content large_stringlengths 0 6.46M | path large_stringlengths 3 331 | license_type large_stringclasses 2
values | repo_name large_stringlengths 5 125 | language large_stringclasses 1
value | is_vendor bool 2
classes | is_generated bool 2
classes | length_bytes int64 4 6.46M | extension large_stringclasses 75
values | text stringlengths 0 6.46M |
|---|---|---|---|---|---|---|---|---|---|
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/cni_auc.R
\name{evaluate_ranking_direct}
\alias{evaluate_ranking_direct}
\title{Evaluate a ranking}
\usage{
evaluate_ranking_direct(
values,
are_true,
num_positive_interactions,
num_possible_interactions,
extend_by = 10000
)
}
\argu... | /package/man/evaluate_ranking_direct.Rd | permissive | dynverse/dyngen_manuscript | R | false | true | 885 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/cni_auc.R
\name{evaluate_ranking_direct}
\alias{evaluate_ranking_direct}
\title{Evaluate a ranking}
\usage{
evaluate_ranking_direct(
values,
are_true,
num_positive_interactions,
num_possible_interactions,
extend_by = 10000
)
}
\argu... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/classes.R
\name{enm.ncoefs}
\alias{enm.ncoefs}
\alias{enm.ncoefs<-}
\alias{enm.ncoefs,ENMdetails-method}
\alias{enm.ncoefs<-,ENMdetails-method}
\title{enm.ncoefs generic for ENMdetails object}
\usage{
enm.ncoefs(x)
enm.ncoefs(x) <- value
\S... | /man/enm.ncoefs.Rd | no_license | jamiemkass/ENMeval | R | false | true | 530 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/classes.R
\name{enm.ncoefs}
\alias{enm.ncoefs}
\alias{enm.ncoefs<-}
\alias{enm.ncoefs,ENMdetails-method}
\alias{enm.ncoefs<-,ENMdetails-method}
\title{enm.ncoefs generic for ENMdetails object}
\usage{
enm.ncoefs(x)
enm.ncoefs(x) <- value
\S... |
\name{pnsdrm}
\alias{pnsdrm}
\alias{pnsdrm.calc}
\alias{pns.plot1}
\title{Parametric, non-parametric or semi-parametric dose-response modelling}
\description{
Parametric, non-parametric or semi-parametric dose-response modelling of both continuous and quantal data.
}
\usage{
pnsdrm(predictor, respo... | /man/pnsdrm.Rd | no_license | cran/mrdrc | R | false | false | 6,681 | rd | \name{pnsdrm}
\alias{pnsdrm}
\alias{pnsdrm.calc}
\alias{pns.plot1}
\title{Parametric, non-parametric or semi-parametric dose-response modelling}
\description{
Parametric, non-parametric or semi-parametric dose-response modelling of both continuous and quantal data.
}
\usage{
pnsdrm(predictor, respo... |
limit <- 1
custom_query <- list(keya="aa")
verbose <- TRUE
timeout <- 20
lat <- "latit"
long <- "longit"
api_url <- "http://www.mapquestapi.com/geocoding/v1/batch"
address_df <- tibble::tribble(~address, "Madrid, ES", "hahuauhauauhu", "Segovia")
#address_df <- tibble::tibble(address = mapSpain::esp_munic.sf[1:101,]$na... | /sandbox/query_debugging/mapquest_batch.R | permissive | jessecambon/tidygeocoder | R | false | false | 5,646 | r | limit <- 1
custom_query <- list(keya="aa")
verbose <- TRUE
timeout <- 20
lat <- "latit"
long <- "longit"
api_url <- "http://www.mapquestapi.com/geocoding/v1/batch"
address_df <- tibble::tribble(~address, "Madrid, ES", "hahuauhauauhu", "Segovia")
#address_df <- tibble::tibble(address = mapSpain::esp_munic.sf[1:101,]$na... |
set.seed(1)
m= 6
n = 5
#couleurs <- sample(colors(), m)
couleurs <- sprintf("Couleur%i", seq_len(m))
couleurs
jeu <- sample(couleurs, n, replace = TRUE)
jeu
proposition <- sample(couleurs, n, replace = TRUE)
proposition
resultat <- reponse(proposition, jeu)
resultat
score(proposition, jeu)
# Retourne le nombre de fi... | /Brouillons/Alain/Code.R | no_license | ARKEnsae/Mastermind_Simulation | R | false | false | 1,343 | r | set.seed(1)
m= 6
n = 5
#couleurs <- sample(colors(), m)
couleurs <- sprintf("Couleur%i", seq_len(m))
couleurs
jeu <- sample(couleurs, n, replace = TRUE)
jeu
proposition <- sample(couleurs, n, replace = TRUE)
proposition
resultat <- reponse(proposition, jeu)
resultat
score(proposition, jeu)
# Retourne le nombre de fi... |
#' query \code{problemInstance}-objects depending on argument \code{type}
#'
#' @param object an object of class \code{problemInstance}
#' @param type a character vector of length 1 defining what to calculate|return|modify. Allowed types are:}
#' \itemize{
#' \item strID: vector of unique IDs for each table cell
#' \it... | /R/generics_problemInstance.r | no_license | sdcTools/sdcTable | R | false | false | 7,930 | r | #' query \code{problemInstance}-objects depending on argument \code{type}
#'
#' @param object an object of class \code{problemInstance}
#' @param type a character vector of length 1 defining what to calculate|return|modify. Allowed types are:}
#' \itemize{
#' \item strID: vector of unique IDs for each table cell
#' \it... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/Functions.R
\name{dna_convert}
\alias{dna_convert}
\title{Convert image DNA to PNG format}
\usage{
dna_convert(dna, maxXY, tempf, pngWH, bg = "white")
}
\arguments{
\item{dna}{matrix or character, untangled or tangled image DNA of any size.}
... | /man/dna_convert.Rd | permissive | herrmannrobert/GenArt | R | false | true | 884 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/Functions.R
\name{dna_convert}
\alias{dna_convert}
\title{Convert image DNA to PNG format}
\usage{
dna_convert(dna, maxXY, tempf, pngWH, bg = "white")
}
\arguments{
\item{dna}{matrix or character, untangled or tangled image DNA of any size.}
... |
## ui.R ##
# Header ####
#https://stackoverflow.com/questions/31440564/adding-a-company-logo-to-shinydashboard-header
header <-
dashboardHeader(
title = "TBDS Shiny Template",
tags$li(a(href = 'https://www.tbdsolutions.com/',
img(src = 'tbdSolutions-logo.png',
height = "20px"... | /ui.R | no_license | bowmasar/TBDS_DataProjectTemplates | R | false | false | 1,504 | r | ## ui.R ##
# Header ####
#https://stackoverflow.com/questions/31440564/adding-a-company-logo-to-shinydashboard-header
header <-
dashboardHeader(
title = "TBDS Shiny Template",
tags$li(a(href = 'https://www.tbdsolutions.com/',
img(src = 'tbdSolutions-logo.png',
height = "20px"... |
ptime <- system.time({
r <- foreach(icount(trials), .combine=cbind) %dopar% {
ind <- sample(100, 100, replace=TRUE)
result1 <- glm(x[ind,2]~x[ind,1], family=binomial(logit))
coefficients(result1)
}
})
library(data.table)
library(stringr)
library(foreach)
library(doMC)
registerDoMC(2) #cha... | /script.R | no_license | rrozas/Kaggle_Driver_Telematics | R | false | false | 1,307 | r | ptime <- system.time({
r <- foreach(icount(trials), .combine=cbind) %dopar% {
ind <- sample(100, 100, replace=TRUE)
result1 <- glm(x[ind,2]~x[ind,1], family=binomial(logit))
coefficients(result1)
}
})
library(data.table)
library(stringr)
library(foreach)
library(doMC)
registerDoMC(2) #cha... |
'''
Developed for Forust.io
A very general script to preprocess data before common Machine Learning procedures.
This script imports data from an excel file, replaces missing values with "0", drops unneeded columns, and provides normalization functions.
Author: Visakh Madathil
'''
#importing Excel File
library(rea... | /DataPreProcess.R | no_license | vmmadathil/Data-Cleaning | R | false | false | 990 | r |
'''
Developed for Forust.io
A very general script to preprocess data before common Machine Learning procedures.
This script imports data from an excel file, replaces missing values with "0", drops unneeded columns, and provides normalization functions.
Author: Visakh Madathil
'''
#importing Excel File
library(rea... |
# remove F.het.MDPP and F.het.MDPL and F.grandis from PCA
# what are % PCA
library(ggplot2)
design
sp<-as.character(unlist(design[1,]))
sp<-sp[-c(1,2)]
ph<-as.character(unlist(design[2,]))
ph<-ph[-c(1,2)]
cl<-as.character(unlist(design[3,]))
cl<-cl[-c(1,2)]
de<-as.character(unlist(design[4,]))
de<-de[-c(1,2)]
# clade
... | /scripts/tSNE.R | no_license | WhiteheadLab/RNAseq_17killifish | R | false | false | 1,371 | r | # remove F.het.MDPP and F.het.MDPL and F.grandis from PCA
# what are % PCA
library(ggplot2)
design
sp<-as.character(unlist(design[1,]))
sp<-sp[-c(1,2)]
ph<-as.character(unlist(design[2,]))
ph<-ph[-c(1,2)]
cl<-as.character(unlist(design[3,]))
cl<-cl[-c(1,2)]
de<-as.character(unlist(design[4,]))
de<-de[-c(1,2)]
# clade
... |
setwd("path")
packages <- c("odbc","dplyr","readr","shinyjs","shiny","shinyWidgets")
lapply(packages, require, character.only = TRUE)
M <- read_csv("path", progress = show_progress(),
trim_ws = TRUE, na = c("","NA"), col_types = cols(.default = co_character()))
m <- data.frame(build=c('a','a','a','a','a'... | /groupBy.r | no_license | KateLam401/r | R | false | false | 685 | r |
setwd("path")
packages <- c("odbc","dplyr","readr","shinyjs","shiny","shinyWidgets")
lapply(packages, require, character.only = TRUE)
M <- read_csv("path", progress = show_progress(),
trim_ws = TRUE, na = c("","NA"), col_types = cols(.default = co_character()))
m <- data.frame(build=c('a','a','a','a','a'... |
map_plot <- function(mapdata, coronavirusdata, type, grouping, trans = "log10") {
current_date <- max(coronavirusdata$date, na.rm=TRUE)
coronavirusdata <-
coronavirusdata %>%
filter(type == {{type}})%>%
group_by(!!(grouping)) %>%
summarize(cases = sum(cases, na.rm=TRUE))
out <- ggplot() +... | /scripts/mapplot.R | no_license | jebyrnes/covid19_shiny | R | false | false | 737 | r | map_plot <- function(mapdata, coronavirusdata, type, grouping, trans = "log10") {
current_date <- max(coronavirusdata$date, na.rm=TRUE)
coronavirusdata <-
coronavirusdata %>%
filter(type == {{type}})%>%
group_by(!!(grouping)) %>%
summarize(cases = sum(cases, na.rm=TRUE))
out <- ggplot() +... |
# Jake Yeung
# Date of Creation: 2021-06-29
# File: ~/projects/scChIX/analysis_scripts/2-check_LDA_outputs.R
#
rm(list=ls())
library(dplyr)
library(tidyr)
library(ggplot2)
library(data.table)
library(Matrix)
library(topicmodels)
library(scchicFuncs)
library(hash)
library(igraph)
library(umap)
library(ggrepel)
sourc... | /analysis_scripts/2-check_LDA_outputs.R | no_license | jakeyeung/scChIX | R | false | false | 18,029 | r | # Jake Yeung
# Date of Creation: 2021-06-29
# File: ~/projects/scChIX/analysis_scripts/2-check_LDA_outputs.R
#
rm(list=ls())
library(dplyr)
library(tidyr)
library(ggplot2)
library(data.table)
library(Matrix)
library(topicmodels)
library(scchicFuncs)
library(hash)
library(igraph)
library(umap)
library(ggrepel)
sourc... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/covid19api.R
\name{GetDayOne}
\alias{GetDayOne}
\title{Get DayOne cases}
\usage{
GetDayOne(country.requested, status.requested, live = FALSE, total = FALSE)
}
\arguments{
\item{country.requested}{Country slug name choosed}
\item{status.reque... | /man/GetDayOne.Rd | permissive | nekrum/covid19api | R | false | true | 1,198 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/covid19api.R
\name{GetDayOne}
\alias{GetDayOne}
\title{Get DayOne cases}
\usage{
GetDayOne(country.requested, status.requested, live = FALSE, total = FALSE)
}
\arguments{
\item{country.requested}{Country slug name choosed}
\item{status.reque... |
testlist <- list(id = integer(0), x = c(2.41785163922926e+24, 0, 0, 0, 0, 0, 0), y = numeric(0))
result <- do.call(ggforce:::enclose_points,testlist)
str(result) | /ggforce/inst/testfiles/enclose_points/libFuzzer_enclose_points/enclose_points_valgrind_files/1609955440-test.R | no_license | akhikolla/updated-only-Issues | R | false | false | 162 | r | testlist <- list(id = integer(0), x = c(2.41785163922926e+24, 0, 0, 0, 0, 0, 0), y = numeric(0))
result <- do.call(ggforce:::enclose_points,testlist)
str(result) |
####Plotting results for Modules Overlap####
library(dplyr)
library(WGCNA)
library(magrittr)
library(readr)
library(gplots)
library(tidyr)
library(vcd)
setwd ("C:/Users/karin/Dropbox/Arquivos_genomica_autistas/artigo_expressao/ASDiPSCTranscriptome")
#pvalues table
modpv=read.delim("DATA/module_overlap... | /ASDiPSCTranscriptome/SCRIPTS/Plot_module_overlap.R | no_license | griesik/ASDiPSCTranscriptome | R | false | false | 2,416 | r | ####Plotting results for Modules Overlap####
library(dplyr)
library(WGCNA)
library(magrittr)
library(readr)
library(gplots)
library(tidyr)
library(vcd)
setwd ("C:/Users/karin/Dropbox/Arquivos_genomica_autistas/artigo_expressao/ASDiPSCTranscriptome")
#pvalues table
modpv=read.delim("DATA/module_overlap... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/get_flow_data.R
\name{get_flow_data}
\alias{get_flow_data}
\title{Get flow data for a given location}
\usage{
get_flow_data(x, code, direction = "both")
}
\arguments{
\item{x}{An \code{epiflows} object.}
\item{code}{A character string denoti... | /man/get_flow_data.Rd | no_license | Paula-Moraga/epiflows | R | false | true | 821 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/get_flow_data.R
\name{get_flow_data}
\alias{get_flow_data}
\title{Get flow data for a given location}
\usage{
get_flow_data(x, code, direction = "both")
}
\arguments{
\item{x}{An \code{epiflows} object.}
\item{code}{A character string denoti... |
source("http://bioconductor.org/biocLite.R")
biocLite("devtools")
biocLite("pachterlab/sleuth")
libraries_file <- "$libraries"
abundances_file <- "$abundances"
full_model <- $fullModel
tx2gene_file <- "$tx2gene"
metadata <- read.table(libraries_file, sep="\t", header=T, stringsAsFactors=F)
abundance_files <- read.tab... | /nextflow/rna-quick/templates/export_sleuth.R | no_license | hmkim/workflow | R | false | false | 1,248 | r | source("http://bioconductor.org/biocLite.R")
biocLite("devtools")
biocLite("pachterlab/sleuth")
libraries_file <- "$libraries"
abundances_file <- "$abundances"
full_model <- $fullModel
tx2gene_file <- "$tx2gene"
metadata <- read.table(libraries_file, sep="\t", header=T, stringsAsFactors=F)
abundance_files <- read.tab... |
Ns=1000
iterations=1:Ns
Prob.Pop.doubling=rep(NA,length = 5)
Pop.project=vector("list",length = 5)
for(aa in 1:5)
{
#2.1. Set selectivity scenarios
Selectivity.SIM=Selectivity.SIM.1=vector("list",length = Ns)
scenario.sel=1
for (s in iterations) Selectivity.SIM.1[[s]]=Sel.fn(ASim[s],LinfSim[s],kSim[s... | /White_shark_test.scenarios.R | no_license | JuanMatiasBraccini/Git_Demography | R | false | false | 4,495 | r | Ns=1000
iterations=1:Ns
Prob.Pop.doubling=rep(NA,length = 5)
Pop.project=vector("list",length = 5)
for(aa in 1:5)
{
#2.1. Set selectivity scenarios
Selectivity.SIM=Selectivity.SIM.1=vector("list",length = Ns)
scenario.sel=1
for (s in iterations) Selectivity.SIM.1[[s]]=Sel.fn(ASim[s],LinfSim[s],kSim[s... |
## select CNVR using cutoff_freq
path_ensembleCNV <- ""
fileName_ensembleCNV <- ""
fileName_CNVR <- ""
cutoff_freq <- 0.01
path_output <- ""
mat_ensembleCNV <- readRDS( file = file.path(path_ensembleCNV, fileName_ensembleCNV) )
n.sample <- ncol( mat_ensembleCNV )
n.CNVR <- nrow( mat_ensembleCNV )
cnvrIDs <- row... | /05_boundary_refinement/step.1.subset.refinement.CNVR.R | no_license | jeffverboon/ensembleCNV | R | false | false | 1,203 | r |
## select CNVR using cutoff_freq
path_ensembleCNV <- ""
fileName_ensembleCNV <- ""
fileName_CNVR <- ""
cutoff_freq <- 0.01
path_output <- ""
mat_ensembleCNV <- readRDS( file = file.path(path_ensembleCNV, fileName_ensembleCNV) )
n.sample <- ncol( mat_ensembleCNV )
n.CNVR <- nrow( mat_ensembleCNV )
cnvrIDs <- row... |
.spaMM_lm.wfit <- function(x, y, offset=NULL,w=NULL) {
if (!is.null(w)) {
XtWX <- .ZtWZwrapper(x,w)
rhs <- crossprod(x,w*y)
} else {
XtWX <- crossprod(x)
rhs <- crossprod(x,y)
}
chmfactor <- Cholesky(XtWX)
if (!is.null(offset)) y <- y-offset
beta <- solve(chmfactor,rhs,system="A")
... | /CRAN/contrib/spaMM/R/sparseX.R | no_license | PRL-PRG/dyntrace-instrumented-packages | R | false | false | 630 | r | .spaMM_lm.wfit <- function(x, y, offset=NULL,w=NULL) {
if (!is.null(w)) {
XtWX <- .ZtWZwrapper(x,w)
rhs <- crossprod(x,w*y)
} else {
XtWX <- crossprod(x)
rhs <- crossprod(x,y)
}
chmfactor <- Cholesky(XtWX)
if (!is.null(offset)) y <- y-offset
beta <- solve(chmfactor,rhs,system="A")
... |
library(ggplot2)
library(ggpubr)
library(RColorBrewer)
library(reshape2)
# 1. Get color vectors
getColors <- function(n) {
col <- brewer.pal.info[brewer.pal.info$category=='qual', ] # get max. 74 colours
col_vector <- unlist(mapply(brewer.pal, col$maxcolors, rownames(col)))
ifelse (n > length(col_vector),
... | /functions.R | no_license | chilampoon/Meta-HCC | R | false | false | 2,134 | r | library(ggplot2)
library(ggpubr)
library(RColorBrewer)
library(reshape2)
# 1. Get color vectors
getColors <- function(n) {
col <- brewer.pal.info[brewer.pal.info$category=='qual', ] # get max. 74 colours
col_vector <- unlist(mapply(brewer.pal, col$maxcolors, rownames(col)))
ifelse (n > length(col_vector),
... |
#
# This is a Shiny web application. You can run the application by clicking
# the 'Run App' button above.
#
# Find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com/
#
library(shiny)
dvvsc <- function(tvvsc,vvvsc){
dvvsc=tvvsc/vvvsc
return(dvvsc)
}
dvvsc(80,20)
#Viaje vacio s... | /Calculadora_Tractores/app.R | no_license | aleszczuk/CostosCosecha | R | false | false | 9,159 | r | #
# This is a Shiny web application. You can run the application by clicking
# the 'Run App' button above.
#
# Find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com/
#
library(shiny)
dvvsc <- function(tvvsc,vvvsc){
dvvsc=tvvsc/vvvsc
return(dvvsc)
}
dvvsc(80,20)
#Viaje vacio s... |
setwd("C:/Users/sbhowmi/Desktop/Self Learning/Exploratory Data Analyis/Course_Directory/Week 1/Git_Project/ExData_Plotting1")
par(mfrow = c(1,1))
png(file = "plot2.png") # set output device
hhpc <- read.table("household_power_consumption.txt", header = TRUE, sep = ";", dec = ".", na.strings = "?") # read the data... | /plot2.R | no_license | saurish/ExData_Plotting1 | R | false | false | 739 | r |
setwd("C:/Users/sbhowmi/Desktop/Self Learning/Exploratory Data Analyis/Course_Directory/Week 1/Git_Project/ExData_Plotting1")
par(mfrow = c(1,1))
png(file = "plot2.png") # set output device
hhpc <- read.table("household_power_consumption.txt", header = TRUE, sep = ";", dec = ".", na.strings = "?") # read the data... |
library(ggplot2)
require(scales)
require(dplyr)
data=read.csv("/Users/shirnschall/Desktop/Numerik2/plots/cg-dense-vs-sparse",header = TRUE ,sep = "\t")
#vergleichsfunktionen
n <- seq(from=0.1,to=1250,by=0.1)
f <- function(a){
a*a
}
g <- function(a){
a
}
t<-c(f(n),g(n))
type<-c(rep("x*x",times=length(n)),
... | /plots/eigen-rafael.R | no_license | shirnschall/Numerik2 | R | false | false | 1,225 | r | library(ggplot2)
require(scales)
require(dplyr)
data=read.csv("/Users/shirnschall/Desktop/Numerik2/plots/cg-dense-vs-sparse",header = TRUE ,sep = "\t")
#vergleichsfunktionen
n <- seq(from=0.1,to=1250,by=0.1)
f <- function(a){
a*a
}
g <- function(a){
a
}
t<-c(f(n),g(n))
type<-c(rep("x*x",times=length(n)),
... |
# this is a list of packages we will load for every chapter
# let's try to keep this to a minimum
# for many chapters, you will load special packages for them -- like if there's a section on matching it will do library(Matching) in the code
# don't add those chapter-specific packages here
bookwide_packages <-
c(
... | /scripts/package_list.R | no_license | snowdj/book-6 | R | false | false | 684 | r | # this is a list of packages we will load for every chapter
# let's try to keep this to a minimum
# for many chapters, you will load special packages for them -- like if there's a section on matching it will do library(Matching) in the code
# don't add those chapter-specific packages here
bookwide_packages <-
c(
... |
# Code for running Hidden Markov Model
# install.packages("depmixS4")
# install.packages("HiddenMarkov")
# install.packages("WriteXLS")
# install.packages("writexl")
# install.packages("lubridate")
# install.packages("R.matlab")
# install.packages("raster")
# install.packages("tidyverse")
# install.packages("g... | /Code/EF_violation_estimation/R_Script_HMMAnnual.R | no_license | ChinchuMohan/Eflows-Biodiversity-Project | R | false | false | 6,010 | r | # Code for running Hidden Markov Model
# install.packages("depmixS4")
# install.packages("HiddenMarkov")
# install.packages("WriteXLS")
# install.packages("writexl")
# install.packages("lubridate")
# install.packages("R.matlab")
# install.packages("raster")
# install.packages("tidyverse")
# install.packages("g... |
# NOT RUN {
library(shiny)
# install.packages('ECharts2Shiny')
library(ECharts2Shiny)
dat <- data.frame(Type.A = c(4300, 10000, 25000, 35000, 50000),
Type.B = c(5000, 14000, 28000, 31000, 42000),
Type.C = c(4000, 2000, 9000, 29000, 35000))
row.names(dat) <- c("Feture 1", "Feature ... | /echarts_integration.r | permissive | ShounakRay/Stanford-COVIDVax | R | false | false | 882 | r | # NOT RUN {
library(shiny)
# install.packages('ECharts2Shiny')
library(ECharts2Shiny)
dat <- data.frame(Type.A = c(4300, 10000, 25000, 35000, 50000),
Type.B = c(5000, 14000, 28000, 31000, 42000),
Type.C = c(4000, 2000, 9000, 29000, 35000))
row.names(dat) <- c("Feture 1", "Feature ... |
# 1.Read dataset
data_full <- read.csv("./household_power_consumption.txt", header=T, sep=';', na.strings="?",
nrows=2075259, check.names=F, stringsAsFactors=F, comment.char="", quote='\"')
data_full$Date <- as.Date(data_full$Date, format="%d/%m/%Y")
# 2.Subsetting the data based on dates
data <-... | /plot2.R | no_license | marklcl/ExData_Plotting1 | R | false | false | 757 | r | # 1.Read dataset
data_full <- read.csv("./household_power_consumption.txt", header=T, sep=';', na.strings="?",
nrows=2075259, check.names=F, stringsAsFactors=F, comment.char="", quote='\"')
data_full$Date <- as.Date(data_full$Date, format="%d/%m/%Y")
# 2.Subsetting the data based on dates
data <-... |
library(ape)
testtree <- read.tree("13324_0.txt")
unrooted_tr <- unroot(testtree)
write.tree(unrooted_tr, file="13324_0_unrooted.txt") | /codeml_files/newick_trees_processed/13324_0/rinput.R | no_license | DaniBoo/cyanobacteria_project | R | false | false | 137 | r | library(ape)
testtree <- read.tree("13324_0.txt")
unrooted_tr <- unroot(testtree)
write.tree(unrooted_tr, file="13324_0_unrooted.txt") |
install.packages("readxl")
install.packages("tidyverse")
library(readxl)
library(tidyverse)
#import the callback information
callbacks <- read.csv(file="~/Desktop/REACH/Data/callback_merged_empty cells.csv", head=T, dec=".", sep=",")
#import the actual version of the cleaned data twice
som<-read.csv(file="~/Desktop/... | /FeedingInCallbacks.R | no_license | causeri3/dataCleaningSOM20 | R | false | false | 4,879 | r | install.packages("readxl")
install.packages("tidyverse")
library(readxl)
library(tidyverse)
#import the callback information
callbacks <- read.csv(file="~/Desktop/REACH/Data/callback_merged_empty cells.csv", head=T, dec=".", sep=",")
#import the actual version of the cleaned data twice
som<-read.csv(file="~/Desktop/... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/vivekn-sentiment-detector.R
\name{nlp_vivekn_sentiment_detector}
\alias{nlp_vivekn_sentiment_detector}
\title{Spark NLP ViveknSentimentApproach}
\usage{
nlp_vivekn_sentiment_detector(x, input_cols, output_col, sentiment_col,
prune_corpus = ... | /man/nlp_vivekn_sentiment_detector.Rd | permissive | mstei4176/sparknlp | R | false | true | 1,895 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/vivekn-sentiment-detector.R
\name{nlp_vivekn_sentiment_detector}
\alias{nlp_vivekn_sentiment_detector}
\title{Spark NLP ViveknSentimentApproach}
\usage{
nlp_vivekn_sentiment_detector(x, input_cols, output_col, sentiment_col,
prune_corpus = ... |
# server for JAEG Tweet
function(input, output) {
# ---- Get User Tweet ----
# Grab Tweet
user_info <- reactive({
withProgress({
setProgress(message = "Grabbing Tweets!")})
input$go
isolate({num_set <- input$num_t
# clean up the @ sign if is there
tweethandle <- gsub("@", "", input$... | /Tweet/Server.R | permissive | NeaterReport/portfolio | R | false | false | 16,150 | r | # server for JAEG Tweet
function(input, output) {
# ---- Get User Tweet ----
# Grab Tweet
user_info <- reactive({
withProgress({
setProgress(message = "Grabbing Tweets!")})
input$go
isolate({num_set <- input$num_t
# clean up the @ sign if is there
tweethandle <- gsub("@", "", input$... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/main.R
\name{bin_mean}
\alias{bin_mean}
\title{Binomial Mean}
\usage{
bin_mean(trials, prob)
}
\arguments{
\item{trials}{input number of trials}
\item{prob}{input probability}
}
\value{
computed mean of the binomial distribution
}
\descripti... | /binomial/man/bin_mean.Rd | no_license | stat133-sp19/hw-stat133-hoangkhanhnghi | R | false | true | 399 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/main.R
\name{bin_mean}
\alias{bin_mean}
\title{Binomial Mean}
\usage{
bin_mean(trials, prob)
}
\arguments{
\item{trials}{input number of trials}
\item{prob}{input probability}
}
\value{
computed mean of the binomial distribution
}
\descripti... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/assertions.R
\name{mlr_assertions}
\alias{mlr_assertions}
\alias{assert_backend}
\alias{assert_experiment}
\alias{assert_task}
\alias{assert_tasks}
\alias{assert_learner}
\alias{assert_learners}
\alias{assert_measure}
\alias{assert_measures}
... | /man/mlr_assertions.Rd | permissive | be-marc/mlr3 | R | false | true | 2,542 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/assertions.R
\name{mlr_assertions}
\alias{mlr_assertions}
\alias{assert_backend}
\alias{assert_experiment}
\alias{assert_task}
\alias{assert_tasks}
\alias{assert_learner}
\alias{assert_learners}
\alias{assert_measure}
\alias{assert_measures}
... |
\name{photoperiod}
\alias{photoperiod}
\alias{photoperiod,numeric-method}
\alias{photoperiod,Date-method}
\alias{photoperiod,data.frame-method}
\alias{photoperiod,SpatRaster-method}
\title{ photoperiod}
\description{
Compute photoperiod (daylength, sunshine duration) at a given latitude and day of the yea... | /man/daylength.Rd | no_license | cran/meteor | R | false | false | 1,303 | rd | \name{photoperiod}
\alias{photoperiod}
\alias{photoperiod,numeric-method}
\alias{photoperiod,Date-method}
\alias{photoperiod,data.frame-method}
\alias{photoperiod,SpatRaster-method}
\title{ photoperiod}
\description{
Compute photoperiod (daylength, sunshine duration) at a given latitude and day of the yea... |
library(dplyr)
library(maps)
library(ggplot2)
library(grid)
source('code/edgeMaker.R')
mapExt <<- data.frame('x' = c(-125,-100), 'y' = c(30,50))
# get the data and combine it
getFlightData <- function(xx = 'data/TestFlights.csv')
{
fd <- read.csv(xx)
latLon <- read.csv('data/LatLon.csv', comment.char = '#')
... | /code/mapFlights.R | no_license | rabutler/myFlightMap | R | false | false | 2,202 | r | library(dplyr)
library(maps)
library(ggplot2)
library(grid)
source('code/edgeMaker.R')
mapExt <<- data.frame('x' = c(-125,-100), 'y' = c(30,50))
# get the data and combine it
getFlightData <- function(xx = 'data/TestFlights.csv')
{
fd <- read.csv(xx)
latLon <- read.csv('data/LatLon.csv', comment.char = '#')
... |
#'@title Example Dataset
#'
#'@description a fictitious dataset showcasing the functionality of the WhatsApp Parser
#'@name Example
#'@docType data
#'@usage showcasing the functionality of the WhatsApp Parser
#'@format A .txt dataframe
#'@keywords datasets, WhatsApp Textfile
NULL
| /R/Example.R | no_license | davidm6433/WhatsAppParser | R | false | false | 290 | r | #'@title Example Dataset
#'
#'@description a fictitious dataset showcasing the functionality of the WhatsApp Parser
#'@name Example
#'@docType data
#'@usage showcasing the functionality of the WhatsApp Parser
#'@format A .txt dataframe
#'@keywords datasets, WhatsApp Textfile
NULL
|
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/appstream_operations.R
\name{appstream_delete_user}
\alias{appstream_delete_user}
\title{Deletes a user from the user pool}
\usage{
appstream_delete_user(UserName, AuthenticationType)
}
\arguments{
\item{UserName}{[required] The email address... | /cran/paws.end.user.computing/man/appstream_delete_user.Rd | permissive | sanchezvivi/paws | R | false | true | 689 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/appstream_operations.R
\name{appstream_delete_user}
\alias{appstream_delete_user}
\title{Deletes a user from the user pool}
\usage{
appstream_delete_user(UserName, AuthenticationType)
}
\arguments{
\item{UserName}{[required] The email address... |
#' Landmark Multidimensional Scaling
#'
#' Landmark MDS is a variant of Classical Multidimensional Scaling in that
#' it first finds a low-dimensional embedding using a small portion of given dataset
#' and graft the others in a manner to preserve as much pairwise distance from
#' all the other data points to landmark ... | /R/linear_LMDS.R | no_license | rcannood/Rdimtools | R | false | false | 4,542 | r | #' Landmark Multidimensional Scaling
#'
#' Landmark MDS is a variant of Classical Multidimensional Scaling in that
#' it first finds a low-dimensional embedding using a small portion of given dataset
#' and graft the others in a manner to preserve as much pairwise distance from
#' all the other data points to landmark ... |
MultCapability <- function(data, lsls, usls, targets,
ncomps = NULL, Target = FALSE) {
X <- as.matrix(data)
m <- nrow(X)
ColMeans <- colMeans(X)
ColSD <- sqrt(colSums((X - rep(colMeans(X), each = m))^2)/(m - 1))
SVD <- svd(cov(X), nu = ncomps, nv = ncomps)
eigenValues <- SVD$d[1:n... | /R/MultCapability.R | no_license | cran/mvdalab | R | false | false | 4,465 | r | MultCapability <- function(data, lsls, usls, targets,
ncomps = NULL, Target = FALSE) {
X <- as.matrix(data)
m <- nrow(X)
ColMeans <- colMeans(X)
ColSD <- sqrt(colSums((X - rep(colMeans(X), each = m))^2)/(m - 1))
SVD <- svd(cov(X), nu = ncomps, nv = ncomps)
eigenValues <- SVD$d[1:n... |
MR <- read.csv("../data/GSE37418.csv", header = T,check.names = F,row.names = 1)
########HEATMAP of G3 vs G4 for GSE37418 #######################
G4 <- c(1,2,4,6,7,8,13,14,15,18,19,20,21,22,25,27,28,33,36, 38,39,40,45,46,49,50, 53,54,55,56,57,58,68, 69, 70, 71, 73, 75, 76)
G3 <- c(9, 10, 11, 12, 17, 23, 24,34, 35, 37... | /figures/suppl/FigureS7.R | no_license | idellyzhang/DDR | R | false | false | 3,025 | r | MR <- read.csv("../data/GSE37418.csv", header = T,check.names = F,row.names = 1)
########HEATMAP of G3 vs G4 for GSE37418 #######################
G4 <- c(1,2,4,6,7,8,13,14,15,18,19,20,21,22,25,27,28,33,36, 38,39,40,45,46,49,50, 53,54,55,56,57,58,68, 69, 70, 71, 73, 75, 76)
G3 <- c(9, 10, 11, 12, 17, 23, 24,34, 35, 37... |
#
# Project: DescTools
#
# Purpose: Tools for descriptive statistics, the missing link...
# Univariat, pairwise bivariate, groupwise und multivariate
#
# Author: Andri Signorell
# Version: 0.99.19 (under construction)
#
# Depends: tcltk
# Imports: boot
# Suggests: RDCOMClient
#
# Datum:
# ... | /R/DescTools.r | no_license | acabaya/DescTools | R | false | false | 476,379 | r | #
# Project: DescTools
#
# Purpose: Tools for descriptive statistics, the missing link...
# Univariat, pairwise bivariate, groupwise und multivariate
#
# Author: Andri Signorell
# Version: 0.99.19 (under construction)
#
# Depends: tcltk
# Imports: boot
# Suggests: RDCOMClient
#
# Datum:
# ... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/gg_scalelocation.R
\name{gg_scalelocation}
\alias{gg_scalelocation}
\title{Plot scale-location (also called spread-location plot) in ggplot.}
\usage{
gg_scalelocation(fitted.lm, method = "loess", scale.factor = 1,
se = FALSE)
}
\arguments{
... | /man/gg_scalelocation.Rd | no_license | alienzj/lindia | R | false | true | 1,056 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/gg_scalelocation.R
\name{gg_scalelocation}
\alias{gg_scalelocation}
\title{Plot scale-location (also called spread-location plot) in ggplot.}
\usage{
gg_scalelocation(fitted.lm, method = "loess", scale.factor = 1,
se = FALSE)
}
\arguments{
... |
anolis.data <- read.csv("anolis.data.csv", header=TRUE)
| /dataSources/anolis.data.R | no_license | ghthomas/motmot | R | false | false | 56 | r | anolis.data <- read.csv("anolis.data.csv", header=TRUE)
|
# Hierarcical Clustering
# Load The dataset
data("iris")
dataset <- as.data.frame(iris)
# Delete Species column
dataset <- dataset[-5]
dendrogram = hclust(d = dist(dataset, method = 'euclidean'), method = 'ward.D')
plot(dendrogram,
main = paste('Dendrogram'),
xlab = 'Customers',
ylab = 'Euclidean dista... | /R/Clustering/Hierarcical Clustering.R | no_license | ferianrian/Trainee | R | false | false | 482 | r | # Hierarcical Clustering
# Load The dataset
data("iris")
dataset <- as.data.frame(iris)
# Delete Species column
dataset <- dataset[-5]
dendrogram = hclust(d = dist(dataset, method = 'euclidean'), method = 'ward.D')
plot(dendrogram,
main = paste('Dendrogram'),
xlab = 'Customers',
ylab = 'Euclidean dista... |
german_credit <- read.csv("C:/Users/asif/Downloads/german_credit.csv",header = T)
str(german_credit)
summary(german_credit$installment_as_income_perc)
german_credit$default<-as.factor(german_credit$default)
str(german_credit)
summary(german_credit$credit_history)
# installment_as_income perc,present_res_since,credit_th... | /NaiveBayes.R | no_license | prathmesh2998/R-program | R | false | false | 2,314 | r | german_credit <- read.csv("C:/Users/asif/Downloads/german_credit.csv",header = T)
str(german_credit)
summary(german_credit$installment_as_income_perc)
german_credit$default<-as.factor(german_credit$default)
str(german_credit)
summary(german_credit$credit_history)
# installment_as_income perc,present_res_since,credit_th... |
#' Get global preferences for the current logged in user
#'
#' @export
#' @param parse (logical) Attempt to parse to data.frame's if possible. Default: \code{TRUE}
#' @template curl
#' @return either a data.frame or a list
#' @examples \dontrun{
#' prefs()
#' }
prefs <- function(parse = TRUE, ...) {
res <- asp_GET("c... | /R/prefs.R | no_license | sckott/aspacer | R | false | false | 387 | r | #' Get global preferences for the current logged in user
#'
#' @export
#' @param parse (logical) Attempt to parse to data.frame's if possible. Default: \code{TRUE}
#' @template curl
#' @return either a data.frame or a list
#' @examples \dontrun{
#' prefs()
#' }
prefs <- function(parse = TRUE, ...) {
res <- asp_GET("c... |
#Write a R program to print the numbers from 1 to 100 and print
#"Fizz" for multiples of 3, print "Buzz" for multiples of 5,
#and print "FizzBuzz" for multiples of both.
for (n in 1:100) {
if (n %% 3 == 0 & n %% 5 == 0) {print("FizzBuzz")}
else if (n %% 3 == 0) {print("Fizz")}
else if (n %% 5 == 0) {print(... | /WID W9 Homework extra2.R | no_license | Faybeee/Session-9-Homework | R | false | false | 350 | r | #Write a R program to print the numbers from 1 to 100 and print
#"Fizz" for multiples of 3, print "Buzz" for multiples of 5,
#and print "FizzBuzz" for multiples of both.
for (n in 1:100) {
if (n %% 3 == 0 & n %% 5 == 0) {print("FizzBuzz")}
else if (n %% 3 == 0) {print("Fizz")}
else if (n %% 5 == 0) {print(... |
# Run this script to generate all the country PDF reports for Investment Climate (FCV) only
# List of countries is based on intersection of TCdata360 country list and Harmonized FCV 2017 list (from WBG IC-FCS team)
##################################
# setwd() to handle images and other files
setwd('/Users/mrpso/Docume... | /Report_Generator_FCVonly.R | no_license | asRodelgo/reportGenerator360 | R | false | false | 817 | r | # Run this script to generate all the country PDF reports for Investment Climate (FCV) only
# List of countries is based on intersection of TCdata360 country list and Harmonized FCV 2017 list (from WBG IC-FCS team)
##################################
# setwd() to handle images and other files
setwd('/Users/mrpso/Docume... |
# ____________________________________________________________________________
# Server ####
library(shiny)
library(plotly)
library(magrittr)
library(shinyjs)
library(stringr)
library(RColorBrewer)
library(DT)
library(shinyBS)
library(shinycssloaders... | /inst/shiny/myApp/server.R | permissive | XPL1986/QRseq | R | false | false | 1,754 | r | # ____________________________________________________________________________
# Server ####
library(shiny)
library(plotly)
library(magrittr)
library(shinyjs)
library(stringr)
library(RColorBrewer)
library(DT)
library(shinyBS)
library(shinycssloaders... |
library(SSrat)
### Name: example1.rat
### Title: Example 1 of rating data that can be processed further to obtain
### social status determinations
### Aliases: example1.rat
### Keywords: datasets
### ** Examples
data(example1.rat)
| /data/genthat_extracted_code/SSrat/examples/example1.rat.Rd.R | no_license | surayaaramli/typeRrh | R | false | false | 242 | r | library(SSrat)
### Name: example1.rat
### Title: Example 1 of rating data that can be processed further to obtain
### social status determinations
### Aliases: example1.rat
### Keywords: datasets
### ** Examples
data(example1.rat)
|
setwd(normalizePath(dirname(R.utils::commandArgs(asValues=TRUE)$"f")))
source('../../h2o-runit.R')
test.glm.bin.accessors <- function(conn) {
Log.info("Making glm with and without validation_frame...")
pros.hex <- h2o.uploadFile(conn, locate("smalldata/prostate/prostate.csv.zip"))
pros.hex[,2] <- as.factor(pros.... | /h2o-r/tests/testdir_algos/glm/runit_NOPASS_GLM_accessors_binomial.R | permissive | dts3/h2o-3 | R | false | false | 5,140 | r | setwd(normalizePath(dirname(R.utils::commandArgs(asValues=TRUE)$"f")))
source('../../h2o-runit.R')
test.glm.bin.accessors <- function(conn) {
Log.info("Making glm with and without validation_frame...")
pros.hex <- h2o.uploadFile(conn, locate("smalldata/prostate/prostate.csv.zip"))
pros.hex[,2] <- as.factor(pros.... |
library(XML)
api.url <-"http://apis.data.go.kr/1611000/BldEngyService/getBeElctyUsgInfo?"#공공데이터 주소 입력
service.key<-"8PZnRzZb4yXsXJQVBDX74xuf8kHhF4cmY5XnEO9apteNWtahGwpA9%2FjrthHB0tX7GBlm9zN1A%2F0rKCx3wGe27g%3D%3D"#Service. key 값 입력
#특정 데이터를 볼러오기 위한 인수 입력/전부다 필요한 것은 아님
rnum<-vector(mode="numeric",length=8),# 순번
useYm<... | /building-energy.R | no_license | youngji-cho/energy-finance | R | false | false | 1,626 | r | library(XML)
api.url <-"http://apis.data.go.kr/1611000/BldEngyService/getBeElctyUsgInfo?"#공공데이터 주소 입력
service.key<-"8PZnRzZb4yXsXJQVBDX74xuf8kHhF4cmY5XnEO9apteNWtahGwpA9%2FjrthHB0tX7GBlm9zN1A%2F0rKCx3wGe27g%3D%3D"#Service. key 값 입력
#특정 데이터를 볼러오기 위한 인수 입력/전부다 필요한 것은 아님
rnum<-vector(mode="numeric",length=8),# 순번
useYm<... |
library(ggpubr)
library(dplyr)
#### read data ####
load("SFig2.RData")
#### pplot ####
med_dat <- dat %>% group_by(x3,x6) %>% summarise(med = median(x4))
p <- ggplot(dat, aes(x=x3, y=x5, group=x3)) + geom_boxplot(aes(color=x3),outlier.shape = NA) +theme_classic(base_size=10) +
ylab("Proportion") + xlab("Method") ... | /paper/Figures/SFig2.R | permissive | Sandyyy123/PGS-LMM | R | false | false | 502 | r | library(ggpubr)
library(dplyr)
#### read data ####
load("SFig2.RData")
#### pplot ####
med_dat <- dat %>% group_by(x3,x6) %>% summarise(med = median(x4))
p <- ggplot(dat, aes(x=x3, y=x5, group=x3)) + geom_boxplot(aes(color=x3),outlier.shape = NA) +theme_classic(base_size=10) +
ylab("Proportion") + xlab("Method") ... |
#' Save API credentials for later use
#'
#' This functions caches the credentials to avoid need for entering it when
#' calling other functions
#' @param app_key application key
#' @examples
#' # since not checking is preformed not to waste API calls
#' # it falls on the user to save correct information
#' save_walmart... | /R/client.R | permissive | EmilHvitfeldt/walmartAPI | R | false | false | 479 | r | #' Save API credentials for later use
#'
#' This functions caches the credentials to avoid need for entering it when
#' calling other functions
#' @param app_key application key
#' @examples
#' # since not checking is preformed not to waste API calls
#' # it falls on the user to save correct information
#' save_walmart... |
library(FactoMineR)
library(dimRed)
library(reshape2)
library(ggplot2)
library(FactoMineR)
library(tm)
library(stringr)
library(NMIcode)
library(LICORS)
library(readr)
library(keras)
library(mclust)
pen.tra = read.table("/Users/jzk/Documents/M2/reducDimold/penDigitss/pendigits.tra", sep = ",")
pen.tes = read.table("/Us... | /.ipynb_checkpoints/ProjetReducDim-checkpoint.r | no_license | yannistannier/deepdr-dae-with-lle | R | false | false | 10,627 | r | library(FactoMineR)
library(dimRed)
library(reshape2)
library(ggplot2)
library(FactoMineR)
library(tm)
library(stringr)
library(NMIcode)
library(LICORS)
library(readr)
library(keras)
library(mclust)
pen.tra = read.table("/Users/jzk/Documents/M2/reducDimold/penDigitss/pendigits.tra", sep = ",")
pen.tes = read.table("/Us... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/find_pattern.R
\name{find_pattern}
\alias{find_pattern}
\alias{is_in_file}
\title{Find a pattern in files from a directory}
\usage{
find_pattern(pattern, where = here(), full_names = FALSE)
is_in_file(pattern, file)
}
\arguments{
\item{patte... | /man/find_pattern.Rd | permissive | BenjaminLouis/benutils | R | false | true | 1,172 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/find_pattern.R
\name{find_pattern}
\alias{find_pattern}
\alias{is_in_file}
\title{Find a pattern in files from a directory}
\usage{
find_pattern(pattern, where = here(), full_names = FALSE)
is_in_file(pattern, file)
}
\arguments{
\item{patte... |
library(tidyverse)
library(extrafont)
library(ggthemr)
ggthemr(palette = "chalk", type = "outer")
fonts()
cran_code <- readr::read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2019/2019-11-12/loc_cran_packages.csv")
lines_code <- cran_code %>%
group_by(pkg_name) %>%
summarise(li... | /Tidy Tuesday #8 - CRAN/cran.R | no_license | skybett/Tidy-Tuesdays | R | false | false | 664 | r | library(tidyverse)
library(extrafont)
library(ggthemr)
ggthemr(palette = "chalk", type = "outer")
fonts()
cran_code <- readr::read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2019/2019-11-12/loc_cran_packages.csv")
lines_code <- cran_code %>%
group_by(pkg_name) %>%
summarise(li... |
#' Homogeneization of GNSS series
#'
#' fit a segmentation in the mean model by taken into account for a functional part and a heterogeneous variance (default is monthly)
#'
#' @param Data a data frame, with size [n x 2], containing the signal (e.g. the daily GPS-ERAI series for GNSS) and the dates (in format yyyy-mm-d... | /R/GNSSseg.R | no_license | arq16/GNSSseg | R | false | false | 16,073 | r | #' Homogeneization of GNSS series
#'
#' fit a segmentation in the mean model by taken into account for a functional part and a heterogeneous variance (default is monthly)
#'
#' @param Data a data frame, with size [n x 2], containing the signal (e.g. the daily GPS-ERAI series for GNSS) and the dates (in format yyyy-mm-d... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/get_urls.R
\name{get_urls}
\alias{get_urls}
\title{Retrieve urls on google search}
\usage{
get_urls(search, how_many = 10)
}
\arguments{
\item{search}{A search string}
\item{how_many}{How many urls do you want to retrive}
}
\description{
Thi... | /man/get_urls.Rd | permissive | samuelmacedo83/google.search.crawler | R | false | true | 445 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/get_urls.R
\name{get_urls}
\alias{get_urls}
\title{Retrieve urls on google search}
\usage{
get_urls(search, how_many = 10)
}
\arguments{
\item{search}{A search string}
\item{how_many}{How many urls do you want to retrive}
}
\description{
Thi... |
library(tidyverse)
library(lubridate)
library(scales)
load(file = "E:/R/COVID-19/covid.ECDC.Rda")
load(file = "E:/R/COVID-19/covid2.Rda")
# test Białoruś na tle UE
ECDC2 <- covid.ECDC%>%
ungroup()%>%
select(ISO3, population)%>%
unique()
a <- covid%>%
#filter(Państwo=="Białoruś"|Państwo=="Szwajcaria"|`Blok Ek... | /bialorus.R | no_license | slawomirmatuszak/COVID-19 | R | false | false | 13,133 | r | library(tidyverse)
library(lubridate)
library(scales)
load(file = "E:/R/COVID-19/covid.ECDC.Rda")
load(file = "E:/R/COVID-19/covid2.Rda")
# test Białoruś na tle UE
ECDC2 <- covid.ECDC%>%
ungroup()%>%
select(ISO3, population)%>%
unique()
a <- covid%>%
#filter(Państwo=="Białoruś"|Państwo=="Szwajcaria"|`Blok Ek... |
# Set workspace directory and bring in datasets + libraries
setwd("/Users/williamjohnson/Desktop/Laura/Hallett_Lab/Repositories/thesis-mussels/site_DATAexplore")
library(tidyverse)
abundance <- as.tibble(read.csv("laurancy.csv", header = TRUE))
streampwr <- as.tibble(read.csv("streamPWR.csv", header = TRUE))
dist <- ... | /site_DATAexplore/StreamPWR.R | no_license | ljohnso8/thesis-mussels | R | false | false | 3,487 | r | # Set workspace directory and bring in datasets + libraries
setwd("/Users/williamjohnson/Desktop/Laura/Hallett_Lab/Repositories/thesis-mussels/site_DATAexplore")
library(tidyverse)
abundance <- as.tibble(read.csv("laurancy.csv", header = TRUE))
streampwr <- as.tibble(read.csv("streamPWR.csv", header = TRUE))
dist <- ... |
pop<-100
K<-1000
pop.hist<-c()
r<-0.05
for (i in 1:150) {
pop.hist[i]<-pop
pop<-pop*exp(r*(1-pop/K))
}
plot(pop.hist)
| /chem160homework7/pop2.R | no_license | nhukim35/chem160homework7 | R | false | false | 122 | r | pop<-100
K<-1000
pop.hist<-c()
r<-0.05
for (i in 1:150) {
pop.hist[i]<-pop
pop<-pop*exp(r*(1-pop/K))
}
plot(pop.hist)
|
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ses_operations.R
\name{ses_update_configuration_set_tracking_options}
\alias{ses_update_configuration_set_tracking_options}
\title{Modifies an association between a configuration set and a custom domain
for open and click event tracking}
\usa... | /cran/paws.customer.engagement/man/ses_update_configuration_set_tracking_options.Rd | permissive | johnnytommy/paws | R | false | true | 1,307 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ses_operations.R
\name{ses_update_configuration_set_tracking_options}
\alias{ses_update_configuration_set_tracking_options}
\title{Modifies an association between a configuration set and a custom domain
for open and click event tracking}
\usa... |
#' @title Query GDC data
#' @description
#' Uses GDC API to search for search, it searches for both controlled and
#' open-access data.
#' For GDC data arguments project, data.category, data.type and workflow.type should be used
#' For the legacy data arguments project, data.category, platform and/or file.exten... | /R/query.R | no_license | romagnolid/TCGAbiolinks | R | false | false | 41,955 | r | #' @title Query GDC data
#' @description
#' Uses GDC API to search for search, it searches for both controlled and
#' open-access data.
#' For GDC data arguments project, data.category, data.type and workflow.type should be used
#' For the legacy data arguments project, data.category, platform and/or file.exten... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/custom_fields.R
\name{update_field}
\alias{update_field}
\title{Update custom field}
\usage{
update_field(id, body = list(name = "New name"), ...)
}
\arguments{
\item{id}{Board ID}
\item{body}{Named list with additional parameters}
\item{..... | /man/update_field.Rd | no_license | amirmahmoodv/trelloR | R | false | true | 465 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/custom_fields.R
\name{update_field}
\alias{update_field}
\title{Update custom field}
\usage{
update_field(id, body = list(name = "New name"), ...)
}
\arguments{
\item{id}{Board ID}
\item{body}{Named list with additional parameters}
\item{..... |
#' Interpolate new positions within a spatiotemporal path data
#'
#' Interpolate new positions within a spatiotemporal path data set
#' (e.g., detections of tagged fish) at regularly-spaced time intervals
#' using linear or non-linear interpolation.
#'
#' @param det An object of class \code{glatos_detections}... | /R/vis-interpolate_path.r | no_license | jsta/glatos | R | false | false | 22,942 | r | #' Interpolate new positions within a spatiotemporal path data
#'
#' Interpolate new positions within a spatiotemporal path data set
#' (e.g., detections of tagged fish) at regularly-spaced time intervals
#' using linear or non-linear interpolation.
#'
#' @param det An object of class \code{glatos_detections}... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/plot.R
\name{plot.timeresolved}
\alias{plot.timeresolved}
\alias{plot.PHdata}
\title{Plot a time resolved mass spectrometry signal}
\usage{
\method{plot}{timeresolved}(x, label, mass, ...)
\method{plot}{PHdata}(x, label, mass, ...)
}
\argume... | /man/plot.Rd | no_license | pvermees/ArArRedux | R | false | true | 869 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/plot.R
\name{plot.timeresolved}
\alias{plot.timeresolved}
\alias{plot.PHdata}
\title{Plot a time resolved mass spectrometry signal}
\usage{
\method{plot}{timeresolved}(x, label, mass, ...)
\method{plot}{PHdata}(x, label, mass, ...)
}
\argume... |
##
##
## plot1.R
## -----------------------
##
## Exploratory Data Analysis Project 1
## David Saint Ruby
## September 5, 2014
##
## comments date
##
## original 9/5/14
## our vector of NA strings
nachars <- c("?")
## read in the file
## use as.is=TRUE to allow easy conversion later of dates and times
househol... | /plot1.R | no_license | davidsaintruby/ExData_Plotting1 | R | false | false | 1,133 | r | ##
##
## plot1.R
## -----------------------
##
## Exploratory Data Analysis Project 1
## David Saint Ruby
## September 5, 2014
##
## comments date
##
## original 9/5/14
## our vector of NA strings
nachars <- c("?")
## read in the file
## use as.is=TRUE to allow easy conversion later of dates and times
househol... |
#########################################
#This function computes #
#the log of a function proportional to #
#the posterior distribution #
#########################################
logpost <- function(parms, indep, Y, times, VN, VF, n,
indBeta, aBeta, bBeta, ind... | /B2Z/R/logpost.R | no_license | ingted/R-Examples | R | false | false | 2,397 | r | #########################################
#This function computes #
#the log of a function proportional to #
#the posterior distribution #
#########################################
logpost <- function(parms, indep, Y, times, VN, VF, n,
indBeta, aBeta, bBeta, ind... |
## Put comments here that give an overall description of what your
## functions do
## Write a short comment describing this function
makeCacheMatrix <- function(x = matrix()) {
m <- NULL
set <- function(y) {
x <<- y
m <<- NULL
}
get <- function() x
setmatrix <- function(matrix) m <<- matrix
getmat... | /cachematrix.R | no_license | sfpacman/datasciencecoursera | R | false | false | 731 | r | ## Put comments here that give an overall description of what your
## functions do
## Write a short comment describing this function
makeCacheMatrix <- function(x = matrix()) {
m <- NULL
set <- function(y) {
x <<- y
m <<- NULL
}
get <- function() x
setmatrix <- function(matrix) m <<- matrix
getmat... |
#integrate samples together
gastric_N.big.normalized<-merge(P3_N1.s, y=c(P3_N2.s, P5_N1.s, P5_N2.s), add.cell.ids=c("P3_N1", "P3_N2", "P5_N1", "P5_N2"), project = "Normal", merge.data = TRUE)
gastric_P.big.normalized<-merge(P3_P1.s, y=c(P3_P2.s, P5_P1.s, P5_P2.s), add.cell.ids=c("P3_P1", "P3_N2", "P5_P1", "P5_P2"), pro... | /scRNAscript/merge_samples.R | no_license | pyanne2000/GC-analysis | R | false | false | 2,903 | r | #integrate samples together
gastric_N.big.normalized<-merge(P3_N1.s, y=c(P3_N2.s, P5_N1.s, P5_N2.s), add.cell.ids=c("P3_N1", "P3_N2", "P5_N1", "P5_N2"), project = "Normal", merge.data = TRUE)
gastric_P.big.normalized<-merge(P3_P1.s, y=c(P3_P2.s, P5_P1.s, P5_P2.s), add.cell.ids=c("P3_P1", "P3_N2", "P5_P1", "P5_P2"), pro... |
testlist <- list(a = 0L, b = 0L, x = c(134744072L, 134744072L, 144678815L, -1616928865L, -1616928865L, -1616928865L, -1616928865L, -1616928865L, -1616928865L, -1616928865L, -1616928865L, -1616928865L, -1616928865L, -1616928865L, -1616928865L, -1616928865L, 134744072L, 134744072L, 134744072L, 134744072L, 134744072L,... | /grattan/inst/testfiles/anyOutside/libFuzzer_anyOutside/anyOutside_valgrind_files/1610131952-test.R | no_license | akhikolla/updated-only-Issues | R | false | false | 516 | r | testlist <- list(a = 0L, b = 0L, x = c(134744072L, 134744072L, 144678815L, -1616928865L, -1616928865L, -1616928865L, -1616928865L, -1616928865L, -1616928865L, -1616928865L, -1616928865L, -1616928865L, -1616928865L, -1616928865L, -1616928865L, -1616928865L, 134744072L, 134744072L, 134744072L, 134744072L, 134744072L,... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/owner.R
\name{owner}
\alias{owner}
\alias{owner<-}
\alias{owner,character-method}
\alias{owner,SsimLibrary-method}
\alias{owner,Project-method}
\alias{owner,Scenario-method}
\alias{owner,Folder-method}
\alias{owner<-,character-method}
\alias{... | /man/owner.Rd | permissive | syncrosim/rsyncrosim | R | false | true | 1,797 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/owner.R
\name{owner}
\alias{owner}
\alias{owner<-}
\alias{owner,character-method}
\alias{owner,SsimLibrary-method}
\alias{owner,Project-method}
\alias{owner,Scenario-method}
\alias{owner,Folder-method}
\alias{owner<-,character-method}
\alias{... |
download.file("https://d396qusza40orc.cloudfront.net/exdata%2Fdata%2Fhousehold_power_consumption.zip", "household_power_consumption.zip")
unzip("household_power_consumption.zip")
library(sqldf)
x<-read.csv.sql("household_power_consumption.txt", sql="select * from file where Date in ('1/2/2007','2/2/2007')", sep = ";",... | /plot1.R | no_license | sebastianovide/ExData_Plotting1 | R | false | false | 589 | r | download.file("https://d396qusza40orc.cloudfront.net/exdata%2Fdata%2Fhousehold_power_consumption.zip", "household_power_consumption.zip")
unzip("household_power_consumption.zip")
library(sqldf)
x<-read.csv.sql("household_power_consumption.txt", sql="select * from file where Date in ('1/2/2007','2/2/2007')", sep = ";",... |
library(fMultivar)
### Name: utils-adapt
### Title: Integrator for multivariate distributions
### Aliases: adapt
### Keywords: math
### ** Examples
## No test:
## Check that dnorm2d is normalized:
# Normal Density:
density <- function(x) dnorm2d(x=x[1], y = x[2])
# Calling Cubature:
BIG <- c(... | /data/genthat_extracted_code/fMultivar/examples/utils-adapt.Rd.R | no_license | surayaaramli/typeRrh | R | false | false | 632 | r | library(fMultivar)
### Name: utils-adapt
### Title: Integrator for multivariate distributions
### Aliases: adapt
### Keywords: math
### ** Examples
## No test:
## Check that dnorm2d is normalized:
# Normal Density:
density <- function(x) dnorm2d(x=x[1], y = x[2])
# Calling Cubature:
BIG <- c(... |
# W knitrze jakos bezsensu ustawia sie filled.contour (legenda zajmuje 50% wykresu!)
# tutaj generuje te obrazki recznie.
pdfFnc = function(name)
{
par(mar = c(2,2,2,2))
pdf(sprintf("contours/%s.pdf",name), pointsize = 16)
}
pdfFnc("e1")
x = mvrnorm(200,c(0,0), cbind(c(1,0.8),c(0.8,1)))
depthContour(x, method = ... | /contoursPlots.R | no_license | zzawadz/DepthProc_PAZUR2014 | R | false | false | 1,282 | r | # W knitrze jakos bezsensu ustawia sie filled.contour (legenda zajmuje 50% wykresu!)
# tutaj generuje te obrazki recznie.
pdfFnc = function(name)
{
par(mar = c(2,2,2,2))
pdf(sprintf("contours/%s.pdf",name), pointsize = 16)
}
pdfFnc("e1")
x = mvrnorm(200,c(0,0), cbind(c(1,0.8),c(0.8,1)))
depthContour(x, method = ... |
# title: "Responding to analysis and communication: Data science the R way"
# subtitle: "DataTeka"
# author: "Tatjana Kecojevic"
# date: "26 April 2018"
# **Tip**💡:
# - When start working on a new R code/R Project in [RStudio IDE](https://support.rstudio.com/hc/en-us/sections/200107586-Using-the-RStudio-IDE) use
# *... | /Slides_Script_NoAnswers.R | no_license | TanjaKec/RWorkshop_xaringan | R | false | false | 6,555 | r | # title: "Responding to analysis and communication: Data science the R way"
# subtitle: "DataTeka"
# author: "Tatjana Kecojevic"
# date: "26 April 2018"
# **Tip**💡:
# - When start working on a new R code/R Project in [RStudio IDE](https://support.rstudio.com/hc/en-us/sections/200107586-Using-the-RStudio-IDE) use
# *... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/gen-namespace-docs.R,
% R/gen-namespace-examples.R
\name{torch_repeat_interleave}
\alias{torch_repeat_interleave}
\title{Repeat_interleave}
\arguments{
\item{input}{(Tensor) the input tensor.}
\item{repeats}{(Tensor or int) The number of r... | /man/torch_repeat_interleave.Rd | permissive | qykong/torch | R | false | true | 1,397 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/gen-namespace-docs.R,
% R/gen-namespace-examples.R
\name{torch_repeat_interleave}
\alias{torch_repeat_interleave}
\title{Repeat_interleave}
\arguments{
\item{input}{(Tensor) the input tensor.}
\item{repeats}{(Tensor or int) The number of r... |
#load libraries
library(quantreg)
library(glmnet)
library(magrittr)
library(purrr)
#load data
#data.half <- readRDS()
#full.data <- readRDS("/Users/Matt Multach/Dropbox/USC_Grad2/Courses/Dissertation/fulldata_091620.RData")
half.data <- readRDS("/Users/Matt Multach/Dropbox/USC_Grad2/Courses/Dissertation/500_data_10052... | /Model_Application/Full_Run/AdaLasso_500.R | no_license | multach87/Dissertation | R | false | false | 10,691 | r | #load libraries
library(quantreg)
library(glmnet)
library(magrittr)
library(purrr)
#load data
#data.half <- readRDS()
#full.data <- readRDS("/Users/Matt Multach/Dropbox/USC_Grad2/Courses/Dissertation/fulldata_091620.RData")
half.data <- readRDS("/Users/Matt Multach/Dropbox/USC_Grad2/Courses/Dissertation/500_data_10052... |
if (!require("pacman")) install.packages("pacman")
pacman::p_load(shinydashboard, plotly, fs, dplyr, stringr, lubridate, fs)
source("helper.R")
source("config.R")
# read dataframes and ALL resulting model objects as stored from model training as training data foundation
load("models/models.Rda")
# read metadata fr... | /server.R | no_license | justusfowl/ddmr | R | false | false | 7,889 | r |
if (!require("pacman")) install.packages("pacman")
pacman::p_load(shinydashboard, plotly, fs, dplyr, stringr, lubridate, fs)
source("helper.R")
source("config.R")
# read dataframes and ALL resulting model objects as stored from model training as training data foundation
load("models/models.Rda")
# read metadata fr... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/power_eeg_bands.R
\name{power_eeg_bands}
\alias{power_eeg_bands}
\title{Get power values for EEG bands}
\usage{
power_eeg_bands(
eeg_signal,
sampling_frequency = 125,
max_frequency = 32,
num_sec_w = 5,
aggreg_level = 6
)
}
\argument... | /man/power_eeg_bands.Rd | no_license | adigherman/EEGSpectralAnalysis | R | false | true | 1,159 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/power_eeg_bands.R
\name{power_eeg_bands}
\alias{power_eeg_bands}
\title{Get power values for EEG bands}
\usage{
power_eeg_bands(
eeg_signal,
sampling_frequency = 125,
max_frequency = 32,
num_sec_w = 5,
aggreg_level = 6
)
}
\argument... |
library(glmnet)
mydata = read.table("./TrainingSet/ReliefF/haematopoietic.csv",head=T,sep=",")
x = as.matrix(mydata[,4:ncol(mydata)])
y = as.matrix(mydata[,1])
set.seed(123)
glm = cv.glmnet(x,y,nfolds=10,type.measure="mse",alpha=0.05,family="gaussian",standardize=FALSE)
sink('./Model/EN/ReliefF/haematopoietic/haematopo... | /Model/EN/ReliefF/haematopoietic/haematopoietic_022.R | no_license | leon1003/QSMART | R | false | false | 377 | r | library(glmnet)
mydata = read.table("./TrainingSet/ReliefF/haematopoietic.csv",head=T,sep=",")
x = as.matrix(mydata[,4:ncol(mydata)])
y = as.matrix(mydata[,1])
set.seed(123)
glm = cv.glmnet(x,y,nfolds=10,type.measure="mse",alpha=0.05,family="gaussian",standardize=FALSE)
sink('./Model/EN/ReliefF/haematopoietic/haematopo... |
get_data <- function(url, zip_file, data_files, output_dir="./data")
{
if (!file.exists(output_dir))
dir.create(output_dir)
file_missing = FALSE
for (data_file in data_files)
{
if (!file.exists(data_file))
file_missing = TRUE
}
if (file_missing)
{
if (!file.exists(zip_file))
{
... | /get_data.R | no_license | cdated/JHUCleaningData | R | false | false | 500 | r | get_data <- function(url, zip_file, data_files, output_dir="./data")
{
if (!file.exists(output_dir))
dir.create(output_dir)
file_missing = FALSE
for (data_file in data_files)
{
if (!file.exists(data_file))
file_missing = TRUE
}
if (file_missing)
{
if (!file.exists(zip_file))
{
... |
#' Value and Circulation of Currency
#'
#' This dataset contains, for the smaller bill denominations, the value of the bill and the total value in circulation. The source for these data is \emph{The World Almanac and Book of Facts 2014}.
#'
#' @format A data frame with 5 rows and 3 variables:
#' \describe{
#' \item{B... | /R/data-Currency.R | no_license | cran/sur | R | false | false | 504 | r | #' Value and Circulation of Currency
#'
#' This dataset contains, for the smaller bill denominations, the value of the bill and the total value in circulation. The source for these data is \emph{The World Almanac and Book of Facts 2014}.
#'
#' @format A data frame with 5 rows and 3 variables:
#' \describe{
#' \item{B... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/aiplatform_objects.R
\name{GoogleCloudAiplatformV1ModelEvaluationSliceSlice}
\alias{GoogleCloudAiplatformV1ModelEvaluationSliceSlice}
\title{GoogleCloudAiplatformV1ModelEvaluationSliceSlice Object}
\usage{
GoogleCloudAiplatformV1ModelEvaluati... | /googleaiplatformv1.auto/man/GoogleCloudAiplatformV1ModelEvaluationSliceSlice.Rd | no_license | justinjm/autoGoogleAPI | R | false | true | 647 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/aiplatform_objects.R
\name{GoogleCloudAiplatformV1ModelEvaluationSliceSlice}
\alias{GoogleCloudAiplatformV1ModelEvaluationSliceSlice}
\title{GoogleCloudAiplatformV1ModelEvaluationSliceSlice Object}
\usage{
GoogleCloudAiplatformV1ModelEvaluati... |
helper <- function(data, outcome, num){
hospital <- data[, 2][order(outcome, data[, 2])[num]]
hospital
}
rankall <- function(outcome, num = "best") {
## Read outcome data
## Check that state and outcome are valid
## For each state, find the hospital of the given rank
## Return a data frame with the ho... | /coursera/compdata-004/Week3/rankall.R | no_license | wz125/course | R | false | false | 2,868 | r | helper <- function(data, outcome, num){
hospital <- data[, 2][order(outcome, data[, 2])[num]]
hospital
}
rankall <- function(outcome, num = "best") {
## Read outcome data
## Check that state and outcome are valid
## For each state, find the hospital of the given rank
## Return a data frame with the ho... |
#modified 7/25/21 to report factor scores so that we can use biplot on the exensions.\
"fa.extension" <-
function(Roe,fo,correct=TRUE) {
cl <- match.call()
omega <-FALSE
if(!is.null(class(fo)[2])) {if(inherits(fo,"fa")) {
if(!is.null(fo$Phi)) {Phi <- fo$Phi} else {Phi <- NULL}
fl <- f... | /R/fa.extension.R | no_license | cran/psych | R | false | false | 5,858 | r |
#modified 7/25/21 to report factor scores so that we can use biplot on the exensions.\
"fa.extension" <-
function(Roe,fo,correct=TRUE) {
cl <- match.call()
omega <-FALSE
if(!is.null(class(fo)[2])) {if(inherits(fo,"fa")) {
if(!is.null(fo$Phi)) {Phi <- fo$Phi} else {Phi <- NULL}
fl <- f... |
favstats(~ hand_width, data = Hand.null)
prop(~ (hand_width <= -6.756), data = Hand.null)
| /inst/snippets/Exploration10.4.6.R | no_license | rpruim/ISIwithR | R | false | false | 91 | r | favstats(~ hand_width, data = Hand.null)
prop(~ (hand_width <= -6.756), data = Hand.null)
|
#' Uji Varians 1 atau 2 Populasi
#'
#' Fungsi digunakan untuk menguji varians baik dari satu ataupun dua populasi
#'
#'
#' @param varsampel varians dari sampel (untuk 1 populasi langsung input nilai, untuk 2 populasi gunakan syntax c(), contoh: c(varsampel1, varsampel2))
#' @param nsampel jumlah sampel (untuk 1 populas... | /R/variance-test.R | no_license | yoursunshineR/statitest | R | false | false | 6,194 | r | #' Uji Varians 1 atau 2 Populasi
#'
#' Fungsi digunakan untuk menguji varians baik dari satu ataupun dua populasi
#'
#'
#' @param varsampel varians dari sampel (untuk 1 populasi langsung input nilai, untuk 2 populasi gunakan syntax c(), contoh: c(varsampel1, varsampel2))
#' @param nsampel jumlah sampel (untuk 1 populas... |
library(ggplot2)
library(twitteR)
library(stringr)
library(wordcloud)
# harvest tweets from each user
epa_tweets = userTimeline("EPAgov", n=500)
nih_tweets = userTimeline("NIHforHealth", n=500)
cdc_tweets = userTimeline("CDCgov", n=500)
# dump tweets information into data frames
epa_df = twListToDF(epa_tweets)
nih_df ... | /twitteR.R | no_license | rtremeaud/code-r | R | false | false | 376 | r | library(ggplot2)
library(twitteR)
library(stringr)
library(wordcloud)
# harvest tweets from each user
epa_tweets = userTimeline("EPAgov", n=500)
nih_tweets = userTimeline("NIHforHealth", n=500)
cdc_tweets = userTimeline("CDCgov", n=500)
# dump tweets information into data frames
epa_df = twListToDF(epa_tweets)
nih_df ... |
#! /usr/bin/env Rscript
## Extract background ADT signal from empty droplets
# using empty droplets from GEX libraries
# subtract background estimated from a 2-component mixture model
# ------- arg parsing ----------
library(optparse)
parser <- OptionParser()
parser <- add_option(parser, c("-x", "--matrixlist"), ty... | /src/bgshift_cpm.R | no_license | MarioniLab/CovidPBMC | R | false | false | 8,363 | r | #! /usr/bin/env Rscript
## Extract background ADT signal from empty droplets
# using empty droplets from GEX libraries
# subtract background estimated from a 2-component mixture model
# ------- arg parsing ----------
library(optparse)
parser <- OptionParser()
parser <- add_option(parser, c("-x", "--matrixlist"), ty... |
# Install required packages -----------------------------------------------
install.packages("forecast")
install.packages("fpp")
install.packages("ggplot2")
# load those packages to the current session ------------------------------
library(ggplot2)
library(forecast)
library(fpp) # get a dataset to work with from 'f... | /6. labs1/Week 8/Time_Series_Lab.R | no_license | wendy-wong/WENDY_DATA_PROJECT | R | false | false | 3,818 | r |
# Install required packages -----------------------------------------------
install.packages("forecast")
install.packages("fpp")
install.packages("ggplot2")
# load those packages to the current session ------------------------------
library(ggplot2)
library(forecast)
library(fpp) # get a dataset to work with from 'f... |
## Test code for Normalization + transformation
x <- rnorm(1000)
y <- rnorm(1000)
z <- rnorm(1000)
site <- rep_len(0.69, 1000)
test.data <- data.frame(x,y,z, site)
gen_config()
test_that("Check normalization, denormalization",{
std.data <- standardize_all(test.data)
expect_true(all(std.data$site == 0.69))
## ... | /tests/testthat/test_standardize.R | no_license | NSAPH/airpred | R | false | false | 479 | r | ## Test code for Normalization + transformation
x <- rnorm(1000)
y <- rnorm(1000)
z <- rnorm(1000)
site <- rep_len(0.69, 1000)
test.data <- data.frame(x,y,z, site)
gen_config()
test_that("Check normalization, denormalization",{
std.data <- standardize_all(test.data)
expect_true(all(std.data$site == 0.69))
## ... |
library(dplyr)
library(rnaturalearth)
library(sf)
library(sp)
library(raster)
library(rgdal)
library(RStoolbox)
select = dplyr::select
#----Making spatial extent----
# making a function for coordinates() w/in a pipe
coordinates_iP = function(spdf){
coordinates(spdf) = ~long+lat
return(spdf)
}
df = expand.grid(da... | /CompileGIS/RasterCoRegister.R | permissive | GatesDupont/Jaguars | R | false | false | 2,067 | r | library(dplyr)
library(rnaturalearth)
library(sf)
library(sp)
library(raster)
library(rgdal)
library(RStoolbox)
select = dplyr::select
#----Making spatial extent----
# making a function for coordinates() w/in a pipe
coordinates_iP = function(spdf){
coordinates(spdf) = ~long+lat
return(spdf)
}
df = expand.grid(da... |
pacman::p_load(tidyverse, magrittr, data.table, janitor, readxl)
input =
"Legislatives 2022/resultats-par-niveau-burvot-t1-france-entiere.xlsx" %>%
readxl::read_excel()
input %<>% janitor::clean_names()
input %<>% rowid_to_column()
CLINNE <- function(data) {
names(data) = c("rowid", "candidat", "voix")
retu... | /Legislatives 2022/Fetch_data_bdv.R | no_license | Reinaldodos/Elections | R | false | false | 907 | r | pacman::p_load(tidyverse, magrittr, data.table, janitor, readxl)
input =
"Legislatives 2022/resultats-par-niveau-burvot-t1-france-entiere.xlsx" %>%
readxl::read_excel()
input %<>% janitor::clean_names()
input %<>% rowid_to_column()
CLINNE <- function(data) {
names(data) = c("rowid", "candidat", "voix")
retu... |
#Загрузите данные в датафрейм. Адрес: github https://raw???путь_к_файлу_найдите_сами???/data/gmp.dat
gmp <- read.table("https://raw.githubusercontent.com/SergeyMirvoda/MD-DA-2018/master/data/gmp.dat", skip = 1)
names(gmp) <- c("ID", "MSA", "gmp", "pcgmp")
gmp$pop <- gmp$gmp/gmp$pcgmp
# Функция, высчитывающая коэффи... | /classwork4/gmp.R | no_license | normall777/MyDataAccessMethods | R | false | false | 5,406 | r | #Загрузите данные в датафрейм. Адрес: github https://raw???путь_к_файлу_найдите_сами???/data/gmp.dat
gmp <- read.table("https://raw.githubusercontent.com/SergeyMirvoda/MD-DA-2018/master/data/gmp.dat", skip = 1)
names(gmp) <- c("ID", "MSA", "gmp", "pcgmp")
gmp$pop <- gmp$gmp/gmp$pcgmp
# Функция, высчитывающая коэффи... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/visualizer.R
\name{clade.anno}
\alias{clade.anno}
\title{clade.anno}
\usage{
clade.anno(gtree, anno.data, alpha = 0.2, anno.depth = 3, anno.x = 10,
anno.y = 40)
}
\arguments{
\item{gtree}{a ggtree object}
\item{anno.data}{a 2 column data.f... | /man/clade.anno.Rd | no_license | zhuchcn/microbiomeViz | R | false | true | 756 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/visualizer.R
\name{clade.anno}
\alias{clade.anno}
\title{clade.anno}
\usage{
clade.anno(gtree, anno.data, alpha = 0.2, anno.depth = 3, anno.x = 10,
anno.y = 40)
}
\arguments{
\item{gtree}{a ggtree object}
\item{anno.data}{a 2 column data.f... |
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