code stringlengths 1 13.8M |
|---|
vpc_cens <- function(sim = NULL,
obs = NULL,
psn_folder = NULL,
bins = "jenks",
n_bins = 8,
bin_mid = "mean",
obs_cols = NULL,
sim_cols = NULL,
software... |
PV_pre_triang_dis=function(data,years=10){
app=rep(NA,years)
for(i in 1:years) app[i]=triangular_moments_dis_U(data,i)
PV=1+sum(app[1:years-1])
return(PV)
} |
do.dne <- function(X, label, ndim=2, numk=max(ceiling(nrow(X)/10),2),
preprocess=c("center","scale","cscale","decorrelate","whiten")){
aux.typecheck(X)
n = nrow(X)
p = ncol(X)
ndim = as.integer(ndim)
if (!check_ndim(ndim,p)){stop("* do.dne : 'ndim' is a positive integer in [1,
... |
structure <- function (.Data, ...)
{
if(is.null(.Data))
warning("Calling 'structure(NULL, *)' is deprecated, as NULL cannot have attributes.\n Consider 'structure(list(), *)' instead.")
attrib <- list(...)
if(length(attrib)) {
specials <- c(".Dim", ".Dimnames", ".Names", ".Tsp", ".... |
library(bmp)
posey <- c(30, 167, 332, 457, 822, 1016, 1199,
1437, 1621, 1770, 1924, 2101, 2251, 2442, 2594,
2757, 2918, 3072, 3205, 3356, 3526, 3685,
4068, 4217)
susac <- c(751, 1286, 1485, 1666, 2030,
2187)
v <- list.files("buster_posey_catching/")
v <- v[order(as.numeric(unlist(lapply(strsplit(v, split="i"), "[[", 1)... |
QA_Results <- data.table::CJ(
Group = c(0, 1, 2, 3),
xregs = c(0, 1, 2, 3),
Trans = c(TRUE, FALSE),
Training = "Failure",
Forecast = "Failure"
)
for (run in seq_len(QA_Results[, .N])) {
if (QA_Results[run, Group] == 0) {
groupvars <- NULL
ModelData <- data.table::fread(file = file.path("C:/Users/... |
catEffectBootAdaptor<-function (df, index, testFnc = sumSqCat, useResp = TRUE, ...) {
if (useResp) respVal <- df$resp
else respVal <- df$bkg
testFnc(respVal[index], df$cat, ...)
} |
count_levels_num <- function(x) {
.Call('_inspectdf_count_levels_num', PACKAGE = 'inspectdf', x)
}
count_levels_char <- function(x) {
.Call('_inspectdf_count_levels_char', PACKAGE = 'inspectdf', x)
}
na_numeric <- function(x) {
.Call('_inspectdf_na_numeric', PACKAGE = 'inspectdf', x)
}
na_character <- funct... |
T <- 50
m <- 10
P <- 5
H <- 2
N_min <- 20
X <- rnorm(T)
mspe <- MSPE(X, m1 = T - m + 1, m2 = T, P = P, H = H, N = c(0, N_min:(T-m-H)))
N <- mspe$N
M <- mspe$mspe
h <- 1
plot(mspe, h, N_min = N_min, legend = (h == 1))
idx1_s <- which(M[h, , N == 0] == min(M[h, , N == 0]), arr.ind = TRUE)[1]
abline(h = M[h, idx1_s, N == ... |
bhl_getunpublisheditems <- function(...) {
.Defunct(package = "rbhl", msg = "API method removed")
} |
if (requiet("testthat") &&
requiet("insight") &&
requiet("robustbase")) {
data(mtcars)
m1 <- lmrob(mpg ~ gear + wt + cyl, data = mtcars)
test_that("model_info", {
expect_true(model_info(m1)$is_linear)
})
test_that("find_predictors", {
expect_identical(find_predictors(m1), list(conditional = c("gea... |
fit_clutter <- function(df, age, dh, basal_area, volume, site, plot, .groups=NA, model = "full", keep_model = FALSE){
basal_area2<-basal_area1<-I1<-I2<-volume2<-.<-Reg<-NULL
if( missing(df) ){
stop("df not set", call. = F)
}else if(!is.data.frame(df)){
stop("df must be a dataframe", call.=F)
... |
wait_slurm <- function(x, ...) UseMethod("wait_slurm")
wait_slurm.slurm_job <- function(x, ...) {
wait_slurm.integer(get_job_id(x), ...)
}
wait_slurm.integer <- function(x, timeout = -1, freq = 0.1, force = TRUE, ...) {
if (opts_slurmR$get_debug()) {
warning("waiting is not available in debug mode.", call. =... |
test_that("compare state works correctly", {
loc <- tempfile("watcher")
dir.create(loc)
empty <- dir_state(loc)
expect_equal(length(empty), 0)
file.create(file.path(loc, "test-1.txt"))
one <- dir_state(loc)
expect_equal(length(one), 1)
expect_equal(basename(names(one)), "test-1.txt")
diff <- compare_s... |
AutoLightGBMClassifier <- function(
data = NULL,
TrainOnFull = FALSE,
ValidationData = NULL,
TestData = NULL,
TargetColumnName = NULL,
... |
.build_client <-
function(api,
encode,
version = NULL,
progress = NULL,
pat = getOption("osfr.pat")) {
api <- match.arg(api, c("osf", "wb"))
encode <- match.arg(encode, c("form", "multipart", "json", "raw"))
server <- Sys.getenv("OSF_SERVER")
url <- switch(api,
... |
BLOSUM62<-function(seqs,label=c(),outFormat="mat",outputFileDist=""){
path.pack=system.file("extdata",package="ftrCOOL")
if(length(seqs)==1&&file.exists(seqs)){
seqs<-fa.read(seqs,alphabet="aa")
seqs_Lab<-alphabetCheck(seqs,alphabet = "aa",label)
seqs<-seqs_Lab[[1]]
label<-seqs_Lab[[2]]
}
else i... |
list2matrix.bas <- function(x, what, which.models = NULL) {
namesx <- x$namesx
if (is.null(which.models)) which.models <- 1:x$n.models
listobj <- x[[what]][which.models]
which <- x$which[which.models]
n.models <- length(which.models)
p <- length(namesx)
mat <- matrix(0, nrow = n.models, ncol = p)
for (i... |
context("elevation utils")
testthat::skip_on_cran()
raster_poa <- system.file("extdata/poa/poa_elevation.tif", package = "r5r")
data_path <- system.file("extdata/poa", package = "r5r")
r5r_core <- setup_r5(data_path = data_path, temp_dir = TRUE)
test_that("tobler_hiking", {
expect_error( tobler_hiking('bananas') )
... |
bbase.os <-
function(x, K, bdeg = 3, eps = 1e-5, intercept = TRUE) {
B <- bs(x, degree = bdeg, df = K + bdeg, intercept = intercept)
B
} |
tcplot <- function (data, u.range, cmax = FALSE, r = 1,
ulow = -Inf, rlow = 1, nt = 25, which = 1:npar, conf = 0.95,
lty = 1, lwd = 1, type = "b", cilty = 1, ask = nb.fig < length(which) &&
dev.interactive(), ...){
n <- length(data)
data <- sort(data)
if (missing(u.range)) {
u.range... |
library(plyr)
suppressPackageStartupMessages(library(dplyr))
library(ggplot2)
library(readr)
gap_dat <- read_tsv("05_gap-merged-with-china-1952.tsv") %>%
mutate(country = factor(country),
continent = factor(continent))
gap_dat %>% str()
gap_dat %>%
sapply(function(x) x %>% is.na() %>% sum())
gap_dat$year... |
"sdtm_ae"
"sdtm_cm"
"sdtm_dm"
"sdtm_ds"
"sdtm_ex"
"sdtm_lb"
"sdtm_mh"
"sdtm_qs"
"sdtm_relrec"
"sdtm_sc"
"sdtm_se"
"sdtm_suppae"
"sdtm_suppdm"
"sdtm_suppds"
"sdtm_supplb"
"sdtm_sv"
"sdtm_ta"
"sdtm_te"
"sdtm_ti"
"sdtm_ts"
"sdtm_tv"
"sdtm_vs" |
tree_add_dates <- function(dated_tree = NULL,
missing_taxa = NULL,
dating_method = "mrbayes",
adding_criterion = "random",
mrbayes_output_file = "mrbayes_tree_add_dates.nexus") {
dated_tree <- tree_check(tree =... |
"dataAGGR" |
library(amt)
data(amt_fisher)
set.seed(123)
tr <- make_trast(amt_fisher[1:50, ], res = 5)
mini_fisher <- amt_fisher[1:40, ]
mcp <- hr_mcp(mini_fisher)
loc <- hr_locoh(mini_fisher)
kde <- hr_kde(mini_fisher)
mini_fisher1 <- amt_fisher[11:50, ]
mcp1 <- hr_mcp(mini_fisher1)
loc1 <- hr_locoh(mini_fisher1)
kde1 <- hr_kde(mi... |
brute_IDs <- function(total.length, redundancy, alphabet, num.tries = 10, available.colors = NULL) {
if (missing(alphabet)) {
stop("Error: you need to enter an 'alphabet size,' e.g. the number of paint colors you have")
}
if (missing(total.length)) {
stop("Error: you need to enter the total length of the ... |
context("ashr with half-uniform mixture priors")
test_that("mixcompdist=+uniform gives all non-negative values for b and zero for a", {
set.seed(1); z=rnorm(10); z.ash=ash(z,1,mixcompdist="+uniform")
k = length(z.ash$fitted_g$pi)
expect_true(all(z.ash$fitted_g$b >= rep(0,k)))
expect_equal(z.ash$fitted_g$a,rep(0... |
women
names(women)
height
attach(women)
height
weight
women$height
g <- "My First List"
h <- c(25, 26, 18, 39)
j <- matrix(1:10, nrow=5)
k <- c("one", "two", "three")
mylist <- list(title=g, ages=h, j, k, women)
mylist
mylist[[2]]
mylist[[5]]
plot(x=height, y=weight, type='b', lty=5, pch=11, fg='red', bg='green',... |
stratsamp <- function(n, distribution, parameters, p) {
lims <- find_strata(p, distribution, parameters)
outmat <- matrix(data = NA, nrow = n, ncol = length(p)-1)
counts <- rep(0, length(lims)-1)
while (any(counts < n)) {
r <- distribution_sampling(1, distribution, parameters)
intvl <- fi... |
context("mlc")
suppressPackageStartupMessages(library(caret))
set.seed(1)
mat <- matrix(rnorm(300), ncol = 3, nrow = 100)
colnames(mat) <- letters[1:3]
y <- sample(factor(c("a", "b")), 100, replace = TRUE)
test_that("fit mlc",{
expect_is( mr <- mlc(mat,y), "list")
expect_equal(names(mr), c("a", "b",... |
semprobit <- function(formula, W, data, subset, ...) {
cl <- match.call()
mf <- match.call(expand.dots = FALSE)
m <- match(c("formula", "data", "subset"), names(mf), 0L)
mf <- mf[c(1L, m)]
mf$drop.unused.levels <- TRUE
mf[[1L]] <- as.name("model.frame")
mf <- eval(mf, paren... |
tar_resources_url <- function(
handle = NULL
) {
out <- resources_url_init(
handle = handle
)
resources_validate(out)
out
} |
export_amira.path<-function(vertices,filename,Lines=c(1:(dim(vertices)[1]-1)-1,-1),path)
{
while(tolower(paste(filename,".am",sep=""))%in%list.files(path)!=FALSE){
i<-1
filename<-paste(filename,"(",i,")",sep="")
i<-i+1
}
cat(paste("
file = paste(path, "/", filename, ".am", sep = ""),
append =... |
test_that("translations", {
expect_identical(pow(5, 2), 25)
expect_identical(phi(0), 0.5)
expect_equal(phi(2), 0.9772499, tolerance = 0.0000001)
x <- NA
log(x) <- log(5)
expect_equal(x, 5)
expect_equal(logit(0.5), 0)
expect_equal(logit(1), Inf)
x <- NA
logit(x) <- logit(0.75)
expect_equal(x, 0.75)... |
read.cross.csv <-
function(dir, file, na.strings=c("-","NA"),
genotypes=c("A","H","B","D","C"),
estimate.map=TRUE, rotate=FALSE, ...)
{
if(missing(file)) file <- "data.csv"
if(!missing(dir) && dir != "") {
file <- file.path(dir, file)
}
args <- list(...)
if... |
gbm.perf <- function(object,
plot.it=TRUE,
oobag.curve=FALSE,
overlay=TRUE,
method,
main="") {
if(!is.logical(plot.it) || (length(plot.it)) > 1 || is.na(plot.it))
stop("plot.it must be a logical - exclud... |
test_that("gives warning markers are not correct", {
expect_warning(style_text(c(
"1+1",
"
"
)))
})
test_that("trailing spaces are stripped when checking marker and written back", {
expect_equal(
style_text(c(
"
"1+1",
"
)) %>%
as.character(),
c("
)
})
test_that("... |
genscorestat<-function(scores,group,correct=0){
N<-length(group); MV<-table(group)
refg<-names(MV)[1]
if(is.numeric(group)) refg<-as.numeric(refg)
if(length(MV)!=2){
message("genscorestat works only for two groups")
out<-NA
}else{
abar<-mean(scores)
ahat<-mean(scores^2)
vv<-... |
"dccm.nma" <-
function(x, nmodes=NULL, ncore=NULL, progress = NULL, ...) {
nma <- x
if (missing(nma))
stop("dccm.nma: must supply a 'nma' object, i.e. from 'nma'")
if(!"nma" %in% class(nma))
stop("dccm.nma: must supply 'nma' object, i.e. from 'nma'")
ncore <- setup.ncore(ncore, bigmem... |
stat.entropyFunction = function(bitString) {
pT = sum(bitString)/length(bitString)
pF = 1-pT
if (pT==1 || pT==0) {
e = 0
} else {
e = -pT*log2(pT)-pF*log2(pF)
}
return(e)
} |
"ChickWeight" <-
structure(list(
weight = c(42, 51, 59, 64, 76, 93, 106, 125, 149,
171, 199, 205, 40, 49, 58, 72, 84, 103, 122, 138, 162, 187, 209,
215, 43, 39, 55, 67, 84, 99, 115, 138, 163, 187, 198, 202, 42,
49, 56, 67, 74, 87, 102, 108, 136, 154, 160, 157, 41, 42, 48,
60, 79, 106, 141, 164,... |
NULL
dcmp = function(x, lambda, nu, log = FALSE)
{
prep = prep.zicmp(length(x), lambda, nu)
dcmp_cpp(x, prep$lambda, prep$nu, take_log = log)
}
rcmp = function(n, lambda, nu)
{
prep = prep.zicmp(n, lambda, nu)
ymax = getOption("COMPoissonReg.ymax")
rcmp_cpp(n, prep$lambda, prep$nu, ymax = ymax)
}
pcmp = function(x... |
groupAndRename <- function(obj, var, before, after, addNA=FALSE) {
groupAndRenameX(obj=obj, var=var, before=before, after=after, addNA=addNA)
}
setGeneric("groupAndRenameX", function(obj, var, before, after, addNA=FALSE) {
standardGeneric("groupAndRenameX")
})
setMethod(f="groupAndRenameX", signature=c("factor"),
d... |
ans <- pl(amount = c(1, -1),
timestamp = c(2, 3),
price = c(1, 2),
along.timestamp = 3:1,
vprice = 1:3)
expect_equal(ans[[1]]$timestamp , 1:3)
expect_equal(unname(ans[[1]]$pl), c(0,1,1)) |
REND <- function(TPDc = NULL, TPDs = NULL){
if (is.null(TPDc) & is.null(TPDs)) {
stop("At least one of 'TPDc' or 'TPDs' must be supplied")
}
if (!is.null(TPDc) & class(TPDc) != "TPDcomm"){
stop("The class of one object do not match the expectations,
Please, specify if your object is a TPDc or a TP... |
r1sd <- function(x, na = TRUE) {
return((x - mean(x, na.rm = na)) / (1 * sd(x, na.rm = na)))
} |
QRSimul <-
function(VecX, tau, times, subj, X, y, d, kn, degree, lambda, gam){
dim = length(subj)
X = matrix(X, nrow=dim)
H = length(tau)
px = ncol(X)
n = length(unique(subj))
if(px != length(VecX))
stop("the length of VecX and the number of covariate(s) must match")
XX = as.matrix(X)
if(all(X[,1]==1)) VecX[1]=1 else V... |
writeEnvelope <- function(obj, centerfun = mean) {
if(inherits(obj, c("SpatialPoints", "SpatialPointsDataFrame"), which = FALSE)) {
SpatialPointsEnvelope(obj)
} else if(inherits(obj, "list") && length(obj) > 0 &&
all(vapply(
X = obj,
FUN = inherits,
FUN.VALU... |
session <- function(url, ...) {
session <- structure(
list(
handle = httr::handle(url),
config = c(..., httr::config(autoreferer = 1L)),
response = NULL,
url = NULL,
back = character(),
forward = character(),
cache = new_environment()
),
class =... |
context('Test the creation of custom indicators')
data(forestgap)
data(serengeti)
datasets <- list(forestgap[3:4],
forestgap[1:2])
test_methods <- function(teststring, datalength, obj) {
ok_print <- any(grepl(teststring, capture.output(print(obj))))
expect_true(ok_print)
ok_summary <- any... |
testthat::context("H2O AUTOML TEST")
test_that("Fire up H2O", {
testthat::skip_on_cran()
h2o.init(
nthreads = -1,
ip = 'localhost',
port = 54321
)
model_spec <<- automl_reg(mode = 'regression') %>%
set_engine(
engine = 'h2o',
max_runtime_sec... |
library(pcalg)
amat1 <- t(cbind(c(0,1,0,1,0),c(0,0,1,0,1),c(0,0,0,1,1),c(0,0,0,0,1),c(0,0,0,0,0)))
amat2 <- t(cbind(c(0,1,0,1,1),c(0,0,0,0,1),c(0,0,0,0,1),c(0,0,0,0,1),c(0,0,0,0,0)))
g1 <- as(amat1,"graphNEL")
g2 <- as(amat2,"graphNEL")
res <- compareGraphs(g1,g2)
if ((round(res["tpr"],5)!=0.83333) | (round(res["fpr"],... |
skip_tests_for_cran <- TRUE
skip_maxnet <- FALSE
skip_maxent.jar <- TRUE
skip_bioclim <- TRUE
skip_simDiff <- TRUE
library(dplyr)
options(warn=-1)
set.seed(48)
occs <- read.csv(file.path(system.file(package="dismo"), "/ex/bradypus.csv"))[,2:3]
envs.orig <- raster::stack(list.files(path=paste(system.file(package='dismo'... |
MCpriorIntFun <-
function(Nsim=200,
prior,
Hpar,
dimData,
FUN=function(par,...){as.vector(par)},
store=TRUE,
show.progress = floor(seq(1, Nsim, length.out = 20 ) ),
Nsim.min=Nsim,
precision = 0,
...)
{
start.time=proc.time()
no... |
NULL
"ghp100k" |
kkmeans <- function(K, parameters) {
state <- list()
state$time <- system.time({
H <- eigen(K, symmetric = TRUE)$vectors[, 1:parameters$cluster_count]
objective <- sum(diag(t(H) %*% K %*% H)) - sum(diag(K))
H_normalized <- H/matrix(sqrt(rowSums(H^2, 2)),
... |
translogEla <- function( xNames, data, coef, coefCov = NULL,
dataLogged = FALSE ) {
checkNames( c( xNames ), names( data ) )
nExog <- length( xNames )
nCoef <- 1 + nExog + nExog * ( nExog + 1 ) / 2
if( nCoef > length( coef ) ) {
stop( "a translog function with ", nExog, " exogenous variables",
... |
.init_base_test_templ <- function() {
templ_dir <- file.path(get_templ_dir(), "BaseTestProjectTemplate")
if (dir.exists(templ_dir)) {
return(templ_dir)
}
unzip(file.path("data", "BaseTestProjectTemplate.zip"), exdir = get_templ_dir())
build_prj <- RSuite::prj_start("BaseTestProjectBuild", skip_rc = TRUE, ... |
getGVGenotype <- function(ped) {
if (hasGenotype(ped)) {
genotype <- ped[ , c("id", "first", "second")]
} else {
genotype <- NULL
}
genotype
} |
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