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 |
|---|---|---|---|---|---|
3321e7219bc32b1795f68ba2743860f2bd00deaf | shengqh/ngsperl | lib/CQS/mapPercentage.R | options(bitmapType='cairo')
# TODO: Add comment
#
# Author: Quanhu Sheng
###############################################################################
resultFile<-outFile
readFileList<-parSampleFile1
require(XML)
library(ggplot2)
readFiles<-read.delim(readFileList,header=F,as.is=T)
samples<-unique(... | 2,452 | apache-2.0 |
be7291076d3ae44483620c8079a486ed8b14e9d0 | jhchung/geneARTP | R/calculate_rank_statistic.R | #' Calculate rank statistic
#'
#' \deqn{r_i = rank of gene_i / K}
#'
#' Where K = total number of genes
#'
#' @param gene_pvalues \code{data.frame} containing gene name and p-value
#' @param pvalue_col \code{character} or \code{integer} defining the column
#' containing p-values
#' @return \code{data.frame} co... | 766 | mit |
12c86a8b209370517cef772045d17d59500f7ea7 | WMBEdmands/MetMSLine | R/pcaClustId.R | #' Identify clusters in a PCA plot from a list of co-variates using PAM clustering.
#'
#' @description attempts to the identify clusters in a pca from a data frame
#' of covariates, using partitioning around the medoid clustering.
#'
#' @param pcaResult a \code{\link{pcaRes}} class object
#' @param peakTable optiona... | 6,958 | gpl-2.0 |
c4b283c0e081d4cca52d85822523a1aa139e1bb3 | ISRICWorldSoil/SoilGrids250m | grids/DAAC/worldmap_DAAC.R | ## Average soil and sedimentary-deposit thickness http://dx.doi.org/10.3334/ORNLDAAC/1304
## Cite as: Pelletier, J.D., P.D. Broxton, P. Hazenberg, X. Zeng, P.A. Troch, G. Niu, Z.C. Williams, M.A. Brunke, and D. Gochis. 2016. Global 1-km Gridded Thickness of Soil, Regolith, and Sedimentary Deposit Layers. ORNL DAAC, Oak... | 698 | gpl-2.0 |
c29d07d8ccd469d4e85c82f7acdf5531fab2a88c | adam-erickson/gapfraction | R/P.pdn.R | #' Point-density-normalized Gap Fraction, Effective LAI, and ACI
#'
#' This function implements Erickson's point-density-normalized gap fraction along with effective LAI and ACI algorithms
#' @param las Path or name of LAS file. Defaults to NA.
#' @param pol.deg Resolution of polar window in degrees. Defaults to 5.
#' ... | 8,623 | apache-2.0 |
d0c7fc6d3b63859027555701977dfaeedf94c6a5 | kmillar/rho | src/extra/testr/filtered-test-suite/psigamma/tc_psigamma_1.R | expected <- eval(parse(text="c(Inf, Inf, Inf, Inf, Inf, 1.64493406684823, 0.644934066848226, 103.345879033255, 14.9576128448637, Inf, 103.063781426486, 28.2660702011406, 14.7693758451323, 10.5916883623902, 9.53924664498912, 10.5700248636461, 14.7259121609613, 28.200530152194, 102.975743610084, Inf, 102.944875362276, 28... | 1,736 | gpl-2.0 |
ac18dd0ddd54a84af7f8ecb63982325caf00ad2d | lenz99-/svmod | exec/sim_mappingExplorer.R | #!/usr/bin/env Rscript
#
# mkuhn, 20140718
# A script to explore patient mappings from a simulation run.
# It produces graphical illustration of clipped read pattern at simulated SV-positions
DEV_MODE <- TRUE
library(logging); basicConfig()
if (isTRUE(DEV_MODE)){
if (require(devtools))
dev_mode(on = TRUE)
... | 2,783 | gpl-3.0 |
d0c7fc6d3b63859027555701977dfaeedf94c6a5 | cxxr-devel/cxxr | src/extra/testr/filtered-test-suite/psigamma/tc_psigamma_1.R | expected <- eval(parse(text="c(Inf, Inf, Inf, Inf, Inf, 1.64493406684823, 0.644934066848226, 103.345879033255, 14.9576128448637, Inf, 103.063781426486, 28.2660702011406, 14.7693758451323, 10.5916883623902, 9.53924664498912, 10.5700248636461, 14.7259121609613, 28.200530152194, 102.975743610084, Inf, 102.944875362276, 28... | 1,736 | gpl-2.0 |
d0c7fc6d3b63859027555701977dfaeedf94c6a5 | krlmlr/cxxr | src/extra/testr/filtered-test-suite/psigamma/tc_psigamma_1.R | expected <- eval(parse(text="c(Inf, Inf, Inf, Inf, Inf, 1.64493406684823, 0.644934066848226, 103.345879033255, 14.9576128448637, Inf, 103.063781426486, 28.2660702011406, 14.7693758451323, 10.5916883623902, 9.53924664498912, 10.5700248636461, 14.7259121609613, 28.200530152194, 102.975743610084, Inf, 102.944875362276, 28... | 1,736 | gpl-2.0 |
d0c7fc6d3b63859027555701977dfaeedf94c6a5 | kmillar/cxxr | src/extra/testr/filtered-test-suite/psigamma/tc_psigamma_1.R | expected <- eval(parse(text="c(Inf, Inf, Inf, Inf, Inf, 1.64493406684823, 0.644934066848226, 103.345879033255, 14.9576128448637, Inf, 103.063781426486, 28.2660702011406, 14.7693758451323, 10.5916883623902, 9.53924664498912, 10.5700248636461, 14.7259121609613, 28.200530152194, 102.975743610084, Inf, 102.944875362276, 28... | 1,736 | gpl-2.0 |
d0c7fc6d3b63859027555701977dfaeedf94c6a5 | rho-devel/rho | src/extra/testr/filtered-test-suite/psigamma/tc_psigamma_1.R | expected <- eval(parse(text="c(Inf, Inf, Inf, Inf, Inf, 1.64493406684823, 0.644934066848226, 103.345879033255, 14.9576128448637, Inf, 103.063781426486, 28.2660702011406, 14.7693758451323, 10.5916883623902, 9.53924664498912, 10.5700248636461, 14.7259121609613, 28.200530152194, 102.975743610084, Inf, 102.944875362276, 28... | 1,736 | gpl-2.0 |
d0c7fc6d3b63859027555701977dfaeedf94c6a5 | ArunChauhan/cxxr | src/extra/testr/filtered-test-suite/psigamma/tc_psigamma_1.R | expected <- eval(parse(text="c(Inf, Inf, Inf, Inf, Inf, 1.64493406684823, 0.644934066848226, 103.345879033255, 14.9576128448637, Inf, 103.063781426486, 28.2660702011406, 14.7693758451323, 10.5916883623902, 9.53924664498912, 10.5700248636461, 14.7259121609613, 28.200530152194, 102.975743610084, Inf, 102.944875362276, 28... | 1,736 | gpl-2.0 |
8ae311051bcff8a392971cf45f8c98fea3adb25d | SchlossLab/Schloss_Cluster_PeerJ_2015 | code/closed_ref_analysis.R | parse_sc_line <- function(line){
split_line <- unlist(strsplit(line, "\t"))
refrence <- split_line[1]
split_line <- split_line[-1]
n_repeats <- length(split_line)
references <- rep(refrence, n_repeats)
names(references) <- split_line
return(references)
}
split_line <- function(line){
sub_vector_names <- unlist... | 4,948 | mit |
7a3630e85dad47e8ceeb3829a09eda9f1627c85e | pbieberstein/Triathlon_estimator | rough_math.R | in_sec <- function(period_time) {
period_to_seconds(period_time)
}
library(lubridate)
# Swim time
#swim_pace = seconds_to_period(117) # sec /100m 1.57 min/100m
swim_pace <- period(minute=1,second=57) # sec /100m 1.57 min/100m
swim_time <-period_to_seconds(swim_pace)*15
swim_time <- seconds_to_period(swim_ti... | 975 | mit |
382768c187451f928a6698a72a2b0e96c36a744e | bfatemi/ninjaR | data-raw/encrypt_config.R | library(yaml)
library(sodium)
##
## Set & save password to encrypt config list and hashed pwd check
##
set_new_encrypted <- function(pwd = NULL, run_build=TRUE){
if(is.null(pwd))
pwd <- rstudioapi::askForPassword("Save new password:")
if(!is.null(pwd)){
##
## save password just receieved
##
ke... | 837 | gpl-2.0 |
c76ed0368a4562c55c54ba1a6242457a9be591bf | Tychobra/shiny-insurance-examples | freq-sev-claims-sim/ui.R | fluidPage(
introjsUI(),
theme = shinytheme("spacelab"),
includeCSS("ractuary-style.css"),
fluidRow(
br(),
headerPanel(
tags$div(
a(
img(
src = "https://res.cloudinary.com/dxqnb8xjb/image/upload/v1499450435/logo-blue_hnvtgb.png",
width = 50
),
... | 5,661 | mit |
188cfc59570b1c1e1f183d844f440c57b6267c76 | EccRiley/Riley | R/Rnetscore.R | Rnetscore <- function(x, percent = FALSE) {
x <- na.omit(x)
good <- length(x[x == 1])
bad <- length(x[x == -1])
neutral <- length(x[x == 0])
total <- sum(good, bad, neutral)
res <- ((good - bad) / total)
if (percent) {
return(res*100)
} else
return(res)
}
Rnet <- functio... | 470 | agpl-3.0 |
59b60249e947425ebef96b7315397358c019251b | ikosmidis/brRasch | tests/testthat/notest_legacy.R | context("LSAT data")
library(ltm)
data(LSAT)
### 2PL
set.seed <- 1
SubjectsIncluded <- seq.int(nrow(LSAT))
ItemsIncluded <- seq.int(5)
Stest <- length(SubjectsIncluded)
Itest <- length(ItemsIncluded)
TestData <- LSAT[SubjectsIncluded, ItemsIncluded]
dimTest <- 1
alphasTest <- runif(Itest, -1, 1)
betasTest <- repli... | 2,915 | gpl-3.0 |
0333d69b0d9e2325176031ef677f9e72276d3e6f | UCanCompBio/Avoidance | scripts/R-scripts/Figure_2.Supp.3.R | require("car")
require("RColorBrewer")
explainedR2=read.csv(file="/home/suu13/projects/antisense/Avoidance_Git/files/Supplementary_file_5.csv",header = T)
explainedR2=explainedR2[with(explainedR2,order(Type,decreasing = T)),]
exporder=c("GFP reporter (n = 52(13))","GFP reporter (n = 154)","sfGFP-mCherry (n = 14234)... | 2,542 | mit |
bc3c0713593e64c66ce1aadcfc915b72065e6fbd | serendio-labs/data-preprocessing-r | premod 1.1/R/code.R |
#'@title Anderson-Darling Normality Test (norm.p)
#'@description Test for normality
#'@details Anderson-Darling Normality Test is used to determine whether a set of observations follows ‘Normal Distribution’. The assumption of ‘Normality’ is widely used in Statistics in the areas of Inferential Statistics, Paramet... | 15,014 | apache-2.0 |
480adb00eb1041f06824cc67fa1350f9bc9676d5 | luiscape/hdxscraper-noaa | app/refresh_countries.R | #
# REFRESH COUNTRIES --------------
#
# This script will refresh the country
# table in the database. That table is
# important because it records the state
# of when each country data was collected.
#
# ---------------------------------------
#
library(sqldf)
library(rnoaa)
library(countrycode)
#
# API TOKEN... | 1,286 | mit |
df87f0e33e1e2dfd3bec040a1c961711c42dcf20 | EnderDom/ThesisRscripts | src/pesticide_usage/pest.R | #Molluscides
y_data1 <- c(
5.6299597646,
5.6358846809,
5.6636632409,
5.689769553,
6.0196591308,
6.0213898554,
5.7015014975,
5.7441998541,
5.8074227193,
5.8190521148,
6.1546798484,
6.1547437177,
6.0829583358,
6.0843217032,
5.8207083879,
5.8259905284,
6.0110563441,
6.0166807495,
6.2594091809,
6.2717665856,
6.0474189591,
... | 1,411 | gpl-3.0 |
ff2ba53164a67251953bbbc91be581ef98e455b7 | radfordneal/pqR | src/library/tcltk/R/unix/zzzstub.R | # File src/library/tcltk/R/unix/zzzstub.R
# Part of the R package, http://www.R-project.org
#
# 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 version 2 of the License, or
# (at your... | 814 | gpl-2.0 |
10e2421472bea6032325ca778a460395f3ff0fdd | STAT-ATA-ASU/STT2810HonorsClassRepo | FirstDay/junk.R | HeightIn <- c(65, 66, 69.5, 70, 62)
mean(HeightIn)
| 51 | mit |
6c9ee5f4a36e7ca3275e71f5cadc3c8f54a5981f | selective-inference/R | tests/randomized/test_randomized.R | library(MASS)
library(selectiveInference)
library(glmnet)
test_randomized = function(seed=1, outfile=NULL, type="partial", loss="ls", lambda_frac=0.7,
nrep=50, n=200, p=800, s=30, rho=0.){
snr = sqrt(2*log(p)/n)
set.seed(seed)
construct_ci=TRUE
penalty_factor = rep(1, p)
... | 4,084 | gpl-2.0 |
6c9ee5f4a36e7ca3275e71f5cadc3c8f54a5981f | jonathan-taylor/R-selective | tests/randomized/test_randomized.R | library(MASS)
library(selectiveInference)
library(glmnet)
test_randomized = function(seed=1, outfile=NULL, type="partial", loss="ls", lambda_frac=0.7,
nrep=50, n=200, p=800, s=30, rho=0.){
snr = sqrt(2*log(p)/n)
set.seed(seed)
construct_ci=TRUE
penalty_factor = rep(1, p)
... | 4,084 | gpl-2.0 |
6c9ee5f4a36e7ca3275e71f5cadc3c8f54a5981f | jonathan-taylor/R | tests/randomized/test_randomized.R | library(MASS)
library(selectiveInference)
library(glmnet)
test_randomized = function(seed=1, outfile=NULL, type="partial", loss="ls", lambda_frac=0.7,
nrep=50, n=200, p=800, s=30, rho=0.){
snr = sqrt(2*log(p)/n)
set.seed(seed)
construct_ci=TRUE
penalty_factor = rep(1, p)
... | 4,084 | gpl-2.0 |
6c9ee5f4a36e7ca3275e71f5cadc3c8f54a5981f | selective-inference/R-software | tests/randomized/test_randomized.R | library(MASS)
library(selectiveInference)
library(glmnet)
test_randomized = function(seed=1, outfile=NULL, type="partial", loss="ls", lambda_frac=0.7,
nrep=50, n=200, p=800, s=30, rho=0.){
snr = sqrt(2*log(p)/n)
set.seed(seed)
construct_ci=TRUE
penalty_factor = rep(1, p)
... | 4,084 | gpl-2.0 |
10e2421472bea6032325ca778a460395f3ff0fdd | STAT-ATA-ASU/STT2810HonorsClassRepo | docs/FirstDay/junk.R | HeightIn <- c(65, 66, 69.5, 70, 62)
mean(HeightIn)
| 51 | mit |
e4f4790378a43bbc050e457d975add270c277669 | willvieira/birdDist | script/dataCleaning/bird_SDM_cleaning.R | #####################################################
##
## change multiple bird script to combined bird csv
##
####################################################
#fix MOCH
mountainchickadee <-read.table("C:\\Users\\anarahlin\\Desktop\\birdSDMcoordinates\\mountain_chick_csv.csv", header = TRUE, sep = ",")
head(moun... | 2,008 | mit |
27b0e0c5c00f563ab7572a5696c2dd09a8c8611d | hlin09/renjin | packages/methods/src/main/R/refClass.R | # File src/library/methods/R/refClass.R
# Part of the R package, http://www.R-project.org
#
# 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 version 2 of the License, or
# (at your o... | 46,140 | gpl-3.0 |
f48abe0b81fa56e21315c4eca022db97d5588686 | stineb/nn_fluxnet2015 | analyse_modobs.R | analyse_modobs <- function( mod, obs,
plot.fil=NA,
plot.xlab="observed",
plot.ylab="modelled",
xlim=NA,
ylim=NA,
plot.title=NA,
... | 3,306 | gpl-3.0 |
82dcc52139e6e3f80786336fb37e696f7594d3c5 | DistanceDevelopment/mrds | R/mrds-package.R | #' Mark-Recapture Distance Sampling (mrds)
#'
#' This package implements mark-recapture distance sampling
#' methods as described in D.L. Borchers, W. Zucchini and Fewster,
#' R.M. (1988), "Mark-recapture models for line transect surveys",
#' Biometrics 54: 1207-1220. and Laake, J.L. (1999) "Distance sampli... | 50,855 | gpl-3.0 |
5a387e763fa92caec423c3de110470e1262f5e8a | paigejo/M9 | predictionsTMB.R | # this script contains functions for generating predictions using TMB parameterizations
# function for computing predictive distribution given subsidence data. Note that
# the subsidence data should only be the data from one earthquake. The returned
# values relating to beta correspond to log zeta. For instance, ... | 26,682 | gpl-2.0 |
3253da7b24504c79a0e1b5819b0c57026561cd91 | dankelley/oce-issues | 05xx/513/513.R | ## Landsat 8
library(oce)
d <- read.landsat('/data/archive/landsat/LC80130272014148LGN00', band='tirs1')
d <- decimate(d, by=33) # because temp plot does not decimate and is SLOW
#options(oceDebug=2) # get debugging in [["temperature"]]
plot(d, band="temperature")
| 265 | gpl-2.0 |
3211a0e5daa258ed02df49cb2cbed5ab83782208 | hartwigmedical/hmftools | linx/src/main/resources/r/fusionPlot.R | library(ggplot2)
library(tidyr)
library(dplyr)
library(cowplot)
library(magick)
theme_set(theme_bw())
# Parse the arguments
args <- commandArgs(trailing=T)
clusterProteinDomainPath <- args[1]
clusterFusedExonPath <- args[2]
circosPicturePath <- args[3]
fontSize <- as.numeric(args[4])
fusionLegendRows <- as.numeric(a... | 6,923 | gpl-3.0 |
5afd9e70e7a89345a8292f59b880384c719d3acf | jakemkc/exposome_variability | src/Figure4_corr_within_class.R | ## Nov 28 2016
## Goal: "intra category" correlation
rm(list=ls()) # clear workspace; # ls() # list objects in the workspace
cat("\014") # same as ctrl-L
# Load data (Total lipid and creatinine adjusted spearman r)
load("results/corr_chems_heatmap__resid_lipid_creat_adj_v2.Rdata")
# ******** -----
# A. Extract s... | 14,316 | mit |
d0989c53236c07eb4a5cdf61420ffda293c57fa9 | cowboysmall/jhudatascience | devdataprod/project1/titanic_app/ui.R | library(shiny)
shinyUI(
fluidPage(
titlePanel("Surviving the Titanic"),
sidebarLayout(
sidebarPanel(
p('Will You Survive? Select relevant details from the options below and see if you will survive.'),
br(),
br(),
selectInpu... | 5,918 | mit |
5f42ce74eefadd4c1e18b4cb19a2ba65458a7b7b | andrewdefries/andrewdefries.github.io | FDA_Pesticide_Glossary/6-chloro-3-phenyl-4-.R | library("knitr")
library("rgl")
#knit("6-chloro-3-phenyl-4-.Rmd")
#markdownToHTML('6-chloro-3-phenyl-4-.md', '6-chloro-3-phenyl-4-.html', options=c("use_xhml"))
#system("pandoc -s 6-chloro-3-phenyl-4-.html -o 6-chloro-3-phenyl-4-.pdf")
knit2html('6-chloro-3-phenyl-4-.Rmd')
| 276 | mit |
f46177e86754ceb579ff78dde4863480c0ab6e68 | glycerine/bigbird | r-3.0.2/src/library/tools/R/sotools.R | # File src/library/tools/R/sotools.R
# Part of the R package, http://www.R-project.org
#
# Copyright (C) 2011-2 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 ver... | 27,025 | bsd-2-clause |
fd5317e08593dcf9b8c65edced8c3a5197614b8b | mhils/shortestpath | tests/testthat/test.aStarSearch.R | context("aStarSearch")
test_that("aStarSearch runs without errors", {
graph <- randomGraph(n=20,euclidean=TRUE)
r <- aStarSearch(graph,"A","K")
})
test_that("aStarSearch finds the minimal distance", {
test_configurations = list(
list(n=2, k=1),
list(n=4, k=2*3/4),
list(n=4, k=2),... | 2,337 | mit |
b443000a9f813b5e88e08427225809c89b0fb4b5 | uds-se/backstage | scripts/cluster_vec.R | require(skmeans)
require(argparse)
require(cluster)
source("utils.R")
parser = ArgumentParser()
parser$add_argument("-u", required=TRUE,dest="ui.file",help="Path to icons")
parser$add_argument("-o", required=TRUE, dest="out.file",help="Path to bin data folder")
parser$add_argument("-m", required=TRUE, dest="model.file"... | 2,526 | gpl-3.0 |
7b1412c1063aefcd57ccb6bfdbeaaaf019ad6050 | Saurabh7/shogun | examples/undocumented/r_static/graphical/svm_classification.R |
C <- 1000;
dims <- 2;
num <- 50;
require(graphics)
#require(lattice)
library('sg')
#uncomment if make install does not work and comment the library("sg") line above
#dyn.load('sg.so')
#sg <- function(...) .External("sg",...,PACKAGE="sg")
#newplot <- get(getOption('device'))
meshgrid <- function(a,b) {
list(
... | 2,097 | mit |
7b1412c1063aefcd57ccb6bfdbeaaaf019ad6050 | jondo/shogun | examples/undocumented/r_static/graphical/svm_classification.R |
C <- 1000;
dims <- 2;
num <- 50;
require(graphics)
#require(lattice)
library('sg')
#uncomment if make install does not work and comment the library("sg") line above
#dyn.load('sg.so')
#sg <- function(...) .External("sg",...,PACKAGE="sg")
#newplot <- get(getOption('device'))
meshgrid <- function(a,b) {
list(
... | 2,097 | gpl-3.0 |
b76796eb6e138c1d9103c7252124778ba972a0b5 | RCura/TimeLineEDB | src/helpers.R | # https://github.com/daattali/advanced-shiny/tree/master/busy-indicator
# Copyright 2016 Dean Attali. Licensed under the MIT license.
# All the code in this file needs to be copied to your Shiny app, and you need
# to call `withBusyIndicatorUI()` and `withBusyIndicatorServer()` in your app.
# You can also include the ... | 2,681 | agpl-3.0 |
7b1412c1063aefcd57ccb6bfdbeaaaf019ad6050 | sperka/shogun | examples/undocumented/r_static/graphical/svm_classification.R |
C <- 1000;
dims <- 2;
num <- 50;
require(graphics)
#require(lattice)
library('sg')
#uncomment if make install does not work and comment the library("sg") line above
#dyn.load('sg.so')
#sg <- function(...) .External("sg",...,PACKAGE="sg")
#newplot <- get(getOption('device'))
meshgrid <- function(a,b) {
list(
... | 2,097 | gpl-3.0 |
7b1412c1063aefcd57ccb6bfdbeaaaf019ad6050 | ratschlab/ASP | examples/undocumented/r_static/graphical/svm_classification.R |
C <- 1000;
dims <- 2;
num <- 50;
require(graphics)
#require(lattice)
library('sg')
#uncomment if make install does not work and comment the library("sg") line above
#dyn.load('sg.so')
#sg <- function(...) .External("sg",...,PACKAGE="sg")
#newplot <- get(getOption('device'))
meshgrid <- function(a,b) {
list(
... | 2,097 | gpl-2.0 |
7b1412c1063aefcd57ccb6bfdbeaaaf019ad6050 | arasuarun/shogun | examples/undocumented/r_static/graphical/svm_classification.R |
C <- 1000;
dims <- 2;
num <- 50;
require(graphics)
#require(lattice)
library('sg')
#uncomment if make install does not work and comment the library("sg") line above
#dyn.load('sg.so')
#sg <- function(...) .External("sg",...,PACKAGE="sg")
#newplot <- get(getOption('device'))
meshgrid <- function(a,b) {
list(
... | 2,097 | gpl-3.0 |
7b1412c1063aefcd57ccb6bfdbeaaaf019ad6050 | cdawei/shogun | examples/undocumented/r_static/graphical/svm_classification.R |
C <- 1000;
dims <- 2;
num <- 50;
require(graphics)
#require(lattice)
library('sg')
#uncomment if make install does not work and comment the library("sg") line above
#dyn.load('sg.so')
#sg <- function(...) .External("sg",...,PACKAGE="sg")
#newplot <- get(getOption('device'))
meshgrid <- function(a,b) {
list(
... | 2,097 | gpl-3.0 |
7b1412c1063aefcd57ccb6bfdbeaaaf019ad6050 | kostajaitachi/shogun | examples/undocumented/r_static/graphical/svm_classification.R |
C <- 1000;
dims <- 2;
num <- 50;
require(graphics)
#require(lattice)
library('sg')
#uncomment if make install does not work and comment the library("sg") line above
#dyn.load('sg.so')
#sg <- function(...) .External("sg",...,PACKAGE="sg")
#newplot <- get(getOption('device'))
meshgrid <- function(a,b) {
list(
... | 2,097 | gpl-3.0 |
7b1412c1063aefcd57ccb6bfdbeaaaf019ad6050 | AzamYahya/shogun | examples/undocumented/r_static/graphical/svm_classification.R |
C <- 1000;
dims <- 2;
num <- 50;
require(graphics)
#require(lattice)
library('sg')
#uncomment if make install does not work and comment the library("sg") line above
#dyn.load('sg.so')
#sg <- function(...) .External("sg",...,PACKAGE="sg")
#newplot <- get(getOption('device'))
meshgrid <- function(a,b) {
list(
... | 2,097 | gpl-3.0 |
106d2901eb612f2f91180cd9d7a91fc38f86bfc3 | mihaiconstantin/chgassesirt | R/ClassEstimatorGRM.R | EstimatorGRM = R6::R6Class("EstimatorGRM",
inherit = Estimator,
# private
private = list(
),
# public
public = list(
initialize = function(data, method) {
super$initialize(data, method)
private$model = "Estimated GRM"
}
)
) # EstimatorGRM | 261 | mit |
7b1412c1063aefcd57ccb6bfdbeaaaf019ad6050 | abhiatgithub/shogun-toolbox | examples/undocumented/r_static/graphical/svm_classification.R |
C <- 1000;
dims <- 2;
num <- 50;
require(graphics)
#require(lattice)
library('sg')
#uncomment if make install does not work and comment the library("sg") line above
#dyn.load('sg.so')
#sg <- function(...) .External("sg",...,PACKAGE="sg")
#newplot <- get(getOption('device'))
meshgrid <- function(a,b) {
list(
... | 2,097 | gpl-3.0 |
106d2901eb612f2f91180cd9d7a91fc38f86bfc3 | mihaiconstantin/simulateirt | R/ClassEstimatorGRM.R | EstimatorGRM = R6::R6Class("EstimatorGRM",
inherit = Estimator,
# private
private = list(
),
# public
public = list(
initialize = function(data, method) {
super$initialize(data, method)
private$model = "Estimated GRM"
}
)
) # EstimatorGRM | 261 | mit |
7b1412c1063aefcd57ccb6bfdbeaaaf019ad6050 | curiousguy13/shogun | examples/undocumented/r_static/graphical/svm_classification.R |
C <- 1000;
dims <- 2;
num <- 50;
require(graphics)
#require(lattice)
library('sg')
#uncomment if make install does not work and comment the library("sg") line above
#dyn.load('sg.so')
#sg <- function(...) .External("sg",...,PACKAGE="sg")
#newplot <- get(getOption('device'))
meshgrid <- function(a,b) {
list(
... | 2,097 | gpl-3.0 |
2ccf1c741ddb91b9079788bd8dfc7cba124a1782 | grailbio/rules_r | tests/packages/exampleC/R/fn.R | # Copyright 2018 The Bazel Authors.
#
# 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 in wr... | 682 | apache-2.0 |
7b1412c1063aefcd57ccb6bfdbeaaaf019ad6050 | rcurtin/shogun | examples/undocumented/r_static/graphical/svm_classification.R |
C <- 1000;
dims <- 2;
num <- 50;
require(graphics)
#require(lattice)
library('sg')
#uncomment if make install does not work and comment the library("sg") line above
#dyn.load('sg.so')
#sg <- function(...) .External("sg",...,PACKAGE="sg")
#newplot <- get(getOption('device'))
meshgrid <- function(a,b) {
list(
... | 2,097 | gpl-3.0 |
7b1412c1063aefcd57ccb6bfdbeaaaf019ad6050 | shangwuhencc/shogun | examples/undocumented/r_static/graphical/svm_classification.R |
C <- 1000;
dims <- 2;
num <- 50;
require(graphics)
#require(lattice)
library('sg')
#uncomment if make install does not work and comment the library("sg") line above
#dyn.load('sg.so')
#sg <- function(...) .External("sg",...,PACKAGE="sg")
#newplot <- get(getOption('device'))
meshgrid <- function(a,b) {
list(
... | 2,097 | gpl-3.0 |
7b1412c1063aefcd57ccb6bfdbeaaaf019ad6050 | chenmoshushi/shogun | examples/undocumented/r_static/graphical/svm_classification.R |
C <- 1000;
dims <- 2;
num <- 50;
require(graphics)
#require(lattice)
library('sg')
#uncomment if make install does not work and comment the library("sg") line above
#dyn.load('sg.so')
#sg <- function(...) .External("sg",...,PACKAGE="sg")
#newplot <- get(getOption('device'))
meshgrid <- function(a,b) {
list(
... | 2,097 | gpl-3.0 |
7b1412c1063aefcd57ccb6bfdbeaaaf019ad6050 | sanuj/shogun | examples/undocumented/r_static/graphical/svm_classification.R |
C <- 1000;
dims <- 2;
num <- 50;
require(graphics)
#require(lattice)
library('sg')
#uncomment if make install does not work and comment the library("sg") line above
#dyn.load('sg.so')
#sg <- function(...) .External("sg",...,PACKAGE="sg")
#newplot <- get(getOption('device'))
meshgrid <- function(a,b) {
list(
... | 2,097 | gpl-3.0 |
7b1412c1063aefcd57ccb6bfdbeaaaf019ad6050 | Ialong/shogun | examples/undocumented/r_static/graphical/svm_classification.R |
C <- 1000;
dims <- 2;
num <- 50;
require(graphics)
#require(lattice)
library('sg')
#uncomment if make install does not work and comment the library("sg") line above
#dyn.load('sg.so')
#sg <- function(...) .External("sg",...,PACKAGE="sg")
#newplot <- get(getOption('device'))
meshgrid <- function(a,b) {
list(
... | 2,097 | gpl-3.0 |
7b1412c1063aefcd57ccb6bfdbeaaaf019ad6050 | youprofit/shogun | examples/undocumented/r_static/graphical/svm_classification.R |
C <- 1000;
dims <- 2;
num <- 50;
require(graphics)
#require(lattice)
library('sg')
#uncomment if make install does not work and comment the library("sg") line above
#dyn.load('sg.so')
#sg <- function(...) .External("sg",...,PACKAGE="sg")
#newplot <- get(getOption('device'))
meshgrid <- function(a,b) {
list(
... | 2,097 | gpl-3.0 |
7b1412c1063aefcd57ccb6bfdbeaaaf019ad6050 | youssef-emad/shogun | examples/undocumented/r_static/graphical/svm_classification.R |
C <- 1000;
dims <- 2;
num <- 50;
require(graphics)
#require(lattice)
library('sg')
#uncomment if make install does not work and comment the library("sg") line above
#dyn.load('sg.so')
#sg <- function(...) .External("sg",...,PACKAGE="sg")
#newplot <- get(getOption('device'))
meshgrid <- function(a,b) {
list(
... | 2,097 | gpl-3.0 |
7b1412c1063aefcd57ccb6bfdbeaaaf019ad6050 | lukw00/shogun | examples/undocumented/r_static/graphical/svm_classification.R |
C <- 1000;
dims <- 2;
num <- 50;
require(graphics)
#require(lattice)
library('sg')
#uncomment if make install does not work and comment the library("sg") line above
#dyn.load('sg.so')
#sg <- function(...) .External("sg",...,PACKAGE="sg")
#newplot <- get(getOption('device'))
meshgrid <- function(a,b) {
list(
... | 2,097 | gpl-3.0 |
7b1412c1063aefcd57ccb6bfdbeaaaf019ad6050 | pavel-odintsov/shogun | examples/undocumented/r_static/graphical/svm_classification.R |
C <- 1000;
dims <- 2;
num <- 50;
require(graphics)
#require(lattice)
library('sg')
#uncomment if make install does not work and comment the library("sg") line above
#dyn.load('sg.so')
#sg <- function(...) .External("sg",...,PACKAGE="sg")
#newplot <- get(getOption('device'))
meshgrid <- function(a,b) {
list(
... | 2,097 | gpl-3.0 |
7b1412c1063aefcd57ccb6bfdbeaaaf019ad6050 | elkingtonmcb/shogun | examples/undocumented/r_static/graphical/svm_classification.R |
C <- 1000;
dims <- 2;
num <- 50;
require(graphics)
#require(lattice)
library('sg')
#uncomment if make install does not work and comment the library("sg") line above
#dyn.load('sg.so')
#sg <- function(...) .External("sg",...,PACKAGE="sg")
#newplot <- get(getOption('device'))
meshgrid <- function(a,b) {
list(
... | 2,097 | gpl-3.0 |
7b1412c1063aefcd57ccb6bfdbeaaaf019ad6050 | JingheZ/shogun | examples/undocumented/r_static/graphical/svm_classification.R |
C <- 1000;
dims <- 2;
num <- 50;
require(graphics)
#require(lattice)
library('sg')
#uncomment if make install does not work and comment the library("sg") line above
#dyn.load('sg.so')
#sg <- function(...) .External("sg",...,PACKAGE="sg")
#newplot <- get(getOption('device'))
meshgrid <- function(a,b) {
list(
... | 2,097 | gpl-3.0 |
a7cf4ce40be3697b0f3e5bcd48ebb534be9c4dd6 | JanMarvin/rstudio | src/cpp/session/modules/SessionClang.R | #
# SessionClang.R
#
# Copyright (C) 2020 by RStudio, PBC
#
# Unless you have received this program directly from RStudio pursuant
# to the terms of a commercial license agreement with RStudio, then
# this program is licensed to you under the terms of version 3 of the
# GNU Affero General Public License. This program i... | 2,216 | agpl-3.0 |
17a7115fa329bbf6f517f3535ce96038a4369edf | DfAC/DataAnalysisAndStatisticalInference | statistics-lab_resources-inference.R | inference <-
function(y, x = NULL,
est = c("mean", "median", "proportion"),
success = NULL, order = NULL,
method = c("theoretical","simulation"),
type = c("ci","ht"),
alternative = c("less","greater","twosi... | 47,101 | gpl-2.0 |
cb0f930305746c0eb3bf107810eea715c2cef636 | ArunChauhan/cxxr | src/extra/testr/filtered-test-suite/POSIXlt2Date/tc_POSIXlt2Date_2.R | expected <- eval(parse(text="structure(c(13823, NA), class = \"Date\")"));
test(id=0, code={
argv <- eval(parse(text="list(structure(list(sec = c(0, NA), min = c(0L, NA), hour = c(0L, NA), mday = c(6L, NA), mon = c(10L, NA), year = c(107L, NA), wday = c(2L, NA), yday = c(309L, NA), isdst = c(0L, -1L)), .Names = c(\... | 510 | gpl-2.0 |
cb0f930305746c0eb3bf107810eea715c2cef636 | kmillar/rho | src/extra/testr/filtered-test-suite/POSIXlt2Date/tc_POSIXlt2Date_2.R | expected <- eval(parse(text="structure(c(13823, NA), class = \"Date\")"));
test(id=0, code={
argv <- eval(parse(text="list(structure(list(sec = c(0, NA), min = c(0L, NA), hour = c(0L, NA), mday = c(6L, NA), mon = c(10L, NA), year = c(107L, NA), wday = c(2L, NA), yday = c(309L, NA), isdst = c(0L, -1L)), .Names = c(\... | 510 | gpl-2.0 |
bbab02e3b1d782a8fe28d465489b2a9d0fb4c833 | seoteam-pro/R-HLOC-App | www/candleStick_orig.R | Read_CSVtoXTS <- function(filename, period = FALSE, tframe = FALSE, sep = ",") {
# ----------
require(xts)
# ----------
#
if (period != FALSE) {
... | 9,310 | gpl-3.0 |
a95f581286bfa2f92666dd937e090c67ad0e7a44 | corybrunson/bitriad | R/triad-tallies.R | #' Triad tallies
#'
#' These functions are called by the full triad census to handle triads of
#' different types using the projection onto actor nodes. The name of each
#' function indicates the number of edges that appear among the three actors of
#' the triad in the projection. (Zero-edge triads do not need to b... | 4,417 | gpl-2.0 |
cb0f930305746c0eb3bf107810eea715c2cef636 | rho-devel/rho | src/extra/testr/filtered-test-suite/POSIXlt2Date/tc_POSIXlt2Date_2.R | expected <- eval(parse(text="structure(c(13823, NA), class = \"Date\")"));
test(id=0, code={
argv <- eval(parse(text="list(structure(list(sec = c(0, NA), min = c(0L, NA), hour = c(0L, NA), mday = c(6L, NA), mon = c(10L, NA), year = c(107L, NA), wday = c(2L, NA), yday = c(309L, NA), isdst = c(0L, -1L)), .Names = c(\... | 510 | gpl-2.0 |
cb0f930305746c0eb3bf107810eea715c2cef636 | krlmlr/cxxr | src/extra/testr/filtered-test-suite/POSIXlt2Date/tc_POSIXlt2Date_2.R | expected <- eval(parse(text="structure(c(13823, NA), class = \"Date\")"));
test(id=0, code={
argv <- eval(parse(text="list(structure(list(sec = c(0, NA), min = c(0L, NA), hour = c(0L, NA), mday = c(6L, NA), mon = c(10L, NA), year = c(107L, NA), wday = c(2L, NA), yday = c(309L, NA), isdst = c(0L, -1L)), .Names = c(\... | 510 | gpl-2.0 |
cb0f930305746c0eb3bf107810eea715c2cef636 | kmillar/cxxr | src/extra/testr/filtered-test-suite/POSIXlt2Date/tc_POSIXlt2Date_2.R | expected <- eval(parse(text="structure(c(13823, NA), class = \"Date\")"));
test(id=0, code={
argv <- eval(parse(text="list(structure(list(sec = c(0, NA), min = c(0L, NA), hour = c(0L, NA), mday = c(6L, NA), mon = c(10L, NA), year = c(107L, NA), wday = c(2L, NA), yday = c(309L, NA), isdst = c(0L, -1L)), .Names = c(\... | 510 | gpl-2.0 |
cb0f930305746c0eb3bf107810eea715c2cef636 | cxxr-devel/cxxr | src/extra/testr/filtered-test-suite/POSIXlt2Date/tc_POSIXlt2Date_2.R | expected <- eval(parse(text="structure(c(13823, NA), class = \"Date\")"));
test(id=0, code={
argv <- eval(parse(text="list(structure(list(sec = c(0, NA), min = c(0L, NA), hour = c(0L, NA), mday = c(6L, NA), mon = c(10L, NA), year = c(107L, NA), wday = c(2L, NA), yday = c(309L, NA), isdst = c(0L, -1L)), .Names = c(\... | 510 | gpl-2.0 |
b29227089269ede275dedcf8879df8a9d8c722eb | LU-C4i/MOOCs-legacy-platform | workflow/generic_helper_functions/helper_functions.R | '
Copyright (C) 2015 Leiden University
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 version 3 of the License, or
(at your option) any later version.
This program is distributed in the hop... | 4,652 | gpl-3.0 |
b29227089269ede275dedcf8879df8a9d8c722eb | LU-CFI/MOOCs | workflow/generic_helper_functions/helper_functions.R | '
Copyright (C) 2015 Leiden University
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 version 3 of the License, or
(at your option) any later version.
This program is distributed in the hop... | 4,652 | gpl-3.0 |
14294b095450ab71c1f9136f64fe42547ff9fbf6 | dankelley/oce-issues | 14xx/1488/1488a.R | library(oce)
data(ctd)
p <- ctd[['pressure']]
if (!interactive()) png("1488a.png")
par(mar=c(3, 3, 1, 1), mgp=c(2, 0.7, 0), mfrow=c(1, 2))
plot(swTFreeze(ctd, eos='unesco'), p, ylim=rev(range(p)), type='l', lwd=2)
lines(swTFreeze(ctd, eos='gsw'), p, col=2, lty=2)
legend('bottomright', c('UNESCO', 'GSW'), lty=1, col=1:2... | 485 | gpl-2.0 |
f90a0af53a61554b417ac1e0fca20064838a90ca | ryantibs/conformal | conformalInference/tests/testthat/test-multisplit.R | #set data
set.seed(1234)
n = 200; p = 100; s = 10
x = matrix(rnorm(n*p),n,p)
beta = c(rnorm(s),rep(0,p-s))
y = x %*% beta + rnorm(n)
n0 = 100
x0 = matrix(rnorm(n0*p),n0,p)
y0 = x0 %*% beta + rnorm(n0)
repl=2
funs=lasso.funs()
#test
test_that("Split Error", {
expect_error(conformal.pred.msplit(x, y, x0, alpha=0.1... | 2,489 | gpl-2.0 |
d67028c2348116af617cf52bfaa4c865ef8b9e38 | dankelley/oce-issues | 08xx/839/839a.R | library(oce)
library(testthat)
if (!length(ls(pattern='^d$')))
d <- read.amsr("f34_20160102v7.2.gz")
## Test accessors (sensible for temperature?)
median(d[["SSTDay"]], na.rm=TRUE)
median(d[["SSTNight"]], na.rm=TRUE)
data("coastlineWorld")
## Visual test: units OK?
summary(d)
if (!interactive()) png("839a.png", p... | 1,276 | gpl-2.0 |
d7edaa2ef668cae363a856ea4282e2962ba39b63 | sunsiyu/timelyr | R/tools.R | #' Get File Extention
#'
#' @param path character of length 1
#' @return character of file extension
#' @examples
#' fileext <- getfileext("example.R")
#' @export
getfileext <- function(path) {
stopifnot(is.character(path))
splitpath <- strsplit(path, split="\\.")[[1]]
if (length(splitpath) <= 1)
return(NULL)... | 1,647 | gpl-2.0 |
a50581af2018ac6cb43be0986a21211114a2e5dc | Fshem/Fanuel-project | Methods/Data Manipulation/seasonal_summary_method.R | # Seasonal Summaries
#' @title plot cumulative and exceedance graphs
#' @name seasonal_summary
#' @author Fanuel Otieno and Frederic Ntirenganya 2015 (AMI)
#' @description \code{seasonal_summary}
#' Adds a column of sesonal summaries e.g rain totals and number of rain days
#' @return columns of seasonal summaries
... | 6,324 | gpl-2.0 |
d6e035f9fd877765b5de4035443891612f676119 | dwoll/shotGroups | inst/shotGroups_RangeStat_legacy/helper.R | library(shotGroups)
library(shiny)
#####---------------------------------------------------------------------------
## option sets and their respective inverse
#####---------------------------------------------------------------------------
rangeStat <- c("Extreme spread"="1", "Figure of Merit"="2", "Bounding Box ... | 2,629 | gpl-2.0 |
6f57efb2987e6b6b0412bf7681fc30dd89f899cc | metno/wgen | R/thermodynamics.Tda.R | #' thermodynamics.Tda
#'
#' temperature on the dry adiabatic; poisson's equation
#' @param T
#' @param p
#' @keywords thermodynamics
#' @export
#' @examples
#' thermodynamics.Tda()
thermodynamics.Tda<-function(T,p){
results<-(T+thermodynamics.constants$K)*((p/1000)^(thermodynamics.constants$R_sd/thermodynamics.const... | 379 | gpl-2.0 |
9b5c29cd55f8d928eedb447db1fd7a6816d4f2c3 | jirikadlec2/global-snow | user_reports/era-interim.R | #Load the R Packages
library(raster)
library(ncdf)
library(sp)
library(WaterML)
library(httr)
library(rworldmap)
library(RColorBrewer)
library(gstat)
my_colors <- brewer.pal(7, "Purples")
#store this file on HydroShare! and use API to access it
#this is the HydroShare resource ID
resource_id <- "cea10ad2d9534d0cae21f... | 5,042 | gpl-2.0 |
246df5f59c68501bd8322cf23b1b92ff313091e5 | fdavidcl/ruta | R/evaluate.R | #' Custom evaluation metrics
#'
#' Create a different evaluation metric from a valid Keras metric
#'
#' @param evaluate_f Must be either a metric function defined by Keras (e.g.
#' `keras::metric_binary_crossentropy`) or a valid function for Keras to
#' create a performance metric (see `\link[keras]{metric_binary_a... | 2,041 | gpl-3.0 |
f328861bfa534960bc6ece8a10fd150fcd75834d | jmarca/calvad_hpms_r_parsing | tests/testthat/test_a_parts_work.R | fname <- c('./files/2011.csv'
,'./files/2012.csv'
,'./files/2013.csv')
test_that(
'can load (some) of csv file for 2012',
{
filename <- fname[2]
df <- read_file(filename)
df <- whitespace_fix(df)
dfn <- extract_numeric(df)
expect_equal(dim(dfn),c(11... | 4,340 | gpl-2.0 |
64f72f4796bc99db6d8b84ad12391b047cf35877 | ecor/geotopsim | roxygenize_2.R |
# file ...
#
# This file roxygenizes all documentation wriiten in "Roxygen" format.
#
# author: Emanuele Cordano on 16-01-2014
#
#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 versi... | 2,710 | gpl-3.0 |
78d55f5bcec979ed5ced271e2a304972dc2d2110 | luwei0917/awsemmd_script | R/two_d_plot.R | library(tidyverse)
setwd("/Users/weilu/Research/server/project/freeEnergy_2xov/pullingDistance_v3/qnqc")
data <- read_table("pmf-350.dat", skip =1)
data <- data[-c(1,6,7,8)]
ggplot(data)+
aes(bin_center_1,bin_center_2,color=f)+
geom_point()
ggplot(data) +
aes(bin_center_1, bin_center_2, z = f) +
stat_contour()... | 321 | mit |
18ed813b1eee3d8204a4e9185c4d9f52620d8468 | dsscollection/basketball | analysis/movement_functions.R | library(raster)
eucl_dist = function(x1, x2) sqrt(sum((x1 - x2) ^ 2))
skip_this_iteration = function(r, k, player_moments) {
# the 'k' passed in should be such that this won't generate an
# index-based error
skip = FALSE
next_coords = player_moments[(k+1), c('x','y')]
curr_coords = player_moments[... | 3,934 | mit |
a1c736e9ed26cde50f0ff4e97ab5e6b303945eb5 | KellyBlack/R-Object-Oriented-Programming | chapter3/chapter_3_ex9.R | trial <- read.table("trialTable.dat")
trial
typeof(trial)
names(trial)
| 75 | mit |
dc8a7efbf9b48df8c957ae97126d182093443fd9 | thomasblanchet/gpinter | R/add-up.R | #' @title Conditional quantile function of the Gumbel copula
#'
#' @author Thomas Blanchet, Juliette Fournier, Thomas Piketty
#'
#' @description Assume (U, V) follows a Gumbel copula. This function gives
#' the quantile function of V given U = u. It is used to simulate the Gumbel
#' copula.
#'
#' @param p A number in [... | 2,999 | mit |
26c3e1f9eb031bfac5c378ea1665d8397f10c7ed | RCollins13/CNValue | plotting_code/AllExampleLoci/SMARCA2/plotSMARCA2.R | #!/usr/bin/env R
#rCNV Map Project
#Spring 2017
#Talkowski Lab & Collaborators
#Copyright (c) 2017 Ryan Collins
#Distributed under terms of the MIT License
#Code to generate locus plot for SMARCA2
#####Set parameters
WRKDIR <- "/Users/rlc/Desktop/Collins/Talkowski/CNV_DB/rCNV_map/"
options(scipen=1000,stringsAsFact... | 6,097 | mit |
26c3e1f9eb031bfac5c378ea1665d8397f10c7ed | RCollins13/rCNVmap | plotting_code/AllExampleLoci/SMARCA2/plotSMARCA2.R | #!/usr/bin/env R
#rCNV Map Project
#Spring 2017
#Talkowski Lab & Collaborators
#Copyright (c) 2017 Ryan Collins
#Distributed under terms of the MIT License
#Code to generate locus plot for SMARCA2
#####Set parameters
WRKDIR <- "/Users/rlc/Desktop/Collins/Talkowski/CNV_DB/rCNV_map/"
options(scipen=1000,stringsAsFact... | 6,097 | mit |
ffc0072c42ac24cabcfc38b64321f82e79901d5b | lxwang/ergm | 3.1/tests/scoping.R | # File tests/scoping.R in package ergm, part of the Statnet suite
# of packages for network analysis, http://statnet.org .
#
# This software is distributed under the GPL-3 license. It is free,
# open source, and has the attribution requirements (GPL Section 7) at
# http://statnet.org/attribution
#
# Copyright 20... | 691 | gpl-3.0 |
d3cbceb095c489bd23e91875667b67ce0d75861f | skochaver/sciencebase_analysis | rileys_k.R | # Load necessary packages
install.packages("spatstat")
library("spatstat")
install.packages("rgdal")
library("rgdal") # Need this to import shapefiles
install.packages("maptools")
library("maptools") # Need this because it contains the as() coercion functions
# Set working directory
#setwd("/home/ygrit... | 2,856 | unlicense |
b39e2d0d7c1743672d58a07c511355b8532e4ce5 | h2oai/h2o-3 | h2o-r/tests/testdir_algos/glm/runit_PUBDEV_8843_glm_lambda_not_null_regPath.R | setwd(normalizePath(dirname(R.utils::commandArgs(asValues=TRUE)$"f")))
source("../../../scripts/h2o-r-test-setup.R")
library(glmnet)
# Test that with regularization on, the p-values are computed
test.glm_reg_path <- function() {
d <- h2o.importFile(path = locate("smalldata/logreg/prostate.csv"))
alphaArray <-... | 637 | apache-2.0 |
a7dab66103a4bca456b3b41f4de5b77891a06a2c | milokmilo/Stranded | R/project.leslie.R | #' Project Leslie matrix
#'
#' Project Leslie matrix. Original from demoR_0.4.2
#' @param A
#' @param no
#' @param tmax
#' @param pop.sum Default = FALSE
#' @keywords Leslie matrix projection
#' @export
#' @examples
#' project.leslie()
project.leslie <- function(A,no,tmax,pop.sum=FALSE){
if(length(no) != dim(A)[1])... | 594 | gpl-2.0 |
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