id stringlengths 40 40 | repo_name stringlengths 5 110 | path stringlengths 2 233 | content stringlengths 0 1.03M ⌀ | size int32 0 60M ⌀ | license stringclasses 15
values |
|---|---|---|---|---|---|
31ea9fcd32a4abbe86e6955e8439ecbc1ab20520 | chendaniely/multidisciplinary-diffusion-model-experiments | staging/recurrent/src/helper-goodness.R | ################################################################################
#
# Goodness calculation functions
#
################################################################################
get_input_i <- function(unit_number){
input <- 0
return(input)
}
get_bias_i <- function(i_j_index_number){
b... | 2,494 | mit |
e22f543b37e4be7ccff548b5b2cf69d75c4c16b3 | Monash-RNA-Systems-Biology-Laboratory/patseqers | Shiny_tutorial/helper.R | # Generates a data frame of random numbers
make_df <- function(number_of_points){
x <- rnorm(number_of_points, mean = 20, sd = 5)
y <- rnorm(number_of_points, mean = 50, sd = 50)
df <- data.frame(x,y)
return(df)
}
| 251 | gpl-2.0 |
b4681f5d4cccf3c2e7478898ef64c0940770a574 | bwilbertz/kaggle_allen_ai | R/runFullModelPipeline.R | # The MIT License (MIT)
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, subl... | 1,547 | mit |
849f3460ee05af84e210dd8c74a1ce45cc189065 | eclee25/flu-SDI-exploratory-age | mapping_code/zipcode_maps_R_code/map-zipcodes_ECLedit.R | ## Name: Elizabeth Lee
## Date: 7/19/13
## Function:
### 1. draw OR map per season, popsize as bubble size
### 1b. draw log(OR map) per season 7/31/13, popsize as bubble size
### 1c. draw OR map per season, incidence as bubble size
### 2. draw incidence map per season
### 3) incidence maps by week 7/23/13
## Note: nee... | 42,043 | mit |
a3b9adf94893b3719f72a2540819286d0145e061 | nextgenusfs/amptk | amptk/check_version.R | #!/usr/bin/env Rscript
is.installed <- function(mypkg){
is.element(mypkg, installed.packages()[,1])
}
Rversion <- R.Version()$version.string
if (!is.installed("dada2")){
dadaversion <- '0.0.0'
} else {
dadaversion <- packageVersion("dada2")
}
if (!is.installed("phyloseq")){
phyloseqversion <- '0.0.0'
... | 645 | bsd-2-clause |
e18dbca9e8c5d29c051cdf7f720c4babd14c660a | Tutuchan/morrisjs | R/morrisjs.R | #' morris.js plot
#'
#' This function prepares the widget to be drawn.
#'
#' In the case of a \code{data.frame} or a \code{tbl_df}, the first column must
#' be a object that can be interpreted as a \code{Data}, the other columns being
#' the data values.
#'
#' @param data the data to be drawn, can be a \code{ts}, \c... | 1,751 | mit |
a3b9adf94893b3719f72a2540819286d0145e061 | nextgenusfs/ufits | amptk/check_version.R | #!/usr/bin/env Rscript
is.installed <- function(mypkg){
is.element(mypkg, installed.packages()[,1])
}
Rversion <- R.Version()$version.string
if (!is.installed("dada2")){
dadaversion <- '0.0.0'
} else {
dadaversion <- packageVersion("dada2")
}
if (!is.installed("phyloseq")){
phyloseqversion <- '0.0.0'
... | 645 | bsd-2-clause |
c0900916ad10eaaf2acb8707ce3fde8d6294d5c9 | andymememe/datasciencecoursera | R Programming/makepower.R | make.power <- function(n) {
pow <- function (x) {
x ^ n
}
pow
} | 73 | gpl-2.0 |
74a3a14eb41cec2ddaf4fcc310849e749244c614 | SMHendryx/quantifyBiomassFromPointClouds | R/watershedSegmentTrees.R | # Script segments a point cloud into clusters using watershed segmentation on rasterized point cloud
# Clear workspace:
rm(list=ls())
library(lidR)
library(feather)
library(data.table)
#terminal output coloring
library(crayon)
error <- red $ bold
warn <- magenta $ underline
note <- cyan
#cat(error("Error: subscript o... | 3,011 | gpl-3.0 |
dd2bd46f4e6d1172285b0e9f0bfe588705613428 | andrewdefries/andrewdefries.github.io | FDA_Pesticide_Glossary/CMU.R | library("knitr")
library("rgl")
#knit("CMU.Rmd")
#markdownToHTML('CMU.md', 'CMU.html', options=c("use_xhml"))
#system("pandoc -s CMU.html -o CMU.pdf")
knit2html('CMU.Rmd')
| 174 | mit |
263ffbd199b804c501306857ec77c01624ef8651 | amschwinn/data_mining_lab | Lab 1/Schwinn_DataMining_Lab_1_Ex2.R | #############################
#Data Mining Practical Session
#Lab 1 Exercise 2
#
#Subject: Clustering with Iris Dataset.
#K-Means & Heirarchial Clustering
#
#Author: Austin Schwinn
#
#Jan 17, 2017
#############################
#install.packages('rstudioapi')
library(rstudioapi)
#Set working directory
setwd(dirname(... | 1,510 | mit |
cadfe7ab0699d8f30e3e85674ab4e70336aef4e2 | PFgimenez/PhD | R-files/data_renault_small_header.R | library(ggplot2)
#--------------------------------------------------------------------------------------------
#Parametres globaux
dataset_name = "renault_small_header"
taille_img_x = 1024/2
taille_img_y = 720/2
#fin parametres globaux
#----------------------------------------------------------------------------------... | 58,938 | gpl-3.0 |
cadfe7ab0699d8f30e3e85674ab4e70336aef4e2 | PFgimenez/thesis | R-files/data_renault_small_header.R | library(ggplot2)
#--------------------------------------------------------------------------------------------
#Parametres globaux
dataset_name = "renault_small_header"
taille_img_x = 1024/2
taille_img_y = 720/2
#fin parametres globaux
#----------------------------------------------------------------------------------... | 58,938 | gpl-3.0 |
29c062e99ea01825f3faf03a4bc83ed93dbb4827 | rho-devel/rho | src/extra/testr/filtered-test-suite/format/tc_format_34.R | expected <- eval(parse(text="structure(c(\"213198964\", \" 652425\"), .Names = c(\"null.deviance\", \"deviance\"))"));
test(id=0, code={
argv <- eval(parse(text="list(structure(c(213198964, 652424.52183908), .Names = c(\"null.deviance\", \"deviance\")), FALSE, 5L, 0L, NULL, 3L, TRUE, NA)")); ... | 479 | gpl-2.0 |
c710fd01f5b72f465ccba907066bc88f2fd967de | realviacauchy/shiny-court-grapher | reports/TDO_Qtrly_Long_FY08-FY15_PLOT.R | ##################
# Draws quarterly graph of adult TDOs from eMagistrate data
# One line, with fiscal quarters on the x axis and counts on the y axis
##################
#source("reports/emagistrate_prep.R")
library(dplyr)
library(pander)
library(ggplot2)
TDO <-
emags %>%
filter(Type=="TDO", FYear>2007)
TDO_Qtr... | 1,149 | mit |
29c062e99ea01825f3faf03a4bc83ed93dbb4827 | cxxr-devel/cxxr | src/extra/testr/filtered-test-suite/format/tc_format_34.R | expected <- eval(parse(text="structure(c(\"213198964\", \" 652425\"), .Names = c(\"null.deviance\", \"deviance\"))"));
test(id=0, code={
argv <- eval(parse(text="list(structure(c(213198964, 652424.52183908), .Names = c(\"null.deviance\", \"deviance\")), FALSE, 5L, 0L, NULL, 3L, TRUE, NA)")); ... | 479 | gpl-2.0 |
c710fd01f5b72f465ccba907066bc88f2fd967de | zhuoaprilfu/demo_fork | reports/TDO_Qtrly_Long_FY08-FY15_PLOT.R | ##################
# Draws quarterly graph of adult TDOs from eMagistrate data
# One line, with fiscal quarters on the x axis and counts on the y axis
##################
#source("reports/emagistrate_prep.R")
library(dplyr)
library(pander)
library(ggplot2)
TDO <-
emags %>%
filter(Type=="TDO", FYear>2007)
TDO_Qtr... | 1,149 | mit |
c710fd01f5b72f465ccba907066bc88f2fd967de | zhuoaprilfu/shiny-court-grapher | reports/TDO_Qtrly_Long_FY08-FY15_PLOT.R | ##################
# Draws quarterly graph of adult TDOs from eMagistrate data
# One line, with fiscal quarters on the x axis and counts on the y axis
##################
#source("reports/emagistrate_prep.R")
library(dplyr)
library(pander)
library(ggplot2)
TDO <-
emags %>%
filter(Type=="TDO", FYear>2007)
TDO_Qtr... | 1,149 | mit |
29c062e99ea01825f3faf03a4bc83ed93dbb4827 | kmillar/cxxr | src/extra/testr/filtered-test-suite/format/tc_format_34.R | expected <- eval(parse(text="structure(c(\"213198964\", \" 652425\"), .Names = c(\"null.deviance\", \"deviance\"))"));
test(id=0, code={
argv <- eval(parse(text="list(structure(c(213198964, 652424.52183908), .Names = c(\"null.deviance\", \"deviance\")), FALSE, 5L, 0L, NULL, 3L, TRUE, NA)")); ... | 479 | gpl-2.0 |
8a4578e2cbad84471373f96e3bb8e75bfca317a9 | ADIRSE/maddata | app/global_functions.R |
#######################
# GLOBAL FUNCS
#######################
# load air quality measure points
fixStationCodes <- function(code) {
# code <- as.character(code)
if (code<10) {
station_code <- paste('2807900',
code, sep='')
}
else {
station_code <- past... | 7,213 | mit |
29c062e99ea01825f3faf03a4bc83ed93dbb4827 | ArunChauhan/cxxr | src/extra/testr/filtered-test-suite/format/tc_format_34.R | expected <- eval(parse(text="structure(c(\"213198964\", \" 652425\"), .Names = c(\"null.deviance\", \"deviance\"))"));
test(id=0, code={
argv <- eval(parse(text="list(structure(c(213198964, 652424.52183908), .Names = c(\"null.deviance\", \"deviance\")), FALSE, 5L, 0L, NULL, 3L, TRUE, NA)")); ... | 479 | gpl-2.0 |
29c062e99ea01825f3faf03a4bc83ed93dbb4827 | kmillar/rho | src/extra/testr/filtered-test-suite/format/tc_format_34.R | expected <- eval(parse(text="structure(c(\"213198964\", \" 652425\"), .Names = c(\"null.deviance\", \"deviance\"))"));
test(id=0, code={
argv <- eval(parse(text="list(structure(c(213198964, 652424.52183908), .Names = c(\"null.deviance\", \"deviance\")), FALSE, 5L, 0L, NULL, 3L, TRUE, NA)")); ... | 479 | gpl-2.0 |
5d622a1e4f8df46cbb031e94bf5701f6dbf5edc7 | chichinabo/popyramids_shiny_apps | apps/resources/auto_check_and_install.R | #A short script to help installing packages on the go
#Most useful if you are distributing a set of script files to people who may not be aware that the needed packages are not installed
#Also useful if you use many packages and want to organise their loading at the beginning of a script
need<-c("shiny", "shinydashboa... | 754 | gpl-3.0 |
5d622a1e4f8df46cbb031e94bf5701f6dbf5edc7 | chichinabo/shiny_popyramids | apps/resources/auto_check_and_install.R | #A short script to help installing packages on the go
#Most useful if you are distributing a set of script files to people who may not be aware that the needed packages are not installed
#Also useful if you use many packages and want to organise their loading at the beginning of a script
need<-c("shiny", "shinydashboa... | 754 | gpl-3.0 |
29c062e99ea01825f3faf03a4bc83ed93dbb4827 | krlmlr/cxxr | src/extra/testr/filtered-test-suite/format/tc_format_34.R | expected <- eval(parse(text="structure(c(\"213198964\", \" 652425\"), .Names = c(\"null.deviance\", \"deviance\"))"));
test(id=0, code={
argv <- eval(parse(text="list(structure(c(213198964, 652424.52183908), .Names = c(\"null.deviance\", \"deviance\")), FALSE, 5L, 0L, NULL, 3L, TRUE, NA)")); ... | 479 | gpl-2.0 |
9af149866568158694b0fb109721e6b128f6f663 | cxxr-devel/cxxr-svn-mirror | src/library/stats/R/ppr.R | # File src/library/stats/R/ppr.R
# Part of the R package, http://www.R-project.org
#
# Copyright (C) 1998 B. D. Ripley
# Copyright (C) 2000-12 The R Core Team
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free... | 6,929 | gpl-2.0 |
9af149866568158694b0fb109721e6b128f6f663 | glycerine/bigbird | r-3.0.2/src/library/stats/R/ppr.R | # File src/library/stats/R/ppr.R
# Part of the R package, http://www.R-project.org
#
# Copyright (C) 1998 B. D. Ripley
# Copyright (C) 2000-12 The R Core Team
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free... | 6,929 | bsd-2-clause |
f27dff1e9c5600ef69ad527852fcbad68ac143ad | sc-camp/2016-R-data-analysis | course_data_modeling/courses/Mod_8_mixed_mods/Mixed effects models.R | #Mixed effects models
#AdvInR
#Script developed by Nils Bunnefeld, and modified by Luc Bussière November 2014
# clear workspace
rm(list=ls())
# analysis of grouse
# import data file
GROUSE<-read.csv("grouse_shooting_mod.csv")
str(GROUSE)
# first will want to divide nr_shot by drive size to facilitate contrasts
GROU... | 10,963 | gpl-3.0 |
b4e8232ce9a45f411ea82f491da7548a69152464 | vinhqdang/my_mooc | MOOC-work/coursera/FINISHED/compdata-004 Computing for Data Analysis/Coursera-Computing-for-Data-Analysis-master/Week3/Assignment3.R | # Part 1
outcome <- read.csv(file="/.../data/outcome-of-care-measures.csv", colClasses = "character")
# "..." is the directory in your computer; masked here for privacy
head(outcome)
names(outcome)
outcome[, 11] <- as.numeric(outcome[, 11])
hist(outcome[, 11], xlab="30-day Dearth Rate", main="Heart Attack 30-day Death ... | 3,251 | mit |
515fe2e7bfb53872808761cc68b8fe1c0a089df8 | cxxr-devel/cxxr-svn-mirror | src/library/Recommended/Matrix/R/lsCMatrix.R | #### Logical Symmetric Sparse Matrices in Compressed column-oriented format
### contains = "lsparseMatrix"
setAs("lsCMatrix", "matrix",
function(from) as(as(from, "generalMatrix"), "matrix"))
setAs("lsCMatrix", "lgCMatrix",
function(from) .Call(Csparse_symmetric_to_general, from))
## needed for indexing... | 2,155 | gpl-2.0 |
3083df7c840fe797c50f376957c908c0c7cb00c5 | sjbonner/Truncated_CJS | TruncatedCJS/R/simulate_ms.R | simulateMS <- function(nstate,u,T,phi,p,debug=FALSE){
if(debug)
browser()
## Generate complete state matrix
Wfull <- sapply(1:(T-1),function(t){
Wfull.tmp <- matrix(NA,sum(u[,t]),T)
Wfull.tmp[,t] <- rep(1:nstate,u[,t])
for(s in t:(T-1)){
for(m in 1:n... | 1,240 | gpl-3.0 |
5c6604e62c883df04b4c1f172f3211e1b5f876c7 | freestone-lab/TSLibrary | TSExperiment/R/old_tsexperiment.R | ##TODO(David): TSprotocol should attach a specific protocol to a subject/session
#
## Note all outward facing functions take input as Data, all inward facing functions
## take input as df.
#
##' Workhorse for creating and updating a TSExperiment
##'
##' @param ExperimentPath The path to the experiment folder
##' @param... | 15,510 | mit |
d7a7a36ef05138fb86d705f79b430449b66fbb85 | SchlossLab/Sze_FollowUps_Microbiome_2017 | code/srn/srn_run_36_RF.R | ### Build the best lesion model possible
### Try XG-Boost, RF, Logit (GLM), C5.0, SVM
### Find the best based on Jenna Wiens suggestions on test and training
## Marc Sze
#Load needed libraries
source('code/functions.R')
loadLibs(c("dplyr", "caret","scales", "doMC"))
load("exploratory/srn_RF_model_setup.RDa... | 1,758 | mit |
02fe2ac01b2df3fa0ed87b8810834402cfbcf554 | KellyBlack/R-Object-Oriented-Programming | chapter12/monteCarloS3.R |
######################################################################
# Create the Monte Carlo class
#
# This class is used to make many simulations
MonteCarlo <- function()
{
# Define the slots
me = list(
## First define the parameters for the stochastic model
N = 0,
T ... | 5,248 | mit |
69e851e89c73fc9f2bb94f65f29138769e4df026 | zedoul/buildEssential | R/buildr.R | #' Get packages
#'
#' @param description_path a file path of DESCRIPTION
#' @importFrom desc desc_get_deps
#' @importFrom yaml yaml.load_file
get_packages <- function(description_path) {
stopifnot(file.exists(description_path))
# Do not consider miniCRAN::getCranDescription function, since this function
# should... | 2,435 | mit |
8b6cc736b0a4854f6aad575aff47792a3c844fd4 | ChiWang/r-source | src/library/stats/R/arima.R | # File src/library/stats/R/arima.R
# Part of the R package, http://www.R-project.org
#
# Copyright (C) 2002-2015 The R Core Team
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either ve... | 18,997 | gpl-2.0 |
20769a023b830ddef7c35ab7c099b5ac260e9f87 | yufree/democode | plot/mass.R | source("http://bioconductor.org/biocLite.R")
biocLite("mzR")
library(mzR)
all <- openMSfile('./FULL200.CDF')
df <- header(all)
bb <- peaks(all)
aaaa <- sapply(bb,as.data.frame)
oddvals <- seq(1, ncol(aaaa), by=2)
aaaaa <- unlist(aaaa[oddvals])
ccc <- unique(c(aaaaa))
ccc <- ccc[order(ccc)]
# bbb <- sapply(b... | 1,185 | mit |
8b6cc736b0a4854f6aad575aff47792a3c844fd4 | jagdeesh109/RRO | R-src/src/library/stats/R/arima.R | # File src/library/stats/R/arima.R
# Part of the R package, http://www.R-project.org
#
# Copyright (C) 2002-2015 The R Core Team
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either ve... | 18,997 | gpl-2.0 |
8b6cc736b0a4854f6aad575aff47792a3c844fd4 | limeng12/r-source | src/library/stats/R/arima.R | # File src/library/stats/R/arima.R
# Part of the R package, http://www.R-project.org
#
# Copyright (C) 2002-2015 The R Core Team
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either ve... | 18,997 | gpl-2.0 |
20769a023b830ddef7c35ab7c099b5ac260e9f87 | jpgroup/democode | plot/mass.R | source("http://bioconductor.org/biocLite.R")
biocLite("mzR")
library(mzR)
all <- openMSfile('./FULL200.CDF')
df <- header(all)
bb <- peaks(all)
aaaa <- sapply(bb,as.data.frame)
oddvals <- seq(1, ncol(aaaa), by=2)
aaaaa <- unlist(aaaa[oddvals])
ccc <- unique(c(aaaaa))
ccc <- ccc[order(ccc)]
# bbb <- sapply(b... | 1,185 | mit |
8b6cc736b0a4854f6aad575aff47792a3c844fd4 | hadley/r-source | src/library/stats/R/arima.R | # File src/library/stats/R/arima.R
# Part of the R package, http://www.R-project.org
#
# Copyright (C) 2002-2015 The R Core Team
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either ve... | 18,997 | gpl-2.0 |
b15aa7e269200525f9dc0ef7208abbcc33437c48 | Monash-RNA-Systems-Biology-Laboratory/patseqers | adele/dev_timepoint_app/ui.R | library(shiny)
source("helper.R")
shinyUI(pageWithSidebar(
headerPanel(h3("Changes in gene expression after C.albicans infection")),
sidebarPanel(
selectInput("select.experiment", label = "Select experiment",
choices = list.dirs(full.names=F, recursive =F),
selected =... | 1,746 | gpl-2.0 |
feb4037aed2d3e385f3bda1e581e3c02520b9716 | uzh/ezRun | script/debug-bwa.R | # p2578
setwd("/scratch/gtan/debug/quickDebug")
library(ezRun)
param = list()
param[['cores']] = '8'
param[['ram']] = '16'
param[['scratch']] = '100'
param[['node']] = ''
param[['process_mode']] = 'SAMPLE'
param[['samples']] = 'C8102P,C5401P,C6701P,C8902-7P,C8301P'
param[['refBuild']] = 'Homo_sapiens/Ensembl/GRCh38.p10... | 2,964 | gpl-3.0 |
a539dc810a518e58cf0368de42f854b0040d960e | debarros/CSIAccountabilityWkbk | crdc.R | #crdc.R
# This prepares data for the CRDC (Civil Rights Data Collection)
BEDSday = BedsDate(year = 2017)
EndDay = schoolYear(x = "end", y = BEDSday) - 29
# Read in the last Student Lite file from the relevant year
StudentLiteExtract = read.csv(file = file.choose(), header = F, stringsAsFactors = F)
colnames(StudentL... | 4,087 | gpl-3.0 |
03eda555017ea544b50990732518082e4c9fd391 | shraddhapai/Rutils | makeColorLighter.R | # #########################################
# makeColorLighter.R
# An R utility to make an RGB colour lighter. Useful in situations where we want to
# plot a lighter confidence interval band across the mean trendline of a dataseries.
#
# Requires: hsv2rgb.R also part of Rcolorutil
#
# Example usage:
# > pal <- c("#D7... | 1,728 | gpl-3.0 |
bb3fa6fc52d8070e846e3b8d52c7afa20ea8bc38 | rigreco/Runge-Kutta-Simulation | AppleX/GRAPHICS/DXBLOCK.R | null | 1,024 | gpl-3.0 |
80434261e701646071de7e79686f821a526936a7 | andeek/conclique-gibbs-sampler | simulation/big-network/DSATUR.R | getNColors <- function(x) {
if (is(x, "matrix")) {
adj_mat <- x
diag(adj_mat) <- FALSE
} else if (is(x, "SpatialPolygons")) {
adj_mat <- getAM(x)
} else {
stop("x must be an adjacency matrix or a SpatialPolygons* object.")
}
nColors <- length(unique(dsatur(adj_mat)))
return(nColors... | 5,249 | gpl-3.0 |
b513e4ecbab9a10ddfc2b80b99d94caf2b8c7c1c | malachig/genome | lib/perl/Genome/Model/Tools/R/CallR.pm.U_test.R | ########################################
######## Draw Copy Number Graph ########
########################################
utest <- function(name1=NULL,name2=NULL,nameAll=NULL,normalize=0,normalizedFile=NULL){
############################ read data ##############################
data1 <- read.table(name1,sep='\t')
... | 789 | lgpl-3.0 |
b513e4ecbab9a10ddfc2b80b99d94caf2b8c7c1c | dufeiyu/genome | lib/perl/Genome/Model/Tools/R/CallR.pm.U_test.R | ########################################
######## Draw Copy Number Graph ########
########################################
utest <- function(name1=NULL,name2=NULL,nameAll=NULL,normalize=0,normalizedFile=NULL){
############################ read data ##############################
data1 <- read.table(name1,sep='\t')
... | 789 | lgpl-3.0 |
b513e4ecbab9a10ddfc2b80b99d94caf2b8c7c1c | genome/genome | lib/perl/Genome/Model/Tools/R/CallR.pm.U_test.R | ########################################
######## Draw Copy Number Graph ########
########################################
utest <- function(name1=NULL,name2=NULL,nameAll=NULL,normalize=0,normalizedFile=NULL){
############################ read data ##############################
data1 <- read.table(name1,sep='\t')
... | 789 | lgpl-3.0 |
b513e4ecbab9a10ddfc2b80b99d94caf2b8c7c1c | gatoravi/genome | lib/perl/Genome/Model/Tools/R/CallR.pm.U_test.R | ########################################
######## Draw Copy Number Graph ########
########################################
utest <- function(name1=NULL,name2=NULL,nameAll=NULL,normalize=0,normalizedFile=NULL){
############################ read data ##############################
data1 <- read.table(name1,sep='\t')
... | 789 | lgpl-3.0 |
b68c3075f75d204aa26d808b5ce7a6d5879ec0f9 | cran/eqtl | R/drop.peakfeat.R | #####################################################################
#
# drop.peakfeat.R
#
# copyright (c) 2008-3, Ahmid A Khalili
#
# last modified Jul, 2008
# first written Mar, 2008
# Licensed under the GNU General Public License version 2 (June, 1991)
#
# Part of the R/eqtl package
# Contains: drop.peakfeat
#
##... | 1,534 | gpl-2.0 |
b513e4ecbab9a10ddfc2b80b99d94caf2b8c7c1c | ahwagner/genome | lib/perl/Genome/Model/Tools/R/CallR.pm.U_test.R | ########################################
######## Draw Copy Number Graph ########
########################################
utest <- function(name1=NULL,name2=NULL,nameAll=NULL,normalize=0,normalizedFile=NULL){
############################ read data ##############################
data1 <- read.table(name1,sep='\t')
... | 789 | lgpl-3.0 |
b513e4ecbab9a10ddfc2b80b99d94caf2b8c7c1c | kkrysiak/genome | lib/perl/Genome/Model/Tools/R/CallR.pm.U_test.R | ########################################
######## Draw Copy Number Graph ########
########################################
utest <- function(name1=NULL,name2=NULL,nameAll=NULL,normalize=0,normalizedFile=NULL){
############################ read data ##############################
data1 <- read.table(name1,sep='\t')
... | 789 | lgpl-3.0 |
b513e4ecbab9a10ddfc2b80b99d94caf2b8c7c1c | jasonwalker80/genome | lib/perl/Genome/Model/Tools/R/CallR.pm.U_test.R | ########################################
######## Draw Copy Number Graph ########
########################################
utest <- function(name1=NULL,name2=NULL,nameAll=NULL,normalize=0,normalizedFile=NULL){
############################ read data ##############################
data1 <- read.table(name1,sep='\t')
... | 789 | lgpl-3.0 |
b513e4ecbab9a10ddfc2b80b99d94caf2b8c7c1c | indraniel/genome | lib/perl/Genome/Model/Tools/R/CallR.pm.U_test.R | ########################################
######## Draw Copy Number Graph ########
########################################
utest <- function(name1=NULL,name2=NULL,nameAll=NULL,normalize=0,normalizedFile=NULL){
############################ read data ##############################
data1 <- read.table(name1,sep='\t')
... | 789 | lgpl-3.0 |
b513e4ecbab9a10ddfc2b80b99d94caf2b8c7c1c | ebelter/genome | lib/perl/Genome/Model/Tools/R/CallR.pm.U_test.R | ########################################
######## Draw Copy Number Graph ########
########################################
utest <- function(name1=NULL,name2=NULL,nameAll=NULL,normalize=0,normalizedFile=NULL){
############################ read data ##############################
data1 <- read.table(name1,sep='\t')
... | 789 | lgpl-3.0 |
b513e4ecbab9a10ddfc2b80b99d94caf2b8c7c1c | ernfrid/genome | lib/perl/Genome/Model/Tools/R/CallR.pm.U_test.R | ########################################
######## Draw Copy Number Graph ########
########################################
utest <- function(name1=NULL,name2=NULL,nameAll=NULL,normalize=0,normalizedFile=NULL){
############################ read data ##############################
data1 <- read.table(name1,sep='\t')
... | 789 | lgpl-3.0 |
b513e4ecbab9a10ddfc2b80b99d94caf2b8c7c1c | susannasiebert/genome | lib/perl/Genome/Model/Tools/R/CallR.pm.U_test.R | ########################################
######## Draw Copy Number Graph ########
########################################
utest <- function(name1=NULL,name2=NULL,nameAll=NULL,normalize=0,normalizedFile=NULL){
############################ read data ##############################
data1 <- read.table(name1,sep='\t')
... | 789 | lgpl-3.0 |
b513e4ecbab9a10ddfc2b80b99d94caf2b8c7c1c | chrisamiller/genome | lib/perl/Genome/Model/Tools/R/CallR.pm.U_test.R | ########################################
######## Draw Copy Number Graph ########
########################################
utest <- function(name1=NULL,name2=NULL,nameAll=NULL,normalize=0,normalizedFile=NULL){
############################ read data ##############################
data1 <- read.table(name1,sep='\t')
... | 789 | lgpl-3.0 |
b513e4ecbab9a10ddfc2b80b99d94caf2b8c7c1c | tmooney/genome | lib/perl/Genome/Model/Tools/R/CallR.pm.U_test.R | ########################################
######## Draw Copy Number Graph ########
########################################
utest <- function(name1=NULL,name2=NULL,nameAll=NULL,normalize=0,normalizedFile=NULL){
############################ read data ##############################
data1 <- read.table(name1,sep='\t')
... | 789 | lgpl-3.0 |
b513e4ecbab9a10ddfc2b80b99d94caf2b8c7c1c | iferguson90/genome | lib/perl/Genome/Model/Tools/R/CallR.pm.U_test.R | ########################################
######## Draw Copy Number Graph ########
########################################
utest <- function(name1=NULL,name2=NULL,nameAll=NULL,normalize=0,normalizedFile=NULL){
############################ read data ##############################
data1 <- read.table(name1,sep='\t')
... | 789 | lgpl-3.0 |
b513e4ecbab9a10ddfc2b80b99d94caf2b8c7c1c | mkiwala/genome | lib/perl/Genome/Model/Tools/R/CallR.pm.U_test.R | ########################################
######## Draw Copy Number Graph ########
########################################
utest <- function(name1=NULL,name2=NULL,nameAll=NULL,normalize=0,normalizedFile=NULL){
############################ read data ##############################
data1 <- read.table(name1,sep='\t')
... | 789 | lgpl-3.0 |
b513e4ecbab9a10ddfc2b80b99d94caf2b8c7c1c | brummett/genome | lib/perl/Genome/Model/Tools/R/CallR.pm.U_test.R | ########################################
######## Draw Copy Number Graph ########
########################################
utest <- function(name1=NULL,name2=NULL,nameAll=NULL,normalize=0,normalizedFile=NULL){
############################ read data ##############################
data1 <- read.table(name1,sep='\t')
... | 789 | lgpl-3.0 |
b513e4ecbab9a10ddfc2b80b99d94caf2b8c7c1c | gschang/genome | lib/perl/Genome/Model/Tools/R/CallR.pm.U_test.R | ########################################
######## Draw Copy Number Graph ########
########################################
utest <- function(name1=NULL,name2=NULL,nameAll=NULL,normalize=0,normalizedFile=NULL){
############################ read data ##############################
data1 <- read.table(name1,sep='\t')
... | 789 | lgpl-3.0 |
14bf36635e0da79c482c2de97a23c12c59e71fd4 | rahuldhote/jpmml-evaluator | pmml-rattle/src/test/R/ClusteringTest.R | library("amap")
library("pmml")
library("rattle")
irisData = readCsv("csv/Iris.csv")
irisData$Species = NULL
writeIris = function(clusters, affinities, file){
result = data.frame("predictedValue" = clusters)
if(!is.null(affinities)){
result = data.frame(result, affinities)
}
writeCsv(result, file)
}
generate... | 1,926 | agpl-3.0 |
b513e4ecbab9a10ddfc2b80b99d94caf2b8c7c1c | apregier/genome | lib/perl/Genome/Model/Tools/R/CallR.pm.U_test.R | ########################################
######## Draw Copy Number Graph ########
########################################
utest <- function(name1=NULL,name2=NULL,nameAll=NULL,normalize=0,normalizedFile=NULL){
############################ read data ##############################
data1 <- read.table(name1,sep='\t')
... | 789 | lgpl-3.0 |
96d8ad61b7d641c7edd8bf06f0401ce63acc774b | USGS-VIZLAB/gages-through-ages | scripts/fetch/getData_siteRecords.R | #Run this independent of vizlab - will require 8 + hours of DL time
#generates csv output currently retrieved from sciencebase
#one part is parellized
#get # years of record for every site
library(dplyr)
library(stringr)
library(data.table)
library(dataRetrieval)
library(lubridate)
library(parallel)
source('scripts/f... | 4,016 | cc0-1.0 |
5c16d744f245ac0a371890b1a8c6e58cae77e480 | sebastianueckert/mirt | R/createGroup.R | #' Create a user defined group-level object with correct generic functions
#'
#' Initializes the proper S4 class and methods necessary for mirt functions to use in estimation for defining
#' customized group-level functions. To use the defined objects pass to the
#' \code{mirt(..., customGroup = OBJECT)} command, and e... | 5,276 | gpl-2.0 |
b56af4788dcf2b74e723ba98e729eb182424722c | himalayajung/neuroR | data/caret_feature_selection.R | require(caret)
require(randomForest)
require(doParallel)
require(foreach)
source('../Rfunctions.R') # R helper functions
## Settings
set.seed(123)
# brain morphometric properties
features=list('_volume','_area','_thickness$','_thicknessstd','_foldind','_meancurv','_gauscurv','_all')
# features=list('_volume')
scale_b... | 2,948 | mit |
781a41d935d1390df1c2d68220a4af4f06c75a08 | BlueGranite/Microsoft-R-Resources | Microsoft-R-Open/WebinarPurl.R | library(rmarkdown)
library(knitr)
knit("BlueGranite R Demo.Rmd")
purl("BlueGranite R Demo.Rmd")
| 104 | mit |
bfeeebd655e70fd0f00a71cfc1b665663812b367 | mizumot/chi | ui.R | library(shiny)
library(shinyAce)
shinyUI(bootstrapPage(
headerPanel("Chi-square Test"),
########## Adding loading message #########
tags$head(tags$style(type="text/css", "
#loadmessage {
position: fixed;
top: 0px;
left: 0px;
width: 100%;
padding: 10px 0px 10px 0px;
text-align: center;
font-weight: bold;
font... | 9,215 | unlicense |
96d8ad61b7d641c7edd8bf06f0401ce63acc774b | jread-usgs/gages-through-ages | scripts/fetch/getData_siteRecords.R | #Run this independent of vizlab - will require 8 + hours of DL time
#generates csv output currently retrieved from sciencebase
#one part is parellized
#get # years of record for every site
library(dplyr)
library(stringr)
library(data.table)
library(dataRetrieval)
library(lubridate)
library(parallel)
source('scripts/f... | 4,016 | cc0-1.0 |
3b0b6b06cf20d57423b736735ba3567ea7038eae | flaneuse/llamar | website_examples.R | library(dplyr)
library(haven)
library(RColorBrewer)
# data sets ---------------------------------------------------------------
dhs_orig = read_dta('~/Documents/USAID/Rwanda/processeddata/DHS_2010_2015_analysis.dta')
dhs = removeAttributes(dhs_orig) %>%
filter(year == 2014)
dhs = factorize(dhs, dhs_orig, 'lvdzon... | 2,536 | mit |
96d8ad61b7d641c7edd8bf06f0401ce63acc774b | ldecicco-USGS/gages-through-ages | scripts/fetch/getData_siteRecords.R | #Run this independent of vizlab - will require 8 + hours of DL time
#generates csv output currently retrieved from sciencebase
#one part is parellized
#get # years of record for every site
library(dplyr)
library(stringr)
library(data.table)
library(dataRetrieval)
library(lubridate)
library(parallel)
source('scripts/f... | 4,016 | cc0-1.0 |
f6f70a59a134f07a54ba970122ed982675715fc6 | rho-devel/rho | src/extra/testr/filtered-test-suite/unlist/tc_unlist_17.R | expected <- eval(parse(text="c(TRUE, TRUE, TRUE, TRUE)"));
test(id=0, code={
argv <- eval(parse(text="list(list(TRUE, TRUE, TRUE, TRUE), FALSE, TRUE)"));
.Internal(`unlist`(argv[[1]], argv[[2]], argv[[3]]));
}, o=expected);
| 260 | gpl-2.0 |
f6f70a59a134f07a54ba970122ed982675715fc6 | ArunChauhan/cxxr | src/extra/testr/filtered-test-suite/unlist/tc_unlist_17.R | expected <- eval(parse(text="c(TRUE, TRUE, TRUE, TRUE)"));
test(id=0, code={
argv <- eval(parse(text="list(list(TRUE, TRUE, TRUE, TRUE), FALSE, TRUE)"));
.Internal(`unlist`(argv[[1]], argv[[2]], argv[[3]]));
}, o=expected);
| 260 | gpl-2.0 |
3dd40a8734a58418bd5208f7d01dc4196bb9490f | carlganz/survey | R/twophase.R | ##
##
twophase<-function(id,strata=NULL, probs=NULL, weights=NULL, fpc=NULL,
subset, data, method=c("full","approx","simple")){
method<-match.arg(method)
if(method=="full") {
if (!is.null(weights)) stop("weights not accepted by method='full'")
return(twophase2(id=id, strata=strata, probs=... | 25,145 | gpl-3.0 |
f6f70a59a134f07a54ba970122ed982675715fc6 | kmillar/cxxr | src/extra/testr/filtered-test-suite/unlist/tc_unlist_17.R | expected <- eval(parse(text="c(TRUE, TRUE, TRUE, TRUE)"));
test(id=0, code={
argv <- eval(parse(text="list(list(TRUE, TRUE, TRUE, TRUE), FALSE, TRUE)"));
.Internal(`unlist`(argv[[1]], argv[[2]], argv[[3]]));
}, o=expected);
| 260 | gpl-2.0 |
f6f70a59a134f07a54ba970122ed982675715fc6 | cxxr-devel/cxxr | src/extra/testr/filtered-test-suite/unlist/tc_unlist_17.R | expected <- eval(parse(text="c(TRUE, TRUE, TRUE, TRUE)"));
test(id=0, code={
argv <- eval(parse(text="list(list(TRUE, TRUE, TRUE, TRUE), FALSE, TRUE)"));
.Internal(`unlist`(argv[[1]], argv[[2]], argv[[3]]));
}, o=expected);
| 260 | gpl-2.0 |
f6f70a59a134f07a54ba970122ed982675715fc6 | kmillar/rho | src/extra/testr/filtered-test-suite/unlist/tc_unlist_17.R | expected <- eval(parse(text="c(TRUE, TRUE, TRUE, TRUE)"));
test(id=0, code={
argv <- eval(parse(text="list(list(TRUE, TRUE, TRUE, TRUE), FALSE, TRUE)"));
.Internal(`unlist`(argv[[1]], argv[[2]], argv[[3]]));
}, o=expected);
| 260 | gpl-2.0 |
f6f70a59a134f07a54ba970122ed982675715fc6 | krlmlr/cxxr | src/extra/testr/filtered-test-suite/unlist/tc_unlist_17.R | expected <- eval(parse(text="c(TRUE, TRUE, TRUE, TRUE)"));
test(id=0, code={
argv <- eval(parse(text="list(list(TRUE, TRUE, TRUE, TRUE), FALSE, TRUE)"));
.Internal(`unlist`(argv[[1]], argv[[2]], argv[[3]]));
}, o=expected);
| 260 | gpl-2.0 |
4f184a67481c62e86136bba02143e616bd46f94f | SoftFx/FDK | FDK2R/FdkRLib/RPackage/R/FdkBarPair.R |
#' Gets the bars' low as requested
#'
#' @param symbol Symbol looked
#' @param barPeriodStr (default 'M1') values like: S1, S10, M1, M5, M15, M30, H1, H4, D1, W1, MN1
#' @param startTime R time as start of interval
#' @param endTime R time as end of interval
#' @param barCountDbl Bar count
#' @export
ttBarsQuotesHist... | 4,834 | mit |
f403d3cc80d96bb9d032068cabb16d96792776ad | tijoseymathew/mlr | todo-files/test_regr_randomUniformForest.R | context("regr_randomUniformForest")
test_that("regr_randomUniformForest", {
skip_on_travis() # FIXME: I dont know why this breaks on travis
requirePackages("randomUniformForest", default.method = "load")
parset.list = list(
list(ntree = 5, mtry = 4)
)
tsk.train = makeRegrTask(data = regr.train, target ... | 1,224 | bsd-2-clause |
f403d3cc80d96bb9d032068cabb16d96792776ad | vinaywv/mlr | todo-files/test_regr_randomUniformForest.R | context("regr_randomUniformForest")
test_that("regr_randomUniformForest", {
skip_on_travis() # FIXME: I dont know why this breaks on travis
requirePackages("randomUniformForest", default.method = "load")
parset.list = list(
list(ntree = 5, mtry = 4)
)
tsk.train = makeRegrTask(data = regr.train, target ... | 1,224 | bsd-2-clause |
71c5bb1c16e31e50b5a38baa1e64dc6ed53116de | guiastrennec/xpose | R/plot_residuals.R | #' Residuals plotted against population predictions
#'
#' @description Model residuals plotted against population predictions (PRED).
#'
#' The residuals can be one of:
#' \itemize{
#' \item RES: model residuals
#' \item WRES: weighted model residuals
#' \item CWRES: conditional weighted model residuals
#' \i... | 10,260 | lgpl-3.0 |
71c5bb1c16e31e50b5a38baa1e64dc6ed53116de | guiastrennec/ggxpose | R/plot_residuals.R | #' Residuals plotted against population predictions
#'
#' @description Model residuals plotted against population predictions (PRED).
#'
#' The residuals can be one of:
#' \itemize{
#' \item RES: model residuals
#' \item WRES: weighted model residuals
#' \item CWRES: conditional weighted model residuals
#' \i... | 10,260 | gpl-3.0 |
34a4a870fd7a95ac605c7b072f6fbd031e1341a1 | magrai/URBAN-MV-VIE_UniBw | fun/computeActivityRates.R |
# Objective ---------------------------------------------------------------
## Compute glance rates for each direction in two versions
## 1) As percentage of first glances
## 2) As percentage of overall glances
computeActivityRates <- function(dat,
col_name_act_level,
... | 8,837 | gpl-3.0 |
69dc476ae6309c2f6c8cfc9ca510157ed1ba3ad1 | eddelbuettel/nanotime | tests/simpleTests.R |
library(nanotime)
z <- RcppCCTZ:::parseDouble("1970-01-01T00:00:00.000000001+00:00")
cat("z is: ")
print(z)
x <- nanotime("1970-01-01T00:00:00.000000001+00:00")
cat("x is: ")
print(x)
format(x)
cat("x+1 is: ")
x <- x + 1
print(x)
format(x)
cat("y is: ")
y <- nanotime(z)
print(y)
#print(class(y))
format(y)
cat("y+... | 1,016 | gpl-2.0 |
b10d1a211c120106c80fdad3d262cc257e4753eb | environmentalinformatics-marburg/Rsenal | R/roc.R | #' Calculation of ROC and AUC
#'
#' @param pred An object of type "RasterLayer" containing the probability of each pixel to belong to the class of investigation.
#' @param obs An object of type "RasterLayer" containing 1 and 0 values with 1 indicating that a pixel belongs to the class of investigation.
#' @param mask ... | 4,668 | gpl-3.0 |
e89793f1135a32879f08c483eb5de406cfc88fc2 | keithschulze/supr | tests/testthat/test-localk-multi.R | context("Local multitype Ripley's K")
test_that("the mean value of cross-type local K values should be the same as Kcross for a given r", {
kc <- spatstat::Kcross(spatstat::amacrine, correction="isotropic", r=c(0, 0.05, 0.1, 0.15))
lkc0.05 <- local_k_cross(spatstat::amacrine, correction="isotropic", rvalue=0.05, v... | 656 | mit |
f7b3e2e05f8ab250e5f20a1abb8df06b8c6e0b85 | dcgerard/vicar | tests/testthat/test_ash.R | library(vicar)
context("ASH Wrappers")
test_that("ash_ruv4 works", {
set.seed(21)
n <- 11
p <- 113
k <- 2
q <- 3
pi_vals <- c(0.5, 0.3, 0.2)
sd_seq <- c(0, 1, 2)
X <- cbind(rep(1, n), sample(c(0, 1), size = n, replace = TRUE))
beta <- matrix(NA, nrow = k, ncol = p)
beta[1, ] ... | 1,182 | gpl-3.0 |
ba7f54862c519e204f06e99f3ee8b06c8fff3741 | citiususc/voila | demo/ornstein.R | library("voila")
# simulate Ornstein-Uhlenbeck time series ---------------------------------
h = 0.001
set.seed(1234)
drift = "-x"
diffusion = "sqrt(1.5)"
x = simulate_sde(drift, diffusion, samplingPeriod = 0.001, tsLength = 20000)
plot.ts(x, ylab = "x(t)", xlab = "Time t", main = "Ornstein-Uhlenbeck process")
# do i... | 3,606 | gpl-3.0 |
caf19087e19219c9ae2dc7c2f1242d73fafe9944 | jefferis/nat.examples | 07-insectbraindb/01-download-neurons.R | ## This script assumed that you have run the file "07-insectbraindb/00-setup.R"
## Functions to talk to insectbraindb.org, a site primarily curated by Prof. Stanley Heinze, are wrapped up into the package neuromorphr
## So let's use that
## What neurons does the insectbraindb.org host?
available.neurons = insectbrai... | 861 | mit |
86432a8c5ab3285ee12fa606aefa1e4a25fa1102 | mmuscarella/StarvationTraits | analyses/tests/GrowthCurveTest.R | ################################################################################
# #
# Test Script for Analysis of Exponential Growth Curve Data #
# This uses ModifiedGomp.R Version 2.0 ... | 1,429 | gpl-3.0 |
653696c813f91dc586ae31cdac73bc430ae093c7 | JoshuaSlocum/model-log | R/generate_entry.R | # Header ------------------------------------------------------------------
# Created: 1/25/2016
# Author: Joshua Slocum
# Purpose: Combine results to make entry
#' Combine results from helper functions to create an entry for the model
#'
#' @param object The model object of the model to be logged
#' @return Named li... | 951 | mit |
3fb1d9c1a0a65557146796daff0ad8e65a5ec253 | gersteinlab/exceRpt | mergePipelineRuns_functions.R | ##########################################################################################
## ##
## Functions to combine pipeline runs for individual samples into something more useful ##
## ... | 67,683 | gpl-3.0 |
86432a8c5ab3285ee12fa606aefa1e4a25fa1102 | jaytlennon/StarvationTraits | analyses/tests/GrowthCurveTest.R | ################################################################################
# #
# Test Script for Analysis of Exponential Growth Curve Data #
# This uses ModifiedGomp.R Version 2.0 ... | 1,429 | gpl-3.0 |
86432a8c5ab3285ee12fa606aefa1e4a25fa1102 | LennonLab/StarvationTraits | analyses/tests/GrowthCurveTest.R | ################################################################################
# #
# Test Script for Analysis of Exponential Growth Curve Data #
# This uses ModifiedGomp.R Version 2.0 ... | 1,429 | gpl-3.0 |
502a51fe90d821322c9ccacb5bcbbda69ae0852f | XiaodanLyu/Lognormal-Extension | 2_Zeros/Code/overlaysd_parallel.R | rm(list = ls(all = T))
setwd("C:/Users/lyux/Box Sync/SAEZeros")
library("multidplyr")
library("parallel")
library("tidyverse")
# library("raster")
# library("sp")
geo.proj <- "+proj=aea +lat_1=29.5 +lat_2=45.5 +lat_0=23 +lon_0=-96 +x_0=0 +y_0=0 +datum=NAD83 +units=m +no_defs +ellps=GRS80 +towgs84=0,0,0"
## CDL raster... | 4,254 | mit |
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