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 |
|---|---|---|---|---|---|
5ca2f288ba2ae5ba7d7f59bb12791c9b79deb399 | inbo/multimput | R/missing_at_random.R | #' Generate missing data at random
#'
#' The observed values will be either equal to the counts or missing.
#' The probability of missing is the inverse of the counts + 1.
#'
#' @param dataset A dataset to a the observation with missing data.
#' @param proportion The proportion of observations that will be missing.
#' ... | 862 | gpl-3.0 |
b13f23d16bc6cde5bfd081bb75aee9d965bfe199 | elahi/cupCorals | bael_IPM_fecundityTest.R | #################################################
# Author: Robin Elahi
# Date: 160315
# Testing the sensitivity of IPM results to variation in
# Ea on x-intercept of fecundity function (which has
# downstream effects on size at maturity, establishment probability)
#################################################
#r... | 4,361 | mit |
674c7a992a5c6c9042b7befb3ab68da1dc13ea69 | C2SM/plotmap-2.3.7 | R/contour.map.R | `contour.map` <-
function(x,y,z,grid.type="lonlat",grid.pars=list(),
lonlim,latlim,
projection="",parameters=NULL,orientation=NULL,
mapdat="world",xmaplim,ymaplim,thin.map=0,
nlevels = 10,
levels=pretty.contours(range(z,finite=TRUE), n=nlevels),
col=par("fg"),lty=p... | 5,366 | gpl-2.0 |
2b71f2c006e2346724fa85f16297f983dfa26778 | famuvie/breedR | tests/testthat/test-splines.R |
context("Splines infrastructure")
########################
test_that("determine.n.knots works for atomic vectors", {
test.length <- 100
sample.sizes <- seq(from = 7, by = 19, length = test.length)
expect_that(length(breedR:::determine.n.knots(sample.sizes)),
equals(test.length))
})
test_that("de... | 1,269 | gpl-3.0 |
2c9e913da436c53cf7cc9a0a8f4b0605ac153ab2 | lehoangha/GSOE9712_S115_RA | packrat/lib/x86_64-pc-linux-gnu/3.2.1/XLConnect/unitTests/runit.workbook.isSheetVisible.R | #############################################################################
#
# XLConnect
# Copyright (C) 2010-2013 Mirai Solutions GmbH
#
# 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... | 2,167 | apache-2.0 |
0734ee3cfc02a3c8ebc2d79a323263c5e642848b | florianm/shreadthatsheet | global.R | library(ckanr)
library(lubridate)
# source("setup_ckan_connection.R")
#' Load a CSV from a URL, title case colnames and parse dates
#'
#' @param url The URL of a CSV file
#' @param date_colnames The column names of date columns, default:
#' 'LastUpdated', 'date', 'Date', date.start', 'date.end', 'year', 'Year'
#' ... | 1,482 | mit |
2d13108829f74b4f73fa23aabd6053ebb5a855b5 | bedatadriven/renjin | packages/stats/tests/test.stats.fft.0fc2f51f7a42b2d9df25fb0d9dac9cdb.R | library(hamcrest)
expected <- c(0x1.a4ecc1f250468p+5 + 0x1.740d87b57be44p-1i, -0x1.6f3df07aa3b26p+5 + -0x1.690cf13a2dc6cp-1i,
0x1.694b0247373d7p+5 + 0x1.5db1236588c38p-1i, -0x1.43f70a8d7a08ep+4 + -0x1.51fcfcd9080d7p-1i,
0x1.81d1dd2879887p+5 + 0x1.45f372881075ap-1i, -0x1.270e6161ac312p+5 + -0x1.39978ef8b3c37p-1i,
0... | 17,223 | gpl-2.0 |
2d13108829f74b4f73fa23aabd6053ebb5a855b5 | jukiewiczm/renjin | packages/stats/src/test/R/test.stats.fft.0fc2f51f7a42b2d9df25fb0d9dac9cdb.R | library(hamcrest)
expected <- c(0x1.a4ecc1f250468p+5 + 0x1.740d87b57be44p-1i, -0x1.6f3df07aa3b26p+5 + -0x1.690cf13a2dc6cp-1i,
0x1.694b0247373d7p+5 + 0x1.5db1236588c38p-1i, -0x1.43f70a8d7a08ep+4 + -0x1.51fcfcd9080d7p-1i,
0x1.81d1dd2879887p+5 + 0x1.45f372881075ap-1i, -0x1.270e6161ac312p+5 + -0x1.39978ef8b3c37p-1i,
0... | 17,223 | gpl-3.0 |
ca7e18a99ba95fa07342221024cfe0416246af6d | gaoyuanjun/SHINYstan | inst/SHINYstan/server_files/outputs/density_plot_reactive.R | # density_plot
density_plot <- reactive({
if (input$param == "") {
return()
}
customize <- input$dens_customize
if (customize & is.null(input$dens_x_breaks)) {
# delay until the customization inputs are ready
return()
}
do.call(".param_dens", args = list(
param = input$param,
da... | 803 | mit |
04431de0afe1ed8a0799270b3fd8f20ce284e195 | jimmyy11/my_project | number_sum.R | number_sum <- function(number_vec, ratio = 2){
number_vec <- number_vec*ratio
sum_vec <- sum(number_vec)
return(sum_vec)
} | 128 | gpl-3.0 |
5c7735809278dc90a2f92f6cfd4f647e8f368e00 | sanuj/shogun | examples/undocumented/r_static/distribution_hmm.R | library("sg")
order <- 3
gap <- 0
reverse <- 'n'
fm_train_dna <- as.matrix(read.table('../data/fm_train_dna.dat'))
fm_train_cube <- as.matrix(read.table('../data/fm_train_cube.dat', colClasses=c('character')))
# HMM
print('HMM')
N <- 3
M <- 6
order <- 1
hmms <- c()
liks <- c()
dump <- sg('set_features', 'TRAIN', f... | 609 | gpl-3.0 |
5c7735809278dc90a2f92f6cfd4f647e8f368e00 | Ialong/shogun | examples/undocumented/r_static/distribution_hmm.R | library("sg")
order <- 3
gap <- 0
reverse <- 'n'
fm_train_dna <- as.matrix(read.table('../data/fm_train_dna.dat'))
fm_train_cube <- as.matrix(read.table('../data/fm_train_cube.dat', colClasses=c('character')))
# HMM
print('HMM')
N <- 3
M <- 6
order <- 1
hmms <- c()
liks <- c()
dump <- sg('set_features', 'TRAIN', f... | 609 | gpl-3.0 |
122ac8c02961b5dea4635d01ca9219bb4f7dc6f8 | jdyen/FREE | R/fitted.FREEfit.R | ##' @method fitted FREEfit
##' @export
fitted.FREEfit <-
function(object, ...){
object$fitted
}
| 98 | gpl-3.0 |
5c7735809278dc90a2f92f6cfd4f647e8f368e00 | curiousguy13/shogun | examples/undocumented/r_static/distribution_hmm.R | library("sg")
order <- 3
gap <- 0
reverse <- 'n'
fm_train_dna <- as.matrix(read.table('../data/fm_train_dna.dat'))
fm_train_cube <- as.matrix(read.table('../data/fm_train_cube.dat', colClasses=c('character')))
# HMM
print('HMM')
N <- 3
M <- 6
order <- 1
hmms <- c()
liks <- c()
dump <- sg('set_features', 'TRAIN', f... | 609 | gpl-3.0 |
5c7735809278dc90a2f92f6cfd4f647e8f368e00 | Saurabh7/shogun | examples/undocumented/r_static/distribution_hmm.R | library("sg")
order <- 3
gap <- 0
reverse <- 'n'
fm_train_dna <- as.matrix(read.table('../data/fm_train_dna.dat'))
fm_train_cube <- as.matrix(read.table('../data/fm_train_cube.dat', colClasses=c('character')))
# HMM
print('HMM')
N <- 3
M <- 6
order <- 1
hmms <- c()
liks <- c()
dump <- sg('set_features', 'TRAIN', f... | 609 | mit |
3c1565a5ca9ee8d22046fd497862cd518048954b | emoron/Data_Science_Riot | Bill_James_Estimators/James_Pythag.R |
###The first section of code is used to gather the data from the Lahman database using a RMySQL connection.
###I left the code so anyone who doen't have R connected directly to the dbase can still see the
###required SQL code to gather the requried information.
library(RMySQL)
##Connect to database. Username and pas... | 2,353 | gpl-2.0 |
5c7735809278dc90a2f92f6cfd4f647e8f368e00 | ratschlab/ASP | examples/undocumented/r_static/distribution_hmm.R | library("sg")
order <- 3
gap <- 0
reverse <- 'n'
fm_train_dna <- as.matrix(read.table('../data/fm_train_dna.dat'))
fm_train_cube <- as.matrix(read.table('../data/fm_train_cube.dat', colClasses=c('character')))
# HMM
print('HMM')
N <- 3
M <- 6
order <- 1
hmms <- c()
liks <- c()
dump <- sg('set_features', 'TRAIN', f... | 609 | gpl-2.0 |
5c7735809278dc90a2f92f6cfd4f647e8f368e00 | youssef-emad/shogun | examples/undocumented/r_static/distribution_hmm.R | library("sg")
order <- 3
gap <- 0
reverse <- 'n'
fm_train_dna <- as.matrix(read.table('../data/fm_train_dna.dat'))
fm_train_cube <- as.matrix(read.table('../data/fm_train_cube.dat', colClasses=c('character')))
# HMM
print('HMM')
N <- 3
M <- 6
order <- 1
hmms <- c()
liks <- c()
dump <- sg('set_features', 'TRAIN', f... | 609 | gpl-3.0 |
5c7735809278dc90a2f92f6cfd4f647e8f368e00 | AzamYahya/shogun | examples/undocumented/r_static/distribution_hmm.R | library("sg")
order <- 3
gap <- 0
reverse <- 'n'
fm_train_dna <- as.matrix(read.table('../data/fm_train_dna.dat'))
fm_train_cube <- as.matrix(read.table('../data/fm_train_cube.dat', colClasses=c('character')))
# HMM
print('HMM')
N <- 3
M <- 6
order <- 1
hmms <- c()
liks <- c()
dump <- sg('set_features', 'TRAIN', f... | 609 | gpl-3.0 |
5c7735809278dc90a2f92f6cfd4f647e8f368e00 | jondo/shogun | examples/undocumented/r_static/distribution_hmm.R | library("sg")
order <- 3
gap <- 0
reverse <- 'n'
fm_train_dna <- as.matrix(read.table('../data/fm_train_dna.dat'))
fm_train_cube <- as.matrix(read.table('../data/fm_train_cube.dat', colClasses=c('character')))
# HMM
print('HMM')
N <- 3
M <- 6
order <- 1
hmms <- c()
liks <- c()
dump <- sg('set_features', 'TRAIN', f... | 609 | gpl-3.0 |
5c7735809278dc90a2f92f6cfd4f647e8f368e00 | elkingtonmcb/shogun | examples/undocumented/r_static/distribution_hmm.R | library("sg")
order <- 3
gap <- 0
reverse <- 'n'
fm_train_dna <- as.matrix(read.table('../data/fm_train_dna.dat'))
fm_train_cube <- as.matrix(read.table('../data/fm_train_cube.dat', colClasses=c('character')))
# HMM
print('HMM')
N <- 3
M <- 6
order <- 1
hmms <- c()
liks <- c()
dump <- sg('set_features', 'TRAIN', f... | 609 | gpl-3.0 |
5c7735809278dc90a2f92f6cfd4f647e8f368e00 | youprofit/shogun | examples/undocumented/r_static/distribution_hmm.R | library("sg")
order <- 3
gap <- 0
reverse <- 'n'
fm_train_dna <- as.matrix(read.table('../data/fm_train_dna.dat'))
fm_train_cube <- as.matrix(read.table('../data/fm_train_cube.dat', colClasses=c('character')))
# HMM
print('HMM')
N <- 3
M <- 6
order <- 1
hmms <- c()
liks <- c()
dump <- sg('set_features', 'TRAIN', f... | 609 | gpl-3.0 |
5c7735809278dc90a2f92f6cfd4f647e8f368e00 | cdawei/shogun | examples/undocumented/r_static/distribution_hmm.R | library("sg")
order <- 3
gap <- 0
reverse <- 'n'
fm_train_dna <- as.matrix(read.table('../data/fm_train_dna.dat'))
fm_train_cube <- as.matrix(read.table('../data/fm_train_cube.dat', colClasses=c('character')))
# HMM
print('HMM')
N <- 3
M <- 6
order <- 1
hmms <- c()
liks <- c()
dump <- sg('set_features', 'TRAIN', f... | 609 | gpl-3.0 |
5c7735809278dc90a2f92f6cfd4f647e8f368e00 | lukw00/shogun | examples/undocumented/r_static/distribution_hmm.R | library("sg")
order <- 3
gap <- 0
reverse <- 'n'
fm_train_dna <- as.matrix(read.table('../data/fm_train_dna.dat'))
fm_train_cube <- as.matrix(read.table('../data/fm_train_cube.dat', colClasses=c('character')))
# HMM
print('HMM')
N <- 3
M <- 6
order <- 1
hmms <- c()
liks <- c()
dump <- sg('set_features', 'TRAIN', f... | 609 | gpl-3.0 |
5c7735809278dc90a2f92f6cfd4f647e8f368e00 | pavel-odintsov/shogun | examples/undocumented/r_static/distribution_hmm.R | library("sg")
order <- 3
gap <- 0
reverse <- 'n'
fm_train_dna <- as.matrix(read.table('../data/fm_train_dna.dat'))
fm_train_cube <- as.matrix(read.table('../data/fm_train_cube.dat', colClasses=c('character')))
# HMM
print('HMM')
N <- 3
M <- 6
order <- 1
hmms <- c()
liks <- c()
dump <- sg('set_features', 'TRAIN', f... | 609 | gpl-3.0 |
5c7735809278dc90a2f92f6cfd4f647e8f368e00 | sperka/shogun | examples/undocumented/r_static/distribution_hmm.R | library("sg")
order <- 3
gap <- 0
reverse <- 'n'
fm_train_dna <- as.matrix(read.table('../data/fm_train_dna.dat'))
fm_train_cube <- as.matrix(read.table('../data/fm_train_cube.dat', colClasses=c('character')))
# HMM
print('HMM')
N <- 3
M <- 6
order <- 1
hmms <- c()
liks <- c()
dump <- sg('set_features', 'TRAIN', f... | 609 | gpl-3.0 |
5c7735809278dc90a2f92f6cfd4f647e8f368e00 | shangwuhencc/shogun | examples/undocumented/r_static/distribution_hmm.R | library("sg")
order <- 3
gap <- 0
reverse <- 'n'
fm_train_dna <- as.matrix(read.table('../data/fm_train_dna.dat'))
fm_train_cube <- as.matrix(read.table('../data/fm_train_cube.dat', colClasses=c('character')))
# HMM
print('HMM')
N <- 3
M <- 6
order <- 1
hmms <- c()
liks <- c()
dump <- sg('set_features', 'TRAIN', f... | 609 | gpl-3.0 |
5c7735809278dc90a2f92f6cfd4f647e8f368e00 | rcurtin/shogun | examples/undocumented/r_static/distribution_hmm.R | library("sg")
order <- 3
gap <- 0
reverse <- 'n'
fm_train_dna <- as.matrix(read.table('../data/fm_train_dna.dat'))
fm_train_cube <- as.matrix(read.table('../data/fm_train_cube.dat', colClasses=c('character')))
# HMM
print('HMM')
N <- 3
M <- 6
order <- 1
hmms <- c()
liks <- c()
dump <- sg('set_features', 'TRAIN', f... | 609 | gpl-3.0 |
5c7735809278dc90a2f92f6cfd4f647e8f368e00 | chenmoshushi/shogun | examples/undocumented/r_static/distribution_hmm.R | library("sg")
order <- 3
gap <- 0
reverse <- 'n'
fm_train_dna <- as.matrix(read.table('../data/fm_train_dna.dat'))
fm_train_cube <- as.matrix(read.table('../data/fm_train_cube.dat', colClasses=c('character')))
# HMM
print('HMM')
N <- 3
M <- 6
order <- 1
hmms <- c()
liks <- c()
dump <- sg('set_features', 'TRAIN', f... | 609 | gpl-3.0 |
5c7735809278dc90a2f92f6cfd4f647e8f368e00 | JingheZ/shogun | examples/undocumented/r_static/distribution_hmm.R | library("sg")
order <- 3
gap <- 0
reverse <- 'n'
fm_train_dna <- as.matrix(read.table('../data/fm_train_dna.dat'))
fm_train_cube <- as.matrix(read.table('../data/fm_train_cube.dat', colClasses=c('character')))
# HMM
print('HMM')
N <- 3
M <- 6
order <- 1
hmms <- c()
liks <- c()
dump <- sg('set_features', 'TRAIN', f... | 609 | gpl-3.0 |
5c7735809278dc90a2f92f6cfd4f647e8f368e00 | kostajaitachi/shogun | examples/undocumented/r_static/distribution_hmm.R | library("sg")
order <- 3
gap <- 0
reverse <- 'n'
fm_train_dna <- as.matrix(read.table('../data/fm_train_dna.dat'))
fm_train_cube <- as.matrix(read.table('../data/fm_train_cube.dat', colClasses=c('character')))
# HMM
print('HMM')
N <- 3
M <- 6
order <- 1
hmms <- c()
liks <- c()
dump <- sg('set_features', 'TRAIN', f... | 609 | gpl-3.0 |
752f2ae459b50736a337d198107e065756a46d1f | jpritikin/OpenMx | R/MxRowObjective.R | #
# Copyright 2007-2019 by the individuals mentioned in the source code history
#
# 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
... | 1,958 | apache-2.0 |
5c7735809278dc90a2f92f6cfd4f647e8f368e00 | abhiatgithub/shogun-toolbox | examples/undocumented/r_static/distribution_hmm.R | library("sg")
order <- 3
gap <- 0
reverse <- 'n'
fm_train_dna <- as.matrix(read.table('../data/fm_train_dna.dat'))
fm_train_cube <- as.matrix(read.table('../data/fm_train_cube.dat', colClasses=c('character')))
# HMM
print('HMM')
N <- 3
M <- 6
order <- 1
hmms <- c()
liks <- c()
dump <- sg('set_features', 'TRAIN', f... | 609 | gpl-3.0 |
5c7735809278dc90a2f92f6cfd4f647e8f368e00 | arasuarun/shogun | examples/undocumented/r_static/distribution_hmm.R | library("sg")
order <- 3
gap <- 0
reverse <- 'n'
fm_train_dna <- as.matrix(read.table('../data/fm_train_dna.dat'))
fm_train_cube <- as.matrix(read.table('../data/fm_train_cube.dat', colClasses=c('character')))
# HMM
print('HMM')
N <- 3
M <- 6
order <- 1
hmms <- c()
liks <- c()
dump <- sg('set_features', 'TRAIN', f... | 609 | gpl-3.0 |
dd0443fb0abd944fbe92635b5d09af89b2bb65c9 | laurieKell/lh | R/lh-generics.R | #### SRR
setGeneric('sv', function(model,params, ...)
standardGeneric('sv'))
setGeneric('ab', function(model,params, ...)
standardGeneric('ab'))
| 150 | gpl-2.0 |
e8ff3348199649308bf3b2b7fb60057ec5a5cb04 | aol-statsols/rm-char-create | R/change_Skills_To_Increase_Each_Level.R | #' A HEIGHT AND WEIGHT FUNCTION
#'
#' FUNCTION TO CHOOSE WHICH SKILLS TO INCREASE EACH LEVEL UNTIL YOU HAVE <10 DP REMAINING (TO GIVE A BUFFER)
#' @param skills.Increase.Record.DF A DATAFRAME CONTAINING WHICH SKILLS HAVE BEEN INCREASED AND HOW OFTEN.
#' @param dev_Points.Total AN INTEGER WHICH IS HOW MANY DEV POINT... | 8,042 | gpl-2.0 |
568f892af3d60dc410aa880b0561847cfaaa74aa | USGS-R/WQ-Review | inst/shiny/WQReviewGUI/server_excelLink.R | # #Populate excel sheets
xl.workbook.add()
xl.sheet.add("DQI needs review")
xlc$a1 = reports$unapprovedData
xl.sheet.add("Ready for DQI change")
xlc$a1 = data.frame(RECORD_NO = NA,
SITE_NO = NA,
STATION_NM = NA,
SAMPLE_START_DT = NA,
MEDI... | 1,776 | unlicense |
ffb52708cefd9dc816a75f74c40d8ad2a07270ee | Miscanthus-Germination/Model_with_Interface | Model/ElipsWeb.R | ###########################################################################
euler <- function(alpha=0, beta=0, gamma=0){
Ra <- matrix(c(cos(alpha), sin(alpha), 0, -sin(alpha), cos(alpha),
0, 0, 0, 1), ncol=3, byrow=T)
Rb <- matrix(c(1, 0, 0, 0, cos(beta), sin(beta), 0, -sin(b... | 2,745 | mit |
f7c8e15a304fce50e1c90dcf7383c93f0e6e39a9 | vervacity/ggr-project | R/plot.profile_heatmaps.not_stranded.R | #!/usr/bin/env Rscript
# description: take in deeptools matrix and plot
library(gplots)
library(RColorBrewer)
library(reshape2)
library(grid)
library(gridGraphics)
library(gridExtra)
# load GGR style guide
load_style_guide <- system("which ggr_style_guide.R", intern=TRUE)
source(load_style_guide)
# args
args <- com... | 5,081 | mit |
977c109846fd4b65bf61559b6ec5ee0d0231e879 | sammorris81/rare-binary | code/analysis/simstudy/sim-3.R | rm(list=ls())
source("./package_load.R", chdir = TRUE)
# get the datasets
load("./simdata.RData")
# data setting and sets to include - written by bash script
setting <- 3
# extract the relevant setting from simdata
y <- simdata[[setting]]$y
s <- simdata[[setting]]$s
x <- simdata[[setting]]$x
# extract info about si... | 13,341 | gpl-2.0 |
b86c8702bb0c067547364fd6bada7116f54f95d8 | KellyChan/python-examples | python/data_science_de/Q4_1-plotting.R | setwd('path')
library(ggplot2)
library(scales)
#-----------------------------------------------------------------------------#
# Daily Visits
data <- read.csv('outputs/stat/tables/holecount-Date.csv', header=TRUE)
data$value <- as.Date(data$value)
p <- ggplot(data=data, aes(x=value, y=freq, group=1)) +
geom_line(... | 1,752 | mit |
b86c8702bb0c067547364fd6bada7116f54f95d8 | kwailamchan/programming-languages | python/data_science_de/Q4_1-plotting.R | setwd('path')
library(ggplot2)
library(scales)
#-----------------------------------------------------------------------------#
# Daily Visits
data <- read.csv('outputs/stat/tables/holecount-Date.csv', header=TRUE)
data$value <- as.Date(data$value)
p <- ggplot(data=data, aes(x=value, y=freq, group=1)) +
geom_line(... | 1,752 | mit |
b86c8702bb0c067547364fd6bada7116f54f95d8 | KellyChan/Python | python/data_science_de/Q4_1-plotting.R | setwd('path')
library(ggplot2)
library(scales)
#-----------------------------------------------------------------------------#
# Daily Visits
data <- read.csv('outputs/stat/tables/holecount-Date.csv', header=TRUE)
data$value <- as.Date(data$value)
p <- ggplot(data=data, aes(x=value, y=freq, group=1)) +
geom_line(... | 1,752 | mit |
e6cb91ce42d8a09dc94ab57d69ee7d1ac001dbfd | cxxr-devel/cxxr-svn-mirror | src/library/base/R/attach.R | # File src/library/base/R/attach.R
# Part of the R package, http://www.R-project.org
#
# Copyright (C) 1995-2012 The R Core Team
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either ve... | 9,643 | gpl-2.0 |
e6cb91ce42d8a09dc94ab57d69ee7d1ac001dbfd | glycerine/bigbird | r-3.0.2/src/library/base/R/attach.R | # File src/library/base/R/attach.R
# Part of the R package, http://www.R-project.org
#
# Copyright (C) 1995-2012 The R Core Team
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either ve... | 9,643 | bsd-2-clause |
528a0685744d47c826fcf4822b2dfb7583e109bf | PFgimenez/thesis | R-files/script_learn_BN.R | #!/usr/bin/Rscript
{
# Parameters : outfile header dataset1 dataset2 …
args = commandArgs(trailingOnly=TRUE)
if(length(args) < 4)
{
stop("Pas assez de paramètres ! Paramètres : outfile algo header dataset1 dataset2 ...")
}
fichier = args[1]
algo = args[2]
header = eval(parse(text=args[3])) # on ... | 4,300 | gpl-3.0 |
528a0685744d47c826fcf4822b2dfb7583e109bf | PFgimenez/PhD | R-files/script_learn_BN.R | #!/usr/bin/Rscript
{
# Parameters : outfile header dataset1 dataset2 …
args = commandArgs(trailingOnly=TRUE)
if(length(args) < 4)
{
stop("Pas assez de paramètres ! Paramètres : outfile algo header dataset1 dataset2 ...")
}
fichier = args[1]
algo = args[2]
header = eval(parse(text=args[3])) # on ... | 4,300 | gpl-3.0 |
a0d91784e07e0dbc122ed0fc1acb654a5e5f780a | adrHuerta/PISCO_Temp | examples/trends/stefan_case.R | library(xts)
library(dplyr)
library(data.table)
rm(list = ls())
### source codes
source('./functions/tools_get_os.R')
##############
if( get_os() == "windows" ) {
load(file.path("G:","DATABASES","DATA","TEMPERATURE_OBSDATASET","databases","step06_QCDATA_05.RData"))
ls()
} else if ( get_... | 1,725 | gpl-3.0 |
a6ec996ad45421f9c5ec929cc2b924f58999bc92 | kakaba2009/MachineLearning | r/R/zzz.R | loadModule("lnlp_module", TRUE)
loadModule("block_lnlp_module", TRUE)
loadModule("xmap_module", TRUE)
.onAttach <- function(...) {
if (!interactive()) return()
intro_message <- paste("If you're new to the rEDM package, please check out the tutorial:",
"> vignette(\"rEDM_tutorial... | 380 | apache-2.0 |
62e3d94b4484bb1a832c6c907468a23fb88ae348 | jread-usgs/necsc-lake-modeling | scripts/datarelease_shapefile.R | library(rgdal)
library(dplyr)
m2ft <- 3.28084
gh_layer <- readOGR('hansen_et_al_lakes','hansen_et_al_lakes')
categories <- read.csv('../climate-fish-habitat/cache/fetch/fish_dominance_categories_by_lake_medians.csv', stringsAsFactors = FALSE, header=TRUE) %>%
rename(WBDY_WBIC=WBIC, early=X1989.2014, mid=X2040.2064, ... | 2,313 | cc0-1.0 |
8555899703e4cdedac2bc57e94991dd137e1a189 | bomeara/sleq | R/GetCodonPhase.R | #' @title Determine the best codon phase and return amino acid sequence
#'
#' @name GetCodonPhase
#'
#' @description \code{GetCodonPhase} determines the best translated amino acid sequence from a consensus DNA alignment by identifying the codon phase that produces the fewest number of stop codons. \code{translate} fr... | 3,710 | gpl-2.0 |
1a7c4fcc98c229af3d4231291d8d96c168716fe3 | droglenc/FSAmisc | R/TroutDietSL.R | #' @title Size and diet data for lake and bull trout from Swan Lake, Montana.
#'
#' @description Size (standard length, total length, and weight) and diet data (volume of three main prey categories) for Bull Trout (\emph{Salvelinus confluentus}) and Lake Trout (\emph{Salvelinus namaycush}) from Swan Lake, Montana, a la... | 2,297 | gpl-2.0 |
62e3d94b4484bb1a832c6c907468a23fb88ae348 | lawinslow/necsc-lake-modeling | scripts/datarelease_shapefile.R | library(rgdal)
library(dplyr)
m2ft <- 3.28084
gh_layer <- readOGR('hansen_et_al_lakes','hansen_et_al_lakes')
categories <- read.csv('../climate-fish-habitat/cache/fetch/fish_dominance_categories_by_lake_medians.csv', stringsAsFactors = FALSE, header=TRUE) %>%
rename(WBDY_WBIC=WBIC, early=X1989.2014, mid=X2040.2064, ... | 2,313 | cc0-1.0 |
62e3d94b4484bb1a832c6c907468a23fb88ae348 | USGS-R/necsc-lake-modeling | scripts/datarelease_shapefile.R | library(rgdal)
library(dplyr)
m2ft <- 3.28084
gh_layer <- readOGR('hansen_et_al_lakes','hansen_et_al_lakes')
categories <- read.csv('../climate-fish-habitat/cache/fetch/fish_dominance_categories_by_lake_medians.csv', stringsAsFactors = FALSE, header=TRUE) %>%
rename(WBDY_WBIC=WBIC, early=X1989.2014, mid=X2040.2064, ... | 2,313 | cc0-1.0 |
9cb7d94d67171aef9255c8ab12cc33f4565a692a | joshgabriel/dft-crossfilter | benchmark-view/ShinyApps/Numerical_Precs_Methods_Scripts/hennig_nls.R | #x11(width=1, height=1) # X11 Plot dimensions
library(minpack.lm) # Load the minpack.lm package
mydata = read.csv("Rdata.csv") # Read CSV data file
x<-mydata$Kpts_atom # Select the kpoints atom density
y<-mydata$P
dy<-mydata$P_err # Select the ground state energy E0
l = len... | 4,803 | mit |
118533d62a60d9fb26c540e9865fee75b8f3a675 | gavinsimpson/analogue | R/dissimilarities.R | ###########################################################################
## ##
## dissimilarities - Extracts dissimilarities from fitted models ##
## ##
## Created ... | 1,675 | gpl-2.0 |
d589d052af1fdf78023f4900409060bab57247ce | omarbenites/shinyApps | R/progressbar2/progressbar2.R | runApp(list(
ui = pageWithSidebar(
headerPanel("Test"),
sidebarPanel(
tags$head(tags$style(type="text/css", "
#loadmessage {
position: fixed;
top: 0px;
left: 0px;
width:... | 1,063 | gpl-2.0 |
118533d62a60d9fb26c540e9865fee75b8f3a675 | jarioksa/analogue | R/dissimilarities.R | ###########################################################################
## ##
## dissimilarities - Extracts dissimilarities from fitted models ##
## ##
## Created ... | 1,675 | gpl-2.0 |
7f9f75873992f2a270ee4c7862b40d82b26c4b43 | Tenenhaus/RGCCA | R/print_comp.R | #' Print the variance of a component
#'
#' Prints the percent of explained variance for a component of a block
#' (by default, the superblock or the last one) analysed by R/SGCCA
#'
#' @inheritParams plot_ind
#' @param n An integer giving the index of the analysis component
#' @param i An integer giving the index of a... | 1,253 | gpl-2.0 |
750f12ebb74fe729b941403dcc5967922482dba6 | wuletawu/Rsenal | R/rasterizeGimms.R | #' Rasterize GIMMS 3G binary data
#'
#' @description
#' Convert GIMMS 3G binary data to an object of class \code{raster} by the use
#' of an ENVI header file.
#'
#' @param file Character. GIMMS binary file to rasterize.
#' @param headerfile Character. Companion header file passed on to
#' \code{\link{read.ENVI}}. ... | 2,762 | gpl-3.0 |
41bf50393a1ad08067c5ea435076ac5b53d723c2 | rorynolan/filesstrings | R/str-locate.R | #' Locate the braces in a string.
#'
#' See [strex::str_locate_braces()].
#'
#' @inheritParams strex::str_locate_braces
#'
#' @export
locate_braces <- strex::str_locate_braces
#' @rdname locate_braces
#' @export
str_locate_braces <- locate_braces
#' Get the indices of the \eqn{n}th instance of a pattern.
#'
#' See [s... | 811 | gpl-3.0 |
8233b266e00d84e88b9da31078864b43f51a848a | richelbilderbeek/Rcpp | R/RcppLdpath.R | # Copyright (C) 2010 - 2013 Dirk Eddelbuettel and Romain Francois
#
# This file is part of Rcpp.
#
# Rcpp 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 option) ... | 2,844 | gpl-3.0 |
8233b266e00d84e88b9da31078864b43f51a848a | experimentalDataAesthetics/smallOFmodules | rcpp/Rcpp/R/RcppLdpath.R | # Copyright (C) 2010 - 2013 Dirk Eddelbuettel and Romain Francois
#
# This file is part of Rcpp.
#
# Rcpp 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 option) ... | 2,844 | gpl-2.0 |
5a41b1728047a8c5e9ac7b3b4666809de9533702 | armgong/DistributedR | algorithms/HPdutility/R/hpdsample.R | #####################################################################################
# Copyright [2013] Hewlett-Packard Development Company, L.P. #
# #
# This program is free software; you can redistribute it and/... | 14,191 | gpl-2.0 |
77587c5f29f4cc8f3f3b1aa6137c5c4395020a51 | arnejohannesholmin/TSD | R/setrange.R | #*********************************************
#*********************************************
#' Sets the range of the input object 'x' to [a,b] (stretching or shrinking and displacing 'x').
#' The calculation is done by the following procedure:
#' (x - min(x)) * (b-a) / (max(x) - min(x)) + a = x * s - min(x) * s... | 2,261 | lgpl-3.0 |
c03f6ea7e4e3d2d7064d73b2d2a1ad1878be291a | Rgui/REndo_1.0 | R/hmlewbel.R | #'@title Fitting Linear Models with Endogenous Regressors using Lewbel's Higher Moments Approach
#'@aliases hmlewbel
# Description
#'@description Fits linear models with one endogenous regressor using internal instruments built using the approach described in
#' Lewbel A. (1997). This is a statistical technique to a... | 7,334 | gpl-3.0 |
7c008b7bea3c0e1f05cfcd0a8d67a28153c63eac | amyecampbell/hgsc_subtypes | 4.Survival/Scripts/B.Summarize_Survival.R | ############################################
# Cross-population analysis of high-grade serous ovarian cancer does not support four subtypes
#
# Way, G.P., Rudd, J., Wang, C., Hamidi, H., Fridley, L.B,
# Konecny, G., Goode, E., Greene, C.S., Doherty, J.A.
# ~~~~~~~~~~~~~~~~~~~~~
# This script will summarize all of th... | 11,017 | bsd-3-clause |
59a7b8afcf0176526f483e1ef3d7f68c2174f14b | markvanderloo/supral | examples/sparse_project.R |
# the system
# x + y = 10
# -x <= 0 # ==> x > 0
# -y <= 0 # ==> y > 0
# Defined in the row-column-coefficient form:
A <- data.frame(
row = c(1,1,2,3)
, col = c(1,2,1,2)
, coef= c(1,1,-1,-1)
)
b <- c(10,0,0)
sparse_project(x=c(4,5),A=A,b=b)
| 257 | gpl-3.0 |
9ca1d1f69fbb8e04149bc86807b1524072f9f89a | rfarouni/rfarouni.github.io | assets/projects/BayesianIRT/shinyStan_for_shinyapps/server_files/outputs/convergence_test_reactive.R | convergence_test <- reactive({
if (is.null(input$convergence_R) | is.null(input$convergence_thin)) {
return()
}
validate(need((nIter %% input$convergence_thin) == 0,
message = "Error: this value for 'Thin' leaves a remainder."))
do.call(".convergence_test", args = list(
session = sess... | 456 | mit |
c40a6649c7b7a19eef8f33fcf71c58b0660588c4 | burakbayramli/dersblog | stat/stat_170_pca/shalizi.R | load("pca-examples.Rdata")
nyt.pca = prcomp(nyt.frame[,-1])
nyt.latent.sem = nyt.pca$rotation
plot(nyt.pca$x[,1:2],type="n")
points(nyt.pca$x[nyt.frame[,"class.labels"]=="art",1:2],
pch="A",col="red")
points(nyt.pca$x[nyt.frame[,"class.labels"]=="music",1:2],
pch="M",col="blue")
| 294 | gpl-3.0 |
a975ff64fa812e9ec8c5a8feb85dd51ea631ff8e | annat22/publicationsDataRcode | intEvo_Artio_EvoBio42_2015/functions-EvoOfInt_EvoBio.R | ### FUNCTIONS needed for prtcl-EvoOfInt_EvoBio.R
#### kmN2Nkm
# Converts an array of k x m x N to a matrix of N x k*m.
# Input (XX) is an array of k x m x N (e.g., N=number of specimens, k=number of landmarks, m=number of dimensions).
# Output is a matrix of N specimens, where each specimen is a row vector arranged a... | 25,076 | gpl-2.0 |
c40a6649c7b7a19eef8f33fcf71c58b0660588c4 | burakbayramli/classnotes | stat/stat_170_pca/shalizi.R | load("pca-examples.Rdata")
nyt.pca = prcomp(nyt.frame[,-1])
nyt.latent.sem = nyt.pca$rotation
plot(nyt.pca$x[,1:2],type="n")
points(nyt.pca$x[nyt.frame[,"class.labels"]=="art",1:2],
pch="A",col="red")
points(nyt.pca$x[nyt.frame[,"class.labels"]=="music",1:2],
pch="M",col="blue")
| 294 | gpl-3.0 |
4a489050ad7700ee5be6d45ebe272761933bbbe1 | wxchan/LightGBM | R-package/R/lightgbm.R | #' Simple interface for training an lightgbm model.
#' Its documentation is combined with lgb.train.
#'
#' @rdname lgb.train
#' @export
lightgbm <- function(data,
label = NULL,
weight = NULL,
params = list(),
nrounds = 10,
... | 3,671 | mit |
4a489050ad7700ee5be6d45ebe272761933bbbe1 | olofer/LightGBM | R-package/R/lightgbm.R | #' Simple interface for training an lightgbm model.
#' Its documentation is combined with lgb.train.
#'
#' @rdname lgb.train
#' @export
lightgbm <- function(data,
label = NULL,
weight = NULL,
params = list(),
nrounds = 10,
... | 3,671 | mit |
4a489050ad7700ee5be6d45ebe272761933bbbe1 | Allardvm/LightGBM | R-package/R/lightgbm.R | #' Simple interface for training an lightgbm model.
#' Its documentation is combined with lgb.train.
#'
#' @rdname lgb.train
#' @export
lightgbm <- function(data,
label = NULL,
weight = NULL,
params = list(),
nrounds = 10,
... | 3,671 | mit |
73ff692be9cdb604f43d63b8fda94e0c296441ae | davetgerrard/GenomicLayers | scripts/predictFromSequence.loadResults.R | scores <- read.delim("data/HYDRA_runs/auto10k/auto10k.out.tab")
head(scores)
plot(scores); abline(v=3100)
subset(scores, iter > 3000 & iter < 3100)
load("data/HYDRA_runs/auto10k/auto10k.final.Rdata")
length(result)
tail(result$optimScores)
load("data/HYDRA_runs/layer5_10k/currentFactorSet.300.Rdata")
leng... | 819 | gpl-3.0 |
2a4ff37b1240a76be09ecb4e37224a5f0b3a685b | GregVial/WordGenerator | WordGenerator.R | ## Word generator
## Gregory Vial - 2016, June 24th
## R version of the generator designed by David Louapre sciencetonnante@gmail.com
## See https://goo.gl/g0ULlN for more info on original idea
## Run this program as many times as you want to generate new words!
## Initialize environment
# Set working directory (set ... | 1,584 | gpl-3.0 |
fe464e3e2f193c30fc7233bd7cbe00ff78abb967 | pschulam-attic/plibr | R/math.R | log_sum <- function(x) {
m <- max(x)
r <- sum(exp(x - m))
m + log(r)
}
log_normalize <- function(x) {
s <- log_sum(x)
x - s
}
| 147 | mit |
d6bb23f986cb51a7f0fea3b36b7988911338868b | orting/emphysema-estimation | Experiments/Experiment-1/StabilityPlots.R | stability.1 <- read.csv("Stability-1.out");
postscript(file="Stability-1-boxplot.ps",
bg="white"
);
boxplot(stability.1[stability.1[,1] == 2, 3],
stability.1[stability.1[,1] == 4, 3],
stability.1[stability.1[,1] == 6, 3],
stability.1[stability.1[,1] == 8, 3],
stabil... | 1,495 | gpl-3.0 |
ef9c31c029562e432b9f7121aa1e469f1dff6131 | erikjsolsen/AtlantisNEUS_R | NOBA/seabird forcing files.R | #' @title Creating NCDF forcing file for Increasing sea-bird mortality to replicate potential effects of wind farms in coastal areas of Norway
#' @details creates a .ncdf file with mortality forcing data pr. time step, box, species age group
#' @author Erik Olsen
mort_force <- function(rscale, boxes, ncfile){
#' LI... | 3,349 | mit |
5cdcf1552e4f4c88956d249295c5336987649e7e | neuromancer/ocean-results | Rscripts/mut_class.R | library("e1071")
#library("caret")
library("tm")
options(mc.cores=1)
dir = "../25-05-2014"
options(stringsAsFactors=F)
if (! ("mycon" %in% ls())) {
mycon = gzcon(gzfile(paste(dir, "sized_buggy_traces.csv.gz", sep="/"), open="r"))
buggy_program_events = read.csv(textConnection(readLines(mycon)), sep="\t", head... | 5,085 | gpl-3.0 |
533f2f4505066bedbb187eb8f04b5a5043080916 | harsh3375/Bank-Marketing | Harsh_Kumar_yadav_project_Phase_II.R | #Question 1
setwd("/Users/Harsh/Desktop/project_resubmit")
library(dplyr)
d <- read.csv("bank-full.csv",sep = ";",stringsAsFactors = FALSE)
glimpse(d)
str(d)
## grouping and dummy creation
## create Dummy Veriable
Dummies1=function(df,dvar){
t=table(df[,dvar])
t=sort(t)
... | 17,860 | apache-2.0 |
9814314d1ea4748fca40f5c935e8403ca01129ee | cran/circular | R/wallraff.test.R | #
# Wallraff procedure for comparing angular distances
#
# Allows to compare the deviation from an angle of interest
# between several data sets. If the angle of interest is
# the mean direction, then it becomes a comparison of
# angular dispersion around the mean.
#
# In essence, it is a rank-based test (Wilcoxon-Man... | 4,242 | gpl-2.0 |
1a7582ee18121efb5d29ce12901c719bc8367cf7 | maddin79/darch | R/RcppExports.R | # Generated by using Rcpp::compileAttributes() -> do not edit by hand
# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
applyDropoutMaskCpp <- function(data, mask) {
.Call('_darch_applyDropoutMaskCpp', PACKAGE = 'darch', data, mask)
}
ditherCpp <- function(data, columnMask) {
.Call('_darch_ditherCpp', P... | 2,306 | gpl-3.0 |
a950e56dbae4cefb6e7d934621f3dad617d7aac5 | randall-romero/CompEconR | R/qnwsimp.R | #==============================================================================
# QNWSIMP
#
#' Simpson's rule quadrature nodes and weights
#'
#' Generates Simpson's rule quadrature nodes and weights for computing the
#' definite integral of a real-valued function defined on a hypercube [a,b] in R^d.
... | 2,046 | mit |
18948983fdcb151247531bf136a74ea04a6e119a | MuhammadShuaib/mwmetrics | R/new_editor/historical.R | source("loader/monthly_new_wikipedians.R")
source("loader/all_monthly_users.R")
month.new_wikipedians = with(
load_monthly_new_wikipedians(reload=T),
rbind(
data.table(
month,
wiki = "ptwiki",
metric = "new wikipedians",
n = pt
),
data.table(
month,
wiki = "enwiki",
metric = "new wikipedia... | 4,799 | mit |
ae5a5d21c2db677860ba67a3e46c0f70cde9e870 | robertzk/objectdiff | tests/testthat/test-squish.R | test_that('it can squish a trivial example', {
expect_identical(squish_patches(NULL, list()), identity_patch(),
info = 'squishing no patches should just give the identity patch')
})
test_that('it can squish one patch into itself', {
iris2 <- iris
iris2[1, 1] <- NA
patch <- objectdiff(iris, iris2)
expect_... | 814 | mit |
18948983fdcb151247531bf136a74ea04a6e119a | mediawiki-utilities/python-mwmetrics | R/new_editor/historical.R | source("loader/monthly_new_wikipedians.R")
source("loader/all_monthly_users.R")
month.new_wikipedians = with(
load_monthly_new_wikipedians(reload=T),
rbind(
data.table(
month,
wiki = "ptwiki",
metric = "new wikipedians",
n = pt
),
data.table(
month,
wiki = "enwiki",
metric = "new wikipedia... | 4,799 | mit |
18948983fdcb151247531bf136a74ea04a6e119a | halfak/mwmetrics | R/new_editor/historical.R | source("loader/monthly_new_wikipedians.R")
source("loader/all_monthly_users.R")
month.new_wikipedians = with(
load_monthly_new_wikipedians(reload=T),
rbind(
data.table(
month,
wiki = "ptwiki",
metric = "new wikipedians",
n = pt
),
data.table(
month,
wiki = "enwiki",
metric = "new wikipedia... | 4,799 | mit |
2ca2ae323816470c5034ecac89708ef0b6920da8 | harvestchoice/hc-shiny | cell5mMap/ui.R | #####################################################################################
# Title: HarvestChoice Data API with leaflet
# Date: July 2015
# Project: HarvestChoice/IFPRI
# Authors: Bacou, Melanie <mel@mbacou.com>
#####################################################################################
head... | 3,654 | mit |
e84dfa5b14040f55e138fa1bef304a8157ecd6d5 | arc12/EdMOOC-SNA-X | Tie Type Comparison/Tie Type Correlation - All Courses.R | # iterate over a number of courses, executing "FAP Forums.Rmd" for each one.
# creates an HTML report for each course
library(knitr)
library(markdown)
# NB including an explicit "~/R Projects/Edinburgh MOOC/EdMOOC-SNA" as argument to markdownToHTML
# causes it to fail to find file. Also get figures directory in wrong... | 1,143 | mit |
3022a78da78219849df1d0e932399b9350a810b9 | JohnGavin/myFirstProject | tests/1.R | # Example Unit Testing Script
require(testthat)
expect_that(1, equals(1))
| 74 | apache-2.0 |
1b4e13dbc697c3aab14833d898f3187e6571e94c | duttashi/LearningR | scripts/statistical concepts/L5.0-Logistic-Regression-exercise.R | # Logistic Regression Exercise
# install the ISLR package and load the stock market data from it
library(ISLR)
attach(Smarket)
# This dataset consists of percentage returns for the S&P 500 stock index over 1,250 days from the begining of year 2001 to the end of year 2005.
# For each date, the percentage of returns for ... | 5,357 | mit |
454d821c1fe52d6c83ecba70477db4333fec73b2 | wStockhausen/rTCSAM2015 | R/plotFisheriesResults.R | #'
#'@title Plot model results for fisheries.
#'
#'@description Function to plot model results for fisheries.
#'
#'@param repObj - report list from a TCSAM2015 model run
#'@param showPlot - flag (T/F) to show plots
#'
#'@return nested list of ggplot objects
#'
#'@export
#'
plotFisheriesResults<-function(repObj,
... | 1,033 | mit |
280600a54c6f536c4fe82fe290b419f9c1c59077 | JoshuaZe/restopicer | restopicer-SCaaS/restopicerRESTful/R/allotHybridRecommender.R | allotHybridRecommend <- function(result_relevent,rated_papers,
topics_filepath,
preference_w,quality_w,summary_w,fresh_w,explore_w,
composite_N){
result_relevent
}
| 265 | mit |
280600a54c6f536c4fe82fe290b419f9c1c59077 | RUCYuLiTeam/restopicer | restopicer-SCaaS/restopicerRESTful/R/allotHybridRecommender.R | allotHybridRecommend <- function(result_relevent,rated_papers,
topics_filepath,
preference_w,quality_w,summary_w,fresh_w,explore_w,
composite_N){
result_relevent
}
| 265 | mit |
487659c7cd21b61fd28f2f9b7a0874e662f14ca3 | tsherma4/CellBasedModel | 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 |
6ff6870f9fa2e607548adf12ffe8203d6046e260 | JovingeLabSoftware/QFlow | server.R |
# This is the server logic for a Shiny web application.
# You can find out more about building applications with Shiny here:
#
# http://www.rstudio.com/shiny/
#
library(shiny)
library(flowCore)
library(flowViz)
library(hexbin)
shinyServer(function(input, output, session) {
data <- NULL
historical <- reactiveF... | 6,262 | mit |
487659c7cd21b61fd28f2f9b7a0874e662f14ca3 | FertigLab/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 |
e42df1e75b807d5e51c093ae0e58ea71583a275f | feralindia/CEPF_monitoring | LANDSAT7/fillnodata.R | ## routine to call gdal_fillnodata.py on targeted folders.
## Use after toar has been done using GRASS
## Pixel width is set to 9 - see the cmd statement.
### see if this function can be made to work. Will probably speed up the gap fill
## fun.gapfill <- function(w,x,y,z,gf){
## gunzip(z, destname=x, skip=TRUE, re... | 3,524 | gpl-3.0 |
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