLAT_TOP', 'value': 1}, {'documentation': {'description': ' Analyzes transients for which duration is longer than the window length. You can also use this window type to provide better frequency resolution for noise measurements.'}, 'name': 'HANNING', 'value': 2}, {'documentation': {'description': ' Analyzes closely-spaced sine waves.'}, 'name': 'HAMMING', 'value': 3}, {'documentation': {'description': ' Provides a good balance of spectral leakage, frequency resolution, and amplitude attenuation. Hence, this windowing is useful for time-frequency analysis.'}, 'name': 'GAUSSIAN', 'value': 4}, {'documentation': {'description': ' Analyzes single tone because it has a low maximum side lobe level and a high side lobe roll-off rate. '}, 'name': 'BLACKMAN', 'value': 5}, {'documentation': {'description': ' Useful as a good general purpose window, having side lobe rejection greater than 90 dB and having a moderately wide main lobe. '}, 'name': 'BLACKMAN_HARRIS', 'value': 6}, {'documentation': {'description': ' Separates two tones with frequencies close to each other but with widely-differing amplitudes. '}, 'name': 'KAISER_BESSEL', 'value': 7}]}, 'ChpMeasurementMode': {'values': [{'documentation': {'description': ' CHP measurement is performed on the acquired signal.'}, 'name': 'MEASURE', 'value': 0}, {'documentation': {'description': ' Manual noise calibration of the signal analyzer is performed for the CHP measurement.'}, 'name': 'CALIBRATE_NOISE_FLOOR', 'value': 1}]}, 'ChpNoiseCalibrationAveragingAuto': {'values': [{'documentation': {'description': ' RFmx uses the averages that you set for the RFMXSPECAN_ATTR_CHP_NOISE_CALIBRATION_AVERAGING_COUNT attribute. '}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' RFmx uses a noise calibration averaging count of 32.'}, 'name': 'TRUE', 'value': 1}]}, 'ChpNoiseCalibrationDataValid': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'ChpNoiseCalibrationMode': {'values': [{'documentation': {'description': ' When you set the RFMXSPECAN_ATTR_CHP_MEASUREMENT_MODE attribute to RFMXSPECAN_VAL_CHP_MEASUREMENT_MODE_CALIBRATE_NOISE_FLOOR, you can initiate instrument noise calibration for the CHP measurement manually. When you set the RFMXSPECAN_ATTR_CHP_MEASUREMENT_MODE attribute to RFMXSPECAN_VAL_CHP_MEASUREMENT_MODE_MEASURE, you can initiate the CHP measurement manually.'}, 'name': 'MANUAL', 'value': 0}, {'documentation': {'description': ' When you set the RFMXSPECAN_ATTR_CHP_NOISE_COMPENSATION_ENABLED attribute to RFMXSPECAN_VAL_CHP_NOISE_COMPENSATION_ENABLED_TRUE, RFmx sets Input Isolation Enabled to Enabled and calibrates the intrument noise in the current state of the instrument. RFmx then resets the Input Isolation Enabled attribute and performs the CHP measurement, including compensation for noise of the instrument. RFmx skips noise calibration in this mode if valid noise calibration data is already cached. When you set the RFMXSPECAN_ATTR_CHP_NOISE_COMPENSATION_ENABLED attribute to RFMXSPECAN_VAL_CHP_NOISE_COMPENSATION_ENABLED_FALSE, RFmx does not calibrate instrument noise and performs only the CHP measurement without compensating for the noise contribution of the instrument.'}, 'name': 'AUTO', 'value': 1}]}, 'ChpNoiseCompensationEnabled': {'values': [{'documentation': {'description': ' Disables noise compensation.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' Enables noise compensation.'}, 'name': 'TRUE', 'value': 1}]}, 'ChpNoiseCompensationType': {'values': [{'documentation': {'description': ' Compensates for noise from the analyzer and the 50 ohm termination. The measured power values are in excess of the thermal noise floor.'}, 'name': 'ANALYZER_AND_TERMINATION', 'value': 0}, {'documentation': {'description': ' Compensates for the analyzer noise only.'}, 'name': 'ANALYZER_ONLY', 'value': 1}]}, 'ChpRbwAutoBandwidth': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'ChpRbwFilterBandwidthDefinition': {'values': [{'documentation': {'description': ' Defines the RBW in terms of the 3 dB bandwidth of the RBW filter. When you set the RFMXSPECAN_ATTR_CHP_RBW_FILTER_TYPE attribute to RFMXSPECAN_VAL_CHP_RBW_FILTER_TYPE_FFT_BASED, RBW is the 3 dB bandwidth of the window specified by the RFMXSPECAN_ATTR_CHP_FFT_WINDOW attribute.'}, 'name': '3_DB', 'value': 0}, {'documentation': {'description': ' Defines the RBW in terms of the spectrum bin width computed using an FFT when you set the RFMXSPECAN_ATTR_CHP_RBW_FILTER_TYPE attribute to FFT Based.'}, 'name': 'BIN_WIDTH', 'value': 2}]}, 'ChpRbwFilterType': {'values': [{'documentation': {'description': ' No RBW filtering is performed.'}, 'name': 'FFT_BASED', 'value': 0}, {'documentation': {'description': ' An RBW filter with a Gaussian response is applied.'}, 'name': 'GAUSSIAN', 'value': 1}, {'documentation': {'description': ' An RBW filter with a flat response is applied. '}, 'name': 'FLAT', 'value': 2}]}, 'ChpSweepTimeAuto': {'values': [{'documentation': {'description': ' The measurement uses the sweep time that you specify in the RFMXSPECAN_ATTR_CHP_SWEEP_TIME_INTERVAL attribute. '}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' The measurement calculates the sweep time based on the value of the RFMXSPECAN_ATTR_CHP_RBW_FILTER_BANDWIDTH attribute.'}, 'name': 'TRUE', 'value': 1}]}, 'DigitalEdgeTriggerEdge': {'values': [{'documentation': {'description': ' The trigger asserts on the rising edge of the signal.'}, 'name': 'RISING_EDGE', 'value': 0}, {'documentation': {'description': ' The trigger asserts on the falling edge of the signal.'}, 'name': 'FALLING_EDGE', 'value': 1}]}, 'DigitalEdgeTriggerSource': {'generate-mappings': True, 'values': [{'documentation': {'description': ' The trigger is received on PFI 0.'}, 'name': 'PFI0', 'value': 'PFI0'}, {'documentation': {'description': ' The trigger is received on PFI 1.'}, 'name': 'PFI1', 'value': 'PFI1'}, {'documentation': {'description': ' The trigger is received on PXI trigger line 0.'}, 'name': 'PXI_TRIG0', 'value': 'PXI_Trig0'}, {'documentation': {'description': ' The trigger is received on PXI trigger line 1.'}, 'name': 'PXI_TRIG1', 'value': 'PXI_Trig1'}, {'documentation': {'description': ' The trigger is received on PXI trigger line 2.'}, 'name': 'PXI_TRIG2', 'value': 'PXI_Trig2'}, {'documentation': {'description': ' The trigger is received on PXI trigger line 3.'}, 'name': 'PXI_TRIG3', 'value': 'PXI_Trig3'}, {'documentation': {'description': ' The trigger is received on PXI trigger line 4.'}, 'name': 'PXI_TRIG4', 'value': 'PXI_Trig4'}, {'documentation': {'description': ' The trigger is received on PXI trigger line 5.'}, 'name': 'PXI_TRIG5', 'value': 'PXI_Trig5'}, {'documentation': {'description': ' The trigger is received on PXI trigger line 6.'}, 'name': 'PXI_TRIG6', 'value': 'PXI_Trig6'}, {'documentation': {'description': ' The trigger is received on PXI trigger line 7.'}, 'name': 'PXI_TRIG7', 'value': 'PXI_Trig7'}, {'documentation': {'description': ' The trigger is received on the PXI star trigger line. '}, 'name': 'PXI_STAR', 'value': 'PXI_STAR'}, {'documentation': {'description': ' The trigger is received on the PXIe DStar B trigger line. '}, 'name': 'PXIE_DSTARB', 'value': 'PXIe_DStarB'}, {'documentation': {'description': ' The trigger is received from the timer event.'}, 'name': 'TIMER_EVENT', 'value': 'TimerEvent'}]}, 'DpdApplyDpdCfrEnabled': {'values': [{'documentation': {'description': ' Disables CFR. The maximum increase in PAPR, after pre-distortion, is limited to 6 dB.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' Enables CFR.'}, 'name': 'TRUE', 'value': 1}]}, 'DpdApplyDpdCfrMethod': {'values': [{'documentation': {'description': ' Hard clips the signal such that the target PAPR is achieved.'}, 'name': 'CLIPPING', 'value': 0}, {'documentation': {'description': ' Scales the peaks in the signal using weighted window function to get smooth peaks and achieve the target PAPR.'}, 'name': 'PEAK_WINDOWING', 'value': 1}, {'documentation': {'description': ' Scales the peaks using modified sigmoid transfer function to get smooth peaks and achieve the target PAPR. This method does not support the filter operation.'}, 'name': 'SIGMOID', 'value': 2}]}, 'DpdApplyDpdCfrTargetPaprType': {'values': [{'documentation': {'description': ' Sets the target PAPR for pre-distorted waveform equal to the PAPR of input waveform.'}, 'name': 'INPUT_PAPR', 'value': 0}, {'documentation': {'description': ' Sets the target PAPR equal to the value that you set for the Apply DPD CFR Target PAPR attribute.'}, 'name': 'CUSTOM', 'value': 1}]}, 'DpdApplyDpdCfrWindowType': {'values': [{'documentation': {'description': ' Uses the flat top window function to scale peaks.'}, 'name': 'FLAT_TOP', 'value': 1}, {'documentation': {'description': ' Uses the Hanning window function to scale peaks.'}, 'name': 'HANNING', 'value': 2}, {'documentation': {'description': ' Uses the Hamming window function to scale peaks.'}, 'name': 'HAMMING', 'value': 3}, {'documentation': {'description': ' Uses the Gaussian window function to scale peaks.'}, 'name': 'GAUSSIAN', 'value': 4}, {'documentation': {'description': ' Uses the Blackman window function to scale peaks.'}, 'name': 'BLACKMAN', 'value': 5}, {'documentation': {'description': ' Uses the Blackman-Harris window function to scale peaks.'}, 'name': 'BLACKMAN_HARRIS', 'value': 6}, {'documentation': {'description': ' Uses the Kaiser-Bessel window function to scale peaks.'}, 'name': 'KAISER_BESSEL', 'value': 7}]}, 'DpdApplyDpdConfigurationInput': {'values': [{'documentation': {'description': ' Uses the computed DPD polynomial or lookup table for applying DPD on an input waveform using the same RFmx session handle. The configuration parameters for applying DPD such as the RFMXSPECAN_ATTR_DPD_DUT_AVERAGE_INPUT_POWER, RFMXSPECAN_ATTR_DPD_MODEL, RFMXSPECAN_ATTR_DPD_MEASUREMENT_SAMPLE_RATE, DPD polynomial, and lookup table are obtained from the DPD measurement configuration. '}, 'name': 'MEASUREMENT', 'value': 0}, {'documentation': {'description': ' Applies DPD by using a computed DPD polynomial or lookup table on an input waveform. You must set the configuration parameters for applying DPD such as the RFMXSPECAN_ATTR_DPD_APPLY_DPD_USER_DUT_AVERAGE_INPUT_POWER, RFMXSPECAN_ATTR_DPD_APPLY_DPD_USER_DPD_MODEL, RFMXSPECAN_ATTR_DPD_APPLY_DPD_USER_MEASUREMENT_SAMPLE_RATE, DPD polynomial, and lookup table. '}, 'name': 'USER', 'value': 1}]}, 'DpdApplyDpdIdleDurationPresent': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'DpdApplyDpdLookupTableCorrectionType': {'values': [{'documentation': {'description': ' The measurement predistorts the magnitude and phase of the input waveform.'}, 'name': 'MAGNITUDE_AND_PHASE', 'value': 0}, {'documentation': {'description': ' The measurement predistorts only the magnitude of the input waveform.'}, 'name': 'MAGNITUDE_ONLY', 'value': 1}, {'documentation': {'description': ' The measurement predistorts only the phase of the input waveform.'}, 'name': 'PHASE_ONLY', 'value': 2}]}, 'DpdApplyDpdMemoryModelCorrectionType': {'values': [{'documentation': {'description': ' The measurement predistorts the magnitude and phase of the input waveform.'}, 'name': 'MAGNITUDE_AND_PHASE', 'value': 0}, {'documentation': {'description': ' The measurement predistorts only the magnitude of the input waveform.'}, 'name': 'MAGNITUDE_ONLY', 'value': 1}, {'documentation': {'description': ' The measurement predistorts only the phase of the input waveform.'}, 'name': 'PHASE_ONLY', 'value': 2}]}, 'DpdApplyDpdUserDpdModel': {'values': [{'documentation': {'description': ' This model computes the complex gain coefficients applied to linearize systems with negligible memory effects.'}, 'name': 'LOOKUP_TABLE', 'value': 0}, {'documentation': {'description': ' This model computes the memory polynomial predistortion coefficients used to linearize systems with moderate memory effects.'}, 'name': 'MEMORY_POLYNOMIAL', 'value': 1}, {'documentation': {'description': ' This model computes the generalized memory polynomial predistortion coefficients used to linearize systems with significant memory effects.'}, 'name': 'GENERALIZED_MEMORY_POLYNOMIAL', 'value': 2}]}, 'DpdApplyDpdUserLookupTableType': {'values': [{'documentation': {'description': ' Input powers in the LUT are specified in dBm.'}, 'name': 'LOG', 'value': 0}, {'documentation': {'description': ' Input powers in the LUT are specified in watts.'}, 'name': 'LINEAR', 'value': 1}]}, 'DpdAutoCarrierDetectionEnabled': {'values': [{'documentation': {'description': ' Disables auto detection of carrier offset and carrier bandwidth.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' Enables auto detection of carrier offset and carrier bandwidth.'}, 'name': 'TRUE', 'value': 1}]}, 'DpdAveragingEnabled': {'values': [{'documentation': {'description': ' The measurement is performed on a single acquisition.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' The DPD measurement uses the RFMXSPECAN_ATTR_DPD_AVERAGING_COUNT attribute as the number of acquisitions over which the signal for the DPD measurement is averaged. '}, 'name': 'TRUE', 'value': 1}]}, 'DpdFrequencyOffsetCorrectionEnabled': {'values': [{'documentation': {'description': ' The measurement computes and corrects any frequency offset between the reference and the acquired waveforms.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' The measurement does not perform frequency offset correction.'}, 'name': 'TRUE', 'value': 1}]}, 'DpdIQOriginOffsetCorrectionEnabled': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'DpdIterativeDpdEnabled': {'values': [{'documentation': {'description': ' RFmx computes the DPD Results DPD Polynomial without considering the value of the DPD Previous DPD Polynomial.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' RFmx computes the DPD Results DPD Polynomial based on the value of the DPD Previous DPD Polynomial.'}, 'name': 'TRUE', 'value': 1}]}, 'DpdLookupTableAMToAMCurveFitType': {'values': [{'name': 'LEAST_SQUARE', 'value': 0}, {'name': 'LEAST_ABSOLUTE_RESIDUAL', 'value': 1}, {'name': 'BISQUARE', 'value': 2}]}, 'DpdLookupTableAMToPMCurveFitType': {'values': [{'name': 'LEAST_SQUARE', 'value': 0}, {'name': 'LEAST_ABSOLUTE_RESIDUAL', 'value': 1}, {'name': 'BISQUARE', 'value': 2}]}, 'DpdLookupTableThresholdEnabled': {'values': [{'documentation': {'description': ' All samples are considered for the DPD measurement.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' Only samples above the threshold level which you specify in the RFMXSPECAN_ATTR_DPD_LOOKUP_TABLE_THRESHOLD_LEVEL attribute are considered for the DPD measurement.'}, 'name': 'TRUE', 'value': 1}]}, 'DpdLookupTableThresholdType': {'values': [{'documentation': {'description': ' The threshold is relative to the peak power of the acquired samples.'}, 'name': 'RELATIVE', 'value': 0}, {'documentation': {'description': ' The threshold is the absolute power, in dBm.'}, 'name': 'ABSOLUTE', 'value': 1}]}, 'DpdLookupTableType': {'values': [{'documentation': {'description': ' Input powers in the LUT are specified in dBm.'}, 'name': 'LOG', 'value': 0}, {'documentation': {'description': ' Input powers in the LUT are specified in watts.'}, 'name': 'LINEAR', 'value': 1}]}, 'DpdMeasurementSampleRateMode': {'values': [{'documentation': {'description': ' The acquisition sample rate is defined by the value of the RFMXSPECAN_ATTR_DPD_MEASUREMENT_SAMPLE_RATE attribute.'}, 'name': 'USER', 'value': 0}, {'documentation': {'description': ' The acquisition sample rate is set to match the sample rate of the reference waveform.'}, 'name': 'REFERENCE_WAVEFORM', 'value': 1}]}, 'DpdModel': {'values': [{'documentation': {'description': ' This model computes the complex gain coefficients applied when performing digital predistortion to linearize systems with negligible memory effects.'}, 'name': 'LOOKUP_TABLE', 'value': 0}, {'documentation': {'description': ' This model computes the memory polynomial predistortion coefficients used to linearize systems with moderate memory effects.'}, 'name': 'MEMORY_POLYNOMIAL', 'value': 1}, {'documentation': {'description': ' This model computes the generalized memory polynomial predistortion coefficients used to linearize systems with significant memory effects.'}, 'name': 'GENERALIZED_MEMORY_POLYNOMIAL', 'value': 2}]}, 'DpdNmseEnabled': {'values': [{'documentation': {'description': ' Disables NMSE computation. NaN is returned as NMSE.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' Enables NMSE computation.'}, 'name': 'TRUE', 'value': 1}]}, 'DpdPreDpdCfrEnabled': {'values': [{'documentation': {'description': ' Disables the CFR. The RFmxSpecAn_DPDApplyPreDPDSignalConditioning function returns an error when the CFR is disabled.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' Enables the CFR.'}, 'name': 'TRUE', 'value': 1}]}, 'DpdPreDpdCfrFilterEnabled': {'values': [{'documentation': {'description': ' Disables the filter operation when performing CFR.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' Enables filter operation when performing CFR. Filter operation is not supported when you set the RFMXSPECAN_ATTR_DPD_PRE_DPD_CFR_METHOD attribute to RFMXSPECAN_VAL_DPD_PRE_DPD_CFR_METHOD_SIGMOID.'}, 'name': 'TRUE', 'value': 1}]}, 'DpdPreDpdCfrMethod': {'values': [{'documentation': {'description': ' Hard clips the signal such that the target PAPR is achieved.'}, 'name': 'CLIPPING', 'value': 0}, {'documentation': {'description': ' Scales the peaks in the signal using weighted window function to get smooth peaks and achieve the target PAPR.'}, 'name': 'PEAK_WINDOWING', 'value': 1}, {'documentation': {'description': ' Scales the peaks using modified sigmoid transfer function to get smooth peaks and achieve the target PAPR. This method does not support the filter operation.'}, 'name': 'SIGMOID', 'value': 2}]}, 'DpdPreDpdCfrWindowType': {'values': [{'documentation': {'description': ' Uses the flat top window function to scale peaks.'}, 'name': 'FLAT_TOP', 'value': 1}, {'documentation': {'description': ' Uses the Hanning window function to scale peaks.'}, 'name': 'HANNING', 'value': 2}, {'documentation': {'description': ' Uses the Hamming window function to scale peaks.'}, 'name': 'HAMMING', 'value': 3}, {'documentation': {'description': ' Uses the Gaussian window function to scale peaks.'}, 'name': 'GAUSSIAN', 'value': 4}, {'documentation': {'description': ' Uses the Blackman window function to scale peaks.'}, 'name': 'BLACKMAN', 'value': 5}, {'documentation': {'description': ' Uses the Blackman-Harris window function to scale peaks.'}, 'name': 'BLACKMAN_HARRIS', 'value': 6}, {'documentation': {'description': ' Uses the Kaiser-Bessel window function to scale peaks.'}, 'name': 'KAISER_BESSEL', 'value': 7}]}, 'DpdReferenceWaveformIdleDurationPresent': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'DpdSignalType': {'values': [{'documentation': {'description': ' The reference waveform is a cellular or connectivity standard signal.'}, 'name': 'MODULATED', 'value': 0}, {'documentation': {'description': ' The reference waveform is a continuous signal comprising one or more tones.'}, 'name': 'TONES', 'value': 1}]}, 'DpdSynchronizationMethod': {'values': [{'documentation': {'description': ' Synchronizes the acquired and reference waveforms assuming that sample rate is sufficient to prevent aliasing in intermediate operations. This method is recommended when measurement sampling rate is high.'}, 'name': 'DIRECT', 'value': 1}, {'documentation': {'description': ' Synchronizes the acquired and reference waveforms while ascertaining that intermediate operations are not impacted by aliasing. This method is recommended for non-contiguous carriers separated by a large gap, and/or when measurement sampling rate is low. Refer to DPD concept help for more information.'}, 'name': 'ALIAS_PROTECTED', 'value': 2}]}, 'DpdTargetGainType': {'values': [{'documentation': {'description': ' The DPD polynomial or lookup table is computed by assuming that the linearized gain expected from the DUT after applying DPD on the input waveform is equal to the average power gain provided by the DUT without DPD.'}, 'name': 'AVERAGE_GAIN', 'value': 0}, {'documentation': {'description': ' The DPD polynomial or lookup table is computed by assuming that the linearized gain expected from the DUT after applying DPD on the input waveform is equal to the gain provided by the DUT, without DPD, to the parts of the reference waveform that do not drive the DUT into non-linear gain-expansion or compression regions of its input-output characteristics.\n\n The measurement computes the linear region gain as the average gain experienced by the parts of the reference waveform that are below a threshold which is computed as shown in the following equation:\n\n Linear region threshold (dBm) = Max {-25, Min {reference waveform power} + 6, DUT Average Input Power -15}'}, 'name': 'LINEAR_REGION_GAIN', 'value': 1}, {'documentation': {'description': ' The DPD polynomial or lookup table is computed by assuming that the linearized gain expected from the DUT after applying DPD on the input waveform is equal to the average power gain provided by the DUT, without DPD, to all the samples of the reference waveform for which the magnitude is greater than the peak power in the reference waveform (dBm) - 0.5dB.'}, 'name': 'PEAK_INPUT_POWER_GAIN', 'value': 2}]}, 'FcntAveragingEnabled': {'values': [{'documentation': {'description': ' The measurement is performed on a single acquisition.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' The FCnt measurement uses the RFMXSPECAN_ATTR_FCNT_AVERAGING_COUNT attribute as the number of acquisitions over which the FCnt measurement is averaged. '}, 'name': 'TRUE', 'value': 1}]}, 'FcntAveragingType': {'values': [{'documentation': {'description': ' The mean of the instantaneous signal phase difference over multiple acquisitions is used for the frequency measurement. '}, 'name': 'MEAN', 'value': 6}, {'documentation': {'description': ' The maximum instantaneous signal phase difference over multiple acquisitions is used for the frequency measurement. '}, 'name': 'MAXIMUM', 'value': 3}, {'documentation': {'description': ' The minimum instantaneous signal phase difference over multiple acquisitions is used for the frequency measurement. '}, 'name': 'MINIMUM', 'value': 4}, {'documentation': {'description': ' The maximum instantaneous signal phase difference over multiple acquisitions is used for the frequency measurement. The sign of the phase difference is ignored to find the maximum instantaneous value.'}, 'name': 'MINMAX', 'value': 7}]}, 'FcntRbwFilterType': {'values': [{'documentation': {'description': ' The measurement does not use any RBW filtering.'}, 'name': 'NONE', 'value': 5}, {'documentation': {'description': ' The RBW filter has a Gaussian response.'}, 'name': 'GAUSSIAN', 'value': 1}, {'documentation': {'description': ' The RBW filter has a flat response.'}, 'name': 'FLAT', 'value': 2}, {'documentation': {'description': ' The RRC filter with the roll-off specified by RFMXSPECAN_ATTR_FCNT_RBW_FILTER_RRC_ALPHA attribute is used as the RBW filter.'}, 'name': 'RRC', 'value': 6}]}, 'FcntThresholdEnabled': {'values': [{'documentation': {'description': ' All samples are considered for the FCnt measurement. '}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' The samples above the threshold level specified in the RFMXSPECAN_ATTR_FCNT_THRESHOLD_LEVEL attribute are considered for the FCnt measurement. '}, 'name': 'TRUE', 'value': 1}]}, 'FcntThresholdType': {'values': [{'documentation': {'description': ' The threshold is relative to the peak power of the acquired samples.'}, 'name': 'RELATIVE', 'value': 0}, {'documentation': {'description': ' The threshold is the absolute power, in dBm.'}, 'name': 'ABSOLUTE', 'value': 1}]}, 'FrequencyReferenceSource': {'generate-mappings': True, 'values': [{'name': 'ONBOARD_CLOCK', 'value': 'OnboardClock'}, {'name': 'REF_IN', 'value': 'RefIn'}, {'name': 'PXI_CLK', 'value': 'PXI_Clk'}, {'name': 'CLK_IN', 'value': 'ClkIn'}]}, 'HarmAutoHarmonicsSetupEnabled': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'HarmAveragingEnabled': {'values': [{'documentation': {'description': ' The measurement is performed on a single acquisition.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' The Harmonics measurement uses the RFMXSPECAN_ATTR_HARM_AVERAGING_COUNT attribute as the number of acquisitions over which the Harmonics measurement is averaged.'}, 'name': 'TRUE', 'value': 1}]}, 'HarmAveragingType': {'values': [{'documentation': {'description': ' The power trace is linearly averaged. RMS averaging reduces signal fluctuations but not the noise floor. '}, 'name': 'RMS', 'value': 0}, {'documentation': {'description': ' The power trace is averaged in a logarithmic scale.'}, 'name': 'LOG', 'value': 1}, {'documentation': {'description': ' The square root of the power trace is averaged.'}, 'name': 'SCALAR', 'value': 2}, {'documentation': {'description': ' The maximum instantaneous power in the power trace is retained from one acquisition to the next.'}, 'name': 'MAXIMUM', 'value': 3}, {'documentation': {'description': ' The minimum instantaneous power in the power trace is retained from one acquisition to the next.'}, 'name': 'MINIMUM', 'value': 4}]}, 'HarmHarmonicEnabled': {'values': [{'documentation': {'description': ' Disables the harmonic for measurement.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' Enables the harmonic for measurement.'}, 'name': 'TRUE', 'value': 1}]}, 'HarmMeasurementMethod': {'values': [{'documentation': {'description': ' The harmonics measurement acquires the signal using the same signal analyzer setting across frequency bands. Use this method when the measurement speed is desirable over higher dynamic range.\n\n Supported devices: PXIe-5644/5645/5646, PXIe-5663/5665/5668'}, 'name': 'TIME_DOMAIN', 'value': 0}, {'documentation': {'description': ' The harmonics measurement acquires the signal using the hardware-specific features, such as the IF filter and IF gain, for different frequency bands. Use this method to get the best dynamic range.\n\n Supported devices: PXIe-5665/5668'}, 'name': 'DYNAMIC_RANGE', 'value': 2}]}, 'HarmNoiseCompensationEnabled': {'values': [{'documentation': {'description': ' Disables compensation of the average harmonic powers for the noise floor of the signal analyzer.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' Enables compensation of the average harmonic powers for the noise floor of the signal analyzer. The noise floor of the signal analyzer is measured for the RF path used by the harmonics measurement and cached for future use. If the signal analyzer or measurement parameters change, noise floors are measured again.\n\n Supported devices: PXIe-5663/5665/5668'}, 'name': 'TRUE', 'value': 1}]}, 'HarmRbwFilterType': {'values': [{'name': 'GAUSSIAN', 'value': 1}, {'name': 'FLAT', 'value': 2}, {'name': 'NONE', 'value': 5}, {'name': 'RRC', 'value': 6}]}, 'IMAmplitudeCorrectionType': {'values': [{'name': 'RF_CENTER_FREQUENCY', 'value': 0}, {'name': 'SPECTRUM_FREQUENCY_BIN', 'value': 1}]}, 'IMAutoIntermodsSetupEnabled': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'IMAveragingEnabled': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'IMAveragingType': {'values': [{'name': 'RMS', 'value': 0}, {'name': 'LOG', 'value': 1}, {'name': 'SCALAR', 'value': 2}, {'name': 'MAXIMUM', 'value': 3}, {'name': 'MINIMUM', 'value': 4}]}, 'IMFftWindow': {'values': [{'name': 'NONE', 'value': 0}, {'name': 'FLAT_TOP', 'value': 1}, {'name': 'HANNING', 'value': 2}, {'name': 'HAMMING', 'value': 3}, {'name': 'GAUSSIAN', 'value': 4}, {'name': 'BLACKMAN', 'value': 5}, {'name': 'BLACKMAN_HARRIS', 'value': 6}, {'name': 'KAISER_BESSEL', 'value': 7}]}, 'IMFrequencyDefinition': {'values': [{'name': 'RELATIVE', 'value': 0}, {'name': 'ABSOLUTE', 'value': 1}]}, 'IMIFOutputPowerOffsetAuto': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'IMIntermodEnabled': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'IMIntermodSide': {'values': [{'name': 'LOWER', 'value': 0}, {'name': 'UPPER', 'value': 1}, {'name': 'BOTH', 'value': 2}]}, 'IMLocalPeakSearchEnabled': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'IMMeasurementMethod': {'values': [{'name': 'NORMAL', 'value': 0}, {'name': 'DYNAMIC_RANGE', 'value': 1}, {'name': 'SEGMENTED', 'value': 2}]}, 'IMRbwFilterAutoBandwidth': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'IMRbwFilterType': {'values': [{'name': 'FFT_BASED', 'value': 0}, {'name': 'GAUSSIAN', 'value': 1}, {'name': 'FLAT', 'value': 2}]}, 'IMSweepTimeAuto': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'IQBandwidthAuto': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'IQDeleteRecordOnFetch': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'IQPowerEdgeTriggerLevelType': {'values': [{'name': 'RELATIVE', 'value': 0}, {'name': 'ABSOLUTE', 'value': 1}]}, 'IQPowerEdgeTriggerSlope': {'values': [{'name': 'RISING_SLOPE', 'value': 0}, {'name': 'FALLING_SLOPE', 'value': 1}]}, 'LimitedConfigurationChange': {'values': [{'documentation': {'description': ' This is the normal mode of RFmx operation. All configuration changes in RFmxInstr attributes or in personality attributes will be applied during RFmx Commit.'}, 'name': 'DISABLED', 'value': 0}, {'documentation': {'description': ' Signal configuration and RFmxInstr configuration are locked after the first Commit or Initiate of the named signal configuration. Any configuration change thereafter either in RFmxInstr attributes or personality attributes will not be considered by subsequent RFmx Commits or Initiates of this signal. Use No Change if you have created named signal configurations for all measurement configurations but are setting some RFmxInstr attributes. Refer to the Limitations of the Limited Configuration Change Attribute topic for more details about the limitations of using this mode. '}, 'name': 'NO_CHANGE', 'value': 1}, {'documentation': {'description': ' Signal configuration, other than center frequency, external attenuation, and RFInstr configuration, is locked after first Commit or Initiate of the named signal configuration. Thereafter, only the Center Frequency and RFMXSPECAN_ATTR_EXTERNAL_ATTENUATION attribute value changes will be considered by subsequent driver Commits or Initiates of this signal. Refer to the Limitations of the Limited Configuration Change Attribute topic for more details about the limitations of using this mode. '}, 'name': 'FREQUENCY', 'value': 2}, {'documentation': {'description': ' Signal configuration, other than the reference level and RFInstr configuration, is locked after first Commit or Initiate of the named signal configuration. Thereafter only the RFMXSPECAN_ATTR_REFERENCE_LEVEL attribute value change will be considered by subsequent driver Commits or Initiates of this signal. If you have configured this signal to use an IQ Power Edge Trigger, NI recommends that you set the RFMXSPECAN_ATTR_IQ_POWER_EDGE_TRIGGER_LEVEL_TYPE to RFMXSPECAN_VAL_IQ_POWER_EDGE_TRIGGER_LEVEL_TYPE_RELATIVE so that the trigger level is automatically adjusted as you adjust the reference level. Refer to the Limitations of the Limited Configuration Change Attribute topic for more details about the limitations of using this mode. '}, 'name': 'REFERENCE_LEVEL', 'value': 3}, {'documentation': {'description': ' Signal configuration, other than center frequency, reference level, external attenuation, and RFInstr configuration, is locked after first Commit or Initiate of the named signal configuration. Thereafter only Center Frequency, RFMXSPECAN_ATTR_REFERENCE_LEVEL, and RFMXSPECAN_ATTR_EXTERNAL_ATTENUATION attribute value changes will be considered by subsequent driver Commits or Initiates of this signal. If you have configured this signal to use an IQ Power Edge Trigger, NI recommends you set the RFMXSPECAN_ATTR_IQ_POWER_EDGE_TRIGGER_LEVEL_TYPE to RFMXSPECAN_VAL_IQ_POWER_EDGE_TRIGGER_LEVEL_TYPE_RELATIVE so that the trigger level is automatically adjusted as you adjust the reference level. Refer to the Limitations of the Limited Configuration Change Attribute topic for more details about the limitations of using this mode. '}, 'name': 'FREQUENCY_AND_REFERENCE_LEVEL', 'value': 4}, {'documentation': {'description': ' Signal configuration, other than Selected Ports, Center frequency, Reference level, External attenuation, and RFInstr configuration, is locked after first Commit or Initiate of the named signal configuration. Thereafter only Selected Ports, Center Frequency, RFMXSPECAN_ATTR_REFERENCE_LEVEL, and RFMXSPECAN_ATTR_EXTERNAL_ATTENUATION attribute value changes will be considered by subsequent driver Commits or Initiates of this signal. If you have configured this signal to use an IQ Power Edge Trigger, NI recommends you set the RFMXSPECAN_ATTR_IQ_POWER_EDGE_TRIGGER_LEVEL_TYPE to RFMXSPECAN_VAL_IQ_POWER_EDGE_TRIGGER_LEVEL_TYPE_RELATIVE so that the trigger level is automatically adjusted as you adjust the reference level. Refer to the Limitations of the Limited Configuration Change Attribute topic for more details about the limitations of using this mode.'}, 'name': 'SELECTED_PORTS_FREQUENCY_AND_REFERENCE_LEVEL', 'value': 5}]}, 'MarkerNextPeak': {'values': [{'name': 'NEXT_HIGHEST', 'value': 0}, {'name': 'NEXT_LEFT', 'value': 1}, {'name': 'NEXT_RIGHT', 'value': 2}]}, 'MarkerPeakExcursionEnabled': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'MarkerThresholdEnabled': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'MarkerTrace': {'values': [{'name': 'ACP_SPECTRUM', 'value': 0}, {'name': 'CCDF_GAUSSIAN_PROBABILITIES_TRACE', 'value': 1}, {'name': 'CCDF_PROBABILITIES_TRACE', 'value': 2}, {'name': 'CHP_SPECTRUM', 'value': 3}, {'name': 'FCNT_POWER_TRACE', 'value': 4}, {'name': 'OBW_SPECTRUM', 'value': 5}, {'name': 'SEM_SPECTRUM', 'value': 6}, {'name': 'SPECTRUM', 'value': 7}, {'name': 'TXP_POWER_TRACE', 'value': 8}]}, 'MarkerType': {'values': [{'name': 'OFF', 'value': 0}, {'name': 'NORMAL', 'value': 1}, {'name': 'DELTA', 'value': 3}]}, 'MeasurementTypes': {'values': [{'name': 'ACP', 'value': 1}, {'name': 'CCDF', 'value': 2}, {'name': 'CHP', 'value': 4}, {'name': 'FCNT', 'value': 8}, {'name': 'HARMONICS', 'value': 16}, {'name': 'OBW', 'value': 32}, {'name': 'SEM', 'value': 64}, {'name': 'SPECTRUM', 'value': 128}, {'name': 'SPUR', 'value': 256}, {'name': 'TXP', 'value': 512}, {'name': 'AMPM', 'value': 1024}, {'name': 'DPD', 'value': 2048}, {'name': 'IQ', 'value': 4096}, {'name': 'IM', 'value': 8192}, {'name': 'NF', 'value': 16384}, {'name': 'PHASENOISE', 'value': 32768}, {'name': 'PAVT', 'value': 65536}]}, 'MechanicalAttenuationAuto': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'NFAveragingEnabled': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'NFCalibrationDataValid': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'NFCalibrationLossCompensationEnabled': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'NFColdSourceMode': {'values': [{'name': 'MEASURE', 'value': 0}, {'name': 'CALIBRATE', 'value': 1}]}, 'NFDutInputLossCompensationEnabled': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'NFDutOutputLossCompensationEnabled': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'NFDutType': {'values': [{'name': 'AMPLIFIER', 'value': 0}, {'name': 'DOWNCONVERTER', 'value': 1}, {'name': 'UPCONVERTER', 'value': 2}]}, 'NFExternalPreampPresent': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'NFFrequencyConverterFrequencyContext': {'values': [{'name': 'RF', 'value': 0}, {'name': 'IF', 'value': 1}]}, 'NFFrequencyConverterSideband': {'values': [{'name': 'LSB', 'value': 0}, {'name': 'USB', 'value': 1}]}, 'NFMeasurementMethod': {'values': [{'name': 'Y_FACTOR', 'value': 0}, {'name': 'COLD_SOURCE', 'value': 1}]}, 'NFYFactorMode': {'values': [{'name': 'MEASURE', 'value': 0}, {'name': 'CALIBRATE', 'value': 1}]}, 'NFYFactorNoiseSourceLossCompensationEnabled': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'ObwAmplitudeCorrectionType': {'values': [{'documentation': {'description': ' All the frequency bins in the spectrum are compensated with a single external attenuation value that corresponds to the RF center frequency.'}, 'name': 'RF_CENTER_FREQUENCY', 'value': 0}, {'documentation': {'description': ' An individual frequency bin in the spectrum is compensated with the external attenuation value corresponding to that frequency.'}, 'name': 'SPECTRUM_FREQUENCY_BIN', 'value': 1}]}, 'ObwAveragingEnabled': {'values': [{'documentation': {'description': ' The measurement is performed on a single acquisition.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' The OBW measurement uses the RFMXSPECAN_ATTR_OBW_AVERAGING_COUNT attribute as the number of acquisitions over which the OBW measurement is averaged.'}, 'name': 'TRUE', 'value': 1}]}, 'ObwAveragingType': {'values': [{'documentation': {'description': ' The power spectrum is linearly averaged. RMS averaging reduces signal fluctuations but not the noise floor. '}, 'name': 'RMS', 'value': 0}, {'documentation': {'description': ' The power spectrum is averaged in a logarithmic scale.'}, 'name': 'LOG', 'value': 1}, {'documentation': {'description': ' The square root of the power spectrum is averaged.'}, 'name': 'SCALAR', 'value': 2}, {'documentation': {'description': ' The peak power in the spectrum at each frequency bin is retained from one acquisition to the next.'}, 'name': 'MAXIMUM', 'value': 3}, {'documentation': {'description': ' The least power in the spectrum at each frequency bin is retained from one acquisition to the next. '}, 'name': 'MINIMUM', 'value': 4}]}, 'ObwFftWindow': {'values': [{'documentation': {'description': ' Analyzes transients for which duration is shorter than the window length. You can also use this window type to separate two tones with frequencies close to each other but with almost equal amplitudes. '}, 'name': 'NONE', 'value': 0}, {'documentation': {'description': ' Measures single-tone amplitudes accurately.'}, 'name': 'FLAT_TOP', 'value': 1}, {'documentation': {'description': ' Analyzes transients for which duration is longer than the window length. You can also use this window type to provide better frequency resolution for noise measurements.'}, 'name': 'HANNING', 'value': 2}, {'documentation': {'description': ' Analyzes closely-spaced sine waves.'}, 'name': 'HAMMING', 'value': 3}, {'documentation': {'description': ' Provides a good balance of spectral leakage, frequency resolution, and amplitude attenuation. Hence, this windowing is useful for time-frequency analysis.'}, 'name': 'GAUSSIAN', 'value': 4}, {'documentation': {'description': ' Analyzes single tone because it has a low maximum side lobe level and a high side lobe roll-off rate. '}, 'name': 'BLACKMAN', 'value': 5}, {'documentation': {'description': ' Useful as a good general purpose window, having side lobe rejection greater than 90 dB and having a moderately wide main lobe. '}, 'name': 'BLACKMAN_HARRIS', 'value': 6}, {'documentation': {'description': ' Separates two tones with frequencies close to each other but with widely-differing amplitudes. '}, 'name': 'KAISER_BESSEL', 'value': 7}]}, 'ObwPowerUnits': {'values': [{'documentation': {'description': ' The absolute powers are reported in dBm.'}, 'name': 'DBM', 'value': 0}, {'documentation': {'description': ' The absolute powers are reported in dBm/Hz.'}, 'name': 'DBM_PER_HZ', 'value': 1}]}, 'ObwRbwAutoBandwidth': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'ObwRbwFilterBandwidthDefinition': {'values': [{'documentation': {'description': ' Defines the RBW in terms of the 3 dB bandwidth of the RBW filter. When you set the RFMXSPECAN_ATTR_OBW_RBW_FILTER_TYPE attribute to RFMXSPECAN_VAL_OBW_RBW_FILTER_TYPE_FFT_BASED, RBW is the 3 dB bandwidth of the window specified by the RFMXSPECAN_ATTR_OBW_FFT_WINDOW attribute.'}, 'name': '3_DB', 'value': 0}, {'documentation': {'description': ' Defines the RBW in terms of the spectrum bin width computed using an FFT when you set the RFMXSPECAN_ATTR_OBW_RBW_FILTER_TYPE attribute to FFT Based.'}, 'name': 'BIN_WIDTH', 'value': 2}]}, 'ObwRbwFilterType': {'values': [{'documentation': {'description': ' No RBW filtering is performed.'}, 'name': 'FFT_BASED', 'value': 0}, {'documentation': {'description': ' The RBW filter has a Gaussian response.'}, 'name': 'GAUSSIAN', 'value': 1}, {'documentation': {'description': ' The RBW filter has a flat response.'}, 'name': 'FLAT', 'value': 2}]}, 'ObwSweepTimeAuto': {'values': [{'documentation': {'description': ' The measurement uses the sweep time that you specify in the RFMXSPECAN_ATTR_OBW_SWEEP_TIME_INTERVAL attribute. '}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' The measurement calculates the sweep time based on the value of the RFMXSPECAN_ATTR_OBW_RBW_FILTER_BANDWIDTH attribute.'}, 'name': 'TRUE', 'value': 1}]}, 'PavtFrequencyOffsetCorrectionEnabled': {'values': [{'documentation': {'description': ' Disables the frequency offset correction.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' Enables the frequency offset correction. The measurement computes and corrects any frequency offset between the reference and the acquired waveforms.'}, 'name': 'TRUE', 'value': 1}]}, 'PavtFrequencyTrackingEnabled': {'values': [{'documentation': {'description': ' Disables the drift correction for the measurement.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' Enables the drift correction. The measurement corrects and reports the frequency offset per segment.'}, 'name': 'TRUE', 'value': 1}]}, 'PavtMeasurementIntervalMode': {'values': [{'documentation': {'description': ' The time offset from the start of segment and the duration over which the measurement is performed is uniform for all segments and is given by the RFMXSPECAN_ATTR_PAVT_MEASUREMENT_OFFSET attribute and the RFMXSPECAN_ATTR_PAVT_MEASUREMENT_LENGTH attribute respectively.'}, 'name': 'UNIFORM', 'value': 0}, {'documentation': {'description': ' The time offset from the start of segment and the duration over which the measurement is performed is configured separately for each segment and is given by the RFMXSPECAN_ATTR_PAVT_SEGMENT_MEASUREMENT_OFFSET attribute and the RFMXSPECAN_ATTR_PAVT_SEGMENT_MEASUREMENT_LENGTH attribute respectively.'}, 'name': 'VARIABLE', 'value': 1}]}, 'PavtMeasurementLocationType': {'values': [{'documentation': {'description': ' The measurement is performed over a single record across multiple segments separated in time. The measurement locations of the segments are specified by the RFMXSPECAN_ATTR_PAVT_SEGMENT_START_TIME attribute. The number of segments is equal to the number of segment start times.'}, 'name': 'TIME', 'value': 0}, {'documentation': {'description': ' The measurement is performed across segments obtained in multiple records, where each record is obtained when a trigger is received. The number of segments is equal to the number of triggers (records).'}, 'name': 'TRIGGER', 'value': 1}]}, 'PavtPhaseUnwrapEnabled': {'values': [{'documentation': {'description': ' Phase measurement results are wrapped within +/-180 degrees.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' Phase measurement results are unwrapped.'}, 'name': 'TRUE', 'value': 1}]}, 'PavtSegmentType': {'values': [{'documentation': {'description': ' Phase and amplitude is measured in this segment.'}, 'name': 'PHASE_AND_AMPLITUDE', 'value': 0}, {'documentation': {'description': ' Amplitude is measured in this segment.'}, 'name': 'AMPLITUDE', 'value': 1}, {'documentation': {'description': ' Frequency error is measured in this segment.'}, 'name': 'FREQUENCY_ERROR_MEASUREMENT', 'value': 2}]}, 'PhaseNoiseCancellationEnabled': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'PhaseNoiseFftWindow': {'values': [{'name': 'NONE', 'value': 0}, {'name': 'FLAT_TOP', 'value': 1}, {'name': 'HANNING', 'value': 2}, {'name': 'HAMMING', 'value': 3}, {'name': 'GAUSSIAN', 'value': 4}, {'name': 'BLACKMAN', 'value': 5}, {'name': 'BLACKMAN_HARRIS', 'value': 6}, {'name': 'KAISER_BESSEL', 'value': 7}]}, 'PhaseNoiseIntegratedNoiseRangeDefinition': {'values': [{'name': 'NONE', 'value': 0}, {'name': 'MEASUREMENT', 'value': 1}, {'name': 'CUSTOM', 'value': 2}]}, 'PhaseNoiseRangeDefinition': {'values': [{'name': 'MANUAL', 'value': 0}, {'name': 'AUTO', 'value': 1}]}, 'PhaseNoiseSmoothingType': {'values': [{'name': 'NONE', 'value': 0}, {'name': 'LINEAR', 'value': 1}, {'name': 'LOGARITHMIC', 'value': 2}, {'name': 'MEDIAN', 'value': 3}]}, 'PhaseNoiseSpurRemovalEnabled': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'RFAttenuationAuto': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'SemAmplitudeCorrectionType': {'values': [{'documentation': {'description': ' All the frequency bins in the spectrum are compensated with a single external attenuation value that corresponds to the RF center frequency.'}, 'name': 'RF_CENTER_FREQUENCY', 'value': 0}, {'documentation': {'description': ' An individual frequency bin in the spectrum is compensated with the external attenuation value corresponding to that frequency.'}, 'name': 'SPECTRUM_FREQUENCY_BIN', 'value': 1}]}, 'SemAveragingEnabled': {'values': [{'documentation': {'description': ' The measurement is performed on a single acquisition.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' The SEM measurement uses the RFMXSPECAN_ATTR_SEM_AVERAGING_COUNT attribute as the number of acquisitions over which the SEM measurement is averaged.'}, 'name': 'TRUE', 'value': 1}]}, 'SemAveragingType': {'values': [{'documentation': {'description': ' The power spectrum is linearly averaged. RMS averaging reduces signal fluctuations but not the noise floor. '}, 'name': 'RMS', 'value': 0}, {'documentation': {'description': ' The power spectrum is averaged in a logarithmic scale.'}, 'name': 'LOG', 'value': 1}, {'documentation': {'description': ' The square root of the power spectrum is averaged.'}, 'name': 'SCALAR', 'value': 2}, {'documentation': {'description': ' The peak power in the spectrum at each frequency bin is retained from one acquisition to the next.'}, 'name': 'MAXIMUM', 'value': 3}, {'documentation': {'description': ' The least power in the spectrum at each frequency bin is retained from one acquisition to the next. '}, 'name': 'MINIMUM', 'value': 4}]}, 'SemCarrierEnabled': {'values': [{'documentation': {'description': ' The carrier power is not considered as part of the total carrier power.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' The carrier power is considered as part of the total carrier power.'}, 'name': 'TRUE', 'value': 1}]}, 'SemCarrierRbwAutoBandwidth': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'SemCarrierRbwFilterBandwidthDefinition': {'values': [{'documentation': {'description': ' Defines the RBW in terms of the 3 dB bandwidth of the RBW filter. When you set the RFMXSPECAN_ATTR_SEM_CARRIER_RBW_FILTER_TYPE attribute to RFMXSPECAN_VAL_SEM_CARRIER_RBW_FILTER_TYPE_FFT_BASED, RBW is the 3 dB bandwidth of the window specified by the RFMXSPECAN_ATTR_SEM_FFT_WINDOW attribute.'}, 'name': '3_DB', 'value': 0}, {'documentation': {'description': ' Defines the RBW in terms of the spectrum bin width computed using an FFT when you set the RFMXSPECAN_ATTR_SEM_CARRIER_RBW_FILTER_TYPE attribute to FFT Based.'}, 'name': 'BIN_WIDTH', 'value': 2}]}, 'SemCarrierRbwFilterType': {'values': [{'documentation': {'description': ' No RBW filtering is performed.'}, 'name': 'FFT_BASED', 'value': 0}, {'documentation': {'description': ' The RBW filter has a Gaussian response.'}, 'name': 'GAUSSIAN', 'value': 1}, {'documentation': {'description': ' The RBW filter has a flat response.'}, 'name': 'FLAT', 'value': 2}]}, 'SemCarrierRrcFilterEnabled': {'values': [{'documentation': {'description': ' The channel power of the acquired carrier channel is measured directly.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' The measurement applies the RRC filter on the acquired carrier channel before measuring the carrier channel power.'}, 'name': 'TRUE', 'value': 1}]}, 'SemCompositeMeasurementStatus': {'values': [{'name': 'FAIL', 'value': 0}, {'name': 'PASS', 'value': 1}]}, 'SemFftWindow': {'values': [{'documentation': {'description': ' Analyzes transients for which duration is shorter than the window length. You can also use this window type to separate two tones with frequencies close to each other but with almost equal amplitudes. '}, 'name': 'NONE', 'value': 0}, {'documentation': {'description': ' Measures single-tone amplitudes accurately.'}, 'name': 'FLAT_TOP', 'value': 1}, {'documentation': {'description': ' Analyzes transients for which duration is longer than the window length. You can also use this window type to provide better frequency resolution for noise measurements.'}, 'name': 'HANNING', 'value': 2}, {'documentation': {'description': ' Analyzes closely-spaced sine waves.'}, 'name': 'HAMMING', 'value': 3}, {'documentation': {'description': ' Provides a good balance of spectral leakage, frequency resolution, and amplitude attenuation. Hence, this windowing is useful for time-frequency analysis.'}, 'name': 'GAUSSIAN', 'value': 4}, {'documentation': {'description': ' Analyzes single tone because it has a low maximum side lobe level and a high side lobe roll-off rate. '}, 'name': 'BLACKMAN', 'value': 5}, {'documentation': {'description': ' Useful as a good general purpose window, having side lobe rejection greater than 90 dB and having a moderately wide main lobe. '}, 'name': 'BLACKMAN_HARRIS', 'value': 6}, {'documentation': {'description': ' Separates two tones with frequencies close to each other but with widely-differing amplitudes. '}, 'name': 'KAISER_BESSEL', 'value': 7}]}, 'SemLowerOffsetMeasurementStatus': {'values': [{'name': 'FAIL', 'value': 0}, {'name': 'PASS', 'value': 1}]}, 'SemOffsetAbsoluteLimitMode': {'values': [{'documentation': {'description': ' The line specified by the RFMXSPECAN_ATTR_SEM_OFFSET_ABSOLUTE_LIMIT_START and RFMXSPECAN_ATTR_SEM_OFFSET_ABSOLUTE_LIMIT_STOP attribute values as the two ends is considered as the mask.'}, 'name': 'MANUAL', 'value': 0}, {'documentation': {'description': ' The two ends of the line are coupled to the value of the RFMXSPECAN_ATTR_SEM_OFFSET_ABSOLUTE_LIMIT_START attribute.'}, 'name': 'COUPLE', 'value': 1}]}, 'SemOffsetEnabled': {'values': [{'documentation': {'description': ' Disables the offset segment for the SEM measurement.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' Enables the offset segment for the SEM measurement.'}, 'name': 'TRUE', 'value': 1}]}, 'SemOffsetFrequencyDefinition': {'values': [{'documentation': {'description': ' The start frequency and stop frequency are defined from the center of the closest carrier channel bandwidth to the center of the offset segment measurement bandwidth.\n\nMeasurement Bandwidth = Resolution Bandwidth * Bandwidth Integral.'}, 'name': 'CARRIER_CENTER_TO_MEASUREMENT_BANDWIDTH_CENTER', 'value': 0}, {'documentation': {'description': ' The start frequency and stop frequency are defined from the center of the closest carrier channel bandwidth to the nearest edge of the offset segment measurement bandwidth.'}, 'name': 'CARRIER_CENTER_TO_MEASUREMENT_BANDWIDTH_EDGE', 'value': 1}, {'documentation': {'description': ' The start frequency and stop frequency are defined from the nearest edge of the closest carrier channel bandwidth to the center of the nearest offset segment measurement bandwidth.'}, 'name': 'CARRIER_EDGE_TO_MEASUREMENT_BANDWIDTH_CENTER', 'value': 2}, {'documentation': {'description': ' The start frequency and stop frequency are defined from the nearest edge of the closest carrier channel bandwidth to the edge of the nearest offset segment measurement bandwidth.'}, 'name': 'CARRIER_EDGE_TO_MEASUREMENT_BANDWIDTH_EDGE', 'value': 3}]}, 'SemOffsetLimitFailMask': {'values': [{'documentation': {'description': ' The measurement fails if the power in the segment exceeds both the absolute and relative masks.'}, 'name': 'ABSOLUTE_AND_RELATIVE', 'value': 0}, {'documentation': {'description': ' The measurement fails if the power in the segment exceeds either the absolute or relative mask.'}, 'name': 'ABSOLUTE_OR_RELATIVE', 'value': 1}, {'documentation': {'description': ' The measurement fails if the power in the segment exceeds the absolute mask.'}, 'name': 'ABSOLUTE', 'value': 2}, {'documentation': {'description': ' The measurement fails if the power in the segment exceeds the relative mask.'}, 'name': 'RELATIVE', 'value': 3}]}, 'SemOffsetRbwAutoBandwidth': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'SemOffsetRbwFilterBandwidthDefinition': {'values': [{'documentation': {'description': ' Defines the RBW in terms of the 3dB bandwidth of the RBW filter. When you set the RFMXSPECAN_ATTR_SEM_OFFSET_RBW_FILTER_TYPE attribute to RFMXSPECAN_VAL_SEM_RBW_FILTER_TYPE_FFT_BASED, RBW is the 3dB bandwidth of the window specified by the RFMXSPECAN_ATTR_SEM_FFT_WINDOW attribute.'}, 'name': '3_DB', 'value': 0}, {'documentation': {'description': ' Defines the RBW in terms of the spectrum bin width computed using FFT when you set the RFMXSPECAN_ATTR_SEM_OFFSET_RBW_FILTER_TYPE attribute to FFT Based.'}, 'name': 'BIN_WIDTH', 'value': 2}]}, 'SemOffsetRbwFilterType': {'values': [{'documentation': {'description': ' No RBW filtering is performed.'}, 'name': 'FFT_BASED', 'value': 0}, {'documentation': {'description': ' The RBW filter has a Gaussian response.'}, 'name': 'GAUSSIAN', 'value': 1}, {'documentation': {'description': ' The RBW filter has a flat response.'}, 'name': 'FLAT', 'value': 2}]}, 'SemOffsetRelativeLimitMode': {'values': [{'documentation': {'description': ' The line specified by the RFMXSPECAN_ATTR_SEM_OFFSET_RELATIVE_LIMIT_START and RFMXSPECAN_ATTR_SEM_OFFSET_RELATIVE_LIMIT_STOP attribute values as the two ends is considered as the mask.'}, 'name': 'MANUAL', 'value': 0}, {'documentation': {'description': ' The two ends of the line are coupled to the value of the RFMXSPECAN_ATTR_SEM_OFFSET_RELATIVE_LIMIT_START attribute.'}, 'name': 'COUPLE', 'value': 1}]}, 'SemOffsetSideband': {'values': [{'documentation': {'description': ' Configures a lower offset segment to the left of the leftmost carrier. '}, 'name': 'NEGATIVE', 'value': 0}, {'documentation': {'description': ' Configures an upper offset segment to the right of the rightmost carrier. '}, 'name': 'POSITIVE', 'value': 1}, {'documentation': {'description': ' Configures both negative and positive offset segments.'}, 'name': 'BOTH', 'value': 2}]}, 'SemPowerUnits': {'values': [{'documentation': {'description': ' The absolute powers are reported in dBm.'}, 'name': 'DBM', 'value': 0}, {'documentation': {'description': ' The absolute powers are reported in dBm/Hz.'}, 'name': 'DBM_PER_HZ', 'value': 1}]}, 'SemReferenceType': {'values': [{'documentation': {'description': ' The power reference is the integrated power of the closest carrier.'}, 'name': 'INTEGRATION', 'value': 0}, {'documentation': {'description': ' The power reference is the peak power of the closest carrier.'}, 'name': 'PEAK', 'value': 1}]}, 'SemSweepTimeAuto': {'values': [{'documentation': {'description': ' The measurement uses the sweep time that you specify in the RFMXSPECAN_ATTR_SEM_SWEEP_TIME_INTERVAL attribute.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' The measurement calculates the sweep time based on the value of the RFMXSPECAN_ATTR_SEM_OFFSET_RBW_FILTER_BANDWIDTH and RFMXSPECAN_ATTR_SEM_CARRIER_RBW_FILTER_BANDWIDTH attributes.'}, 'name': 'TRUE', 'value': 1}]}, 'SemUpperOffsetMeasurementStatus': {'values': [{'name': 'FAIL', 'value': 0}, {'name': 'PASS', 'value': 1}]}, 'SpectrumAmplitudeCorrectionType': {'values': [{'documentation': {'description': ' All the frequency bins in the spectrum are compensated with a single external attenuation value that corresponds to the RF center frequency.'}, 'name': 'RF_CENTER_FREQUENCY', 'value': 0}, {'documentation': {'description': ' An individual frequency bin in the spectrum is compensated with the external attenuation value corresponding to that frequency.'}, 'name': 'SPECTRUM_FREQUENCY_BIN', 'value': 1}]}, 'SpectrumAnalysisInput': {'values': [{'documentation': {'description': ' Measurement analyzes the acquired I+jQ data, resulting generally in a spectrum that is not symmetric around 0 Hz. Spectrum trace result contains both positive and negative frequencies. Since the RMS power of the complex envelope is 3.01 dB higher than that of its equivalent real RF signal, the spectrum trace result of the acquired I+jQ data is scaled by -3.01 dB. '}, 'name': 'IQ', 'value': 0}, {'documentation': {'description': ' Measurement ignores the Q data from the acquired I+jQ data and analyzes I+j0, resulting in a spectrum that is symmetric around 0 Hz. Spectrum trace result contains positive frequencies only. Spectrum of I+j0 data is scaled by +3.01 dB to account for the power of the negative frequencies that are not returned in the spectrum trace.'}, 'name': 'I_ONLY', 'value': 1}, {'documentation': {'description': ' Measurement ignores the I data from the acquired I+jQ data and analyzes Q+j0, resulting in a spectrum that is symmetric around 0 Hz. Spectrum trace result contains positive frequencies only. Spectrum of Q+j0 data is scaled by +3.01 dB to account for the power of the negative frequencies that are not returned in the spectrum trace.'}, 'name': 'Q_ONLY', 'value': 2}]}, 'SpectrumAveragingEnabled': {'values': [{'documentation': {'description': ' The measurement is performed on a single acquisition.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' The spectrum measurement uses the RFMXSPECAN_ATTR_SPECTRUM_AVERAGING_COUNT attribute as the number of acquisitions over which the spectrum measurement is averaged.'}, 'name': 'TRUE', 'value': 1}]}, 'SpectrumAveragingType': {'values': [{'documentation': {'description': ' The power spectrum is linearly averaged. RMS averaging reduces signal fluctuations but not the noise floor. '}, 'name': 'RMS', 'value': 0}, {'documentation': {'description': ' The power spectrum is averaged in a logarithmic scale.'}, 'name': 'LOG', 'value': 1}, {'documentation': {'description': ' The square root of the power spectrum is averaged.'}, 'name': 'SCALAR', 'value': 2}, {'documentation': {'description': ' The peak power in the spectrum at each frequency bin is retained from one acquisition to the next.'}, 'name': 'MAXIMUM', 'value': 3}, {'documentation': {'description': ' The least power in the spectrum at each frequency bin is retained from one acquisition to the next. '}, 'name': 'MINIMUM', 'value': 4}]}, 'SpectrumDetectorType': {'values': [{'documentation': {'description': ' The detector is disabled.'}, 'name': 'NONE', 'value': 0}, {'documentation': {'description': ' The middle sample in the bucket is detected.'}, 'name': 'SAMPLE', 'value': 1}, {'documentation': {'description': ' The maximum value of the samples within the bucket is detected if the signal only rises or if the signal only falls. If the signal, within a bucket, both rises and falls, then the maximum and minimum values of the samples are detected in alternate buckets.'}, 'name': 'NORMAL', 'value': 2}, {'documentation': {'description': ' The maximum value of the samples in the bucket is detected.'}, 'name': 'PEAK', 'value': 3}, {'documentation': {'description': ' The minimum value of the samples in the bucket is detected.'}, 'name': 'NEGATIVE_PEAK', 'value': 4}, {'documentation': {'description': ' The average RMS of all the samples in the bucket is detected.'}, 'name': 'AVERAGE_RMS', 'value': 5}, {'documentation': {'description': ' The average voltage of all the samples in the bucket is detected. '}, 'name': 'AVERAGE_VOLTAGE', 'value': 6}, {'documentation': {'description': ' The average log of all the samples in the bucket is detected.'}, 'name': 'AVERAGE_LOG', 'value': 7}]}, 'SpectrumFftWindow': {'values': [{'documentation': {'description': ' Analyzes transients for which duration is shorter than the window length. You can also use this window type to separate two tones with frequencies close to each other but with almost equal amplitudes. '}, 'name': 'NONE', 'value': 0}, {'documentation': {'description': ' Measures single-tone amplitudes accurately.'}, 'name': 'FLAT_TOP', 'value': 1}, {'documentation': {'description': ' Analyzes transients for which duration is longer than the window length. You can also use this window type to provide better frequency resolution for noise measurements.'}, 'name': 'HANNING', 'value': 2}, {'documentation': {'description': ' Analyzes closely-spaced sine waves.'}, 'name': 'HAMMING', 'value': 3}, {'documentation': {'description': ' Provides a good balance of spectral leakage, frequency resolution, and amplitude attenuation. Hence, this windowing is useful for time-frequency analysis.'}, 'name': 'GAUSSIAN', 'value': 4}, {'documentation': {'description': ' Analyzes single tone because it has a low maximum side lobe level and a high side lobe roll-off rate. '}, 'name': 'BLACKMAN', 'value': 5}, {'documentation': {'description': ' Useful as a good general purpose window, having side lobe rejection greater than 90 dB and having a moderately wide main lobe. '}, 'name': 'BLACKMAN_HARRIS', 'value': 6}, {'documentation': {'description': ' Separates two tones with frequencies close to each other but with widely-differing amplitudes. '}, 'name': 'KAISER_BESSEL', 'value': 7}]}, 'SpectrumMeasurementMode': {'values': [{'documentation': {'description': ' Spectrum measurement is performed on the acquired signal. '}, 'name': 'MEASURE', 'value': 0}, {'documentation': {'description': ' Manual noise calibration of the signal analyzer is performed for the spectrum measurement.'}, 'name': 'CALIBRATE_NOISE_FLOOR', 'value': 1}]}, 'SpectrumNoiseCalibrationAveragingAuto': {'values': [{'documentation': {'description': ' RFmx uses the averages that you set for the RFMXSPECAN_ATTR_SPECTRUM_NOISE_CALIBRATION_AVERAGING_COUNT attribute.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' RFmx uses a noise calibration averaging count of 32.'}, 'name': 'TRUE', 'value': 1}]}, 'SpectrumNoiseCalibrationDataValid': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'SpectrumNoiseCalibrationMode': {'values': [{'documentation': {'description': ' When you set the RFMXSPECAN_ATTR_SPECTRUM_MEASUREMENT_MODE attribute to RFMXSPECAN_VAL_SPECTRUM_MEASUREMENT_MODE_CALIBRATE_NOISE_FLOOR, you can initiate instrument noise calibration for the spectrum measurement manually. When you set the RFMXSPECAN_ATTR_SPECTRUM_MEASUREMENT_MODE attribute to RFMXSPECAN_VAL_SPECTRUM_MEASUREMENT_MODE_MEASURE, you can initiate the spectrum measurement manually.'}, 'name': 'MANUAL', 'value': 0}, {'documentation': {'description': ' When you set the RFMXSPECAN_ATTR_SPECTRUM_NOISE_COMPENSATION_ENABLED attribute to RFMXSPECAN_VAL_SPECTRUM_NOISE_COMPENSATION_ENABLED_TRUE, RFmx sets the Input Isolation Enabled attribute to Enabled and calibrates the intrument noise in the current state of the instrument. RFmx then resets the Input Isolation Enabled attribute and performs the spectrum measurement, including compensation for noise from the instrument. RFmx skips noise calibration in this mode if valid noise calibration data is already cached. When you set the RFMXSPECAN_ATTR_SPECTRUM_NOISE_COMPENSATION_ENABLED attribute to RFMXSPECAN_VAL_SPECTRUM_NOISE_COMPENSATION_ENABLED_FALSE, RFmx does not calibrate instrument noise and performs only the spectrum measurement without compensating for the noise from the instrument.'}, 'name': 'AUTO', 'value': 1}]}, 'SpectrumNoiseCompensationEnabled': {'values': [{'documentation': {'description': ' Disables compensation of the spectrum for the noise floor of the signal analyzer.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' Enables compensation of the spectrum for the noise floor of the signal analyzer. The noise floor of the signal analyzer is measured for the RF path used by the Spectrum measurement and cached for future use. If signal analyzer or measurement parameters change, noise floors are measured again.'}, 'name': 'TRUE', 'value': 1}]}, 'SpectrumNoiseCompensationType': {'values': [{'documentation': {'description': ' Compensates for noise from the analyzer and the 50 ohm termination. The measured power values are in excess of the thermal noise floor.'}, 'name': 'ANALYZER_AND_TERMINATION', 'value': 0}, {'documentation': {'description': ' Compensates for the analyzer noise only.'}, 'name': 'ANALYZER_ONLY', 'value': 1}]}, 'SpectrumPowerUnits': {'values': [{'documentation': {'description': ' The absolute powers are reported in dBm.'}, 'name': 'DBM', 'value': 0}, {'documentation': {'description': ' The absolute powers are reported in dBm/Hz.'}, 'name': 'DBM_PER_HZ', 'value': 1}, {'documentation': {'description': ' The absolute powers are reported in dBW.'}, 'name': 'DBW', 'value': 2}, {'documentation': {'description': ' The absolute powers are reported in dBV.'}, 'name': 'DBV', 'value': 3}, {'documentation': {'description': ' The absolute powers are reported in dBmV.'}, 'name': 'DBMV', 'value': 4}, {'documentation': {'description': ' The absolute powers are reported in dBuV.'}, 'name': 'DBUV', 'value': 5}, {'documentation': {'description': ' The absolute powers are reported in W.'}, 'name': 'WATTS', 'value': 6}, {'documentation': {'description': ' The absolute powers are reported in volts.'}, 'name': 'VOLTS', 'value': 7}, {'documentation': {'description': ' The absolute powers are reported in volts2.'}, 'name': 'VOLTS_SQUARED', 'value': 8}]}, 'SpectrumRbwAutoBandwidth': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'SpectrumRbwFilterBandwidthDefinition': {'values': [{'documentation': {'description': ' Defines the RBW in terms of the 3dB bandwidth of the RBW filter. When you set the RFMXSPECAN_ATTR_SPECTRUM_RBW_FILTER_TYPE attribute to RFMXSPECAN_VAL_SPECTRUM_RBW_FILTER_TYPE_FFT_BASED, RBW is the 3dB bandwidth of the window specified by the RFMXSPECAN_ATTR_SPECTRUM_FFT_WINDOW attribute.'}, 'name': '3_DB', 'value': 0}, {'documentation': {'description': ' Defines the RBW in terms of the 6dB bandwidth of the RBW filter. When you set the RFMXSPECAN_ATTR_SPECTRUM_RBW_FILTER_TYPE attribute to FFT Based, RBW is the 6dB bandwidth of the window specified by the RFMXSPECAN_ATTR_SPECTRUM_FFT_WINDOW attribute.'}, 'name': '6_DB', 'value': 1}, {'documentation': {'description': ' Defines the RBW in terms of the spectrum bin width computed using FFT when you set the RFMXSPECAN_ATTR_SPECTRUM_RBW_FILTER_TYPE attribute to FFT Based.'}, 'name': 'BIN_WIDTH', 'value': 2}, {'documentation': {'description': ' Defines the RBW in terms of the ENBW bandwidth of the RBW filter. When you set the RFMXSPECAN_ATTR_SPECTRUM_RBW_FILTER_TYPE attribute to FFT Based, RBW is the ENBW bandwidth of the window specified by the RFMXSPECAN_ATTR_SPECTRUM_FFT_WINDOW attribute.'}, 'name': 'ENBW', 'value': 3}]}, 'SpectrumRbwFilterType': {'values': [{'documentation': {'description': ' No RBW filtering is performed.'}, 'name': 'FFT_BASED', 'value': 0}, {'documentation': {'description': ' The RBW filter has a Gaussian response.'}, 'name': 'GAUSSIAN', 'value': 1}, {'documentation': {'description': ' The RBW filter has a flat response.'}, 'name': 'FLAT', 'value': 2}]}, 'SpectrumSweepTimeAuto': {'values': [{'documentation': {'description': ' The measurement uses the sweep time that you specify in the RFMXSPECAN_ATTR_SPECTRUM_SWEEP_TIME_INTERVAL attribute. '}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' The measurement calculates the sweep time based on the value of the RFMXSPECAN_ATTR_SPECTRUM_RBW_FILTER_BANDWIDTH attribute.'}, 'name': 'TRUE', 'value': 1}]}, 'SpectrumVbwFilterAutoBandwidth': {'values': [{'documentation': {'description': ' Specify the video bandwidth in the RFMXSPECAN_ATTR_SPECTRUM_VBW_FILTER_BANDWIDTH attribute. The RFMXSPECAN_ATTR_SPECTRUM_VBW_FILTER_VBW_TO_RBW_RATIO attribute is disregarded in this mode.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' Specify video bandwidth in terms of the VBW to RBW ratio. The value of the video bandwidth is then computed by using the RFMXSPECAN_ATTR_SPECTRUM_VBW_FILTER_VBW_TO_RBW_RATIO attribute and the RFMXSPECAN_ATTR_SPECTRUM_RBW_FILTER_BANDWIDTH attribute. The value of the RFMXSPECAN_ATTR_SPECTRUM_VBW_FILTER_BANDWIDTH attribute is disregarded in this mode.'}, 'name': 'TRUE', 'value': 1}]}, 'SpurAbsoluteLimitMode': {'values': [{'name': 'MANUAL', 'value': 0}, {'name': 'COUPLE', 'value': 1}]}, 'SpurAmplitudeCorrectionType': {'values': [{'documentation': {'description': ' All the frequency bins in the spectrum are compensated with a single external attenuation value that corresponds to the RF center frequency.'}, 'name': 'RF_CENTER_FREQUENCY', 'value': 0}, {'documentation': {'description': ' An individual frequency bin in the spectrum is compensated with the external attenuation value corresponding to that frequency.'}, 'name': 'SPECTRUM_FREQUENCY_BIN', 'value': 1}]}, 'SpurAveragingEnabled': {'values': [{'documentation': {'description': ' The measurement is performed on a single acquisition.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' The Spur measurement uses the RFMXSPECAN_ATTR_SPUR_AVERAGING_COUNT attribute as the number of acquisitions over which the Spur measurement is averaged.'}, 'name': 'TRUE', 'value': 1}]}, 'SpurAveragingType': {'values': [{'documentation': {'description': ' The power spectrum is linearly averaged. RMS averaging reduces signal fluctuations but not the noise floor. '}, 'name': 'RMS', 'value': 0}, {'documentation': {'description': ' The power spectrum is averaged in a logarithmic scale.'}, 'name': 'LOG', 'value': 1}, {'documentation': {'description': ' The square root of the power spectrum is averaged.'}, 'name': 'SCALAR', 'value': 2}, {'documentation': {'description': ' The peak power in the spectrum at each frequency bin is retained from one acquisition to the next.'}, 'name': 'MAXIMUM', 'value': 3}, {'documentation': {'description': ' The least power in the spectrum at each frequency bin is retained from one acquisition to the next. '}, 'name': 'MINIMUM', 'value': 4}]}, 'SpurFftWindow': {'values': [{'documentation': {'description': ' Analyzes transients for which duration is shorter than the window length. You can also use this window type to separate two tones with frequencies close to each other but with almost equal amplitudes. '}, 'name': 'NONE', 'value': 0}, {'documentation': {'description': ' Measures single-tone amplitudes accurately.'}, 'name': 'FLAT_TOP', 'value': 1}, {'documentation': {'description': ' Analyzes transients for which duration is longer than the window length. You can also use this window type to provide better frequency resolution for noise measurements.'}, 'name': 'HANNING', 'value': 2}, {'documentation': {'description': ' Analyzes closely-spaced sine waves.'}, 'name': 'HAMMING', 'value': 3}, {'documentation': {'description': ' Provides a balance of spectral leakage, frequency resolution, and amplitude attenuation. This windowing is useful for time-frequency analysis.'}, 'name': 'GAUSSIAN', 'value': 4}, {'documentation': {'description': ' Analyzes single tone because it has a low maximum side lobe level and a high side lobe roll-off rate. '}, 'name': 'BLACKMAN', 'value': 5}, {'documentation': {'description': ' Useful as a good general purpose window, having side lobe rejection greater than 90 dB and having a moderately wide main lobe. '}, 'name': 'BLACKMAN_HARRIS', 'value': 6}, {'documentation': {'description': ' Separates two tones with frequencies close to each other but with widely-differing amplitudes.'}, 'name': 'KAISER_BESSEL', 'value': 7}]}, 'SpurMeasurementStatus': {'values': [{'name': 'FAIL', 'value': 0}, {'name': 'PASS', 'value': 1}]}, 'SpurRangeDetectorType': {'values': [{'documentation': {'description': ' The detector is disabled.'}, 'name': 'NONE', 'value': 0}, {'documentation': {'description': ' The middle sample in the bucket is detected.'}, 'name': 'SAMPLE', 'value': 1}, {'documentation': {'description': ' The maximum value of the samples within the bucket is detected if the signal only rises or if the signal only falls. If the signal, within a bucket, both rises and falls, then the maximum and minimum values of the samples are detected in alternate buckets.'}, 'name': 'NORMAL', 'value': 2}, {'documentation': {'description': ' The maximum value of the samples in the bucket is detected.'}, 'name': 'PEAK', 'value': 3}, {'documentation': {'description': ' The minimum value of the samples in the bucket is detected.'}, 'name': 'NEGATIVE_PEAK', 'value': 4}, {'documentation': {'description': ' The average RMS of all the samples in the bucket is detected.'}, 'name': 'AVERAGE_RMS', 'value': 5}, {'documentation': {'description': ' The average voltage of all the samples in the bucket is detected. '}, 'name': 'AVERAGE_VOLTAGE', 'value': 6}, {'documentation': {'description': ' The average log of all the samples in the bucket is detected.'}, 'name': 'AVERAGE_LOG', 'value': 7}]}, 'SpurRangeEnabled': {'values': [{'documentation': {'description': ' Disables the acquisition of the frequency range.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' Enables measurement of Spurs in the frequency range.'}, 'name': 'TRUE', 'value': 1}]}, 'SpurRangeStatus': {'values': [{'name': 'FAIL', 'value': 0}, {'name': 'PASS', 'value': 1}]}, 'SpurRangeVbwFilterAutoBandwidth': {'values': [{'documentation': {'description': ' Specify the video bandwidth in the RFMXSPECAN_ATTR_SPUR_RANGE_VBW_FILTER_BANDWIDTH attribute. The Spur VBW to RBW Ratio attribute is disregarded in this mode.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' Specify video bandwidth in terms of the VBW to RBW ratio. The value of the video bandwidth is then computed by using the RFMXSPECAN_ATTR_SPUR_RANGE_VBW_FILTER_VBW_TO_RBW_RATIO attribute and the RFMXSPECAN_ATTR_SPUR_RANGE_RBW_FILTER_BANDWIDTH attribute. The value of the RFMXSPECAN_ATTR_SPUR_RANGE_VBW_FILTER_BANDWIDTH attribute is disregarded in this mode.'}, 'name': 'TRUE', 'value': 1}]}, 'SpurRbwAutoBandwidth': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'SpurRbwFilterBandwidthDefinition': {'values': [{'name': '3_DB', 'value': 0}, {'name': 'BIN_WIDTH', 'value': 2}, {'name': 'ENBW', 'value': 3}]}, 'SpurRbwFilterType': {'values': [{'name': 'FFT_BASED', 'value': 0}, {'name': 'GAUSSIAN', 'value': 1}, {'name': 'FLAT', 'value': 2}]}, 'SpurSweepTimeAuto': {'values': [{'name': 'FALSE', 'value': 0}, {'name': 'TRUE', 'value': 1}]}, 'TriggerMinimumQuietTimeMode': {'values': [{'documentation': {'description': ' The minimum quiet time for triggering is the value of the RFMXSPECAN_ATTR_TRIGGER_MINIMUM_QUIET_TIME_DURATION attribute. '}, 'name': 'MANUAL', 'value': 0}, {'documentation': {'description': ' The measurement computes the minimum quiet time used for triggering.'}, 'name': 'AUTO', 'value': 1}]}, 'TriggerType': {'values': [{'documentation': {'description': ' No Reference Trigger is configured.'}, 'name': 'NONE', 'value': 0}, {'documentation': {'description': ' The Reference Trigger is not asserted until a digital edge is detected. The source of the digital edge is specified using the RFMXSPECAN_ATTR_DIGITAL_EDGE_TRIGGER_SOURCE attribute.'}, 'name': 'DIGITAL_EDGE', 'value': 1}, {'documentation': {'description': ' The Reference Trigger is asserted when the signal changes past the level specified by the slope (rising or falling), which is configured using the RFMXSPECAN_ATTR_IQ_POWER_EDGE_TRIGGER_SLOPE attribute.'}, 'name': 'IQ_POWER_EDGE', 'value': 2}, {'documentation': {'description': ' The Reference Trigger is not asserted until a software trigger occurs. '}, 'name': 'SOFTWARE', 'value': 3}]}, 'TxpAveragingEnabled': {'values': [{'documentation': {'description': ' The measurement is performed on a single acquisition.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' The TXP measurement uses the RFMXSPECAN_ATTR_TXP_AVERAGING_COUNT attribute as the number of acquisitions over which the TXP measurement is averaged.'}, 'name': 'TRUE', 'value': 1}]}, 'TxpAveragingType': {'values': [{'documentation': {'description': ' The power trace is linearly averaged.'}, 'name': 'RMS', 'value': 0}, {'documentation': {'description': ' The power trace is averaged in a logarithmic scale.'}, 'name': 'LOG', 'value': 1}, {'documentation': {'description': ' The square root of the power trace is averaged.'}, 'name': 'SCALAR', 'value': 2}, {'documentation': {'description': ' The maximum instantaneous power in the power trace is retained from one acquisition to the next.'}, 'name': 'MAXIMUM', 'value': 3}, {'documentation': {'description': ' The minimum instantaneous power in the power trace is retained from one acquisition to the next.'}, 'name': 'MINIMUM', 'value': 4}]}, 'TxpRbwFilterType': {'values': [{'documentation': {'description': ' The RBW filter has a Gaussian response.'}, 'name': 'NONE', 'value': 1}, {'documentation': {'description': ' The RBW filter has a flat response.'}, 'name': 'GAUSSIAN', 'value': 2}, {'documentation': {'description': ' The measurement does not use any RBW filtering.'}, 'name': 'FLAT', 'value': 5}, {'documentation': {'description': ' The RRC filter with the roll-off specified by the RFMXSPECAN_ATTR_TXP_RBW_FILTER_ALPHA attribute is used as the RBW filter.'}, 'name': 'RRC', 'value': 6}]}, 'TxpThresholdEnabled': {'values': [{'documentation': {'description': ' All the acquired samples are considered for the TXP measurement.'}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' The samples above the threshold level specified in the RFMXSPECAN_ATTR_TXP_THRESHOLD_LEVEL attribute are considered for the TXP measurement.'}, 'name': 'TRUE', 'value': 1}]}, 'TxpThresholdType': {'values': [{'documentation': {'description': ' The threshold is relative to the peak power of the acquired samples.'}, 'name': 'RELATIVE', 'value': 0}, {'documentation': {'description': ' The threshold is the absolute power, in dBm.'}, 'name': 'ABSOLUTE', 'value': 1}]}, 'TxpVbwFilterAutoBandwidth': {'values': [{'documentation': {'description': ' Specify the video bandwidth in the RFMXSPECAN_ATTR_TXP_VBW_FILTER_BANDWIDTH attribute. The RFMXSPECAN_ATTR_TXP_VBW_FILTER_VBW_TO_RBW_RATIO attribute is disregarded in this mode. '}, 'name': 'FALSE', 'value': 0}, {'documentation': {'description': ' Specify video bandwidth in terms of the VBW to RBW ratio. The value of the video bandwidth is then computed by using the RFMXSPECAN_ATTR_TXP_VBW_FILTER_VBW_TO_RBW_RATIO attribute and the RFMXSPECAN_ATTR_TXP_RBW_FILTER_BANDWIDTH attribute. The value of the RFMXSPECAN_ATTR_TXP_VBW_FILTER_BANDWIDTH attribute is disregarded in this mode.'}, 'name': 'TRUE', 'value': 1}]}}
for letra in 'Laiana Nardi': print(letra) print("For loop letra!") for contador in range(2,8): print(contador) print("For Loop contador!") friends = ['John','Terry','Eric','Michael','George'] # for friend in friends: # print(friend) for index in range(len(friends)): print(friends[index]) for friend in friends: if friend == 'Eric': print('Found ' + friend + '!') break # continue print(friend) for friend in friends: for number in [1,2,3]: print(friend, number) print("For Loop friend done!")
for letra in 'Laiana Nardi': print(letra) print('For loop letra!') for contador in range(2, 8): print(contador) print('For Loop contador!') friends = ['John', 'Terry', 'Eric', 'Michael', 'George'] for index in range(len(friends)): print(friends[index]) for friend in friends: if friend == 'Eric': print('Found ' + friend + '!') break print(friend) for friend in friends: for number in [1, 2, 3]: print(friend, number) print('For Loop friend done!')
"""Result class definitions.""" class _WriteResult(object): """Base class for write result classes.""" def __init__(self, acknowledged=True): self.acknowledged = acknowledged # here only to PyMongo compat class InsertOneResult(_WriteResult): """The return type for :meth:`~tinymongo.TinyMongoCollection.insert_one`. """ __slots__ = ("__inserted_id", "__acknowledged", "__eid") def __init__(self, eid, inserted_id, acknowledged=True): self.__eid = eid self.__inserted_id = inserted_id super(InsertOneResult, self).__init__(acknowledged) @property def inserted_id(self): """The inserted document's _id.""" return self.__inserted_id @property def eid(self): """The inserted document's tinyDB eid.""" return self.__eid class InsertManyResult(_WriteResult): """The return type for :meth:`~tinymongo.TinyMongoCollection.insert_many`. """ __slots__ = ("__inserted_ids", "__acknowledged", "__eids") def __init__(self, eids, inserted_ids, acknowledged=True): self.__eids = eids self.__inserted_ids = inserted_ids super(InsertManyResult, self).__init__(acknowledged) @property def inserted_ids(self): """A list of _ids of the inserted documents, in the order provided.""" return self.__inserted_ids @property def eids(self): """A list of _ids of the inserted documents, in the order provided.""" return self.__eids class UpdateResult(_WriteResult): """The return type for :meth:`~tinymongo.TinyMongoCollection.update_one`, :meth:`~tinymongo.TinyMongoCollection.update_many`, and :meth:`~tinymongo.TinyMongoCollection.replace_one`. """ __slots__ = ("__raw_result", "__acknowledged") def __init__(self, raw_result, acknowledged=True): self.__raw_result = raw_result super(UpdateResult, self).__init__(acknowledged) @property def raw_result(self): """The raw result document returned by the server.""" return self.__raw_result @property def matched_count(self): """The number of documents matched for this update.""" # TODO: Implement this @property def modified_count(self): """The number of documents modified. """ # TODO: Implement this @property def upserted_id(self): """The _id of the inserted document if an upsert took place. Otherwise ``None``. """ # TODO: Implement this class DeleteResult(_WriteResult): """The return type for :meth:`~tinymongo.TinyMongoCollection.delete_one` and :meth:`~tinymongo.TinyMongoCollection.delete_many`""" __slots__ = ("__raw_result", "__acknowledged") def __init__(self, raw_result, acknowledged=True): self.__raw_result = raw_result super(DeleteResult, self).__init__(acknowledged) @property def raw_result(self): """The raw result document returned by the server.""" return self.__raw_result @property def deleted_count(self): """The number of documents deleted.""" if isinstance(self.raw_result, list): return len(self.raw_result) else: return self.raw_result
"""Result class definitions.""" class _Writeresult(object): """Base class for write result classes.""" def __init__(self, acknowledged=True): self.acknowledged = acknowledged class Insertoneresult(_WriteResult): """The return type for :meth:`~tinymongo.TinyMongoCollection.insert_one`. """ __slots__ = ('__inserted_id', '__acknowledged', '__eid') def __init__(self, eid, inserted_id, acknowledged=True): self.__eid = eid self.__inserted_id = inserted_id super(InsertOneResult, self).__init__(acknowledged) @property def inserted_id(self): """The inserted document's _id.""" return self.__inserted_id @property def eid(self): """The inserted document's tinyDB eid.""" return self.__eid class Insertmanyresult(_WriteResult): """The return type for :meth:`~tinymongo.TinyMongoCollection.insert_many`. """ __slots__ = ('__inserted_ids', '__acknowledged', '__eids') def __init__(self, eids, inserted_ids, acknowledged=True): self.__eids = eids self.__inserted_ids = inserted_ids super(InsertManyResult, self).__init__(acknowledged) @property def inserted_ids(self): """A list of _ids of the inserted documents, in the order provided.""" return self.__inserted_ids @property def eids(self): """A list of _ids of the inserted documents, in the order provided.""" return self.__eids class Updateresult(_WriteResult): """The return type for :meth:`~tinymongo.TinyMongoCollection.update_one`, :meth:`~tinymongo.TinyMongoCollection.update_many`, and :meth:`~tinymongo.TinyMongoCollection.replace_one`. """ __slots__ = ('__raw_result', '__acknowledged') def __init__(self, raw_result, acknowledged=True): self.__raw_result = raw_result super(UpdateResult, self).__init__(acknowledged) @property def raw_result(self): """The raw result document returned by the server.""" return self.__raw_result @property def matched_count(self): """The number of documents matched for this update.""" @property def modified_count(self): """The number of documents modified. """ @property def upserted_id(self): """The _id of the inserted document if an upsert took place. Otherwise ``None``. """ class Deleteresult(_WriteResult): """The return type for :meth:`~tinymongo.TinyMongoCollection.delete_one` and :meth:`~tinymongo.TinyMongoCollection.delete_many`""" __slots__ = ('__raw_result', '__acknowledged') def __init__(self, raw_result, acknowledged=True): self.__raw_result = raw_result super(DeleteResult, self).__init__(acknowledged) @property def raw_result(self): """The raw result document returned by the server.""" return self.__raw_result @property def deleted_count(self): """The number of documents deleted.""" if isinstance(self.raw_result, list): return len(self.raw_result) else: return self.raw_result
num = int(input()) def ListOfNum(num): L = [] while num != 0: x = num%10 num = num//10 L.append(x) return L def Multiply(L): result = 1 for i in L: result = result *i return result L = ListOfNum(num) #L = [2,6,8] result = 0 while len(L) > 1: result +=1 x = Multiply(L) L = ListOfNum(x) print(result) number = int(input("enter number")) product = 1 persistence = 0 print(number) while number > 9: for digit in range(0, len(str(number))): product *= int(str(number)[digit]) print(product) persistence += 1 number = product product = 1 print("persistence:", persistence)
num = int(input()) def list_of_num(num): l = [] while num != 0: x = num % 10 num = num // 10 L.append(x) return L def multiply(L): result = 1 for i in L: result = result * i return result l = list_of_num(num) result = 0 while len(L) > 1: result += 1 x = multiply(L) l = list_of_num(x) print(result) number = int(input('enter number')) product = 1 persistence = 0 print(number) while number > 9: for digit in range(0, len(str(number))): product *= int(str(number)[digit]) print(product) persistence += 1 number = product product = 1 print('persistence:', persistence)
class Term: def __init__(self, name, type="constant"): """ Args: value (string): type (str): ``constant '' or ``variable'' """ self.name = name self.type = type @classmethod def new_term(cls, name, type="constant"): return cls(name, type) def __hash__(self): return hash(self.type + str(self.name)) def __str__(self): return self.name def __eq__(self, other): if isinstance(other, Term): return self.type == other.type and self.name == other.name return False
class Term: def __init__(self, name, type='constant'): """ Args: value (string): type (str): ``constant '' or ``variable'' """ self.name = name self.type = type @classmethod def new_term(cls, name, type='constant'): return cls(name, type) def __hash__(self): return hash(self.type + str(self.name)) def __str__(self): return self.name def __eq__(self, other): if isinstance(other, Term): return self.type == other.type and self.name == other.name return False
def average(nums): """Find mean of a list of numbers.""" return sum(nums) / len(nums) def test_average(): """ >>> test_average() """ assert 12.0 == average([3, 6, 9, 12, 15, 18, 21]) assert 20 == average([5, 10, 15, 20, 25, 30, 35]) assert 4.5 == average([1, 2, 3, 4, 5, 6, 7, 8]) if __name__ == "__main__": """Call average module to find mean of a specific list of numbers.""" print(average([2, 4, 6, 8, 20, 50, 70]))
def average(nums): """Find mean of a list of numbers.""" return sum(nums) / len(nums) def test_average(): """ >>> test_average() """ assert 12.0 == average([3, 6, 9, 12, 15, 18, 21]) assert 20 == average([5, 10, 15, 20, 25, 30, 35]) assert 4.5 == average([1, 2, 3, 4, 5, 6, 7, 8]) if __name__ == '__main__': 'Call average module to find mean of a specific list of numbers.' print(average([2, 4, 6, 8, 20, 50, 70]))
l=[] fo=open("EnglishWords.txt","r") st=fo.read() st=st.split() for line in st: if line[0]=='t': l.append(line) print(len(l))
l = [] fo = open('EnglishWords.txt', 'r') st = fo.read() st = st.split() for line in st: if line[0] == 't': l.append(line) print(len(l))
""" @project: parser @file: node.py @author: Guillaume Sottas @date: 05.04.2018 """ node_to_class = dict() def a2l_node_type(node_type): def wrapper(cls): node_to_class[node_type] = cls cls._node = node_type return cls return wrapper class A2lNode(object): __slots__ = '_node', '_parent', '_children' def __init__(self, *args, **kwargs): if not isinstance(self.__slots__, tuple): raise ValueError('__slot__ attribute must be a list (maybe \',\' is missing at the end?).') self._parent = None self._children = list() for attribute, value in args: attr = getattr(self, attribute) if isinstance(attr, list): attr.append(value) elif attr is None: setattr(self, attribute, value) else: raise AttributeError(attribute) if isinstance(value, A2lNode): value.set_parent(self) self.add_children(value) def set_parent(self, a2l_node): self._parent = a2l_node def add_children(self, a2l_node): self._children.append(a2l_node) def get_properties(self): return (p for p in self.__slots__ if not p.startswith('_')) def node(self): return self._node def get_node(self, node_name): nodes = list() for node in self._children: if node.node() == node_name: nodes.append(node) nodes += node.get_node(node_name) return nodes def get_json(self): tmp = dict(node=self.node()) for p in self.properties: v = getattr(self, p) if isinstance(v, A2lNode): tmp[p] = v.json elif isinstance(v, list): tmp[p] = list() for e in v: if isinstance(e, A2lNode): tmp[p].append(e.json) else: tmp[p].append(e) else: tmp[p] = v return tmp properties = property(fget=get_properties) json = property(fget=get_json) @a2l_node_type('ROOT') class A2lFile(A2lNode): __slots__ = 'asap2_version', 'a2ml_version', 'project' def __init__(self, args): self.asap2_version = None self.a2ml_version = None self.project = None super(A2lFile, self).__init__(*args) @a2l_node_type('VERSION') class Version(A2lNode): __slots__ = 'version_no', 'upgrade_no' def __init__(self, version_no, upgrade_no): self.version_no = version_no self.upgrade_no = upgrade_no super(Version, self).__init__() @a2l_node_type('A2ML_VERSION') class A2MLVersion(Version): pass @a2l_node_type('ADDRESS_MAPPING') class AddressMapping(A2lNode): __slots__ = 'orig_address', 'mapping_address', 'length' def __init__(self, orig_address, mapping_address, length): self.orig_address = orig_address self.mapping_address = mapping_address self.length = length super(AddressMapping, self).__init__() @a2l_node_type('ANNOTATION') class Annotation(A2lNode): __slots__ = 'annotation_label', 'annotation_origin', 'annotation_text' def __init__(self, args): self.annotation_label = None self.annotation_origin = None self.annotation_text = None super(Annotation, self).__init__(*args) @a2l_node_type('ANNOTATION_TEXT') class AnnotationText(A2lNode): __slots__ = 'annotation_text', def __init__(self, args): self.annotation_text = list() super(AnnotationText, self).__init__(*args) @a2l_node_type('ASAP2_VERSION') class ASAP2Version(Version): pass @a2l_node_type('AVAILABLE_EVENT_LIST') class AvailableEventList(A2lNode): __slots__ = 'event', def __init__(self, args): self.event = list() super(AvailableEventList, self).__init__(*args) @a2l_node_type('AXIS_DESCR') class AxisDescr(A2lNode): __slots__ = 'attribute', 'input_quantity', 'conversion', 'max_axis_points', 'lower_limit', 'upper_limit', \ 'read_only', 'format', 'annotation', 'axis_pts_ref', 'max_grad', 'monotony', 'byte_order', \ 'extended_limits', 'fix_axis_par', 'fix_axis_par_dist', 'fix_axis_par_list', 'deposit', 'curve_axis_ref' def __init__(self, attribute, input_quantity, conversion, max_axis_points, lower_limit, upper_limit, args): self.attribute = attribute self.input_quantity = input_quantity self.conversion = conversion self.max_axis_points = max_axis_points self.lower_limit = lower_limit self.upper_limit = upper_limit self.read_only = None self.format = None self.annotation = list() self.axis_pts_ref = None self.max_grad = None self.monotony = None self.byte_order = None self.extended_limits = None self.fix_axis_par = None self.fix_axis_par_dist = None self.fix_axis_par_list = None self.deposit = None self.curve_axis_ref = None super(AxisDescr, self).__init__(*args) @a2l_node_type('AXIS_PTS') class AxisPts(A2lNode): __slots__ = 'name', 'long_identifier', 'address', 'input_quantity', 'deposit', 'max_diff', 'conversion', \ 'max_axis_points', 'lower_limit', 'upper_limit', 'display_identifier', 'read_only', 'format', \ 'deposit', 'byte_order', 'function_list', 'ref_memory_segment', 'guard_rails', 'extended_limits', \ 'annotation', 'if_data_axis_pts', 'calibration_access', 'ecu_address_extension' def __init__(self, name, long_identifier, address, input_quantity, deposit, max_diff, conversion, max_axis_points, lower_limit, upper_limit, args): self.name = name self.long_identifier = long_identifier self.address = address self.input_quantity = input_quantity self.deposit = deposit self.max_diff = max_diff self.conversion = conversion self.max_axis_points = max_axis_points self.lower_limit = lower_limit self.upper_limit = upper_limit self.display_identifier = None self.read_only = None self.format = None self.deposit = None self.byte_order = None self.function_list = None self.ref_memory_segment = None self.guard_rails = None self.extended_limits = None self.annotation = list() self.if_data_axis_pts = list() self.calibration_access = None self.ecu_address_extension = None super(AxisPts, self).__init__(*args) class AxisPtsXYZ(A2lNode): __slots__ = 'position', 'data_type', 'index_incr', 'addressing' def __init__(self, position, data_type, index_incr, addressing): self.position = position self.data_type = data_type self.index_incr = index_incr self.addressing = addressing super(AxisPtsXYZ, self).__init__() @a2l_node_type('AXIS_PTS_X') class AxisPtsX(AxisPtsXYZ): pass @a2l_node_type('AXIS_PTS_Y') class AxisPtsY(AxisPtsXYZ): pass @a2l_node_type('AXIS_PTS_Z') class AxisPtsZ(AxisPtsXYZ): pass class AxisRescale(A2lNode): __slots__ = 'position', 'data_type', 'max_number_of_rescale_pairs', 'index_incr', 'addressing' def __init__(self, position, data_type, max_number_of_rescale_pairs, index_incr, addressing): self.position = position self.data_type = data_type self.max_number_of_rescale_pairs = max_number_of_rescale_pairs self.index_incr = index_incr self.addressing = addressing super(AxisRescale, self).__init__() @a2l_node_type('AXIS_RESCALE_X') class AxisRescaleX(AxisRescale): pass @a2l_node_type('AXIS_RESCALE_Y') class AxisRescaleY(AxisRescale): pass @a2l_node_type('AXIS_RESCALE_Z') class AxisRescaleZ(AxisRescale): pass @a2l_node_type('BIT_OPERATION') class BitOperation(A2lNode): __slots__ = 'left_shift', 'right_shift', 'sign_extend' def __init__(self, args): self.left_shift = None self.right_shift = None self.sign_extend = None super(BitOperation, self).__init__(*args) @a2l_node_type('CALIBRATION_METHOD') class CalibrationMethod(A2lNode): __slots__ = 'method', 'version', 'calibration_handle' def __init__(self, method, version, args): self.method = method self.version = version self.calibration_handle = list() super(CalibrationMethod, self).__init__(*args) @a2l_node_type('CHARACTERISTIC') class Characteristic(A2lNode): __slots__ = 'name', 'long_identifier', 'type', 'address', 'deposit', 'max_diff', 'conversion', 'lower_limit', \ 'upper_limit', 'display_identifier', 'format', 'byte_order', 'bit_mask', 'function_list', 'number', \ 'extended_limits', 'read_only', 'guard_rails', 'map_list', 'max_refresh', 'dependent_characteristic', \ 'virtual_characteristic', 'ref_memory_segment', 'annotation', 'comparison_quantity', \ 'if_data_characteristic', 'axis_descr', 'calibration_access', 'matrix_dim', 'ecu_address_extension','symbol_link' def __init__(self, name, long_identifier, type, address, deposit, max_diff, conversion, lower_limit, upper_limit, args): self.name = name self.long_identifier = long_identifier self.type = type self.address = address self.deposit = deposit self.max_diff = max_diff self.conversion = conversion self.lower_limit = lower_limit self.upper_limit = upper_limit self.display_identifier = None self.format = None self.byte_order = None self.bit_mask = None self.function_list = None self.number = None self.symbol_link=None self.extended_limits = None self.read_only = None self.guard_rails = None self.map_list = None self.max_refresh = None self.dependent_characteristic = None self.virtual_characteristic = None self.ref_memory_segment = None self.annotation = list() self.comparison_quantity = None self.if_data_characteristic = list() self.axis_descr = list() self.calibration_access = None self.matrix_dim = None self.ecu_address_extension = None super(Characteristic, self).__init__(*args) @a2l_node_type('CHECKSUM') class Checksum(A2lNode): __slots__ = 'checksum_dll', 'max_block_size' def __init__(self, checksum_dll, max_block_size): self.checksum_dll = checksum_dll self.max_block_size = max_block_size super(Checksum, self).__init__() @a2l_node_type('COEFFS') class Coeffs(A2lNode): __slots__ = 'a', 'b', 'c', 'd', 'e', 'f' def __init__(self, a, b, c, d, e, f): self.a = a self.b = b self.c = c self.d = d self.e = e self.f = f super(Coeffs, self).__init__() @a2l_node_type('COMPU_METHOD') class CompuMethod(A2lNode): __slots__ = 'name', 'long_identifier', 'conversion_type', 'format', 'unit', 'formula', 'coeffs', 'coeffs_linear', \ 'compu_tab_ref', 'ref_unit' def __init__(self, name, long_identifier, conversion_type, format, unit, args): self.name = name self.long_identifier = long_identifier self.conversion_type = conversion_type self.format = format self.unit = unit self.formula = None self.coeffs = None self.coeffs_linear = None # TODO: should be removed, according to 1.51. self.compu_tab_ref = None self.ref_unit = None super(CompuMethod, self).__init__(*args) @a2l_node_type('COMPU_TAB') class CompuTab(A2lNode): __slots__ = 'name', 'long_identifier', 'conversion_type', 'number_value_pairs', 'in_val_out_val', 'default_value', \ 'default_value_numeric' def __init__(self, name, long_identifier, conversion_type, number_value_pairs, args): self.name = name self.long_identifier = long_identifier self.conversion_type = conversion_type self.number_value_pairs = number_value_pairs self.in_val_out_val = None self.default_value = None self.default_value_numeric = None # TODO: should be removed, according to 1.51. super(CompuTab, self).__init__(*args) @a2l_node_type('COMPU_VTAB') class CompuVTab(A2lNode): __slots__ = 'name', 'long_identifier', 'conversion_type', 'number_value_pairs', 'compu_vtab_in_val_out_val', \ 'default_value' def __init__(self, name, long_identifier, conversion_type, number_value_pairs, args): self.name = name self.long_identifier = long_identifier self.conversion_type = conversion_type self.number_value_pairs = number_value_pairs self.compu_vtab_in_val_out_val = None # TODO: replace with in_val_out_val... self.default_value = None super(CompuVTab, self).__init__(*args) @a2l_node_type('COMPU_VTAB_RANGE') class CompuVTabRange(A2lNode): __slots__ = 'name', 'long_identifier', 'number_value_triples', 'compu_vtab_range_in_val_out_val', 'default_value' def __init__(self, name, long_identifier, number_value_triples, args): self.name = name self.long_identifier = long_identifier self.number_value_triples = number_value_triples self.compu_vtab_range_in_val_out_val = None # TODO: replace with in_val_min_in_val_max_out_val... self.default_value = None super(CompuVTabRange, self).__init__(*args) @a2l_node_type('DAQ') class Daq(A2lNode): __slots__ = 'daq_config_type', 'max_daq', 'max_event_channel', 'min_daq', 'optimisation_type', \ 'address_extension', 'identification_field_type', 'granularity_odt_entry', 'max_odt_entry_size_daq', \ 'overload_indication', 'prescaler_supported', 'resume_supported', 'daq_list', 'timestamp_supported', \ 'event', 'EVENT', 'IDENT', 'NUMERIC','stim' def __init__(self, daq_config_type, max_daq, max_event_channel, min_daq, optimisation_type, address_extension, identification_field_type, granularity_odt_entry, max_odt_entry_size_daq, overload_indication, args): self.daq_config_type = daq_config_type self.max_daq = max_daq self.max_event_channel = max_event_channel self.min_daq = min_daq self.optimisation_type = optimisation_type self.address_extension = address_extension self.identification_field_type = identification_field_type self.granularity_odt_entry = granularity_odt_entry self.max_odt_entry_size_daq = max_odt_entry_size_daq self.overload_indication = overload_indication self.prescaler_supported = None self.resume_supported = None self.daq_list = list() self.timestamp_supported = list() self.stim = list() self.event = list() self.EVENT = list() self.IDENT = list() self.NUMERIC = list() super(Daq, self).__init__(*args) @a2l_node_type('DAQ_EVENT') class DaqEvent(A2lNode): __slots__ = 'name', 'available_event_list', 'default_event_list' def __init__(self, name, args): self.name = name self.available_event_list = list() self.default_event_list = list() super(DaqEvent, self).__init__(*args) @a2l_node_type('DAQ_LIST') class DaqList(A2lNode): __slots__ = 'daq_list_number', 'daq_list_type', 'max_odt', 'max_odt_entries', 'first_pid', 'event_fixed', \ 'predefined' def __init__(self, daq_list_number, args): self.daq_list_number = daq_list_number self.daq_list_type = None self.max_odt = None self.max_odt_entries = None self.first_pid = None self.event_fixed = None self.predefined = list() super(DaqList, self).__init__(*args) @a2l_node_type('DAQ_LIST_CAN_ID') class DaqListCanId(A2lNode): __slots__ = 'identifier', 'daq_list_can_id_type_fixed', 'daq_list_can_id_type_variable' def __init__(self, identifier, args): self.identifier = identifier self.daq_list_can_id_type_fixed = None self.daq_list_can_id_type_variable = None super(DaqListCanId, self).__init__(*args) @a2l_node_type('DEFAULT_EVENT_LIST') class DefaultEventList(A2lNode): __slots__ = 'event', def __init__(self, args): self.event = list() super(DefaultEventList, self).__init__(*args) @a2l_node_type('DEF_CHARACTERISTIC') class DefCharacteristic(A2lNode): __slots__ = 'identifier', def __init__(self, args): self.identifier = list() super(DefCharacteristic, self).__init__(*args) @a2l_node_type('DEPENDENT_CHARACTERISTIC') class DependentCharacteristic(A2lNode): __slots__ = 'formula', 'characteristic' def __init__(self, formula, args): self.formula = formula self.characteristic = list() super(DependentCharacteristic, self).__init__(*args) class DistOp(A2lNode): __slots__ = 'position', 'data_type' def __init__(self, position, data_type): self.position = position self.data_type = data_type super(DistOp, self).__init__() @a2l_node_type('DIST_OP_X') class DistOpX(DistOp): pass @a2l_node_type('DIST_OP_Y') class DistOpY(DistOp): pass @a2l_node_type('DIST_OP_Z') class DistOpZ(DistOp): pass @a2l_node_type('EVENT') class Event(A2lNode): __slots__ = 'name', 'short_name', 'event_channel_number', 'daq_list_type', 'max_daq_list', 'time_cycle', \ 'time_unit', 'priority' def __init__(self, name, short_name, event_channel_number, daq_list_type, max_daq_list, time_cycle, time_unit, priority): self.name = name self.short_name = short_name self.event_channel_number = event_channel_number self.daq_list_type = daq_list_type self.max_daq_list = max_daq_list self.time_cycle = time_cycle self.time_unit = time_unit self.priority = priority super(Event, self).__init__() @a2l_node_type('EVENT_GROUP') class EventGroup(A2lNode): __slots__ = 'raster_grp_name', 'short_name', 'raster_id' def __init__(self, raster_grp_name, short_name, raster_id): self.raster_grp_name = raster_grp_name self.short_name = short_name self.raster_id = raster_id super(EventGroup, self).__init__() @a2l_node_type('FIX_AXIS_PAR') class FixAxisPar(A2lNode): __slots__ = 'offset', 'shift', 'numberapo' def __init__(self, offset, shift, numberapo): self.offset = offset self.shift = shift self.numberapo = numberapo super(FixAxisPar, self).__init__() @a2l_node_type('FIX_AXIS_PAR_DIST') class FixAxisParDist(FixAxisPar): __slots__ = 'offset', 'distance', 'numberapo' def __init__(self, offset, distance, numberapo): self.offset = offset self.distance = distance self.numberapo = numberapo super(FixAxisPar, self).__init__() class FixNoAxisPts(A2lNode): __slots__ = 'number_of_axis_points', def __init__(self, number_of_axis_points): self.number_of_axis_points = number_of_axis_points super(FixNoAxisPts, self).__init__() @a2l_node_type('FIX_NO_AXIS_PTS_X') class FixNoAxisPtsX(FixNoAxisPts): pass @a2l_node_type('FIX_NO_AXIS_PTS_Y') class FixNoAxisPtsY(FixNoAxisPts): pass @a2l_node_type('FIX_NO_AXIS_PTS_Z') class FixNoAxisPtsZ(FixNoAxisPts): pass @a2l_node_type('FNC_VALUES') class FncValues(A2lNode): __slots__ = 'position', 'data_type', 'index_mode', 'addresstype' def __init__(self, position, data_type, index_mode, addresstype): self.position = position self.data_type = data_type self.index_mode = index_mode self.addresstype = addresstype super(FncValues, self).__init__() @a2l_node_type('FORMULA') class Formula(A2lNode): __slots__ = 'f', 'formula_inv' def __init__(self, f, args): self.f = f self.formula_inv = None super(Formula, self).__init__(*args) @a2l_node_type('FRAME') class Frame(A2lNode): __slots__ = 'name', 'long_identifier', 'scaling_unit', 'rate', 'frame_measurement', 'if_data_frame' def __init__(self, name, long_identifier, scaling_unit, rate, args): self.name = name self.long_identifier = long_identifier self.scaling_unit = scaling_unit self.rate = rate self.frame_measurement = None self.if_data_frame = list() super(Frame, self).__init__(*args) @a2l_node_type('FRAME_MEASUREMENT') class FrameMeasurement(A2lNode): __slots__ = 'identifier', def __init__(self, args): self.identifier = list() super(FrameMeasurement, self).__init__(*args) @a2l_node_type('FUNCTION') class Function(A2lNode): __slots__ = 'name', 'long_identifier', 'annotation', 'def_characteristic', 'ref_characteristic', 'in_measurement', \ 'out_measurement', 'loc_measurement', 'sub_function', 'function_version' def __init__(self, name, long_identifier, args): self.name = name self.long_identifier = long_identifier self.annotation = list() self.def_characteristic = None self.ref_characteristic = None self.in_measurement = None self.out_measurement = None self.loc_measurement = None self.sub_function = None self.function_version = None super(Function, self).__init__(*args) @a2l_node_type('FUNCTION_LIST') class FunctionList(A2lNode): __slots__ = 'name', def __init__(self, args): self.name = list() super(FunctionList, self).__init__(*args) @a2l_node_type('GROUP') class Group(A2lNode): __slots__ = 'group_name', 'group_long_identifier', 'annotation', 'root', 'ref_characteristic', 'ref_measurement', \ 'function_list', 'sub_group' def __init__(self, group_name, group_long_identifier, args): self.group_name = group_name self.group_long_identifier = group_long_identifier self.annotation = list() self.root = None self.ref_characteristic = None self.ref_measurement = None self.function_list = None self.sub_group = None super(Group, self).__init__(*args) @a2l_node_type('HEADER') class Header(A2lNode): __slots__ = 'comment', 'version', 'project_no' def __init__(self, comment, args): self.comment = comment self.version = None self.project_no = None super(Header, self).__init__(*args) @a2l_node_type('IDENTIFICATION') class Identification(A2lNode): __slots__ = 'position', 'data_type' def __init__(self, position, data_type): self.position = position self.data_type = data_type super(Identification, self).__init__() @a2l_node_type('if_data_frame') class IfDataFrame(A2lNode): __slots__ = 'name', def __init__(self, name, args): self.name = name super(IfDataFrame, self).__init__(*args) @a2l_node_type('if_data_memory_segment') class IfDataMemorySegment(A2lNode): __slots__ = 'name', 'address_mapping', 'segment', 'generic_parameter' def __init__(self, name, args): self.name = name self.address_mapping = list() self.segment = list() self.generic_parameter = list() super(IfDataMemorySegment, self).__init__(*args) @a2l_node_type('if_data_module') class IfDataModule(A2lNode): __slots__ = 'name', 'source', 'raster', 'event_group', 'seed_key', 'checksum', 'tp_blob', 'tp_data','if_data_module_unsupported_element' def __init__(self, name, args): self.name = name self.source = list() self.raster = list() self.event_group = list() self.seed_key = None self.checksum = None self.tp_blob = None self.tp_data = None self.if_data_module_unsupported_element=None super(IfDataModule, self).__init__(*args) @a2l_node_type('if_data_xcp') class IfDataXcp(A2lNode): __slots__ = 'protocol_layer', 'daq', 'pag', 'pgm', 'segment', 'daq_event', 'xcp_on_can', 'generic_parameter_list' def __init__(self, args): self.protocol_layer = list() self.daq = list() self.pag = list() self.pgm = list() self.segment = list() self.daq_event = list() self.xcp_on_can = list() self.generic_parameter_list = None super(IfDataXcp, self).__init__(*args) @a2l_node_type('IN_MEASUREMENT') class InMeasurement(A2lNode): __slots__ = 'identifier', def __init__(self, args): self.identifier = list() super(InMeasurement, self).__init__(*args) @a2l_node_type('LOC_MEASUREMENT') class LocMeasurement(A2lNode): __slots__ = 'identifier', def __init__(self, args): self.identifier = list() super(LocMeasurement, self).__init__(*args) @a2l_node_type('MAX_REFRESH') class MaxRefresh(A2lNode): __slots__ = 'scaling_unit', 'rate' def __init__(self, scaling_unit, rate): self.scaling_unit = scaling_unit self.rate = rate super(MaxRefresh, self).__init__() @a2l_node_type('MEASUREMENT') class Measurement(A2lNode): __slots__ = 'name', 'long_identifier', 'data_type', 'conversion', 'resolution', 'accuracy', 'lower_limit', \ 'upper_limit', 'display_identifier', 'read_write', 'format', 'array_size', 'bit_mask', \ 'bit_operation', 'byte_order', 'max_refresh', 'virtual', 'function_list', 'ecu_address', 'error_mask', \ 'ref_memory_segment', 'annotation', 'if_data_xcp', 'if_data_measurement', 'matrix_dim', \ 'ecu_address_extension','symbol_link' def __init__(self, name, long_identifier, data_type, conversion, resolution, accuracy, lower_limit, upper_limit, args): self.name = name self.long_identifier = long_identifier self.data_type = data_type self.conversion = conversion self.resolution = resolution self.accuracy = accuracy self.lower_limit = lower_limit self.upper_limit = upper_limit self.display_identifier = None self.read_write = None self.symbol_link = None self.format = None self.array_size = None self.bit_mask = None self.bit_operation = None self.byte_order = None self.max_refresh = None self.virtual = None self.function_list = None self.ecu_address = None self.error_mask = None self.ref_memory_segment = None self.annotation = list() self.if_data_xcp = list() self.if_data_measurement = list() self.matrix_dim = None self.ecu_address_extension = None super(Measurement, self).__init__(*args) @a2l_node_type('MEMORY_LAYOUT') class MemoryLayout(A2lNode): __slots__ = 'prg_type', 'address', 'size', 'offset', 'if_data_memory_layout' def __init__(self, prg_type, address, size, offset, args): self.prg_type = prg_type self.address = address self.size = size self.offset = offset self.if_data_memory_layout = list() super(MemoryLayout, self).__init__(*args) @a2l_node_type('MEMORY_SEGMENT') class MemorySegment(A2lNode): __slots__ = 'name', 'long_identifier', 'prg_type', 'memory_type', 'attribute', 'address', 'size', 'offset', \ 'if_data_memory_segment', 'if_data_xcp' def __init__(self, name, long_identifier, prg_type, memory_type, attribute, address, size, offset, args): self.name = name self.long_identifier = long_identifier self.prg_type = prg_type self.memory_type = memory_type self.attribute = attribute self.address = address self.size = size self.offset = offset self.if_data_memory_segment = list() self.if_data_xcp = list() super(MemorySegment, self).__init__(*args) @a2l_node_type('MODULE') class Module(A2lNode): __slots__ = 'name', 'long_identifier', 'a2ml', 'mod_par', 'mod_common', 'if_data_xcp', 'if_data_module', \ 'characteristic', 'axis_pts', 'measurement', 'compu_method', 'compu_tab', 'compu_vtab', \ 'compu_vtab_range', 'function', 'group', 'record_layout', 'variant_coding', 'frame', 'user_rights', \ 'unit' def __init__(self, name, long_identifier, args): self.name = name self.long_identifier = long_identifier self.a2ml = None self.mod_par = None self.mod_common = None self.if_data_xcp = None self.if_data_module = list() self.characteristic = list() self.axis_pts = list() self.measurement = list() self.compu_method = list() self.compu_tab = list() self.compu_vtab = list() self.compu_vtab_range = list() self.function = list() self.group = list() self.record_layout = list() self.variant_coding = None self.frame = None self.user_rights = list() self.unit = list() super(Module, self).__init__(*args) @a2l_node_type('MOD_COMMON') class ModCommon(A2lNode): __slots__ = 'comment', 's_rec_layout', 'deposit', 'byte_order', 'data_size', 'alignment_byte', 'alignment_word', \ 'alignment_long', 'alignment_float32_ieee', 'alignment_float64_ieee','alignment_int64' def __init__(self, comment, args): self.comment = comment self.s_rec_layout = None self.deposit = None self.byte_order = None self.data_size = None self.alignment_byte = None self.alignment_word = None self.alignment_long = None self.alignment_int64 = None self.alignment_float32_ieee = None self.alignment_float64_ieee = None super(ModCommon, self).__init__(*args) @a2l_node_type('MOD_PAR') class ModPar(A2lNode): __slots__ = 'comment', 'version', 'addr_epk', 'epk', 'supplier', 'customer', 'customer_no', 'user', 'phone_no', \ 'ecu', 'cpu_type', 'no_of_interfaces', 'ecu_calibration_offset', 'calibration_method', \ 'memory_layout', 'memory_segment', 'system_constant' def __init__(self, comment, args): self.comment = comment self.version = None self.addr_epk = list() self.epk = None self.supplier = None self.customer = None self.customer_no = None self.user = None self.phone_no = None self.ecu = None self.cpu_type = None self.no_of_interfaces = None self.ecu_calibration_offset = None self.calibration_method = list() self.memory_layout = list() self.memory_segment = list() self.system_constant = list() super(ModPar, self).__init__(*args) class NoAxisPts(A2lNode): __slots__ = 'position', 'data_type' def __init__(self, position, data_type): self.position = position self.data_type = data_type super(NoAxisPts, self).__init__() @a2l_node_type('NO_AXIS_PTS_X') class NoAxisPtsX(NoAxisPts): pass @a2l_node_type('NO_AXIS_PTS_Y') class NoAxisPtsY(NoAxisPts): pass @a2l_node_type('NO_AXIS_PTS_Z') class NoAxisPtsZ(NoAxisPts): pass class NoRescale(A2lNode): __slots__ = 'position', 'data_type' def __init__(self, position, data_type): self.position = position self.data_type = data_type super(NoRescale, self).__init__() @a2l_node_type('NO_RESCALE_X') class NoRescaleX(NoRescale): pass @a2l_node_type('NO_RESCALE_Y') class NoRescaleY(NoRescale): pass @a2l_node_type('NO_RESCALE_Z') class NoRescaleZ(NoRescale): pass class Offset(A2lNode): __slots__ = 'position', 'data_type' def __init__(self, position, data_type): self.position = position self.data_type = data_type super(Offset, self).__init__() @a2l_node_type('OFFSET_X') class OffsetX(Offset): pass @a2l_node_type('OFFSET_Y') class OffsetY(Offset): pass @a2l_node_type('OFFSET_Z') class OffsetZ(Offset): pass @a2l_node_type('OUT_MEASUREMENT') class OutMeasurement(A2lNode): __slots__ = 'identifier', def __init__(self, args): self.identifier = list() super(OutMeasurement, self).__init__(*args) @a2l_node_type('PAG') class Pag(A2lNode): __slots__ = 'max_segments', 'freeze_supported' def __init__(self, max_segments, args): self.max_segments = max_segments self.freeze_supported = None super(Pag, self).__init__(*args) @a2l_node_type('PGM') class Pgm(A2lNode): __slots__ = 'mode', 'max_sectors', 'max_cto_pgm', 'sector', 'generic_parameter_list' def __init__(self, mode, max_sectors, max_cto_pgm, args): self.mode = mode self.max_sectors = max_sectors self.max_cto_pgm = max_cto_pgm self.sector = list() self.generic_parameter_list = None super(Pgm, self).__init__(*args) @a2l_node_type('PROJECT') class Project(A2lNode): __slots__ = 'name', 'long_identifier', 'header', 'module' def __init__(self, name, long_identifier, args): self.name = name self.long_identifier = long_identifier self.header = None self.module = list() super(Project, self).__init__(*args) @a2l_node_type('PROTOCOL_LAYER') class ProtocolLayer(A2lNode): __slots__ = 'xcp_protocol_layer_version', 't1', 't2', 't3', 't4', 't5', 't6', 't7', 'max_cto', 'max_dto' def __init__(self, xcp_protocol_layer_version, t1, t2, t3, t4, t5, t6, t7, max_cto, max_dto): self.xcp_protocol_layer_version = xcp_protocol_layer_version self.t1 = t1 self.t2 = t2 self.t3 = t3 self.t4 = t4 self.t5 = t5 self.t6 = t6 self.t7 = t7 self.max_cto = max_cto self.max_dto = max_dto super(ProtocolLayer, self).__init__() @a2l_node_type('RASTER') class Raster(A2lNode): __slots__ = 'raster_name', 'short_name', 'raster_id', 'scaling_unit', 'rate' def __init__(self, raster_name, short_name, raster_id, scaling_unit, rate): self.raster_name = raster_name self.short_name = short_name self.raster_id = raster_id self.scaling_unit = scaling_unit self.rate = rate super(Raster, self).__init__() @a2l_node_type('RECORD_LAYOUT') class RecordLayout(A2lNode): __slots__ = 'name', 'fnc_values', 'identification', 'axis_pts_x', 'axis_pts_y', 'axis_pts_z', 'axis_rescale_x', \ 'axis_rescale_y', 'axis_rescale_z', 'no_axis_pts_x', 'no_axis_pts_y', 'no_axis_pts_z', 'no_rescale_x', \ 'no_rescale_y', 'no_rescale_z', 'fix_no_axis_pts_x', 'fix_no_axis_pts_y', 'fix_no_axis_pts_z', \ 'src_addr_x', 'src_addr_y', 'src_addr_z', 'rip_addr_x', 'rip_addr_y', 'rip_addr_z', 'rip_addr_w', \ 'shift_op_x', 'shift_op_y', 'shift_op_z', 'offset_x', 'offset_y', 'offset_z', 'dist_op_x', \ 'dist_op_y', 'dist_op_z', 'alignment_byte', 'alignment_word', 'alignment_long', \ 'alignment_float32_ieee', 'alignment_float64_ieee', 'reserved','alignment_int64' def __init__(self, name, args): self.name = name self.fnc_values = None self.identification = None self.axis_pts_x = None self.axis_pts_y = None self.axis_pts_z = None self.axis_rescale_x = None self.axis_rescale_y = None self.axis_rescale_z = None self.no_axis_pts_x = None self.no_axis_pts_y = None self.no_axis_pts_z = None self.no_rescale_x = None self.no_rescale_y = None self.no_rescale_z = None self.fix_no_axis_pts_x = None self.fix_no_axis_pts_y = None self.fix_no_axis_pts_z = None self.src_addr_x = None self.src_addr_y = None self.src_addr_z = None self.rip_addr_x = None self.rip_addr_y = None self.rip_addr_z = None self.rip_addr_w = None self.shift_op_x = None self.shift_op_y = None self.shift_op_z = None self.offset_x = None self.offset_y = None self.offset_z = None self.dist_op_x = None self.dist_op_y = None self.dist_op_z = None self.alignment_byte = None self.alignment_word = None self.alignment_long = None self.alignment_float32_ieee = None self.alignment_float64_ieee = None self.alignment_int64 = None self.reserved = list() super(RecordLayout, self).__init__(*args) @a2l_node_type('REF_CHARACTERISTIC') class RefCharacteristic(A2lNode): __slots__ = 'identifier', def __init__(self, args): self.identifier = list() super(RefCharacteristic, self).__init__(*args) @a2l_node_type('REF_GROUP') class RefGroup(A2lNode): __slots__ = 'identifier', def __init__(self, args): self.identifier = list() super(RefGroup, self).__init__(*args) @a2l_node_type('REF_MEASUREMENT') class RefMeasurement(A2lNode): __slots__ = 'identifier', def __init__(self, args): self.identifier = list() super(RefMeasurement, self).__init__(*args) @a2l_node_type('RESERVED') class Reserved(A2lNode): __slots__ = 'position', 'data_size' def __init__(self, position, data_size): self.position = position self.data_size = data_size super(Reserved, self).__init__() class RipAddr(A2lNode): __slots__ = 'position', 'data_type' def __init__(self, position, data_type): self.position = position self.data_type = data_type super(RipAddr, self).__init__() @a2l_node_type('RIP_ADDR_X') class RipAddrX(RipAddr): pass @a2l_node_type('RIP_ADDR_Y') class RipAddrY(RipAddr): pass @a2l_node_type('RIP_ADDR_Z') class RipAddrZ(RipAddr): pass @a2l_node_type('RIP_ADDR_W') class RipAddrW(RipAddr): pass @a2l_node_type('SECTOR') class Sector(A2lNode): __slots__ = 'name', 'sector_number', 'address', 'length', 'erase_number', 'program_number', 'programming_method' def __init__(self, name, sector_number, address, length, erase_number, program_number, programming_method): self.name = name self.sector_number = sector_number self.address = address self.length = length self.erase_number = erase_number self.program_number = program_number self.programming_method = programming_method super(Sector, self).__init__() @a2l_node_type('SEED_KEY') class SeedKey(A2lNode): __slots__ = 'cal_dll', 'daq_dll', 'pgm_dll' def __init__(self, cal_dll, daq_dll, pgm_dll): self.cal_dll = cal_dll self.daq_dll = daq_dll self.pgm_dll = pgm_dll super(SeedKey, self).__init__() @a2l_node_type('SEGMENT') class Segment(A2lNode): __slots__ = 'segment_logical_number', 'number_of_pages', 'address_extension', 'compression_method', \ 'encryption_method', 'checksum', 'page' def __init__(self, segment_logical_number, number_of_pages, address_extension, compression_method, encryption_method, args): self.segment_logical_number = segment_logical_number self.number_of_pages = number_of_pages self.address_extension = address_extension self.compression_method = compression_method self.encryption_method = encryption_method self.checksum = None self.page = None super(Segment, self).__init__(*args) class ShiftOp(A2lNode): __slots__ = 'position', 'data_type' def __init__(self, position, data_type): self.position = position self.data_type = data_type super(ShiftOp, self).__init__() @a2l_node_type('SHIFT_OP_X') class ShiftOpX(ShiftOp): pass @a2l_node_type('SHIFT_OP_Y') class ShiftOpY(ShiftOp): pass @a2l_node_type('SHIFT_OP_Z') class ShiftOpZ(ShiftOp): pass @a2l_node_type('SI_EXPONENTS') class SiExponents(A2lNode): __slots__ = 'length', 'mass', 'time', 'electric_current', 'temperature', 'amount_of_substance', 'luminous_intensity' def __init__(self, length, mass, time, electric_current, temperature, amount_of_substance, luminous_intensity): self.length = length self.mass = mass self.time = time self.electric_current = electric_current self.temperature = temperature self.amount_of_substance = amount_of_substance self.luminous_intensity = luminous_intensity super(SiExponents, self).__init__() @a2l_node_type('SOURCE') class Source(A2lNode): __slots__ = 'name', 'scaling_unit', 'rate', 'display_identifier', 'qp_blob', 'qp_data' def __init__(self, name, scaling_unit, rate, args): self.name = name self.scaling_unit = scaling_unit self.rate = rate self.display_identifier = None self.qp_blob = None self.qp_data = None super(Source, self).__init__(*args) class SrcAddr(A2lNode): __slots__ = 'position', 'data_type' def __init__(self, position, data_type): self.position = position self.data_type = data_type super(SrcAddr, self).__init__() @a2l_node_type('SRC_ADDR_X') class SrcAddrX(SrcAddr): pass @a2l_node_type('SRC_ADDR_Y') class SrcAddrY(SrcAddr): pass @a2l_node_type('SRC_ADDR_Z') class SrcAddrZ(SrcAddr): pass @a2l_node_type('SUB_FUNCTION') class SubFunction(A2lNode): __slots__ = 'identifier', def __init__(self, args): self.identifier = list() super(SubFunction, self).__init__(*args) @a2l_node_type('SUB_GROUP') class SubGroup(A2lNode): __slots__ = 'identifier', def __init__(self, args): self.identifier = list() super(SubGroup, self).__init__(*args) @a2l_node_type('SYSTEM_CONSTANT') class SystemConstant(A2lNode): __slots__ = 'name', 'value' def __init__(self, name, value): self.name = name self.value = value super(SystemConstant, self).__init__() @a2l_node_type('TIMESTAMP_SUPPORTED') class TimestampSupported(A2lNode): __slots__ = 'timestamp_ticks', 'size', 'unit', 'timestamp_fixed' def __init__(self, timestamp_ticks, size, unit, args): self.timestamp_ticks = timestamp_ticks self.size = size self.unit = unit self.timestamp_fixed = None super(TimestampSupported, self).__init__(*args) @a2l_node_type('STIM') class Stim(A2lNode): def __init__(self,args): super(Stim, self).__init__(*args) @a2l_node_type('UNIT') class Unit(A2lNode): __slots__ = 'name', 'long_identifier', 'display', 'type', 'si_exponents', 'ref_unit', 'unit_conversion' def __init__(self, name, long_identifier, display, type, args): self.name = name self.long_identifier = long_identifier self.display = display self.type = type self.si_exponents = None self.ref_unit = None self.unit_conversion = None super(Unit, self).__init__(*args) @a2l_node_type('UNIT_CONVERSION') class UnitConversion(A2lNode): __slots__ = 'gradient', 'offset' def __init__(self, gradient, offset): self.gradient = gradient self.offset = offset super(UnitConversion, self).__init__() @a2l_node_type('USER_RIGHTS') class UserRights(A2lNode): __slots__ = 'user_level_id', 'read_only', 'ref_group' def __init__(self, user_level_id, args): self.user_level_id = user_level_id self.read_only = None self.ref_group = list() super(UserRights, self).__init__(*args) @a2l_node_type('VARIANT_CODING') class VariantCoding(A2lNode): __slots__ = 'var_separator', 'var_naming', 'var_criterion', 'var_forbidden_comb', 'var_characteristic' def __init__(self, args): self.var_separator = None self.var_naming = None self.var_criterion = list() self.var_forbidden_comb = list() self.var_characteristic = list() super(VariantCoding, self).__init__(*args) @a2l_node_type('VAR_ADDRESS') class VarAddress(A2lNode): __slots__ = 'address', def __init__(self, args): self.address = list() super(VarAddress, self).__init__(*args) @a2l_node_type('VAR_CHARACTERISTIC') class VarCharacteristic(A2lNode): __slots__ = 'name', 'criterion_name', 'var_address' def __init__(self, name, criterion_name, args): self.name = name self.criterion_name = criterion_name self.var_address = None super(VarCharacteristic, self).__init__(args) @a2l_node_type('VAR_CRITERION') class VarCriterion(A2lNode): __slots__ = 'name', 'long_identifier', 'value', 'var_measurement', 'var_selection_characteristic' def __init__(self, name, long_identifier, value, args): self.name = name self.long_identifier = long_identifier self.value = value self.var_measurement = None self.var_selection_characteristic = None super(VarCriterion, self).__init__(*args) @a2l_node_type('VAR_FORBIDDEN_COMB') class VarForbiddenComb(A2lNode): __slots__ = 'criterion_name', 'criterion_value' def __init__(self, *args): self.criterion_name = list() self.criterion_value = list() super(VarForbiddenComb, self).__init__(*args) @a2l_node_type('VIRTUAL_CHARACTERISTIC') class VirtualCharacteristic(A2lNode): __slots__ = 'formula', 'characteristic' def __init__(self, formula, args): self.formula = formula self.characteristic = list() super(VirtualCharacteristic, self).__init__(*args) @a2l_node_type('XCP_ON_CAN') class XcpOnCan(A2lNode): __slots__ = 'identifier', 'can_id_broadcast', 'can_id_master', 'can_id_slave', 'baudrate', 'sample_point', \ 'sample_rate', 'btl_cycles', 'sjw', 'sync_edge', 'daq_list_can_id' def __init__(self, identifier, args): self.identifier = identifier self.can_id_broadcast = None self.can_id_master = None self.can_id_slave = None self.baudrate = None self.sample_point = None self.sample_rate = None self.btl_cycles = None self.sjw = None self.sync_edge = None self.daq_list_can_id = list() super(XcpOnCan, self).__init__(*args) def a2l_node_factory(node_type, *args, **kwargs): try: return node_to_class[node_type](*args, **kwargs) except KeyError: raise NotImplementedError(str(node_type)) except: raise
""" @project: parser @file: node.py @author: Guillaume Sottas @date: 05.04.2018 """ node_to_class = dict() def a2l_node_type(node_type): def wrapper(cls): node_to_class[node_type] = cls cls._node = node_type return cls return wrapper class A2Lnode(object): __slots__ = ('_node', '_parent', '_children') def __init__(self, *args, **kwargs): if not isinstance(self.__slots__, tuple): raise value_error("__slot__ attribute must be a list (maybe ',' is missing at the end?).") self._parent = None self._children = list() for (attribute, value) in args: attr = getattr(self, attribute) if isinstance(attr, list): attr.append(value) elif attr is None: setattr(self, attribute, value) else: raise attribute_error(attribute) if isinstance(value, A2lNode): value.set_parent(self) self.add_children(value) def set_parent(self, a2l_node): self._parent = a2l_node def add_children(self, a2l_node): self._children.append(a2l_node) def get_properties(self): return (p for p in self.__slots__ if not p.startswith('_')) def node(self): return self._node def get_node(self, node_name): nodes = list() for node in self._children: if node.node() == node_name: nodes.append(node) nodes += node.get_node(node_name) return nodes def get_json(self): tmp = dict(node=self.node()) for p in self.properties: v = getattr(self, p) if isinstance(v, A2lNode): tmp[p] = v.json elif isinstance(v, list): tmp[p] = list() for e in v: if isinstance(e, A2lNode): tmp[p].append(e.json) else: tmp[p].append(e) else: tmp[p] = v return tmp properties = property(fget=get_properties) json = property(fget=get_json) @a2l_node_type('ROOT') class A2Lfile(A2lNode): __slots__ = ('asap2_version', 'a2ml_version', 'project') def __init__(self, args): self.asap2_version = None self.a2ml_version = None self.project = None super(A2lFile, self).__init__(*args) @a2l_node_type('VERSION') class Version(A2lNode): __slots__ = ('version_no', 'upgrade_no') def __init__(self, version_no, upgrade_no): self.version_no = version_no self.upgrade_no = upgrade_no super(Version, self).__init__() @a2l_node_type('A2ML_VERSION') class A2Mlversion(Version): pass @a2l_node_type('ADDRESS_MAPPING') class Addressmapping(A2lNode): __slots__ = ('orig_address', 'mapping_address', 'length') def __init__(self, orig_address, mapping_address, length): self.orig_address = orig_address self.mapping_address = mapping_address self.length = length super(AddressMapping, self).__init__() @a2l_node_type('ANNOTATION') class Annotation(A2lNode): __slots__ = ('annotation_label', 'annotation_origin', 'annotation_text') def __init__(self, args): self.annotation_label = None self.annotation_origin = None self.annotation_text = None super(Annotation, self).__init__(*args) @a2l_node_type('ANNOTATION_TEXT') class Annotationtext(A2lNode): __slots__ = ('annotation_text',) def __init__(self, args): self.annotation_text = list() super(AnnotationText, self).__init__(*args) @a2l_node_type('ASAP2_VERSION') class Asap2Version(Version): pass @a2l_node_type('AVAILABLE_EVENT_LIST') class Availableeventlist(A2lNode): __slots__ = ('event',) def __init__(self, args): self.event = list() super(AvailableEventList, self).__init__(*args) @a2l_node_type('AXIS_DESCR') class Axisdescr(A2lNode): __slots__ = ('attribute', 'input_quantity', 'conversion', 'max_axis_points', 'lower_limit', 'upper_limit', 'read_only', 'format', 'annotation', 'axis_pts_ref', 'max_grad', 'monotony', 'byte_order', 'extended_limits', 'fix_axis_par', 'fix_axis_par_dist', 'fix_axis_par_list', 'deposit', 'curve_axis_ref') def __init__(self, attribute, input_quantity, conversion, max_axis_points, lower_limit, upper_limit, args): self.attribute = attribute self.input_quantity = input_quantity self.conversion = conversion self.max_axis_points = max_axis_points self.lower_limit = lower_limit self.upper_limit = upper_limit self.read_only = None self.format = None self.annotation = list() self.axis_pts_ref = None self.max_grad = None self.monotony = None self.byte_order = None self.extended_limits = None self.fix_axis_par = None self.fix_axis_par_dist = None self.fix_axis_par_list = None self.deposit = None self.curve_axis_ref = None super(AxisDescr, self).__init__(*args) @a2l_node_type('AXIS_PTS') class Axispts(A2lNode): __slots__ = ('name', 'long_identifier', 'address', 'input_quantity', 'deposit', 'max_diff', 'conversion', 'max_axis_points', 'lower_limit', 'upper_limit', 'display_identifier', 'read_only', 'format', 'deposit', 'byte_order', 'function_list', 'ref_memory_segment', 'guard_rails', 'extended_limits', 'annotation', 'if_data_axis_pts', 'calibration_access', 'ecu_address_extension') def __init__(self, name, long_identifier, address, input_quantity, deposit, max_diff, conversion, max_axis_points, lower_limit, upper_limit, args): self.name = name self.long_identifier = long_identifier self.address = address self.input_quantity = input_quantity self.deposit = deposit self.max_diff = max_diff self.conversion = conversion self.max_axis_points = max_axis_points self.lower_limit = lower_limit self.upper_limit = upper_limit self.display_identifier = None self.read_only = None self.format = None self.deposit = None self.byte_order = None self.function_list = None self.ref_memory_segment = None self.guard_rails = None self.extended_limits = None self.annotation = list() self.if_data_axis_pts = list() self.calibration_access = None self.ecu_address_extension = None super(AxisPts, self).__init__(*args) class Axisptsxyz(A2lNode): __slots__ = ('position', 'data_type', 'index_incr', 'addressing') def __init__(self, position, data_type, index_incr, addressing): self.position = position self.data_type = data_type self.index_incr = index_incr self.addressing = addressing super(AxisPtsXYZ, self).__init__() @a2l_node_type('AXIS_PTS_X') class Axisptsx(AxisPtsXYZ): pass @a2l_node_type('AXIS_PTS_Y') class Axisptsy(AxisPtsXYZ): pass @a2l_node_type('AXIS_PTS_Z') class Axisptsz(AxisPtsXYZ): pass class Axisrescale(A2lNode): __slots__ = ('position', 'data_type', 'max_number_of_rescale_pairs', 'index_incr', 'addressing') def __init__(self, position, data_type, max_number_of_rescale_pairs, index_incr, addressing): self.position = position self.data_type = data_type self.max_number_of_rescale_pairs = max_number_of_rescale_pairs self.index_incr = index_incr self.addressing = addressing super(AxisRescale, self).__init__() @a2l_node_type('AXIS_RESCALE_X') class Axisrescalex(AxisRescale): pass @a2l_node_type('AXIS_RESCALE_Y') class Axisrescaley(AxisRescale): pass @a2l_node_type('AXIS_RESCALE_Z') class Axisrescalez(AxisRescale): pass @a2l_node_type('BIT_OPERATION') class Bitoperation(A2lNode): __slots__ = ('left_shift', 'right_shift', 'sign_extend') def __init__(self, args): self.left_shift = None self.right_shift = None self.sign_extend = None super(BitOperation, self).__init__(*args) @a2l_node_type('CALIBRATION_METHOD') class Calibrationmethod(A2lNode): __slots__ = ('method', 'version', 'calibration_handle') def __init__(self, method, version, args): self.method = method self.version = version self.calibration_handle = list() super(CalibrationMethod, self).__init__(*args) @a2l_node_type('CHARACTERISTIC') class Characteristic(A2lNode): __slots__ = ('name', 'long_identifier', 'type', 'address', 'deposit', 'max_diff', 'conversion', 'lower_limit', 'upper_limit', 'display_identifier', 'format', 'byte_order', 'bit_mask', 'function_list', 'number', 'extended_limits', 'read_only', 'guard_rails', 'map_list', 'max_refresh', 'dependent_characteristic', 'virtual_characteristic', 'ref_memory_segment', 'annotation', 'comparison_quantity', 'if_data_characteristic', 'axis_descr', 'calibration_access', 'matrix_dim', 'ecu_address_extension', 'symbol_link') def __init__(self, name, long_identifier, type, address, deposit, max_diff, conversion, lower_limit, upper_limit, args): self.name = name self.long_identifier = long_identifier self.type = type self.address = address self.deposit = deposit self.max_diff = max_diff self.conversion = conversion self.lower_limit = lower_limit self.upper_limit = upper_limit self.display_identifier = None self.format = None self.byte_order = None self.bit_mask = None self.function_list = None self.number = None self.symbol_link = None self.extended_limits = None self.read_only = None self.guard_rails = None self.map_list = None self.max_refresh = None self.dependent_characteristic = None self.virtual_characteristic = None self.ref_memory_segment = None self.annotation = list() self.comparison_quantity = None self.if_data_characteristic = list() self.axis_descr = list() self.calibration_access = None self.matrix_dim = None self.ecu_address_extension = None super(Characteristic, self).__init__(*args) @a2l_node_type('CHECKSUM') class Checksum(A2lNode): __slots__ = ('checksum_dll', 'max_block_size') def __init__(self, checksum_dll, max_block_size): self.checksum_dll = checksum_dll self.max_block_size = max_block_size super(Checksum, self).__init__() @a2l_node_type('COEFFS') class Coeffs(A2lNode): __slots__ = ('a', 'b', 'c', 'd', 'e', 'f') def __init__(self, a, b, c, d, e, f): self.a = a self.b = b self.c = c self.d = d self.e = e self.f = f super(Coeffs, self).__init__() @a2l_node_type('COMPU_METHOD') class Compumethod(A2lNode): __slots__ = ('name', 'long_identifier', 'conversion_type', 'format', 'unit', 'formula', 'coeffs', 'coeffs_linear', 'compu_tab_ref', 'ref_unit') def __init__(self, name, long_identifier, conversion_type, format, unit, args): self.name = name self.long_identifier = long_identifier self.conversion_type = conversion_type self.format = format self.unit = unit self.formula = None self.coeffs = None self.coeffs_linear = None self.compu_tab_ref = None self.ref_unit = None super(CompuMethod, self).__init__(*args) @a2l_node_type('COMPU_TAB') class Computab(A2lNode): __slots__ = ('name', 'long_identifier', 'conversion_type', 'number_value_pairs', 'in_val_out_val', 'default_value', 'default_value_numeric') def __init__(self, name, long_identifier, conversion_type, number_value_pairs, args): self.name = name self.long_identifier = long_identifier self.conversion_type = conversion_type self.number_value_pairs = number_value_pairs self.in_val_out_val = None self.default_value = None self.default_value_numeric = None super(CompuTab, self).__init__(*args) @a2l_node_type('COMPU_VTAB') class Compuvtab(A2lNode): __slots__ = ('name', 'long_identifier', 'conversion_type', 'number_value_pairs', 'compu_vtab_in_val_out_val', 'default_value') def __init__(self, name, long_identifier, conversion_type, number_value_pairs, args): self.name = name self.long_identifier = long_identifier self.conversion_type = conversion_type self.number_value_pairs = number_value_pairs self.compu_vtab_in_val_out_val = None self.default_value = None super(CompuVTab, self).__init__(*args) @a2l_node_type('COMPU_VTAB_RANGE') class Compuvtabrange(A2lNode): __slots__ = ('name', 'long_identifier', 'number_value_triples', 'compu_vtab_range_in_val_out_val', 'default_value') def __init__(self, name, long_identifier, number_value_triples, args): self.name = name self.long_identifier = long_identifier self.number_value_triples = number_value_triples self.compu_vtab_range_in_val_out_val = None self.default_value = None super(CompuVTabRange, self).__init__(*args) @a2l_node_type('DAQ') class Daq(A2lNode): __slots__ = ('daq_config_type', 'max_daq', 'max_event_channel', 'min_daq', 'optimisation_type', 'address_extension', 'identification_field_type', 'granularity_odt_entry', 'max_odt_entry_size_daq', 'overload_indication', 'prescaler_supported', 'resume_supported', 'daq_list', 'timestamp_supported', 'event', 'EVENT', 'IDENT', 'NUMERIC', 'stim') def __init__(self, daq_config_type, max_daq, max_event_channel, min_daq, optimisation_type, address_extension, identification_field_type, granularity_odt_entry, max_odt_entry_size_daq, overload_indication, args): self.daq_config_type = daq_config_type self.max_daq = max_daq self.max_event_channel = max_event_channel self.min_daq = min_daq self.optimisation_type = optimisation_type self.address_extension = address_extension self.identification_field_type = identification_field_type self.granularity_odt_entry = granularity_odt_entry self.max_odt_entry_size_daq = max_odt_entry_size_daq self.overload_indication = overload_indication self.prescaler_supported = None self.resume_supported = None self.daq_list = list() self.timestamp_supported = list() self.stim = list() self.event = list() self.EVENT = list() self.IDENT = list() self.NUMERIC = list() super(Daq, self).__init__(*args) @a2l_node_type('DAQ_EVENT') class Daqevent(A2lNode): __slots__ = ('name', 'available_event_list', 'default_event_list') def __init__(self, name, args): self.name = name self.available_event_list = list() self.default_event_list = list() super(DaqEvent, self).__init__(*args) @a2l_node_type('DAQ_LIST') class Daqlist(A2lNode): __slots__ = ('daq_list_number', 'daq_list_type', 'max_odt', 'max_odt_entries', 'first_pid', 'event_fixed', 'predefined') def __init__(self, daq_list_number, args): self.daq_list_number = daq_list_number self.daq_list_type = None self.max_odt = None self.max_odt_entries = None self.first_pid = None self.event_fixed = None self.predefined = list() super(DaqList, self).__init__(*args) @a2l_node_type('DAQ_LIST_CAN_ID') class Daqlistcanid(A2lNode): __slots__ = ('identifier', 'daq_list_can_id_type_fixed', 'daq_list_can_id_type_variable') def __init__(self, identifier, args): self.identifier = identifier self.daq_list_can_id_type_fixed = None self.daq_list_can_id_type_variable = None super(DaqListCanId, self).__init__(*args) @a2l_node_type('DEFAULT_EVENT_LIST') class Defaulteventlist(A2lNode): __slots__ = ('event',) def __init__(self, args): self.event = list() super(DefaultEventList, self).__init__(*args) @a2l_node_type('DEF_CHARACTERISTIC') class Defcharacteristic(A2lNode): __slots__ = ('identifier',) def __init__(self, args): self.identifier = list() super(DefCharacteristic, self).__init__(*args) @a2l_node_type('DEPENDENT_CHARACTERISTIC') class Dependentcharacteristic(A2lNode): __slots__ = ('formula', 'characteristic') def __init__(self, formula, args): self.formula = formula self.characteristic = list() super(DependentCharacteristic, self).__init__(*args) class Distop(A2lNode): __slots__ = ('position', 'data_type') def __init__(self, position, data_type): self.position = position self.data_type = data_type super(DistOp, self).__init__() @a2l_node_type('DIST_OP_X') class Distopx(DistOp): pass @a2l_node_type('DIST_OP_Y') class Distopy(DistOp): pass @a2l_node_type('DIST_OP_Z') class Distopz(DistOp): pass @a2l_node_type('EVENT') class Event(A2lNode): __slots__ = ('name', 'short_name', 'event_channel_number', 'daq_list_type', 'max_daq_list', 'time_cycle', 'time_unit', 'priority') def __init__(self, name, short_name, event_channel_number, daq_list_type, max_daq_list, time_cycle, time_unit, priority): self.name = name self.short_name = short_name self.event_channel_number = event_channel_number self.daq_list_type = daq_list_type self.max_daq_list = max_daq_list self.time_cycle = time_cycle self.time_unit = time_unit self.priority = priority super(Event, self).__init__() @a2l_node_type('EVENT_GROUP') class Eventgroup(A2lNode): __slots__ = ('raster_grp_name', 'short_name', 'raster_id') def __init__(self, raster_grp_name, short_name, raster_id): self.raster_grp_name = raster_grp_name self.short_name = short_name self.raster_id = raster_id super(EventGroup, self).__init__() @a2l_node_type('FIX_AXIS_PAR') class Fixaxispar(A2lNode): __slots__ = ('offset', 'shift', 'numberapo') def __init__(self, offset, shift, numberapo): self.offset = offset self.shift = shift self.numberapo = numberapo super(FixAxisPar, self).__init__() @a2l_node_type('FIX_AXIS_PAR_DIST') class Fixaxispardist(FixAxisPar): __slots__ = ('offset', 'distance', 'numberapo') def __init__(self, offset, distance, numberapo): self.offset = offset self.distance = distance self.numberapo = numberapo super(FixAxisPar, self).__init__() class Fixnoaxispts(A2lNode): __slots__ = ('number_of_axis_points',) def __init__(self, number_of_axis_points): self.number_of_axis_points = number_of_axis_points super(FixNoAxisPts, self).__init__() @a2l_node_type('FIX_NO_AXIS_PTS_X') class Fixnoaxisptsx(FixNoAxisPts): pass @a2l_node_type('FIX_NO_AXIS_PTS_Y') class Fixnoaxisptsy(FixNoAxisPts): pass @a2l_node_type('FIX_NO_AXIS_PTS_Z') class Fixnoaxisptsz(FixNoAxisPts): pass @a2l_node_type('FNC_VALUES') class Fncvalues(A2lNode): __slots__ = ('position', 'data_type', 'index_mode', 'addresstype') def __init__(self, position, data_type, index_mode, addresstype): self.position = position self.data_type = data_type self.index_mode = index_mode self.addresstype = addresstype super(FncValues, self).__init__() @a2l_node_type('FORMULA') class Formula(A2lNode): __slots__ = ('f', 'formula_inv') def __init__(self, f, args): self.f = f self.formula_inv = None super(Formula, self).__init__(*args) @a2l_node_type('FRAME') class Frame(A2lNode): __slots__ = ('name', 'long_identifier', 'scaling_unit', 'rate', 'frame_measurement', 'if_data_frame') def __init__(self, name, long_identifier, scaling_unit, rate, args): self.name = name self.long_identifier = long_identifier self.scaling_unit = scaling_unit self.rate = rate self.frame_measurement = None self.if_data_frame = list() super(Frame, self).__init__(*args) @a2l_node_type('FRAME_MEASUREMENT') class Framemeasurement(A2lNode): __slots__ = ('identifier',) def __init__(self, args): self.identifier = list() super(FrameMeasurement, self).__init__(*args) @a2l_node_type('FUNCTION') class Function(A2lNode): __slots__ = ('name', 'long_identifier', 'annotation', 'def_characteristic', 'ref_characteristic', 'in_measurement', 'out_measurement', 'loc_measurement', 'sub_function', 'function_version') def __init__(self, name, long_identifier, args): self.name = name self.long_identifier = long_identifier self.annotation = list() self.def_characteristic = None self.ref_characteristic = None self.in_measurement = None self.out_measurement = None self.loc_measurement = None self.sub_function = None self.function_version = None super(Function, self).__init__(*args) @a2l_node_type('FUNCTION_LIST') class Functionlist(A2lNode): __slots__ = ('name',) def __init__(self, args): self.name = list() super(FunctionList, self).__init__(*args) @a2l_node_type('GROUP') class Group(A2lNode): __slots__ = ('group_name', 'group_long_identifier', 'annotation', 'root', 'ref_characteristic', 'ref_measurement', 'function_list', 'sub_group') def __init__(self, group_name, group_long_identifier, args): self.group_name = group_name self.group_long_identifier = group_long_identifier self.annotation = list() self.root = None self.ref_characteristic = None self.ref_measurement = None self.function_list = None self.sub_group = None super(Group, self).__init__(*args) @a2l_node_type('HEADER') class Header(A2lNode): __slots__ = ('comment', 'version', 'project_no') def __init__(self, comment, args): self.comment = comment self.version = None self.project_no = None super(Header, self).__init__(*args) @a2l_node_type('IDENTIFICATION') class Identification(A2lNode): __slots__ = ('position', 'data_type') def __init__(self, position, data_type): self.position = position self.data_type = data_type super(Identification, self).__init__() @a2l_node_type('if_data_frame') class Ifdataframe(A2lNode): __slots__ = ('name',) def __init__(self, name, args): self.name = name super(IfDataFrame, self).__init__(*args) @a2l_node_type('if_data_memory_segment') class Ifdatamemorysegment(A2lNode): __slots__ = ('name', 'address_mapping', 'segment', 'generic_parameter') def __init__(self, name, args): self.name = name self.address_mapping = list() self.segment = list() self.generic_parameter = list() super(IfDataMemorySegment, self).__init__(*args) @a2l_node_type('if_data_module') class Ifdatamodule(A2lNode): __slots__ = ('name', 'source', 'raster', 'event_group', 'seed_key', 'checksum', 'tp_blob', 'tp_data', 'if_data_module_unsupported_element') def __init__(self, name, args): self.name = name self.source = list() self.raster = list() self.event_group = list() self.seed_key = None self.checksum = None self.tp_blob = None self.tp_data = None self.if_data_module_unsupported_element = None super(IfDataModule, self).__init__(*args) @a2l_node_type('if_data_xcp') class Ifdataxcp(A2lNode): __slots__ = ('protocol_layer', 'daq', 'pag', 'pgm', 'segment', 'daq_event', 'xcp_on_can', 'generic_parameter_list') def __init__(self, args): self.protocol_layer = list() self.daq = list() self.pag = list() self.pgm = list() self.segment = list() self.daq_event = list() self.xcp_on_can = list() self.generic_parameter_list = None super(IfDataXcp, self).__init__(*args) @a2l_node_type('IN_MEASUREMENT') class Inmeasurement(A2lNode): __slots__ = ('identifier',) def __init__(self, args): self.identifier = list() super(InMeasurement, self).__init__(*args) @a2l_node_type('LOC_MEASUREMENT') class Locmeasurement(A2lNode): __slots__ = ('identifier',) def __init__(self, args): self.identifier = list() super(LocMeasurement, self).__init__(*args) @a2l_node_type('MAX_REFRESH') class Maxrefresh(A2lNode): __slots__ = ('scaling_unit', 'rate') def __init__(self, scaling_unit, rate): self.scaling_unit = scaling_unit self.rate = rate super(MaxRefresh, self).__init__() @a2l_node_type('MEASUREMENT') class Measurement(A2lNode): __slots__ = ('name', 'long_identifier', 'data_type', 'conversion', 'resolution', 'accuracy', 'lower_limit', 'upper_limit', 'display_identifier', 'read_write', 'format', 'array_size', 'bit_mask', 'bit_operation', 'byte_order', 'max_refresh', 'virtual', 'function_list', 'ecu_address', 'error_mask', 'ref_memory_segment', 'annotation', 'if_data_xcp', 'if_data_measurement', 'matrix_dim', 'ecu_address_extension', 'symbol_link') def __init__(self, name, long_identifier, data_type, conversion, resolution, accuracy, lower_limit, upper_limit, args): self.name = name self.long_identifier = long_identifier self.data_type = data_type self.conversion = conversion self.resolution = resolution self.accuracy = accuracy self.lower_limit = lower_limit self.upper_limit = upper_limit self.display_identifier = None self.read_write = None self.symbol_link = None self.format = None self.array_size = None self.bit_mask = None self.bit_operation = None self.byte_order = None self.max_refresh = None self.virtual = None self.function_list = None self.ecu_address = None self.error_mask = None self.ref_memory_segment = None self.annotation = list() self.if_data_xcp = list() self.if_data_measurement = list() self.matrix_dim = None self.ecu_address_extension = None super(Measurement, self).__init__(*args) @a2l_node_type('MEMORY_LAYOUT') class Memorylayout(A2lNode): __slots__ = ('prg_type', 'address', 'size', 'offset', 'if_data_memory_layout') def __init__(self, prg_type, address, size, offset, args): self.prg_type = prg_type self.address = address self.size = size self.offset = offset self.if_data_memory_layout = list() super(MemoryLayout, self).__init__(*args) @a2l_node_type('MEMORY_SEGMENT') class Memorysegment(A2lNode): __slots__ = ('name', 'long_identifier', 'prg_type', 'memory_type', 'attribute', 'address', 'size', 'offset', 'if_data_memory_segment', 'if_data_xcp') def __init__(self, name, long_identifier, prg_type, memory_type, attribute, address, size, offset, args): self.name = name self.long_identifier = long_identifier self.prg_type = prg_type self.memory_type = memory_type self.attribute = attribute self.address = address self.size = size self.offset = offset self.if_data_memory_segment = list() self.if_data_xcp = list() super(MemorySegment, self).__init__(*args) @a2l_node_type('MODULE') class Module(A2lNode): __slots__ = ('name', 'long_identifier', 'a2ml', 'mod_par', 'mod_common', 'if_data_xcp', 'if_data_module', 'characteristic', 'axis_pts', 'measurement', 'compu_method', 'compu_tab', 'compu_vtab', 'compu_vtab_range', 'function', 'group', 'record_layout', 'variant_coding', 'frame', 'user_rights', 'unit') def __init__(self, name, long_identifier, args): self.name = name self.long_identifier = long_identifier self.a2ml = None self.mod_par = None self.mod_common = None self.if_data_xcp = None self.if_data_module = list() self.characteristic = list() self.axis_pts = list() self.measurement = list() self.compu_method = list() self.compu_tab = list() self.compu_vtab = list() self.compu_vtab_range = list() self.function = list() self.group = list() self.record_layout = list() self.variant_coding = None self.frame = None self.user_rights = list() self.unit = list() super(Module, self).__init__(*args) @a2l_node_type('MOD_COMMON') class Modcommon(A2lNode): __slots__ = ('comment', 's_rec_layout', 'deposit', 'byte_order', 'data_size', 'alignment_byte', 'alignment_word', 'alignment_long', 'alignment_float32_ieee', 'alignment_float64_ieee', 'alignment_int64') def __init__(self, comment, args): self.comment = comment self.s_rec_layout = None self.deposit = None self.byte_order = None self.data_size = None self.alignment_byte = None self.alignment_word = None self.alignment_long = None self.alignment_int64 = None self.alignment_float32_ieee = None self.alignment_float64_ieee = None super(ModCommon, self).__init__(*args) @a2l_node_type('MOD_PAR') class Modpar(A2lNode): __slots__ = ('comment', 'version', 'addr_epk', 'epk', 'supplier', 'customer', 'customer_no', 'user', 'phone_no', 'ecu', 'cpu_type', 'no_of_interfaces', 'ecu_calibration_offset', 'calibration_method', 'memory_layout', 'memory_segment', 'system_constant') def __init__(self, comment, args): self.comment = comment self.version = None self.addr_epk = list() self.epk = None self.supplier = None self.customer = None self.customer_no = None self.user = None self.phone_no = None self.ecu = None self.cpu_type = None self.no_of_interfaces = None self.ecu_calibration_offset = None self.calibration_method = list() self.memory_layout = list() self.memory_segment = list() self.system_constant = list() super(ModPar, self).__init__(*args) class Noaxispts(A2lNode): __slots__ = ('position', 'data_type') def __init__(self, position, data_type): self.position = position self.data_type = data_type super(NoAxisPts, self).__init__() @a2l_node_type('NO_AXIS_PTS_X') class Noaxisptsx(NoAxisPts): pass @a2l_node_type('NO_AXIS_PTS_Y') class Noaxisptsy(NoAxisPts): pass @a2l_node_type('NO_AXIS_PTS_Z') class Noaxisptsz(NoAxisPts): pass class Norescale(A2lNode): __slots__ = ('position', 'data_type') def __init__(self, position, data_type): self.position = position self.data_type = data_type super(NoRescale, self).__init__() @a2l_node_type('NO_RESCALE_X') class Norescalex(NoRescale): pass @a2l_node_type('NO_RESCALE_Y') class Norescaley(NoRescale): pass @a2l_node_type('NO_RESCALE_Z') class Norescalez(NoRescale): pass class Offset(A2lNode): __slots__ = ('position', 'data_type') def __init__(self, position, data_type): self.position = position self.data_type = data_type super(Offset, self).__init__() @a2l_node_type('OFFSET_X') class Offsetx(Offset): pass @a2l_node_type('OFFSET_Y') class Offsety(Offset): pass @a2l_node_type('OFFSET_Z') class Offsetz(Offset): pass @a2l_node_type('OUT_MEASUREMENT') class Outmeasurement(A2lNode): __slots__ = ('identifier',) def __init__(self, args): self.identifier = list() super(OutMeasurement, self).__init__(*args) @a2l_node_type('PAG') class Pag(A2lNode): __slots__ = ('max_segments', 'freeze_supported') def __init__(self, max_segments, args): self.max_segments = max_segments self.freeze_supported = None super(Pag, self).__init__(*args) @a2l_node_type('PGM') class Pgm(A2lNode): __slots__ = ('mode', 'max_sectors', 'max_cto_pgm', 'sector', 'generic_parameter_list') def __init__(self, mode, max_sectors, max_cto_pgm, args): self.mode = mode self.max_sectors = max_sectors self.max_cto_pgm = max_cto_pgm self.sector = list() self.generic_parameter_list = None super(Pgm, self).__init__(*args) @a2l_node_type('PROJECT') class Project(A2lNode): __slots__ = ('name', 'long_identifier', 'header', 'module') def __init__(self, name, long_identifier, args): self.name = name self.long_identifier = long_identifier self.header = None self.module = list() super(Project, self).__init__(*args) @a2l_node_type('PROTOCOL_LAYER') class Protocollayer(A2lNode): __slots__ = ('xcp_protocol_layer_version', 't1', 't2', 't3', 't4', 't5', 't6', 't7', 'max_cto', 'max_dto') def __init__(self, xcp_protocol_layer_version, t1, t2, t3, t4, t5, t6, t7, max_cto, max_dto): self.xcp_protocol_layer_version = xcp_protocol_layer_version self.t1 = t1 self.t2 = t2 self.t3 = t3 self.t4 = t4 self.t5 = t5 self.t6 = t6 self.t7 = t7 self.max_cto = max_cto self.max_dto = max_dto super(ProtocolLayer, self).__init__() @a2l_node_type('RASTER') class Raster(A2lNode): __slots__ = ('raster_name', 'short_name', 'raster_id', 'scaling_unit', 'rate') def __init__(self, raster_name, short_name, raster_id, scaling_unit, rate): self.raster_name = raster_name self.short_name = short_name self.raster_id = raster_id self.scaling_unit = scaling_unit self.rate = rate super(Raster, self).__init__() @a2l_node_type('RECORD_LAYOUT') class Recordlayout(A2lNode): __slots__ = ('name', 'fnc_values', 'identification', 'axis_pts_x', 'axis_pts_y', 'axis_pts_z', 'axis_rescale_x', 'axis_rescale_y', 'axis_rescale_z', 'no_axis_pts_x', 'no_axis_pts_y', 'no_axis_pts_z', 'no_rescale_x', 'no_rescale_y', 'no_rescale_z', 'fix_no_axis_pts_x', 'fix_no_axis_pts_y', 'fix_no_axis_pts_z', 'src_addr_x', 'src_addr_y', 'src_addr_z', 'rip_addr_x', 'rip_addr_y', 'rip_addr_z', 'rip_addr_w', 'shift_op_x', 'shift_op_y', 'shift_op_z', 'offset_x', 'offset_y', 'offset_z', 'dist_op_x', 'dist_op_y', 'dist_op_z', 'alignment_byte', 'alignment_word', 'alignment_long', 'alignment_float32_ieee', 'alignment_float64_ieee', 'reserved', 'alignment_int64') def __init__(self, name, args): self.name = name self.fnc_values = None self.identification = None self.axis_pts_x = None self.axis_pts_y = None self.axis_pts_z = None self.axis_rescale_x = None self.axis_rescale_y = None self.axis_rescale_z = None self.no_axis_pts_x = None self.no_axis_pts_y = None self.no_axis_pts_z = None self.no_rescale_x = None self.no_rescale_y = None self.no_rescale_z = None self.fix_no_axis_pts_x = None self.fix_no_axis_pts_y = None self.fix_no_axis_pts_z = None self.src_addr_x = None self.src_addr_y = None self.src_addr_z = None self.rip_addr_x = None self.rip_addr_y = None self.rip_addr_z = None self.rip_addr_w = None self.shift_op_x = None self.shift_op_y = None self.shift_op_z = None self.offset_x = None self.offset_y = None self.offset_z = None self.dist_op_x = None self.dist_op_y = None self.dist_op_z = None self.alignment_byte = None self.alignment_word = None self.alignment_long = None self.alignment_float32_ieee = None self.alignment_float64_ieee = None self.alignment_int64 = None self.reserved = list() super(RecordLayout, self).__init__(*args) @a2l_node_type('REF_CHARACTERISTIC') class Refcharacteristic(A2lNode): __slots__ = ('identifier',) def __init__(self, args): self.identifier = list() super(RefCharacteristic, self).__init__(*args) @a2l_node_type('REF_GROUP') class Refgroup(A2lNode): __slots__ = ('identifier',) def __init__(self, args): self.identifier = list() super(RefGroup, self).__init__(*args) @a2l_node_type('REF_MEASUREMENT') class Refmeasurement(A2lNode): __slots__ = ('identifier',) def __init__(self, args): self.identifier = list() super(RefMeasurement, self).__init__(*args) @a2l_node_type('RESERVED') class Reserved(A2lNode): __slots__ = ('position', 'data_size') def __init__(self, position, data_size): self.position = position self.data_size = data_size super(Reserved, self).__init__() class Ripaddr(A2lNode): __slots__ = ('position', 'data_type') def __init__(self, position, data_type): self.position = position self.data_type = data_type super(RipAddr, self).__init__() @a2l_node_type('RIP_ADDR_X') class Ripaddrx(RipAddr): pass @a2l_node_type('RIP_ADDR_Y') class Ripaddry(RipAddr): pass @a2l_node_type('RIP_ADDR_Z') class Ripaddrz(RipAddr): pass @a2l_node_type('RIP_ADDR_W') class Ripaddrw(RipAddr): pass @a2l_node_type('SECTOR') class Sector(A2lNode): __slots__ = ('name', 'sector_number', 'address', 'length', 'erase_number', 'program_number', 'programming_method') def __init__(self, name, sector_number, address, length, erase_number, program_number, programming_method): self.name = name self.sector_number = sector_number self.address = address self.length = length self.erase_number = erase_number self.program_number = program_number self.programming_method = programming_method super(Sector, self).__init__() @a2l_node_type('SEED_KEY') class Seedkey(A2lNode): __slots__ = ('cal_dll', 'daq_dll', 'pgm_dll') def __init__(self, cal_dll, daq_dll, pgm_dll): self.cal_dll = cal_dll self.daq_dll = daq_dll self.pgm_dll = pgm_dll super(SeedKey, self).__init__() @a2l_node_type('SEGMENT') class Segment(A2lNode): __slots__ = ('segment_logical_number', 'number_of_pages', 'address_extension', 'compression_method', 'encryption_method', 'checksum', 'page') def __init__(self, segment_logical_number, number_of_pages, address_extension, compression_method, encryption_method, args): self.segment_logical_number = segment_logical_number self.number_of_pages = number_of_pages self.address_extension = address_extension self.compression_method = compression_method self.encryption_method = encryption_method self.checksum = None self.page = None super(Segment, self).__init__(*args) class Shiftop(A2lNode): __slots__ = ('position', 'data_type') def __init__(self, position, data_type): self.position = position self.data_type = data_type super(ShiftOp, self).__init__() @a2l_node_type('SHIFT_OP_X') class Shiftopx(ShiftOp): pass @a2l_node_type('SHIFT_OP_Y') class Shiftopy(ShiftOp): pass @a2l_node_type('SHIFT_OP_Z') class Shiftopz(ShiftOp): pass @a2l_node_type('SI_EXPONENTS') class Siexponents(A2lNode): __slots__ = ('length', 'mass', 'time', 'electric_current', 'temperature', 'amount_of_substance', 'luminous_intensity') def __init__(self, length, mass, time, electric_current, temperature, amount_of_substance, luminous_intensity): self.length = length self.mass = mass self.time = time self.electric_current = electric_current self.temperature = temperature self.amount_of_substance = amount_of_substance self.luminous_intensity = luminous_intensity super(SiExponents, self).__init__() @a2l_node_type('SOURCE') class Source(A2lNode): __slots__ = ('name', 'scaling_unit', 'rate', 'display_identifier', 'qp_blob', 'qp_data') def __init__(self, name, scaling_unit, rate, args): self.name = name self.scaling_unit = scaling_unit self.rate = rate self.display_identifier = None self.qp_blob = None self.qp_data = None super(Source, self).__init__(*args) class Srcaddr(A2lNode): __slots__ = ('position', 'data_type') def __init__(self, position, data_type): self.position = position self.data_type = data_type super(SrcAddr, self).__init__() @a2l_node_type('SRC_ADDR_X') class Srcaddrx(SrcAddr): pass @a2l_node_type('SRC_ADDR_Y') class Srcaddry(SrcAddr): pass @a2l_node_type('SRC_ADDR_Z') class Srcaddrz(SrcAddr): pass @a2l_node_type('SUB_FUNCTION') class Subfunction(A2lNode): __slots__ = ('identifier',) def __init__(self, args): self.identifier = list() super(SubFunction, self).__init__(*args) @a2l_node_type('SUB_GROUP') class Subgroup(A2lNode): __slots__ = ('identifier',) def __init__(self, args): self.identifier = list() super(SubGroup, self).__init__(*args) @a2l_node_type('SYSTEM_CONSTANT') class Systemconstant(A2lNode): __slots__ = ('name', 'value') def __init__(self, name, value): self.name = name self.value = value super(SystemConstant, self).__init__() @a2l_node_type('TIMESTAMP_SUPPORTED') class Timestampsupported(A2lNode): __slots__ = ('timestamp_ticks', 'size', 'unit', 'timestamp_fixed') def __init__(self, timestamp_ticks, size, unit, args): self.timestamp_ticks = timestamp_ticks self.size = size self.unit = unit self.timestamp_fixed = None super(TimestampSupported, self).__init__(*args) @a2l_node_type('STIM') class Stim(A2lNode): def __init__(self, args): super(Stim, self).__init__(*args) @a2l_node_type('UNIT') class Unit(A2lNode): __slots__ = ('name', 'long_identifier', 'display', 'type', 'si_exponents', 'ref_unit', 'unit_conversion') def __init__(self, name, long_identifier, display, type, args): self.name = name self.long_identifier = long_identifier self.display = display self.type = type self.si_exponents = None self.ref_unit = None self.unit_conversion = None super(Unit, self).__init__(*args) @a2l_node_type('UNIT_CONVERSION') class Unitconversion(A2lNode): __slots__ = ('gradient', 'offset') def __init__(self, gradient, offset): self.gradient = gradient self.offset = offset super(UnitConversion, self).__init__() @a2l_node_type('USER_RIGHTS') class Userrights(A2lNode): __slots__ = ('user_level_id', 'read_only', 'ref_group') def __init__(self, user_level_id, args): self.user_level_id = user_level_id self.read_only = None self.ref_group = list() super(UserRights, self).__init__(*args) @a2l_node_type('VARIANT_CODING') class Variantcoding(A2lNode): __slots__ = ('var_separator', 'var_naming', 'var_criterion', 'var_forbidden_comb', 'var_characteristic') def __init__(self, args): self.var_separator = None self.var_naming = None self.var_criterion = list() self.var_forbidden_comb = list() self.var_characteristic = list() super(VariantCoding, self).__init__(*args) @a2l_node_type('VAR_ADDRESS') class Varaddress(A2lNode): __slots__ = ('address',) def __init__(self, args): self.address = list() super(VarAddress, self).__init__(*args) @a2l_node_type('VAR_CHARACTERISTIC') class Varcharacteristic(A2lNode): __slots__ = ('name', 'criterion_name', 'var_address') def __init__(self, name, criterion_name, args): self.name = name self.criterion_name = criterion_name self.var_address = None super(VarCharacteristic, self).__init__(args) @a2l_node_type('VAR_CRITERION') class Varcriterion(A2lNode): __slots__ = ('name', 'long_identifier', 'value', 'var_measurement', 'var_selection_characteristic') def __init__(self, name, long_identifier, value, args): self.name = name self.long_identifier = long_identifier self.value = value self.var_measurement = None self.var_selection_characteristic = None super(VarCriterion, self).__init__(*args) @a2l_node_type('VAR_FORBIDDEN_COMB') class Varforbiddencomb(A2lNode): __slots__ = ('criterion_name', 'criterion_value') def __init__(self, *args): self.criterion_name = list() self.criterion_value = list() super(VarForbiddenComb, self).__init__(*args) @a2l_node_type('VIRTUAL_CHARACTERISTIC') class Virtualcharacteristic(A2lNode): __slots__ = ('formula', 'characteristic') def __init__(self, formula, args): self.formula = formula self.characteristic = list() super(VirtualCharacteristic, self).__init__(*args) @a2l_node_type('XCP_ON_CAN') class Xcponcan(A2lNode): __slots__ = ('identifier', 'can_id_broadcast', 'can_id_master', 'can_id_slave', 'baudrate', 'sample_point', 'sample_rate', 'btl_cycles', 'sjw', 'sync_edge', 'daq_list_can_id') def __init__(self, identifier, args): self.identifier = identifier self.can_id_broadcast = None self.can_id_master = None self.can_id_slave = None self.baudrate = None self.sample_point = None self.sample_rate = None self.btl_cycles = None self.sjw = None self.sync_edge = None self.daq_list_can_id = list() super(XcpOnCan, self).__init__(*args) def a2l_node_factory(node_type, *args, **kwargs): try: return node_to_class[node_type](*args, **kwargs) except KeyError: raise not_implemented_error(str(node_type)) except: raise
# -*- coding: utf-8 -*- # Copyright: (c) 2019-2021, Dell EMC """Module for PowerStore constants""" # HTTP constants GET = 'GET' POST = 'POST' PUT = 'PUT' DELETE = 'DELETE' PATCH = 'PATCH' # Default Connection Timeout in seconds TIMEOUT = 120.0 # Pagination Constants # offset is 0 and limit is 99 for first request # offset for second request OFFSET = 100 # max number of items limit in a response MAX_LIMIT = 2000 # Query params SELECT_ALL_VOLUME = {"select": "id,name,description,type,wwn,appliance_id," "state,size,creation_timestamp," "protection_policy_id,performance_policy_id," "protection_policy(name,id)," "performance_policy(name,id)," "is_replication_destination," "migration_session_id," "protection_data,location_history,type_l10n," "state_l10n,host_group(name,id),host(name,id)," "volume_groups(name,id)" } SELECT_ALL_HOST = {"select": "id,name,description,os_type," "host_group_id," "host_initiators,os_type_l10n" } SELECT_ALL_HOST_GROUP = {"select": "name,id,description,hosts(id,name)"} SELECT_ALL_VG = {"select": "id,name,description,creation_" "timestamp, member_type," "is_protectable, protection_policy_id," "migration_session_id," "is_write_order_consistent," "placement_rule,type," "is_replication_destination,protection_data," "is_importing,location_history," "member_type_l10n,type_l10n,volumes"} SELECT_ALL_VOL_GROUP = {"select": "id,name,description,creation_" "timestamp," "is_protectable, protection_policy_id," "protection_policy(name,id)," "migration_session_id," "is_write_order_consistent," "placement_rule,type," "is_replication_destination,protection_data," "is_importing,location_history," "type_l10n,volumes(name,id)"} SELECT_ID_AND_NAME = {"select": "id,name"} # For getting the list of appliances (mentioned in configuration.py) SELECT_ID_NAME_AND_MODEL = {"select": "id,name,model"} SELECT_ID = {"select": "id"} SELECT_VERSION = {"select": "release_version"} SELECT_ID_AND_PATH = {"select": "id,path"} SELECT_ALL_HOST_VOLUME_MAPPING = {"select": "id, host_id, host_group_id," "logical_unit_number"} SELECT_ALL_FILESYSTEM = {"select": "id,name, description," "parent_id, filesystem_type, size_total,size_used," "access_policy,locking_policy," "folder_rename_policy, is_smb_sync_writes_enabled," "is_smb_op_locks_enabled, is_smb_no_notify_enabled," "is_smb_notify_on_access_enabled," "is_smb_notify_on_write_enabled," "smb_notify_on_change_dir_depth," "is_async_MTime_enabled, is_quota_enabled," "grace_period, default_hard_limit," "default_soft_limit, creation_timestamp," "expiration_timestamp, last_refresh_timestamp," "last_writable_timestamp, is_modified,access_type," "creator_type, filesystem_type_l10n," "access_policy_l10n, locking_policy_l10n," "folder_rename_policy_l10n, access_type_l10n," "creator_type_l10n,nas_server(name,id)," "protection_policy(name,id)"} SELECT_ALL_NAS_SERVER = {"select": "id,name, description, operational_status," "current_node_id,preferred_node_id," "default_unix_user,default_windows_user," "current_unix_directory_service," "is_username_translation_enabled," "is_auto_user_mapping_enabled," "production_IPv4_interface_id," "production_IPv6_interface_id," "backup_IPv4_interface_id," "backup_IPv6_interface_id," "current_preferred_IPv4_interface_id," "current_preferred_IPv6_interface_id," "operational_status_l10n," "current_unix_directory_service_l10n," "file_interfaces(name,id,ip_address)," "nfs_servers,smb_servers," "file_ldaps,file_nises,file_systems(id,name)" } SELECT_ALL_SMB_SHARE = {"select": "id,name,path,description,umask," "is_continuous_availability_enabled," "is_encryption_enabled," "is_ABE_enabled,is_branch_cache_enabled," "offline_availability," "file_system(id,name,filesystem_type," "nas_server(id,name))"} # Select all tree quota SELECT_ALL_TREE_QUOTA = {"select": "id,path,description," "is_user_quotas_enforced,state," "hard_limit,soft_limit," "remaining_grace_period,size_used," "file_system(id,name,filesystem_type," "nas_server(id,name))"} # Select all user quota SELECT_ALL_USER_QUOTA = {"select": "id,tree_quota_id,uid,unix_name," "windows_name,windows_sid,state," "hard_limit,soft_limit," "remaining_grace_period,size_used," "state_l10n,file_system(id,name," "filesystem_type,nas_server(id,name))," "tree_quota(path,description,hard_limit," "soft_limit,remaining_grace_period," "size_used)"} # Select All NFS Export SELECT_ALL_NFS_EXPORT = {"select": "id, name, file_system(id, name, " "filesystem_type, nas_server(id, name)), " "path, description, default_access, " "min_security, nfs_owner_username, " "no_access_hosts, read_only_hosts, " "read_only_root_hosts, read_write_hosts, " "read_write_root_hosts, anonymous_UID, " "anonymous_GID, is_no_SUID, " "default_access_l10n, min_security_l10n"} # SELECT JOB DETAILS JOB_DETAILS_QUERY = { 'select': 'id,resource_action,resource_type,resource_id,resource_name,' 'description_l10n,state,start_time,phase,end_time,' 'estimated_completion_time,progress_percentage,parent_id,' 'root_id,user,response_body,step_order,' 'resource_action_l10n,resource_type_l10n,state_l10n,phase_l10n' } # Select cluster details CLUSTER_DETAILS_QUERY = { 'select': 'id,global_id,name,management_address,' 'storage_discovery_address,master_appliance_id,' 'appliance_count,physical_mtu,is_encryption_enabled,' 'compatibility_level,state,state_l10n' } # Network details NETWORK_DETAILS_QUERY = { 'select': 'id,type,ip_version,vlan_id,prefix_length,' 'gateway,mtu,type_l10n,ip_version_l10n' } # Role details ROLE_DETAILS_QUERY = { 'select': 'id,name,is_built_in,description' } # IP pool details IP_DETAILS_QUERY = { 'select': 'id,network_id,ip_port_id,appliance_id,node_id,address,' 'purposes,purposes_l10n' } # CHAP config details CHAP_CONFIG_DETAILS_QUERY = { 'select': 'id,mode,mode_l10n' } # Service config details SERVICE_CONFIG_DETAILS_QUERY = { 'select': 'id,appliance_id,is_ssh_enabled' } # Service user details SERVICE_USER_DETAILS_QUERY = { 'select': 'id,name,is_built_in,is_default_password' } # Local user details LOCAL_USER_DETAILS_QUERY = { 'select': 'id,name,is_built_in,is_locked,is_default_password,role_id' } # IP port details IP_PORT_DETAILS_QUERY = { 'select': 'id,partner_id,target_iqn,available_usages,current_usages,' 'bond_id,eth_port_id,veth_port_id,available_usages_l10n,' 'current_usages_l10n' } # vCenter details VCENTER_DETAILS_QUERY = { 'select': 'id,instance_uuid,address,username' } # Appliance details APPLIANCE_DETAILS_QUERY = { 'select': 'id,name,service_tag,express_service_code,model,nodes,' 'veth_ports,maintenance_windows,fc_ports,sas_ports,eth_ports,' 'software_installed,virtual_volumes,hardware,volumes,' 'ip_pool_addresses' } # Select all Snapshot EQUALS = 'eq.' # API endpoints # Software version GET_SOFTWARE_VERSION = 'https://{0}/api/rest/software_installed' # Volume endpoints VOLUME_CREATE_URL = 'https://{0}/api/rest/volume' GET_VOLUME_LIST_URL = VOLUME_CREATE_URL GET_VOLUME_DETAILS_URL = 'https://{0}/api/rest/volume/{1}' MODIFY_VOLUME_URL = 'https://{0}/api/rest/volume/{1}' DELETE_VOLUME_URL = MODIFY_VOLUME_URL MAP_VOLUME_TO_HOST_URL = 'https://{0}/api/rest/volume/{1}/attach' UNMAP_VOLUME_FROM_HOST_URL = 'https://{0}/api/rest/volume/{1}/detach' RESTORE_VOLUME_FROM_SNAPSHOT_URL = 'https://{0}/api/rest/volume/{1}/restore' GET_VOLUME_BY_NAME_URL = VOLUME_CREATE_URL CREATE_VOLUME_SNAPSHOT_URL = 'https://{0}/api/rest/volume/{1}/snapshot' # Host endpoints GET_HOST_LIST_URL = 'https://{0}/api/rest/host' GET_HOST_DETAILS_URL = 'https://{0}/api/rest/host/{1}' CREATE_HOST_URL = GET_HOST_LIST_URL MODIFY_HOST_URL = 'https://{0}/api/rest/host/{1}' DELETE_HOST_URL = MODIFY_HOST_URL ATTACH_HOST_URL = 'https://{0}/api/rest/host/{1}/attach' DETACH_HOST_URL = 'https://{0}/api/rest/host/{1}/detach' GET_HOST_BY_NAME_URL = GET_HOST_LIST_URL # Hostgroup endpoints GET_HOST_GROUP_LIST_URL = 'https://{0}/api/rest/host_group' CREATE_HOST_GROUP_URL = GET_HOST_GROUP_LIST_URL GET_HOST_GROUP_DETAILS_URL = 'https://{0}/api/rest/host_group/{1}' MODIFY_HOST_GROUP_URL = GET_HOST_GROUP_DETAILS_URL DELETE_HOST_GROUP_URL = GET_HOST_GROUP_DETAILS_URL GET_HOST_GROUP_BY_NAME_URL = 'https://{0}/api/rest/host_group' GET_HOSTS_BY_HOST_GROUP = GET_HOST_GROUP_LIST_URL # Volume Group Endpoints GET_VOLUME_GROUP_LIST_URL = 'https://{0}/api/rest/volume_group' CREATE_VOLUME_GROUP_URL = GET_VOLUME_GROUP_LIST_URL GET_VOLUME_GROUP_DETAILS_URL = 'https://{0}/api/rest/volume_group/{1}' MODIFY_VOLUME_GROUP_URL = GET_VOLUME_GROUP_DETAILS_URL DELETE_VOLUME_GROUP_URL = GET_VOLUME_GROUP_DETAILS_URL ADD_MEMBERS_TO_VOLUME_GROUP_URL = \ 'https://{0}/api/rest/volume_group/{1}/add_members' REMOVE_MEMBERS_FROM_VOLUME_GROUP_URL = \ 'https://{0}/api/rest/volume_group/{1}/remove_members' GET_VOLUME_GROUP_BY_NAME_URL = GET_VOLUME_GROUP_LIST_URL GET_VOLUMES_FROM_VOLUME_GROUP = GET_VOLUME_GROUP_LIST_URL CREATE_VOLUME_GROUP_SNAPSHOT_URL = \ 'https://{0}/api/rest/volume_group/{1}/snapshot' # Cluster endpoints GET_CLUSTER = 'https://{0}/api/rest/cluster' # Node endpoints GET_NODE = 'https://{0}/api/rest/node' # Snapshot Rule endpoints SNAPSHOT_RULE_LIST_URL = 'https://{0}/api/rest/snapshot_rule' SNAPSHOT_RULE_OBJECT_URL = 'https://{0}/api/rest/snapshot_rule/{1}' # Replication rule endpoints REPLICATION_RULE_LIST_URL = 'https://{0}/api/rest/replication_rule' REPLICATION_RULE_OBJECT_URL = 'https://{0}/api/rest/replication_rule/{1}' # Replication session endpoints REPLICATION_SESSION_LIST_URL = 'https://{0}/api/rest/replication_session' REPLICATION_SESSION_OBJECT_URL = 'https://{0}/api/rest/replication_session/{1}' REPLICATION_SESSION_SYNC_URL = 'https://{0}/api/rest/replication_session/{1}/sync' REPLICATION_SESSION_PAUSE_URL = 'https://{0}/api/rest/replication_session/{1}/pause' REPLICATION_SESSION_RESUME_URL = 'https://{0}/api/rest/replication_session/{1}/resume' REPLICATION_SESSION_FAILOVER_URL = 'https://{0}/api/rest/replication_session/{1}/failover' REPLICATION_SESSION_REPROTECT_URL = 'https://{0}/api/rest/replication_session/{1}/reprotect' # Remote system endpoints REMOTE_SYSTEM_LIST_URL = 'https://{0}/api/rest/remote_system' REMOTE_SYSTEM_OBJECT_URL = 'https://{0}/api/rest/remote_system/{1}' # Protection Policy endpoint PROTECTION_POLICY_LIST_URL = 'https://{0}/api/rest/policy' PROTECTION_POLICY_OBJECT_URL = 'https://{0}/api/rest/policy/{1}' # Host Volume Mapping endpoints HOST_VOLUME_MAPPING_URL = 'https://{0}/api/rest/host_volume_mapping' # NAS Server endpoints GET_NAS_SERVER_LIST_URL = 'https://{0}/api/rest/nas_server' GET_NAS_SERVER_DETAILS_URL = 'https://{0}/api/rest/nas_server/{1}' GET_NAS_SERVER_DETAILS_BY_NAME_URL = GET_NAS_SERVER_LIST_URL MODIFY_NAS_SERVER_URL = GET_NAS_SERVER_DETAILS_URL # NFS Export endpoints GET_NFS_EXPORT_LIST_URL = 'https://{0}/api/rest/nfs_export' GET_NFS_EXPORT_DETAILS_URL = 'https://{0}/api/rest/nfs_export/{1}' GET_NFS_EXPORT_DETAILS_BY_NAME_URL = GET_NFS_EXPORT_LIST_URL CREATE_NFS_EXPORT_URL = GET_NFS_EXPORT_LIST_URL MODIFY_NFS_EXPORT_URL = GET_NFS_EXPORT_DETAILS_URL DELETE_NFS_EXPORT_URL = GET_NFS_EXPORT_DETAILS_URL # SMB Share endpoints GET_SMB_SHARE_LIST_URL = 'https://{0}/api/rest/smb_share' CREATE_SMB_SHARE_URL = GET_SMB_SHARE_LIST_URL GET_SMB_SHARE_DETAILS_URL = 'https://{0}/api/rest/smb_share/{1}' MODIFY_SMB_SHARE_URL = GET_SMB_SHARE_DETAILS_URL DELETE_SMB_SHARE_URL = GET_SMB_SHARE_DETAILS_URL # File Tree Quota endpoints GET_TREE_QUOTA_LIST_URL = 'https://{0}/api/rest/file_tree_quota' CREATE_TREE_QUOTA_URL = GET_TREE_QUOTA_LIST_URL GET_TREE_QUOTA_DETAILS_URL = 'https://{0}/api/rest/file_tree_quota/{1}' MODIFY_TREE_QUOTA_URL = GET_TREE_QUOTA_DETAILS_URL DELETE_TREE_QUOTA_URL = GET_TREE_QUOTA_DETAILS_URL # File User Quota endpoints GET_USER_QUOTA_LIST_URL = 'https://{0}/api/rest/file_user_quota' CREATE_USER_QUOTA_URL = GET_USER_QUOTA_LIST_URL GET_USER_QUOTA_DETAILS_URL = 'https://{0}/api/rest/file_user_quota/{1}' MODIFY_USER_QUOTA_URL = GET_USER_QUOTA_DETAILS_URL # File System endpoints GET_FILE_SYSTEM_LIST_URL = 'https://{0}/api/rest/file_system' GET_FILESYSTEM_DETAILS_URL = 'https://{0}/api/rest/file_system/{1}' GET_FILESYSTEM_DETAILS_BY_NAME_URL = GET_FILE_SYSTEM_LIST_URL CREATE_FILESYSTEM_URL = GET_FILESYSTEM_DETAILS_BY_NAME_URL DELETE_FILESYSTEM_URL = GET_FILESYSTEM_DETAILS_URL MODIFY_FILESYSTEM_URL = GET_FILESYSTEM_DETAILS_URL CREATE_FILESYSTEM_SNAPSHOT_URL = 'https://{0}/api/rest/file_system/{1}/' \ 'snapshot' GET_SNAPSHOTS_FILESYSTEM_URL = GET_FILE_SYSTEM_LIST_URL # Network endpoints GET_NETWORK_DETAILS_URL = 'https://{0}/api/rest/network/{1}' GET_NETWORK_LIST_URL = 'https://{0}/api/rest/network' MODIFY_NETWORK_URL = GET_NETWORK_DETAILS_URL ADD_REMOVE_IP_PORTS = 'https://{0}/api/rest/network/{1}/scale' # Role endpoints GET_ROLE_LIST_URL = 'https://{0}/api/rest/role' GET_ROLE_DETAILS_URL = 'https://{0}/api/rest/role/{1}' # Logout endpoint LOGOUT_URL = 'https://{0}/api/rest/logout' # Login session endpoint LOGIN_SESSION = 'https://{0}/api/rest/login_session' # Local_user endpoints GET_LOCAL_USER_LIST_URL = 'https://{0}/api/rest/local_user' # IP Pool Address endpoint GET_IP_POOL_LIST_URL = 'https://{0}/api/rest/ip_pool_address' # Cluster endpoints GET_CLUSTER_DETAILS_URL = 'https://{0}/api/rest/cluster/{1}' GET_CLUSTER_LIST_URL = 'https://{0}/api/rest/cluster' MODIFY_CLUSTER_URL = GET_CLUSTER_DETAILS_URL # CHAP config endpoints GET_CHAP_CONFIG_LIST_URL = 'https://{0}/api/rest/chap_config' GET_CHAP_CONFIG_DETAILS_URL = 'https://{0}/api/rest/chap_config/{1}' MODIFY_CHAP_CONFIG_URL = GET_CHAP_CONFIG_DETAILS_URL # Service config endpoints GET_SERVICE_CONFIG_LIST_URL = 'https://{0}/api/rest/service_config' GET_SERVICE_CONFIG_DETAILS_URL = 'https://{0}/api/rest/service_config/{1}' MODIFY_SERVICE_CONFIG_URL = GET_SERVICE_CONFIG_DETAILS_URL # Service user endpoints GET_SERVICE_USER_LIST_URL = 'https://{0}/api/rest/service_user' GET_SERVICE_USER_DETAILS_URL = 'https://{0}/api/rest/service_user/{1}' MODIFY_SERVICE_USER_URL = GET_SERVICE_USER_DETAILS_URL # Local user endpoints GET_LOCAL_USER_LIST_URL = 'https://{0}/api/rest/local_user' GET_LOCAL_USER_DETAILS_URL = 'https://{0}/api/rest/local_user/{1}' MODIFY_LOCAL_USER_URL = GET_LOCAL_USER_DETAILS_URL DELETE_LOCAL_USER_URL = GET_LOCAL_USER_DETAILS_URL CREATE_LOCAL_USER_URL = GET_LOCAL_USER_LIST_URL # IP port endpoints GET_IP_PORT_DETAILS_URL = 'https://{0}/api/rest/ip_port/{1}' # Job endpoints GET_JOB_DETAILS_URL = 'https://{0}/api/rest/job/{1}' # vCenter endpoints GET_VCENTER_LIST_URL = 'https://{0}/api/rest/vcenter' GET_VCENTER_DETAILS_URL = 'https://{0}/api/rest/vcenter/{1}' MODIFY_VCENTER_URL = GET_VCENTER_DETAILS_URL # Appliance endpoints GET_APPLIANCE_LIST_URL = 'https://{0}/api/rest/appliance' GET_APPLIANCE_DETAILS_URL = 'https://{0}/api/rest/appliance/{1}'
"""Module for PowerStore constants""" get = 'GET' post = 'POST' put = 'PUT' delete = 'DELETE' patch = 'PATCH' timeout = 120.0 offset = 100 max_limit = 2000 select_all_volume = {'select': 'id,name,description,type,wwn,appliance_id,state,size,creation_timestamp,protection_policy_id,performance_policy_id,protection_policy(name,id),performance_policy(name,id),is_replication_destination,migration_session_id,protection_data,location_history,type_l10n,state_l10n,host_group(name,id),host(name,id),volume_groups(name,id)'} select_all_host = {'select': 'id,name,description,os_type,host_group_id,host_initiators,os_type_l10n'} select_all_host_group = {'select': 'name,id,description,hosts(id,name)'} select_all_vg = {'select': 'id,name,description,creation_timestamp, member_type,is_protectable, protection_policy_id,migration_session_id,is_write_order_consistent,placement_rule,type,is_replication_destination,protection_data,is_importing,location_history,member_type_l10n,type_l10n,volumes'} select_all_vol_group = {'select': 'id,name,description,creation_timestamp,is_protectable, protection_policy_id,protection_policy(name,id),migration_session_id,is_write_order_consistent,placement_rule,type,is_replication_destination,protection_data,is_importing,location_history,type_l10n,volumes(name,id)'} select_id_and_name = {'select': 'id,name'} select_id_name_and_model = {'select': 'id,name,model'} select_id = {'select': 'id'} select_version = {'select': 'release_version'} select_id_and_path = {'select': 'id,path'} select_all_host_volume_mapping = {'select': 'id, host_id, host_group_id,logical_unit_number'} select_all_filesystem = {'select': 'id,name, description,parent_id, filesystem_type, size_total,size_used,access_policy,locking_policy,folder_rename_policy, is_smb_sync_writes_enabled,is_smb_op_locks_enabled, is_smb_no_notify_enabled,is_smb_notify_on_access_enabled,is_smb_notify_on_write_enabled,smb_notify_on_change_dir_depth,is_async_MTime_enabled, is_quota_enabled,grace_period, default_hard_limit,default_soft_limit, creation_timestamp,expiration_timestamp, last_refresh_timestamp,last_writable_timestamp, is_modified,access_type,creator_type, filesystem_type_l10n,access_policy_l10n, locking_policy_l10n,folder_rename_policy_l10n, access_type_l10n,creator_type_l10n,nas_server(name,id),protection_policy(name,id)'} select_all_nas_server = {'select': 'id,name, description, operational_status,current_node_id,preferred_node_id,default_unix_user,default_windows_user,current_unix_directory_service,is_username_translation_enabled,is_auto_user_mapping_enabled,production_IPv4_interface_id,production_IPv6_interface_id,backup_IPv4_interface_id,backup_IPv6_interface_id,current_preferred_IPv4_interface_id,current_preferred_IPv6_interface_id,operational_status_l10n,current_unix_directory_service_l10n,file_interfaces(name,id,ip_address),nfs_servers,smb_servers,file_ldaps,file_nises,file_systems(id,name)'} select_all_smb_share = {'select': 'id,name,path,description,umask,is_continuous_availability_enabled,is_encryption_enabled,is_ABE_enabled,is_branch_cache_enabled,offline_availability,file_system(id,name,filesystem_type,nas_server(id,name))'} select_all_tree_quota = {'select': 'id,path,description,is_user_quotas_enforced,state,hard_limit,soft_limit,remaining_grace_period,size_used,file_system(id,name,filesystem_type,nas_server(id,name))'} select_all_user_quota = {'select': 'id,tree_quota_id,uid,unix_name,windows_name,windows_sid,state,hard_limit,soft_limit,remaining_grace_period,size_used,state_l10n,file_system(id,name,filesystem_type,nas_server(id,name)),tree_quota(path,description,hard_limit,soft_limit,remaining_grace_period,size_used)'} select_all_nfs_export = {'select': 'id, name, file_system(id, name, filesystem_type, nas_server(id, name)), path, description, default_access, min_security, nfs_owner_username, no_access_hosts, read_only_hosts, read_only_root_hosts, read_write_hosts, read_write_root_hosts, anonymous_UID, anonymous_GID, is_no_SUID, default_access_l10n, min_security_l10n'} job_details_query = {'select': 'id,resource_action,resource_type,resource_id,resource_name,description_l10n,state,start_time,phase,end_time,estimated_completion_time,progress_percentage,parent_id,root_id,user,response_body,step_order,resource_action_l10n,resource_type_l10n,state_l10n,phase_l10n'} cluster_details_query = {'select': 'id,global_id,name,management_address,storage_discovery_address,master_appliance_id,appliance_count,physical_mtu,is_encryption_enabled,compatibility_level,state,state_l10n'} network_details_query = {'select': 'id,type,ip_version,vlan_id,prefix_length,gateway,mtu,type_l10n,ip_version_l10n'} role_details_query = {'select': 'id,name,is_built_in,description'} ip_details_query = {'select': 'id,network_id,ip_port_id,appliance_id,node_id,address,purposes,purposes_l10n'} chap_config_details_query = {'select': 'id,mode,mode_l10n'} service_config_details_query = {'select': 'id,appliance_id,is_ssh_enabled'} service_user_details_query = {'select': 'id,name,is_built_in,is_default_password'} local_user_details_query = {'select': 'id,name,is_built_in,is_locked,is_default_password,role_id'} ip_port_details_query = {'select': 'id,partner_id,target_iqn,available_usages,current_usages,bond_id,eth_port_id,veth_port_id,available_usages_l10n,current_usages_l10n'} vcenter_details_query = {'select': 'id,instance_uuid,address,username'} appliance_details_query = {'select': 'id,name,service_tag,express_service_code,model,nodes,veth_ports,maintenance_windows,fc_ports,sas_ports,eth_ports,software_installed,virtual_volumes,hardware,volumes,ip_pool_addresses'} equals = 'eq.' get_software_version = 'https://{0}/api/rest/software_installed' volume_create_url = 'https://{0}/api/rest/volume' get_volume_list_url = VOLUME_CREATE_URL get_volume_details_url = 'https://{0}/api/rest/volume/{1}' modify_volume_url = 'https://{0}/api/rest/volume/{1}' delete_volume_url = MODIFY_VOLUME_URL map_volume_to_host_url = 'https://{0}/api/rest/volume/{1}/attach' unmap_volume_from_host_url = 'https://{0}/api/rest/volume/{1}/detach' restore_volume_from_snapshot_url = 'https://{0}/api/rest/volume/{1}/restore' get_volume_by_name_url = VOLUME_CREATE_URL create_volume_snapshot_url = 'https://{0}/api/rest/volume/{1}/snapshot' get_host_list_url = 'https://{0}/api/rest/host' get_host_details_url = 'https://{0}/api/rest/host/{1}' create_host_url = GET_HOST_LIST_URL modify_host_url = 'https://{0}/api/rest/host/{1}' delete_host_url = MODIFY_HOST_URL attach_host_url = 'https://{0}/api/rest/host/{1}/attach' detach_host_url = 'https://{0}/api/rest/host/{1}/detach' get_host_by_name_url = GET_HOST_LIST_URL get_host_group_list_url = 'https://{0}/api/rest/host_group' create_host_group_url = GET_HOST_GROUP_LIST_URL get_host_group_details_url = 'https://{0}/api/rest/host_group/{1}' modify_host_group_url = GET_HOST_GROUP_DETAILS_URL delete_host_group_url = GET_HOST_GROUP_DETAILS_URL get_host_group_by_name_url = 'https://{0}/api/rest/host_group' get_hosts_by_host_group = GET_HOST_GROUP_LIST_URL get_volume_group_list_url = 'https://{0}/api/rest/volume_group' create_volume_group_url = GET_VOLUME_GROUP_LIST_URL get_volume_group_details_url = 'https://{0}/api/rest/volume_group/{1}' modify_volume_group_url = GET_VOLUME_GROUP_DETAILS_URL delete_volume_group_url = GET_VOLUME_GROUP_DETAILS_URL add_members_to_volume_group_url = 'https://{0}/api/rest/volume_group/{1}/add_members' remove_members_from_volume_group_url = 'https://{0}/api/rest/volume_group/{1}/remove_members' get_volume_group_by_name_url = GET_VOLUME_GROUP_LIST_URL get_volumes_from_volume_group = GET_VOLUME_GROUP_LIST_URL create_volume_group_snapshot_url = 'https://{0}/api/rest/volume_group/{1}/snapshot' get_cluster = 'https://{0}/api/rest/cluster' get_node = 'https://{0}/api/rest/node' snapshot_rule_list_url = 'https://{0}/api/rest/snapshot_rule' snapshot_rule_object_url = 'https://{0}/api/rest/snapshot_rule/{1}' replication_rule_list_url = 'https://{0}/api/rest/replication_rule' replication_rule_object_url = 'https://{0}/api/rest/replication_rule/{1}' replication_session_list_url = 'https://{0}/api/rest/replication_session' replication_session_object_url = 'https://{0}/api/rest/replication_session/{1}' replication_session_sync_url = 'https://{0}/api/rest/replication_session/{1}/sync' replication_session_pause_url = 'https://{0}/api/rest/replication_session/{1}/pause' replication_session_resume_url = 'https://{0}/api/rest/replication_session/{1}/resume' replication_session_failover_url = 'https://{0}/api/rest/replication_session/{1}/failover' replication_session_reprotect_url = 'https://{0}/api/rest/replication_session/{1}/reprotect' remote_system_list_url = 'https://{0}/api/rest/remote_system' remote_system_object_url = 'https://{0}/api/rest/remote_system/{1}' protection_policy_list_url = 'https://{0}/api/rest/policy' protection_policy_object_url = 'https://{0}/api/rest/policy/{1}' host_volume_mapping_url = 'https://{0}/api/rest/host_volume_mapping' get_nas_server_list_url = 'https://{0}/api/rest/nas_server' get_nas_server_details_url = 'https://{0}/api/rest/nas_server/{1}' get_nas_server_details_by_name_url = GET_NAS_SERVER_LIST_URL modify_nas_server_url = GET_NAS_SERVER_DETAILS_URL get_nfs_export_list_url = 'https://{0}/api/rest/nfs_export' get_nfs_export_details_url = 'https://{0}/api/rest/nfs_export/{1}' get_nfs_export_details_by_name_url = GET_NFS_EXPORT_LIST_URL create_nfs_export_url = GET_NFS_EXPORT_LIST_URL modify_nfs_export_url = GET_NFS_EXPORT_DETAILS_URL delete_nfs_export_url = GET_NFS_EXPORT_DETAILS_URL get_smb_share_list_url = 'https://{0}/api/rest/smb_share' create_smb_share_url = GET_SMB_SHARE_LIST_URL get_smb_share_details_url = 'https://{0}/api/rest/smb_share/{1}' modify_smb_share_url = GET_SMB_SHARE_DETAILS_URL delete_smb_share_url = GET_SMB_SHARE_DETAILS_URL get_tree_quota_list_url = 'https://{0}/api/rest/file_tree_quota' create_tree_quota_url = GET_TREE_QUOTA_LIST_URL get_tree_quota_details_url = 'https://{0}/api/rest/file_tree_quota/{1}' modify_tree_quota_url = GET_TREE_QUOTA_DETAILS_URL delete_tree_quota_url = GET_TREE_QUOTA_DETAILS_URL get_user_quota_list_url = 'https://{0}/api/rest/file_user_quota' create_user_quota_url = GET_USER_QUOTA_LIST_URL get_user_quota_details_url = 'https://{0}/api/rest/file_user_quota/{1}' modify_user_quota_url = GET_USER_QUOTA_DETAILS_URL get_file_system_list_url = 'https://{0}/api/rest/file_system' get_filesystem_details_url = 'https://{0}/api/rest/file_system/{1}' get_filesystem_details_by_name_url = GET_FILE_SYSTEM_LIST_URL create_filesystem_url = GET_FILESYSTEM_DETAILS_BY_NAME_URL delete_filesystem_url = GET_FILESYSTEM_DETAILS_URL modify_filesystem_url = GET_FILESYSTEM_DETAILS_URL create_filesystem_snapshot_url = 'https://{0}/api/rest/file_system/{1}/snapshot' get_snapshots_filesystem_url = GET_FILE_SYSTEM_LIST_URL get_network_details_url = 'https://{0}/api/rest/network/{1}' get_network_list_url = 'https://{0}/api/rest/network' modify_network_url = GET_NETWORK_DETAILS_URL add_remove_ip_ports = 'https://{0}/api/rest/network/{1}/scale' get_role_list_url = 'https://{0}/api/rest/role' get_role_details_url = 'https://{0}/api/rest/role/{1}' logout_url = 'https://{0}/api/rest/logout' login_session = 'https://{0}/api/rest/login_session' get_local_user_list_url = 'https://{0}/api/rest/local_user' get_ip_pool_list_url = 'https://{0}/api/rest/ip_pool_address' get_cluster_details_url = 'https://{0}/api/rest/cluster/{1}' get_cluster_list_url = 'https://{0}/api/rest/cluster' modify_cluster_url = GET_CLUSTER_DETAILS_URL get_chap_config_list_url = 'https://{0}/api/rest/chap_config' get_chap_config_details_url = 'https://{0}/api/rest/chap_config/{1}' modify_chap_config_url = GET_CHAP_CONFIG_DETAILS_URL get_service_config_list_url = 'https://{0}/api/rest/service_config' get_service_config_details_url = 'https://{0}/api/rest/service_config/{1}' modify_service_config_url = GET_SERVICE_CONFIG_DETAILS_URL get_service_user_list_url = 'https://{0}/api/rest/service_user' get_service_user_details_url = 'https://{0}/api/rest/service_user/{1}' modify_service_user_url = GET_SERVICE_USER_DETAILS_URL get_local_user_list_url = 'https://{0}/api/rest/local_user' get_local_user_details_url = 'https://{0}/api/rest/local_user/{1}' modify_local_user_url = GET_LOCAL_USER_DETAILS_URL delete_local_user_url = GET_LOCAL_USER_DETAILS_URL create_local_user_url = GET_LOCAL_USER_LIST_URL get_ip_port_details_url = 'https://{0}/api/rest/ip_port/{1}' get_job_details_url = 'https://{0}/api/rest/job/{1}' get_vcenter_list_url = 'https://{0}/api/rest/vcenter' get_vcenter_details_url = 'https://{0}/api/rest/vcenter/{1}' modify_vcenter_url = GET_VCENTER_DETAILS_URL get_appliance_list_url = 'https://{0}/api/rest/appliance' get_appliance_details_url = 'https://{0}/api/rest/appliance/{1}'
#!/usr/bin/python3 #-- Use pprint module.. x=[[1,2,3,4],[11,22,33,44],[111,222,333,444]] #-- Use printf style formatting.. x = 22/7 #-- Write some multivariate for loops.. for x,y in [[1,2]]: print('x',x,'y',y) for x in enumerate(range(5)): print('x',x) #-- Compute diagonal sums with lambdas.. m=[ [ 5, 2, 3, 4, 1], [ 10, 40, 30, 20, 50], [ 100, 200, 300, 400, 500], [ 1001, 4000, 3000, 2000, 5000], [50000,20000,30000,40000,10000] ] #-- Use a list comprehension to produce a list of lists.. m=8 n=9 #-- Use a dictionary comprehension.. #-- Obtain user input to fill a list with integers (use split and strip).. #-- Open a file, write to a file.. #-- Develop a class.. #-- Use list unpacking to pass variable number of args.. #-- Use dictionary unpacking to combine two dictionaries.. #-- Use 'zip()' in an example.. #-- Use regular expressions.. #-- Convert this to a simpler expression using 'in'.. # # if socket.gethostname() == "bristle" or socket.gethostname() == "rete": # DEBUG = False # else: # DEBUG = True #-- Write something using closures.. #-- Write something using decorators..
x = [[1, 2, 3, 4], [11, 22, 33, 44], [111, 222, 333, 444]] x = 22 / 7 for (x, y) in [[1, 2]]: print('x', x, 'y', y) for x in enumerate(range(5)): print('x', x) m = [[5, 2, 3, 4, 1], [10, 40, 30, 20, 50], [100, 200, 300, 400, 500], [1001, 4000, 3000, 2000, 5000], [50000, 20000, 30000, 40000, 10000]] m = 8 n = 9
# -*- coding: utf-8 -*- class ExampleLibraryException(Exception): '''It is a good practice to throw library specific exceptions so that you know where the exception is comming''' pass class ExampleLibrary(object): '''Libraries should be documented according to Robot Framework User Guide''' def library_keyword(self): '''Document keywords as well''' return True
class Examplelibraryexception(Exception): """It is a good practice to throw library specific exceptions so that you know where the exception is comming""" pass class Examplelibrary(object): """Libraries should be documented according to Robot Framework User Guide""" def library_keyword(self): """Document keywords as well""" return True
def getNumericVal(number): if number == 1: return 3 elif number == 2: return 3 elif number == 3: return 5 elif number == 4: return 4 elif number == 5: return 4 elif number == 6: return 3 elif number == 7: return 5 elif number == 8: return 5 elif number == 9: return 4 def lessThan20(number): if number < 10: return getNumericVal(number) if number == 10: return 3 elif number == 11: return 6 elif number == 12: return 6 elif number == 13: return 8 elif number == 14: return 8 elif number == 15: return 7 elif number == 16: return 7 elif number == 17: return 9 elif number == 18: return 8 elif number == 19: return 8 def lessThan100(number): if number < 20: return lessThan20(number) value1 = number % 10 value2 = number // 10 if value2 == 2: if value1 == 0: return 6 else: return 6 + getNumericVal(value1) elif value2 == 3: if value1 == 0: return 6 else: return 6 + getNumericVal(value1) elif value2 == 4: if value1 == 0: return 5 else: return 5 + getNumericVal(value1) elif value2 == 5: if value1 == 0: return 5 else: return 5 + getNumericVal(value1) elif value2 == 6: if value1 == 0: return 5 else: return 5 + getNumericVal(value1) elif value2 == 7: if value1 == 0: return 7 else: return 7 + getNumericVal(value1) elif value2 == 8: if value1 == 0: return 6 else: return 6 + getNumericVal(value1) elif value2 == 9: if value1 == 0: return 6 else: return 6 + getNumericVal(value1) def lessThan1000(number): temp = number value1 = temp % 10 temp = temp // 10 value2 = temp % 10 temp = temp // 10 value3 = temp if value1 == 0 and value2 == 0: return getNumericVal(value3) + 7 else: return getNumericVal(value3) + 7 + 3 + lessThan100(10 * value2 + value1) def countLetters(max_val): count = 0 for i in range(1, max_val + 1): if i <= 9: count += getNumericVal(i) elif i < 100: count += lessThan100(i) elif i < 1000: count += lessThan1000(i) elif i == 1000: count += 11 return count print(countLetters(1000))
def get_numeric_val(number): if number == 1: return 3 elif number == 2: return 3 elif number == 3: return 5 elif number == 4: return 4 elif number == 5: return 4 elif number == 6: return 3 elif number == 7: return 5 elif number == 8: return 5 elif number == 9: return 4 def less_than20(number): if number < 10: return get_numeric_val(number) if number == 10: return 3 elif number == 11: return 6 elif number == 12: return 6 elif number == 13: return 8 elif number == 14: return 8 elif number == 15: return 7 elif number == 16: return 7 elif number == 17: return 9 elif number == 18: return 8 elif number == 19: return 8 def less_than100(number): if number < 20: return less_than20(number) value1 = number % 10 value2 = number // 10 if value2 == 2: if value1 == 0: return 6 else: return 6 + get_numeric_val(value1) elif value2 == 3: if value1 == 0: return 6 else: return 6 + get_numeric_val(value1) elif value2 == 4: if value1 == 0: return 5 else: return 5 + get_numeric_val(value1) elif value2 == 5: if value1 == 0: return 5 else: return 5 + get_numeric_val(value1) elif value2 == 6: if value1 == 0: return 5 else: return 5 + get_numeric_val(value1) elif value2 == 7: if value1 == 0: return 7 else: return 7 + get_numeric_val(value1) elif value2 == 8: if value1 == 0: return 6 else: return 6 + get_numeric_val(value1) elif value2 == 9: if value1 == 0: return 6 else: return 6 + get_numeric_val(value1) def less_than1000(number): temp = number value1 = temp % 10 temp = temp // 10 value2 = temp % 10 temp = temp // 10 value3 = temp if value1 == 0 and value2 == 0: return get_numeric_val(value3) + 7 else: return get_numeric_val(value3) + 7 + 3 + less_than100(10 * value2 + value1) def count_letters(max_val): count = 0 for i in range(1, max_val + 1): if i <= 9: count += get_numeric_val(i) elif i < 100: count += less_than100(i) elif i < 1000: count += less_than1000(i) elif i == 1000: count += 11 return count print(count_letters(1000))
class BaseError(Exception): pass class RecordNotFound(BaseError): pass
class Baseerror(Exception): pass class Recordnotfound(BaseError): pass
# liczby Fibonacciego def fibRek(n): if n == 0 or n == 1: return n else: return fibRek(n-1) + fibRek(n-2) def fib(n): """Wypisuje liczby Fibonacciego mniejsze niz n """ a, b = 0, 1 while b < n: print (b) a, b = b, a+b def fib2(n): """Zwraca liste liczb Fibonacciego mniejszych niz n """ result = [] a, b = 0, 1 while b < n: result.append(b) a, b = b, a+b return result def silnia(n): if n == 0: return 1 elif n > 0: return n * silnia(n-1) else: return (-1)*silnia((-1)*n) def a(n): return n def b(n): return a(n)
def fib_rek(n): if n == 0 or n == 1: return n else: return fib_rek(n - 1) + fib_rek(n - 2) def fib(n): """Wypisuje liczby Fibonacciego mniejsze niz n """ (a, b) = (0, 1) while b < n: print(b) (a, b) = (b, a + b) def fib2(n): """Zwraca liste liczb Fibonacciego mniejszych niz n """ result = [] (a, b) = (0, 1) while b < n: result.append(b) (a, b) = (b, a + b) return result def silnia(n): if n == 0: return 1 elif n > 0: return n * silnia(n - 1) else: return -1 * silnia(-1 * n) def a(n): return n def b(n): return a(n)
""" Copyright 2018 abbas ehsanfar """ """ genfigs: generate figures """
""" Copyright 2018 abbas ehsanfar """ '\ngenfigs: generate figures\n'
class ArmatureActuator: bone = None constraint = None influence = None mode = None secondary_target = None target = None weight = None
class Armatureactuator: bone = None constraint = None influence = None mode = None secondary_target = None target = None weight = None
# Definition for singly-linked list. # class ListNode: # def __init__(self, val=0, next=None): # self.val = val # self.next = next class Solution: def mergeTwoLists(self, list1: Optional[ListNode], list2: Optional[ListNode]) -> Optional[ListNode]: cur = dummy = ListNode() while list1 and list2: if list1.val < list2.val: cur.next = list1 list1, cur = list1.next, list1 else: cur.next = list2 list2, cur = list2.next, list2 if list1 or list2: cur.next = list1 if list1 else list2 return dummy.next
class Solution: def merge_two_lists(self, list1: Optional[ListNode], list2: Optional[ListNode]) -> Optional[ListNode]: cur = dummy = list_node() while list1 and list2: if list1.val < list2.val: cur.next = list1 (list1, cur) = (list1.next, list1) else: cur.next = list2 (list2, cur) = (list2.next, list2) if list1 or list2: cur.next = list1 if list1 else list2 return dummy.next
file_name = "nameslist.txt" names_list = open(file_name, "rt").read().splitlines(False) print(names_list) names_count = {} for name in names_list: if name not in names_count: names_count[name] = 0 names_count[name] += 1 print(names_count)
file_name = 'nameslist.txt' names_list = open(file_name, 'rt').read().splitlines(False) print(names_list) names_count = {} for name in names_list: if name not in names_count: names_count[name] = 0 names_count[name] += 1 print(names_count)
n, d = map(int,input().split()) l=[] for i in range(n): l1=list(map(int,input().split())) l.append(l1) l=sorted(l) i, j, ans, s = 0, 0, 0, 0 while j<n: if l[i][0]+d > l[j][0]: s+=l[j][1] j+=1 else: s-=l[i][1] i+=1 ans=max(ans,s) print(ans)
(n, d) = map(int, input().split()) l = [] for i in range(n): l1 = list(map(int, input().split())) l.append(l1) l = sorted(l) (i, j, ans, s) = (0, 0, 0, 0) while j < n: if l[i][0] + d > l[j][0]: s += l[j][1] j += 1 else: s -= l[i][1] i += 1 ans = max(ans, s) print(ans)
class Atom: def __init__(self): pass def __repr__(self): raise NotImplementedError() class Tmp(Atom): __slots__ = ['tmp_idx'] def __init__(self, tmp_idx): super(Tmp, self).__init__() self.tmp_idx = tmp_idx def __repr__(self): return "<Tmp %d>" % self.tmp_idx def __eq__(self, other): return type(other) is Tmp and \ self.tmp_idx == other.tmp_idx def __hash__(self): return hash(('tmp', self.tmp_idx)) class Register(Atom): __slots__ = ['reg_offset', 'size'] def __init__(self, reg_offset, size): super(Register, self).__init__() self.reg_offset = reg_offset self.size = size def __repr__(self): return "<Reg %d<%d>>" % (self.reg_offset, self.size) def __eq__(self, other): return type(other) is Register and \ self.reg_offset == other.reg_offset and \ self.size == other.size def __hash__(self): return hash(('reg', self.reg_offset, self.size)) class MemoryLocation(Atom): __slots__ = ['addr', 'size'] def __init__(self, addr, size): super(MemoryLocation, self).__init__() self.addr = addr self.size = size def __repr__(self): return "<Mem %s<%d>>" % (hex(self.addr) if type(self.addr) is int else self.addr, self.size) @property def bits(self): return self.size * 8 @property def symbolic(self): return not type(self.addr) is int def __eq__(self, other): return type(other) is MemoryLocation and \ self.addr == other.addr and \ self.size == other.size def __hash__(self): return hash(('mem', self.addr, self.size)) class Parameter(Atom): __slots__ = ['value', 'type_', 'meta'] def __init__(self, value, type_=None, meta=None): super(Parameter, self).__init__() self.value = value self.type_ = type_ self.meta = meta def __repr__(self): type_ = ', type=%s' % self.type_ if self.type_ is not None else '' meta = ', meta=%s' % self.meta if self.meta is not None else '' return '<Param %s%s%s>' % (self.value, type_, meta) def __eq__(self, other): return type(other) is Parameter and \ self.value == other.value and \ self.type_ == other.type_ and \ self.meta == other.meta
class Atom: def __init__(self): pass def __repr__(self): raise not_implemented_error() class Tmp(Atom): __slots__ = ['tmp_idx'] def __init__(self, tmp_idx): super(Tmp, self).__init__() self.tmp_idx = tmp_idx def __repr__(self): return '<Tmp %d>' % self.tmp_idx def __eq__(self, other): return type(other) is Tmp and self.tmp_idx == other.tmp_idx def __hash__(self): return hash(('tmp', self.tmp_idx)) class Register(Atom): __slots__ = ['reg_offset', 'size'] def __init__(self, reg_offset, size): super(Register, self).__init__() self.reg_offset = reg_offset self.size = size def __repr__(self): return '<Reg %d<%d>>' % (self.reg_offset, self.size) def __eq__(self, other): return type(other) is Register and self.reg_offset == other.reg_offset and (self.size == other.size) def __hash__(self): return hash(('reg', self.reg_offset, self.size)) class Memorylocation(Atom): __slots__ = ['addr', 'size'] def __init__(self, addr, size): super(MemoryLocation, self).__init__() self.addr = addr self.size = size def __repr__(self): return '<Mem %s<%d>>' % (hex(self.addr) if type(self.addr) is int else self.addr, self.size) @property def bits(self): return self.size * 8 @property def symbolic(self): return not type(self.addr) is int def __eq__(self, other): return type(other) is MemoryLocation and self.addr == other.addr and (self.size == other.size) def __hash__(self): return hash(('mem', self.addr, self.size)) class Parameter(Atom): __slots__ = ['value', 'type_', 'meta'] def __init__(self, value, type_=None, meta=None): super(Parameter, self).__init__() self.value = value self.type_ = type_ self.meta = meta def __repr__(self): type_ = ', type=%s' % self.type_ if self.type_ is not None else '' meta = ', meta=%s' % self.meta if self.meta is not None else '' return '<Param %s%s%s>' % (self.value, type_, meta) def __eq__(self, other): return type(other) is Parameter and self.value == other.value and (self.type_ == other.type_) and (self.meta == other.meta)
# Utilities and color maps for plotting # Colours from https://s-rip.ees.hokudai.ac.jp/mediawiki/index.php/Notes_for_Authors reanalysis_color = { 'MERRA2' :'#e21f26', 'MERRA' :'#f69999', 'ERAI' :'#295f8a', 'ERA5' :'#5f98c6', 'ERA40' :'#afcbe3', 'JRA55' :'#723b7a', 'JRA55C' :'#ad71b5', 'JRA25' :'#d6b8da', 'NCEP1' :'#f57e20', 'NCEP2' :'#fdbf6e', '20CRV2C' :'#ec008c', '20CRV2' :'#f799D1', 'CERA20C' :'#00aeef', 'ERA20C' :'#60c8e8', 'CFSR' :'#34a048', 'REM' :'#b35b28', # reanalysis ensemble mean 'OTHER' :'#ffd700', 'OBS' :'#000000', # observations black 'OBS2' :'#777777', } # observations grey
reanalysis_color = {'MERRA2': '#e21f26', 'MERRA': '#f69999', 'ERAI': '#295f8a', 'ERA5': '#5f98c6', 'ERA40': '#afcbe3', 'JRA55': '#723b7a', 'JRA55C': '#ad71b5', 'JRA25': '#d6b8da', 'NCEP1': '#f57e20', 'NCEP2': '#fdbf6e', '20CRV2C': '#ec008c', '20CRV2': '#f799D1', 'CERA20C': '#00aeef', 'ERA20C': '#60c8e8', 'CFSR': '#34a048', 'REM': '#b35b28', 'OTHER': '#ffd700', 'OBS': '#000000', 'OBS2': '#777777'}
# maximum_subarray_sum.py # https://www.codewars.com/kata/54521e9ec8e60bc4de000d6c def max_sequence(arr): if len(arr) == 0: return 0 all_elements_negative = True for item in arr: if item > 0: all_elements_negative = False break if all_elements_negative: return 0 maximum_sum = max(arr) current_sum = 0 max_subarray = [] for i in range(len(arr)): current_sum = 0 for j in range(i, len(arr)): current_sum += arr[j] print(i, j, current_sum, arr[i:j+1]) if current_sum > maximum_sum: maximum_sum = current_sum max_subarray = arr[i:j+1] return maximum_sum if __name__ == "__main__": print(max_sequence([-2, 1, -3, 4, -1, 2, 1, -5, 4]))
def max_sequence(arr): if len(arr) == 0: return 0 all_elements_negative = True for item in arr: if item > 0: all_elements_negative = False break if all_elements_negative: return 0 maximum_sum = max(arr) current_sum = 0 max_subarray = [] for i in range(len(arr)): current_sum = 0 for j in range(i, len(arr)): current_sum += arr[j] print(i, j, current_sum, arr[i:j + 1]) if current_sum > maximum_sum: maximum_sum = current_sum max_subarray = arr[i:j + 1] return maximum_sum if __name__ == '__main__': print(max_sequence([-2, 1, -3, 4, -1, 2, 1, -5, 4]))
""" PASSENGERS """ numPassengers = 22944 passenger_arriving = ( (5, 6, 5, 9, 4, 1, 2, 3, 2, 1, 1, 1, 0, 7, 6, 8, 4, 8, 2, 3, 1, 0, 1, 1, 1, 0), # 0 (7, 6, 3, 10, 7, 1, 1, 1, 6, 1, 2, 1, 0, 3, 5, 7, 7, 5, 4, 5, 0, 2, 2, 0, 1, 0), # 1 (5, 3, 10, 5, 3, 3, 4, 2, 1, 1, 1, 1, 0, 9, 9, 4, 3, 5, 2, 4, 2, 4, 1, 1, 0, 0), # 2 (7, 12, 10, 9, 4, 3, 10, 0, 2, 0, 0, 1, 0, 9, 9, 7, 3, 10, 1, 1, 0, 1, 2, 0, 0, 0), # 3 (8, 6, 6, 8, 6, 3, 3, 8, 1, 2, 1, 1, 0, 13, 8, 4, 7, 5, 3, 2, 1, 6, 0, 1, 0, 0), # 4 (9, 12, 7, 8, 6, 3, 5, 5, 5, 2, 2, 1, 0, 4, 11, 8, 6, 7, 4, 5, 3, 0, 0, 1, 0, 0), # 5 (6, 8, 6, 4, 8, 3, 1, 4, 5, 5, 0, 3, 0, 6, 7, 3, 3, 10, 6, 6, 4, 1, 4, 1, 1, 0), # 6 (4, 4, 10, 5, 7, 6, 8, 4, 6, 3, 0, 2, 0, 10, 6, 3, 6, 7, 4, 1, 2, 0, 2, 3, 1, 0), # 7 (10, 7, 7, 11, 6, 1, 7, 8, 4, 1, 1, 0, 0, 11, 16, 9, 3, 8, 8, 4, 2, 4, 2, 1, 2, 0), # 8 (6, 6, 6, 11, 2, 3, 1, 1, 3, 1, 0, 1, 0, 9, 8, 7, 5, 6, 5, 3, 0, 0, 3, 0, 0, 0), # 9 (7, 8, 10, 5, 6, 4, 2, 5, 2, 0, 1, 1, 0, 13, 12, 5, 5, 9, 6, 3, 0, 4, 2, 2, 3, 0), # 10 (8, 15, 6, 15, 14, 3, 4, 0, 1, 2, 2, 1, 0, 8, 12, 10, 3, 8, 4, 4, 3, 3, 2, 0, 3, 0), # 11 (11, 13, 9, 12, 5, 2, 4, 3, 1, 2, 2, 0, 0, 11, 12, 8, 8, 9, 5, 5, 2, 6, 5, 4, 0, 0), # 12 (11, 14, 3, 13, 3, 4, 6, 4, 6, 2, 1, 1, 0, 13, 8, 7, 6, 6, 4, 3, 1, 2, 5, 6, 1, 0), # 13 (10, 11, 4, 9, 12, 4, 8, 5, 3, 0, 3, 0, 0, 8, 8, 6, 9, 7, 5, 3, 3, 2, 4, 3, 1, 0), # 14 (11, 7, 8, 14, 11, 3, 5, 3, 4, 5, 0, 1, 0, 11, 10, 6, 10, 6, 5, 3, 4, 4, 4, 2, 1, 0), # 15 (14, 17, 7, 10, 9, 3, 3, 6, 5, 3, 0, 1, 0, 11, 10, 6, 8, 8, 6, 4, 6, 6, 3, 5, 2, 0), # 16 (7, 11, 8, 5, 10, 3, 4, 5, 5, 2, 1, 1, 0, 9, 8, 6, 6, 9, 4, 6, 5, 4, 4, 4, 0, 0), # 17 (10, 10, 8, 13, 12, 4, 3, 5, 3, 1, 1, 0, 0, 14, 11, 6, 6, 3, 10, 4, 3, 2, 5, 4, 2, 0), # 18 (16, 6, 10, 8, 5, 4, 8, 3, 7, 4, 0, 0, 0, 5, 15, 6, 12, 12, 6, 5, 5, 6, 4, 1, 2, 0), # 19 (15, 10, 7, 9, 11, 7, 2, 4, 3, 4, 0, 1, 0, 9, 16, 9, 6, 9, 6, 7, 3, 4, 6, 1, 0, 0), # 20 (17, 17, 8, 17, 11, 4, 5, 5, 8, 4, 1, 2, 0, 10, 10, 11, 4, 8, 9, 6, 1, 5, 9, 2, 1, 0), # 21 (17, 19, 15, 12, 12, 4, 7, 5, 8, 3, 2, 2, 0, 11, 13, 10, 9, 5, 9, 3, 6, 7, 3, 3, 0, 0), # 22 (7, 11, 6, 12, 11, 4, 7, 3, 3, 1, 2, 0, 0, 19, 9, 4, 5, 9, 9, 5, 5, 5, 2, 4, 2, 0), # 23 (15, 11, 8, 8, 15, 7, 5, 4, 6, 2, 3, 0, 0, 13, 8, 12, 6, 11, 6, 5, 2, 7, 4, 2, 1, 0), # 24 (18, 17, 17, 5, 5, 7, 8, 6, 6, 1, 2, 0, 0, 14, 6, 6, 4, 13, 4, 4, 1, 8, 5, 0, 0, 0), # 25 (14, 10, 8, 9, 11, 4, 4, 4, 4, 1, 2, 2, 0, 19, 11, 9, 6, 9, 11, 6, 1, 1, 4, 5, 1, 0), # 26 (12, 17, 12, 11, 8, 12, 4, 8, 4, 1, 6, 1, 0, 15, 5, 7, 10, 4, 7, 2, 2, 3, 4, 1, 1, 0), # 27 (15, 17, 16, 14, 12, 3, 5, 5, 5, 1, 4, 2, 0, 6, 8, 9, 8, 4, 4, 5, 1, 4, 0, 3, 3, 0), # 28 (14, 16, 10, 15, 14, 7, 3, 5, 8, 0, 3, 0, 0, 15, 3, 10, 9, 9, 8, 3, 1, 6, 5, 2, 1, 0), # 29 (13, 15, 10, 6, 6, 4, 10, 1, 7, 3, 1, 0, 0, 11, 13, 7, 8, 12, 8, 7, 3, 3, 2, 1, 0, 0), # 30 (15, 15, 15, 15, 9, 4, 4, 3, 1, 3, 1, 1, 0, 8, 17, 8, 7, 9, 5, 7, 2, 7, 5, 4, 3, 0), # 31 (13, 11, 16, 11, 10, 3, 8, 9, 5, 2, 3, 0, 0, 4, 10, 12, 5, 12, 8, 3, 5, 3, 4, 2, 0, 0), # 32 (11, 18, 10, 12, 10, 4, 4, 3, 7, 0, 6, 1, 0, 14, 13, 12, 4, 9, 7, 7, 1, 6, 0, 0, 1, 0), # 33 (7, 16, 18, 13, 11, 3, 5, 9, 8, 4, 0, 2, 0, 13, 10, 8, 3, 10, 4, 4, 1, 1, 3, 0, 1, 0), # 34 (18, 12, 9, 14, 7, 4, 4, 2, 4, 2, 1, 1, 0, 6, 5, 2, 12, 9, 8, 4, 4, 5, 2, 1, 1, 0), # 35 (14, 10, 13, 15, 5, 6, 5, 2, 2, 3, 1, 0, 0, 9, 10, 5, 11, 15, 2, 4, 2, 6, 5, 3, 0, 0), # 36 (12, 12, 7, 10, 12, 3, 7, 4, 3, 1, 3, 1, 0, 7, 4, 7, 7, 5, 5, 4, 2, 3, 3, 3, 0, 0), # 37 (13, 17, 15, 10, 13, 2, 8, 8, 3, 5, 2, 1, 0, 12, 13, 11, 6, 8, 9, 6, 4, 5, 4, 2, 0, 0), # 38 (14, 5, 20, 5, 8, 3, 4, 3, 10, 2, 3, 1, 0, 14, 8, 12, 5, 8, 9, 6, 6, 4, 2, 1, 1, 0), # 39 (9, 8, 5, 8, 5, 2, 2, 2, 5, 2, 1, 1, 0, 10, 5, 7, 10, 12, 12, 7, 1, 7, 2, 1, 2, 0), # 40 (11, 9, 8, 8, 4, 4, 9, 7, 6, 3, 3, 0, 0, 8, 14, 5, 13, 7, 4, 7, 2, 6, 3, 0, 0, 0), # 41 (11, 12, 8, 9, 6, 5, 5, 6, 1, 1, 0, 0, 0, 5, 4, 9, 6, 15, 6, 4, 3, 3, 2, 1, 2, 0), # 42 (11, 21, 9, 11, 9, 6, 7, 9, 3, 2, 0, 1, 0, 17, 13, 12, 7, 9, 8, 4, 2, 2, 5, 3, 1, 0), # 43 (13, 17, 10, 14, 10, 7, 6, 2, 3, 1, 2, 1, 0, 8, 12, 6, 3, 3, 3, 5, 4, 6, 4, 3, 0, 0), # 44 (14, 17, 6, 8, 12, 8, 6, 4, 7, 3, 3, 1, 0, 13, 10, 11, 9, 11, 4, 6, 4, 1, 3, 3, 1, 0), # 45 (12, 17, 12, 9, 10, 4, 11, 7, 3, 3, 1, 0, 0, 14, 5, 6, 8, 8, 3, 6, 2, 3, 3, 1, 0, 0), # 46 (18, 15, 9, 9, 16, 6, 3, 3, 4, 0, 4, 0, 0, 9, 7, 6, 6, 10, 8, 8, 2, 5, 4, 3, 2, 0), # 47 (10, 10, 10, 10, 7, 5, 3, 4, 3, 6, 0, 0, 0, 10, 10, 6, 8, 10, 5, 3, 2, 4, 1, 3, 0, 0), # 48 (13, 7, 11, 13, 7, 1, 3, 4, 7, 4, 0, 0, 0, 11, 11, 9, 7, 8, 7, 3, 1, 4, 5, 2, 0, 0), # 49 (17, 16, 11, 12, 11, 2, 1, 6, 9, 0, 2, 1, 0, 10, 10, 10, 13, 4, 3, 4, 2, 3, 3, 1, 1, 0), # 50 (11, 16, 12, 13, 11, 5, 9, 3, 2, 2, 1, 1, 0, 12, 5, 7, 6, 8, 6, 4, 1, 2, 4, 1, 2, 0), # 51 (13, 11, 5, 11, 10, 4, 4, 3, 4, 2, 2, 2, 0, 10, 10, 8, 9, 8, 5, 8, 5, 1, 5, 3, 0, 0), # 52 (10, 12, 13, 12, 6, 5, 5, 3, 6, 2, 0, 1, 0, 11, 12, 6, 7, 15, 5, 2, 5, 4, 5, 1, 2, 0), # 53 (14, 8, 11, 8, 8, 4, 3, 0, 4, 3, 3, 0, 0, 14, 7, 6, 8, 8, 5, 5, 1, 3, 5, 3, 0, 0), # 54 (12, 18, 11, 9, 8, 7, 5, 6, 3, 0, 1, 0, 0, 15, 9, 10, 9, 10, 6, 0, 4, 2, 1, 2, 0, 0), # 55 (17, 11, 7, 13, 8, 4, 3, 5, 3, 2, 1, 0, 0, 18, 7, 8, 7, 9, 5, 1, 5, 5, 7, 2, 1, 0), # 56 (8, 12, 13, 6, 11, 3, 6, 4, 5, 3, 0, 0, 0, 7, 6, 6, 7, 15, 3, 3, 4, 2, 2, 2, 1, 0), # 57 (7, 11, 6, 14, 9, 5, 5, 4, 6, 5, 1, 2, 0, 11, 14, 6, 6, 11, 9, 1, 3, 5, 7, 2, 2, 0), # 58 (13, 10, 7, 8, 7, 5, 4, 5, 5, 3, 1, 1, 0, 10, 19, 7, 2, 3, 4, 2, 2, 5, 6, 2, 1, 0), # 59 (16, 8, 9, 14, 11, 2, 6, 1, 8, 3, 0, 1, 0, 17, 10, 7, 6, 6, 7, 8, 3, 3, 6, 4, 0, 0), # 60 (18, 15, 15, 10, 4, 5, 7, 4, 3, 3, 4, 1, 0, 14, 10, 12, 2, 11, 7, 10, 5, 3, 4, 1, 0, 0), # 61 (11, 9, 9, 12, 12, 4, 1, 2, 5, 4, 3, 0, 0, 9, 14, 9, 6, 6, 3, 6, 4, 9, 5, 2, 1, 0), # 62 (17, 8, 12, 8, 11, 2, 4, 4, 5, 3, 3, 1, 0, 12, 6, 10, 6, 6, 4, 6, 3, 2, 5, 0, 1, 0), # 63 (15, 10, 12, 5, 12, 6, 2, 1, 6, 0, 2, 2, 0, 18, 13, 10, 7, 8, 5, 5, 3, 8, 1, 3, 1, 0), # 64 (13, 14, 13, 7, 6, 3, 14, 5, 6, 4, 2, 0, 0, 17, 13, 7, 2, 11, 7, 4, 4, 6, 2, 2, 1, 0), # 65 (7, 12, 14, 10, 7, 4, 4, 2, 2, 2, 0, 2, 0, 9, 9, 6, 6, 10, 5, 3, 3, 7, 2, 3, 1, 0), # 66 (9, 8, 11, 9, 9, 7, 2, 4, 5, 3, 0, 0, 0, 11, 11, 4, 7, 7, 5, 5, 6, 8, 5, 0, 1, 0), # 67 (7, 17, 4, 4, 15, 6, 5, 9, 8, 4, 2, 0, 0, 10, 9, 7, 12, 9, 5, 6, 3, 5, 3, 1, 2, 0), # 68 (8, 8, 8, 14, 8, 3, 3, 2, 6, 1, 3, 0, 0, 12, 11, 8, 5, 7, 3, 3, 2, 5, 7, 1, 0, 0), # 69 (13, 10, 6, 9, 7, 4, 3, 3, 3, 0, 2, 1, 0, 9, 6, 4, 7, 8, 5, 4, 3, 6, 2, 2, 2, 0), # 70 (11, 4, 8, 16, 9, 3, 5, 2, 2, 2, 3, 3, 0, 14, 10, 6, 5, 5, 4, 5, 3, 3, 5, 1, 0, 0), # 71 (11, 14, 11, 8, 11, 5, 7, 3, 5, 1, 2, 0, 0, 13, 16, 7, 5, 6, 9, 7, 3, 10, 5, 2, 1, 0), # 72 (14, 9, 14, 12, 14, 7, 4, 2, 1, 3, 0, 1, 0, 11, 9, 6, 9, 10, 4, 4, 4, 6, 3, 2, 1, 0), # 73 (12, 18, 17, 12, 7, 4, 5, 3, 6, 1, 2, 1, 0, 7, 12, 8, 5, 11, 4, 3, 6, 5, 5, 3, 1, 0), # 74 (16, 18, 10, 19, 11, 2, 5, 2, 8, 4, 1, 2, 0, 11, 7, 6, 6, 12, 1, 5, 0, 5, 4, 2, 1, 0), # 75 (10, 7, 9, 15, 12, 5, 7, 3, 6, 1, 1, 0, 0, 8, 8, 9, 7, 9, 9, 7, 3, 6, 0, 0, 1, 0), # 76 (17, 13, 12, 9, 14, 4, 7, 0, 5, 1, 1, 1, 0, 11, 6, 6, 3, 12, 8, 7, 3, 4, 4, 1, 4, 0), # 77 (19, 13, 9, 10, 13, 7, 6, 7, 5, 1, 1, 1, 0, 8, 12, 5, 3, 10, 4, 3, 4, 2, 6, 3, 0, 0), # 78 (7, 11, 6, 8, 6, 4, 1, 6, 5, 4, 3, 2, 0, 12, 9, 5, 4, 14, 7, 6, 2, 2, 6, 2, 3, 0), # 79 (13, 15, 5, 13, 11, 7, 8, 0, 6, 1, 0, 1, 0, 14, 7, 14, 7, 14, 2, 3, 2, 1, 1, 2, 0, 0), # 80 (12, 7, 10, 12, 8, 2, 2, 2, 4, 1, 1, 2, 0, 11, 9, 9, 5, 9, 4, 3, 1, 4, 1, 4, 2, 0), # 81 (8, 10, 9, 9, 13, 4, 2, 6, 10, 1, 4, 0, 0, 15, 12, 9, 2, 11, 6, 3, 3, 4, 2, 0, 1, 0), # 82 (11, 8, 7, 11, 10, 0, 3, 5, 2, 2, 3, 2, 0, 7, 13, 9, 4, 10, 0, 3, 2, 3, 7, 2, 1, 0), # 83 (9, 10, 12, 16, 7, 6, 3, 3, 2, 3, 2, 0, 0, 6, 14, 5, 8, 18, 5, 3, 2, 2, 1, 3, 3, 0), # 84 (15, 12, 11, 11, 12, 8, 6, 2, 5, 2, 1, 0, 0, 10, 9, 9, 5, 9, 8, 4, 3, 5, 3, 3, 2, 0), # 85 (9, 12, 12, 9, 11, 8, 8, 1, 3, 3, 1, 1, 0, 10, 6, 2, 1, 9, 3, 2, 3, 5, 5, 1, 0, 0), # 86 (6, 11, 9, 10, 5, 4, 4, 3, 6, 4, 2, 0, 0, 8, 11, 2, 8, 9, 6, 8, 4, 4, 5, 4, 0, 0), # 87 (16, 15, 6, 12, 8, 3, 4, 4, 1, 2, 2, 2, 0, 13, 9, 5, 7, 7, 7, 3, 2, 4, 1, 3, 0, 0), # 88 (21, 8, 15, 7, 11, 2, 3, 2, 1, 2, 2, 0, 0, 22, 15, 3, 9, 10, 8, 3, 3, 3, 1, 1, 0, 0), # 89 (14, 14, 11, 9, 12, 2, 6, 5, 2, 3, 1, 1, 0, 9, 11, 7, 9, 7, 9, 4, 4, 5, 7, 2, 0, 0), # 90 (9, 5, 9, 9, 11, 4, 5, 3, 2, 2, 1, 0, 0, 13, 8, 8, 3, 8, 5, 3, 3, 4, 1, 2, 4, 0), # 91 (11, 8, 9, 8, 6, 3, 3, 6, 4, 0, 0, 2, 0, 11, 10, 9, 4, 9, 5, 5, 2, 5, 4, 3, 0, 0), # 92 (10, 12, 10, 10, 11, 2, 5, 1, 2, 5, 3, 0, 0, 7, 7, 7, 11, 12, 7, 4, 5, 2, 5, 3, 0, 0), # 93 (11, 12, 16, 7, 5, 5, 4, 4, 3, 3, 1, 0, 0, 8, 9, 8, 8, 12, 2, 4, 7, 5, 3, 3, 0, 0), # 94 (13, 8, 8, 6, 13, 5, 6, 3, 4, 1, 3, 1, 0, 13, 14, 9, 5, 5, 7, 8, 0, 7, 4, 3, 0, 0), # 95 (11, 7, 8, 9, 11, 5, 1, 4, 3, 3, 1, 1, 0, 12, 11, 7, 7, 13, 8, 4, 2, 3, 4, 0, 1, 0), # 96 (10, 11, 9, 9, 6, 1, 7, 3, 3, 2, 1, 0, 0, 10, 5, 8, 8, 4, 5, 7, 2, 4, 4, 2, 0, 0), # 97 (13, 6, 4, 16, 8, 3, 3, 6, 4, 2, 1, 0, 0, 15, 12, 7, 7, 11, 1, 2, 3, 5, 10, 0, 1, 0), # 98 (14, 11, 10, 9, 11, 8, 3, 3, 3, 0, 2, 2, 0, 11, 13, 7, 7, 10, 2, 5, 4, 7, 2, 2, 3, 0), # 99 (21, 10, 11, 5, 10, 9, 5, 1, 7, 3, 0, 0, 0, 8, 10, 4, 6, 8, 4, 5, 7, 5, 4, 2, 1, 0), # 100 (14, 16, 13, 8, 5, 1, 3, 3, 6, 2, 4, 2, 0, 11, 7, 6, 4, 8, 5, 1, 3, 2, 5, 0, 1, 0), # 101 (10, 9, 14, 13, 15, 3, 8, 1, 5, 2, 1, 1, 0, 9, 11, 7, 5, 5, 5, 5, 1, 4, 2, 3, 0, 0), # 102 (8, 11, 11, 9, 10, 3, 3, 6, 5, 1, 0, 1, 0, 8, 6, 10, 7, 8, 3, 5, 1, 4, 3, 2, 2, 0), # 103 (11, 8, 9, 9, 8, 1, 4, 3, 6, 1, 2, 0, 0, 22, 9, 8, 9, 4, 2, 2, 3, 5, 1, 2, 1, 0), # 104 (16, 6, 8, 15, 6, 4, 0, 4, 5, 1, 0, 1, 0, 15, 7, 3, 6, 7, 2, 6, 1, 2, 2, 1, 1, 0), # 105 (13, 11, 7, 17, 9, 2, 2, 2, 5, 0, 2, 0, 0, 6, 7, 11, 1, 9, 5, 4, 1, 1, 5, 1, 0, 0), # 106 (16, 5, 9, 9, 11, 6, 0, 5, 4, 2, 2, 1, 0, 9, 6, 4, 3, 12, 5, 4, 3, 6, 4, 2, 1, 0), # 107 (19, 13, 10, 9, 7, 5, 1, 2, 4, 3, 0, 1, 0, 13, 16, 7, 5, 8, 5, 2, 8, 1, 0, 3, 2, 0), # 108 (12, 5, 4, 10, 4, 3, 2, 3, 8, 0, 2, 1, 0, 12, 6, 9, 7, 7, 2, 1, 1, 5, 4, 3, 0, 0), # 109 (14, 10, 9, 8, 4, 6, 2, 3, 3, 1, 0, 0, 0, 8, 10, 6, 6, 11, 8, 3, 4, 6, 4, 2, 0, 0), # 110 (16, 9, 10, 7, 12, 4, 6, 3, 1, 2, 1, 2, 0, 15, 16, 5, 5, 9, 3, 5, 3, 4, 7, 2, 0, 0), # 111 (10, 5, 6, 14, 3, 2, 4, 2, 5, 2, 1, 1, 0, 13, 5, 6, 5, 6, 7, 1, 1, 1, 9, 1, 2, 0), # 112 (15, 11, 7, 9, 8, 3, 3, 3, 2, 1, 0, 0, 0, 11, 4, 7, 4, 6, 4, 3, 1, 2, 2, 1, 1, 0), # 113 (12, 9, 6, 5, 11, 6, 7, 7, 2, 3, 3, 0, 0, 22, 10, 5, 5, 4, 7, 1, 4, 2, 4, 1, 1, 0), # 114 (10, 6, 8, 8, 6, 4, 3, 2, 4, 3, 0, 0, 0, 15, 15, 6, 3, 8, 4, 5, 6, 5, 2, 1, 2, 0), # 115 (14, 9, 14, 7, 9, 2, 2, 5, 3, 1, 1, 1, 0, 17, 7, 8, 4, 8, 5, 6, 3, 6, 4, 2, 2, 0), # 116 (6, 9, 7, 8, 7, 5, 4, 4, 5, 1, 2, 0, 0, 11, 8, 8, 9, 6, 6, 4, 2, 7, 3, 3, 0, 0), # 117 (17, 8, 13, 6, 6, 2, 2, 6, 2, 0, 0, 1, 0, 10, 9, 6, 5, 14, 2, 2, 4, 4, 9, 0, 0, 0), # 118 (9, 7, 13, 11, 11, 6, 2, 2, 6, 2, 3, 3, 0, 13, 6, 4, 5, 10, 3, 0, 2, 5, 2, 2, 0, 0), # 119 (13, 9, 13, 11, 9, 1, 2, 2, 1, 4, 0, 0, 0, 13, 11, 10, 2, 11, 5, 6, 2, 4, 6, 2, 1, 0), # 120 (12, 8, 12, 8, 9, 3, 5, 6, 7, 1, 2, 2, 0, 13, 13, 5, 10, 6, 4, 3, 1, 5, 0, 3, 0, 0), # 121 (10, 3, 7, 6, 6, 3, 6, 5, 6, 2, 3, 1, 0, 16, 7, 10, 3, 7, 9, 3, 1, 1, 4, 2, 0, 0), # 122 (14, 7, 15, 17, 9, 10, 0, 1, 7, 1, 2, 0, 0, 16, 11, 1, 5, 7, 3, 5, 3, 3, 6, 0, 0, 0), # 123 (10, 9, 8, 13, 5, 10, 3, 5, 2, 2, 1, 1, 0, 13, 10, 11, 6, 7, 2, 1, 2, 1, 3, 3, 1, 0), # 124 (11, 5, 11, 11, 8, 8, 5, 1, 10, 4, 2, 0, 0, 13, 3, 6, 8, 6, 4, 3, 1, 4, 4, 2, 1, 0), # 125 (9, 2, 7, 8, 4, 4, 3, 3, 4, 2, 3, 1, 0, 9, 9, 10, 5, 9, 2, 6, 3, 3, 1, 2, 0, 0), # 126 (12, 12, 8, 3, 6, 7, 1, 2, 3, 0, 0, 2, 0, 9, 13, 6, 6, 6, 3, 3, 2, 4, 2, 3, 2, 0), # 127 (14, 6, 7, 12, 10, 0, 6, 3, 8, 0, 2, 0, 0, 14, 6, 8, 3, 7, 4, 2, 2, 3, 3, 2, 1, 0), # 128 (18, 8, 10, 4, 2, 3, 2, 3, 2, 3, 2, 0, 0, 9, 8, 8, 5, 8, 0, 1, 0, 6, 1, 1, 0, 0), # 129 (11, 11, 8, 8, 9, 3, 2, 1, 5, 1, 1, 0, 0, 15, 8, 4, 8, 9, 7, 2, 5, 6, 5, 1, 1, 0), # 130 (13, 12, 11, 8, 8, 6, 1, 4, 4, 2, 3, 2, 0, 8, 12, 3, 1, 4, 7, 6, 5, 7, 3, 2, 0, 0), # 131 (8, 7, 9, 8, 5, 6, 1, 3, 0, 1, 2, 0, 0, 16, 13, 5, 6, 9, 5, 4, 0, 9, 4, 1, 0, 0), # 132 (11, 5, 14, 14, 10, 4, 10, 4, 6, 2, 2, 0, 0, 8, 5, 7, 4, 9, 3, 0, 2, 4, 9, 3, 0, 0), # 133 (11, 3, 6, 5, 11, 4, 3, 0, 4, 2, 1, 0, 0, 11, 10, 6, 3, 8, 4, 3, 1, 4, 5, 3, 0, 0), # 134 (5, 9, 3, 8, 9, 4, 3, 2, 11, 1, 1, 0, 0, 12, 6, 6, 8, 8, 4, 3, 1, 1, 3, 1, 0, 0), # 135 (8, 9, 15, 2, 10, 5, 4, 2, 6, 3, 1, 0, 0, 10, 8, 5, 5, 12, 4, 6, 2, 3, 3, 1, 2, 0), # 136 (8, 1, 12, 5, 5, 3, 4, 3, 5, 4, 0, 1, 0, 16, 8, 9, 4, 8, 4, 6, 1, 2, 4, 3, 1, 0), # 137 (7, 4, 11, 5, 10, 3, 1, 4, 2, 0, 3, 1, 0, 13, 7, 4, 6, 9, 6, 1, 8, 5, 4, 2, 0, 0), # 138 (5, 7, 8, 8, 7, 4, 3, 5, 3, 6, 4, 0, 0, 16, 6, 7, 5, 9, 4, 4, 2, 3, 1, 1, 1, 0), # 139 (10, 8, 14, 9, 9, 5, 4, 2, 3, 0, 0, 1, 0, 4, 13, 8, 5, 11, 5, 2, 3, 6, 2, 4, 1, 0), # 140 (10, 10, 6, 11, 6, 3, 3, 2, 4, 0, 0, 0, 0, 8, 7, 6, 7, 9, 5, 3, 0, 6, 3, 3, 1, 0), # 141 (9, 5, 9, 10, 10, 1, 5, 2, 5, 2, 1, 0, 0, 10, 9, 7, 2, 9, 3, 2, 3, 6, 0, 1, 2, 0), # 142 (8, 5, 12, 6, 10, 1, 4, 3, 5, 1, 0, 2, 0, 6, 9, 8, 6, 5, 2, 1, 3, 3, 2, 2, 0, 0), # 143 (7, 4, 10, 11, 8, 2, 1, 3, 7, 0, 0, 0, 0, 9, 12, 4, 3, 11, 3, 5, 1, 2, 0, 1, 0, 0), # 144 (2, 10, 4, 4, 4, 2, 1, 1, 7, 1, 0, 0, 0, 14, 7, 2, 4, 5, 3, 4, 3, 4, 4, 1, 0, 0), # 145 (5, 11, 14, 12, 9, 4, 1, 5, 4, 0, 1, 0, 0, 10, 9, 6, 6, 11, 5, 4, 3, 3, 4, 2, 0, 0), # 146 (13, 11, 2, 9, 7, 4, 1, 2, 0, 0, 2, 0, 0, 10, 15, 9, 6, 9, 4, 1, 5, 5, 5, 1, 0, 0), # 147 (7, 3, 11, 6, 8, 1, 4, 2, 5, 2, 0, 0, 0, 10, 10, 3, 8, 5, 3, 3, 2, 4, 1, 2, 2, 0), # 148 (10, 6, 5, 8, 9, 4, 4, 1, 3, 2, 3, 1, 0, 8, 8, 6, 6, 10, 5, 5, 2, 3, 2, 1, 1, 0), # 149 (8, 8, 14, 10, 9, 7, 3, 2, 4, 2, 1, 2, 0, 6, 9, 12, 1, 15, 2, 1, 1, 2, 6, 2, 0, 0), # 150 (9, 5, 10, 6, 7, 5, 3, 1, 2, 2, 1, 3, 0, 11, 5, 2, 5, 7, 2, 3, 5, 1, 5, 0, 1, 0), # 151 (8, 9, 6, 12, 10, 4, 4, 2, 4, 1, 1, 2, 0, 8, 9, 10, 6, 8, 3, 2, 3, 6, 3, 0, 1, 0), # 152 (11, 7, 13, 12, 7, 6, 3, 5, 3, 0, 1, 0, 0, 14, 9, 4, 1, 7, 6, 1, 3, 6, 3, 2, 2, 0), # 153 (10, 14, 8, 8, 9, 7, 4, 2, 4, 0, 3, 3, 0, 14, 8, 4, 5, 4, 4, 1, 2, 3, 4, 0, 2, 0), # 154 (7, 6, 7, 7, 13, 1, 3, 2, 6, 5, 1, 2, 0, 9, 10, 2, 6, 3, 6, 2, 2, 7, 4, 2, 0, 0), # 155 (6, 5, 10, 11, 9, 7, 2, 2, 2, 2, 1, 0, 0, 13, 7, 6, 2, 2, 3, 2, 5, 9, 3, 0, 0, 0), # 156 (7, 6, 14, 8, 6, 8, 6, 1, 5, 2, 2, 0, 0, 8, 10, 4, 4, 8, 3, 4, 3, 3, 1, 1, 1, 0), # 157 (6, 3, 2, 14, 5, 4, 5, 1, 1, 1, 0, 0, 0, 6, 14, 6, 8, 6, 7, 1, 4, 7, 1, 1, 0, 0), # 158 (7, 8, 10, 10, 6, 4, 2, 5, 5, 1, 1, 0, 0, 6, 8, 6, 3, 7, 3, 2, 1, 5, 1, 0, 0, 0), # 159 (6, 5, 7, 4, 7, 4, 1, 3, 3, 2, 0, 0, 0, 10, 5, 5, 9, 5, 7, 3, 3, 3, 3, 0, 0, 0), # 160 (7, 6, 5, 5, 1, 3, 5, 2, 1, 2, 1, 0, 0, 11, 6, 8, 2, 7, 3, 3, 5, 4, 5, 2, 1, 0), # 161 (5, 5, 6, 11, 14, 4, 2, 1, 4, 2, 1, 2, 0, 8, 9, 7, 3, 3, 1, 5, 1, 2, 3, 3, 1, 0), # 162 (3, 8, 6, 6, 8, 2, 2, 3, 2, 0, 3, 0, 0, 11, 6, 7, 4, 4, 6, 1, 2, 4, 2, 0, 0, 0), # 163 (10, 6, 8, 10, 8, 1, 4, 1, 4, 1, 0, 1, 0, 8, 7, 7, 4, 5, 5, 1, 1, 4, 1, 2, 0, 0), # 164 (9, 8, 7, 4, 7, 2, 2, 1, 1, 2, 3, 0, 0, 6, 10, 8, 7, 14, 4, 3, 2, 3, 1, 3, 2, 0), # 165 (5, 8, 9, 6, 5, 3, 5, 3, 2, 2, 2, 0, 0, 8, 9, 2, 2, 8, 6, 2, 1, 4, 0, 3, 0, 0), # 166 (4, 4, 6, 6, 10, 2, 5, 1, 4, 0, 3, 3, 0, 9, 2, 4, 3, 4, 1, 3, 1, 2, 2, 1, 0, 0), # 167 (3, 7, 7, 9, 10, 3, 4, 2, 1, 1, 0, 1, 0, 9, 4, 4, 2, 3, 3, 2, 2, 2, 3, 2, 1, 0), # 168 (3, 4, 3, 4, 5, 3, 3, 2, 0, 1, 0, 2, 0, 12, 9, 7, 2, 12, 5, 0, 4, 4, 5, 1, 1, 0), # 169 (5, 4, 2, 10, 5, 5, 5, 4, 4, 0, 3, 0, 0, 6, 6, 5, 5, 5, 4, 2, 2, 5, 3, 1, 0, 0), # 170 (8, 8, 7, 6, 5, 4, 4, 2, 6, 0, 2, 0, 0, 4, 7, 4, 4, 4, 4, 0, 1, 1, 1, 1, 0, 0), # 171 (4, 3, 7, 4, 6, 4, 1, 2, 4, 3, 1, 1, 0, 11, 5, 1, 7, 3, 3, 2, 4, 1, 3, 1, 0, 0), # 172 (10, 7, 7, 7, 10, 3, 2, 2, 4, 1, 1, 0, 0, 5, 3, 5, 4, 4, 6, 2, 1, 2, 4, 0, 1, 0), # 173 (3, 3, 4, 10, 2, 1, 0, 1, 1, 1, 0, 0, 0, 6, 1, 2, 2, 3, 1, 0, 3, 2, 4, 0, 0, 0), # 174 (6, 3, 3, 6, 5, 1, 3, 2, 2, 0, 1, 0, 0, 9, 8, 1, 2, 9, 3, 6, 0, 4, 1, 0, 2, 0), # 175 (5, 3, 2, 3, 3, 3, 2, 2, 3, 0, 0, 0, 0, 6, 8, 6, 3, 6, 0, 3, 1, 6, 0, 1, 1, 0), # 176 (3, 4, 6, 2, 3, 0, 2, 2, 0, 0, 0, 1, 0, 7, 4, 5, 2, 3, 2, 3, 1, 3, 1, 1, 0, 0), # 177 (7, 4, 6, 3, 1, 2, 1, 2, 0, 1, 0, 2, 0, 4, 3, 3, 3, 3, 2, 2, 1, 0, 1, 1, 0, 0), # 178 (0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), # 179 ) station_arriving_intensity = ( (6.025038694046121, 6.630346271631799, 6.253539875535008, 7.457601328636119, 6.665622729131534, 3.766385918444806, 4.9752427384486975, 5.583811407575308, 7.308118874601608, 4.749618018626843, 5.046318196662723, 5.877498093967408, 6.100656255094035), # 0 (6.425192582423969, 7.06807283297371, 6.666415909596182, 7.950173103931939, 7.106988404969084, 4.015180300851067, 5.303362729516432, 5.951416467486849, 7.79069439159949, 5.062776830732579, 5.3797153631473575, 6.265459992977225, 6.503749976927826), # 1 (6.8240676107756775, 7.504062205069175, 7.077650742656896, 8.440785245597752, 7.546755568499692, 4.262982137414934, 5.630182209552845, 6.317550297485303, 8.271344168253059, 5.3746965300246545, 5.711787778531575, 6.651879182463666, 6.905237793851628), # 2 (7.220109351775874, 7.936584602323736, 7.485613043183825, 8.927491689038488, 7.983194011202282, 4.508808747102135, 5.954404369977547, 6.680761388993408, 8.74816219310531, 5.684139238111417, 6.041218094192859, 7.035222821916553, 7.30352736750507), # 3 (7.611763378099177, 8.363910239142928, 7.8886714796436435, 9.408346369659084, 8.41457352455579, 4.751677448878401, 6.27473240221015, 7.039598233433898, 9.219242454699248, 5.9898670766012145, 6.36668896150869, 7.413958070825716, 7.69702635952778), # 4 (7.9974752624202115, 8.784309329932306, 8.285194720503021, 9.881403222864472, 8.839163900039136, 4.990605561709457, 6.589869497670269, 7.392609322229511, 9.682678941577871, 6.290642167102395, 6.686883031856559, 7.786552088680978, 8.084142431559393), # 5 (8.375690577413598, 9.196052089097401, 8.673551434228639, 10.344716184059582, 9.255234929131252, 5.224610404561036, 6.898518847777515, 7.738343146802986, 10.136565642284177, 6.58522663122331, 7.000482956613939, 8.15147203497217, 8.463283245239527), # 6 (8.744854895753962, 9.597408731043757, 9.052110289287162, 10.796339188649354, 9.661056403311065, 5.452709296398865, 7.199383643951502, 8.075348198577062, 10.578996545361173, 6.872382590572303, 7.306171387158321, 8.507185069189115, 8.832856462207822), # 7 (9.103413790115921, 9.986649470176918, 9.419239954145274, 11.234326172038713, 10.054898114057503, 5.673919556188667, 7.491167077611837, 8.402172968974469, 11.008065639351846, 7.150872166757728, 7.602630974867185, 8.852158350821643, 9.1912697441039), # 8 (9.449812833174102, 10.362044520902426, 9.773309097269644, 11.656731069632603, 10.43502985284949, 5.88725850289618, 7.772572340178144, 8.717365949417955, 11.421866912799208, 7.419457481387929, 7.888544371118013, 9.184859039359576, 9.536930752567395), # 9 (9.782497597603118, 10.721864097625819, 10.11268638712695, 12.061607816835945, 10.79972141116596, 6.091743455487129, 8.042302623070025, 9.019475631330252, 11.818494354246257, 7.676900656071257, 8.162594227288288, 9.503754294292742, 9.868247149237932), # 10 (10.099913656077605, 11.064378414752648, 10.435740492183857, 12.447010349053675, 11.14724258048584, 6.286391732927242, 8.2990611177071, 9.307050506134097, 12.196041952235992, 7.921963812416062, 8.423463194755499, 9.807311275110973, 10.183626595755133), # 11 (10.400506581272174, 11.387857686688436, 10.740840080907047, 12.810992601690733, 11.475863152288053, 6.470220654182243, 8.541551015508974, 9.578639065252224, 12.552603695311413, 8.153409072030685, 8.669833924897121, 10.093997141304081, 10.48147675375864), # 12 (10.68272194586145, 11.690572127838744, 11.026353821763193, 13.151608510152052, 11.78385291805152, 6.642247538217868, 8.768475507895266, 9.832789800107378, 12.886273572015517, 8.369998556523484, 8.900389069090641, 10.362279052361904, 10.760205284888082), # 13 (10.945005322520059, 11.970791952609106, 11.290650383218976, 13.46691200984255, 12.069481669255188, 6.801489703999841, 8.978537786285592, 10.068051202122295, 13.195145570891304, 8.5704943875028, 9.113811278713541, 10.610624167774272, 11.018219850783076), # 14 (11.185802283922625, 12.22678737540506, 11.53209843374105, 13.754957036167182, 12.33101919737797, 6.946964470493895, 9.17044104209955, 10.282971762719706, 13.477313680481783, 8.753658686576989, 9.308783205143303, 10.837499647031004, 11.253928113083257), # 15 (11.40355840274376, 12.456828610632158, 11.749066641796109, 14.01379752453086, 12.5667352938988, 7.077689156665751, 9.34288846675677, 10.476099973322352, 13.730871889329944, 8.918253575354395, 9.483987499757415, 11.041372649621927, 11.465737733428254), # 16 (11.59671925165809, 12.659185872695934, 11.939923675850823, 14.241487410338534, 12.774899750296605, 7.192681081481142, 9.494583251676852, 10.64598432535298, 13.95391418597878, 9.06304117544336, 9.638106813933359, 11.220710335036866, 11.652056373457699), # 17 (11.763730403340244, 12.832129376001928, 12.103038204371856, 14.436080628995134, 12.953782358050306, 7.290957563905803, 9.62422858827942, 10.791173310234312, 14.144534558971316, 9.186783608452243, 9.76982379904861, 11.373979862765658, 11.811291694811214), # 18 (11.903037430464838, 12.973929334955693, 12.236778895825895, 14.595631115905576, 13.101652908638838, 7.37153592290545, 9.730527667984072, 10.910215419389093, 14.300826996850533, 9.288242995989393, 9.877821106480653, 11.499648392298115, 11.941851359128435), # 19 (12.013085905706498, 13.082855963962754, 12.339514418679602, 14.718192806474825, 13.216781193541133, 7.4334334774458215, 9.812183682210435, 11.00165914424006, 14.420885488159437, 9.36618145966315, 9.96078138760698, 11.59618308312407, 12.042143028048988), # 20 (12.09232140173984, 13.15717947742867, 12.409613441399662, 14.801819636107782, 13.297437004236105, 7.475667546492642, 9.86789982237811, 11.064052976209947, 14.502804021441024, 9.419361121081865, 10.01738729380507, 11.662051094733352, 12.110574363212494), # 21 (12.139189491239494, 13.195170089758973, 12.445444632452743, 14.844565540209402, 13.341890132202689, 7.497255449011639, 9.89637927990672, 11.095945406721498, 14.544676585238298, 9.44654410185389, 10.046321476452407, 11.695719586615787, 12.145553026258591), # 22 (12.156472036011166, 13.199668312757202, 12.449907818930042, 14.849916975308643, 13.353278467239116, 7.5, 9.899764802711205, 11.099392592592592, 14.54991148148148, 9.44975072702332, 10.049949644594088, 11.69987709190672, 12.15), # 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144 (9.858407607482972, 7.891647099014518, 10.195968678999947, 11.764830198535073, 11.67823835562988, 6.4479428145050885, 6.294169225213792, 6.880810171770211, 12.329567899769344, 6.351463681171185, 7.460569437354474, 8.881989883113016, 10.41245928452676), # 145 (9.79914421275282, 7.83392113092257, 10.156403453489059, 11.71027933717995, 11.62876122378119, 6.428770902375816, 6.253984464732396, 6.863975227664311, 12.299140665088327, 6.318151670529565, 7.423534194988978, 8.839888524472823, 10.367574997365741), # 146 (9.73839716926632, 7.774778197407756, 10.115592926186292, 11.654101346711496, 11.577883318388821, 6.4089038806048295, 6.212712636165577, 6.846356224645698, 12.267539938126548, 6.283831972278175, 7.385344328241643, 8.796509314016532, 10.321407081432142), # 147 (9.676122838090825, 7.714145838909944, 10.0734898035013, 11.596232646402955, 11.525568490944673, 6.38830862459132, 6.170299173747152, 6.827897434471509, 12.234706557806435, 6.248454356350137, 7.345941639724779, 8.751797087318483, 10.27391918441993), # 148 (9.612277580293695, 7.651951595868995, 10.030046791843732, 11.536609655527563, 11.471780592940645, 6.366952009734479, 6.126689511710929, 6.80854312889888, 12.200581363050405, 6.211968592678576, 7.3052679320506915, 8.705696679953029, 10.225074954023084), # 149 (9.546817756942277, 7.588123008724775, 9.985216597623232, 11.475168793358565, 11.416483475868631, 6.344800911433499, 6.08182908429072, 6.788237579684948, 12.165105192780901, 6.174324451196612, 7.2632650078316905, 8.658152927494514, 10.174838037935576), # 150 (9.47969972910393, 7.522587617917144, 9.93895192724945, 11.411846479169196, 11.359640991220532, 6.321822205087566, 6.03566332572034, 6.7669250585868514, 12.128218885920345, 6.135471701837373, 7.2198746696800855, 8.609110665517285, 10.123172083851381), # 151 (9.41087985784601, 7.455272963885967, 9.89120548713204, 11.346579132232701, 11.301216990488243, 6.297982766095876, 5.9881376702335976, 6.744549837361729, 12.089863281391164, 6.095360114533979, 7.175038720208185, 8.558514729595691, 10.070040739464476), # 152 (9.340314504235872, 7.386106587071107, 9.841929983680641, 11.279303171822319, 11.241175325163667, 6.273249469857618, 5.939197552064303, 6.721056187766714, 12.049979218115787, 6.053939459219555, 7.128698962028299, 8.506309955304076, 10.015407652468832), # 153 (9.267960029340873, 7.315016027912428, 9.79107812330491, 11.209955017211291, 11.179479846738696, 6.247589191771985, 5.888788405446274, 6.696388381558948, 12.008507535016639, 6.011159505827223, 7.080797197752734, 8.45244117821679, 9.959236470558428), # 154 (9.193772794228362, 7.241928826849794, 9.73860261241449, 11.138471087672853, 11.116094406705235, 6.220968807238165, 5.836855664613313, 6.670490690495563, 11.965389071016153, 5.966970024290105, 7.0312752299938, 8.396853233908178, 9.901490841427231), # 155 (9.117709159965697, 7.166772524323065, 9.684456157419032, 11.06478780248025, 11.050982856555176, 6.193355191655353, 5.7833447637992395, 6.643307386333702, 11.920564665036752, 5.921320784541327, 6.980074861363805, 8.339490957952586, 9.842134412769221), # 156 (9.039725487620235, 7.089474660772107, 9.628591464728181, 10.988841580906724, 10.984109047780422, 6.164715220422736, 5.728201137237862, 6.614782740830498, 11.873975156000865, 5.874161556514009, 6.927137894475059, 8.280299185924363, 9.781130832278372), # 157 (8.957617135686286, 7.008543744926709, 9.568310344682827, 10.907723497981491, 10.912417327045196, 6.133229371580532, 5.6701280651134285, 6.582956342819247, 11.821994509918916, 5.824039099549372, 6.870714903046731, 8.217119477033206, 9.715783031298415), # 158 (8.858744120374082, 6.915678383519373, 9.488085382083584, 10.804772590546143, 10.818229571737954, 6.088427577608523, 5.601855316062859, 6.536656239317259, 11.743712713466573, 5.762737192918494, 6.800900322742793, 8.13763502841973, 9.630513176304232), # 159 (8.741846513885172, 6.810116074248857, 9.386305149547066, 10.67829301249063, 10.699704157616154, 6.0292095552572205, 5.5226924980605405, 6.4747190274328155, 11.636910272674381, 5.689446782235472, 6.716711410331447, 8.040602338665416, 9.523704730672296), # 160 (8.607866465503152, 6.692545041696563, 9.26405636629237, 10.529487004508074, 10.558071749138534, 5.956292689884377, 5.433217735208252, 6.397920639731736, 11.50299572039882, 5.604789831805125, 6.618889985519648, 7.926920962689085, 9.396448853782916), # 161 (8.457746124511628, 6.563653510443886, 9.122425751538595, 10.359556807291591, 10.394563010763845, 5.870394366847746, 5.334009151607771, 6.307037008779842, 11.343377589496363, 5.509388305932277, 6.508177868014344, 7.797490455409552, 9.2498367050164), # 162 (8.292427640194196, 6.424129705072228, 8.962500024504841, 10.16970466153432, 10.210408606950825, 5.772231971505087, 5.22564487136088, 6.20284406714295, 11.159464412823487, 5.40386416892175, 6.38531687752249, 7.653210371745638, 9.084959443753055), # 163 (8.11285316183446, 6.2746618501629845, 8.785365904410211, 9.961132807929381, 10.006839202158226, 5.662522889214155, 5.108703018569359, 6.086117747386882, 10.952664723236667, 5.2888393850783615, 6.251048833751035, 7.494980266616163, 8.902908229373192), # 164 (7.9199648387160195, 6.115938170297558, 8.592110110473802, 9.735043487169902, 9.785085460844789, 5.541984505332703, 4.983761717334986, 5.957633982077455, 10.724387053592375, 5.164935918706936, 6.106115556406933, 7.323699694939943, 8.704774221257123), # 165 (7.714704820122476, 5.948646890057345, 8.383819361914712, 9.492638939949002, 9.546378047469256, 5.41133420521849, 4.851399091759543, 5.818168703780493, 10.476039936747087, 5.0327757341122945, 5.9512588651971345, 7.140268211635801, 8.491648578785155), # 166 (7.498015255337426, 5.773476234023744, 8.161580377952045, 9.235121406959811, 9.291947626490375, 5.27128937422927, 4.712193265944809, 5.668497845061811, 10.209031905557278, 4.892980795599256, 5.787220579828592, 6.94558537162255, 8.264622461337595), # 167 (7.2708382936444735, 5.591114426778154, 7.926479877804897, 8.963693128895455, 9.02302486236689, 5.122567397722799, 4.5667223639925645, 5.509397338487231, 9.924771492879426, 4.746173067472646, 5.614742520008257, 6.740550729819013, 8.024787028294753), # 168 (7.034116084327218, 5.402249692901975, 7.67960458069237, 8.67955634644906, 8.740840419557543, 4.965885661056833, 4.4155645100045895, 5.341643116622574, 9.624667231570005, 4.592974514037284, 5.434566505443081, 6.526063841144007, 7.773233439036942), # 169 (6.78879077666926, 5.207570256976605, 7.422041205833562, 8.383913300313743, 8.44662496252108, 4.8019615495891275, 4.259297828082663, 5.166011112033656, 9.310127654485486, 4.434007099597989, 5.247434355840019, 6.3030242605163505, 7.5110528529444665), # 170 (6.5358045199542, 5.007764343583441, 7.154876472447573, 8.077966231182643, 8.141609155716246, 4.631512448677438, 4.098500442328566, 4.983277257286299, 8.982561294482347, 4.269892788459586, 5.054087890906017, 6.072331542854863, 7.239336429397638), # 171 (6.276099463465638, 4.803520177303883, 6.879197099753504, 7.762917379748876, 7.827023663601784, 4.45525574367952, 3.9337504768440783, 4.794217484946325, 8.643376684417062, 4.101253544926895, 4.855268930348032, 5.834885243078365, 6.959175327776763), # 172 (6.010617756487176, 4.59552598271933, 6.596089806970453, 7.43996898670557, 7.504099150636442, 4.27390881995313, 3.7656260557309795, 4.599607727579548, 8.293982357146106, 3.9287113333047374, 4.651719293873013, 5.59158491610567, 6.671660707462155), # 173 (5.740301548302412, 4.384469984411181, 6.306641313317521, 7.110323292745848, 7.174066281278959, 4.088189062856022, 3.5947053030910503, 4.400223917751792, 7.935786845525956, 3.752888117897936, 4.444180801187913, 5.3433301168556016, 6.37788372783412), # 174 (5.466092988194946, 4.171040406960834, 6.01193833801381, 6.775182538562841, 6.838155719988083, 3.898813857745954, 3.421566343026069, 4.196841988028875, 7.570198682413086, 3.574405863011309, 4.233395271999683, 5.091020400246977, 6.078935548272969), # 175 (5.188934225448382, 3.9559254749496873, 5.713067600278413, 6.43574896484967, 6.497598131222556, 3.7065005899806795, 3.2467872996378175, 3.9902378709766184, 7.1986264006639695, 3.3938865329496806, 4.020104526015276, 4.835555321198615, 5.7759073281590085), # 176 (4.909767409346319, 3.7398134129591414, 5.411115819330436, 6.09322481229946, 6.1536241794411275, 3.511966644917956, 3.0709462970280748, 3.781187499160839, 6.822478533135084, 3.2119520920178695, 3.8050503829416424, 4.5778344346293345, 5.4698902268725496), # 177 (4.629534689172356, 3.5233924455705936, 5.107169714388976, 5.748812321605339, 5.807464529102536, 3.3159294079155393, 2.894621459298621, 3.5704668051473587, 6.443163612682903, 3.0292245045207, 3.588974662485735, 4.318757295457952, 5.161975403793902), # 178 (0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0), # 179 ) passenger_arriving_acc = ( (5, 6, 5, 9, 4, 1, 2, 3, 2, 1, 1, 1, 0, 7, 6, 8, 4, 8, 2, 3, 1, 0, 1, 1, 1, 0), # 0 (12, 12, 8, 19, 11, 2, 3, 4, 8, 2, 3, 2, 0, 10, 11, 15, 11, 13, 6, 8, 1, 2, 3, 1, 2, 0), # 1 (17, 15, 18, 24, 14, 5, 7, 6, 9, 3, 4, 3, 0, 19, 20, 19, 14, 18, 8, 12, 3, 6, 4, 2, 2, 0), # 2 (24, 27, 28, 33, 18, 8, 17, 6, 11, 3, 4, 4, 0, 28, 29, 26, 17, 28, 9, 13, 3, 7, 6, 2, 2, 0), # 3 (32, 33, 34, 41, 24, 11, 20, 14, 12, 5, 5, 5, 0, 41, 37, 30, 24, 33, 12, 15, 4, 13, 6, 3, 2, 0), # 4 (41, 45, 41, 49, 30, 14, 25, 19, 17, 7, 7, 6, 0, 45, 48, 38, 30, 40, 16, 20, 7, 13, 6, 4, 2, 0), # 5 (47, 53, 47, 53, 38, 17, 26, 23, 22, 12, 7, 9, 0, 51, 55, 41, 33, 50, 22, 26, 11, 14, 10, 5, 3, 0), # 6 (51, 57, 57, 58, 45, 23, 34, 27, 28, 15, 7, 11, 0, 61, 61, 44, 39, 57, 26, 27, 13, 14, 12, 8, 4, 0), # 7 (61, 64, 64, 69, 51, 24, 41, 35, 32, 16, 8, 11, 0, 72, 77, 53, 42, 65, 34, 31, 15, 18, 14, 9, 6, 0), # 8 (67, 70, 70, 80, 53, 27, 42, 36, 35, 17, 8, 12, 0, 81, 85, 60, 47, 71, 39, 34, 15, 18, 17, 9, 6, 0), # 9 (74, 78, 80, 85, 59, 31, 44, 41, 37, 17, 9, 13, 0, 94, 97, 65, 52, 80, 45, 37, 15, 22, 19, 11, 9, 0), # 10 (82, 93, 86, 100, 73, 34, 48, 41, 38, 19, 11, 14, 0, 102, 109, 75, 55, 88, 49, 41, 18, 25, 21, 11, 12, 0), # 11 (93, 106, 95, 112, 78, 36, 52, 44, 39, 21, 13, 14, 0, 113, 121, 83, 63, 97, 54, 46, 20, 31, 26, 15, 12, 0), # 12 (104, 120, 98, 125, 81, 40, 58, 48, 45, 23, 14, 15, 0, 126, 129, 90, 69, 103, 58, 49, 21, 33, 31, 21, 13, 0), # 13 (114, 131, 102, 134, 93, 44, 66, 53, 48, 23, 17, 15, 0, 134, 137, 96, 78, 110, 63, 52, 24, 35, 35, 24, 14, 0), # 14 (125, 138, 110, 148, 104, 47, 71, 56, 52, 28, 17, 16, 0, 145, 147, 102, 88, 116, 68, 55, 28, 39, 39, 26, 15, 0), # 15 (139, 155, 117, 158, 113, 50, 74, 62, 57, 31, 17, 17, 0, 156, 157, 108, 96, 124, 74, 59, 34, 45, 42, 31, 17, 0), # 16 (146, 166, 125, 163, 123, 53, 78, 67, 62, 33, 18, 18, 0, 165, 165, 114, 102, 133, 78, 65, 39, 49, 46, 35, 17, 0), # 17 (156, 176, 133, 176, 135, 57, 81, 72, 65, 34, 19, 18, 0, 179, 176, 120, 108, 136, 88, 69, 42, 51, 51, 39, 19, 0), # 18 (172, 182, 143, 184, 140, 61, 89, 75, 72, 38, 19, 18, 0, 184, 191, 126, 120, 148, 94, 74, 47, 57, 55, 40, 21, 0), # 19 (187, 192, 150, 193, 151, 68, 91, 79, 75, 42, 19, 19, 0, 193, 207, 135, 126, 157, 100, 81, 50, 61, 61, 41, 21, 0), # 20 (204, 209, 158, 210, 162, 72, 96, 84, 83, 46, 20, 21, 0, 203, 217, 146, 130, 165, 109, 87, 51, 66, 70, 43, 22, 0), # 21 (221, 228, 173, 222, 174, 76, 103, 89, 91, 49, 22, 23, 0, 214, 230, 156, 139, 170, 118, 90, 57, 73, 73, 46, 22, 0), # 22 (228, 239, 179, 234, 185, 80, 110, 92, 94, 50, 24, 23, 0, 233, 239, 160, 144, 179, 127, 95, 62, 78, 75, 50, 24, 0), # 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150 (1748, 1544, 1461, 1478, 1315, 624, 644, 538, 669, 299, 226, 118, 0, 1698, 1441, 1068, 910, 1309, 762, 610, 413, 610, 536, 289, 132, 0), # 151 (1756, 1553, 1467, 1490, 1325, 628, 648, 540, 673, 300, 227, 120, 0, 1706, 1450, 1078, 916, 1317, 765, 612, 416, 616, 539, 289, 133, 0), # 152 (1767, 1560, 1480, 1502, 1332, 634, 651, 545, 676, 300, 228, 120, 0, 1720, 1459, 1082, 917, 1324, 771, 613, 419, 622, 542, 291, 135, 0), # 153 (1777, 1574, 1488, 1510, 1341, 641, 655, 547, 680, 300, 231, 123, 0, 1734, 1467, 1086, 922, 1328, 775, 614, 421, 625, 546, 291, 137, 0), # 154 (1784, 1580, 1495, 1517, 1354, 642, 658, 549, 686, 305, 232, 125, 0, 1743, 1477, 1088, 928, 1331, 781, 616, 423, 632, 550, 293, 137, 0), # 155 (1790, 1585, 1505, 1528, 1363, 649, 660, 551, 688, 307, 233, 125, 0, 1756, 1484, 1094, 930, 1333, 784, 618, 428, 641, 553, 293, 137, 0), # 156 (1797, 1591, 1519, 1536, 1369, 657, 666, 552, 693, 309, 235, 125, 0, 1764, 1494, 1098, 934, 1341, 787, 622, 431, 644, 554, 294, 138, 0), # 157 (1803, 1594, 1521, 1550, 1374, 661, 671, 553, 694, 310, 235, 125, 0, 1770, 1508, 1104, 942, 1347, 794, 623, 435, 651, 555, 295, 138, 0), # 158 (1810, 1602, 1531, 1560, 1380, 665, 673, 558, 699, 311, 236, 125, 0, 1776, 1516, 1110, 945, 1354, 797, 625, 436, 656, 556, 295, 138, 0), # 159 (1816, 1607, 1538, 1564, 1387, 669, 674, 561, 702, 313, 236, 125, 0, 1786, 1521, 1115, 954, 1359, 804, 628, 439, 659, 559, 295, 138, 0), # 160 (1823, 1613, 1543, 1569, 1388, 672, 679, 563, 703, 315, 237, 125, 0, 1797, 1527, 1123, 956, 1366, 807, 631, 444, 663, 564, 297, 139, 0), # 161 (1828, 1618, 1549, 1580, 1402, 676, 681, 564, 707, 317, 238, 127, 0, 1805, 1536, 1130, 959, 1369, 808, 636, 445, 665, 567, 300, 140, 0), # 162 (1831, 1626, 1555, 1586, 1410, 678, 683, 567, 709, 317, 241, 127, 0, 1816, 1542, 1137, 963, 1373, 814, 637, 447, 669, 569, 300, 140, 0), # 163 (1841, 1632, 1563, 1596, 1418, 679, 687, 568, 713, 318, 241, 128, 0, 1824, 1549, 1144, 967, 1378, 819, 638, 448, 673, 570, 302, 140, 0), # 164 (1850, 1640, 1570, 1600, 1425, 681, 689, 569, 714, 320, 244, 128, 0, 1830, 1559, 1152, 974, 1392, 823, 641, 450, 676, 571, 305, 142, 0), # 165 (1855, 1648, 1579, 1606, 1430, 684, 694, 572, 716, 322, 246, 128, 0, 1838, 1568, 1154, 976, 1400, 829, 643, 451, 680, 571, 308, 142, 0), # 166 (1859, 1652, 1585, 1612, 1440, 686, 699, 573, 720, 322, 249, 131, 0, 1847, 1570, 1158, 979, 1404, 830, 646, 452, 682, 573, 309, 142, 0), # 167 (1862, 1659, 1592, 1621, 1450, 689, 703, 575, 721, 323, 249, 132, 0, 1856, 1574, 1162, 981, 1407, 833, 648, 454, 684, 576, 311, 143, 0), # 168 (1865, 1663, 1595, 1625, 1455, 692, 706, 577, 721, 324, 249, 134, 0, 1868, 1583, 1169, 983, 1419, 838, 648, 458, 688, 581, 312, 144, 0), # 169 (1870, 1667, 1597, 1635, 1460, 697, 711, 581, 725, 324, 252, 134, 0, 1874, 1589, 1174, 988, 1424, 842, 650, 460, 693, 584, 313, 144, 0), # 170 (1878, 1675, 1604, 1641, 1465, 701, 715, 583, 731, 324, 254, 134, 0, 1878, 1596, 1178, 992, 1428, 846, 650, 461, 694, 585, 314, 144, 0), # 171 (1882, 1678, 1611, 1645, 1471, 705, 716, 585, 735, 327, 255, 135, 0, 1889, 1601, 1179, 999, 1431, 849, 652, 465, 695, 588, 315, 144, 0), # 172 (1892, 1685, 1618, 1652, 1481, 708, 718, 587, 739, 328, 256, 135, 0, 1894, 1604, 1184, 1003, 1435, 855, 654, 466, 697, 592, 315, 145, 0), # 173 (1895, 1688, 1622, 1662, 1483, 709, 718, 588, 740, 329, 256, 135, 0, 1900, 1605, 1186, 1005, 1438, 856, 654, 469, 699, 596, 315, 145, 0), # 174 (1901, 1691, 1625, 1668, 1488, 710, 721, 590, 742, 329, 257, 135, 0, 1909, 1613, 1187, 1007, 1447, 859, 660, 469, 703, 597, 315, 147, 0), # 175 (1906, 1694, 1627, 1671, 1491, 713, 723, 592, 745, 329, 257, 135, 0, 1915, 1621, 1193, 1010, 1453, 859, 663, 470, 709, 597, 316, 148, 0), # 176 (1909, 1698, 1633, 1673, 1494, 713, 725, 594, 745, 329, 257, 136, 0, 1922, 1625, 1198, 1012, 1456, 861, 666, 471, 712, 598, 317, 148, 0), # 177 (1916, 1702, 1639, 1676, 1495, 715, 726, 596, 745, 330, 257, 138, 0, 1926, 1628, 1201, 1015, 1459, 863, 668, 472, 712, 599, 318, 148, 0), # 178 (1916, 1702, 1639, 1676, 1495, 715, 726, 596, 745, 330, 257, 138, 0, 1926, 1628, 1201, 1015, 1459, 863, 668, 472, 712, 599, 318, 148, 0), # 179 ) passenger_arriving_rate = ( (6.025038694046121, 6.077817415662483, 5.211283229612507, 5.593200996477089, 4.443748486087689, 2.197058452426137, 2.4876213692243487, 2.3265880864897115, 2.4360396248672025, 1.187404504656711, 0.8410530327771206, 0.4897915078306174, 0.0, 6.100656255094035, 5.38770658613679, 4.205265163885603, 3.562213513970132, 4.872079249734405, 3.257223321085596, 2.4876213692243487, 1.5693274660186693, 2.2218742430438443, 1.8644003321590301, 1.0422566459225016, 0.5525288559693167, 0.0), # 0 (6.425192582423969, 6.479066763559234, 5.555346591330152, 5.9626298279489545, 4.737992269979389, 2.342188508829789, 2.651681364758216, 2.479756861452854, 2.5968981305331633, 1.265694207683145, 0.8966192271912263, 0.5221216660814355, 0.0, 6.503749976927826, 5.743338326895789, 4.483096135956131, 3.7970826230494343, 5.193796261066327, 3.4716596060339957, 2.651681364758216, 1.6729917920212778, 2.3689961349896946, 1.9875432759829852, 1.1110693182660305, 0.589006069414476, 0.0), # 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172 (6.010617756487176, 4.212565484159386, 5.4967415058087115, 5.579976740029178, 5.002732767090961, 2.4931134783059927, 1.8828130278654898, 1.916503219824812, 2.7646607857153684, 0.9821778333261846, 0.7752865489788355, 0.4659654096754725, 0.0, 6.671660707462155, 5.125619506430197, 3.8764327448941778, 2.9465334999785533, 5.529321571430737, 2.6831045077547366, 1.8828130278654898, 1.7807953416471376, 2.5013663835454807, 1.859992246676393, 1.0993483011617424, 0.38296049855994424, 0.0), # 173 (5.740301548302412, 4.019097485710249, 5.2555344277646014, 5.332742469559387, 4.782710854185972, 2.3847769533326795, 1.7973526515455251, 1.8334266323965802, 2.645262281841985, 0.9382220294744842, 0.7406968001979856, 0.44527750973796687, 0.0, 6.37788372783412, 4.898052607117634, 3.7034840009899272, 2.814666088423452, 5.29052456368397, 2.5667972853552126, 1.7973526515455251, 1.7034121095233423, 2.391355427092986, 1.7775808231864625, 1.0511068855529204, 0.3653724987009318, 0.0), # 174 (5.466092988194946, 3.823453706380764, 5.009948615011508, 5.08138690392213, 4.558770479992055, 2.2743080836851397, 1.7107831715130346, 1.748684161678698, 2.5233995608043616, 0.8936014657528275, 0.7055658786666139, 0.4242517000205815, 0.0, 6.078935548272969, 4.666768700226395, 3.5278293933330693, 2.680804397258482, 5.046799121608723, 2.4481578263501773, 1.7107831715130346, 1.6245057740608142, 2.2793852399960275, 1.6937956346407106, 1.0019897230023018, 0.3475867005800695, 0.0), # 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7 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 8 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 9 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 10 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 11 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 12 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 13 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 14 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 15 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 16 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 17 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 18 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 19 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 20 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 21 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 22 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 23 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 24 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 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178 (0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 179 ) """ parameters for reproducibiliy. More information: https://numpy.org/doc/stable/reference/random/parallel.html """ #initial entropy entropy = 8991598675325360468762009371570610170 #index for seed sequence child child_seed_index = ( 1, # 0 36, # 1 )
""" PASSENGERS """ num_passengers = 22944 passenger_arriving = ((5, 6, 5, 9, 4, 1, 2, 3, 2, 1, 1, 1, 0, 7, 6, 8, 4, 8, 2, 3, 1, 0, 1, 1, 1, 0), (7, 6, 3, 10, 7, 1, 1, 1, 6, 1, 2, 1, 0, 3, 5, 7, 7, 5, 4, 5, 0, 2, 2, 0, 1, 0), (5, 3, 10, 5, 3, 3, 4, 2, 1, 1, 1, 1, 0, 9, 9, 4, 3, 5, 2, 4, 2, 4, 1, 1, 0, 0), (7, 12, 10, 9, 4, 3, 10, 0, 2, 0, 0, 1, 0, 9, 9, 7, 3, 10, 1, 1, 0, 1, 2, 0, 0, 0), (8, 6, 6, 8, 6, 3, 3, 8, 1, 2, 1, 1, 0, 13, 8, 4, 7, 5, 3, 2, 1, 6, 0, 1, 0, 0), (9, 12, 7, 8, 6, 3, 5, 5, 5, 2, 2, 1, 0, 4, 11, 8, 6, 7, 4, 5, 3, 0, 0, 1, 0, 0), (6, 8, 6, 4, 8, 3, 1, 4, 5, 5, 0, 3, 0, 6, 7, 3, 3, 10, 6, 6, 4, 1, 4, 1, 1, 0), (4, 4, 10, 5, 7, 6, 8, 4, 6, 3, 0, 2, 0, 10, 6, 3, 6, 7, 4, 1, 2, 0, 2, 3, 1, 0), (10, 7, 7, 11, 6, 1, 7, 8, 4, 1, 1, 0, 0, 11, 16, 9, 3, 8, 8, 4, 2, 4, 2, 1, 2, 0), (6, 6, 6, 11, 2, 3, 1, 1, 3, 1, 0, 1, 0, 9, 8, 7, 5, 6, 5, 3, 0, 0, 3, 0, 0, 0), (7, 8, 10, 5, 6, 4, 2, 5, 2, 0, 1, 1, 0, 13, 12, 5, 5, 9, 6, 3, 0, 4, 2, 2, 3, 0), (8, 15, 6, 15, 14, 3, 4, 0, 1, 2, 2, 1, 0, 8, 12, 10, 3, 8, 4, 4, 3, 3, 2, 0, 3, 0), (11, 13, 9, 12, 5, 2, 4, 3, 1, 2, 2, 0, 0, 11, 12, 8, 8, 9, 5, 5, 2, 6, 5, 4, 0, 0), (11, 14, 3, 13, 3, 4, 6, 4, 6, 2, 1, 1, 0, 13, 8, 7, 6, 6, 4, 3, 1, 2, 5, 6, 1, 0), (10, 11, 4, 9, 12, 4, 8, 5, 3, 0, 3, 0, 0, 8, 8, 6, 9, 7, 5, 3, 3, 2, 4, 3, 1, 0), (11, 7, 8, 14, 11, 3, 5, 3, 4, 5, 0, 1, 0, 11, 10, 6, 10, 6, 5, 3, 4, 4, 4, 2, 1, 0), (14, 17, 7, 10, 9, 3, 3, 6, 5, 3, 0, 1, 0, 11, 10, 6, 8, 8, 6, 4, 6, 6, 3, 5, 2, 0), (7, 11, 8, 5, 10, 3, 4, 5, 5, 2, 1, 1, 0, 9, 8, 6, 6, 9, 4, 6, 5, 4, 4, 4, 0, 0), (10, 10, 8, 13, 12, 4, 3, 5, 3, 1, 1, 0, 0, 14, 11, 6, 6, 3, 10, 4, 3, 2, 5, 4, 2, 0), (16, 6, 10, 8, 5, 4, 8, 3, 7, 4, 0, 0, 0, 5, 15, 6, 12, 12, 6, 5, 5, 6, 4, 1, 2, 0), (15, 10, 7, 9, 11, 7, 2, 4, 3, 4, 0, 1, 0, 9, 16, 9, 6, 9, 6, 7, 3, 4, 6, 1, 0, 0), (17, 17, 8, 17, 11, 4, 5, 5, 8, 4, 1, 2, 0, 10, 10, 11, 4, 8, 9, 6, 1, 5, 9, 2, 1, 0), (17, 19, 15, 12, 12, 4, 7, 5, 8, 3, 2, 2, 0, 11, 13, 10, 9, 5, 9, 3, 6, 7, 3, 3, 0, 0), (7, 11, 6, 12, 11, 4, 7, 3, 3, 1, 2, 0, 0, 19, 9, 4, 5, 9, 9, 5, 5, 5, 2, 4, 2, 0), (15, 11, 8, 8, 15, 7, 5, 4, 6, 2, 3, 0, 0, 13, 8, 12, 6, 11, 6, 5, 2, 7, 4, 2, 1, 0), (18, 17, 17, 5, 5, 7, 8, 6, 6, 1, 2, 0, 0, 14, 6, 6, 4, 13, 4, 4, 1, 8, 5, 0, 0, 0), (14, 10, 8, 9, 11, 4, 4, 4, 4, 1, 2, 2, 0, 19, 11, 9, 6, 9, 11, 6, 1, 1, 4, 5, 1, 0), (12, 17, 12, 11, 8, 12, 4, 8, 4, 1, 6, 1, 0, 15, 5, 7, 10, 4, 7, 2, 2, 3, 4, 1, 1, 0), (15, 17, 16, 14, 12, 3, 5, 5, 5, 1, 4, 2, 0, 6, 8, 9, 8, 4, 4, 5, 1, 4, 0, 3, 3, 0), (14, 16, 10, 15, 14, 7, 3, 5, 8, 0, 3, 0, 0, 15, 3, 10, 9, 9, 8, 3, 1, 6, 5, 2, 1, 0), (13, 15, 10, 6, 6, 4, 10, 1, 7, 3, 1, 0, 0, 11, 13, 7, 8, 12, 8, 7, 3, 3, 2, 1, 0, 0), (15, 15, 15, 15, 9, 4, 4, 3, 1, 3, 1, 1, 0, 8, 17, 8, 7, 9, 5, 7, 2, 7, 5, 4, 3, 0), (13, 11, 16, 11, 10, 3, 8, 9, 5, 2, 3, 0, 0, 4, 10, 12, 5, 12, 8, 3, 5, 3, 4, 2, 0, 0), (11, 18, 10, 12, 10, 4, 4, 3, 7, 0, 6, 1, 0, 14, 13, 12, 4, 9, 7, 7, 1, 6, 0, 0, 1, 0), (7, 16, 18, 13, 11, 3, 5, 9, 8, 4, 0, 2, 0, 13, 10, 8, 3, 10, 4, 4, 1, 1, 3, 0, 1, 0), (18, 12, 9, 14, 7, 4, 4, 2, 4, 2, 1, 1, 0, 6, 5, 2, 12, 9, 8, 4, 4, 5, 2, 1, 1, 0), (14, 10, 13, 15, 5, 6, 5, 2, 2, 3, 1, 0, 0, 9, 10, 5, 11, 15, 2, 4, 2, 6, 5, 3, 0, 0), (12, 12, 7, 10, 12, 3, 7, 4, 3, 1, 3, 1, 0, 7, 4, 7, 7, 5, 5, 4, 2, 3, 3, 3, 0, 0), (13, 17, 15, 10, 13, 2, 8, 8, 3, 5, 2, 1, 0, 12, 13, 11, 6, 8, 9, 6, 4, 5, 4, 2, 0, 0), (14, 5, 20, 5, 8, 3, 4, 3, 10, 2, 3, 1, 0, 14, 8, 12, 5, 8, 9, 6, 6, 4, 2, 1, 1, 0), (9, 8, 5, 8, 5, 2, 2, 2, 5, 2, 1, 1, 0, 10, 5, 7, 10, 12, 12, 7, 1, 7, 2, 1, 2, 0), (11, 9, 8, 8, 4, 4, 9, 7, 6, 3, 3, 0, 0, 8, 14, 5, 13, 7, 4, 7, 2, 6, 3, 0, 0, 0), (11, 12, 8, 9, 6, 5, 5, 6, 1, 1, 0, 0, 0, 5, 4, 9, 6, 15, 6, 4, 3, 3, 2, 1, 2, 0), (11, 21, 9, 11, 9, 6, 7, 9, 3, 2, 0, 1, 0, 17, 13, 12, 7, 9, 8, 4, 2, 2, 5, 3, 1, 0), (13, 17, 10, 14, 10, 7, 6, 2, 3, 1, 2, 1, 0, 8, 12, 6, 3, 3, 3, 5, 4, 6, 4, 3, 0, 0), (14, 17, 6, 8, 12, 8, 6, 4, 7, 3, 3, 1, 0, 13, 10, 11, 9, 11, 4, 6, 4, 1, 3, 3, 1, 0), (12, 17, 12, 9, 10, 4, 11, 7, 3, 3, 1, 0, 0, 14, 5, 6, 8, 8, 3, 6, 2, 3, 3, 1, 0, 0), (18, 15, 9, 9, 16, 6, 3, 3, 4, 0, 4, 0, 0, 9, 7, 6, 6, 10, 8, 8, 2, 5, 4, 3, 2, 0), (10, 10, 10, 10, 7, 5, 3, 4, 3, 6, 0, 0, 0, 10, 10, 6, 8, 10, 5, 3, 2, 4, 1, 3, 0, 0), (13, 7, 11, 13, 7, 1, 3, 4, 7, 4, 0, 0, 0, 11, 11, 9, 7, 8, 7, 3, 1, 4, 5, 2, 0, 0), (17, 16, 11, 12, 11, 2, 1, 6, 9, 0, 2, 1, 0, 10, 10, 10, 13, 4, 3, 4, 2, 3, 3, 1, 1, 0), (11, 16, 12, 13, 11, 5, 9, 3, 2, 2, 1, 1, 0, 12, 5, 7, 6, 8, 6, 4, 1, 2, 4, 1, 2, 0), (13, 11, 5, 11, 10, 4, 4, 3, 4, 2, 2, 2, 0, 10, 10, 8, 9, 8, 5, 8, 5, 1, 5, 3, 0, 0), (10, 12, 13, 12, 6, 5, 5, 3, 6, 2, 0, 1, 0, 11, 12, 6, 7, 15, 5, 2, 5, 4, 5, 1, 2, 0), (14, 8, 11, 8, 8, 4, 3, 0, 4, 3, 3, 0, 0, 14, 7, 6, 8, 8, 5, 5, 1, 3, 5, 3, 0, 0), (12, 18, 11, 9, 8, 7, 5, 6, 3, 0, 1, 0, 0, 15, 9, 10, 9, 10, 6, 0, 4, 2, 1, 2, 0, 0), (17, 11, 7, 13, 8, 4, 3, 5, 3, 2, 1, 0, 0, 18, 7, 8, 7, 9, 5, 1, 5, 5, 7, 2, 1, 0), (8, 12, 13, 6, 11, 3, 6, 4, 5, 3, 0, 0, 0, 7, 6, 6, 7, 15, 3, 3, 4, 2, 2, 2, 1, 0), (7, 11, 6, 14, 9, 5, 5, 4, 6, 5, 1, 2, 0, 11, 14, 6, 6, 11, 9, 1, 3, 5, 7, 2, 2, 0), (13, 10, 7, 8, 7, 5, 4, 5, 5, 3, 1, 1, 0, 10, 19, 7, 2, 3, 4, 2, 2, 5, 6, 2, 1, 0), (16, 8, 9, 14, 11, 2, 6, 1, 8, 3, 0, 1, 0, 17, 10, 7, 6, 6, 7, 8, 3, 3, 6, 4, 0, 0), (18, 15, 15, 10, 4, 5, 7, 4, 3, 3, 4, 1, 0, 14, 10, 12, 2, 11, 7, 10, 5, 3, 4, 1, 0, 0), (11, 9, 9, 12, 12, 4, 1, 2, 5, 4, 3, 0, 0, 9, 14, 9, 6, 6, 3, 6, 4, 9, 5, 2, 1, 0), (17, 8, 12, 8, 11, 2, 4, 4, 5, 3, 3, 1, 0, 12, 6, 10, 6, 6, 4, 6, 3, 2, 5, 0, 1, 0), (15, 10, 12, 5, 12, 6, 2, 1, 6, 0, 2, 2, 0, 18, 13, 10, 7, 8, 5, 5, 3, 8, 1, 3, 1, 0), (13, 14, 13, 7, 6, 3, 14, 5, 6, 4, 2, 0, 0, 17, 13, 7, 2, 11, 7, 4, 4, 6, 2, 2, 1, 0), (7, 12, 14, 10, 7, 4, 4, 2, 2, 2, 0, 2, 0, 9, 9, 6, 6, 10, 5, 3, 3, 7, 2, 3, 1, 0), (9, 8, 11, 9, 9, 7, 2, 4, 5, 3, 0, 0, 0, 11, 11, 4, 7, 7, 5, 5, 6, 8, 5, 0, 1, 0), (7, 17, 4, 4, 15, 6, 5, 9, 8, 4, 2, 0, 0, 10, 9, 7, 12, 9, 5, 6, 3, 5, 3, 1, 2, 0), (8, 8, 8, 14, 8, 3, 3, 2, 6, 1, 3, 0, 0, 12, 11, 8, 5, 7, 3, 3, 2, 5, 7, 1, 0, 0), (13, 10, 6, 9, 7, 4, 3, 3, 3, 0, 2, 1, 0, 9, 6, 4, 7, 8, 5, 4, 3, 6, 2, 2, 2, 0), (11, 4, 8, 16, 9, 3, 5, 2, 2, 2, 3, 3, 0, 14, 10, 6, 5, 5, 4, 5, 3, 3, 5, 1, 0, 0), (11, 14, 11, 8, 11, 5, 7, 3, 5, 1, 2, 0, 0, 13, 16, 7, 5, 6, 9, 7, 3, 10, 5, 2, 1, 0), (14, 9, 14, 12, 14, 7, 4, 2, 1, 3, 0, 1, 0, 11, 9, 6, 9, 10, 4, 4, 4, 6, 3, 2, 1, 0), (12, 18, 17, 12, 7, 4, 5, 3, 6, 1, 2, 1, 0, 7, 12, 8, 5, 11, 4, 3, 6, 5, 5, 3, 1, 0), (16, 18, 10, 19, 11, 2, 5, 2, 8, 4, 1, 2, 0, 11, 7, 6, 6, 12, 1, 5, 0, 5, 4, 2, 1, 0), (10, 7, 9, 15, 12, 5, 7, 3, 6, 1, 1, 0, 0, 8, 8, 9, 7, 9, 9, 7, 3, 6, 0, 0, 1, 0), (17, 13, 12, 9, 14, 4, 7, 0, 5, 1, 1, 1, 0, 11, 6, 6, 3, 12, 8, 7, 3, 4, 4, 1, 4, 0), (19, 13, 9, 10, 13, 7, 6, 7, 5, 1, 1, 1, 0, 8, 12, 5, 3, 10, 4, 3, 4, 2, 6, 3, 0, 0), (7, 11, 6, 8, 6, 4, 1, 6, 5, 4, 3, 2, 0, 12, 9, 5, 4, 14, 7, 6, 2, 2, 6, 2, 3, 0), (13, 15, 5, 13, 11, 7, 8, 0, 6, 1, 0, 1, 0, 14, 7, 14, 7, 14, 2, 3, 2, 1, 1, 2, 0, 0), (12, 7, 10, 12, 8, 2, 2, 2, 4, 1, 1, 2, 0, 11, 9, 9, 5, 9, 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4, 2, 0), (47, 53, 47, 53, 38, 17, 26, 23, 22, 12, 7, 9, 0, 51, 55, 41, 33, 50, 22, 26, 11, 14, 10, 5, 3, 0), (51, 57, 57, 58, 45, 23, 34, 27, 28, 15, 7, 11, 0, 61, 61, 44, 39, 57, 26, 27, 13, 14, 12, 8, 4, 0), (61, 64, 64, 69, 51, 24, 41, 35, 32, 16, 8, 11, 0, 72, 77, 53, 42, 65, 34, 31, 15, 18, 14, 9, 6, 0), (67, 70, 70, 80, 53, 27, 42, 36, 35, 17, 8, 12, 0, 81, 85, 60, 47, 71, 39, 34, 15, 18, 17, 9, 6, 0), (74, 78, 80, 85, 59, 31, 44, 41, 37, 17, 9, 13, 0, 94, 97, 65, 52, 80, 45, 37, 15, 22, 19, 11, 9, 0), (82, 93, 86, 100, 73, 34, 48, 41, 38, 19, 11, 14, 0, 102, 109, 75, 55, 88, 49, 41, 18, 25, 21, 11, 12, 0), (93, 106, 95, 112, 78, 36, 52, 44, 39, 21, 13, 14, 0, 113, 121, 83, 63, 97, 54, 46, 20, 31, 26, 15, 12, 0), (104, 120, 98, 125, 81, 40, 58, 48, 45, 23, 14, 15, 0, 126, 129, 90, 69, 103, 58, 49, 21, 33, 31, 21, 13, 0), (114, 131, 102, 134, 93, 44, 66, 53, 48, 23, 17, 15, 0, 134, 137, 96, 78, 110, 63, 52, 24, 35, 35, 24, 14, 0), (125, 138, 110, 148, 104, 47, 71, 56, 52, 28, 17, 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0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1)) '\nparameters for reproducibiliy. More information: https://numpy.org/doc/stable/reference/random/parallel.html\n' entropy = 8991598675325360468762009371570610170 child_seed_index = (1, 36)
# -*- coding: utf-8 -*- # # Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not use this file except in compliance # with the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. # AIRFLOW_VAR_NAME_FORMAT_MAPPING = { 'AIRFLOW_CONTEXT_DAG_ID': {'default': 'airflow.ctx.dag_id', 'env_var_format': 'AIRFLOW_CTX_DAG_ID'}, 'AIRFLOW_CONTEXT_TASK_ID': {'default': 'airflow.ctx.task_id', 'env_var_format': 'AIRFLOW_CTX_TASK_ID'}, 'AIRFLOW_CONTEXT_EXECUTION_DATE': {'default': 'airflow.ctx.execution_date', 'env_var_format': 'AIRFLOW_CTX_EXECUTION_DATE'}, 'AIRFLOW_CONTEXT_DAG_RUN_ID': {'default': 'airflow.ctx.dag_run_id', 'env_var_format': 'AIRFLOW_CTX_DAG_RUN_ID'} } def context_to_airflow_vars(context, in_env_var_format=False): """ Given a context, this function provides a dictionary of values that can be used to externally reconstruct relations between dags, dag_runs, tasks and task_instances. Default to abc.def.ghi format and can be made to ABC_DEF_GHI format if in_env_var_format is set to True. :param context: The context for the task_instance of interest. :type context: dict :param in_env_var_format: If returned vars should be in ABC_DEF_GHI format. :type in_env_var_format: bool :return: task_instance context as dict. """ params = dict() if in_env_var_format: name_format = 'env_var_format' else: name_format = 'default' task_instance = context.get('task_instance') if task_instance and task_instance.dag_id: params[AIRFLOW_VAR_NAME_FORMAT_MAPPING['AIRFLOW_CONTEXT_DAG_ID'][ name_format]] = task_instance.dag_id if task_instance and task_instance.task_id: params[AIRFLOW_VAR_NAME_FORMAT_MAPPING['AIRFLOW_CONTEXT_TASK_ID'][ name_format]] = task_instance.task_id if task_instance and task_instance.execution_date: params[ AIRFLOW_VAR_NAME_FORMAT_MAPPING['AIRFLOW_CONTEXT_EXECUTION_DATE'][ name_format]] = task_instance.execution_date.isoformat() dag_run = context.get('dag_run') if dag_run and dag_run.run_id: params[AIRFLOW_VAR_NAME_FORMAT_MAPPING['AIRFLOW_CONTEXT_DAG_RUN_ID'][ name_format]] = dag_run.run_id return params
airflow_var_name_format_mapping = {'AIRFLOW_CONTEXT_DAG_ID': {'default': 'airflow.ctx.dag_id', 'env_var_format': 'AIRFLOW_CTX_DAG_ID'}, 'AIRFLOW_CONTEXT_TASK_ID': {'default': 'airflow.ctx.task_id', 'env_var_format': 'AIRFLOW_CTX_TASK_ID'}, 'AIRFLOW_CONTEXT_EXECUTION_DATE': {'default': 'airflow.ctx.execution_date', 'env_var_format': 'AIRFLOW_CTX_EXECUTION_DATE'}, 'AIRFLOW_CONTEXT_DAG_RUN_ID': {'default': 'airflow.ctx.dag_run_id', 'env_var_format': 'AIRFLOW_CTX_DAG_RUN_ID'}} def context_to_airflow_vars(context, in_env_var_format=False): """ Given a context, this function provides a dictionary of values that can be used to externally reconstruct relations between dags, dag_runs, tasks and task_instances. Default to abc.def.ghi format and can be made to ABC_DEF_GHI format if in_env_var_format is set to True. :param context: The context for the task_instance of interest. :type context: dict :param in_env_var_format: If returned vars should be in ABC_DEF_GHI format. :type in_env_var_format: bool :return: task_instance context as dict. """ params = dict() if in_env_var_format: name_format = 'env_var_format' else: name_format = 'default' task_instance = context.get('task_instance') if task_instance and task_instance.dag_id: params[AIRFLOW_VAR_NAME_FORMAT_MAPPING['AIRFLOW_CONTEXT_DAG_ID'][name_format]] = task_instance.dag_id if task_instance and task_instance.task_id: params[AIRFLOW_VAR_NAME_FORMAT_MAPPING['AIRFLOW_CONTEXT_TASK_ID'][name_format]] = task_instance.task_id if task_instance and task_instance.execution_date: params[AIRFLOW_VAR_NAME_FORMAT_MAPPING['AIRFLOW_CONTEXT_EXECUTION_DATE'][name_format]] = task_instance.execution_date.isoformat() dag_run = context.get('dag_run') if dag_run and dag_run.run_id: params[AIRFLOW_VAR_NAME_FORMAT_MAPPING['AIRFLOW_CONTEXT_DAG_RUN_ID'][name_format]] = dag_run.run_id return params
x = int(input()) y = float(input()) gasto = x / y print('{:.3f} km/l'.format(gasto))
x = int(input()) y = float(input()) gasto = x / y print('{:.3f} km/l'.format(gasto))
# Created by MechAviv # ID :: [931050000] # Hidden Street : Extraction Room 1 sm.curNodeEventEnd(True) sm.setTemporarySkillSet(0) sm.setInGameDirectionMode(True, True, False, False) sm.setStandAloneMode(True) def failMessage(crack): sm.chatScript("Tap the Control Key repeatedly to break the wall.") sm.showEffect("Effect/Direction6.img/effect/tuto/guide1/0", 3000, 0, -100, 20, 0, False, 0) sm.showEffect("Effect/Direction6.img/effect/tuto/breakEgg/" + str(crack), 6600, 0, 0, 1, 0, False, 0) if not "1" in sm.getQRValue(23206): sm.createQuestWithQRValue(23206, "1") sm.levelUntil(10) sm.sendDelay(3000) sm.showFieldEffect("demonSlayer/text12", 0) sm.sendDelay(5000) sm.forcedInput(1) sm.sendDelay(10) sm.forcedInput(0) sm.setSpeakerID(2159311) sm.removeEscapeButton() sm.setPlayerAsSpeaker() sm.setSpeakerType(3) sm.sendNext("........") sm.showEffect("Effect/Direction6.img/effect/tuto/balloonMsg0/14", 2000, 130, 50, 10, 0, False, 0) sm.sendDelay(2000) sm.setSpeakerID(2159311) sm.removeEscapeButton() sm.setPlayerAsSpeaker() sm.setSpeakerType(3) sm.sendNext("(I think I hear something...)") sm.showEffect("Effect/Direction6.img/effect/tuto/balloonMsg0/15", 2000, -130, 50, 10, 0, False, 0) sm.sendDelay(2000) sm.setSpeakerID(2159311) sm.removeEscapeButton() sm.setPlayerAsSpeaker() sm.setSpeakerType(3) sm.sendNext("(Where am I? Am I still alive...?)") sm.showEffect("Effect/Direction6.img/effect/tuto/balloonMsg0/16", 2000, 130, 50, 10, 0, False, 0) sm.sendDelay(2000) sm.setSpeakerID(2159311) sm.removeEscapeButton() sm.setPlayerAsSpeaker() sm.setSpeakerType(3) sm.sendNext("(Ugh... My energy... Something is stealing my energy!)") sm.showEffect("Effect/Direction6.img/effect/tuto/balloonMsg0/17", 2000, -130, 50, 10, 0, False, 0) sm.sendDelay(2000) sm.setSpeakerID(2159311) sm.removeEscapeButton() sm.setPlayerAsSpeaker() sm.setSpeakerType(3) sm.sendNext("(I must escape before they drain all my power!)") sm.setPatternInputCount(0) sm.chatScript("Tap the Control Key repeatedly to break the wall.") sm.showEffect("Effect/Direction6.img/effect/tuto/guide1/0", 3000, 0, -100, 20, 0, False, 0) while not sm.patternInputRequest("17#17#17#", 2, 2, 3000) and sm.getPatternInputCount() < 7: failMessage(0) sm.setPatternInputCount(0) sm.playSound("demonSlayer/punch", 100) sm.playSound("demonSlayer/crackEgg", 100) sm.chatScript("Tap the Control Key repeatedly to break the wall.") sm.showEffect("Effect/Direction6.img/effect/tuto/guide1/0", 3000, 0, -100, 20, 0, False, 0) sm.showEffect("Effect/Direction6.img/effect/tuto/breakEgg/0", 6600, 0, 0, 1, 0, False, 0) while not sm.patternInputRequest("17#17#17#", 2, 2, 3000) and sm.getPatternInputCount() < 7: failMessage(0) sm.setPatternInputCount(0) sm.playSound("demonSlayer/punch", 100) sm.playSound("demonSlayer/crackEgg", 100) sm.showEffect("Effect/Direction6.img/effect/tuto/balloonMsg0/7", 2000, 130, 100, 10, 0, False, 0) sm.chatScript("Tap the Control Key repeatedly to break the wall.") sm.showEffect("Effect/Direction6.img/effect/tuto/guide1/0", 3000, 0, -100, 20, 0, False, 0) sm.showEffect("Effect/Direction6.img/effect/tuto/breakEgg/0", 6600, 0, 0, 1, 0, False, 0) while not sm.patternInputRequest("17#17#17#", 2, 2, 3000) and sm.getPatternInputCount() < 7: failMessage(0) sm.setPatternInputCount(0) sm.playSound("demonSlayer/punch", 100) sm.playSound("demonSlayer/crackEgg", 100) sm.chatScript("Tap the Control Key repeatedly to break the wall.") sm.showEffect("Effect/Direction6.img/effect/tuto/guide1/0", 3000, 0, -100, 20, 0, False, 0) sm.showEffect("Effect/Direction6.img/effect/tuto/breakEgg/1", 6600, 0, 0, 1, 0, False, 0) while not sm.patternInputRequest("17#17#17#", 2, 2, 3000) and sm.getPatternInputCount() < 7: failMessage(1) sm.setPatternInputCount(0) sm.showEffect("Effect/Direction6.img/effect/tuto/breakEgg/0", 3600, 0, 0, 1, 0, False, 0) sm.sendDelay(3000) sm.showEffect("Effect/Direction6.img/effect/tuto/breakEgg/1", 3600, 0, 0, 1, 0, False, 0) sm.showEffect("Effect/Direction6.img/effect/tuto/balloonMsg1/1", 2000, -130, 50, 10, 0, False, 0) sm.playSound("demonSlayer/crackEgg", 100) sm.sendDelay(1000) sm.showEffect("Effect/Direction6.img/effect/tuto/breakEgg/2", 9000, 0, 0, 1, 0, False, 0) sm.showEffect("Effect/Direction6.img/effect/tuto/balloonMsg1/2", 2000, 130, 50, 10, 0, False, 0) sm.sendDelay(1000) sm.playSound("demonSlayer/breakEgg", 100) sm.showFieldEffect("demonSlayer/whiteOut", 0) sm.warpInstanceIn(931050020, 0)
sm.curNodeEventEnd(True) sm.setTemporarySkillSet(0) sm.setInGameDirectionMode(True, True, False, False) sm.setStandAloneMode(True) def fail_message(crack): sm.chatScript('Tap the Control Key repeatedly to break the wall.') sm.showEffect('Effect/Direction6.img/effect/tuto/guide1/0', 3000, 0, -100, 20, 0, False, 0) sm.showEffect('Effect/Direction6.img/effect/tuto/breakEgg/' + str(crack), 6600, 0, 0, 1, 0, False, 0) if not '1' in sm.getQRValue(23206): sm.createQuestWithQRValue(23206, '1') sm.levelUntil(10) sm.sendDelay(3000) sm.showFieldEffect('demonSlayer/text12', 0) sm.sendDelay(5000) sm.forcedInput(1) sm.sendDelay(10) sm.forcedInput(0) sm.setSpeakerID(2159311) sm.removeEscapeButton() sm.setPlayerAsSpeaker() sm.setSpeakerType(3) sm.sendNext('........') sm.showEffect('Effect/Direction6.img/effect/tuto/balloonMsg0/14', 2000, 130, 50, 10, 0, False, 0) sm.sendDelay(2000) sm.setSpeakerID(2159311) sm.removeEscapeButton() sm.setPlayerAsSpeaker() sm.setSpeakerType(3) sm.sendNext('(I think I hear something...)') sm.showEffect('Effect/Direction6.img/effect/tuto/balloonMsg0/15', 2000, -130, 50, 10, 0, False, 0) sm.sendDelay(2000) sm.setSpeakerID(2159311) sm.removeEscapeButton() sm.setPlayerAsSpeaker() sm.setSpeakerType(3) sm.sendNext('(Where am I? Am I still alive...?)') sm.showEffect('Effect/Direction6.img/effect/tuto/balloonMsg0/16', 2000, 130, 50, 10, 0, False, 0) sm.sendDelay(2000) sm.setSpeakerID(2159311) sm.removeEscapeButton() sm.setPlayerAsSpeaker() sm.setSpeakerType(3) sm.sendNext('(Ugh... My energy... Something is stealing my energy!)') sm.showEffect('Effect/Direction6.img/effect/tuto/balloonMsg0/17', 2000, -130, 50, 10, 0, False, 0) sm.sendDelay(2000) sm.setSpeakerID(2159311) sm.removeEscapeButton() sm.setPlayerAsSpeaker() sm.setSpeakerType(3) sm.sendNext('(I must escape before they drain all my power!)') sm.setPatternInputCount(0) sm.chatScript('Tap the Control Key repeatedly to break the wall.') sm.showEffect('Effect/Direction6.img/effect/tuto/guide1/0', 3000, 0, -100, 20, 0, False, 0) while not sm.patternInputRequest('17#17#17#', 2, 2, 3000) and sm.getPatternInputCount() < 7: fail_message(0) sm.setPatternInputCount(0) sm.playSound('demonSlayer/punch', 100) sm.playSound('demonSlayer/crackEgg', 100) sm.chatScript('Tap the Control Key repeatedly to break the wall.') sm.showEffect('Effect/Direction6.img/effect/tuto/guide1/0', 3000, 0, -100, 20, 0, False, 0) sm.showEffect('Effect/Direction6.img/effect/tuto/breakEgg/0', 6600, 0, 0, 1, 0, False, 0) while not sm.patternInputRequest('17#17#17#', 2, 2, 3000) and sm.getPatternInputCount() < 7: fail_message(0) sm.setPatternInputCount(0) sm.playSound('demonSlayer/punch', 100) sm.playSound('demonSlayer/crackEgg', 100) sm.showEffect('Effect/Direction6.img/effect/tuto/balloonMsg0/7', 2000, 130, 100, 10, 0, False, 0) sm.chatScript('Tap the Control Key repeatedly to break the wall.') sm.showEffect('Effect/Direction6.img/effect/tuto/guide1/0', 3000, 0, -100, 20, 0, False, 0) sm.showEffect('Effect/Direction6.img/effect/tuto/breakEgg/0', 6600, 0, 0, 1, 0, False, 0) while not sm.patternInputRequest('17#17#17#', 2, 2, 3000) and sm.getPatternInputCount() < 7: fail_message(0) sm.setPatternInputCount(0) sm.playSound('demonSlayer/punch', 100) sm.playSound('demonSlayer/crackEgg', 100) sm.chatScript('Tap the Control Key repeatedly to break the wall.') sm.showEffect('Effect/Direction6.img/effect/tuto/guide1/0', 3000, 0, -100, 20, 0, False, 0) sm.showEffect('Effect/Direction6.img/effect/tuto/breakEgg/1', 6600, 0, 0, 1, 0, False, 0) while not sm.patternInputRequest('17#17#17#', 2, 2, 3000) and sm.getPatternInputCount() < 7: fail_message(1) sm.setPatternInputCount(0) sm.showEffect('Effect/Direction6.img/effect/tuto/breakEgg/0', 3600, 0, 0, 1, 0, False, 0) sm.sendDelay(3000) sm.showEffect('Effect/Direction6.img/effect/tuto/breakEgg/1', 3600, 0, 0, 1, 0, False, 0) sm.showEffect('Effect/Direction6.img/effect/tuto/balloonMsg1/1', 2000, -130, 50, 10, 0, False, 0) sm.playSound('demonSlayer/crackEgg', 100) sm.sendDelay(1000) sm.showEffect('Effect/Direction6.img/effect/tuto/breakEgg/2', 9000, 0, 0, 1, 0, False, 0) sm.showEffect('Effect/Direction6.img/effect/tuto/balloonMsg1/2', 2000, 130, 50, 10, 0, False, 0) sm.sendDelay(1000) sm.playSound('demonSlayer/breakEgg', 100) sm.showFieldEffect('demonSlayer/whiteOut', 0) sm.warpInstanceIn(931050020, 0)
class HTTPError(Exception): pass class VersionSpecificationError(Exception): pass
class Httperror(Exception): pass class Versionspecificationerror(Exception): pass
# -*- coding: utf-8 -*- ''' Splunk User State Module .. versionadded:: 2016.3.0. This state is used to ensure presence of users in splunk. .. code-block:: yaml ensure example test user 1: splunk.present: - name: 'Example TestUser1' - email: [email protected] ''' def __virtual__(): ''' Only load if the splunk module is available in __salt__ ''' return 'splunk' if 'splunk.list_users' in __salt__ else False def present(email, profile="splunk", **kwargs): ''' Ensure a user is present .. code-block:: yaml ensure example test user 1: splunk.user_present: - realname: 'Example TestUser1' - name: 'exampleuser' - email: '[email protected]' - roles: ['user'] The following parameters are required: email This is the email of the user in splunk ''' name = kwargs.get('name') ret = { 'name': name, 'changes': {}, 'result': None, 'comment': '' } target = __salt__['splunk.get_user'](email, profile=profile, user_details=True) if not target: if __opts__['test']: ret['comment'] = 'User {0} will be created'.format(name) return ret # create the user result = __salt__['splunk.create_user']( email, profile=profile, **kwargs ) if result: ret['changes'].setdefault('old', None) ret['changes'].setdefault('new', 'User {0} exists'.format(name)) ret['result'] = True else: ret['result'] = False ret['comment'] = 'Failed to create {0}'.format(name) return ret else: ret['comment'] = 'User {0} set to be updated.'.format(name) if __opts__['test']: ret['result'] = None return ret # found a user... updating result = __salt__['splunk.update_user']( email, profile, **kwargs ) if isinstance(result, bool) and result: # no update ret['result'] = None ret['comment'] = "No changes" else: diff = {} for field in ['name', 'realname', 'roles', 'defaultApp', 'tz', 'capabilities']: if field == 'roles': diff['roles'] = list(set(target.get(field, [])).symmetric_difference(set(result.get(field, [])))) elif target.get(field) != result.get(field): diff[field] = result.get(field) newvalues = result ret['result'] = True ret['changes']['diff'] = diff ret['changes']['old'] = target ret['changes']['new'] = newvalues return ret def absent(email, profile="splunk", **kwargs): ''' Ensure a splunk user is absent .. code-block:: yaml ensure example test user 1: splunk.absent: - email: '[email protected]' - name: 'exampleuser' The following parameters are required: email This is the email of the user in splunk name This is the splunk username used to identify the user. ''' user_identity = kwargs.get('name') ret = { 'name': user_identity, 'changes': {}, 'result': None, 'comment': 'User {0} is absent.'.format(user_identity) } target = __salt__['splunk.get_user'](email, profile=profile) if not target: ret['comment'] = 'User {0} does not exist'.format(user_identity) ret['result'] = True return ret if __opts__['test']: ret['comment'] = "User {0} is all set to be deleted".format(user_identity) ret['result'] = None return ret result = __salt__['splunk.delete_user'](email, profile=profile) if result: ret['comment'] = 'Deleted user {0}'.format(user_identity) ret['changes'].setdefault('old', 'User {0} exists'.format(user_identity)) ret['changes'].setdefault('new', 'User {0} deleted'.format(user_identity)) ret['result'] = True else: ret['comment'] = 'Failed to delete {0}'.format(user_identity) ret['result'] = False return ret
""" Splunk User State Module .. versionadded:: 2016.3.0. This state is used to ensure presence of users in splunk. .. code-block:: yaml ensure example test user 1: splunk.present: - name: 'Example TestUser1' - email: [email protected] """ def __virtual__(): """ Only load if the splunk module is available in __salt__ """ return 'splunk' if 'splunk.list_users' in __salt__ else False def present(email, profile='splunk', **kwargs): """ Ensure a user is present .. code-block:: yaml ensure example test user 1: splunk.user_present: - realname: 'Example TestUser1' - name: 'exampleuser' - email: '[email protected]' - roles: ['user'] The following parameters are required: email This is the email of the user in splunk """ name = kwargs.get('name') ret = {'name': name, 'changes': {}, 'result': None, 'comment': ''} target = __salt__['splunk.get_user'](email, profile=profile, user_details=True) if not target: if __opts__['test']: ret['comment'] = 'User {0} will be created'.format(name) return ret result = __salt__['splunk.create_user'](email, profile=profile, **kwargs) if result: ret['changes'].setdefault('old', None) ret['changes'].setdefault('new', 'User {0} exists'.format(name)) ret['result'] = True else: ret['result'] = False ret['comment'] = 'Failed to create {0}'.format(name) return ret else: ret['comment'] = 'User {0} set to be updated.'.format(name) if __opts__['test']: ret['result'] = None return ret result = __salt__['splunk.update_user'](email, profile, **kwargs) if isinstance(result, bool) and result: ret['result'] = None ret['comment'] = 'No changes' else: diff = {} for field in ['name', 'realname', 'roles', 'defaultApp', 'tz', 'capabilities']: if field == 'roles': diff['roles'] = list(set(target.get(field, [])).symmetric_difference(set(result.get(field, [])))) elif target.get(field) != result.get(field): diff[field] = result.get(field) newvalues = result ret['result'] = True ret['changes']['diff'] = diff ret['changes']['old'] = target ret['changes']['new'] = newvalues return ret def absent(email, profile='splunk', **kwargs): """ Ensure a splunk user is absent .. code-block:: yaml ensure example test user 1: splunk.absent: - email: '[email protected]' - name: 'exampleuser' The following parameters are required: email This is the email of the user in splunk name This is the splunk username used to identify the user. """ user_identity = kwargs.get('name') ret = {'name': user_identity, 'changes': {}, 'result': None, 'comment': 'User {0} is absent.'.format(user_identity)} target = __salt__['splunk.get_user'](email, profile=profile) if not target: ret['comment'] = 'User {0} does not exist'.format(user_identity) ret['result'] = True return ret if __opts__['test']: ret['comment'] = 'User {0} is all set to be deleted'.format(user_identity) ret['result'] = None return ret result = __salt__['splunk.delete_user'](email, profile=profile) if result: ret['comment'] = 'Deleted user {0}'.format(user_identity) ret['changes'].setdefault('old', 'User {0} exists'.format(user_identity)) ret['changes'].setdefault('new', 'User {0} deleted'.format(user_identity)) ret['result'] = True else: ret['comment'] = 'Failed to delete {0}'.format(user_identity) ret['result'] = False return ret
#!/usr/bin/env python #fn: copy.py # write specifi contents of alignment_py.py to blast_py.py INPUT = open('alignment_py.py','r') OUTPUT = open('blast_py.py','a') lnum = 0 for line in INPUT: lnum += 1 line = line.strip('\n') if lnum > 6 and lnum < 138: OUTPUT.write(line+'\n')
input = open('alignment_py.py', 'r') output = open('blast_py.py', 'a') lnum = 0 for line in INPUT: lnum += 1 line = line.strip('\n') if lnum > 6 and lnum < 138: OUTPUT.write(line + '\n')
"""WebSocket message class""" class WebSocketMessage: """A class representing a WS message""" # pylint: disable=redefined-builtin,invalid-name __slots__ = ["type", "id", "data", "reply"] def __init__(self, data: dict) -> None: self.type = data["type"] self.id = data.get("id") self.data = data self.reply = data.get("reply") def success(self, data: object) -> dict: """Generates a success response""" return { "type": "reply", "id": self.id, "success": True, "data": data } def error(self, type: str, message: str) -> dict: """Generates an error response""" return { "type": "reply", "id": self.id, "success": False, "error": { "type": type, "message": message } }
"""WebSocket message class""" class Websocketmessage: """A class representing a WS message""" __slots__ = ['type', 'id', 'data', 'reply'] def __init__(self, data: dict) -> None: self.type = data['type'] self.id = data.get('id') self.data = data self.reply = data.get('reply') def success(self, data: object) -> dict: """Generates a success response""" return {'type': 'reply', 'id': self.id, 'success': True, 'data': data} def error(self, type: str, message: str) -> dict: """Generates an error response""" return {'type': 'reply', 'id': self.id, 'success': False, 'error': {'type': type, 'message': message}}
__author__ = 'sanyi' class IpsetError(Exception): pass class IpsetNotFound(Exception): pass class IpsetNoRights(Exception): pass class IpsetInvalidResponse(Exception): pass class IpsetCommandHangs(Exception): pass class IpsetSetNotFound(Exception): pass class IpsetEntryNotFound(Exception): pass
__author__ = 'sanyi' class Ipseterror(Exception): pass class Ipsetnotfound(Exception): pass class Ipsetnorights(Exception): pass class Ipsetinvalidresponse(Exception): pass class Ipsetcommandhangs(Exception): pass class Ipsetsetnotfound(Exception): pass class Ipsetentrynotfound(Exception): pass
# MODFLOW 6 version file automatically created using...make_release.py # created on...February 18, 2021 08:23:34 major = 6 minor = 2 micro = 1 __version__ = '{:d}.{:d}.{:d}'.format(major, minor, micro)
major = 6 minor = 2 micro = 1 __version__ = '{:d}.{:d}.{:d}'.format(major, minor, micro)
def getFuel(data): return [int(s) for s in data.split("\n")] def fuelbois(n): return (n // 3) - 2 def part1(data): return sum(map(fuelbois, getFuel(data))) def part2(data): return sum(map(doTheThing, getFuel(data))) def doTheThing(n): s = fuelbois(n) if s <= 0: return 0 return s + doTheThing(s)
def get_fuel(data): return [int(s) for s in data.split('\n')] def fuelbois(n): return n // 3 - 2 def part1(data): return sum(map(fuelbois, get_fuel(data))) def part2(data): return sum(map(doTheThing, get_fuel(data))) def do_the_thing(n): s = fuelbois(n) if s <= 0: return 0 return s + do_the_thing(s)
class Sidelink: def __init__(self, name, link, subtitle, http=False, css_classes='sidelink', onclick=''): self.name = name self.link = link self.subtitle = subtitle self.http = http self.css_classes = css_classes self.onclick = onclick class Sidebar: def __init__(self, name, link, http=False): self.name = name self.link = link self.http = http
class Sidelink: def __init__(self, name, link, subtitle, http=False, css_classes='sidelink', onclick=''): self.name = name self.link = link self.subtitle = subtitle self.http = http self.css_classes = css_classes self.onclick = onclick class Sidebar: def __init__(self, name, link, http=False): self.name = name self.link = link self.http = http
class InvalidNoteException(Exception): pass class InvalidModeException(Exception): pass class InvalidChord(Exception): pass
class Invalidnoteexception(Exception): pass class Invalidmodeexception(Exception): pass class Invalidchord(Exception): pass
# Middlewares # https://docs.djangoproject.com/en/3.0/topics/http/middleware/ MIDDLEWARE = [ 'whitenoise.middleware.WhiteNoiseMiddleware', 'django.middleware.security.SecurityMiddleware', 'django.contrib.sessions.middleware.SessionMiddleware', 'corsheaders.middleware.CorsMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware', ] # Password validation # https://docs.djangoproject.com/en/3.0/ref/settings/#auth-password-validators AUTH_PASSWORD_VALIDATORS = [ { 'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator', }, { 'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator', }, { 'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator', }, { 'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator', }, ] AUTH_USER_MODEL = 'users.User' # Custom User Model
middleware = ['whitenoise.middleware.WhiteNoiseMiddleware', 'django.middleware.security.SecurityMiddleware', 'django.contrib.sessions.middleware.SessionMiddleware', 'corsheaders.middleware.CorsMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware'] auth_password_validators = [{'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator'}, {'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator'}, {'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator'}, {'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator'}] auth_user_model = 'users.User'
# Copyright (c) 2016 EMC Corporation. # All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. class StoropsException(Exception): message = 'Storops Error.' class VNXException(StoropsException): message = "VNX Error." class VNXStorageGroupError(VNXException): pass class VNXAttachAluError(VNXException): pass class VNXAluAlreadyAttachedError(VNXAttachAluError): message = ( 'LUN already exists in the specified storage group', 'Requested LUN has already been added to this Storage Group') class VNXDetachAluError(VNXStorageGroupError): pass class VNXDetachAluNotFoundError(VNXDetachAluError): message = 'No such Host LUN in this Storage Group' class VNXCreateStorageGroupError(VNXStorageGroupError): pass class VNXStorageGroupNameInUseError(VNXCreateStorageGroupError): message = 'Storage Group name already in use' class VNXNoHluAvailableError(VNXStorageGroupError): pass class VNXMigrationError(VNXException): pass class VNXLunNotMigratingError(VNXException): pass class VNXLunSyncCompletedError(VNXMigrationError): error_code = 0x714a8021 class VNXTargetNotReadyError(VNXMigrationError): message = 'The destination LUN is not available for migration' class VNXSnapError(VNXException): pass class VNXDeleteAttachedSnapError(VNXSnapError): error_code = 0x716d8003 class VNXCreateSnapError(VNXException): message = 'Cannot create the snapshot.' class VNXAttachSnapError(VNXSnapError): message = 'Cannot attach the snapshot.' class VNXDetachSnapError(VNXSnapError): message = 'Cannot detach the snapshot.' class VNXSnapAlreadyMountedError(VNXSnapError): error_code = 0x716d8055 class VNXSnapNameInUseError(VNXSnapError): error_code = 0x716d8005 class VNXSnapNotExistsError(VNXSnapError): message = 'The specified snapshot does not exist.' class VNXLunError(VNXException): pass class VNXCreateLunError(VNXLunError): pass class VNXLunNameInUseError(VNXCreateLunError): error_code = 0x712d8d04 class VNXLunExtendError(VNXLunError): pass class VNXLunExpandSizeError(VNXLunExtendError): error_code = 0x712d8e04 class VNXLunPreparingError(VNXLunError): error_code = 0x712d8e0e class VNXLunNotFoundError(VNXLunError): message = 'Could not retrieve the specified (pool lun).' class VNXDeleteLunError(VNXLunError): pass class VNXLunUsedByFeatureError(VNXLunError): pass class VNXCompressionError(VNXLunError): pass class VNXCompressionAlreadyEnabledError(VNXCompressionError): message = 'Compression on the specified LUN is already turned on.' class VNXConsistencyGroupError(VNXException): pass class VNXCreateConsistencyGroupError(VNXConsistencyGroupError): pass class VNXConsistencyGroupNameInUseError(VNXCreateConsistencyGroupError): error_code = 0x716d8021 class VNXConsistencyGroupNotFoundError(VNXConsistencyGroupError): message = 'Cannot find the consistency group' class VNXPingNodeError(VNXException): pass class VNXMirrorException(VNXException): pass class VNXMirrorNameInUseError(VNXMirrorException): message = 'Mirror name already in use' class VNXMirrorPromotePrimaryError(VNXMirrorException): message = 'Cannot remove or promote a primary image.' class VNXMirrorNotFoundError(VNXMirrorException): message = 'Mirror not found' class VNXMirrorGroupNameInUseError(VNXMirrorException): message = 'Mirror Group name already in use' class VNXMirrorGroupNotFoundError(VNXMirrorException): message = 'Unable to locate the specified group' class VNXMirrorGroupAlreadyMemberError(VNXMirrorException): message = 'The mirror is already a member of a group' class VNXMirrorGroupMirrorNotMemberError(VNXMirrorException): message = 'The specified mirror is not a member of the group' class VNXMirrorGroupAlreadyPromotedError(VNXMirrorException): message = 'The Consistency Group has no secondary images to promote'
class Storopsexception(Exception): message = 'Storops Error.' class Vnxexception(StoropsException): message = 'VNX Error.' class Vnxstoragegrouperror(VNXException): pass class Vnxattachaluerror(VNXException): pass class Vnxalualreadyattachederror(VNXAttachAluError): message = ('LUN already exists in the specified storage group', 'Requested LUN has already been added to this Storage Group') class Vnxdetachaluerror(VNXStorageGroupError): pass class Vnxdetachalunotfounderror(VNXDetachAluError): message = 'No such Host LUN in this Storage Group' class Vnxcreatestoragegrouperror(VNXStorageGroupError): pass class Vnxstoragegroupnameinuseerror(VNXCreateStorageGroupError): message = 'Storage Group name already in use' class Vnxnohluavailableerror(VNXStorageGroupError): pass class Vnxmigrationerror(VNXException): pass class Vnxlunnotmigratingerror(VNXException): pass class Vnxlunsynccompletederror(VNXMigrationError): error_code = 1900707873 class Vnxtargetnotreadyerror(VNXMigrationError): message = 'The destination LUN is not available for migration' class Vnxsnaperror(VNXException): pass class Vnxdeleteattachedsnaperror(VNXSnapError): error_code = 1903001603 class Vnxcreatesnaperror(VNXException): message = 'Cannot create the snapshot.' class Vnxattachsnaperror(VNXSnapError): message = 'Cannot attach the snapshot.' class Vnxdetachsnaperror(VNXSnapError): message = 'Cannot detach the snapshot.' class Vnxsnapalreadymountederror(VNXSnapError): error_code = 1903001685 class Vnxsnapnameinuseerror(VNXSnapError): error_code = 1903001605 class Vnxsnapnotexistserror(VNXSnapError): message = 'The specified snapshot does not exist.' class Vnxlunerror(VNXException): pass class Vnxcreatelunerror(VNXLunError): pass class Vnxlunnameinuseerror(VNXCreateLunError): error_code = 1898810628 class Vnxlunextenderror(VNXLunError): pass class Vnxlunexpandsizeerror(VNXLunExtendError): error_code = 1898810884 class Vnxlunpreparingerror(VNXLunError): error_code = 1898810894 class Vnxlunnotfounderror(VNXLunError): message = 'Could not retrieve the specified (pool lun).' class Vnxdeletelunerror(VNXLunError): pass class Vnxlunusedbyfeatureerror(VNXLunError): pass class Vnxcompressionerror(VNXLunError): pass class Vnxcompressionalreadyenablederror(VNXCompressionError): message = 'Compression on the specified LUN is already turned on.' class Vnxconsistencygrouperror(VNXException): pass class Vnxcreateconsistencygrouperror(VNXConsistencyGroupError): pass class Vnxconsistencygroupnameinuseerror(VNXCreateConsistencyGroupError): error_code = 1903001633 class Vnxconsistencygroupnotfounderror(VNXConsistencyGroupError): message = 'Cannot find the consistency group' class Vnxpingnodeerror(VNXException): pass class Vnxmirrorexception(VNXException): pass class Vnxmirrornameinuseerror(VNXMirrorException): message = 'Mirror name already in use' class Vnxmirrorpromoteprimaryerror(VNXMirrorException): message = 'Cannot remove or promote a primary image.' class Vnxmirrornotfounderror(VNXMirrorException): message = 'Mirror not found' class Vnxmirrorgroupnameinuseerror(VNXMirrorException): message = 'Mirror Group name already in use' class Vnxmirrorgroupnotfounderror(VNXMirrorException): message = 'Unable to locate the specified group' class Vnxmirrorgroupalreadymembererror(VNXMirrorException): message = 'The mirror is already a member of a group' class Vnxmirrorgroupmirrornotmembererror(VNXMirrorException): message = 'The specified mirror is not a member of the group' class Vnxmirrorgroupalreadypromotederror(VNXMirrorException): message = 'The Consistency Group has no secondary images to promote'
#------------------------------------------------------------------------------- # Name: Signals types (voltage and current) # Author: d.Fathi # Created: 31/03/2020 # Modified: 19/09/2021 # Copyright: (c) PyAMS 2020 # Licence: unlicense #------------------------------------------------------------------------------- voltage={'discipline':'electrical', 'nature':'potential', 'abstol': 1e-8, 'chgtol':1e-14, 'signalType':'voltage', 'unit':'V' } current={'discipline':'electrical', 'nature':'flow', 'abstol': 1e-8, 'chgtol':1e-14, 'signalType':'voltage', 'unit':'A' } electrical={ 'potential':voltage, 'flow':current }
voltage = {'discipline': 'electrical', 'nature': 'potential', 'abstol': 1e-08, 'chgtol': 1e-14, 'signalType': 'voltage', 'unit': 'V'} current = {'discipline': 'electrical', 'nature': 'flow', 'abstol': 1e-08, 'chgtol': 1e-14, 'signalType': 'voltage', 'unit': 'A'} electrical = {'potential': voltage, 'flow': current}
# Replaced with the current commit when building the wheels. __commit__ = "{{CLOUDTIK_COMMIT_SHA}}" __version__ = "0.9.0"
__commit__ = '{{CLOUDTIK_COMMIT_SHA}}' __version__ = '0.9.0'
def configure(conf): conf.env.ARCHITECTURE = 'mips' conf.env.VALID_ARCHITECTURES = ['mips'] conf.env.ARCH_FAMILY = 'mips' conf.env.ARCH_LP64 = False conf.env.append_unique('DEFINES', ['_MIPS'])
def configure(conf): conf.env.ARCHITECTURE = 'mips' conf.env.VALID_ARCHITECTURES = ['mips'] conf.env.ARCH_FAMILY = 'mips' conf.env.ARCH_LP64 = False conf.env.append_unique('DEFINES', ['_MIPS'])
# -*- coding: utf-8 -*- # Copyright 2019 Cohesity Inc. class SQLServerInstanceVersion(object): """Implementation of the 'SQLServerInstanceVersion' model. Specifies the Server Instance Version. Attributes: build (int): Specfies the build. major_version (int): Specfies the major version. minor_version (int): Specfies the minor version. revision (int): Specfies the revision. version_string (string): Specfies the version string. """ # Create a mapping from Model property names to API property names _names = { "build":'build', "major_version":'majorVersion', "minor_version":'minorVersion', "revision":'revision', "version_string":'versionString' } def __init__(self, build=None, major_version=None, minor_version=None, revision=None, version_string=None): """Constructor for the SQLServerInstanceVersion class""" # Initialize members of the class self.build = build self.major_version = major_version self.minor_version = minor_version self.revision = revision self.version_string = version_string @classmethod def from_dictionary(cls, dictionary): """Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary representation of the object as obtained from the deserialization of the server's response. The keys MUST match property names in the API description. Returns: object: An instance of this structure class. """ if dictionary is None: return None # Extract variables from the dictionary build = dictionary.get('build') major_version = dictionary.get('majorVersion') minor_version = dictionary.get('minorVersion') revision = dictionary.get('revision') version_string = dictionary.get('versionString') # Return an object of this model return cls(build, major_version, minor_version, revision, version_string)
class Sqlserverinstanceversion(object): """Implementation of the 'SQLServerInstanceVersion' model. Specifies the Server Instance Version. Attributes: build (int): Specfies the build. major_version (int): Specfies the major version. minor_version (int): Specfies the minor version. revision (int): Specfies the revision. version_string (string): Specfies the version string. """ _names = {'build': 'build', 'major_version': 'majorVersion', 'minor_version': 'minorVersion', 'revision': 'revision', 'version_string': 'versionString'} def __init__(self, build=None, major_version=None, minor_version=None, revision=None, version_string=None): """Constructor for the SQLServerInstanceVersion class""" self.build = build self.major_version = major_version self.minor_version = minor_version self.revision = revision self.version_string = version_string @classmethod def from_dictionary(cls, dictionary): """Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary representation of the object as obtained from the deserialization of the server's response. The keys MUST match property names in the API description. Returns: object: An instance of this structure class. """ if dictionary is None: return None build = dictionary.get('build') major_version = dictionary.get('majorVersion') minor_version = dictionary.get('minorVersion') revision = dictionary.get('revision') version_string = dictionary.get('versionString') return cls(build, major_version, minor_version, revision, version_string)