import streamlit as st
import streamlit.components.v1 as components
import networkx as nx
import matplotlib.pyplot as plt
from pyvis.network import Network
import got 
import numpy as np
import pandas as pd
import time
import re
import graphviz as graphviz
import pydeck as pdk

from st_click_detector import click_detector




st.graphviz_chart('''
    digraph {
PR0001INCOME  ->  AbleToBuyOnlyNecessities
PR0001INCOME  ->  DifficultyBuyingNecessities
PR0001INCOME  ->  DifficultyWithMoneyManagement
PR0001INCOME  ->  LowNoIncome
PR0001INCOME  ->  UninsuredMedicalExpenses
            }
''')

st.graphviz_chart('''
    digraph {
PR0012MENTALHEALTH  ->  Apprehension  ->  UndefinedFearAnxious
PR0012MENTALHEALTH  ->  Attempts  ->  SuicideHomicide
PR0012MENTALHEALTH  ->  Difficulty  ->  Managing  ->  Anger
PR0012MENTALHEALTH  ->  Difficulty  ->  Managing  ->  Stress
PR0012MENTALHEALTH  ->  Expresses  ->  SuicidalHomicidalThoughts
PR0012MENTALHEALTH  ->  False  ->  BeliefsDelusions
PR0012MENTALHEALTH  ->  False  ->  PerceptionsHallucinationsIllusions
PR0012MENTALHEALTH  ->  FlatAffectLackofEmotion
PR0012MENTALHEALTH  ->  IrritableAgitatedAggressive
PR0012MENTALHEALTH  ->  LossofInterest  ->  Involvementin  ->  ActivitiesSelfCare
PR0012MENTALHEALTH  ->  MoodSwings
PR0012MENTALHEALTH  ->  NarrowedtoScattered  ->  AttentionFocus
PR0012MENTALHEALTH  ->  PurposelessCompulsiveRepetitiveActivity
PR0012MENTALHEALTH  ->  SadnessHopelessnessDecreasedSelfEsteem
PR0012MENTALHEALTH  ->  SomaticComplaintsFatigue
            }
''')



df = pd.read_csv("testfile.csv")
@st.cache
def convert_df(df):
   return df.to_csv().encode('utf-8')
csv = convert_df(df)
st.download_button(
   "Press to Download",
   csv,
   "testfile.csv",
   "text/csv",
   key='download-csv'
)


st.title('Streamlit Visualization')
dataframe = pd.DataFrame(np.random.randn(10, 20),
  columns = ('col %d' % i
    for i in range(20)))
st.write(dataframe)

dataframe = pd.DataFrame(np.random.randn(10, 5),
  columns = ('col %d' % i
    for i in range(5)))
dataframe
st.write('This is a line_chart.')
st.line_chart(dataframe)

st.write('This is a area_chart.')
st.area_chart(dataframe)

st.write('This is a bar_chart.')
st.bar_chart(dataframe)

st.write('Map data')
data_of_map = pd.DataFrame(
  np.random.randn(1000, 2) / [60, 60] + [36.66, -121.6],
  columns = ['latitude', 'longitude'])
st.map(data_of_map)

image = Image.open('picture.jpg')
st.image(image, caption = 'This is a picture', use_column_width = True)




st.title('Pyvis VisJS DOTlang Legend')

Network(notebook=True)
# make Network show itself with repr_html

def net_repr_html(self):
  nodes, edges, height, width, options = self.get_network_data()
  html = self.template.render(height=height, width=width, nodes=nodes, edges=edges, options=options)
  return html

Network._repr_html_ = net_repr_html

st.sidebar.title('Choose your favorite Graph')
option=st.sidebar.selectbox('select graph',('Simple','Karate', 'GOT'))
physics=st.sidebar.checkbox('add physics interactivity?')
got.simple_func(physics)

if option=='Simple':
  HtmlFile = open("test.html", 'r', encoding='utf-8')
  source_code = HtmlFile.read() 
  components.html(source_code, height = 900,width=900)

got.got_func(physics)

if option=='GOT':
  HtmlFile = open("gameofthrones.html", 'r', encoding='utf-8')
  source_code = HtmlFile.read() 
  components.html(source_code, height = 1200,width=1000)

got.karate_func(physics)

if option=='Karate':
  HtmlFile = open("karate.html", 'r', encoding='utf-8')
  source_code = HtmlFile.read() 
  components.html(source_code, height = 1200,width=1000)