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 |
|---|---|---|---|---|---|
487659c7cd21b61fd28f2f9b7a0874e662f14ca3 | CancerInSilico/CancerInSilico | R/class-OffLatticeModel.R | #' @include class-CellModel.R
NULL
library(methods)
################ Class Definition ################
#' @title OffLatticeModel
#' @description General description of an off-lattice cell-based model.
#' not quite a full implementation, but contains much of the neccesary
#' structure for models of this type
#'
#' @s... | 12,312 | gpl-3.0 |
687073ffd78a13a798d6fb57794917aa4bb64d9c | naokazumizuta/RecSys2013YelpBusinessRatingPrediction | r/init.R | # initial settings
root <- "C:/Users/nao/Documents/GitHub/RecSys2013YelpBusinessRatingPrediction"
folder <- list()
folder_name <- c(
"data",
"docs",
"log",
"py",
"r",
"raw",
"rdata",
"submit")
for(name in folder_name) {
folder[[name]] <- file.path(root, name)
dir.create(folder[... | 434 | mit |
ba490b7f4c43b7f6faccdfb56b4283561b3c4fbf | duhi23/CouchDB | classify_emotion.R | classify_emotion <- function(textColumns,algorithm="bayes",prior=1.0,verbose=FALSE,...) {
matrix <- create_matrix(textColumns,...)
lexicon <- read.csv(system.file("data/emotions.csv.gz",package="sentiment"),header=FALSE)
counts <- list(anger=length(which(lexicon[,2]=="anger")),disgust=length(wh... | 2,787 | gpl-3.0 |
91fe2aab3520f8a0f17f86fdc24cc250f82c1742 | kakaba2009/MachineLearning | r/learn/times/stft.R | library(e1071)
library(xts)
source('./mylib/mcalc.R')
source('./mylib/mtool.R')
options(max.print=5.5E5)
df <- loadSymbol('JPY=X')
df <- df$Close
ts <- as.ts(df)
x <- tail(ts, n=1000)
y <- stft(x, win=6, inc=1, coef=64)
plot(y) | 231 | apache-2.0 |
1fd36dbce6955314812dfa1ddc1934bb59eebafc | rstudio/reticulate | tests/testthat/resources/venv-activate.R |
args <- commandArgs(TRUE)
venv <- args[[1]]
Sys.unsetenv("RETICULATE_PYTHON")
Sys.unsetenv("RETICULATE_PYTHON_ENV")
reticulate::use_virtualenv(venv, required = TRUE)
sys <- reticulate::import("sys")
writeLines(sys$path)
| 223 | apache-2.0 |
92e8032a1f2328d0d10c16745c567570796222f6 | kapsitis/ddgatve-stat | nms-reports/topResults.R |
# listInit <- function(tensBySch, tensByLang, tensByMun, tensByGend,
# sch, lang, mun, gend) {
# if (!sch %in% names(tensBySch)) {
# tensBySch[[sch]] <- 0
# }
# if (!lang %in% names(tensByLang)) {
# tensByLang[[lang]] <- 0
# }
# if (!mun %in% names(tensByMun)) {
# ... | 3,115 | apache-2.0 |
1fd36dbce6955314812dfa1ddc1934bb59eebafc | terrytangyuan/reticulate | tests/testthat/resources/venv-activate.R |
args <- commandArgs(TRUE)
venv <- args[[1]]
Sys.unsetenv("RETICULATE_PYTHON")
Sys.unsetenv("RETICULATE_PYTHON_ENV")
reticulate::use_virtualenv(venv, required = TRUE)
sys <- reticulate::import("sys")
writeLines(sys$path)
| 223 | apache-2.0 |
b36a145f0df82bfc348c3e54046568f16d0e000c | arcolombo/sleuthData | R/zzz.R | cat("Results from GSE37704 are available in",
system.file("extdata", "results", package="sleuthData"))
| 108 | artistic-2.0 |
cb79b016a986ebbc62d38bad2d5781681d177182 | rstudio/reticulate | tests/testthat/test-python-objects.R | context("objects")
test_that("the length of a Python object can be computed", {
skip_if_no_python()
m <- py_eval("[1, 2, 3]", convert = FALSE)
expect_equal(length(m), 3L)
x <- py_eval("None", convert = FALSE)
expect_identical(length(x), 0L)
expect_identical(py_bool(x), FALSE)
expect_error(py_len(x), "'... | 1,236 | apache-2.0 |
5430aa0337d5f5f0393413efc8a523835afcc6d3 | MulletLab/leafangle_supplement | h2_and_qtl/rqtl_mqm_scripts/scantwo_perm_R07018xR07020.R | ################################################################################
# Calculate Penalties for curated Multiple QTL Mapping in R\qtl #
# Written by Sandra Truong 10/14/2014 #
# Much of the code originates from http://www.rqtl.org/tutorials ... | 3,398 | gpl-2.0 |
1c89d8e03f966a4b6e584e30de574532513b7b1c | zlskidmore/GenVisR | R/covBars_qual.R | #' Construct coverage cohort plot
#'
#' given a matrix construct a plot to display coverage as percentage bars for a
#' group of samples
#' @name covBars_qual
#' @param x object of class matrix containing rows for the coverage and columns
#' the sample names
#' @return a list of data frame and color vector
covBars_qua... | 1,621 | cc0-1.0 |
7787765a9d1cccd54b1f2b1f52e4d8da778dcae5 | richelbilderbeek/R | old_notes/Phylogenies/get_test_fasta_filename.R | get_test_fasta_filename <- function() {
fasta_filename <- "convert_alignment_to_fasta.fasta"
#fasta_filename <- "convert_fasta_file_to_sequences.fasta"
if (file.exists(fasta_filename)) { return (fasta_filename) }
fasta_filename <- paste("~/GitHubs/R/Phylogenies/",fasta_filename,sep="")
if (file.exists(fasta_... | 451 | gpl-3.0 |
a8fac03dddeb188cf33d668bfa70d4a3aeb36cc8 | fernandojunior/online-players-behavior | src/R/evaluation_measures.R | # Functions to evaluate a predictive model
# http://journals.plos.org/plosone/article/figure/image?size=large&id=info:doi/10.1371/journal.pone.0118432.t001
# targets
# outcomes 0 1
# 0 TN FN
# 1 FP TP
confusion_matrix = function (outcomes, targets) {
return(table(outcomes, targets))
}
... | 2,712 | mit |
1c89d8e03f966a4b6e584e30de574532513b7b1c | jkunisak/GenVisR | R/covBars_qual.R | #' Construct coverage cohort plot
#'
#' given a matrix construct a plot to display coverage as percentage bars for a
#' group of samples
#' @name covBars_qual
#' @param x object of class matrix containing rows for the coverage and columns
#' the sample names
#' @return a list of data frame and color vector
covBars_qua... | 1,621 | cc0-1.0 |
cb6dfce429bc9ced5678b9dd40ecb7e791747e2e | wch/r-source | src/library/datasets/data/Harman74.cor.R | "Harman74.cor" <-
structure(list(cov = structure(c(1, 0.318, 0.403, 0.468, 0.321,
0.335, 0.304, 0.332, 0.326, 0.116, 0.308, 0.314, 0.489, 0.125,
0.238, 0.414, 0.176, 0.368, 0.27, 0.365, 0.369, 0.413, 0.474,
0.282, 0.318, 1, 0.317, 0.23, 0.285, 0.234, 0.157, 0.157, 0.195,
0.057, 0.15, 0.145, 0.239, 0.103, 0.131, 0.272, ... | 5,023 | gpl-2.0 |
32b5814be04ef6ed07b5b884809385407005a98f | jyfeather/LASSO-BN | R/auc_real.R | rm(list = ls())
require("genlasso") # Lasso solver
require("ROCR") # ROC
require("Matrix")
set.seed(2015)
kIteration <- 200
node.num <- 22
sig.set <- c(0.1, 0.3, 0.5, 0.7, 1, 1.5) # Mean shift magnitude
var.df <- 1 # 1, 2, 3, 4, 5 guessed amount of mean shift vars
ns <- 1 # 1, 2, 5, 10
load("./dat/real/weig... | 2,364 | mit |
5430aa0337d5f5f0393413efc8a523835afcc6d3 | thkhavi/leafangle_supplement | h2_and_qtl/rqtl_mqm_scripts/scantwo_perm_R07018xR07020.R | ################################################################################
# Calculate Penalties for curated Multiple QTL Mapping in R\qtl #
# Written by Sandra Truong 10/14/2014 #
# Much of the code originates from http://www.rqtl.org/tutorials ... | 3,398 | gpl-2.0 |
1c89d8e03f966a4b6e584e30de574532513b7b1c | zskidmor/GenVisR | R/covBars_qual.R | #' Construct coverage cohort plot
#'
#' given a matrix construct a plot to display coverage as percentage bars for a
#' group of samples
#' @name covBars_qual
#' @param x object of class matrix containing rows for the coverage and columns
#' the sample names
#' @return a list of data frame and color vector
covBars_qua... | 1,621 | cc0-1.0 |
1c89d8e03f966a4b6e584e30de574532513b7b1c | zskidmor/GGgenome | R/covBars_qual.R | #' Construct coverage cohort plot
#'
#' given a matrix construct a plot to display coverage as percentage bars for a
#' group of samples
#' @name covBars_qual
#' @param x object of class matrix containing rows for the coverage and columns
#' the sample names
#' @return a list of data frame and color vector
covBars_qua... | 1,621 | cc0-1.0 |
1c89d8e03f966a4b6e584e30de574532513b7b1c | Alanocallaghan/GenVisR | R/covBars_qual.R | #' Construct coverage cohort plot
#'
#' given a matrix construct a plot to display coverage as percentage bars for a
#' group of samples
#' @name covBars_qual
#' @param x object of class matrix containing rows for the coverage and columns
#' the sample names
#' @return a list of data frame and color vector
covBars_qua... | 1,621 | cc0-1.0 |
1c89d8e03f966a4b6e584e30de574532513b7b1c | ahwagner/GenVisR | R/covBars_qual.R | #' Construct coverage cohort plot
#'
#' given a matrix construct a plot to display coverage as percentage bars for a
#' group of samples
#' @name covBars_qual
#' @param x object of class matrix containing rows for the coverage and columns
#' the sample names
#' @return a list of data frame and color vector
covBars_qua... | 1,621 | cc0-1.0 |
7192f17c13810bf0cad9a5333c8338350063c9f2 | athyuttamre/accessible-facebook-ui | public/conversejs/components/otr/test/plot.R | #!/usr/bin/env Rscript
# most from ry
# https://github.com/joyent/node/blob/master/benchmark/plot.R
library(ggplot2)
hist_png_filename <- "hist.png"
png(filename = hist_png_filename, width = 480, height = 380, units = "px")
da = read.csv(
"./data.csv",
sep="\t",
header=F,
col.names = c("time")
)
qplot(
... | 448 | mit |
aa969a55ec80e4b042ac0eab07551f6b56e46a0d | alonzi/fundamentals | coding_tips/R/pipes.R | # stolen from Hadley Wickam
# Packages in the tidyverse load %>% for you automatically, so you don’t usually load magrittr explicitly.
f(x,y) # is pretty easy to read
f(g(x,y),z) # is a little harder to read
# R let's you pipe objects into arguments of functions with %>%
f(g(x,y),z)
# becomes
x %>%
g(y) %>%
f... | 899 | gpl-2.0 |
5c3530738d96bd0fde56a906a9211259bbd5236f | JackyCode/Data_Science | KMeans/self_kmeans.R | ############################################################
# self_kmeans.R:
# -------------------
# tells how to use custom function to achieve the k-means
#
############################################################
# license:
# --------
# Copyright (c) 2014 JackyCode
# Distributed under the [MIT License][MIT].
# ... | 1,741 | mit |
1aa19e527012b03d87257233e0b7e0f058ab8b8f | Zhiwu-Zhang-Lab/GAPIT | GAPIT.Create.Indicator.R | `GAPIT.Create.Indicator` <-
function(xs, SNP.impute = "Major" ){
#Object: To esimate variance component by using EMMA algorithm and perform GWAS with P3D/EMMAx
#Output: ps, REMLs, stats, dfs, vgs, ves, BLUP, BLUP_Plus_Mean, PEV
#Authors: Alex Lipka and Zhiwu Zhang
# Last update: April 30, 2012
########################... | 1,859 | gpl-2.0 |
3677ee16c4611fc4e61535857c8b36459c80167a | miceli/BMR | tests/dsge/gensys/nkm_dsgevar.R |
#
rm(list=ls())
library(BMR)
source("nkm_model.R")
#
data(BMRVARData)
dsgedata <- USMacroData[24:211,-c(1,3)]
dsgedata <- as.matrix(dsgedata)
for(i in 1:2){
dsgedata[,i] <- dsgedata[,i] - mean(dsgedata[,i])
}
#
obj <- new(dsgevar_gensys)
obj$set_model_fn(nkm_model_simple)
x <- c(1)
obj$eval_model(x)
#
l... | 1,423 | gpl-2.0 |
9f4cc88e4218578049e3eb7813be4a5aa1cffe75 | lulab/PI | Rscript/machine_learning/plot_result.R | library('e1071')
require(randomForest)
require(RColorBrewer)
input=read.csv("bins.training-5classes.sampled.csv")
model_file="5classes.rf.model"
dataall=input[,c(8:12,15:16,18:19)]
classesall=subset(input,select=X1.Annotation)
#Generate training and testing sets
nall=nrow(input)
ntrain=2*floor(nall/3)
datatrain <- dat... | 675 | gpl-2.0 |
3677ee16c4611fc4e61535857c8b36459c80167a | kthohr/BMR | tests/dsge/gensys/nkm_dsgevar.R |
#
rm(list=ls())
library(BMR)
source("nkm_model.R")
#
data(BMRVARData)
dsgedata <- USMacroData[24:211,-c(1,3)]
dsgedata <- as.matrix(dsgedata)
for(i in 1:2){
dsgedata[,i] <- dsgedata[,i] - mean(dsgedata[,i])
}
#
obj <- new(dsgevar_gensys)
obj$set_model_fn(nkm_model_simple)
x <- c(1)
obj$eval_model(x)
#
l... | 1,423 | gpl-2.0 |
3d93551eb71de137b7cd59515f53c669cdb0b83f | glycerine/bigbird | r-3.0.2/src/gnuwin32/installer/JRins.R | # File src/gnuwin32/installer/JRins.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... | 4,565 | bsd-2-clause |
f580b38b5bef5d2c920c8abbe61b73e8a8e09dda | Prateek2690/APP_ | highcharter/ui-orig.R | #library("shiny")
#library("shinydashboard")
library("highcharter")
#library("dplyr")
#library("viridisLite")
library("markdown")
library("quantmod")
library("tidyr")
#library("ggplot2")
library("treemap")
library("forecast")
library("DT")
#rm(list = ls())
dashboardPage(
skin = "black",
dashboardHe... | 2,782 | mit |
3d93551eb71de137b7cd59515f53c669cdb0b83f | lajus/customr | src/gnuwin32/installer/JRins.R | # File src/gnuwin32/installer/JRins.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... | 4,565 | gpl-2.0 |
f580b38b5bef5d2c920c8abbe61b73e8a8e09dda | Prateek2690/APP_ | highcharter/highcharter/ui-orig.R | #library("shiny")
#library("shinydashboard")
library("highcharter")
#library("dplyr")
#library("viridisLite")
library("markdown")
library("quantmod")
library("tidyr")
#library("ggplot2")
library("treemap")
library("forecast")
library("DT")
#rm(list = ls())
dashboardPage(
skin = "black",
dashboardHe... | 2,782 | mit |
3d93551eb71de137b7cd59515f53c669cdb0b83f | cxxr-devel/cxxr-svn-mirror | src/gnuwin32/installer/JRins.R | # File src/gnuwin32/installer/JRins.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... | 4,565 | gpl-2.0 |
3a12b5e5e12ccbd88942655110ed42ad854f3a08 | thomasvangurp/epiGBS | RnBeads/RnBeads/R/assemblies.R | ########################################################################################################################
## annotations.R
## created: 2012-08-16
## creator: Yassen Assenov
## ---------------------------------------------------------------------------------------------------------------------
## Collecti... | 7,310 | mit |
051cf708912da9d7c4b23cef72c206df58bae18e | mul118/shinyMCE | R/shinyMCE.R | #' tinyMCE editor element
#'
#' Display a tinyMCE editor within an application page.
#' @param inputId id associated with the editor
#' @param content editor content. May be a string or HTML embedded in an \code{\link{HTML}} function
#' @param options string containing tinyMCE initialization options. See demos or sourc... | 1,808 | mit |
3a12b5e5e12ccbd88942655110ed42ad854f3a08 | thomasvangurp/epiGBS | RnBeads/templates/assemblies.R | ########################################################################################################################
## annotations.R
## created: 2012-08-16
## creator: Yassen Assenov
## ---------------------------------------------------------------------------------------------------------------------
## Collecti... | 7,310 | mit |
fe7f2d65484526e64128e22478eab82c02cfba4c | natematias/reddit-data-reanalysis | analysis/gaps_summaries.R | library(ggplot2)
library(lubridate)
rm(list=ls())
#### PLOT MISSING DATA PER DAY (COMMENTS)
missing_data_comments <- read.csv("../data/aggregate_data/Missing Data Timeline - Comment Timeline.csv")
missing_data_comments$day <- as.Date(missing_data_comments$Date, format="%m/%d/%Y")
ggplot(missing_data_comments, aes(d... | 6,579 | mit |
e55c7febdb970038126ceb12b470fbf5a83d8659 | graalvm/fastr | com.oracle.truffle.r.test.native/packages/testrffi/testrffi/tests/simpleTests.R | # Copyright (c) 2018, 2021, Oracle and/or its affiliates. All rights reserved.
# DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
#
# This code is free software; you can redistribute it and/or modify it
# under the terms of the GNU General Public License version 3 only, as
# published by the Free Software ... | 12,765 | gpl-2.0 |
a87eace14716a46a5d8be1cde654b55eb68e7512 | peter19852001/decomp | sim.R | #
# to randomly generate (synthetic) gene network in the form of matrices,
# where each link a_ij has a number representing the
# effect of gene i on gene j: +ve for activation, -ve for inhibition.
# Associated with each a_ij =/= 0 is t_ij > 0, which represents the time delay
# of the effect of gene i on gene j.
gen_g... | 8,813 | gpl-2.0 |
dd75f6967819f8cde072ad067cb78c5505d42e9c | longphin/Bayesian---STA250 | HW2/BLB/BLB_lin_reg_process.R |
# Read in and process BLB results:
mini <- FALSE
if (mini){
d <- 40
} else {
d <- 1000
}
# BLB specs:
s <- 5 # 50
r <- 50 # 100
outpath <- "output"
respath <- "final"
if (mini){
rootfilename <- "blb_lin_reg_mini"
} else {
rootfilename <- "blb_lin_reg_data"
}
results.se.filename <- paste0(respath,"/",rootfilen... | 1,727 | mit |
1cd49fccbb37e19521b27591b91df512d913de9e | everdark/rbasic | samplecodes/src.R |
findVAR <- function() exists("VAR")
| 40 | cc0-1.0 |
dd75f6967819f8cde072ad067cb78c5505d42e9c | longphin/Stuff | HW2/BLB/BLB_lin_reg_process.R |
# Read in and process BLB results:
mini <- FALSE
if (mini){
d <- 40
} else {
d <- 1000
}
# BLB specs:
s <- 5 # 50
r <- 50 # 100
outpath <- "output"
respath <- "final"
if (mini){
rootfilename <- "blb_lin_reg_mini"
} else {
rootfilename <- "blb_lin_reg_data"
}
results.se.filename <- paste0(respath,"/",rootfilen... | 1,727 | mit |
dd75f6967819f8cde072ad067cb78c5505d42e9c | STA250/Stuff | HW2/BLB/BLB_lin_reg_process.R |
# Read in and process BLB results:
mini <- FALSE
if (mini){
d <- 40
} else {
d <- 1000
}
# BLB specs:
s <- 5 # 50
r <- 50 # 100
outpath <- "output"
respath <- "final"
if (mini){
rootfilename <- "blb_lin_reg_mini"
} else {
rootfilename <- "blb_lin_reg_data"
}
results.se.filename <- paste0(respath,"/",rootfilen... | 1,727 | mit |
dd75f6967819f8cde072ad067cb78c5505d42e9c | dmtryshmtv/STA250Stuff | HW2/BLB/BLB_lin_reg_process.R |
# Read in and process BLB results:
mini <- FALSE
if (mini){
d <- 40
} else {
d <- 1000
}
# BLB specs:
s <- 5 # 50
r <- 50 # 100
outpath <- "output"
respath <- "final"
if (mini){
rootfilename <- "blb_lin_reg_mini"
} else {
rootfilename <- "blb_lin_reg_data"
}
results.se.filename <- paste0(respath,"/",rootfilen... | 1,727 | mit |
dd75f6967819f8cde072ad067cb78c5505d42e9c | minjay/Stuff | HW2/BLB/BLB_lin_reg_process.R |
# Read in and process BLB results:
mini <- FALSE
if (mini){
d <- 40
} else {
d <- 1000
}
# BLB specs:
s <- 5 # 50
r <- 50 # 100
outpath <- "output"
respath <- "final"
if (mini){
rootfilename <- "blb_lin_reg_mini"
} else {
rootfilename <- "blb_lin_reg_data"
}
results.se.filename <- paste0(respath,"/",rootfilen... | 1,727 | mit |
39c0de72b42d7a611d7ffafbe2ee8bfda651ae75 | SaraVarela/Bucanetes | script_bucanetes.R | ##### load libraries
library (raster)
library (rgdal)
library (dismo)
##### download climatic variables for the last glacial maximum (LGM) and for the present from worldclim.org
## ** = write the directory of the variables
setwd ("**")
LGM_CCSM<- stack (raster ("bio1.bil"), raster ("bio2.bil"),raster ("bio3.bil"),
... | 3,276 | unlicense |
b01fb5fc09f468868cf321d25b1084c28e59ec79 | osofr/gridisl | R/ModelPredictionStack.R | #' S3 methods for printing model fit summary for PredictionModel R6 class object
#'
#' Prints the modeling summaries
#' @param x The model fit object produced by functions \code{make_PredictionStack}.
#' @param ... Additional options passed on to \code{print.PredictionModel}.
#' @export
print.PredictionStack <- functio... | 13,309 | mit |
4da46794bad8aa0e8d9840f2fbfc51af38ef29e5 | berdaniera/StreamPULSE | spfns/spFunctions.R | checkpkg = function(pkg){
if(!pkg %in% rownames(installed.packages())) install.packages(pkg)
suppressPackageStartupMessages(library(pkg, character.only=TRUE))
}
checkpkg("zoo")
checkpkg("tibble")
checkpkg("readr")
checkpkg("dplyr")
# Calculate depth with water pressure (kPa), air pressure (kPa), air temp (C), dept... | 2,777 | gpl-3.0 |
fd7bdca89ac5633b512700721a0c91a763f34dcd | IQSS/Zelig4 | tests/NO-CRAN-bootstrap.R | library(Zelig)
data(coalition)
z.out <- zelig(duration ~ fract + numst2 + crisis, model = "gamma", data = coalition[1:100, ])
x.low <- setx(z.out, fract=300, numst2 = 0, crisis=200)
x.high <- setx(z.out, fract=300, numst2 = 1, crisis=200)
s.out <- sim(z.out, x = x.low, x1 = x.high, num = 10, bootstrap=TRUE)
| 313 | gpl-2.0 |
89e9e2b61f8e062034630403197c77f8261b3f21 | MazamaScience/PWFSLSmoke | R/addWindBarbs.R | #' @keywords plotting
#' @export
#' @title Add wind barbs to a map
#' @param x vector of longitudes
#' @param y vector of latitudes
#' @param speed vector of wind speeds in knots
#' @param dir wind directions in degrees clockwise from north
#' @param circleSize size of the circle
#' @param circleFill circle fill color... | 2,148 | gpl-3.0 |
00baa6ae9043b11a0021a9efd8d286a492001b9c | franticspider/q2e | tests/isotest2.R |
require(q2e)
readline("Testing IGQPGAVGPAGIR")
q2e_isodists("IGQPGAVGPAGIR")
readline("Testing GPPGPQGAR")
q2e_isodists("GPPGPQGAR")
readline("Testing ACDEFGHIKLMNPQRSTVWY")
q2e_isodists("ACDEFGHIKLMNPQRSTVWY")
readline("Testing ABCDEFGHIJKLMNOPQRSTUVWXYZ")
q2e_isodists("ABCDEFGHIJKLMNOPQRSTUVWXYZ")
| 314 | lgpl-3.0 |
c7ac0e37f79ea727c182c0bf6e4411a980250649 | kannix68/advent_of_code_2015 | adventcode2015_01a.R | ## R (R-language)
# advent of code 2015. kannix68 (@github).
# Day 1: Not Quite Lisp.
# sorry, please currently set your directory
setwd('~/devel/advent_of_code_2015')
inFileName = 'adventcode2015_in01.txt'
#** our algorithm
algo <- function(s){
ups = gsub('\\)', '', s)
n_all = nchar(s)
n_ups = nchar(ups)
n_... | 1,053 | mit |
923b2efcf3dc138e1d35a2277079e1bb37bda019 | tangelo-hub/romanescoTools | R/getDocData.R | #' Get Documentation Information for a Function
#'
#' Get documentation information for a function, including package, title, description, examples, and argument names and descriptions.
#'
#' @param functionName name of the function
#'
#' @return a named list of documentation components
#'
#' @examples
#' a <- getDoc... | 3,288 | bsd-3-clause |
f6efff0bf8e07d76d2f070ca46d1285e59f0cdb5 | gustavobio/plumber | R/processor-image.R | #' @include processor.R
#' @include plumber.R
PlumberProcessor$new(
"jpeg",
function(req, res, data){
t <- tempfile()
data$file <- t
jpeg(t)
},
function(val, req, res, data){
dev.off()
con <- file(data$file, "rb")
img <- readBin(con, "raw", file.info(data$file)$size)
close(con)
... | 748 | mit |
923b2efcf3dc138e1d35a2277079e1bb37bda019 | hafen/cardoonTools | R/getDocData.R | #' Get Documentation Information for a Function
#'
#' Get documentation information for a function, including package, title, description, examples, and argument names and descriptions.
#'
#' @param functionName name of the function
#'
#' @return a named list of documentation components
#'
#' @examples
#' a <- getDoc... | 3,288 | bsd-3-clause |
f6efff0bf8e07d76d2f070ca46d1285e59f0cdb5 | paulhendricks/plumber | R/processor-image.R | #' @include processor.R
#' @include plumber.R
PlumberProcessor$new(
"jpeg",
function(req, res, data){
t <- tempfile()
data$file <- t
jpeg(t)
},
function(val, req, res, data){
dev.off()
con <- file(data$file, "rb")
img <- readBin(con, "raw", file.info(data$file)$size)
close(con)
... | 748 | mit |
7ce7532b667abf6d9df8412eb1aa6e27f7252a07 | ChristosChristofidis/h2o-3 | h2o-r/tests/Utils/shared_javapredict_GBM.R |
heading("BEGIN TEST")
conn <- new("H2OConnection", ip=myIP, port=myPort)
heading("Uploading train data to H2O")
iris_train.hex <- h2o.importFile(conn, train)
heading("Creating GBM model in H2O")
distribution <- if (exists("distribution")) distribution else "AUTO"
balance_classes <- if (exists("balance_classes")) bal... | 4,264 | apache-2.0 |
0774423aa79824fd9215129bbf74930bfc11aabc | google/rappor | pipeline/metric_status.R | #!/usr/bin/Rscript
#
# Write an overview of task status, per-metric task status, task histograms.
library(data.table)
library(ggplot2)
options(stringsAsFactors = FALSE) # get rid of annoying behavior
Log <- function(fmt, ...) {
cat(sprintf(fmt, ...))
cat('\n')
}
# max of non-NA values; NA if there are none
May... | 11,041 | apache-2.0 |
e039d22db6eb2c4e07fa62c1c16c027c995ae275 | andrewdefries/andrewdefries.github.io | FDA_Pesticide_Glossary/OPUS.R | library("knitr")
library("rgl")
#knit("OPUS.Rmd")
#markdownToHTML('OPUS.md', 'OPUS.html', options=c("use_xhml"))
#system("pandoc -s OPUS.html -o OPUS.pdf")
knit2html('OPUS.Rmd')
| 180 | mit |
40b8b6603e58170e7eca658faf4fd9b9b15d5c2c | b0rxa/scmamp | R/data_manipulation.R | #' @title Expression based row filtering
#'
#' @description This is a simple function to filter data based on an expression defined using the colum names
#' @param data A NAMED matrix or data frame to be filtered (column names are required).
#' @param condition A string indicating the condition that the row have to ful... | 9,624 | gpl-2.0 |
a674fc588a01d17087562dbbad63d0b84985a3e8 | seacode/rsimGmacs | R/midpoints.R | #'
#'@title Calculate the midpoints of a vector.
#'
#'@description Function to calculate the midpoints of a vector.
#'
#'@param x - the vector to calculate the midpoints for
#'
#'@return the vector of midpoints
#'
#'@export
#'
midpoints<-function(x){
n<-length(x)-1;
d<-0.5*(x[1+(1:n)]+x[1:n]);
names(d)<-nam... | 343 | mit |
a674fc588a01d17087562dbbad63d0b84985a3e8 | wStockhausen/rsimTCSAM | R/midpoints.R | #'
#'@title Calculate the midpoints of a vector.
#'
#'@description Function to calculate the midpoints of a vector.
#'
#'@param x - the vector to calculate the midpoints for
#'
#'@return the vector of midpoints
#'
#'@export
#'
midpoints<-function(x){
n<-length(x)-1;
d<-0.5*(x[1+(1:n)]+x[1:n]);
names(d)<-nam... | 343 | mit |
79e7d6656dae041bb5c4f9af4f1f2af9f8c7f950 | molgenis/NIPTeR | R/regression_result.R | regression_template <- function(result_set, chromo_focus, correction_status, samplenames,
potential_predictors, models, sample_names_train_set = NULL,
train_set_statistics = NULL, train_set_Zscores = NULL, type){
if (is.null(train_set_statistics)){
... | 5,725 | lgpl-3.0 |
79e7d6656dae041bb5c4f9af4f1f2af9f8c7f950 | ljohansson/NIPTeR | R/regression_result.R | regression_template <- function(result_set, chromo_focus, correction_status, samplenames,
potential_predictors, models, sample_names_train_set = NULL,
train_set_statistics = NULL, train_set_Zscores = NULL, type){
if (is.null(train_set_statistics)){
... | 5,725 | lgpl-3.0 |
9fed949cb47107181f6dc549b48bf5a89525033d | alsotoes/compstat2016 | tarea3IntegracionMonteCarlo/realMonteCarlo_example.R | fun <- function(x){
aux <- num*sqrt(10*x-x^2-24);
aux[is.nan(aux)] <- 0;
return(aux)
}
fun2 <- function(x){
aux <- sqrt(4-x^2)
aux[is.nan(aux)] <- 0
return (aux)
}
from <- -2
to <- 2
n <- 1000
x <- runif(n, from, to)
to1 <- to-from
(monteCarlo <- mean(fun(x)))
(monteCarlo <- to1*mean(... | 331 | gpl-3.0 |
8167ed1e8e2be63ed2a65a72fa55930c9ffe49fc | pdcarr/KIC8462852 | astro_funcs.R | ###########################################################
AirMass <- function(JD,locObs,starLoc) {
# JD is the vector of Julian dates
# locObs is the decimal location = c(lat,long) of the observatory
# starLoc is a vector of declination degrees, minutes, seconds and right ascension in h,m,s of the star
# calculates A... | 1,076 | mit |
27e1fe154ceff3eddd0c8c6c6d4aeb4a57239019 | psobczyk/pesel_simulations | MiceAnalysis.R |
library(FactoMineR)
library(pesel)
mouse = read.table("http://factominer.free.fr/docs/souris.csv", header = T, sep = ";",
row.names = 1)
expressions = mouse[, 24: ncol(mouse)]
dim(expressions)
# 40 120
## Pesel analysis
res <- pesel(expressions, npc.min = 0, npc.max = min(ncol(expressions) -2, nrow... | 1,157 | gpl-3.0 |
4da92e531459fe220e48102aacc78d70b1a6c05b | RGLab/preprocessData | R/skeleton.R | #' @importFrom assertthat assert_that
#' @importFrom purrr map
#' @importFrom usethis create_package
.codefile_validate <- function(code_files) {
# do they exist?
assertthat::assert_that(all(unlist(purrr::map(
code_files, file.exists
))), msg = "code_files do not all exist!")
# are the .Rmd files?
assertt... | 7,916 | artistic-2.0 |
462f63f876ad9a99364a37cdda1e904559c9e15b | NovaInstitute/Rpackages | novaUtils/R/splitMobenzi2.R |
#' Decodes Mobenzi data with extraction of repeating sections
#'
#' @param filePaths A character argument containing the paths to .csv files (one per
#' section) as downloaded from Mobenzi.
#' @param formatOtions If true, formats the question options of code book variables
#' with 'format_char'.
#' @param tidy... | 9,276 | mit |
555c77f84714bdc169ef537de964e76f0ce6b785 | gmaubach/R-Project-Utilities | Development/t_frequencies.R | t_frequencies <- function(variable,
sort = FALSE, # sort freq
decimals = 1, # round to decimals
useNA = "always",
max_print = 100)
{
if (sort)
{
v_abs <- sort(table(variable, useNA = useNA))
} else
{
... | 1,380 | gpl-2.0 |
3ec554a9c20bb56792d95cb979bacf693dae2e71 | wStockhausen/rCompTCMs | R/modelComparisons.ModelFits.ZCsByYear.Fisheries.R | #'
#' @title Render a document of comparison plots for model fits to fishery size composition data by year
#'
#' @description Function to render a document of comparison plots for model fits to
#' fishery size composition data by year.
#'
#' @param models - named list of model results (as resLst objects) to compare
#' ... | 4,922 | mit |
91b18c85b2727f90361628f6a968d5d3d45a066f | USGS-R/mda.streams | R/list_metab_models.R | #' List the available metab_model objects
#'
#' @param text if specified, the query only returns metab_models whose text (or
#' description, if available) matches the word[s] in \code{text}. Note that
#' partial words are not matched -- e.g., text='nwis_0138' will not match
#' models whose title includes 'nwis... | 1,759 | cc0-1.0 |
91b18c85b2727f90361628f6a968d5d3d45a066f | aappling-usgs/mda.streams | R/list_metab_models.R | #' List the available metab_model objects
#'
#' @param text if specified, the query only returns metab_models whose text (or
#' description, if available) matches the word[s] in \code{text}. Note that
#' partial words are not matched -- e.g., text='nwis_0138' will not match
#' models whose title includes 'nwis... | 1,759 | cc0-1.0 |
cc9f81b1d65bbe0e7b7b9e6899378221be2a9537 | tweed1e/networkasymmetry | R/solve_gamma.R | ########################################################################
# solve_lambda_gamma.R
# Function to solve for unobserved \Lambda and \Gamma, given observed A and G.
# License: MIT
# ""
# Jesse Tweedle
# , 2016
########################################################################
solve_gamma <- function(R... | 2,534 | mit |
00f255b3d71c0236ff12fe84ff0768980eb99e13 | stharrold/demo | demo/app_intro/examples/2016_RMachineLearningByExample/Ch6_PredictCredit/dt_classifier.R | library(rpart)# tree models
library(caret) # feature selection
library(rpart.plot) # plot dtree
library(ROCR) # model evaluation
library(e1071) # tuning model
source("performance_plot_utils.R") # plotting curves
## separate feature and class variables
test.feature.vars <- test.data[,-1]
test.class.var <- tes... | 2,349 | mit |
ca53789a149e73b184ef94b33778106fe03e73bf | chipster/chipster-tools | tools/ngs/R/test-mothur.R | # TOOL test-mothur.R: "Test-Mothur"
# INPUT file.fasta: "FASTA file" TYPE GENERIC
# INPUT final.count_table: "Mothur count file" TYPE MOTHUR_COUNT
# INPUT sequences-taxonomy-assignment.txt: "Sequences taxonomy assignment file" TYPE GENERIC
# OUTPUT OPTIONAL final.unique.list
# OUTPUT OPTIONAL final.asv.shared
# OUTPUT ... | 3,697 | mit |
b5a179cc122c58b014bd96c0b1a99707ffaa190d | ElCep/bazaRd | coop_viti/scrape_caves_particulieres.R | ##script pour parser les pages du site http://www.si-vitifrance.com/ pour les caves particulière
library(rgdal) ##manipumation de données spatial avec gdal
library(XML)
library(RCurl)
library(stringr) ##manipulation des chaines de charactères
rm(list=ls())
setwd("~/github/bazaRd/coop_viti/")
########################... | 1,969 | gpl-2.0 |
dc1c8e3884bdfe4f2cc5cc8d1b2c8bc0d562e9f0 | v2south/spatial_bgsmtr | R_file/Create_W_true.R | #load pacakages
library(mvtnorm)
library(MCMCpack)
library(miscTools)
library(PottsUtils)
library(matrixcalc)
set.seed(12)
rm(list=ls())
setwd(dir = "~/spatial_bgsmtr/")
# create a W_true matrix
# W_true matrix is simulated from the hierarchical model
# gr... | 5,866 | gpl-3.0 |
901488a995c8c514fb67b955aec87112d3f518fd | AlejandroRuete/IgnoranceMaps | SLWapp/server.R | require(raster)
require(rgdal)
library(maptools)
Swe<-readShapePoly("data/Sweden Simple Sweref.shp", proj4string=CRS("+proj=utm +zone=33 +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs"))
GreyColors<-colorRampPalette(c("white", "black"),interpolate="spline", space="Lab")( 16 )
RedBlue<-colorRampPalette(c("blue"... | 16,996 | gpl-3.0 |
81d8e554ba916dcfeaa7cffd2e1d939939e379b7 | MicroPasts/MicroPasts-Scripts | crowdSourcingAdmin/contributorLists.R | ## Creation of contributors to project text file.
# Set working directory (for example as below)
setwd("~/Documents/research/micropasts/analysis/contributions/") #MacOSX
#setwd("C:\\micropasts\\analysis") #Windows
#setwd("micropasts/analysis") #Linux
# Create CSV directory if it does not exist
if (!file.exists('csv')... | 2,279 | apache-2.0 |
531c5900fb4f7b992f5b9c96dc9b66cee686f5bb | polde-live/sgh-labs | 20161015_przetw/20161015_setup.R | # Laboratorium z przetwarzania danych
# 2016-10-15
# Biblioteki do realizacji poszczególnych zadań
library(sas7bdat)
library(dplyr)
library(lubridate)
library(stringr)
# Uwaga - tylko na komputerze z uczelni!
setwd(d);
# Czytanie zbioru sas do f
# Biblioteka sas7bdat
# Funkcja sas7bdat::read.sas7bdat
readsas <- func... | 453 | unlicense |
40185032b62834a5b0d82a34f06f44037e84e304 | DFITC/fts | c1/1-1.R | #
# Copyright (c) 2015-2016 by Yuchao Zhao, Xiaoye Meng.
#
# 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 prog... | 962 | gpl-3.0 |
40185032b62834a5b0d82a34f06f44037e84e304 | xiaoyem/fts | c1/1-1.R | #
# Copyright (c) 2015-2016 by Yuchao Zhao, Xiaoye Meng.
#
# 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 prog... | 962 | gpl-3.0 |
986619e724f5fb856711673e172f75b1db02cd78 | keboola/application-sample | gettingStarted.R | #' this script will get you going
#'
#'
installedPackages <- rownames(installed.packages())
cranPackages <- c("devtools", "shiny", "DT", "ggplot2", "plotly")
new.packages <- cranPackages[!(cranPackages %in% installedPackages)]
if(length(new.packages)) install.packages(new.packages)
library(devtools)
if (("aws.si... | 1,124 | mit |
3174222824dc7bdad8b99df7621dabff92790827 | mexicoevalua/app_municipios | server.R | library(shiny)
# Load the ggplot2 package which provides
# the 'mpg' dataset.
data <- read.csv("data/data_table.csv", encoding="utf8")
# Define a server for the Shiny app
shinyServer(function(input, output) {
# Filter data based on selections
output$table <- renderDataTable({
if (input$estado != "Todos"... | 569 | mit |
412cbe6ae82169b0f817a624bd0a398246dc1d46 | ttriche/dma | R/model.update3.R | model.update3 <-
function (piold, gamma, eps, y, yhat, predvar) {
# Revised June 29, 2009:
# Modified to regularize the posterior model probabilities away from zero
# by adding eps to each one and renormalizing.
# August 23, 2007. Update model posterior probabilities using
# flattening. See C8338-9.
# This will be... | 1,040 | gpl-2.0 |
c4091591db74fc2d986696c1fe146ea20ebe3ba0 | SCAR/solong | data-raw/equations_krill.R | refs$Goeb2007 <- bibentry(bibtype="Article",key="Goeb2007",
author=c(person(c("M","E"),"Goebel"),person(c("J","D"),"Lipsky"),person(c("C","S"),"Reiss"),person(c("V","J"),"Loeb")),
year=2007,
title="Using carapace measurements to dete... | 55,797 | mit |
cf98983afb6d24fc0dec9d44cbcdd2b0114126e1 | isidiomartins/TESTE | ui.R | # ui.R
library(shiny)
portarias <- readRDS("portarias_MAPA_2016-09-08.RDS")
# Define UI for application that draws a histogram
shinyUI(fluidPage(
HTML('<div align = "center">'),
# Application title
titlePanel("Portarias do Ministério da Agricultura, Pecuária e Abastecimento"),
HTML('</div>'),
# Sidebar with... | 1,057 | gpl-3.0 |
dc48243b883e97fb8159dd7431e529afe5047c80 | rgorman/syntacto_stylistics | R_files/code/open_ling/chunkByCountRelPos_July28.R | library(XML)
source("code/corpusFunctions.R")
input.dir <- "../rel_pos_prose"
files.v <- dir(path=input.dir, pattern=".*xml")
#the following script calls the user-defined function "getSwordChunkMaster).
#this function will return a list of lists of tables, each table with a maximum of words = the second variable
... | 2,362 | cc0-1.0 |
dd8c175a13cfe3e4e443f51822c8f520f2e69bfc | pchmieli/h2o-3 | h2o-r/h2o-package/R/export.R | #`
#` Data Export
#`
#` Export data to local disk or HDFS.
#` Save models to local disk or HDFS.
#' Export an H2O Data Frame to a File
#'
#' Exports an H2O Frame (which can be either VA or FV) to a file.
#' This file may be on the H2O instace's local filesystem, or to HDFS (preface
#' the path with hdfs://) or to S3N ... | 5,183 | apache-2.0 |
90ef48829092b8d1cc8b2a2c11e17638477cc566 | yukoga/useful-r | chap3 preprocessing and transform/3-2 how to deal with missing data.R | employee.IQ.JP <- data.frame(
IQ = c(78, 84, 84, 85, 87, 91, 92, 94, 94, 96, 99, 105, 105, 106, 108, 112, 113, 115, 118, 134),
JobPerformance = c(9, 13, 10, 8, 7, 7, 9, 9, 11, 7, 7, 10, 11, 15, 10, 10, 12, 14, 16, 12)
)
employee.IQ.JP
# create missing data flag
library(ggplot2)
employee.IQ.JP$MCAR <- employee.IQ.J... | 1,439 | mit |
959d065853c0f18a409f8862008af865b8fe2389 | nickreich/hospital-surv-data | code/read-data.R | #########################################
#########################################
### Research project: ###
### characterizing seasonal epidemics ###
### Emily Ramos, Nick Reich ###
### Modified 11/17/14 ###
#########################################
##########################... | 4,334 | gpl-2.0 |
dc48243b883e97fb8159dd7431e529afe5047c80 | rgorman/SyntaxMetrics | R_files/code/open_ling/chunkByCountRelPos_July28.R | library(XML)
source("code/corpusFunctions.R")
input.dir <- "../rel_pos_prose"
files.v <- dir(path=input.dir, pattern=".*xml")
#the following script calls the user-defined function "getSwordChunkMaster).
#this function will return a list of lists of tables, each table with a maximum of words = the second variable
... | 2,362 | gpl-2.0 |
6777b724cbc1a265ab6b5bd8818244ab3415e177 | ArdiaD/PeerPerformance | R/sharpeTesting.R | ## Set of R functions for Sharpe ratio testing
# #' @name .sharpeTesting
# #' @import compiler
.sharpeTesting <- function(x, y, control = list()) {
x <- as.matrix(x)
y <- as.matrix(y)
# process control parameters
ctr <- processControl(control)
# check if enough data are available for testing
dxy <... | 15,101 | gpl-2.0 |
75913ce251243f34d4183b4df3a0db93f13e9178 | cran/dcemri | demo/avg152T1_RL.R | avg152T1.RL <- read.img("avg152T1_RL_nifti")
X <- nrow(avg152T1.RL)
Y <- ncol(avg152T1.RL)
Z <- nsli(avg152T1.RL)
zrange <- range(avg152T1.RL)
par(mfrow=c(10,10), mar=rep(0,4))
for (z in 1:Z) {
image(1:X, 1:Y, avg152T1.RL[X:1,,z], zlim=zrange, col=grey(0:64/64),
xlab="", ylab="", axes=FALSE)
}
| 308 | bsd-3-clause |
8230bd705262a1b8dcb3b9e5b7b88e99ee20b16e | Gargonslipfisk/NLP | Topic_Modeling_2.R | #Ruta del directorio de trabajo
setwd("~/Erreria/Topic Modelling")
#Importa corpus como caracteres
Hoteles_raw = readLines("Hotels.csv", encoding = "ANSI")
#Convierte corpus a matriz
Hoteles = as.matrix(Hoteles_raw)
library(textcat)
c <- textcat(Hoteles)
# z <- cbind(Hoteles,c)
# names(z)<- c("verbatim","l... | 5,023 | gpl-3.0 |
05a7d07d6dbaee6992d1d7683b9e1e35f484e884 | gleday/ShrinkNet | R/getSVD.R | #' Convenience function for singular value decomposition
#'
#' @param ii integer. Gene index.
#' @param tX p by n matrix of gene expression.
#'
#' @details
#' The function returns the singular value decomposition of X_{ii}=UDV^T where
#' X_{ii} is the transpose of tX_{ii} which represents the matrix tX without the iith... | 668 | gpl-2.0 |
e8d727817ab0932e9b3597eec0bd88a5bb7633eb | oneillkza/ContiBAIT | R/plotContigOrder.R | plotContigOrder.func <- function(contigOrder, lg='all', verbose=TRUE)
{
masterGroups <- sapply(1:nrow(contigOrder), function(x) strsplit(as.character(contigOrder[,1]), "\\.")[[x]][1])
if(lg == 'all'){lg <- seq(1:length(unique(masterGroups)))}
for(link in lg)
{
if(verbose){message(' -> Processing ', link)}
con... | 3,738 | bsd-2-clause |
07bd15ba1428d40c5b475f388468267e91bf0b6c | mingkaijiang/quasi_equil_analytical | Plots/Figure5.R |
#### Functions to generate Figure 5
#### Purpose:
#### to draw barchart of wood, slow and passive SOM pools
#### and demonstrate the effect of wood stoichiometric flexibility
################################################################################
######### Main program
Figure_5_plotting <- function() {
m... | 1,642 | gpl-3.0 |
c0370bfa2a9389fa002791d82ff6aef28cf9ed5e | rho-devel/rho | src/extra/testr/filtered-test-suite/isnan/tc_isnan_8.R | expected <- eval(parse(text="c(FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, FALSE)"));
test(id=0, code={
argv <- eval(parse(text="list(c(-Inf, 2.17292368994844e-311, 4.3458473798... | 852 | gpl-2.0 |
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