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values | repo_name large_stringlengths 5 125 | language large_stringclasses 1
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classes | is_generated bool 2
classes | length_bytes int64 4 6.46M | extension large_stringclasses 75
values | text stringlengths 0 6.46M |
|---|---|---|---|---|---|---|---|---|---|
#' Sales Taxes Project
#' This code estimates the demand using the proposed method. First, we
#' run a Basic DiD model by initial price level and estimate the "long run" models
#' splitting the sample by quantiles increasing the number of groups.
#' Here initial level means previous period and we divide by groups wit... | /R/regressions/Semester_regressions/Demand_semester_initprice_quantiles_COUNTY.R | no_license | lancelothdf/sales.taxes | R | false | false | 7,644 | r | #' Sales Taxes Project
#' This code estimates the demand using the proposed method. First, we
#' run a Basic DiD model by initial price level and estimate the "long run" models
#' splitting the sample by quantiles increasing the number of groups.
#' Here initial level means previous period and we divide by groups wit... |
#' @title Get data of NTB experiments in customized format
#'
#' @author Paul Volkmann
#'
#' @name getexpdata
#'
#' @description A function that imports an NTB dataset and prepares the data for plotting and analysis as
#' dataframe or matrix.
#' For right formatting of your files, please consider the "ReadMe for ntbgr... | /R/getexpdata.R | no_license | volkmannp/ntbgraphics | R | false | false | 21,279 | r | #' @title Get data of NTB experiments in customized format
#'
#' @author Paul Volkmann
#'
#' @name getexpdata
#'
#' @description A function that imports an NTB dataset and prepares the data for plotting and analysis as
#' dataframe or matrix.
#' For right formatting of your files, please consider the "ReadMe for ntbgr... |
`%||%` <- function(a, b) if (is.null(a)) b else a
is_named <- function(x) {
all(has_names(x))
}
has_names <- function(x) {
nms <- names(x)
if (is.null(nms)) {
rep(FALSE, length(x))
} else {
!(is.na(nms) | nms == "")
}
}
# non smart quote version of sQuote
quote_str <- function(x, quote = "\"") {
... | /R/utils.R | no_license | gothub/xml2 | R | false | false | 610 | r | `%||%` <- function(a, b) if (is.null(a)) b else a
is_named <- function(x) {
all(has_names(x))
}
has_names <- function(x) {
nms <- names(x)
if (is.null(nms)) {
rep(FALSE, length(x))
} else {
!(is.na(nms) | nms == "")
}
}
# non smart quote version of sQuote
quote_str <- function(x, quote = "\"") {
... |
library(tidyverse)
library(lubridate)
source("./R/import/import_Fitbit_HR.R")
source("./R/import/import_gpx_HR.R")
glimpse(polar_hr)
glimpse(fitbit_hr)
# ajusting the "timezone" and merging both devices
polar_hr %>%
mutate(datetime = datetime - hours(2)) %>%
inner_join(fitbit_hr, by = "datetime") -> hr_data
g... | /R/analysis/analysis_polar_x_fitbit.R | no_license | GiulSposito/fitbit_api | R | false | false | 3,682 | r | library(tidyverse)
library(lubridate)
source("./R/import/import_Fitbit_HR.R")
source("./R/import/import_gpx_HR.R")
glimpse(polar_hr)
glimpse(fitbit_hr)
# ajusting the "timezone" and merging both devices
polar_hr %>%
mutate(datetime = datetime - hours(2)) %>%
inner_join(fitbit_hr, by = "datetime") -> hr_data
g... |
#' Copyright(c) 2017-2020 R. Mark Sharp
#' This file is part of nprcgenekeepr
context("convertRelationships")
library(testthat)
ped <- nprcgenekeepr::smallPed
kmat <- kinship(ped$id, ped$sire, ped$dam, ped$gen, sparse = FALSE)
ids <- c("A", "B", "D", "E", "F", "G", "I", "J", "L", "M", "O", "P")
relIds <- convertRelatio... | /tests/testthat/test_convertRelationships.R | permissive | jhagberg/nprcgenekeepr | R | false | false | 2,074 | r | #' Copyright(c) 2017-2020 R. Mark Sharp
#' This file is part of nprcgenekeepr
context("convertRelationships")
library(testthat)
ped <- nprcgenekeepr::smallPed
kmat <- kinship(ped$id, ped$sire, ped$dam, ped$gen, sparse = FALSE)
ids <- c("A", "B", "D", "E", "F", "G", "I", "J", "L", "M", "O", "P")
relIds <- convertRelatio... |
#
# This is the user-interface definition of a Shiny web application. You can
# run the application by clicking 'Run App' above.
#
# Find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com/
#
library(shiny)
# Define UI for application that draws a histogram
ui <- shinyUI(fluidPage(
... | /routetest/app.R | no_license | jhollist/cloud_gov_shiny | R | false | false | 1,314 | r | #
# This is the user-interface definition of a Shiny web application. You can
# run the application by clicking 'Run App' above.
#
# Find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com/
#
library(shiny)
# Define UI for application that draws a histogram
ui <- shinyUI(fluidPage(
... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/RcppExports.R
\name{FindTpsIp}
\alias{FindTpsIp}
\title{Gets IP address of TPS2.}
\usage{
FindTpsIp(TpsSerial, timeout)
}
\arguments{
\item{TpsSerial}{Serial number of TPS2.}
\item{timeout}{Timeout in ms to wait for the UDP packet.}
}
\value... | /man/FindTpsIp.Rd | no_license | pasturm/TofDaqR | R | false | true | 677 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/RcppExports.R
\name{FindTpsIp}
\alias{FindTpsIp}
\title{Gets IP address of TPS2.}
\usage{
FindTpsIp(TpsSerial, timeout)
}
\arguments{
\item{TpsSerial}{Serial number of TPS2.}
\item{timeout}{Timeout in ms to wait for the UDP packet.}
}
\value... |
## Monte Carlo calculation of posterior probability ##
s <- as.numeric(commandArgs(trailingOnly=TRUE))
ntasks <- 21
pdff <- function(filename){pdf(file=paste0(filename,'.pdf'),paper='a4r',height=11.7,width=16.5)}
#library('ggplot2')
library('RColorBrewer')
#library('cowplot')
#library('png')
#library('plot3D')
librar... | /codev3/posteriors.R | no_license | pglpm/nanunana | R | false | false | 3,517 | r | ## Monte Carlo calculation of posterior probability ##
s <- as.numeric(commandArgs(trailingOnly=TRUE))
ntasks <- 21
pdff <- function(filename){pdf(file=paste0(filename,'.pdf'),paper='a4r',height=11.7,width=16.5)}
#library('ggplot2')
library('RColorBrewer')
#library('cowplot')
#library('png')
#library('plot3D')
librar... |
#This code is revised from Zhenyu Zhang's code here:http://github.com/ZhenyuZ/eqtl/blob/master/cnv/GetGeneLevelCNA.r
options(stringsAsFactors=F)
library("GenomicRanges")
library(DESeq)
library(optparse)
option_list <- list(
make_option("--locfile", type="character", help="path to locations file"),
make_option... | /cnv.aggr.R | no_license | stutiagrawal/nbl | R | false | false | 3,140 | r | #This code is revised from Zhenyu Zhang's code here:http://github.com/ZhenyuZ/eqtl/blob/master/cnv/GetGeneLevelCNA.r
options(stringsAsFactors=F)
library("GenomicRanges")
library(DESeq)
library(optparse)
option_list <- list(
make_option("--locfile", type="character", help="path to locations file"),
make_option... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/nn-utils-clip-grad.R
\name{nn_utils_clip_grad_value_}
\alias{nn_utils_clip_grad_value_}
\title{Clips gradient of an iterable of parameters at specified value.}
\usage{
nn_utils_clip_grad_value_(parameters, clip_value)
}
\arguments{
\item{para... | /man/nn_utils_clip_grad_value_.Rd | permissive | mlverse/torch | R | false | true | 674 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/nn-utils-clip-grad.R
\name{nn_utils_clip_grad_value_}
\alias{nn_utils_clip_grad_value_}
\title{Clips gradient of an iterable of parameters at specified value.}
\usage{
nn_utils_clip_grad_value_(parameters, clip_value)
}
\arguments{
\item{para... |
# importing libraries
library(shiny)
library(tidyverse)
library(scales)
library(shinythemes)
library(ggrepel)
# importing data
scatter_data <- read_csv("Data Wrangling/school-enrollment-and-water-access.csv")
# defining choice values and labels for user inputs
country_choices <- unique(scatter_data$country)
# for s... | /Jamie_Shiny2.R | no_license | stat231-s21/Blog-JAMS | R | false | false | 2,573 | r | # importing libraries
library(shiny)
library(tidyverse)
library(scales)
library(shinythemes)
library(ggrepel)
# importing data
scatter_data <- read_csv("Data Wrangling/school-enrollment-and-water-access.csv")
# defining choice values and labels for user inputs
country_choices <- unique(scatter_data$country)
# for s... |
% Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/2_SimpleModels.R
\name{M_M_1}
\alias{M_M_1}
\title{Obtains the main characteristics of a M/M/1 queueing model}
\usage{
M_M_1(lambda = 3, mu = 6)
}
\arguments{
\item{lambda}{Mean arrival rate}
\item{mu}{Mean service rate}
}
\value{
Re... | /man/M_M_1.Rd | no_license | vishkey/arqas | R | false | false | 1,678 | rd | % Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/2_SimpleModels.R
\name{M_M_1}
\alias{M_M_1}
\title{Obtains the main characteristics of a M/M/1 queueing model}
\usage{
M_M_1(lambda = 3, mu = 6)
}
\arguments{
\item{lambda}{Mean arrival rate}
\item{mu}{Mean service rate}
}
\value{
Re... |
#SEM practicing
library(lavaan)
library(semPlot)
library(tidyverse)
#path Analysis
n<-3094
sd<-c(.71,.75,.90,.69,1.84,1.37)
lowercorr<-c(1.00,
.28,1.00,
.19,.21,1.00,
.15,.15,.23,1.00,
.35,.09,.20,.20,1.00,
.08,.11,.09,.11,.23,1.00)
fullcorr<-lav_matrix_lower2full(lowercorr)
covmat<-cor2cov(R = fullcorr,sds = s... | /SEM.R | no_license | VetMomen/Statistical-practice | R | false | false | 8,463 | r | #SEM practicing
library(lavaan)
library(semPlot)
library(tidyverse)
#path Analysis
n<-3094
sd<-c(.71,.75,.90,.69,1.84,1.37)
lowercorr<-c(1.00,
.28,1.00,
.19,.21,1.00,
.15,.15,.23,1.00,
.35,.09,.20,.20,1.00,
.08,.11,.09,.11,.23,1.00)
fullcorr<-lav_matrix_lower2full(lowercorr)
covmat<-cor2cov(R = fullcorr,sds = s... |
# test <- wilcox.test(statsAov$Median~statsAov$PRESa, exact=T, estimate=T)
## Kruskal Wallis tests for differences between groups
## helper function
require(xtable)
require(dplyr)
require(pgirmess)
rdec <- function(x, k){format(round(x), nsmall=k)}
#
# load("./output/statsAov_medianCI.Rda")
# load("./output/simConc... | /Analysis/scripts/08_statAnalysis_MannW_presence.R | no_license | the-Hull/Diss | R | false | false | 4,397 | r | # test <- wilcox.test(statsAov$Median~statsAov$PRESa, exact=T, estimate=T)
## Kruskal Wallis tests for differences between groups
## helper function
require(xtable)
require(dplyr)
require(pgirmess)
rdec <- function(x, k){format(round(x), nsmall=k)}
#
# load("./output/statsAov_medianCI.Rda")
# load("./output/simConc... |
# should be parsed as dependencies (use only lower-case letters for package names)
library(a)
library("b")
base::library(c)
base::library("d", character.only = TRUE)
requireNamespace("e")
base::requireNamespace("f", quietly = TRUE)
xfun::pkg_attach(c("g", "h"))
pkg_attach2("i", "j")
k::foo()
l:::bar()
"m"::baz()
# sh... | /tests/testthat/resources/code.R | permissive | rstudio/renv | R | false | false | 435 | r |
# should be parsed as dependencies (use only lower-case letters for package names)
library(a)
library("b")
base::library(c)
base::library("d", character.only = TRUE)
requireNamespace("e")
base::requireNamespace("f", quietly = TRUE)
xfun::pkg_attach(c("g", "h"))
pkg_attach2("i", "j")
k::foo()
l:::bar()
"m"::baz()
# sh... |
library(glmnet)
mydata = read.table("./TrainingSet/Correlation/urinary_tract.csv",head=T,sep=",")
x = as.matrix(mydata[,4:ncol(mydata)])
y = as.matrix(mydata[,1])
set.seed(123)
glm = cv.glmnet(x,y,nfolds=10,type.measure="mae",alpha=0.75,family="gaussian",standardize=TRUE)
sink('./Model/EN/Correlation/urinary_tract/urin... | /Model/EN/Correlation/urinary_tract/urinary_tract_079.R | no_license | leon1003/QSMART | R | false | false | 381 | r | library(glmnet)
mydata = read.table("./TrainingSet/Correlation/urinary_tract.csv",head=T,sep=",")
x = as.matrix(mydata[,4:ncol(mydata)])
y = as.matrix(mydata[,1])
set.seed(123)
glm = cv.glmnet(x,y,nfolds=10,type.measure="mae",alpha=0.75,family="gaussian",standardize=TRUE)
sink('./Model/EN/Correlation/urinary_tract/urin... |
loadDigestDataFromXL_Severity <- function(xlsPath, sheets, labelCol="B", positionCol="C", dataCol="D") {
# Loads digest data from Excel.
#
# The data for fire severity samples are in separate worksheets.
# Unlike the similar fire frequency data files, the sheet names do not
# always match sample label, so in... | /scripts/loadDigestDataFromXL_Severity.R | no_license | mbedward/robert_fire_sev | R | false | false | 2,770 | r | loadDigestDataFromXL_Severity <- function(xlsPath, sheets, labelCol="B", positionCol="C", dataCol="D") {
# Loads digest data from Excel.
#
# The data for fire severity samples are in separate worksheets.
# Unlike the similar fire frequency data files, the sheet names do not
# always match sample label, so in... |
% Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/rfVIP_master.R
\name{createRFmodel}
\alias{createRFmodel}
\title{createRFmodel}
\usage{
createRFmodel(train.x, train.y, m.try, nSeed = 3456, nCores = 1)
}
\arguments{
\item{train.x}{dataframe containing x values}
\item{train.y}{vecto... | /man/createRFmodel.Rd | no_license | kpadm/rfeVIP | R | false | false | 727 | rd | % Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/rfVIP_master.R
\name{createRFmodel}
\alias{createRFmodel}
\title{createRFmodel}
\usage{
createRFmodel(train.x, train.y, m.try, nSeed = 3456, nCores = 1)
}
\arguments{
\item{train.x}{dataframe containing x values}
\item{train.y}{vecto... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/cashflows.R
\name{shift_for_dividends}
\alias{shift_for_dividends}
\title{Shift a set of grid values for dividends paid, using spline interpolation}
\usage{
shift_for_dividends(grid_values_before_shift, stock_prices, div_sum)
}
\arguments{
\i... | /man/shift_for_dividends.Rd | no_license | freephys/ragtop | R | false | true | 833 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/cashflows.R
\name{shift_for_dividends}
\alias{shift_for_dividends}
\title{Shift a set of grid values for dividends paid, using spline interpolation}
\usage{
shift_for_dividends(grid_values_before_shift, stock_prices, div_sum)
}
\arguments{
\i... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/motifComparision.r
\name{locHist2}
\alias{locHist2}
\title{locHist}
\usage{
locHist2(t1, x, xlab = "Histogram", limits = c(-32, 32))
}
\description{
locHist
}
| /man/locHist2.Rd | permissive | alexjgriffith/CCCA | R | false | true | 238 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/motifComparision.r
\name{locHist2}
\alias{locHist2}
\title{locHist}
\usage{
locHist2(t1, x, xlab = "Histogram", limits = c(-32, 32))
}
\description{
locHist
}
|
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/loadCLSAData.R
\name{loadCLSAData}
\alias{loadCLSAData}
\title{Load CLSA Comprehensive and Tracking Datasets}
\usage{
loadCLSAData(path)
}
\arguments{
\item{path}{The path to the folder containging the comprehensive and
tracking .csv files}
}... | /man/loadCLSAData.Rd | permissive | gevamaimon/CLSAR | R | false | true | 983 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/loadCLSAData.R
\name{loadCLSAData}
\alias{loadCLSAData}
\title{Load CLSA Comprehensive and Tracking Datasets}
\usage{
loadCLSAData(path)
}
\arguments{
\item{path}{The path to the folder containging the comprehensive and
tracking .csv files}
}... |
% Generated by roxygen2 (4.0.1): do not edit by hand
\name{wmatrix}
\alias{wmatrix}
\title{Model variance-covariance matrix of the multinomial mixed models}
\usage{
wmatrix(M, pr)
}
\arguments{
\item{M}{vector with area sample sizes.}
\item{pr}{matrix with the estimated probabilities for the categories of th... | /man/wmatrix.Rd | no_license | cran/mme | R | false | false | 1,810 | rd | % Generated by roxygen2 (4.0.1): do not edit by hand
\name{wmatrix}
\alias{wmatrix}
\title{Model variance-covariance matrix of the multinomial mixed models}
\usage{
wmatrix(M, pr)
}
\arguments{
\item{M}{vector with area sample sizes.}
\item{pr}{matrix with the estimated probabilities for the categories of th... |
#
# Author: Joyce Woznica
# Class: IST 719
# Date: 3/16/2020
# Subject: Lab 10, Week 10
#
# Lab 10
#---------------- Package Load -------------------
library(shiny)
server <- function(input, output)
{
output$myPie <- renderPlot(
{
pie (c(8,12,3), main = "Hello World")
})
}
ui <- fluidPage(
mainPanel(p... | /Labs/Lab10/.Rproj.user/CA2B7130/sources/s-621F4385/D52BC42E-contents | no_license | jlwoznic/IST719 | R | false | false | 364 | #
# Author: Joyce Woznica
# Class: IST 719
# Date: 3/16/2020
# Subject: Lab 10, Week 10
#
# Lab 10
#---------------- Package Load -------------------
library(shiny)
server <- function(input, output)
{
output$myPie <- renderPlot(
{
pie (c(8,12,3), main = "Hello World")
})
}
ui <- fluidPage(
mainPanel(p... | |
options(stringsAsFactors=FALSE, width=400, max.print=10^6)
projpath <- getwd()
library(XML)
library(rjson)
library(rlist)
library(dynamicDensity)
xpath_mainData <- Sys.getenv("PATH_DZ_MAIN_DATA")
xpath_scrapedData <- file.path(xpath_mainData, "MLBjsons")
if(!dir.exists(xpath_scrapedData)) {
dir.create(xp... | /__06_week_01/__06b_go_MLB_02clean.R | no_license | davezes/MAS405_S2021 | R | false | false | 1,811 | r |
options(stringsAsFactors=FALSE, width=400, max.print=10^6)
projpath <- getwd()
library(XML)
library(rjson)
library(rlist)
library(dynamicDensity)
xpath_mainData <- Sys.getenv("PATH_DZ_MAIN_DATA")
xpath_scrapedData <- file.path(xpath_mainData, "MLBjsons")
if(!dir.exists(xpath_scrapedData)) {
dir.create(xp... |
#' airqualityES: Air quality measurements in Spain
#'
#' aiqualityES dataset contains daily quality air measurements from 2001 to 2018.
#'
#' @author Jose V. Die \email{jose.die@uco.es}, Jose R. Caro
#'
#' @docType package
#'
#' @name airqualityES
#'
"_PACKAGE"
| /R/airquaityES.R | no_license | rOpenSpain/airqualityES | R | false | false | 262 | r | #' airqualityES: Air quality measurements in Spain
#'
#' aiqualityES dataset contains daily quality air measurements from 2001 to 2018.
#'
#' @author Jose V. Die \email{jose.die@uco.es}, Jose R. Caro
#'
#' @docType package
#'
#' @name airqualityES
#'
"_PACKAGE"
|
slr.predict <-
function (y, x, newx=x, polydeg=1, interval,
conf.level=95, no.intercept=FALSE, ndigit=2)
{
if (!is.vector(y)) return("First Argument has to be Numeric Vector")
if(!is.vector(x)) return("Second Argument has to be Numeric Vector")
namResp <- deparse(substitute(y))
namPred <- ... | /R/slr.predict.R | no_license | WolfgangRolke/Resma3 | R | false | false | 1,655 | r | slr.predict <-
function (y, x, newx=x, polydeg=1, interval,
conf.level=95, no.intercept=FALSE, ndigit=2)
{
if (!is.vector(y)) return("First Argument has to be Numeric Vector")
if(!is.vector(x)) return("Second Argument has to be Numeric Vector")
namResp <- deparse(substitute(y))
namPred <- ... |
#' Trend analysis for single-cases data
#'
#' The `trend()` function provides an overview of linear trends in single case
#' data. By default, it provides the intercept and slope of a linear and
#' quadratic regression of measurement time on scores. Models are calculated
#' separately for each phase and across all phas... | /R/trend.R | no_license | cran/scan | R | false | false | 4,395 | r | #' Trend analysis for single-cases data
#'
#' The `trend()` function provides an overview of linear trends in single case
#' data. By default, it provides the intercept and slope of a linear and
#' quadratic regression of measurement time on scores. Models are calculated
#' separately for each phase and across all phas... |
###############################################################################
################## FIGURE 5: LEARNING TRIAL LOOKING IN EXP 1 ##################
###############################################################################
quartz(width=4,height=3,title = "Learning")
p <- ggplot(train.data.e1.notd, aes(... | /analysis/journal/dot_graphs.R | no_license | dyurovsky/ATT-WORD | R | false | false | 6,322 | r | ###############################################################################
################## FIGURE 5: LEARNING TRIAL LOOKING IN EXP 1 ##################
###############################################################################
quartz(width=4,height=3,title = "Learning")
p <- ggplot(train.data.e1.notd, aes(... |
library(archetypes)
library(lattice)
library(doParallel)
library(ggplot2)
library(dplyr)
registerDoParallel()
getDoParWorkers()
library(readr)
library(reshape2)
a<-"~/Archetypes/AfSIS"
#Read mir data
mir <- read_csv("~/Dropbox/AfSIS_reporting_data/Seperated_datasets/Calibration_Htsxt_MIR.csv")
#Read chem data
chem... | /afsis_spectral_archetype_analysis.R | no_license | asila/Soil_Archetypes | R | false | false | 4,135 | r | library(archetypes)
library(lattice)
library(doParallel)
library(ggplot2)
library(dplyr)
registerDoParallel()
getDoParWorkers()
library(readr)
library(reshape2)
a<-"~/Archetypes/AfSIS"
#Read mir data
mir <- read_csv("~/Dropbox/AfSIS_reporting_data/Seperated_datasets/Calibration_Htsxt_MIR.csv")
#Read chem data
chem... |
library(pheatmap)
library(DESeq2)
##assumes environment has res and countData loaded from short_read_deseq.R
genes <- rownames(resOrdered[1:30, ])
countData_filtered <- countData[match(genes, rownames(countData)),]
rownames(countData_filtered) <- (str_split_fixed(rownames(countData_filtered),'\\|',2)[, 2])
#view(cou... | /short_read_code/heatmap.R | no_license | qhauck16/Quinn-Summer-2020 | R | false | false | 622 | r | library(pheatmap)
library(DESeq2)
##assumes environment has res and countData loaded from short_read_deseq.R
genes <- rownames(resOrdered[1:30, ])
countData_filtered <- countData[match(genes, rownames(countData)),]
rownames(countData_filtered) <- (str_split_fixed(rownames(countData_filtered),'\\|',2)[, 2])
#view(cou... |
\name{trclcomp}
\alias{trclcomp}
\title{Tree-Clustering Comparison}
\description{
This function compares the within-group variation for groups formed by
tree partitioning and unconstrained clustering.
The results are plotted and returned invisibly.
}
\usage{
trclcomp(x, method = "com", km = TRUE, mrt = TRUE)
}
... | /man/trclcomp.Rd | no_license | mvignon/mvpart | R | false | false | 1,350 | rd | \name{trclcomp}
\alias{trclcomp}
\title{Tree-Clustering Comparison}
\description{
This function compares the within-group variation for groups formed by
tree partitioning and unconstrained clustering.
The results are plotted and returned invisibly.
}
\usage{
trclcomp(x, method = "com", km = TRUE, mrt = TRUE)
}
... |
#' Plot a fitted trajectory
#'
#' @param x an object returned from \code{\link{fit_trajectory}}
#' @param center should the trajectory be centered around the median WHO standard? This is equivalent to plotting the age difference score (like height-for-age difference - HAD)
#' @param x_range a vector specifying the ran... | /R/plot_trajectory.R | permissive | skhan890/hbgd | R | false | false | 12,513 | r | #' Plot a fitted trajectory
#'
#' @param x an object returned from \code{\link{fit_trajectory}}
#' @param center should the trajectory be centered around the median WHO standard? This is equivalent to plotting the age difference score (like height-for-age difference - HAD)
#' @param x_range a vector specifying the ran... |
library(tidyverse)
library(rtracklayer)
library(ggrastr)
library(patchwork)
library(furrr)
plan(multiprocess(workers = 10))
load('misc/cons_ko.rda')
tads <- import.bed('misc/tad.bed')
load('misc/g33.rda')
load('misc/deg.rda')
load('misc/dac.rda')
signif.num <- function(x) {
symnum(x, corr = FALSE, na = FALSE, lege... | /scripts/4d.R | no_license | yuzhenpeng/hnscc_nsd1 | R | false | false | 7,195 | r | library(tidyverse)
library(rtracklayer)
library(ggrastr)
library(patchwork)
library(furrr)
plan(multiprocess(workers = 10))
load('misc/cons_ko.rda')
tads <- import.bed('misc/tad.bed')
load('misc/g33.rda')
load('misc/deg.rda')
load('misc/dac.rda')
signif.num <- function(x) {
symnum(x, corr = FALSE, na = FALSE, lege... |
# Collapsed samples overlap
# Tahel Ronel, June 2021
# This script calculates the TCR overlap (using the 5-part Decombinator id, DCR) between any two samples produced using Collapsinator from Decombinator V4.
# The overlap is calculated as follows:
# Let A be the overlap matrix. Then for any two samples i,j,
# A_{... | /collapsed_sample_overlap/collapsed_sample_overlap.R | no_license | innate2adaptive/Decombinator-Tools | R | false | false | 6,856 | r |
# Collapsed samples overlap
# Tahel Ronel, June 2021
# This script calculates the TCR overlap (using the 5-part Decombinator id, DCR) between any two samples produced using Collapsinator from Decombinator V4.
# The overlap is calculated as follows:
# Let A be the overlap matrix. Then for any two samples i,j,
# A_{... |
################################################################################
##' @title Analyze log size - LODI
##'
##' @author Robin Elahi
##' @contact elahi.robin@gmail.com
##'
##' @date 2017-12-17
##'
##' @log
################################################################################
##### PACKAGES, DA... | /3_analyse_data/02_analyse_logsize_lodi.R | permissive | elahi/sbs_analysis | R | false | false | 5,753 | r | ################################################################################
##' @title Analyze log size - LODI
##'
##' @author Robin Elahi
##' @contact elahi.robin@gmail.com
##'
##' @date 2017-12-17
##'
##' @log
################################################################################
##### PACKAGES, DA... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/properties.R
\name{sol_set_property}
\alias{sol_set_property}
\alias{sol_get_property}
\title{Set or get the property name}
\usage{
sol_set_property(x, prop, with_units, ...)
sol_get_property(x)
}
\arguments{
\item{x}{vector: dat... | /man/sol_set_property.Rd | permissive | SCAR/solong | R | false | true | 1,001 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/properties.R
\name{sol_set_property}
\alias{sol_set_property}
\alias{sol_get_property}
\title{Set or get the property name}
\usage{
sol_set_property(x, prop, with_units, ...)
sol_get_property(x)
}
\arguments{
\item{x}{vector: dat... |
# This file implemented all the classifiers with feature selection
# This file will use the variables from the other 3 files to plot the graph
# Please run the other 3 files first
# Setup ----
rm(list=ls())
# !!CHANGE WORKING DIR TO MATCH YOUR CASE!!
setwd("/Users/shuqishang/Documents/courses/Statistical_Learning/proj... | /Ecoli/selective_all_methods.R | no_license | sshang0309/Statistical-Learning-in-Biology-Information-Systems | R | false | false | 5,955 | r | # This file implemented all the classifiers with feature selection
# This file will use the variables from the other 3 files to plot the graph
# Please run the other 3 files first
# Setup ----
rm(list=ls())
# !!CHANGE WORKING DIR TO MATCH YOUR CASE!!
setwd("/Users/shuqishang/Documents/courses/Statistical_Learning/proj... |
\name{HMRF}
\alias{HMRF}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{Image Segmentation using Hidden Markov Random Field with EM Algorithm
%% ~~function to do ... ~~
}
\description{This function can be used to obtain the segmented image using HMRF-EM Algorithm.
}
%% ~~ A concise (1-5 lines)... | /man/HMRF.Rd | no_license | rwang14/implant | R | false | false | 4,133 | rd | \name{HMRF}
\alias{HMRF}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{Image Segmentation using Hidden Markov Random Field with EM Algorithm
%% ~~function to do ... ~~
}
\description{This function can be used to obtain the segmented image using HMRF-EM Algorithm.
}
%% ~~ A concise (1-5 lines)... |
# evaluate post.predictive checks
library(readr)
library(ggplot2)
library(tidyr)
library(dplyr)
source("R/martin.R")
# simulated based on posteriors
all_checks1 <- read_delim("output/model_evaluation/check5_postpred/sims_10000kbot500_post_pred_checks2.txt", delim = " ")
all_checks2 <- read_delim("output/model_evaluati... | /R/posterior_predictive_checks.R | no_license | mastoffel/pinniped_bottlenecks | R | false | false | 2,388 | r | # evaluate post.predictive checks
library(readr)
library(ggplot2)
library(tidyr)
library(dplyr)
source("R/martin.R")
# simulated based on posteriors
all_checks1 <- read_delim("output/model_evaluation/check5_postpred/sims_10000kbot500_post_pred_checks2.txt", delim = " ")
all_checks2 <- read_delim("output/model_evaluati... |
# Title : TODO
# Objective : TODO
# Created by: yz
# Created on: 2018/9/19
library(tidyverse)
getSub <- function(data, filterPeak, response) {
subData = subset(data, SEC >= filterPeak$rtmin & SEC <= filterPeak$rtmax)
if (response == "height") {
index <- order(abs(subData$SEC - filterPeak$rt))[1]
subDa... | /server/rScripts/findPeak.R | no_license | yz8169/product_tmbq | R | false | false | 11,502 | r | # Title : TODO
# Objective : TODO
# Created by: yz
# Created on: 2018/9/19
library(tidyverse)
getSub <- function(data, filterPeak, response) {
subData = subset(data, SEC >= filterPeak$rtmin & SEC <= filterPeak$rtmax)
if (response == "height") {
index <- order(abs(subData$SEC - filterPeak$rt))[1]
subDa... |
library(mcp)
library(tidybayes)
library(changepoint)
library(dplyr)
library(tidyr)
library(lubridate)
library(readr)
library(hrbrthemes)
library(ggplot2)
library(stringr)
library(RcppRoll)
library(ragg)
plot_county <- function(the_state, the_county, counties=my_counties) {
state <- counties %>% filter(state == t... | /any-county.R | no_license | schnee/covid-19 | R | false | false | 5,073 | r | library(mcp)
library(tidybayes)
library(changepoint)
library(dplyr)
library(tidyr)
library(lubridate)
library(readr)
library(hrbrthemes)
library(ggplot2)
library(stringr)
library(RcppRoll)
library(ragg)
plot_county <- function(the_state, the_county, counties=my_counties) {
state <- counties %>% filter(state == t... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/app.R
\name{plot_clustering}
\alias{plot_clustering}
\title{Graphic representation of the evaluation measures.}
\usage{
plot_clustering(df, metric)
}
\arguments{
\item{df}{data matrix or data frame with the result of running the clustering
al... | /man/plot_clustering.Rd | no_license | minghao2016/Clustering-1 | R | false | true | 1,063 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/app.R
\name{plot_clustering}
\alias{plot_clustering}
\title{Graphic representation of the evaluation measures.}
\usage{
plot_clustering(df, metric)
}
\arguments{
\item{df}{data matrix or data frame with the result of running the clustering
al... |
#' @import chromote
#' @import later
#' @import promises
#'
NULL
#' Take a screenshot of a URL
#'
#' @param url A vector of URLs to visit. If multiple URLs are provided, it will
#' load and take screenshots of those web pages in parallel.
#' @param file A vector of names of output files. Should end with \code{.png}... | /R/webshot.R | no_license | LouisStAmour/webshot2 | R | false | false | 10,127 | r | #' @import chromote
#' @import later
#' @import promises
#'
NULL
#' Take a screenshot of a URL
#'
#' @param url A vector of URLs to visit. If multiple URLs are provided, it will
#' load and take screenshots of those web pages in parallel.
#' @param file A vector of names of output files. Should end with \code{.png}... |
# The script below estimates selection coefficients of L1 from the
# 1000 genome data using insertion estimates obtained by MELT
#
##########################################
# #
# Load packages #
# #
#############... | /Scripts/EstimateL1SelectionPars_MELT.R | no_license | hdohna/L1polymORFgit | R | false | false | 51,169 | r | # The script below estimates selection coefficients of L1 from the
# 1000 genome data using insertion estimates obtained by MELT
#
##########################################
# #
# Load packages #
# #
#############... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/CreateRandom.R
\name{CreateOneRandomMutSigProfile}
\alias{CreateOneRandomMutSigProfile}
\title{Create one "random" artificial signature profile.}
\usage{
CreateOneRandomMutSigProfile(row.names)
}
\arguments{
\item{row.names}{One of the \code{... | /man/CreateOneRandomMutSigProfile.Rd | no_license | steverozen/SynSigGen | R | false | true | 597 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/CreateRandom.R
\name{CreateOneRandomMutSigProfile}
\alias{CreateOneRandomMutSigProfile}
\title{Create one "random" artificial signature profile.}
\usage{
CreateOneRandomMutSigProfile(row.names)
}
\arguments{
\item{row.names}{One of the \code{... |
## Merging files
# Import Libraries
library(plyr)
library(tidyverse)
library(lubridate) # work with dates
mydir = "Stack_2" # Change this to direct to your data directory
# List files
A_K2 = list.files(path = mydir, pattern = "*A_K2.csv", full.names = TRUE)
B_K2 = list.files(path = mydir, pattern = "*B_K2.csv", ... | /data-combining.R | no_license | nshyam97/Group-Project-CSC8633 | R | false | false | 1,869 | r | ## Merging files
# Import Libraries
library(plyr)
library(tidyverse)
library(lubridate) # work with dates
mydir = "Stack_2" # Change this to direct to your data directory
# List files
A_K2 = list.files(path = mydir, pattern = "*A_K2.csv", full.names = TRUE)
B_K2 = list.files(path = mydir, pattern = "*B_K2.csv", ... |
plot3 <- function() {
# step 1--Reading data
hpcdata <- read.csv("./data/household_power_consumption.txt",TRUE,sep=";",na.strings="?",as.is = c(2) )
# step 2 - Subsetting 01-02/02/2007 dates
hpcdatafilt <- hpcdata[hpcdata$Date %in% c("1/2/2007","2/2/2007"),]
# adding datetime column
hpcdatafilt$datetime <-... | /plot3.R | no_license | paolobudroni/ExData_Plotting1 | R | false | false | 1,081 | r | plot3 <- function() {
# step 1--Reading data
hpcdata <- read.csv("./data/household_power_consumption.txt",TRUE,sep=";",na.strings="?",as.is = c(2) )
# step 2 - Subsetting 01-02/02/2007 dates
hpcdatafilt <- hpcdata[hpcdata$Date %in% c("1/2/2007","2/2/2007"),]
# adding datetime column
hpcdatafilt$datetime <-... |
testlist <- list(A = structure(c(2.31584307392677e+77, 9.53818251789663e+295, 1.22810536108214e+146, 4.12396251261199e-221, 0), .Dim = c(5L, 1L)), B = structure(0, .Dim = c(1L, 1L)))
result <- do.call(multivariance:::match_rows,testlist)
str(result) | /multivariance/inst/testfiles/match_rows/AFL_match_rows/match_rows_valgrind_files/1613112922-test.R | no_license | akhikolla/updatedatatype-list3 | R | false | false | 251 | r | testlist <- list(A = structure(c(2.31584307392677e+77, 9.53818251789663e+295, 1.22810536108214e+146, 4.12396251261199e-221, 0), .Dim = c(5L, 1L)), B = structure(0, .Dim = c(1L, 1L)))
result <- do.call(multivariance:::match_rows,testlist)
str(result) |
fitted.JMbayes <-
function (object, process = c("Longitudinal", "longitudinal", "Event", "event"),
type = c("Marginal", "marginal", "Subject", "subject"), nullY = FALSE, ...) {
if (!inherits(object, "JMbayes"))
stop("Use only with 'JMbayes' objects.\n")
process <- match.arg(... | /R/fitted.JMbayes.R | no_license | guptashilpa/JMbayes | R | false | false | 4,505 | r | fitted.JMbayes <-
function (object, process = c("Longitudinal", "longitudinal", "Event", "event"),
type = c("Marginal", "marginal", "Subject", "subject"), nullY = FALSE, ...) {
if (!inherits(object, "JMbayes"))
stop("Use only with 'JMbayes' objects.\n")
process <- match.arg(... |
#!/usr/bin/Rscript
library(rEDM)
library(zoo)
source( "helpers/helper.r" )
source( "helpers/mve.r" )
set.seed( 19 )
## filename = paste0("http://science.sciencemag.org/highwire/filestream/683325/",
## "field_highwire_adjunct_files/1/aag0863_SupportingFile_Suppl._Excel_seq1_v2.xlsx")
save_predictions... | /runnable.r | no_license | yairdaon/weight-pred | R | false | false | 5,202 | r | #!/usr/bin/Rscript
library(rEDM)
library(zoo)
source( "helpers/helper.r" )
source( "helpers/mve.r" )
set.seed( 19 )
## filename = paste0("http://science.sciencemag.org/highwire/filestream/683325/",
## "field_highwire_adjunct_files/1/aag0863_SupportingFile_Suppl._Excel_seq1_v2.xlsx")
save_predictions... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/unsupervised.R
\name{mcoa}
\alias{mcoa}
\title{Multiple Co-Inertia Analysis - MCOA}
\usage{
mcoa(X, ncomp = 2, scale = FALSE, verbose = FALSE, ...)
}
\arguments{
\item{X}{\code{list} of input blocks.}
\item{ncomp}{\code{integer} number of co... | /man/mcoa.Rd | no_license | minghao2016/multiblock | R | false | true | 2,026 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/unsupervised.R
\name{mcoa}
\alias{mcoa}
\title{Multiple Co-Inertia Analysis - MCOA}
\usage{
mcoa(X, ncomp = 2, scale = FALSE, verbose = FALSE, ...)
}
\arguments{
\item{X}{\code{list} of input blocks.}
\item{ncomp}{\code{integer} number of co... |
## Wynand van Staden
## Least-Squares Claibrtion method using the Peak prevalence data
## Copyright 2019
samSize <- 1000
# sir model returning infectious prevalences at 2 time points + the peak prevalence time point
sirModelPeakPrev <- function(gamma, beta = 0.2, N = 10000, inf = 0.1, sampleSize = samSize){
... | /Wynand Masters Thesis R code/1 Parameter with Peak Prev/1 One parameter Peak Prev with LS.R | no_license | Wynand93/Wynand_Masters_R_Code | R | false | false | 3,945 | r | ## Wynand van Staden
## Least-Squares Claibrtion method using the Peak prevalence data
## Copyright 2019
samSize <- 1000
# sir model returning infectious prevalences at 2 time points + the peak prevalence time point
sirModelPeakPrev <- function(gamma, beta = 0.2, N = 10000, inf = 0.1, sampleSize = samSize){
... |
require(dplyr)
data <- read.table("household_power_consumption.txt", sep = ";", dec =".", stringsAsFactors = F, header = T)
samp <- data %>% filter(Date %in% c("1/2/2007","2/2/2007"))
datetime <- strptime(paste(samp$Date,samp$Time,sep = " "), format = "%d/%m/%Y %H:%M:%S")
for (i in 3:8) {
samp[, i] <- as... | /plot3.R | no_license | kimlongngo/ExData_Plotting1 | R | false | false | 718 | r | require(dplyr)
data <- read.table("household_power_consumption.txt", sep = ";", dec =".", stringsAsFactors = F, header = T)
samp <- data %>% filter(Date %in% c("1/2/2007","2/2/2007"))
datetime <- strptime(paste(samp$Date,samp$Time,sep = " "), format = "%d/%m/%Y %H:%M:%S")
for (i in 3:8) {
samp[, i] <- as... |
install.packages(c("TTR", "forecast", "tseries"))
# call libraries
library(TTR)
library(forecast)
library(tseries)
# read data
wine <- read.csv("./dataset/timedata/AustralianWines.csv")
head(wine)
# 1980년 1월부터의 자료인 것을 확인할 수 있다.
#======================================================
# Problem 1. Fortified, Red, Rose... | /on_site_training/3. 고급 데이터 분석 - 정성규 교수님/Demo_Exercises/TimeSeries-exercise_sol.R | no_license | soykim-snail/Begas-BigDataTraining | R | false | false | 3,445 | r | install.packages(c("TTR", "forecast", "tseries"))
# call libraries
library(TTR)
library(forecast)
library(tseries)
# read data
wine <- read.csv("./dataset/timedata/AustralianWines.csv")
head(wine)
# 1980년 1월부터의 자료인 것을 확인할 수 있다.
#======================================================
# Problem 1. Fortified, Red, Rose... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/registry.R
\name{add_credential_function}
\alias{add_credential_function}
\title{Add a new credential fetching function.}
\usage{
add_credential_function(f)
}
\arguments{
\item{f}{A function with the right signature.}
}
\description{
Note tha... | /man/add_credential_function.Rd | permissive | sunivazquez/gauth | R | false | true | 499 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/registry.R
\name{add_credential_function}
\alias{add_credential_function}
\title{Add a new credential fetching function.}
\usage{
add_credential_function(f)
}
\arguments{
\item{f}{A function with the right signature.}
}
\description{
Note tha... |
library(rvest)
washington <- read_html("https://www.washingtonian.com/2016/05/05/best-cheap-restaurants-in-washington-dc/")
names <-
washington %>%
html_nodes(".styled-list a") %>%
html_text()
# build data frame
numberToLoad <- 100
restaurants <- data.frame(matrix(nrow = length(names[1:numberToLoad])))
restau... | /restaurants.R | no_license | danielgwilson/RestaurantDC | R | false | false | 4,700 | r | library(rvest)
washington <- read_html("https://www.washingtonian.com/2016/05/05/best-cheap-restaurants-in-washington-dc/")
names <-
washington %>%
html_nodes(".styled-list a") %>%
html_text()
# build data frame
numberToLoad <- 100
restaurants <- data.frame(matrix(nrow = length(names[1:numberToLoad])))
restau... |
###########################################################################/**
# @RdocFunction withCapture
# @alias evalCapture
#
# @title "Evaluates an expression and captures the code and/or the output"
#
# \description{
# @get "title".
# }
#
# @synopsis
#
# \arguments{
# \item{expr}{The R expression to be evaluat... | /R.utils/R/withCapture.R | no_license | ingted/R-Examples | R | false | false | 9,176 | r | ###########################################################################/**
# @RdocFunction withCapture
# @alias evalCapture
#
# @title "Evaluates an expression and captures the code and/or the output"
#
# \description{
# @get "title".
# }
#
# @synopsis
#
# \arguments{
# \item{expr}{The R expression to be evaluat... |
pairs(NOISE ~., filter)
# Plot data
par(mfrow = c(1,2))
boxplot(NOISE ~ size, df, xlab = "Gender", ylab = "Distance", col = c(2,3))
boxplot(Distance ~ Grade, df, xlab = "Grade", ylab = "Distance")
boxplot(Distance ~ Gender, df, xlab = "Gender", ylab = "Distance", col = c(2,3))
plot(as.numeric(df$Gender), df$Distance, ... | /Exercises_AppliedStatisticsCourse/fertilizer.R | no_license | rebekabato/DTU-archive | R | false | false | 536 | r | pairs(NOISE ~., filter)
# Plot data
par(mfrow = c(1,2))
boxplot(NOISE ~ size, df, xlab = "Gender", ylab = "Distance", col = c(2,3))
boxplot(Distance ~ Grade, df, xlab = "Grade", ylab = "Distance")
boxplot(Distance ~ Gender, df, xlab = "Gender", ylab = "Distance", col = c(2,3))
plot(as.numeric(df$Gender), df$Distance, ... |
\name{mUnits}
\alias{mUnits}
\title{Metric system}
\description{This function control metric units.}
\usage{mUnits(x, from = "mm", to = "mm")}
\arguments{
\item{x}{\code{numeric} vector.}
\item{from}{\code{character}. Initial metric unit.}
\item{to}{\code{character}. Final metric unit.}
}
\details{Chara... | /man/mUnits.Rd | no_license | cran/BIOdry | R | false | false | 1,012 | rd | \name{mUnits}
\alias{mUnits}
\title{Metric system}
\description{This function control metric units.}
\usage{mUnits(x, from = "mm", to = "mm")}
\arguments{
\item{x}{\code{numeric} vector.}
\item{from}{\code{character}. Initial metric unit.}
\item{to}{\code{character}. Final metric unit.}
}
\details{Chara... |
# Obtenemos el directorio de trabajo actual
currentWD <- getwd()
# Obtenemos el directorio del proyecto
dirProyect <- dirname(rstudioapi::getSourceEditorContext()$path)
# Verificamos si estamos en el mismo directorio del proyecto
if (dirProyect != currentWD)
{
setwd(dirProyect) # Ponemos el directorio del proyecto
... | /Sesion 2/postwork/postwork-s2.R | no_license | Deltarios/bedu-postwork-e2p1 | R | false | false | 2,603 | r | # Obtenemos el directorio de trabajo actual
currentWD <- getwd()
# Obtenemos el directorio del proyecto
dirProyect <- dirname(rstudioapi::getSourceEditorContext()$path)
# Verificamos si estamos en el mismo directorio del proyecto
if (dirProyect != currentWD)
{
setwd(dirProyect) # Ponemos el directorio del proyecto
... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/customvision_imgs.R
\name{browse_images}
\alias{browse_images}
\title{View images uploaded to a Custom Vision project}
\usage{
browse_images(project, img_ids, which = c("resized", "original",
"thumbnail"), max_images = 20, iteration = NULL)... | /man/browse_images.Rd | permissive | isabella232/AzureVision | R | false | true | 1,076 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/customvision_imgs.R
\name{browse_images}
\alias{browse_images}
\title{View images uploaded to a Custom Vision project}
\usage{
browse_images(project, img_ids, which = c("resized", "original",
"thumbnail"), max_images = 20, iteration = NULL)... |
vwc.data.50cm <- read.csv('C:/Users/smdevine/Desktop/rangeland project/soilmoisture/all.sites.50cmVWC.csv', stringsAsFactors = FALSE)
lapply(vwc.data.50cm, class)
time.cols <- grepl('time', colnames(vwc.data.50cm))
vwc.cols <- grepl('VWC', colnames(vwc.data.50cm))
vwc.data.50cm[,time.cols] <- lapply(vwc.data.50cm[,time... | /analysis_dissertation/50cm.VWC.allsites.R | no_license | smdevine/RangelandTheta | R | false | false | 2,122 | r | vwc.data.50cm <- read.csv('C:/Users/smdevine/Desktop/rangeland project/soilmoisture/all.sites.50cmVWC.csv', stringsAsFactors = FALSE)
lapply(vwc.data.50cm, class)
time.cols <- grepl('time', colnames(vwc.data.50cm))
vwc.cols <- grepl('VWC', colnames(vwc.data.50cm))
vwc.data.50cm[,time.cols] <- lapply(vwc.data.50cm[,time... |
fileUrl <- "https://data.baltimorecity.gov/api/views/dz54-2aru/rows.csv?accessType=DOWNLOAD"
if(!file.exists("data")){
dir.create("data")
}
download.file(fileUrl, destfile="./data/cameras.csv", method="curl")
dateDownloaded <- date()
save(dateDownloaded, file="./data/downloadDate.rda")
| /Workshop1/downloadData.R | no_license | lindsayrutter/SISBID | R | false | false | 290 | r | fileUrl <- "https://data.baltimorecity.gov/api/views/dz54-2aru/rows.csv?accessType=DOWNLOAD"
if(!file.exists("data")){
dir.create("data")
}
download.file(fileUrl, destfile="./data/cameras.csv", method="curl")
dateDownloaded <- date()
save(dateDownloaded, file="./data/downloadDate.rda")
|
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/processData.R
\name{correlationOmics}
\alias{correlationOmics}
\title{Correlation beetween omics data}
\usage{
correlationOmics(dataOmics1, dataOmics2)
}
\arguments{
\item{dataOmics1}{}
\item{dataOmics2}{}
}
\value{
}
\description{
Get corr... | /man/correlationOmics.Rd | no_license | miccec/CPTACBiolinks | R | false | true | 368 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/processData.R
\name{correlationOmics}
\alias{correlationOmics}
\title{Correlation beetween omics data}
\usage{
correlationOmics(dataOmics1, dataOmics2)
}
\arguments{
\item{dataOmics1}{}
\item{dataOmics2}{}
}
\value{
}
\description{
Get corr... |
marfissci.simple.map<-function(rds,
agg.by = "SPECIES_CODE",
colour.by = "SUM_RND_WEIGHT_KGS",
crs.out="+proj=utm +zone=20 +datum=WGS84",
xlim=c(-68,-53),
ylim=c(40... | /mpa/src/_Rfunctions/marfissci.simple.map.r | no_license | surfcao/ecomod | R | false | false | 9,209 | r | marfissci.simple.map<-function(rds,
agg.by = "SPECIES_CODE",
colour.by = "SUM_RND_WEIGHT_KGS",
crs.out="+proj=utm +zone=20 +datum=WGS84",
xlim=c(-68,-53),
ylim=c(40... |
# package umap
#
# UMAP stands for "Uniform Manifold Approximation and Projection"
# UMAP is a method proposed by Leland McInnes and John Healy.
#
# The original implementation was written in python by Leland McInnes.
# The original implementation is available at https://github.com/lmcinnes/umap
#
# This package is an ... | /R/umap.R | permissive | tkonopka/umap | R | false | false | 8,472 | r | # package umap
#
# UMAP stands for "Uniform Manifold Approximation and Projection"
# UMAP is a method proposed by Leland McInnes and John Healy.
#
# The original implementation was written in python by Leland McInnes.
# The original implementation is available at https://github.com/lmcinnes/umap
#
# This package is an ... |
#### download file ####
download.file("https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip", "project",method = "curl")
#### unzip foleder####
unzip("project")
#### view files in folders ####
list.files(".")
list.files("UCI HAR Dataset")
list.files("UCI HAR Dataset/test")
#### Read a... | /run_analysis.R | no_license | Rlopez3013/Tidy-Data | R | false | false | 3,512 | r | #### download file ####
download.file("https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip", "project",method = "curl")
#### unzip foleder####
unzip("project")
#### view files in folders ####
list.files(".")
list.files("UCI HAR Dataset")
list.files("UCI HAR Dataset/test")
#### Read a... |
# R_code_exam.r
# Copernicus data: https://land.copernicus.vgt.vito.be/PDF/portal/Application.html
# 1. 01_R_code_first.r
# 2. 02_R_code_spatial.r
# 3. 03_R_code_point_patterns.r
# 4. 04_R_code_TeleRil.r
# 5. 05_R_code_multitemp.r
# 6. 06_R_code_multitemp_NO2.r
# 7. 07_R_code_snow.r
# 8. 0... | /R_code_exam.r | no_license | GiovanniZanfei/Ecologia_del_Paesaggio | R | false | false | 43,455 | r | # R_code_exam.r
# Copernicus data: https://land.copernicus.vgt.vito.be/PDF/portal/Application.html
# 1. 01_R_code_first.r
# 2. 02_R_code_spatial.r
# 3. 03_R_code_point_patterns.r
# 4. 04_R_code_TeleRil.r
# 5. 05_R_code_multitemp.r
# 6. 06_R_code_multitemp_NO2.r
# 7. 07_R_code_snow.r
# 8. 0... |
testlist <- list(Beta = 0, CVLinf = 86341236051411296, FM = 1.53632495265886e-311, L50 = 0, L95 = 0, LenBins = c(2.0975686864138e+162, -2.68131210337361e-144, -1.11215735981244e+199, -4.48649879577108e+143, 1.6611802228813e+218, 900371.947279558, 1.07063092954708e+238, 2.88003257377011e-142, 1.29554... | /DLMtool/inst/testfiles/LBSPRgen/AFL_LBSPRgen/LBSPRgen_valgrind_files/1615833644-test.R | no_license | akhikolla/updatedatatype-list2 | R | false | false | 2,046 | r | testlist <- list(Beta = 0, CVLinf = 86341236051411296, FM = 1.53632495265886e-311, L50 = 0, L95 = 0, LenBins = c(2.0975686864138e+162, -2.68131210337361e-144, -1.11215735981244e+199, -4.48649879577108e+143, 1.6611802228813e+218, 900371.947279558, 1.07063092954708e+238, 2.88003257377011e-142, 1.29554... |
library(httr)
# Auth0 custom rule streams relevant user info to Keen.io after successful sign-in. Use a saved Keen.io query
# to retrieve the latest streamed event to identify the user within Shiny. It's lame having to use these third-party
# platforms, but as of now, unable to authenticate in open-source shiny-server ... | /global.R | no_license | Chrisss93/Diagnostics | R | false | false | 1,628 | r | library(httr)
# Auth0 custom rule streams relevant user info to Keen.io after successful sign-in. Use a saved Keen.io query
# to retrieve the latest streamed event to identify the user within Shiny. It's lame having to use these third-party
# platforms, but as of now, unable to authenticate in open-source shiny-server ... |
#' Create Related Numeric Columns
#'
#' Generate coumns that are related.
#'
#' @param x A starting column.
#' @param j The number of columns to produce.
#' @param name An optional prefix name to give to the columns. If \code{NULL}
#' attepts to take from the \code{varname} attribute of \code{x}. If not found,
#' "Va... | /R/relate.R | no_license | ds4ci/wakefield | R | false | false | 2,931 | r | #' Create Related Numeric Columns
#'
#' Generate coumns that are related.
#'
#' @param x A starting column.
#' @param j The number of columns to produce.
#' @param name An optional prefix name to give to the columns. If \code{NULL}
#' attepts to take from the \code{varname} attribute of \code{x}. If not found,
#' "Va... |
#' Power calculations.
#'
#' This function simply counts the proportion of people who selected the data plot,
#' in a set of lineups. It adjusts for multiple picks by the same individual, by weighting
#' by the total number of choices.
#' @param data summary of the results, containing columns id, pic_id, response, dete... | /R/power.r | no_license | sa-lee/nullabor | R | false | false | 781 | r | #' Power calculations.
#'
#' This function simply counts the proportion of people who selected the data plot,
#' in a set of lineups. It adjusts for multiple picks by the same individual, by weighting
#' by the total number of choices.
#' @param data summary of the results, containing columns id, pic_id, response, dete... |
# R script for Peak Model
# -- generated by MACS
p <- c(0.0414937466192,0.0489353039017,0.0560707211693,0.0635358276837,0.0698234726027,0.070247358777,0.0698705710665,0.0689521510222,0.0688815033264,0.0689286017903,0.0690934464136,0.0691405448774,0.0689757002541,0.0686460110074,0.0691169956455,0.0698941202984,0.070741... | /output/macs_peaks/arid2_model.r | permissive | ytakemon/raab_swisnf_2015 | R | false | false | 78,410 | r | # R script for Peak Model
# -- generated by MACS
p <- c(0.0414937466192,0.0489353039017,0.0560707211693,0.0635358276837,0.0698234726027,0.070247358777,0.0698705710665,0.0689521510222,0.0688815033264,0.0689286017903,0.0690934464136,0.0691405448774,0.0689757002541,0.0686460110074,0.0691169956455,0.0698941202984,0.070741... |
#19 febbraio 2018
#Unisci serie storiche con serie nuove scaricate da Centro Funzionale Calabria
rm(list=objects())
library("tidyverse")
library("stringr")
library("readr")
library("purrr")
options(error=recover,warn = 2)
ANNO<-as.integer(2017)
#Se il file delle nuove serie contiene i codici HisCentral OD (in anagraf... | /calabria_centro_funzionale/unisci_serieStoriche_nuoviDati.R | no_license | guidofioravanti/serie_giornaliere | R | false | false | 2,936 | r | #19 febbraio 2018
#Unisci serie storiche con serie nuove scaricate da Centro Funzionale Calabria
rm(list=objects())
library("tidyverse")
library("stringr")
library("readr")
library("purrr")
options(error=recover,warn = 2)
ANNO<-as.integer(2017)
#Se il file delle nuove serie contiene i codici HisCentral OD (in anagraf... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data.R
\docType{data}
\name{irish_county_data}
\alias{irish_county_data}
\title{Irish county data}
\format{
An object of class \code{sf} (inherits from \code{tbl_df}, \code{tbl}, \code{data.frame}) with 8008 rows and 10 columns.
}
\source{
\u... | /man/irish_county_data.Rd | permissive | hamilton-institute/hamiltonCovid19 | R | false | true | 469 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data.R
\docType{data}
\name{irish_county_data}
\alias{irish_county_data}
\title{Irish county data}
\format{
An object of class \code{sf} (inherits from \code{tbl_df}, \code{tbl}, \code{data.frame}) with 8008 rows and 10 columns.
}
\source{
\u... |
# Load amniote csv and master synonyms file
dat <- read.csv(file = "/Users/Anna/Google Drive/bird trait networks/inputs/data/r data/match data/preAves_Synonyms.csv")
synonyms <- read.csv(file = "/Users/Anna/Google Drive/bird trait networks/inputs/data/r data/match data/pre_synonyms.csv")
# clean amniote synonyms
dat ... | /R/add amniote synonyms.R | no_license | annakrystalli/bird_trait_networks | R | false | false | 710 | r |
# Load amniote csv and master synonyms file
dat <- read.csv(file = "/Users/Anna/Google Drive/bird trait networks/inputs/data/r data/match data/preAves_Synonyms.csv")
synonyms <- read.csv(file = "/Users/Anna/Google Drive/bird trait networks/inputs/data/r data/match data/pre_synonyms.csv")
# clean amniote synonyms
dat ... |
# This code is related to the extreme value theory (EVT)
# It builds a graph that shows the mean excess loss as a function of the threhold.
SP500 = read.csv("/Users/Larry/Documents/UIUC Schedule/FIN 580/HW/HW4.data.csv")
SP500$loss = -SP500$Return
loss <- SP500$loss[!is.na(SP500$loss)] # make sure "NA" is not output ... | /Mean_excess_function.R | no_license | Karagul/risk_management | R | false | false | 1,920 | r | # This code is related to the extreme value theory (EVT)
# It builds a graph that shows the mean excess loss as a function of the threhold.
SP500 = read.csv("/Users/Larry/Documents/UIUC Schedule/FIN 580/HW/HW4.data.csv")
SP500$loss = -SP500$Return
loss <- SP500$loss[!is.na(SP500$loss)] # make sure "NA" is not output ... |
zilele trecute , spre seara , am oprit in Piata Domenii din Bucuresti .
piramide de pepeni , prapad de legume si stive de lazi cu prune .
ziceai ca s - au rupt barajele toamnei si toate s - au pravalit in acel loc .
am cerut unui taran din Dimbovita doua kilograme de prune brumarii .
cu miinile sale latarete a umpl... | /data/Newspapers/2001.09.08.editorial.70827.0712.r | no_license | narcis96/decrypting-alpha | R | false | false | 3,330 | r | zilele trecute , spre seara , am oprit in Piata Domenii din Bucuresti .
piramide de pepeni , prapad de legume si stive de lazi cu prune .
ziceai ca s - au rupt barajele toamnei si toate s - au pravalit in acel loc .
am cerut unui taran din Dimbovita doua kilograme de prune brumarii .
cu miinile sale latarete a umpl... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/job_get.R
\name{job_get}
\alias{job_get}
\title{Get a single job}
\usage{
job_get(id, verbose = TRUE, ...)
}
\arguments{
\item{id}{A character string containing an ID for job.}
\item{verbose}{A logical indicating whether to print additional ... | /man/job_get.Rd | no_license | isabella232/crowdflower | R | false | true | 1,035 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/job_get.R
\name{job_get}
\alias{job_get}
\title{Get a single job}
\usage{
job_get(id, verbose = TRUE, ...)
}
\arguments{
\item{id}{A character string containing an ID for job.}
\item{verbose}{A logical indicating whether to print additional ... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/general_misc_utils.R
\name{getDataFromTextArea}
\alias{getDataFromTextArea}
\title{Transform two column text to data matrix}
\usage{
getDataFromTextArea(txtInput, sep.type = "space")
}
\arguments{
\item{txtInput}{Input text}
\item{sep.type}{... | /man/getDataFromTextArea.Rd | permissive | xia-lab/MetaboAnalystR | R | false | true | 576 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/general_misc_utils.R
\name{getDataFromTextArea}
\alias{getDataFromTextArea}
\title{Transform two column text to data matrix}
\usage{
getDataFromTextArea(txtInput, sep.type = "space")
}
\arguments{
\item{txtInput}{Input text}
\item{sep.type}{... |
# Functions for handling data from stateior, https://github.com/USEPA/stateior
#' Load two-region IO data of model iolevel and year from user's local directory
#' or the EPA Data Commons.
#' @description Load two-region IO data of model iolevel and year from user's
#' local directory or the EPA Data Commons.
#' @param... | /R/StateiorFunctions.R | permissive | USEPA/useeior | R | false | false | 2,291 | r | # Functions for handling data from stateior, https://github.com/USEPA/stateior
#' Load two-region IO data of model iolevel and year from user's local directory
#' or the EPA Data Commons.
#' @description Load two-region IO data of model iolevel and year from user's
#' local directory or the EPA Data Commons.
#' @param... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/homebrewanalytics-package.R
\docType{package}
\name{homebrewanalytics}
\alias{homebrewanalytics}
\alias{homebrewanalytics-package}
\title{homebrewanalytics}
\description{
The 'Homebrew Project' <brew.sh> has a myriad of "recipes" that
make li... | /man/homebrewanalytics.Rd | no_license | pombredanne/homebrewanalytics | R | false | true | 641 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/homebrewanalytics-package.R
\docType{package}
\name{homebrewanalytics}
\alias{homebrewanalytics}
\alias{homebrewanalytics-package}
\title{homebrewanalytics}
\description{
The 'Homebrew Project' <brew.sh> has a myriad of "recipes" that
make li... |
#' Old Radial Matrix Element.
#'
#' \code{radial_matrix_element} calculates the radial matrix element.
#'
#' This function calculates the radial matrix element for two arbitrary states
#' (n1, l1, j1) and (n2, l2, j2). A Numerov algorithm is used to compute the
#' radial matrix elements as done in Appendix A of Zimmerm... | /R/old_radial_matrix_element.R | no_license | bgrich/starkr | R | false | false | 7,326 | r | #' Old Radial Matrix Element.
#'
#' \code{radial_matrix_element} calculates the radial matrix element.
#'
#' This function calculates the radial matrix element for two arbitrary states
#' (n1, l1, j1) and (n2, l2, j2). A Numerov algorithm is used to compute the
#' radial matrix elements as done in Appendix A of Zimmerm... |
## 2018 APPLIED PUBLIC HEALTH STATISTICS BREAKFAST WORKSHOP ##
## R EXAMPLE 2: DESCRIPTIVES AND VISUALIZATION OF ILD ##
# SUMMER FRANK-PEARCE & TRENT L. LALONDE #
# R FILE FOR VISUALIZATION AND EXPLORATION OF ILD #
# CONTENTS: #
# ALL ANALYSES REPEATED FOR BOTH MJ AND SMK DATASETS #
#
# (1) DATA SUMMA... | /2 - ILDVisualization.R | no_license | lalondetl/APHSWorkshop | R | false | false | 8,563 | r | ## 2018 APPLIED PUBLIC HEALTH STATISTICS BREAKFAST WORKSHOP ##
## R EXAMPLE 2: DESCRIPTIVES AND VISUALIZATION OF ILD ##
# SUMMER FRANK-PEARCE & TRENT L. LALONDE #
# R FILE FOR VISUALIZATION AND EXPLORATION OF ILD #
# CONTENTS: #
# ALL ANALYSES REPEATED FOR BOTH MJ AND SMK DATASETS #
#
# (1) DATA SUMMA... |
library(tidyverse)
# https://stat.ethz.ch/R-manual/R-devel/library/datasets/html/00Index.html
# ability.cov
# airmiles
# AirPassengers
airquality %>%
dplyr::group_by(Month) %>%
dplyr::summarise_all(mean, na.rm = TRUE)
tidy_anscombe = anscombe %>%
tibble::rowid_to_column("id") %>%
tidyr::pivot_longer(!id,
... | /rstats/datasets.R | permissive | heavywatal/scribble | R | false | false | 9,479 | r | library(tidyverse)
# https://stat.ethz.ch/R-manual/R-devel/library/datasets/html/00Index.html
# ability.cov
# airmiles
# AirPassengers
airquality %>%
dplyr::group_by(Month) %>%
dplyr::summarise_all(mean, na.rm = TRUE)
tidy_anscombe = anscombe %>%
tibble::rowid_to_column("id") %>%
tidyr::pivot_longer(!id,
... |
createFreqTable = function() {
CountsUM = as.data.frame(xtabs(~ Area + Organisation.Type + Year + Classified + Description, data=UM))
SortedCounts = CountsUM[order(-CountsUM$Freq), ]
names(SortedCounts)[names(SortedCounts)=="Organisation.Type"] <- "Type"
names(SortedCounts)[names(SortedCounts)=="Classifi... | /R/createFreqTable.R | no_license | Anjs04/UM | R | false | false | 386 | r | createFreqTable = function() {
CountsUM = as.data.frame(xtabs(~ Area + Organisation.Type + Year + Classified + Description, data=UM))
SortedCounts = CountsUM[order(-CountsUM$Freq), ]
names(SortedCounts)[names(SortedCounts)=="Organisation.Type"] <- "Type"
names(SortedCounts)[names(SortedCounts)=="Classifi... |
################################################################################
# Accompanying code for the paper:
# Root traits influence storm-water performance in a green roof microcosm
#
# Authorship:
# Garland Xie (1)
# Jeremy Lundholm (2)
#
# Corresponding for this script:
# Garland Xie (1)
#
# Institu... | /src/02-03-LMM_tot_water_ret.R | no_license | garlandxie/MS_MSc_Roots | R | false | false | 4,708 | r | ################################################################################
# Accompanying code for the paper:
# Root traits influence storm-water performance in a green roof microcosm
#
# Authorship:
# Garland Xie (1)
# Jeremy Lundholm (2)
#
# Corresponding for this script:
# Garland Xie (1)
#
# Institu... |
t <- read.table("household_power_consumption.txt", header=TRUE, sep=";", na.strings = "?", colClasses = c('character','character','numeric','numeric','numeric','numeric','numeric','numeric','numeric'))
## Format date to Type Date
t$Date <- as.Date(t$Date, "%d/%m/%Y")
## Filter data set from Feb. 1, 2007 to Feb. 2, ... | /plot4.R | no_license | aryangupta07/ExData_Plotting1 | R | false | false | 1,514 | r | t <- read.table("household_power_consumption.txt", header=TRUE, sep=";", na.strings = "?", colClasses = c('character','character','numeric','numeric','numeric','numeric','numeric','numeric','numeric'))
## Format date to Type Date
t$Date <- as.Date(t$Date, "%d/%m/%Y")
## Filter data set from Feb. 1, 2007 to Feb. 2, ... |
library(data.table)
library(stringr)
library(data.table)
library(igraph)
library(RColorBrewer)
###############
# Set options #
###############
args=(commandArgs(TRUE))
print(args)
#########################
# Significant SNP-pairs #
#########################
Pvalue_SNPs=fread(paste(args[1], "/pvalues/sign_SNPpairs.tx... | /pipeline/network_visualization.R | permissive | DianeDuroux/BiologicalEpistasis | R | false | false | 3,546 | r | library(data.table)
library(stringr)
library(data.table)
library(igraph)
library(RColorBrewer)
###############
# Set options #
###############
args=(commandArgs(TRUE))
print(args)
#########################
# Significant SNP-pairs #
#########################
Pvalue_SNPs=fread(paste(args[1], "/pvalues/sign_SNPpairs.tx... |
## Put comments here that give an overall description of what your
## functions do
## There are two functions here.
## 1. The first function, makeCacheMatrix, creates a special kind of matrix(CacheMatrix). The one which can cache its own inverse (once computed (AND PROVIDED)). This kind of a matrix
## also contains h... | /cachematrix.R | no_license | gunapemmaraju/ProgrammingAssignment2 | R | false | false | 3,867 | r | ## Put comments here that give an overall description of what your
## functions do
## There are two functions here.
## 1. The first function, makeCacheMatrix, creates a special kind of matrix(CacheMatrix). The one which can cache its own inverse (once computed (AND PROVIDED)). This kind of a matrix
## also contains h... |
defineModule(sim, list(
name = "stateVars",
description = "keep track of stat transitions affecting multiple moduls; also classification",
keywords = c("insert key words here"),
authors = c(person(c("First", "Middle"), "Last", email="email@example.com", role=c("aut", "cre"))),
childModules = character(),
ve... | /stateVars/stateVars.R | no_license | SteveCumming/scfmModules | R | false | false | 5,476 | r | defineModule(sim, list(
name = "stateVars",
description = "keep track of stat transitions affecting multiple moduls; also classification",
keywords = c("insert key words here"),
authors = c(person(c("First", "Middle"), "Last", email="email@example.com", role=c("aut", "cre"))),
childModules = character(),
ve... |
Mixture=function(data,pre)
{
resultall=0
for(i in 1:length(pre$mean))
{
resultall=resultall+pre$pro[i]/sum(pre$pro)*stats::dnorm(data,mean=pre$mean[i],sd=pre$sd[i])
}
return(resultall)
}
| /R/Mixture.R | no_license | cran/BANFF | R | false | false | 201 | r | Mixture=function(data,pre)
{
resultall=0
for(i in 1:length(pre$mean))
{
resultall=resultall+pre$pro[i]/sum(pre$pro)*stats::dnorm(data,mean=pre$mean[i],sd=pre$sd[i])
}
return(resultall)
}
|
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/sql.R
\name{set_path}
\alias{set_path}
\alias{get_path}
\alias{append_path}
\alias{prepend_path}
\alias{path_contains}
\title{PostgreSQL path variable}
\usage{
set_path(..., default = FALSE)
get_path(default = FALSE)
append_path(..., defaul... | /man/path.Rd | no_license | keittlab/rpg | R | false | true | 625 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/sql.R
\name{set_path}
\alias{set_path}
\alias{get_path}
\alias{append_path}
\alias{prepend_path}
\alias{path_contains}
\title{PostgreSQL path variable}
\usage{
set_path(..., default = FALSE)
get_path(default = FALSE)
append_path(..., defaul... |
library(raster)
library(rgdal)
library(rgeos)
library(prettymapr)
library(rasterVis)
library(ggplot2)
library(cowplot)
library(grid)
rm(list=ls())
dev.off()
# Lectura de archivos ----
setwd('C:/Users/Usuario/Documents/Francisco/proyecto_agua/coberturas_FFMC')
pendiente <- raster('pendiente_marco_trabajo_Rio_Imperia... | /mapa_de_pendiente.R | no_license | fmanquehual/proyecto_agua_en_R | R | false | false | 4,793 | r | library(raster)
library(rgdal)
library(rgeos)
library(prettymapr)
library(rasterVis)
library(ggplot2)
library(cowplot)
library(grid)
rm(list=ls())
dev.off()
# Lectura de archivos ----
setwd('C:/Users/Usuario/Documents/Francisco/proyecto_agua/coberturas_FFMC')
pendiente <- raster('pendiente_marco_trabajo_Rio_Imperia... |
library(loggit)
### Name: setLogFile
### Title: Set Log File
### Aliases: setLogFile
### ** Examples
setLogFile(file.path(tempdir(), "loggit.json"))
| /data/genthat_extracted_code/loggit/examples/setLogFile.Rd.R | no_license | surayaaramli/typeRrh | R | false | false | 157 | r | library(loggit)
### Name: setLogFile
### Title: Set Log File
### Aliases: setLogFile
### ** Examples
setLogFile(file.path(tempdir(), "loggit.json"))
|
Part 1
#a)
load("nrw17.RDATA")
length(nrw17)
attributes(nrw17)
#b)
nrw17$inhalt[1]
#c)
ww = strsplit(nrw17$inhalt[1:10], " ")
ww = sapply(ww, function(w) w[!grepl("[^a-zA-Z]", w)])
sapply(ww, "[", 2)
#d)
ww2 = nrw17$inhalt[1:100]
ww2 = ww2[!nrw17$isretweet[1:100]]
ww2 = strsplit(ww2, " ")
ww2 = sapply(ww2, function(w)... | /HW2/2. Übungsblatt-20171107/2.r | no_license | valentyn1boreiko/R_class | R | false | false | 3,334 | r | Part 1
#a)
load("nrw17.RDATA")
length(nrw17)
attributes(nrw17)
#b)
nrw17$inhalt[1]
#c)
ww = strsplit(nrw17$inhalt[1:10], " ")
ww = sapply(ww, function(w) w[!grepl("[^a-zA-Z]", w)])
sapply(ww, "[", 2)
#d)
ww2 = nrw17$inhalt[1:100]
ww2 = ww2[!nrw17$isretweet[1:100]]
ww2 = strsplit(ww2, " ")
ww2 = sapply(ww2, function(w)... |
\name{mean}
\alias{cor}
\alias{cov}
\alias{favstats}
\alias{fivenum}
\alias{iqr}
\alias{IQR}
\alias{max}
\alias{mean}
\alias{median}
\alias{min}
\alias{prod}
\alias{range}
\alias{sd}
\alias{sum}
\alias{var}
\title{Aggregating functions}
\usage{
mean(x, ..., data, groups = NULL, ..fun.. = base::mean)
median(x, ...,... | /man/aggregating.Rd | no_license | datandrews/mosaic | R | false | false | 2,258 | rd | \name{mean}
\alias{cor}
\alias{cov}
\alias{favstats}
\alias{fivenum}
\alias{iqr}
\alias{IQR}
\alias{max}
\alias{mean}
\alias{median}
\alias{min}
\alias{prod}
\alias{range}
\alias{sd}
\alias{sum}
\alias{var}
\title{Aggregating functions}
\usage{
mean(x, ..., data, groups = NULL, ..fun.. = base::mean)
median(x, ...,... |
### bag-grid.R file ###
source("blind.R") # load the blind search methods
source("grid.R") # load the grid search methods
source("functions.R") # load the profit function
# grid search for all bag prices, step of 100$
PTM <- proc.time() # start clock
S1 <- gsearch(rep(100, 5), rep(1, 5), rep(1000, 5), profit, "max")
... | /src/chapters/Chapter3/bag-grid.R | permissive | wilsonify/ModernOptimization | R | false | false | 988 | r | ### bag-grid.R file ###
source("blind.R") # load the blind search methods
source("grid.R") # load the grid search methods
source("functions.R") # load the profit function
# grid search for all bag prices, step of 100$
PTM <- proc.time() # start clock
S1 <- gsearch(rep(100, 5), rep(1, 5), rep(1000, 5), profit, "max")
... |
# Normalise la liste des logiciels
standardise_logiciels <- function(liste){
a <- as.character(liste)
a[a == ""] <- NA
a[a == "autre"] <- NA
a[a == "Christalnet (module DMU)"] <- "Cristalnet"
a[a == "Clinicom (Siemens)"] <- "Clinicom"
a[a == "CORA McKesson"] <- "Cora"
a[a == "CrystalNet"] <- "Cristalnet"
a[a == "DMU (... | /functions.R | no_license | jcrb/InformatisationSU | R | false | false | 2,476 | r | # Normalise la liste des logiciels
standardise_logiciels <- function(liste){
a <- as.character(liste)
a[a == ""] <- NA
a[a == "autre"] <- NA
a[a == "Christalnet (module DMU)"] <- "Cristalnet"
a[a == "Clinicom (Siemens)"] <- "Clinicom"
a[a == "CORA McKesson"] <- "Cora"
a[a == "CrystalNet"] <- "Cristalnet"
a[a == "DMU (... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/class-cwl.R
\docType{class}
\name{WorkflowStepInput-class}
\alias{WorkflowStepInput-class}
\alias{WorkflowStepInput}
\alias{WorkflowStepOutput-class}
\alias{WorkflowStepOutput}
\alias{WorkflowStepInputList}
\alias{WorkflowStepInputList-class}... | /man/WorkflowStep.Rd | permissive | sbg/sevenbridges-r | R | false | true | 7,052 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/class-cwl.R
\docType{class}
\name{WorkflowStepInput-class}
\alias{WorkflowStepInput-class}
\alias{WorkflowStepInput}
\alias{WorkflowStepOutput-class}
\alias{WorkflowStepOutput}
\alias{WorkflowStepInputList}
\alias{WorkflowStepInputList-class}... |
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