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 |
|---|---|---|---|---|---|
7f32cb99adfedb0a79c1d812f2eb87bb5a003d5a | kingaa/pomp | examples/trajectory.R | \donttest{
## The basic components needed to compute trajectories
## of a deterministic dynamical system are
## rinit and skeleton.
## The following specifies these for a simple continuous-time
## model: dx/dt = r (1+e cos(t)) x
trajectory(
t0 = 0, times = seq(1,30,by=0.1),
rinit = function (x0, .... | 1,013 | gpl-3.0 |
5484bccf3c032d53a849f55eb7f3a3ee317d7f86 | frareb/pqb | server.R | library(shiny)
archivo<-"data/cuestionarioquinuarjj-2016-01-04-18-03-29.csv"
tipoDatos<-c("factor","factor","Date","factor","factor","factor","factor","factor",
"factor","character","character","factor","integer","character","factor",
"logical","logical","logical","logical","logical","factor"... | 1,925 | gpl-2.0 |
495aeda45512dc212a93a260aa0ccac5961b7233 | cboettig/pdg_control | R/active_adaptive_simulate.R | #' @export
setmodel <- function(f, pars){
function(x_t1, x_t0){
mu = f(x_t0, 0, pars)
(mu <= 0) * (x_t1 == 0) +
(mu > 0) * dlnorm(x_t1, log(mu), sigma_g)
}
}
# internal function
bin <- function(v, v_grid){
v_grid[which.min(abs(v_grid - v))]
# i = 1
# n = length(v_grid)
# while(v_grid[i] < v & i < ... | 5,211 | cc0-1.0 |
6c8936770bb353f38cc483b597ced8c5a42c3a0e | Bioinformatics-Support-Unit/shiny | app1/global.R | source("profile_plot.R")
load("deploy2.Rdata")
data_names <- c('Raw Data', 'Normalised Data')
| 94 | apache-2.0 |
ee3edda17ca237a7a0cdbe958a69cc75191935d7 | kyoren/https-github.com-h2oai-h2o-3 | h2o-r/tests/testdir_docexamples/runit_Rdoc_screeplot.R | setwd(normalizePath(dirname(R.utils::commandArgs(asValues=TRUE)$"f")))
source('../h2o-runit.R')
test.rdoc_screeplot.golden <- function() {
ausPath <- system.file("extdata", "australia.csv", package = "h2o")
australia.hex <- h2o.uploadFile(path = ausPath)
australia.pca <- h2o.prcomp(training_frame = australia.hex... | 445 | apache-2.0 |
eb2fddf7c8ab123c6845f5ce859fb22b637846c1 | jkushida/BanditsBook | r/comparisons/plot_comparisons.R | library("plyr")
library("ggplot2")
annealing.results <- read.csv("julia/algorithms/epsilon_greedy/annealing_results.csv", header = FALSE)
names(annealing.results) <- c("Sim", "T", "ChosenArm", "Reward", "CumulativeReward")
annealing.results <- transform(annealing.results, Algorithm = "Annealing epsilon-Greedy")
epsil... | 3,631 | mit |
ed55a2315e7a2f7bbe43bedea369d9771b3a872f | datachand/h2o-3 | h2o-r/tests/testdir_algos/glm/runit_GLM_offset_poisson_comparison1.R | ### This tests offset in glm on real data ######
setwd(normalizePath(dirname(R.utils::commandArgs(asValues=TRUE)$"f")))
source('../../h2o-runit.R')
test <- function(h) {
insurance_h2o <- h2o.importFile(locate("smalldata/glm_test/insurance.csv"))
insurance_h2o$logHolders <- log(insurance_h2o$Holders)
insur... | 2,274 | apache-2.0 |
ed55a2315e7a2f7bbe43bedea369d9771b3a872f | printedheart/h2o-3 | h2o-r/tests/testdir_algos/glm/runit_GLM_offset_poisson_comparison1.R | ### This tests offset in glm on real data ######
setwd(normalizePath(dirname(R.utils::commandArgs(asValues=TRUE)$"f")))
source('../../h2o-runit.R')
test <- function(h) {
insurance_h2o <- h2o.importFile(locate("smalldata/glm_test/insurance.csv"))
insurance_h2o$logHolders <- log(insurance_h2o$Holders)
insur... | 2,274 | apache-2.0 |
eb2fddf7c8ab123c6845f5ce859fb22b637846c1 | Mario-LopezTelecom/BanditsBook | r/comparisons/plot_comparisons.R | library("plyr")
library("ggplot2")
annealing.results <- read.csv("julia/algorithms/epsilon_greedy/annealing_results.csv", header = FALSE)
names(annealing.results) <- c("Sim", "T", "ChosenArm", "Reward", "CumulativeReward")
annealing.results <- transform(annealing.results, Algorithm = "Annealing epsilon-Greedy")
epsil... | 3,631 | mit |
6dadb96ece94b5602647f42c97ab6f1afdaabd71 | definitelysean/sgaphd | R/data.R | #' All of the Gene Set Collections from the Broad Institutes MSigDB
#'
#' A collated version of all the gene set collections created by the Broad Institute.
#' Generated by downloading the Entrez .gmt's for each gene set, parsing them with
#' roller, and concatenating them al together.
#' Useful for GSEA and GSVA shot... | 807 | mit |
ed55a2315e7a2f7bbe43bedea369d9771b3a872f | junwucs/h2o-3 | h2o-r/tests/testdir_algos/glm/runit_GLM_offset_poisson_comparison1.R | ### This tests offset in glm on real data ######
setwd(normalizePath(dirname(R.utils::commandArgs(asValues=TRUE)$"f")))
source('../../h2o-runit.R')
test <- function(h) {
insurance_h2o <- h2o.importFile(locate("smalldata/glm_test/insurance.csv"))
insurance_h2o$logHolders <- log(insurance_h2o$Holders)
insur... | 2,274 | apache-2.0 |
ed55a2315e7a2f7bbe43bedea369d9771b3a872f | brightchen/h2o-3 | h2o-r/tests/testdir_algos/glm/runit_GLM_offset_poisson_comparison1.R | ### This tests offset in glm on real data ######
setwd(normalizePath(dirname(R.utils::commandArgs(asValues=TRUE)$"f")))
source('../../h2o-runit.R')
test <- function(h) {
insurance_h2o <- h2o.importFile(locate("smalldata/glm_test/insurance.csv"))
insurance_h2o$logHolders <- log(insurance_h2o$Holders)
insur... | 2,274 | apache-2.0 |
eb2fddf7c8ab123c6845f5ce859fb22b637846c1 | SalemAmeen/BanditsBook | r/comparisons/plot_comparisons.R | library("plyr")
library("ggplot2")
annealing.results <- read.csv("julia/algorithms/epsilon_greedy/annealing_results.csv", header = FALSE)
names(annealing.results) <- c("Sim", "T", "ChosenArm", "Reward", "CumulativeReward")
annealing.results <- transform(annealing.results, Algorithm = "Annealing epsilon-Greedy")
epsil... | 3,631 | mit |
eb2fddf7c8ab123c6845f5ce859fb22b637846c1 | sweaterr/BanditsBook | r/comparisons/plot_comparisons.R | library("plyr")
library("ggplot2")
annealing.results <- read.csv("julia/algorithms/epsilon_greedy/annealing_results.csv", header = FALSE)
names(annealing.results) <- c("Sim", "T", "ChosenArm", "Reward", "CumulativeReward")
annealing.results <- transform(annealing.results, Algorithm = "Annealing epsilon-Greedy")
epsil... | 3,631 | mit |
445cb2189e9a5ca7a6873d093b1c72c4d1670e77 | chipster/chipster-tools | tools/microarray/R/stat-one-group.R | # TOOL stat-one-group.R: "One sample tests" (Tests whether genes are differentially expressed, i.e., whether their expression is significantly different from the expected.)
# INPUT normalized.tsv: normalized.tsv TYPE GENE_EXPRS
# OUTPUT one-sample.tsv: one-sample.tsv
# PARAMETER test: "Test" TYPE [t-test: t-test, Wil... | 3,460 | mit |
eb2fddf7c8ab123c6845f5ce859fb22b637846c1 | johnmyleswhite/BanditsBook | r/comparisons/plot_comparisons.R | library("plyr")
library("ggplot2")
annealing.results <- read.csv("julia/algorithms/epsilon_greedy/annealing_results.csv", header = FALSE)
names(annealing.results) <- c("Sim", "T", "ChosenArm", "Reward", "CumulativeReward")
annealing.results <- transform(annealing.results, Algorithm = "Annealing epsilon-Greedy")
epsil... | 3,631 | mit |
86137d0770d3ce761a22b5248cc1112e2ffb6bac | Robinlovelace/twitter-sandy | R Scripts/loading-mysql-tweets.R | # load twitter db
library(RMySQL)
con <- dbConnect(dbDriver("MySQL"), user = "root", password = "NDean19", dbname = "twitter")
## list the tables in the database
dbListTables(con)
tweets1 <- dbReadTable(con, "tweets_1")
head(tweets1)
save.image("tweets1.RData")
| 263 | mit |
7e895b58d7841ed182a0a55ae559bc87d40cc6fc | marchtaylor/sinkr | R/shadowtext.R | #' Add border to plotted text
#'
#' @param x,y numeric vectors of coordinates where the text labels should
#' be written. If the length of x and y differs, the shorter one is recycled.
#' @param labels a character vector or expression specifying the text to be
#' written. An attempt is made to coerce other langua... | 2,194 | gpl-3.0 |
7ed3b4d2cfb496074155084e9eae38c6fea0e151 | andy-thomason/r-source | src/library/utils/R/aspell.R | # File src/library/utils/R/aspell.R
# Part of the R package, https://www.R-project.org
#
# Copyright (C) 1995-2015 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 ... | 39,670 | gpl-2.0 |
4f14a238b5feb0978403112fef1ad9d7a3a5152d | kmillar/cxxr | src/extra/testr/filtered-test-suite/enc2native/tc_enc2native_3.R | expected <- eval(parse(text="\"José Pinheiro [aut] (S version)\""));
test(id=0, code={
argv <- eval(parse(text="list(\"José Pinheiro [aut] (S version)\")"));
do.call(`enc2native`, argv);
}, o=expected);
| 221 | gpl-2.0 |
141fa3ae8801518a0e4fe0ce3b5831019bbb8199 | JamesMcGuigan/datasciencecoursera | ExploratoryDataAnalysis/CourseProject2/plot4.R | # Exploratory Data Analysis - Course Project 2
# Author - James McGuigan
#
# Question 4: Across the United States, how have emissions
# from coal combustion-related sources changed from 1999–2008?
source("dataLoad.R")
library("plyr")
library("ggplot2")
# Extract the list of SCC codes containing coal in t... | 961 | mit |
4f14a238b5feb0978403112fef1ad9d7a3a5152d | cxxr-devel/cxxr | src/extra/testr/filtered-test-suite/enc2native/tc_enc2native_3.R | expected <- eval(parse(text="\"José Pinheiro [aut] (S version)\""));
test(id=0, code={
argv <- eval(parse(text="list(\"José Pinheiro [aut] (S version)\")"));
do.call(`enc2native`, argv);
}, o=expected);
| 221 | gpl-2.0 |
7ed3b4d2cfb496074155084e9eae38c6fea0e151 | LeifAndersen/R | src/library/utils/R/aspell.R | # File src/library/utils/R/aspell.R
# Part of the R package, https://www.R-project.org
#
# Copyright (C) 1995-2015 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 ... | 39,670 | gpl-2.0 |
7ed3b4d2cfb496074155084e9eae38c6fea0e151 | mathematicalcoffee/r-source | src/library/utils/R/aspell.R | # File src/library/utils/R/aspell.R
# Part of the R package, https://www.R-project.org
#
# Copyright (C) 1995-2015 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 ... | 39,670 | gpl-2.0 |
b6ab08cc21acd6dccd3953bccfed108702650160 | lbkchen/visual-reddit | fnetwork.R | list.of.packages <- c("bigrquery", "ggplot2", "dplyr", "lubridate", "mosaic", "tidyr", "knitr", "beepr", "igraph", "network")
new.packages <- list.of.packages[!(list.of.packages %in% installed.packages()[,"Package"])]
if(length(new.packages)) install.packages(new.packages)
library(bigrquery)
library(ggplot2)
library(m... | 7,002 | mit |
7ed3b4d2cfb496074155084e9eae38c6fea0e151 | nathan-russell/r-source | src/library/utils/R/aspell.R | # File src/library/utils/R/aspell.R
# Part of the R package, https://www.R-project.org
#
# Copyright (C) 1995-2015 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 ... | 39,670 | gpl-2.0 |
4f14a238b5feb0978403112fef1ad9d7a3a5152d | ArunChauhan/cxxr | src/extra/testr/filtered-test-suite/enc2native/tc_enc2native_3.R | expected <- eval(parse(text="\"José Pinheiro [aut] (S version)\""));
test(id=0, code={
argv <- eval(parse(text="list(\"José Pinheiro [aut] (S version)\")"));
do.call(`enc2native`, argv);
}, o=expected);
| 221 | gpl-2.0 |
4f14a238b5feb0978403112fef1ad9d7a3a5152d | rho-devel/rho | src/extra/testr/filtered-test-suite/enc2native/tc_enc2native_3.R | expected <- eval(parse(text="\"José Pinheiro [aut] (S version)\""));
test(id=0, code={
argv <- eval(parse(text="list(\"José Pinheiro [aut] (S version)\")"));
do.call(`enc2native`, argv);
}, o=expected);
| 221 | gpl-2.0 |
7ed3b4d2cfb496074155084e9eae38c6fea0e151 | abiyug/r-source | src/library/utils/R/aspell.R | # File src/library/utils/R/aspell.R
# Part of the R package, https://www.R-project.org
#
# Copyright (C) 1995-2015 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 ... | 39,670 | gpl-2.0 |
4f14a238b5feb0978403112fef1ad9d7a3a5152d | kmillar/rho | src/extra/testr/filtered-test-suite/enc2native/tc_enc2native_3.R | expected <- eval(parse(text="\"José Pinheiro [aut] (S version)\""));
test(id=0, code={
argv <- eval(parse(text="list(\"José Pinheiro [aut] (S version)\")"));
do.call(`enc2native`, argv);
}, o=expected);
| 221 | gpl-2.0 |
4f14a238b5feb0978403112fef1ad9d7a3a5152d | krlmlr/cxxr | src/extra/testr/filtered-test-suite/enc2native/tc_enc2native_3.R | expected <- eval(parse(text="\"José Pinheiro [aut] (S version)\""));
test(id=0, code={
argv <- eval(parse(text="list(\"José Pinheiro [aut] (S version)\")"));
do.call(`enc2native`, argv);
}, o=expected);
| 221 | gpl-2.0 |
7ed3b4d2cfb496074155084e9eae38c6fea0e151 | WelkinGuan/r-source | src/library/utils/R/aspell.R | # File src/library/utils/R/aspell.R
# Part of the R package, https://www.R-project.org
#
# Copyright (C) 1995-2015 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 ... | 39,670 | gpl-2.0 |
2dd5819431da6e88400d3681ec0dc7a0d981194d | mensxmachina/MXM-R-Package | R/gammabsreg.R | gammabsreg <- function(target, dataset, threshold = 0.05, wei = NULL) {
threshold <- log(threshold)
dm <- dim(dataset)
if ( is.null(dm) ) {
n <- length(target)
p <- 1
} else {
n <- dm[1] ## sample size
p <- dm[2] ## number of variables
}
if ( p > n ) {
res <- paste("T... | 4,676 | gpl-2.0 |
2a575a8c6cf243ee1b9104c2aba0610ceddcdbd0 | cran/TIMP | R/kin.R | "kin" <-
function(...){
new("kin", ...)
}
| 44 | gpl-2.0 |
fe0e66295bd9413f7770ef978b0ed8a7b80d5124 | hodgeslab/workflows | velocyto/velocyto.R | #!~/usr/bin/Rscript
library(methods)
library(hodgeslabR)
library(velocyto.R)
library(pagoda2)
library(igraph)
library(pheatmap)
library(grid)
library(RColorBrewer)
args <- commandArgs(TRUE)
infile <- args[1]
ldat <- read.loom.matrices(infile)
emat <- ldat$spliced
# filter on cells with large numbers of splicing even... | 4,286 | mit |
f3972136d5429a4a31f96ba6bd06c2679bdb041f | gahoo/10010 | ui.R |
# This is the user-interface definition of a Shiny web application.
# You can find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com
#
library(shiny)
library(DT)
library(ggvis)
library(leaflet)
shinyUI(bootstrapPage(
tags$style(type = "text/css", "html, body {width:100%;height:100%... | 2,209 | gpl-2.0 |
30882d2cfed75134d50d657f70e0076364bc0ad2 | bostasie/WFCTSI-Public | ACS/acs5yrextraction_Clean20180510.R | #Extract block and ZCTA level variables from ACS using tidy census
#This file should be utilized as a templace with some modification necessary
#Must extract block by calling intdividual counties or missing blocks if calling by state.
#Code blocked in extractions due to memory restrictions
#Package/Version inform... | 5,376 | mit |
74d133fde86360c4591639e964c05ed5f41e23cd | mlhim/tb | src/models/BrazilianPublicHospitalDischargeSummary2012/ccdBrazilianPublicHospitalDischargeSummary201290c28fec7d00/R/CauseofDeath.R | # Copyright 2015, Timothy W. Cook <tim@mlhim.org>
# Licensed under the Apache License, Version 2.0 (the 'License');
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to ... | 2,626 | gpl-3.0 |
1f242bced8001e848137839fe74fbe4016935296 | joshkeating/global-gag-rule | ui.R |
library(shiny)
library(dplyr)
library(plotly)
library(scales)
UNyOpts1 <- c("CP_Any_Method", "CP_Any_Modern_Method", "CP_Any_Traditional_Method", "UN_Unmet_Need_Total", "Demand_Satisfied_By_Modern_Methods")
names(UNyOpts1) <- c("Contraceptive Prevalence", "Contraceptive (Modern) Prevalence", "Contraceptive (Tradition... | 26,346 | mit |
88cda0dbd26aa85271586e0923dc36c3c70c1591 | momdadok/process_temp | peak3.R | invisible(readline("check file path. Press [enter] to continue..."))
date<-as.POSIXct(readline("input date in yyyy-mm-dd format: "))
input_complete<-"n"
while (input_complete=="n"){
data_source<-readline("input data source? ")
path<-"c:/Users/Clai/Documents/Line_2/"
file_date<-format(date,"%m%d%y... | 8,342 | mit |
45299f4827f5af7cc53b1a98a177e43212562fd7 | polmath/plot_ball | server.R |
library(shiny)
shinyServer(function(input, output, session) {
xymax <- 100
output$text <- renderUI({
withMathJax(helpText(h4(paste0("The distance is defined on \\( \\mathbb{R}_+^2 \\) by \\( d_p(x, y) = \\| x - y \\|_p\\)."))))
})
output$text0 <- renderUI({
withMathJax(helpText(h4(paste0("The dis... | 2,310 | mit |
7ddcf5109daa5bdf7799fe1c36ad3b846ee76812 | rozsasarpi/Interactive-snow-map-R | R/get_repr_values.R | get_repr_values = function(data, distr_type){
## Exceptional snow check per EN:1991-1-3 background document (Sanpaolesi 1998)
## Characteristic value - 0.98 fractile based on the entire data
# handle seasons with no snow
P_snow = sum(data > 0)/length(data)
idx_snow = !(data == 0)
data = data[... | 1,588 | mit |
9bac769e37974ec1fadf7664e154b796fd3b9e98 | franticspider/bioarch | tests/ba_test_sheets.R |
#MASTER TEST FUNCTION
test_sheets <- function(){
}
#This works on mammalian collagen seqences v0.1.1, which should be passed in
test_colidx(sheet){
#Using sheet[1,ANQ] = 405 (but note, this might be a formula: ANK1 + 5)
#We are interested in column ANU
message("Column ANU is:)
for(i in 6:... | 344 | gpl-3.0 |
59ed40a39bba8844f09d7e3b6c0b48f68c6d29d1 | YzPaul3/h2o-3 | h2o-r/demos/rdemo.not.equal.factor.R | library(h2o)
h2o.init()
filePath <- "https://raw.github.com/0xdata/h2o/master/smalldata/airlines/allyears2k_headers.zip"
testFilePath <-"https://raw.github.com/0xdata/h2o/master/smalldata/airlines/allyears2k_headers.zip"
# Uploading data file to h2o.
air <- h2o.importFile(filePath, "air")
# Print dataset size.
dim(a... | 442 | apache-2.0 |
59ed40a39bba8844f09d7e3b6c0b48f68c6d29d1 | nilbody/h2o-3 | h2o-r/demos/rdemo.not.equal.factor.R | library(h2o)
h2o.init()
filePath <- "https://raw.github.com/0xdata/h2o/master/smalldata/airlines/allyears2k_headers.zip"
testFilePath <-"https://raw.github.com/0xdata/h2o/master/smalldata/airlines/allyears2k_headers.zip"
# Uploading data file to h2o.
air <- h2o.importFile(filePath, "air")
# Print dataset size.
dim(a... | 442 | apache-2.0 |
59ed40a39bba8844f09d7e3b6c0b48f68c6d29d1 | spennihana/h2o-3 | h2o-r/demos/rdemo.not.equal.factor.R | library(h2o)
h2o.init()
filePath <- "https://raw.github.com/0xdata/h2o/master/smalldata/airlines/allyears2k_headers.zip"
testFilePath <-"https://raw.github.com/0xdata/h2o/master/smalldata/airlines/allyears2k_headers.zip"
# Uploading data file to h2o.
air <- h2o.importFile(filePath, "air")
# Print dataset size.
dim(a... | 442 | apache-2.0 |
59ed40a39bba8844f09d7e3b6c0b48f68c6d29d1 | michalkurka/h2o-3 | h2o-r/demos/rdemo.not.equal.factor.R | library(h2o)
h2o.init()
filePath <- "https://raw.github.com/0xdata/h2o/master/smalldata/airlines/allyears2k_headers.zip"
testFilePath <-"https://raw.github.com/0xdata/h2o/master/smalldata/airlines/allyears2k_headers.zip"
# Uploading data file to h2o.
air <- h2o.importFile(filePath, "air")
# Print dataset size.
dim(a... | 442 | apache-2.0 |
59ed40a39bba8844f09d7e3b6c0b48f68c6d29d1 | h2oai/h2o-3 | h2o-r/demos/rdemo.not.equal.factor.R | library(h2o)
h2o.init()
filePath <- "https://raw.github.com/0xdata/h2o/master/smalldata/airlines/allyears2k_headers.zip"
testFilePath <-"https://raw.github.com/0xdata/h2o/master/smalldata/airlines/allyears2k_headers.zip"
# Uploading data file to h2o.
air <- h2o.importFile(filePath, "air")
# Print dataset size.
dim(a... | 442 | apache-2.0 |
59ed40a39bba8844f09d7e3b6c0b48f68c6d29d1 | h2oai/h2o-dev | h2o-r/demos/rdemo.not.equal.factor.R | library(h2o)
h2o.init()
filePath <- "https://raw.github.com/0xdata/h2o/master/smalldata/airlines/allyears2k_headers.zip"
testFilePath <-"https://raw.github.com/0xdata/h2o/master/smalldata/airlines/allyears2k_headers.zip"
# Uploading data file to h2o.
air <- h2o.importFile(filePath, "air")
# Print dataset size.
dim(a... | 442 | apache-2.0 |
33581e8aae0c51fa218e4c876f087f6190c68c7f | sammorris81/spatial-skew-t | code/analysis/ozone/US-all/us-all-6.R | source("./package_load.R", chdir = TRUE)
setting <- 6
method <- "t"
nknots <- 1
keep.knots <- F
threshold <- 85
tau.init <- 0.05
thresh.quant <- F
skew <- T
outputfile <- paste("results/us-all-", setting, ".RData", sep="")
start <- proc.time()
fit <- vector(mode="list", length=2)
for(val in 1:2){
set.seed(setting... | 1,229 | gpl-2.0 |
59ed40a39bba8844f09d7e3b6c0b48f68c6d29d1 | jangorecki/h2o-3 | h2o-r/demos/rdemo.not.equal.factor.R | library(h2o)
h2o.init()
filePath <- "https://raw.github.com/0xdata/h2o/master/smalldata/airlines/allyears2k_headers.zip"
testFilePath <-"https://raw.github.com/0xdata/h2o/master/smalldata/airlines/allyears2k_headers.zip"
# Uploading data file to h2o.
air <- h2o.importFile(filePath, "air")
# Print dataset size.
dim(a... | 442 | apache-2.0 |
59ed40a39bba8844f09d7e3b6c0b48f68c6d29d1 | mathemage/h2o-3 | h2o-r/demos/rdemo.not.equal.factor.R | library(h2o)
h2o.init()
filePath <- "https://raw.github.com/0xdata/h2o/master/smalldata/airlines/allyears2k_headers.zip"
testFilePath <-"https://raw.github.com/0xdata/h2o/master/smalldata/airlines/allyears2k_headers.zip"
# Uploading data file to h2o.
air <- h2o.importFile(filePath, "air")
# Print dataset size.
dim(a... | 442 | apache-2.0 |
ad2c41cbef582dbb097ba9e92293214a60e0100e | shuaimeng/r | thesis/chap5/fig5-9_2.R |
#25G
x1<-c(2,2.2)
y1<-c(0.8,0.8)
#30G
x2<-c(1.6,1.8,2,2.2)
y2<-c(0.8,1.8,2.8,2.9)
#32G
x3<-c(1.8,2,2.2)
y3<-c(2.8,3.5,0.4)
#34G
x4<-c(1.8,2)
y4<-c(2,3)
data<-c(0,0.8,0,0, 0,1.8,2.8,2, 0.8,2.8,3.5,3, 0.8,2.9,0.4,0)
mycolor<-c("red","blue","black","green3","red","blue","black","green3",
"red","blue","blac... | 936 | mit |
a1c5139653e8b99a390701c108348e3be876d4a8 | johndharrison/webpagetestr | R/utils.R | WPTPaths <-
list(testStatus = "testStatus.php",
testResults = "jsonResult.php",
locations = "getLocations.php",
testers = "getTesters.php",
test = "runtest.php",
gzip = "getgzip.php",
har = "export.php",
waterfall = "waterfall.php",
thumbnail = "thumbnai... | 27,626 | mit |
8707891d89da745592f18ae818879def5aea8a91 | russellkong/dissertation_model | cwm.R | library(readxl)
library(xlsx)
library(dplyr)
library(data.table)
library(lubridate)
## Coding of CWm's Small grain cereal phenology model
## Author: Russell Kong
## Date: 19 JUN 2017
## version: 0
#'############################
#'# master script to execute
#'############################
#'
#' @param str_weather_file w... | 19,038 | apache-2.0 |
62f8b0c42f872f14d202d93e12cf6a4735fb3bb3 | jonpage/r-course | beforeScript.R | rm(list = ls(all = TRUE))
knitr::opts_chunk$set(message = FALSE, warning = FALSE, error = FALSE, cache = TRUE)
| 111 | cc0-1.0 |
2eb5163acfc5ec8a0061988172a9a06a6acdca93 | erikjsolsen/AtlantisNEUS_R | NOBA/str_split.R | #' String split function
#' by Alex Keth
#'
str_split_twice <- function(char, min_only){
patterns <- c(" ", "\t")
if (all(!stringr::str_detect(string = char, pattern = patterns))) {
stop("Neither space nor tab present in variable char (string)!")
}
for (i in seq_along(patterns)) {
char <- unlist(stri... | 571 | mit |
9480086df15217c5c7162dac6380f1d9d34d422a | TeamErlich/venter_response | no_face_value.R | #### run the main function by typing:
# success_rate = test_venter(rounds, n)
#n is the number of people in each group
#rounds is the number of simulation rounds.
#success_rate is the identifiability power of demographic iddentifiers
# The function runs a simple procedure that matches the Venter et al.
# definition o... | 2,886 | mit |
15723164a1b15f7f9478aff44dde164a316382d1 | tsackton/ratite-genomics | 06_protein_coding_analysis/paml_branch/analyze_initial_perms.R | #analyze initial RER permutations
library(tidyverse)
data_path <- "../init_perms/" # path to the data
files <- dir(data_path, pattern = "*.out")
data <- data_frame(filename = files) %>% # create a data frame
# holding the file names
mutate(file_contents = map(filename, # read files into
... | 835 | gpl-3.0 |
d86e36810963390664169af3c75660eaffddb98e | ipmbook/first-edition | Rcode/c6/SizeQualityB2B.R | # R code illustrating Bin-to-Bin implementation of a size-quality IPM
# using 5th order Gauss Legendre for initial and final bins
rm(list=ls(all=TRUE))
root=ifelse(.Platform$OS.type=="windows","c:/repos","~/Repos");
setwd(paste(root,"/ipm_book/Rcode/c6",sep=""));
require(Matrix); require(statmod);
source("domEig... | 7,435 | gpl-2.0 |
5c57c9c16881b08fc74e192584b8e14078afcd85 | nobel1154/edX-Learning-From-Data-Solutions | Final/Rcode/by_anant_sogani/final_q11.R | #!/usr/bin/env Rscript
# Input.
X = matrix(c(1, 0, 0, 1, 0, -1, -1, 0, 0, 2, 0, -2, -2, 0),
ncol = 2, byrow = TRUE)
# Labels.
Y = c(-1, -1, -1, 1, 1, 1, 1)
# Sample Size.
N = length(Y)
# Non-Linear Transform.
Z = cbind(X[, 2]^2 - 2 * X[, 1] - 1,
X[, 1]^2 - 2 * X[, 2] + 1)
#
# METHOD 1: Geometr... | 1,330 | apache-2.0 |
5c57c9c16881b08fc74e192584b8e14078afcd85 | kirbs-/edX-Learning-From-Data-Solutions | Final/Rcode/by_anant_sogani/final_q11.R | #!/usr/bin/env Rscript
# Input.
X = matrix(c(1, 0, 0, 1, 0, -1, -1, 0, 0, 2, 0, -2, -2, 0),
ncol = 2, byrow = TRUE)
# Labels.
Y = c(-1, -1, -1, 1, 1, 1, 1)
# Sample Size.
N = length(Y)
# Non-Linear Transform.
Z = cbind(X[, 2]^2 - 2 * X[, 1] - 1,
X[, 1]^2 - 2 * X[, 2] + 1)
#
# METHOD 1: Geometr... | 1,330 | apache-2.0 |
5c57c9c16881b08fc74e192584b8e14078afcd85 | JMill/edX-Learning-From-Data-Solutions-jm | Final/Rcode/by_anant_sogani/final_q11.R | #!/usr/bin/env Rscript
# Input.
X = matrix(c(1, 0, 0, 1, 0, -1, -1, 0, 0, 2, 0, -2, -2, 0),
ncol = 2, byrow = TRUE)
# Labels.
Y = c(-1, -1, -1, 1, 1, 1, 1)
# Sample Size.
N = length(Y)
# Non-Linear Transform.
Z = cbind(X[, 2]^2 - 2 * X[, 1] - 1,
X[, 1]^2 - 2 * X[, 2] + 1)
#
# METHOD 1: Geometr... | 1,330 | apache-2.0 |
2f295fc8fafa0e2898f32d6fce3a9de5837f5ad9 | bjsmith/reversallearning | diagnostic-rev2aa-MCMC-group1-distribution-error.R | source("visualization/geom_hdi.R")
source("diagnostics.R")
#this file follows on from du_model_revised_2aa_4runs_mcmc_firstniterations.R
for (i in 1:length(model.summaries)){
if(model.summaries[[i]]$m=="double_update_nov_rev2-a-a" & model.summaries[[i]]$g==1
){
print("got it")
m.g1.mcmc<-model.summaries[[i... | 976 | apache-2.0 |
203b0a56c508caf8728e25556cbf22d97ecd7c95 | andrewhooker/xpose4 | R/change.ab.graph.par.R |
#' Functions changing variable definitions in Xpose 4
#'
#' These functions allow customization of Xpose's graphics settings.
#'
#' Settings can be saved and loaded using \code{\link{export.graph.par}} and
#' \code{\link{import.graph.par}}, respectively.
#'
#' @param object An \code{xpose.data} object.
#' @param cl... | 4,160 | lgpl-3.0 |
930d6be7603c41a56fb0b46807b7b7b410a84db9 | sainathadapa/rotmulaag | glimpse_output_as_org_table.R | library(dplyr)
library(stringr)
glimpse_output_as_org_table <- function(x) {
capture.output(glimpse(x)) %>%
str_replace_all('^\\$', '| ') %>%
str_replace_all('(.*)<(.*)>(.*)', '\\1|<\\2>|\\3 |') %>%
paste0(collapse = '\n') %>% cat
}
| 252 | mit |
4ce7c4a72d4c02c78924493f701141ffadc8bf1e | gbasulto/mvdeconvolution | R/imported.R | #' @import reshape2 dplyr ggplot2 mvtnorm
NULL
## @importFrom ggplot2 qplot
| 81 | mit |
8960948b11b862338188ac7c753a9e70d0d05cf6 | gvlproject/tools-iuc | tools/scater/scater-manual-filter.R | #!/usr/bin/env Rscript
# Manually filter SingleCellExperiment with user-defined parameters
# Load optparse we need to check inputs
library(optparse)
library(workflowscriptscommon)
library(LoomExperiment)
library(scater)
# parse options
option_list = list(
make_option(
c("-i", "--input-loom"),
action = "stor... | 2,565 | mit |
2a6383931a5b56e76a61f44ae00b51cc27dd1db5 | polde-live/getdata | q3/q3.R | # quiz 3
# question 1
u <- url("https://d396qusza40orc.cloudfront.net/getdata%2Fdata%2Fss06hid.csv")
d <- read.csv(u)
# ACR == 3: House on ten or more acres
# AGS == 6: $10000+
agricultureLogical <- d$ACR == 3 & d$AGS == 6
head(d[which(agricultureLogical),])
# question 2
install.packages("jpeg")
library(jpeg)
u... | 983 | unlicense |
942ef119eed42dfcbf8abf73f56490335b6cf429 | iliastsergoulas/shinyapps | sector/en/honey_production_minagric/app.R | # Data: Honey production based on data by Greek Ministry of Agricultural Production and Food
# This R script is created as a Shiny application to process data
# from Hellenic Ministry of Agricultural Development and Food and create plots and maps.
# The code is available under MIT license, as stipulated in https://git... | 5,895 | mit |
97037338f07ae5b2a99e5eacaf22669cf145b909 | elahi/bright_spots | R/BS_resFactors_examples.R | #################################################
# O'Leary et al. 2015
# Bright spots of hope: resilience of nearshore
# marine ecosystems to climatic impacts
# Prepare expert examples data
# (to plot factors that promote and prevent resilience)
# Author: Robin Elahi
# Date: 151211
##################################... | 4,882 | mit |
3c8e14b06af26b790af9383618e66ef0b7d1b767 | marcianito/UmbrellaEffect | R/convert_gravity_response.R | #' @title Convert gravity data
#'
#' @description Converts gravity data from outside of the building to the gravity response
#' below the building. This is done multiplying with factors 1 & 2, both
#' obtained as a consequence of dominant hydrological scenario, SG position and SG building size.
#'
#' @param gravity_inp... | 1,756 | gpl-3.0 |
24d5bac800b506d730e8965e5568bd02b3c5ad1d | jlp2duke/EnsCat | Runoflowdimension.R | # Numerical analysis via R on low-dimensioal
#########################
library(EnsCat)
#########################
#########################
#########################
#########################
###### Run on Zoo data
#########################
#########################
#########################
data("zoo")
DisALzoo0<... | 2,381 | gpl-3.0 |
def46d8c246d0332d9fdbf8ba6a86f746da6e3b2 | earlbellinger/asteroseismology | forward/profile_interval.R | #### Determine how often a profile should be written. Also returns max year.
#### Author: Earl Bellinger ( bellinger@mps.mpg.de )
#### Stellar predictions & Galactic Evolution Group
#### Max-Planck-Institut fur Sonnensystemforschung
DF <- read.table('LOGS/history.data', skip=5, header=1)
decreasing_L <- which(diff... | 1,027 | gpl-2.0 |
c4a97456a13fa105b6e6b8d57fc114d82f91d326 | hpiwowar/jdap | src/_plotLikert2.R |
responses <- c("Strongly Agree","Agree","Somewhat Agree","Somewhat Disagree","Disagree","Strongly Disagree") # from top to bottom
library(reshape2)
x <- melt(d, measure.vars=c('Q4','Q5','Q17','Q21','Q22'))
p <- plot_likert(x, response='value', var_x='PolicyAdoptedAtPublication', var_facet="variable", response_order=... | 3,547 | mit |
32d02d499a134ceff27152d1622c9b1cf12d7888 | earlbellinger/asteroseismology | mixmode/animate.R | #### Animate asteroseismological quantities across an evolutionary track
#### Author: Earl Bellinger ( bellinger@mps.mpg.de )
#### Department of Astronomy, Yale University;
#### Stellar Ages & Galactic Evolution Group,
#### Max-Planck-Institut fur Sonnensystemforschung
library(parallel)
library(parallelMap)
li... | 31,125 | gpl-2.0 |
453bed5443ec17f93a2b12f8fb1f2ac83d0167e2 | eugenebell/R-scripts | R-samples/Chemical-data/corr.R | corr <- function(directory, threshold = 0) {
## 'directory' is a character vector of length 1 indicating
## the location of the CSV files
## 'threshold' is a numeric vector of length 1 indicating the
## number of completely observed observations (on all
## variables) required to compute the correlation bet... | 970 | apache-2.0 |
20a251bf4a26eb70dad07a2093d39b7fd6cfb907 | Sage-Bionetworks/SynapseShinyFacetedSearch | ui.R |
# This is the user-interface definition of a Shiny web application.
# You can find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com
#
library(shiny)
shinyUI(
fluidPage(
title = 'Faceted Data Search',
mainPanel(
tabsetPanel(
tabPanel("All",
... | 377 | mit |
20a251bf4a26eb70dad07a2093d39b7fd6cfb907 | thomasyu888/beatAMLFacet | ui.R |
# This is the user-interface definition of a Shiny web application.
# You can find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com
#
library(shiny)
shinyUI(
fluidPage(
title = 'Faceted Data Search',
mainPanel(
tabsetPanel(
tabPanel("All",
... | 377 | mit |
c30dacade377840e151e5a210d06466748498087 | neuroconductor/extrantsr | R/reg_flip.R | #' @title Flip Image with Registration
#'
#' @description This function performs registration to a template
#' using ANTsR and will run \code{\link{fslswapdim}}
#' @param t1 filename (or nifti objects) of T1 image
#' @param register Register image to template file
#' @param native If images are registered, should the n... | 11,942 | gpl-3.0 |
05e06083596b876c83055a0bbb48b169ccbfea1c | gilestrolab/rethomics | rethomics/R/sleep.R | #@include
NULL
#' Determines whether an animal is asleep
#'
#' This function uses a motion classifier to first decide whether an animal is moving during a given time window.
#' Then, it defines sleep as contiguous immobility for a minimal duration.
#'
#' @param data the data (i.e a data.table) from a \emph{single} re... | 13,878 | gpl-3.0 |
f58b5e91fdc7f6d894c08311747d74c053f3797d | luiscape/hdxscraper-who-gar-api | scripts/R/helpers/sw_status.R | ## Functions to manipulate the status of
## ScraperWiki boxes.
library(RCurl)
changeSwStatus <- function(type = NULL, message = NULL, verbose = F) {
if (!is.null(message)) { content = paste("type=", type, "&message=", message, sep="") }
else content = paste("type=", type, sep="")
curlPerform(postfields = conten... | 424 | mit |
c30dacade377840e151e5a210d06466748498087 | muschellij2/extrantsr | R/reg_flip.R | #' @title Flip Image with Registration
#'
#' @description This function performs registration to a template
#' using ANTsR and will run \code{\link{fslswapdim}}
#' @param t1 filename (or nifti objects) of T1 image
#' @param register Register image to template file
#' @param native If images are registered, should the n... | 11,942 | gpl-3.0 |
e7f0af72a33c62f4b0abd878ea932f07e4da5f9d | CartwrightLab/Cavefish2017 | figures/fig-newgrid-k.R | #!/usr/bin/Rscript --vanilla
#setup figure
scriptname = sub("^--file=",'',grep("^--file=",commandArgs(),value=TRUE)[1])
pdfname = sub("\\.[^.]*$", ".pdf", scriptname)
library(extrafont)
library(RColorBrewer)
library(reshape2)
library(ggplot2)
bcz = brewer.pal(10,"RdYlBu")
keylevels = seq(0,1,length.out=length(bcz)+1)... | 5,368 | mit |
2c578fdfc0b87d5409790ce075e48eb4d72170d8 | douglasgscofield/readGenalex | R/old/is.genalex.R | #' Check to see if \code{data.frame} was created by the \code{readGenalex}
#' package
#'
#' Check to see if \code{data.frame} was created by the \code{readGenalex}
#' package. It specifically checks that the \code{genetic.data.format}
#' attribute of the input \code{data.frame} is \code{"genalex"}.
#'
#'
#' @param ... | 1,144 | lgpl-3.0 |
636396da6028279d61bd03f1b4dbb31ea5b51f14 | greatgray/scorecard | R/strength_ROC.R | #' Creates a ranking of rate of change representing strength of asset returns.
#' Uses the \code{TTR::ROC} function for rate-of-change value.
#' Applies the \code{TTR::runSD} running standard deviations.
#' Computes strength as \code{strength <- roc / rd}.
#' Uses the discrete ROC type.
#' @param x price history as XTS... | 1,000 | mit |
7265263a4a02d1c30234693ab00cb90d9cde913a | michalkurka/h2o-3 | h2o-r/tests/testdir_algos/sharedtree/runit_feature_frequencies.R | setwd(normalizePath(dirname(R.utils::commandArgs(asValues=TRUE)$"f")))
source("../../../scripts/h2o-r-test-setup.R")
test.feature_frequencies <- function() {
prostate_hex <- h2o.importFile(locate('smalldata/testng/prostate.csv'))
prostate_hex$CAPSULE <- as.factor(prostate_hex$CAPSULE)
prostate_hex$ID <- ... | 1,109 | apache-2.0 |
7265263a4a02d1c30234693ab00cb90d9cde913a | h2oai/h2o-3 | h2o-r/tests/testdir_algos/sharedtree/runit_feature_frequencies.R | setwd(normalizePath(dirname(R.utils::commandArgs(asValues=TRUE)$"f")))
source("../../../scripts/h2o-r-test-setup.R")
test.feature_frequencies <- function() {
prostate_hex <- h2o.importFile(locate('smalldata/testng/prostate.csv'))
prostate_hex$CAPSULE <- as.factor(prostate_hex$CAPSULE)
prostate_hex$ID <- ... | 1,109 | apache-2.0 |
358a1116aab4863e8c09ce24d8ce7299793ed22f | scossin/IMthesaurusANSM | R/062015/R/thesaurus062015.R | ##### Parsing le thesaurus de juin 2015
library(methods)
source("../../parsing_POO_thesaurus.R")
test <- new(Class = "Thesaurus",fichier_thesaurus_txt = "../TXT/thesaurus_2015.txt",
fichier_mol_seules_csv = "../CSV/mol_thesaurus_seules2015.csv"
,fichier_mol_famille_csv="../CSV/mol_famille_thesa... | 1,524 | gpl-3.0 |
121f7299cf6ea47a2e5a33297d577f5fbabe6bc8 | chitly852456/SeniorProject_Python | graph_similar/ui.R | library(shiny)
shinyUI(fluidPage(
titlePanel("Graph"),
plotOutput("graphPlot",height="800px")
)) | 100 | mit |
d2409a28d8bd7d0ef804413ba3deae166215b826 | acz-icm/coansys | document-similarity/document-similarity-logic/src/main/R/03.read_results-num-of-sims.R | vector_len <- read.csv("~/vector_len.csv", header=F)
vector_len$V2 <- log10(vector_len$V2)
#require('ggplot')
plot(vector_len)
data_type = "sim"
sourcePath <- paste("/home/pdendek/icm_kod/Projects/CoAnSys/document-similarity/document-similarity-logic/src/main/resources/rd/number_of_docs_with_given_",data_type,"/",se... | 1,454 | agpl-3.0 |
d2409a28d8bd7d0ef804413ba3deae166215b826 | CeON/CoAnSys | document-similarity/document-similarity-logic/src/main/R/03.read_results-num-of-sims.R | vector_len <- read.csv("~/vector_len.csv", header=F)
vector_len$V2 <- log10(vector_len$V2)
#require('ggplot')
plot(vector_len)
data_type = "sim"
sourcePath <- paste("/home/pdendek/icm_kod/Projects/CoAnSys/document-similarity/document-similarity-logic/src/main/resources/rd/number_of_docs_with_given_",data_type,"/",se... | 1,454 | agpl-3.0 |
d2409a28d8bd7d0ef804413ba3deae166215b826 | kuraju/CoAnSys | document-similarity/document-similarity-logic/src/main/R/03.read_results-num-of-sims.R | vector_len <- read.csv("~/vector_len.csv", header=F)
vector_len$V2 <- log10(vector_len$V2)
#require('ggplot')
plot(vector_len)
data_type = "sim"
sourcePath <- paste("/home/pdendek/icm_kod/Projects/CoAnSys/document-similarity/document-similarity-logic/src/main/resources/rd/number_of_docs_with_given_",data_type,"/",se... | 1,454 | agpl-3.0 |
d2409a28d8bd7d0ef804413ba3deae166215b826 | pdendek/CoAnSys | document-similarity/document-similarity-logic/src/main/R/03.read_results-num-of-sims.R | vector_len <- read.csv("~/vector_len.csv", header=F)
vector_len$V2 <- log10(vector_len$V2)
#require('ggplot')
plot(vector_len)
data_type = "sim"
sourcePath <- paste("/home/pdendek/icm_kod/Projects/CoAnSys/document-similarity/document-similarity-logic/src/main/resources/rd/number_of_docs_with_given_",data_type,"/",se... | 1,454 | agpl-3.0 |
47a11cedc7eb2f1cbc8aa41500e2567fc28d5725 | Lukaschen1986/rinds | R/utils.R |
.installPkg <- function(pkg, lib.loc, install, ...) {
tmp.load <- FALSE
eval(parse(text = paste("tmp.load <- suppressWarnings(require(",
pkg, ", lib.loc = '", lib.loc,
"', warn.conflicts = FALSE))", sep = "")))
tmp.calls <- as.list(match.call())
tmp.calls[[1]] <- NULL
tmp.calls[["pkg... | 533 | lgpl-3.0 |
47a11cedc7eb2f1cbc8aa41500e2567fc28d5725 | snowdj/rinds | R/utils.R |
.installPkg <- function(pkg, lib.loc, install, ...) {
tmp.load <- FALSE
eval(parse(text = paste("tmp.load <- suppressWarnings(require(",
pkg, ", lib.loc = '", lib.loc,
"', warn.conflicts = FALSE))", sep = "")))
tmp.calls <- as.list(match.call())
tmp.calls[[1]] <- NULL
tmp.calls[["pkg... | 533 | lgpl-3.0 |
47a11cedc7eb2f1cbc8aa41500e2567fc28d5725 | lijian13/rinds | R/utils.R |
.installPkg <- function(pkg, lib.loc, install, ...) {
tmp.load <- FALSE
eval(parse(text = paste("tmp.load <- suppressWarnings(require(",
pkg, ", lib.loc = '", lib.loc,
"', warn.conflicts = FALSE))", sep = "")))
tmp.calls <- as.list(match.call())
tmp.calls[[1]] <- NULL
tmp.calls[["pkg... | 533 | lgpl-3.0 |
b57d162db95418db12ae26520c59fa9357a5d409 | vmikk/metagMisc | R/abbreviate_taxa_names.R |
#' @title Abbreviate taxa names
#' @param names Character vector of species names
#' @param nlet Number of letters to take from genus-species parts
#' @param totl Number of letters in the final abbreviation
#' @param sep Which separator to use for genus-species case (default is underscore)
#' @param seconditem Logical... | 1,939 | mit |
4029baa214ef5b9eec5a315e21c2afccb5a3aa41 | cemalley/ADRN-EH-Project | Genotyping/pca_with_ref.R |
rm(list=ls())
library(psy)
dat1=read.table("ADRN_499_plus_ref_CAAPA_MDS_data_smartPCA_clean_markers_04-16-14.txt", header=T, stringsAsFactors=F)
m11=mean(dat1$PC2)
s11=sd(dat1$PC2)
m12=mean(dat1$PC3)
s12=sd(dat1$PC3)
mycol1=c("blue","red","green","coral")
pdf("ADRN_plot_CAAPA_MDS_PCA_with_ref_clean_markers_PC2vsPC... | 1,517 | gpl-3.0 |
841c727cdf1fea5f5f8308cc06c66f673c9cdea6 | privefl/mySO | vec-runif.R | lower <- c(0, 1, 2.5, 5, 12, 26, 40)
upper <- c(lower[-1], 100)
E <- data.frame(ACCNS = sample(lower, 50, replace = TRUE))
ind <- match(E$ACCNS, lower)
E$ACCNSrandom <- runif(length(ind), lower[ind], upper[ind])
E
| 216 | gpl-3.0 |
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