content large_stringlengths 0 6.46M | path large_stringlengths 3 331 | license_type large_stringclasses 2
values | repo_name large_stringlengths 5 125 | language large_stringclasses 1
value | is_vendor bool 2
classes | is_generated bool 2
classes | length_bytes int64 4 6.46M | extension large_stringclasses 75
values | text stringlengths 0 6.46M |
|---|---|---|---|---|---|---|---|---|---|
# Please build your own test file from test-Template.R, and place it in tests folder
# please specify the package you need to run the sim function in the test files.
# to test all the test files in the tests folder:
test_dir("/Users/stevec/Dropbox/Courses/7043H16/Lab/scfmModules/scfmSpread/tests")
# Alternative, you... | /modules/scfmSpread/tests/unitTests.R | no_license | tati-micheletti/SpaDESinAction | R | false | false | 484 | r |
# Please build your own test file from test-Template.R, and place it in tests folder
# please specify the package you need to run the sim function in the test files.
# to test all the test files in the tests folder:
test_dir("/Users/stevec/Dropbox/Courses/7043H16/Lab/scfmModules/scfmSpread/tests")
# Alternative, you... |
\name{Run_permutation}
\alias{Run_permutation}
\title{Derive importance scores for M permuted data sets.}
\usage{
Run_permutation(X, W, ntree, mtry,genes.name,M)
}
\arguments{
\item{X}{\code{(n x p)} Matrix containing expression levels for \code{n} samples and \code{p} genes.}
\item{W}{\code{(p x p)} Matrix containing... | /man/Run_permutation.Rd | no_license | cran/iRafNet | R | false | false | 2,893 | rd | \name{Run_permutation}
\alias{Run_permutation}
\title{Derive importance scores for M permuted data sets.}
\usage{
Run_permutation(X, W, ntree, mtry,genes.name,M)
}
\arguments{
\item{X}{\code{(n x p)} Matrix containing expression levels for \code{n} samples and \code{p} genes.}
\item{W}{\code{(p x p)} Matrix containing... |
#' @title Delete a person
#' @description Function to Delete a person on pipedrive.
#' @param id ID of the person
#' @param api_token To validate your requests, you'll need your api_token - this means that our system will need to know who you are and be able to connect all actions you do with your chosen Pipedrive a... | /R/persons.delete.R | no_license | cran/Rpipedrive | R | false | false | 1,559 | r | #' @title Delete a person
#' @description Function to Delete a person on pipedrive.
#' @param id ID of the person
#' @param api_token To validate your requests, you'll need your api_token - this means that our system will need to know who you are and be able to connect all actions you do with your chosen Pipedrive a... |
#' get an envrionment variable `HEADLESS_CHROME`
#'
#' @md
#' @note This only return an envrionment variable `HEADLESS_CHROME`.
#' @export
#' @examples
#' get_env()
get_chrome_env <- function() {
Sys.getenv("HEADLESS_CHROME")
}
#' set an envrionment variable `HEADLESS_CHROME`
#'
#' @md
#' @note This only grabs the `... | /R/env.R | no_license | markwsac/decapitated | R | false | false | 628 | r | #' get an envrionment variable `HEADLESS_CHROME`
#'
#' @md
#' @note This only return an envrionment variable `HEADLESS_CHROME`.
#' @export
#' @examples
#' get_env()
get_chrome_env <- function() {
Sys.getenv("HEADLESS_CHROME")
}
#' set an envrionment variable `HEADLESS_CHROME`
#'
#' @md
#' @note This only grabs the `... |
# Figure S2: exclusivity surface plots for different initial connectivity and resource share type -------
## Load data on disproportionate share type: this scenario calculates individual payoffs in which the group-level resource share is determined by the size of the groups, considering that larger groups outcompete s... | /Figure_codes/FigureS2.R | no_license | sabrinatucci/Cantor-Farine-Repro-Project | R | false | false | 22,088 | r | # Figure S2: exclusivity surface plots for different initial connectivity and resource share type -------
## Load data on disproportionate share type: this scenario calculates individual payoffs in which the group-level resource share is determined by the size of the groups, considering that larger groups outcompete s... |
# Yige Wu @WashU Apr 2020
## running on local
## for plotting average expression of known pathogenic pathway genes for each tumor subclusters (manually grouped)
## VHL-HIF pathway
# set up libraries and output directory -----------------------------------
## set working directory
baseD = "~/Box/"
setwd(baseD)
source("... | /tumor_subcluster/plotting/heatmap/heatmap_tumor_manualsubcluster_mtorpathway.R | no_license | ding-lab/ccRCC_snRNA_analysis | R | false | false | 5,458 | r | # Yige Wu @WashU Apr 2020
## running on local
## for plotting average expression of known pathogenic pathway genes for each tumor subclusters (manually grouped)
## VHL-HIF pathway
# set up libraries and output directory -----------------------------------
## set working directory
baseD = "~/Box/"
setwd(baseD)
source("... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/PASWR-package.R
\docType{data}
\name{Formula1}
\alias{Formula1}
\title{Pit Stop Times}
\format{
A data frame with 10 observations on the following 3 variables:
\describe{
\item{Race}{number corresponding to a race site}
\item{Team1}{pit stop... | /man/Formula1.Rd | no_license | alanarnholt/PASWR | R | false | true | 685 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/PASWR-package.R
\docType{data}
\name{Formula1}
\alias{Formula1}
\title{Pit Stop Times}
\format{
A data frame with 10 observations on the following 3 variables:
\describe{
\item{Race}{number corresponding to a race site}
\item{Team1}{pit stop... |
#' @title Create input indicator(s)
#'
#' @description The function creates the input indicators from the inputs and
#' the outputs.
#' @param data_table A symmetric input-output table, a use table,
#' a margins or tax table retrieved by the \code{\link{iotable_get}}
#' function.
#' @param input_row The name... | /R/input_indicator_create.R | permissive | cran/iotables | R | false | false | 3,104 | r | #' @title Create input indicator(s)
#'
#' @description The function creates the input indicators from the inputs and
#' the outputs.
#' @param data_table A symmetric input-output table, a use table,
#' a margins or tax table retrieved by the \code{\link{iotable_get}}
#' function.
#' @param input_row The name... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/wiki_graph.R
\docType{data}
\name{wiki_data}
\alias{wiki_data}
\title{Dataset creation for wiki graph.}
\format{A data frame with 18 rows and 3 variables:
\describe{
\item{v1}{edge1 of graph}
\item{v2}{edge2 of grpah}
\item{w}{weight of... | /man/wiki_data.Rd | permissive | MuhammadFaizanKhalid/euclidspackage | R | false | true | 530 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/wiki_graph.R
\docType{data}
\name{wiki_data}
\alias{wiki_data}
\title{Dataset creation for wiki graph.}
\format{A data frame with 18 rows and 3 variables:
\describe{
\item{v1}{edge1 of graph}
\item{v2}{edge2 of grpah}
\item{w}{weight of... |
##--------------------------------##
## Small ODE example: EnvZ/OmpR ##
##--------------------------------##
rm(list = ls())
library(episode)
library(ggplot2); library(reshape)
library(igraph)
source("../ggplot_theme.R")
## Define system ##
x0 <- c('(EnvZ-P)OmpR' = 4,
'EnvZ(OmpR-P)' = 5,
'EnvZ-P'... | /SimStudies/SimF_EnvZOmpR/main.R | no_license | nielsrhansen/SLODE | R | false | false | 9,948 | r | ##--------------------------------##
## Small ODE example: EnvZ/OmpR ##
##--------------------------------##
rm(list = ls())
library(episode)
library(ggplot2); library(reshape)
library(igraph)
source("../ggplot_theme.R")
## Define system ##
x0 <- c('(EnvZ-P)OmpR' = 4,
'EnvZ(OmpR-P)' = 5,
'EnvZ-P'... |
AUTH_SCOPES = c('https://www.googleapis.com/auth/cloud-platform')
GCS_PATH_SEPARATOR = '/'
#' Access datasets from Google Cloud Storage
#'
#' Helper functions for loading datasets from Google Cloud Storage (GCS). In case of
#' tabular data, provides functions which can be used in concert with
#' \link[megautils]{impo... | /R/gcs.R | permissive | gmega/megautils | R | false | false | 2,699 | r | AUTH_SCOPES = c('https://www.googleapis.com/auth/cloud-platform')
GCS_PATH_SEPARATOR = '/'
#' Access datasets from Google Cloud Storage
#'
#' Helper functions for loading datasets from Google Cloud Storage (GCS). In case of
#' tabular data, provides functions which can be used in concert with
#' \link[megautils]{impo... |
options(servr.daemon = interactive(),
blogdown.YAML.empty = TRUE,
blogdown.author = 'Alexander C. Hungerford',
blogdown.ext = '.Rmd',
blogdown.subdir = 'post')
| /.Rprofile | permissive | achungerford/rsite | R | false | false | 176 | rprofile | options(servr.daemon = interactive(),
blogdown.YAML.empty = TRUE,
blogdown.author = 'Alexander C. Hungerford',
blogdown.ext = '.Rmd',
blogdown.subdir = 'post')
|
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/gdfpd_get_inflation_data.R
\name{gdfpd.get.inflation.data}
\alias{gdfpd.get.inflation.data}
\title{Downloads and read inflation data from github}
\usage{
gdfpd.get.inflation.data(inflation.index, do.cache)
}
\arguments{
\item{inflation.index}... | /man/gdfpd.get.inflation.data.Rd | no_license | msperlin/GetDFPData | R | false | true | 920 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/gdfpd_get_inflation_data.R
\name{gdfpd.get.inflation.data}
\alias{gdfpd.get.inflation.data}
\title{Downloads and read inflation data from github}
\usage{
gdfpd.get.inflation.data(inflation.index, do.cache)
}
\arguments{
\item{inflation.index}... |
c DCNF-Autarky [version 0.0.1].
c Copyright (c) 2018-2019 Swansea University.
c
c Input Clause Count: 2133
c Performing E1-Autarky iteration.
c Remaining clauses count after E-Reduction: 2133
c
c Input Parameter (command line, file):
c input filename QBFLIB/Jordan-Kaiser/reduction-finding-full-set-params-k1c3n4/e... | /code/dcnf-ankit-optimized/Results/QBFLIB-2018/E1/Experiments/Jordan-Kaiser/reduction-finding-full-set-params-k1c3n4/eequery_query64_1344n/eequery_query64_1344n.R | no_license | arey0pushpa/dcnf-autarky | R | false | false | 710 | r | c DCNF-Autarky [version 0.0.1].
c Copyright (c) 2018-2019 Swansea University.
c
c Input Clause Count: 2133
c Performing E1-Autarky iteration.
c Remaining clauses count after E-Reduction: 2133
c
c Input Parameter (command line, file):
c input filename QBFLIB/Jordan-Kaiser/reduction-finding-full-set-params-k1c3n4/e... |
library(tidyverse)
# ** calculate the mean, sd, cov and se **
data_15P_cal_HE_outlier_replaced <- read_csv("data/tidydata/data_15P_cal_HE_outlier_replaced.csv")
variation <- data_15P_cal_HE_outlier_replaced %>%
group_by(Sample, Time) %>%
summarise(Mean_HE = mean(HE, na.rm = TRUE... | /scripts/calculation/calculation_var_15P.R | no_license | Yuzi-00/starch-degradation | R | false | false | 1,186 | r |
library(tidyverse)
# ** calculate the mean, sd, cov and se **
data_15P_cal_HE_outlier_replaced <- read_csv("data/tidydata/data_15P_cal_HE_outlier_replaced.csv")
variation <- data_15P_cal_HE_outlier_replaced %>%
group_by(Sample, Time) %>%
summarise(Mean_HE = mean(HE, na.rm = TRUE... |
# Read in the data from the text file...
data <- read.table("household_power_consumption.txt", sep=";", na.strings="?", header=TRUE)
#Subset the data desired for Feb 1st and 2nd, 2007
feb <- data[(data$Date==c("1/2/2007")| data$Date==c("2/2/2007")),]
hist(feb$Global_active_power, col="red", xlab="Global Active Power... | /plot1.R | no_license | susanst/ExData_Plotting1 | R | false | false | 459 | r |
# Read in the data from the text file...
data <- read.table("household_power_consumption.txt", sep=";", na.strings="?", header=TRUE)
#Subset the data desired for Feb 1st and 2nd, 2007
feb <- data[(data$Date==c("1/2/2007")| data$Date==c("2/2/2007")),]
hist(feb$Global_active_power, col="red", xlab="Global Active Power... |
608f72c3c5f27301083afd596371276d trivial_query25_1344n.qdimacs 885 4022 | /code/dcnf-ankit-optimized/Results/QBFLIB-2018/E1/Database/Jordan-Kaiser/reduction-finding-full-set-params-k1c3n4/trivial_query25_1344n/trivial_query25_1344n.R | no_license | arey0pushpa/dcnf-autarky | R | false | false | 71 | r | 608f72c3c5f27301083afd596371276d trivial_query25_1344n.qdimacs 885 4022 |
plot4 <- function()
{
epc_table <- read.table("household_power_consumption.txt", sep=";", header=TRUE, stringsAsFactors = FALSE)
epc_table[,1] <- as.Date(epc_table[,1],format="%d/%m/%Y")
epc_table_subset <- with(epc_table, epc_table[(Date >= "2007-02-01" & Date <= "2007-02-02"), ])
epc_table_subset["datetime"] ... | /plot4.R | no_license | kazkibergetic/ExData_Plotting1 | R | false | false | 1,350 | r | plot4 <- function()
{
epc_table <- read.table("household_power_consumption.txt", sep=";", header=TRUE, stringsAsFactors = FALSE)
epc_table[,1] <- as.Date(epc_table[,1],format="%d/%m/%Y")
epc_table_subset <- with(epc_table, epc_table[(Date >= "2007-02-01" & Date <= "2007-02-02"), ])
epc_table_subset["datetime"] ... |
#Data has been download into working directory first
#Load the household data into R
household_data <- read.csv("household_power_consumption.txt", header =TRUE, sep = ";")
#subset of the data required for the graphs
graph_data <- subset(household_data, household_data$Date=="1/2/2007" | household_data$Date =="2/... | /Plot1.R | no_license | Nativim/ExData_Plotting1 | R | false | false | 781 | r |
#Data has been download into working directory first
#Load the household data into R
household_data <- read.csv("household_power_consumption.txt", header =TRUE, sep = ";")
#subset of the data required for the graphs
graph_data <- subset(household_data, household_data$Date=="1/2/2007" | household_data$Date =="2/... |
library(shiny)
phasefit<-function(CumulativeTime, Response){
CosTime<-cos(2*pi*CumulativeTime / 24) # Create two new predictor variables, CosTime and SinTime
SinTime<-sin(2*pi*CumulativeTime / 24)
lm1<-lm(Response ~ CosTime + SinTime)
summary(lm1) # Response can be modelled as a linear... | /server.R | no_license | gtatters/CosinorFit | R | false | false | 7,971 | r | library(shiny)
phasefit<-function(CumulativeTime, Response){
CosTime<-cos(2*pi*CumulativeTime / 24) # Create two new predictor variables, CosTime and SinTime
SinTime<-sin(2*pi*CumulativeTime / 24)
lm1<-lm(Response ~ CosTime + SinTime)
summary(lm1) # Response can be modelled as a linear... |
####################################################################################################
#' Function to order contigs within a single linkage group using a greedy algorithms
#' Attempt to order contigs within
#' @useDynLib contiBAIT
#' @import Rcpp TSP
#
#' @param linkageGroupReadTable dataframe of strand... | /R/orderContigsGreedy.R | permissive | oneillkza/ContiBAIT | R | false | false | 3,228 | r | ####################################################################################################
#' Function to order contigs within a single linkage group using a greedy algorithms
#' Attempt to order contigs within
#' @useDynLib contiBAIT
#' @import Rcpp TSP
#
#' @param linkageGroupReadTable dataframe of strand... |
library(readr)
library(data.table)
daten_moocall <- read_delim("Rohdaten/Rohdaten_10-Sep-2018_Faersen.csv",
";", escape_double = FALSE, trim_ws = TRUE)
print_tables <- function(confusion_table) {
table = epitools::epitable(c(sum(confusion_table$RP),sum(confusion_table$FP), su... | /alex/MooCall/Auswertung_Faersen.R | no_license | whllnd/studie | R | false | false | 7,622 | r | library(readr)
library(data.table)
daten_moocall <- read_delim("Rohdaten/Rohdaten_10-Sep-2018_Faersen.csv",
";", escape_double = FALSE, trim_ws = TRUE)
print_tables <- function(confusion_table) {
table = epitools::epitable(c(sum(confusion_table$RP),sum(confusion_table$FP), su... |
\name{ READ }
\alias{ READ }
\docType{data}
\title{ Rectum adenocarcinoma }
\description{
A document describing the TCGA cancer code
}
\details{
\preformatted{
> experiments( READ )
ExperimentList class object of length 14:
[1] READ_CNASeq-20160128: RaggedExperiment with 56380 rows and 70 columns
[2] READ_CNASNP-2... | /man/READ.Rd | no_license | shawnspei/curatedTCGAData | R | false | false | 5,654 | rd | \name{ READ }
\alias{ READ }
\docType{data}
\title{ Rectum adenocarcinoma }
\description{
A document describing the TCGA cancer code
}
\details{
\preformatted{
> experiments( READ )
ExperimentList class object of length 14:
[1] READ_CNASeq-20160128: RaggedExperiment with 56380 rows and 70 columns
[2] READ_CNASNP-2... |
# Function makeCacheMatrix and cacheSolve are used in combination.
# makeCacheMatrix creates a cache object for a matrix and its inverse matrix.
# Function cacheSolve takes a makeCacheMatrix object and computes the inverse of the cached matrix and store the result as a cache in the makeCacheMatrix object.
# If there is... | /cachematrix.R | no_license | eov/ProgrammingAssignment2 | R | false | false | 1,944 | r | # Function makeCacheMatrix and cacheSolve are used in combination.
# makeCacheMatrix creates a cache object for a matrix and its inverse matrix.
# Function cacheSolve takes a makeCacheMatrix object and computes the inverse of the cached matrix and store the result as a cache in the makeCacheMatrix object.
# If there is... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/model-feature-selection.R
\name{featsel_stepforward}
\alias{featsel_stepforward}
\title{Feature selection vis stepwise forward}
\usage{
featsel_stepforward(model, ...)
}
\arguments{
\item{model}{model}
\item{...}{Additional arguments for sta... | /man/featsel_stepforward.Rd | permissive | jbkunst/risk3r | R | false | true | 502 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/model-feature-selection.R
\name{featsel_stepforward}
\alias{featsel_stepforward}
\title{Feature selection vis stepwise forward}
\usage{
featsel_stepforward(model, ...)
}
\arguments{
\item{model}{model}
\item{...}{Additional arguments for sta... |
\name{CAAIlluminatedFraction_VenusMagnitudeAA}
\alias{CAAIlluminatedFraction_VenusMagnitudeAA}
\title{
CAAIlluminatedFraction_VenusMagnitudeAA
}
\description{
CAAIlluminatedFraction_VenusMagnitudeAA
}
\usage{
CAAIlluminatedFraction_VenusMagnitudeAA(r, Delta, i)
}
\arguments{
\item{r}{
r The planet's dist... | /man/CAAIlluminatedFraction_VenusMagnitudeAA.Rd | no_license | helixcn/skycalc | R | false | false | 843 | rd | \name{CAAIlluminatedFraction_VenusMagnitudeAA}
\alias{CAAIlluminatedFraction_VenusMagnitudeAA}
\title{
CAAIlluminatedFraction_VenusMagnitudeAA
}
\description{
CAAIlluminatedFraction_VenusMagnitudeAA
}
\usage{
CAAIlluminatedFraction_VenusMagnitudeAA(r, Delta, i)
}
\arguments{
\item{r}{
r The planet's dist... |
#' Custom save to .csv function
#'
#' This function saves data.tables or data.frames as .csv in the root working directory or a specified subfolder.
#' Additionally the current date is automatically included in the file name.
#'
#' @param file The data.table or data.frame to be saved.
#'
#' @param file_name Character s... | /R/save_csv_carl.R | no_license | cfbeuchel/CarlHelpR | R | false | false | 3,635 | r | #' Custom save to .csv function
#'
#' This function saves data.tables or data.frames as .csv in the root working directory or a specified subfolder.
#' Additionally the current date is automatically included in the file name.
#'
#' @param file The data.table or data.frame to be saved.
#'
#' @param file_name Character s... |
library(data.table)
library(jsonlite)
library(optparse)
# make an options parsing list
option_list = list(
make_option(c("-u", "--user"), type="character", default=NULL,
help="user_id", metavar="character")
);
opt_parser = OptionParser(option_list=option_list);
opt = parse_args(opt_parser);
# get the arguments that... | /Lectures/9.Script_writing/Scripting_2_wacky_boost.R | no_license | sharonsunpeng/PSU_Stat_184 | R | false | false | 2,403 | r | library(data.table)
library(jsonlite)
library(optparse)
# make an options parsing list
option_list = list(
make_option(c("-u", "--user"), type="character", default=NULL,
help="user_id", metavar="character")
);
opt_parser = OptionParser(option_list=option_list);
opt = parse_args(opt_parser);
# get the arguments that... |
output$pageStub <- renderUI(
fluidPage(useShinyjs(),theme = shinytheme('superhero'),
fluidRow( column( 7, offset = 1, h2("WHO IS MOST LIKELY TO LIVE? ")
)
),
fluidRow ( id = "greyBox", align = "center",imageOutput("grey", click = "grey_click")
... | /GameofThrones/predictions.R | no_license | zembrodta/GOT | R | false | false | 2,715 | r | output$pageStub <- renderUI(
fluidPage(useShinyjs(),theme = shinytheme('superhero'),
fluidRow( column( 7, offset = 1, h2("WHO IS MOST LIKELY TO LIVE? ")
)
),
fluidRow ( id = "greyBox", align = "center",imageOutput("grey", click = "grey_click")
... |
rm(list=ls())
library(ggplot2)
library(plyr)
library(dplyr)
library(moments)
home_wd = "/Users/caraebrook/Documents/R/R_repositories/COVID-Ct-Madagascar/Mada-Ct-Distribute/"
main_wd = paste0(home_wd, "/fig-plots/")
setwd(main_wd)
#Ct and distribution fits
mada.df.tot <- read.csv("mada-ct-cross-gp.csv", header = TRU... | /fig-plots/Fig3-S7-S8-S9.R | no_license | carabrook/Mada-Ct-Distribute | R | false | false | 12,197 | r | rm(list=ls())
library(ggplot2)
library(plyr)
library(dplyr)
library(moments)
home_wd = "/Users/caraebrook/Documents/R/R_repositories/COVID-Ct-Madagascar/Mada-Ct-Distribute/"
main_wd = paste0(home_wd, "/fig-plots/")
setwd(main_wd)
#Ct and distribution fits
mada.df.tot <- read.csv("mada-ct-cross-gp.csv", header = TRU... |
# Code used to create charts for 1.2 Grammar of Graphics
# Not for distribution to students
library(tidyverse) # Makes tidyverse accessible to this script
baseball <- read_csv("/Users/mchapple/Desktop/baseball.csv")
baseball <- baseball %>%
gather(year, wins, -Team) %>%
rename(team=Team)
baseball$year <- as.inte... | /R/ggplot2 - LinkedIn Learning/1_2_examples.r | no_license | robbyjeffries1/DataSciencePortfolio | R | false | false | 1,085 | r | # Code used to create charts for 1.2 Grammar of Graphics
# Not for distribution to students
library(tidyverse) # Makes tidyverse accessible to this script
baseball <- read_csv("/Users/mchapple/Desktop/baseball.csv")
baseball <- baseball %>%
gather(year, wins, -Team) %>%
rename(team=Team)
baseball$year <- as.inte... |
library(ssvd)
### Name: ssvd
### Title: Sparse SVD
### Aliases: ssvd
### Keywords: sparse SVD iterative thresholding
### ** Examples
ssvd(matrix(rnorm(2^15),2^7,2^8), method = "method")
| /data/genthat_extracted_code/ssvd/examples/ssvd.Rd.R | no_license | surayaaramli/typeRrh | R | false | false | 193 | r | library(ssvd)
### Name: ssvd
### Title: Sparse SVD
### Aliases: ssvd
### Keywords: sparse SVD iterative thresholding
### ** Examples
ssvd(matrix(rnorm(2^15),2^7,2^8), method = "method")
|
# VideoData
rm(list=ls())
setwd("~/Jasmine uni/Imperial/Winter project/")
library(igraph)
library(dplyr)
library(plyr)
##HB=hidden badge, VB=visible badge
#Read in RFID-fitted cage data from every aviary:
total_interaction<- read.csv("~/Jasmine uni/Imperial/Winter project/total_interaction2.csv")
data<-total_i... | /SNASimulations.R | no_license | j-somerville/MResEECWinter2018 | R | false | false | 8,019 | r | # VideoData
rm(list=ls())
setwd("~/Jasmine uni/Imperial/Winter project/")
library(igraph)
library(dplyr)
library(plyr)
##HB=hidden badge, VB=visible badge
#Read in RFID-fitted cage data from every aviary:
total_interaction<- read.csv("~/Jasmine uni/Imperial/Winter project/total_interaction2.csv")
data<-total_i... |
#' Fast flight phase for the cube method modified
#'
#' @description
#'
#' implementation modified from the package sampling.
#'
#' @param X matrix of auxiliary variables.
#' @param pik vector of inclusion probabilities.
#' @param order order to rearrange the data. Default 1
#' @param comment bool, if comment should... | /R/fastflightcubeSPOT.R | no_license | RJauslin/SamplingC | R | false | false | 3,933 | r | #' Fast flight phase for the cube method modified
#'
#' @description
#'
#' implementation modified from the package sampling.
#'
#' @param X matrix of auxiliary variables.
#' @param pik vector of inclusion probabilities.
#' @param order order to rearrange the data. Default 1
#' @param comment bool, if comment should... |
library(magrittr)
library(purrr)
library(dplyr)
library(ggplot2)
semilla = 800
# base descargada de
# https://www.kaggle.com/aljarah/xAPI-Edu-Data
# notas para la clase -----------------------------------------------------
# leer documentacion de como parte arbol y RF las numericas y las categoricas
# leer ISLR de... | /clases_full/05-arboles_full.r | no_license | ftvalentini/curso-CepalR2019 | R | false | false | 8,162 | r | library(magrittr)
library(purrr)
library(dplyr)
library(ggplot2)
semilla = 800
# base descargada de
# https://www.kaggle.com/aljarah/xAPI-Edu-Data
# notas para la clase -----------------------------------------------------
# leer documentacion de como parte arbol y RF las numericas y las categoricas
# leer ISLR de... |
#' @title Declare a target.
#' @export
#' @description A target is a single step of computation in a pipeline.
#' It runs an R command and returns a value.
#' This value gets treated as an R object that can be used
#' by the commands of targets downstream. Targets that
#' are already up to date are skipped. See... | /R/tar_target.R | permissive | tjmahr/targets | R | false | false | 13,123 | r | #' @title Declare a target.
#' @export
#' @description A target is a single step of computation in a pipeline.
#' It runs an R command and returns a value.
#' This value gets treated as an R object that can be used
#' by the commands of targets downstream. Targets that
#' are already up to date are skipped. See... |
# This is the server logic for a Shiny web application.
# You can find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com
#
library(shiny)
library(ggplot2)
buoydata <- read.csv('data/FormattedBuoyData.csv')
buoydata$DateTime <- as.Date(buoydata$DateTime,format="%m/%d/%Y")
... | /ExampleWaterQualityApp/server.R | no_license | UtahHydroinformatics/ExampleWQAppSolution | R | false | false | 1,355 | r |
# This is the server logic for a Shiny web application.
# You can find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com
#
library(shiny)
library(ggplot2)
buoydata <- read.csv('data/FormattedBuoyData.csv')
buoydata$DateTime <- as.Date(buoydata$DateTime,format="%m/%d/%Y")
... |
## ----echo = FALSE-------------------------------------------------------------
knitr::opts_chunk$set(collapse = TRUE, warning = FALSE, comment = "#>")
suppressPackageStartupMessages(library(sjmisc))
## ----message=FALSE------------------------------------------------------------
library(sjmisc)
data(efc)
##... | /packrat/lib/x86_64-apple-darwin19.4.0/4.0.4/sjmisc/doc/recodingvariables.R | no_license | marilotte/Pregancy_Relapse_Count_Simulation | R | false | false | 3,869 | r | ## ----echo = FALSE-------------------------------------------------------------
knitr::opts_chunk$set(collapse = TRUE, warning = FALSE, comment = "#>")
suppressPackageStartupMessages(library(sjmisc))
## ----message=FALSE------------------------------------------------------------
library(sjmisc)
data(efc)
##... |
##
## hierstrauss.R
##
## $Revision: 1.4 $ $Date: 2015/01/08 07:34:30 $
##
## The hierarchical Strauss process
##
## HierStrauss() create an instance of the hierarchical Strauss process
## [an object of class 'interact']
##
## -------------------------------------------------------------... | /R/hierstrauss.R | no_license | jmetz/spatstat | R | false | false | 9,511 | r | ##
## hierstrauss.R
##
## $Revision: 1.4 $ $Date: 2015/01/08 07:34:30 $
##
## The hierarchical Strauss process
##
## HierStrauss() create an instance of the hierarchical Strauss process
## [an object of class 'interact']
##
## -------------------------------------------------------------... |
sqndwdecomp <-
function (x, J, filter.number, family)
{
lx <- length(x)
ans <- matrix(0, nrow = J, ncol = length(x))
dw <- hwwn.dw(J, filter.number, family)
longest.support <- length(dw[[J]])
scale.shift <- 0
for (j in 1:J) {
l <- length(dw[[j]])
init <- (filter.number - 1) * (l... | /R/sqndwdecomp.R | no_license | cran/hwwntest | R | false | false | 720 | r | sqndwdecomp <-
function (x, J, filter.number, family)
{
lx <- length(x)
ans <- matrix(0, nrow = J, ncol = length(x))
dw <- hwwn.dw(J, filter.number, family)
longest.support <- length(dw[[J]])
scale.shift <- 0
for (j in 1:J) {
l <- length(dw[[j]])
init <- (filter.number - 1) * (l... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/plots.R
\name{plot_branches_method1}
\alias{plot_branches_method1}
\title{Plot a tree with branches colored according to molecular data, method 1}
\usage{
plot_branches_method1(
x,
tip_label = "otu",
drop_outgroup = TRUE,
ladderize_tr... | /man/plot_branches_method1.Rd | no_license | McTavishLab/physcraperex | R | false | true | 864 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/plots.R
\name{plot_branches_method1}
\alias{plot_branches_method1}
\title{Plot a tree with branches colored according to molecular data, method 1}
\usage{
plot_branches_method1(
x,
tip_label = "otu",
drop_outgroup = TRUE,
ladderize_tr... |
At the end of the dada2 tutorial (http://benjjneb.github.io/dada2/tutorial.html), you end up with chimera removed variant tables which can be saved as .rds, piped directly into phyloseq, or converted into biom tables for qiime. In the scripts below, I'm saving one of my libraries as seqtabG_nochim.rds(1). In the nex... | /scripts/create_otu.R | permissive | megaptera-helvetiae/SalmoTruttaVals | R | false | false | 2,077 | r | At the end of the dada2 tutorial (http://benjjneb.github.io/dada2/tutorial.html), you end up with chimera removed variant tables which can be saved as .rds, piped directly into phyloseq, or converted into biom tables for qiime. In the scripts below, I'm saving one of my libraries as seqtabG_nochim.rds(1). In the nex... |
# Copyright 2019 Battelle Memorial Institute; see the LICENSE file.
#' module_socio_L180.GDP_macro
#'
#' National accounts information for GDP macro.
#'
#' @param command API command to execute
#' @param ... other optional parameters, depending on command
#' @return Depends on \code{command}: either a vector of requir... | /input/gcamdata/R/zsocio_L180.GDP_macro.R | permissive | JGCRI/gcam-core | R | false | false | 15,661 | r | # Copyright 2019 Battelle Memorial Institute; see the LICENSE file.
#' module_socio_L180.GDP_macro
#'
#' National accounts information for GDP macro.
#'
#' @param command API command to execute
#' @param ... other optional parameters, depending on command
#' @return Depends on \code{command}: either a vector of requir... |
#'A dataset containing NO2 data for 2010
#'
#'This dataset contains smoothed NO2 data from March to September 2010
#'
#'@format An array of 4 x 179 x 360 dimensions.
#'\describe{
#' \item{Dimension 1}{Each \code{NO2_2010[t, , ]} contains NO2 data for a given month with \code{t=1} corresponding to March and \code{t=7} ... | /R/NO2_2010-data.R | permissive | battyone/eventstream | R | false | false | 567 | r | #'A dataset containing NO2 data for 2010
#'
#'This dataset contains smoothed NO2 data from March to September 2010
#'
#'@format An array of 4 x 179 x 360 dimensions.
#'\describe{
#' \item{Dimension 1}{Each \code{NO2_2010[t, , ]} contains NO2 data for a given month with \code{t=1} corresponding to March and \code{t=7} ... |
## ----setup, include=FALSE------------------------------------------------
require(knitr)
knitr::opts_chunk$set(echo = TRUE)
library(mvITR)
## ----Generate data set, results='markup', echo=TRUE----------------------
set.seed(123)
dat <- generateData(n = 1000)
str(dat)
## ----Summary plots, results='mar... | /inst/doc/mvITR-vignette.R | no_license | kdoub5ha/mvITR | R | false | false | 4,758 | r | ## ----setup, include=FALSE------------------------------------------------
require(knitr)
knitr::opts_chunk$set(echo = TRUE)
library(mvITR)
## ----Generate data set, results='markup', echo=TRUE----------------------
set.seed(123)
dat <- generateData(n = 1000)
str(dat)
## ----Summary plots, results='mar... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/Case1.r
\docType{data}
\name{Case1}
\alias{Case1}
\title{Virtual dataset Case 1}
\format{
A data frame with 1200 rows and 30 variables:
\describe{
\item{SR_ 0.1}{Empty column denoting the start of the record sampled at a
sampling resolution o... | /man/Case1.Rd | no_license | cran/seasonalclumped | R | false | true | 3,180 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/Case1.r
\docType{data}
\name{Case1}
\alias{Case1}
\title{Virtual dataset Case 1}
\format{
A data frame with 1200 rows and 30 variables:
\describe{
\item{SR_ 0.1}{Empty column denoting the start of the record sampled at a
sampling resolution o... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/partydf.R
\name{partition}
\alias{partition}
\title{Partition data across workers in a cluster}
\usage{
partition(data, cluster)
}
\arguments{
\item{data}{Dataset to partition, typically grouped. When grouped, all
observations in a ... | /multidplyr/man/partition.Rd | permissive | yp1227/Multiplier | R | false | true | 984 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/partydf.R
\name{partition}
\alias{partition}
\title{Partition data across workers in a cluster}
\usage{
partition(data, cluster)
}
\arguments{
\item{data}{Dataset to partition, typically grouped. When grouped, all
observations in a ... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/transfer_coda.R
\name{clrvar2phi}
\alias{clrvar2phi}
\title{Calculate Phi Statistics (Proportionality) from CLR Covariances}
\usage{
clrvar2phi(Sigma)
}
\arguments{
\item{Sigma}{Covariance matrix Px(PN) where N is number of
covariance matric... | /man/clrvar2phi.Rd | no_license | jsilve24/RcppCoDA | R | false | true | 752 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/transfer_coda.R
\name{clrvar2phi}
\alias{clrvar2phi}
\title{Calculate Phi Statistics (Proportionality) from CLR Covariances}
\usage{
clrvar2phi(Sigma)
}
\arguments{
\item{Sigma}{Covariance matrix Px(PN) where N is number of
covariance matric... |
# Congratulations on learning GitHub!
# Make any edits you like here:
jbkku j | /practicescript.R | no_license | garciajj/github-intro-2 | R | false | false | 80 | r | # Congratulations on learning GitHub!
# Make any edits you like here:
jbkku j |
% Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/boynton.R
\name{show_boynton}
\alias{show_boynton}
\title{Show the colors in a palette view}
\usage{
show_boynton()
}
\description{
Show the colors in a palette view
}
| /man/show_boynton.Rd | no_license | btupper/catecolors | R | false | false | 255 | rd | % Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/boynton.R
\name{show_boynton}
\alias{show_boynton}
\title{Show the colors in a palette view}
\usage{
show_boynton()
}
\description{
Show the colors in a palette view
}
|
#------------------------------------------------------------------------------#
# Replication of Brookhart M.A. et al. (2006)
# Variable Selection for Propensity Score Models.
# American Journal of Epidemiology, 163(12), 1149–1156.
#
# Replicator: K Luijken
# Co-pilot: B B L Penning de Vries
#
# Helper function to est... | /Replication.Brookhart.2006/R/estimate_effect_quintiles.R | permissive | replisims/Brookhart_MA-2006 | R | false | false | 2,352 | r | #------------------------------------------------------------------------------#
# Replication of Brookhart M.A. et al. (2006)
# Variable Selection for Propensity Score Models.
# American Journal of Epidemiology, 163(12), 1149–1156.
#
# Replicator: K Luijken
# Co-pilot: B B L Penning de Vries
#
# Helper function to est... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/rls_update.R
\name{rls_update}
\alias{rls_update}
\title{Updates the model fits}
\usage{
rls_update(model, datatr = NA, y = NA, runcpp = TRUE)
}
\arguments{
\item{model}{A model object}
\item{datatr}{a data.list with transformed data (from m... | /onlineforecast/man/rls_update.Rd | no_license | akhikolla/updatedatatype-list2 | R | false | true | 1,073 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/rls_update.R
\name{rls_update}
\alias{rls_update}
\title{Updates the model fits}
\usage{
rls_update(model, datatr = NA, y = NA, runcpp = TRUE)
}
\arguments{
\item{model}{A model object}
\item{datatr}{a data.list with transformed data (from m... |
pollutantmean <- function(directory, pollutant, id = 1:332){
data <- NA
result <- 0
# the id vector is a reference to the monitor data we need to read.
# read in the monitors specified by the callee
files = file.path(directory, paste0(formatC(id, width=3, format="d", flag="0"), ".csv"))
# print... | /Week2/pollutantmean.R | no_license | XAGV1YBGAdk34WDPVVLn/datasciencecoursera | R | false | false | 869 | r | pollutantmean <- function(directory, pollutant, id = 1:332){
data <- NA
result <- 0
# the id vector is a reference to the monitor data we need to read.
# read in the monitors specified by the callee
files = file.path(directory, paste0(formatC(id, width=3, format="d", flag="0"), ".csv"))
# print... |
#!/usr/bin/env Rscript
library(TitanCNA)
version <- "0.1.2"
args <- commandArgs(TRUE)
tumWig <- args[1]
normWig <- args[2]
gc <- args[3]
map <- args[4]
target_list <- args[5]
outfile <- args[6]
genometype <- args[7]
message('titan: Correcting GC content and mappability biases...')
if( target_list!="NULL" ){
targ... | /dockerfiles/titan/correctReads.R | no_license | shahcompbio/wgspipeline_docker_containers | R | false | false | 712 | r | #!/usr/bin/env Rscript
library(TitanCNA)
version <- "0.1.2"
args <- commandArgs(TRUE)
tumWig <- args[1]
normWig <- args[2]
gc <- args[3]
map <- args[4]
target_list <- args[5]
outfile <- args[6]
genometype <- args[7]
message('titan: Correcting GC content and mappability biases...')
if( target_list!="NULL" ){
targ... |
#######################################################################
# Mike Safar - CorpusSummary
# ----------------------------------------------
# Copyright (C) 2018. All Rights Reserved.
########################################################################
library(R6)
library(logging)
library(tm)
library(s... | /corpusSummary.R | no_license | mikesafar/signal-boost | R | false | false | 9,808 | r | #######################################################################
# Mike Safar - CorpusSummary
# ----------------------------------------------
# Copyright (C) 2018. All Rights Reserved.
########################################################################
library(R6)
library(logging)
library(tm)
library(s... |
library(ISLR)
library(tidyverse)
library(caret)
library(keras)
library(neuralnet)
library(Hmisc)
data = read.csv("Datos.csv") %>%
filter(G3 != 0)
data_nn= data %>%
dplyr::select(,c("G2","G1","age","studytime","failures",
"G3","traveltime","absences"))#,"Medu",
#"Fedu","famre... | /NNSCRIP.R | no_license | stuarstuar/modelospredictivos2 | R | false | false | 1,402 | r | library(ISLR)
library(tidyverse)
library(caret)
library(keras)
library(neuralnet)
library(Hmisc)
data = read.csv("Datos.csv") %>%
filter(G3 != 0)
data_nn= data %>%
dplyr::select(,c("G2","G1","age","studytime","failures",
"G3","traveltime","absences"))#,"Medu",
#"Fedu","famre... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/antsImageIterator_class.R
\name{antsImageIteratorIsAtEnd}
\alias{antsImageIteratorIsAtEnd}
\title{antsImageIteratorIsAtEnd}
\usage{
antsImageIteratorIsAtEnd(x)
}
\arguments{
\item{x}{antsImageIterator}
}
\value{
boolean indicating position
}
... | /man/antsImageIteratorIsAtEnd.Rd | permissive | alainlompo/ANTsR | R | false | true | 525 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/antsImageIterator_class.R
\name{antsImageIteratorIsAtEnd}
\alias{antsImageIteratorIsAtEnd}
\title{antsImageIteratorIsAtEnd}
\usage{
antsImageIteratorIsAtEnd(x)
}
\arguments{
\item{x}{antsImageIterator}
}
\value{
boolean indicating position
}
... |
library(plotrix)
library(cowplot)
library(gridGraphics)
space = seq(0, 1, 0.1)
star = 0.8 * space + 0.1
circle = -0.8 * space + 0.9
d1 = data.frame(space = c(space, space),
fitness = c(star, circle),
type = c(rep("star", length(star)),
rep("circle", length(circle)... | /Figure1.R | no_license | singhal/hz_metaanalysis | R | false | false | 3,225 | r | library(plotrix)
library(cowplot)
library(gridGraphics)
space = seq(0, 1, 0.1)
star = 0.8 * space + 0.1
circle = -0.8 * space + 0.9
d1 = data.frame(space = c(space, space),
fitness = c(star, circle),
type = c(rep("star", length(star)),
rep("circle", length(circle)... |
library(testthat)
suppressPackageStartupMessages(library(sluRm))
test_check("sluRm")
| /tests/testthat.R | permissive | pmarjora/sluRm | R | false | false | 87 | r | library(testthat)
suppressPackageStartupMessages(library(sluRm))
test_check("sluRm")
|
make_type <- function(x) {
if (is.null(x)) {
return()
}
if (substr(x, 1, 1) == ".") {
x <- mime::guess_type(x, empty = NULL)
}
list(`Content-Type` = x)
}
# adapted from https://github.com/hadley/httr
raw_body <- function(body, type = NULL) {
if (is.character(body)) {
body <- charToRaw(paste(bo... | /R/body.R | permissive | dickoa/crul | R | false | false | 2,217 | r | make_type <- function(x) {
if (is.null(x)) {
return()
}
if (substr(x, 1, 1) == ".") {
x <- mime::guess_type(x, empty = NULL)
}
list(`Content-Type` = x)
}
# adapted from https://github.com/hadley/httr
raw_body <- function(body, type = NULL) {
if (is.character(body)) {
body <- charToRaw(paste(bo... |
library(lme4)
library(data.table)
cd52.expr=read.table('cd52.txt')
cd52.covs=fread('cd52.covs.txt', sep=',',header=T)
#lets put all of our variables in here
df=data.frame(cd52.covs, cd52=cd52.expr)
#just get the monocytes for now, and just SLE
df.use=df[intersect(grep('CD14', df$ct_cov), which(df$disease_cov=='sle')... | /scQTL.R | no_license | yelabucsf/sceQTL | R | false | false | 1,903 | r | library(lme4)
library(data.table)
cd52.expr=read.table('cd52.txt')
cd52.covs=fread('cd52.covs.txt', sep=',',header=T)
#lets put all of our variables in here
df=data.frame(cd52.covs, cd52=cd52.expr)
#just get the monocytes for now, and just SLE
df.use=df[intersect(grep('CD14', df$ct_cov), which(df$disease_cov=='sle')... |
getVal <- function(x, vars = "both"){
#' Get the vector of Kc/c values from the chaos01.res object.
#'
#' This function allows easy extraction of Kc/c values from the chaos01.res object.
#' @param x the object of "chaos01.res" class, produced by testChaos01 function when parameter out = "TRUE". Subset the outp... | /R/getval.R | no_license | cran/Chaos01 | R | false | false | 1,770 | r | getVal <- function(x, vars = "both"){
#' Get the vector of Kc/c values from the chaos01.res object.
#'
#' This function allows easy extraction of Kc/c values from the chaos01.res object.
#' @param x the object of "chaos01.res" class, produced by testChaos01 function when parameter out = "TRUE". Subset the outp... |
path <- "~/Desktop/PhD/GitKraken/gmse_fork_RQ1/batch6-perfObs/"
setwd(dir = path)
# get the directory content
content <- dir()
# order alphabetically
content <- content[order(content)]
#### sim results ####
# initialize a table with the UT0
at0 <- grep(pattern = c("UT0pt0-"), x = content, fixed = T, value = T)
at0... | /merge-results.R | no_license | AdrianBach/gmse | R | false | false | 4,133 | r | path <- "~/Desktop/PhD/GitKraken/gmse_fork_RQ1/batch6-perfObs/"
setwd(dir = path)
# get the directory content
content <- dir()
# order alphabetically
content <- content[order(content)]
#### sim results ####
# initialize a table with the UT0
at0 <- grep(pattern = c("UT0pt0-"), x = content, fixed = T, value = T)
at0... |
% Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/function.R
\name{distr}
\alias{distr}
\title{Length distribution}
\usage{
distr(mu, sigma, l, par = data.frame())
}
\arguments{
\item{mu}{mean length for all ages}
\item{sigma}{standard deviation of length for all ages}
\item{l}{len... | /man/distr.Rd | no_license | milokmilo/rgadget | R | false | false | 558 | rd | % Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/function.R
\name{distr}
\alias{distr}
\title{Length distribution}
\usage{
distr(mu, sigma, l, par = data.frame())
}
\arguments{
\item{mu}{mean length for all ages}
\item{sigma}{standard deviation of length for all ages}
\item{l}{len... |
#' Bayes Factor Calculation Scheme for META prior
#'
#' A function that calculates bayes factor for each data pair on each grid point
#' in log scale.
#'
#' @param data A dataset which is constructed by pairs of coefficient
#' values \eqn{ \beta } and standard errors \eqn{ se(\beta)}.
#' @param hyperparam A two... | /R/bf.cal.meta.R | no_license | cran/INTRIGUE | R | false | false | 2,634 | r | #' Bayes Factor Calculation Scheme for META prior
#'
#' A function that calculates bayes factor for each data pair on each grid point
#' in log scale.
#'
#' @param data A dataset which is constructed by pairs of coefficient
#' values \eqn{ \beta } and standard errors \eqn{ se(\beta)}.
#' @param hyperparam A two... |
% Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/parameterEstimation.R
\name{Cvb}
\alias{Cvb}
\title{Cvb function}
\usage{
Cvb(xyt, spatial.intensity, N = 100, spatial.covmodel, covpars)
}
\arguments{
\item{xyt}{object of class stppp}
\item{spatial.intensity}{bivariate density esti... | /man/Cvb.Rd | no_license | bentaylor1/lgcp | R | false | false | 1,256 | rd | % Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/parameterEstimation.R
\name{Cvb}
\alias{Cvb}
\title{Cvb function}
\usage{
Cvb(xyt, spatial.intensity, N = 100, spatial.covmodel, covpars)
}
\arguments{
\item{xyt}{object of class stppp}
\item{spatial.intensity}{bivariate density esti... |
# List of sample names to combine each person's sequencing for CAZyme analysis
map <- read.delim(file = "~/Documents/Projects/dietstudy/data/maps/SampleID_map.txt")
map$X.SampleID <- gsub("\\.", "_", map$X.SampleID)
run1names <- read.delim(file = "~/Documents/Projects/dietstudy/data/run1names.txt", header = F, col.na... | /lib/processing_scripts/sequencingrunnames.R | no_license | knights-lab/dietstudy_analyses | R | false | false | 1,460 | r | # List of sample names to combine each person's sequencing for CAZyme analysis
map <- read.delim(file = "~/Documents/Projects/dietstudy/data/maps/SampleID_map.txt")
map$X.SampleID <- gsub("\\.", "_", map$X.SampleID)
run1names <- read.delim(file = "~/Documents/Projects/dietstudy/data/run1names.txt", header = F, col.na... |
# plot of all 2017 balls and strikes
library(dplyr)
library(tibble)
library(ggplot2)
#pitches <- as_data_frame(readRDS("pitches2017.Rda"))
# Rule book zone: up/down pz's have been normalized to go from
# 1.5 to 3.5. Width of baseball is 0.245 feet, so we add 1/2 of
# a baseball's width to each edge. Width of plate is ... | /figures/ball_strike_cloud.R | no_license | djhunter/inconsistency | R | false | false | 3,485 | r | # plot of all 2017 balls and strikes
library(dplyr)
library(tibble)
library(ggplot2)
#pitches <- as_data_frame(readRDS("pitches2017.Rda"))
# Rule book zone: up/down pz's have been normalized to go from
# 1.5 to 3.5. Width of baseball is 0.245 feet, so we add 1/2 of
# a baseball's width to each edge. Width of plate is ... |
raw.data = file.choose()
Vigilance.Calc.Block.Function = function(dataset,binsize){
acc.start = 15
omission.start = 65
total.bins = 50 / binsize
new.data = as.data.frame(matrix(nrow=nrow(dataset),ncol=(total.bins * 2)))
bin.num = 1
for(a in 1:total.bins){
acc.col = a
colnames(new.data)[ac... | /Chris Vigilance.R | no_license | dpalmer9/Weston_QC_Processor | R | false | false | 2,117 | r | raw.data = file.choose()
Vigilance.Calc.Block.Function = function(dataset,binsize){
acc.start = 15
omission.start = 65
total.bins = 50 / binsize
new.data = as.data.frame(matrix(nrow=nrow(dataset),ncol=(total.bins * 2)))
bin.num = 1
for(a in 1:total.bins){
acc.col = a
colnames(new.data)[ac... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/xls-find.R
\name{xls_find}
\alias{xls_find}
\title{Find the pair of Excel files from a automatic weather station}
\usage{
xls_find(file.name, verbose = TRUE)
}
\arguments{
\item{file.name}{character vector with paths to Excel files;
in genera... | /man/xls_find.Rd | permissive | lhmet/rinmetxls | R | false | true | 958 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/xls-find.R
\name{xls_find}
\alias{xls_find}
\title{Find the pair of Excel files from a automatic weather station}
\usage{
xls_find(file.name, verbose = TRUE)
}
\arguments{
\item{file.name}{character vector with paths to Excel files;
in genera... |
\name{runShiny}
\alias{runShiny}
\title{
Run Shiny Web interface
}
\description{
Web interface for univariate, bivariate and multivariate breakeven analysis
}
\usage{
runShiny(...,name="shiny_perctolimit")
}
\arguments{
\item{\dots}{
Arguments to pass to \code{\link{runApp}}
}
\item{name}{
User interface to... | /man/runShiny.Rd | no_license | josephguillaume/cost_benefit_breakeven | R | false | false | 550 | rd | \name{runShiny}
\alias{runShiny}
\title{
Run Shiny Web interface
}
\description{
Web interface for univariate, bivariate and multivariate breakeven analysis
}
\usage{
runShiny(...,name="shiny_perctolimit")
}
\arguments{
\item{\dots}{
Arguments to pass to \code{\link{runApp}}
}
\item{name}{
User interface to... |
# Install Requried Packages
installed.packages("SnowballC")
installed.packages("tm")
installed.packages("twitteR")
installed.packages("syuzhet")
# Load Requried Packages
library("SnowballC")
library("tm")
library("twitteR")
library("syuzhet")
library(data.table)
data_republicans <- fread("C:/Users/uia91182/Desktop... | /scripts/wordseperation_republicans.R | no_license | sakethg/Sentiment-Analysis-on-political-twitter-data | R | false | false | 2,836 | r | # Install Requried Packages
installed.packages("SnowballC")
installed.packages("tm")
installed.packages("twitteR")
installed.packages("syuzhet")
# Load Requried Packages
library("SnowballC")
library("tm")
library("twitteR")
library("syuzhet")
library(data.table)
data_republicans <- fread("C:/Users/uia91182/Desktop... |
#Load library
library(plyr)
url<-"https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip"
file <- "dataset.zip"
baseDir <-"UCI HAR Dataset"
# Download the files if required
if(!file.exists(file)){
download.file(url, file, method="curl")
unzip(file, list = FALSE, overwrite = TRUE... | /course-project/run_analysis.R | no_license | senthil69/datasciencecoursera | R | false | false | 2,402 | r | #Load library
library(plyr)
url<-"https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip"
file <- "dataset.zip"
baseDir <-"UCI HAR Dataset"
# Download the files if required
if(!file.exists(file)){
download.file(url, file, method="curl")
unzip(file, list = FALSE, overwrite = TRUE... |
/Practica 8/ref_reto1.R | no_license | DavidM0413/Simulacion_Sistemas | R | false | false | 3,625 | r | ||
#' Power Generation
#'
#' This function computes instantaneous power generation
#’ from a reservoir given its height and flow rate into turbines
#' @param rho Density of water (kg/m3) Default is 1000
#' @param g Acceleration due to gravity (m/sec2) Default is 9.8
#' @param Kefficiency Turbine Efficiency (0-1) Default i... | /power_gen.R | no_license | tcobian/ESM_232 | R | false | false | 649 | r | #' Power Generation
#'
#' This function computes instantaneous power generation
#’ from a reservoir given its height and flow rate into turbines
#' @param rho Density of water (kg/m3) Default is 1000
#' @param g Acceleration due to gravity (m/sec2) Default is 9.8
#' @param Kefficiency Turbine Efficiency (0-1) Default i... |
#NAOC 2020 count data workshop distance probability distribution lesson
#By Evan Adams and Beth Ross
###########################################################
#Not a lot of code here, just showing how we created the distributions shown in the presentation
#coin flipping
hist(rbinom(10, 1, 0.5))
#proba... | /lessons/probability_distribution_lesson_code.R | no_license | dubrewer92/NAOC2020-Count-Data-Workshop | R | false | false | 1,171 | r | #NAOC 2020 count data workshop distance probability distribution lesson
#By Evan Adams and Beth Ross
###########################################################
#Not a lot of code here, just showing how we created the distributions shown in the presentation
#coin flipping
hist(rbinom(10, 1, 0.5))
#proba... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/clustering.R
\name{cluster_pathways}
\alias{cluster_pathways}
\title{Cluster Pathways}
\usage{
cluster_pathways(enrichment_res, method = "hierarchical",
kappa_threshold = 0.35, plot_clusters_graph = TRUE,
use_names = FALSE, use_active_snw... | /man/cluster_pathways.Rd | no_license | KUNJU-PITT/pathfindR | R | false | true | 2,311 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/clustering.R
\name{cluster_pathways}
\alias{cluster_pathways}
\title{Cluster Pathways}
\usage{
cluster_pathways(enrichment_res, method = "hierarchical",
kappa_threshold = 0.35, plot_clusters_graph = TRUE,
use_names = FALSE, use_active_snw... |
# Read in data
library(data.table)
data_train <- fread("data/train.csv")
data_test <- fread("data/test.csv")
##### Preprocess
## For imputation, stack predictors in training and test together
allPred <- rbindlist(list(data_train,data_test),use.names=TRUE,fill=TRUE,idcol = "Source")
ol.mask <- allPred$Fare==0|allPred... | /titanic2.R | no_license | chelsyx/titanic_kaggle | R | false | false | 5,741 | r | # Read in data
library(data.table)
data_train <- fread("data/train.csv")
data_test <- fread("data/test.csv")
##### Preprocess
## For imputation, stack predictors in training and test together
allPred <- rbindlist(list(data_train,data_test),use.names=TRUE,fill=TRUE,idcol = "Source")
ol.mask <- allPred$Fare==0|allPred... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/readmsb.R
\name{ms2bed}
\alias{ms2bed}
\title{Import the output of the \code{ms} program in a \code{BED} object}
\usage{
ms2bed(fname)
}
\arguments{
\item{fname}{the name of the text file containing \code{ms} output}
}
\value{
a bed object
}
... | /man/ms2bed.Rd | no_license | plantarum/hierfstat | R | false | true | 489 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/readmsb.R
\name{ms2bed}
\alias{ms2bed}
\title{Import the output of the \code{ms} program in a \code{BED} object}
\usage{
ms2bed(fname)
}
\arguments{
\item{fname}{the name of the text file containing \code{ms} output}
}
\value{
a bed object
}
... |
setwd('~/Downloads/battleship/data_visualization')
# model 1
basic_model1 = read.csv('../results/basic_test_model1.csv')
b_model1_BT = subset(basic_model1, `propagation.type` == 'BT')
b_model1_FC = subset(basic_model1, `propagation.type` == 'FC')
b_model1_GAC = subset(basic_model1, `propagation.type` == 'GAC')
b_mode... | /data_visualization/PD_board_size_basic.R | no_license | pyliaorachel/battleship-ai | R | false | false | 4,045 | r | setwd('~/Downloads/battleship/data_visualization')
# model 1
basic_model1 = read.csv('../results/basic_test_model1.csv')
b_model1_BT = subset(basic_model1, `propagation.type` == 'BT')
b_model1_FC = subset(basic_model1, `propagation.type` == 'FC')
b_model1_GAC = subset(basic_model1, `propagation.type` == 'GAC')
b_mode... |
while(TRUE){
print('Hello') # use print inside loops
}
counter <- 1
while(counter < 12){
print(counter)
counter <- counter + 1 # counter++ does not work
}
# Iterate i from 1 to 5
for(i in 1:5){
print("Hello R")
}
# Prints Hello 6 times
for(i in 5:10){
print("Hello R")
}
| /loops.R | no_license | rhymermj/R-practice | R | false | false | 298 | r | while(TRUE){
print('Hello') # use print inside loops
}
counter <- 1
while(counter < 12){
print(counter)
counter <- counter + 1 # counter++ does not work
}
# Iterate i from 1 to 5
for(i in 1:5){
print("Hello R")
}
# Prints Hello 6 times
for(i in 5:10){
print("Hello R")
}
|
networkER <- function(p.){
# Input : p. - total dim
# Output : a matrix with Erdos-Renyi structure
A <- matrix(0,p.,p.)
for (i in 1:p.){
for (j in 1:p.) A[i,j] <- ifelse(rbinom(1, size=1, 0.3), ifelse(rbinom(1, size=1, 0.5),
runif(1, min ... | /networks.R | no_license | DeniseYi/Assisted_Differential_Network | R | false | false | 4,313 | r | networkER <- function(p.){
# Input : p. - total dim
# Output : a matrix with Erdos-Renyi structure
A <- matrix(0,p.,p.)
for (i in 1:p.){
for (j in 1:p.) A[i,j] <- ifelse(rbinom(1, size=1, 0.3), ifelse(rbinom(1, size=1, 0.5),
runif(1, min ... |
setMethod("initialize", signature(.Object="BeadStudioSetList"),
function(.Object,
assayDataList=AssayDataList(baf=baf, lrr=lrr),
lrr=list(),
baf=lapply(lrr, function(x) matrix(nrow=nrow(x), ncol=ncol(x))),
featureDataList=GenomeAnnotatedDataFrameFrom(assayDataList, annotation, genome),
chrom... | /R/methods-BeadStudioSetList.R | no_license | benilton/oligoClasses | R | false | false | 7,111 | r | setMethod("initialize", signature(.Object="BeadStudioSetList"),
function(.Object,
assayDataList=AssayDataList(baf=baf, lrr=lrr),
lrr=list(),
baf=lapply(lrr, function(x) matrix(nrow=nrow(x), ncol=ncol(x))),
featureDataList=GenomeAnnotatedDataFrameFrom(assayDataList, annotation, genome),
chrom... |
\name{Principal coordinate analysis using the Jensen-Shannon divergence}
\alias{esov.mds}
\title{
Principal coordinate analysis using the Jensen-Shannon divergence
}
\description{
Principal coordinate analysis using the Jensen-Shannon divergence.
}
\usage{
esov.mds(x, k = 2, eig = TRUE)
}
\arguments{
... | /man/esov.mds.Rd | no_license | cran/Compositional | R | false | false | 1,740 | rd | \name{Principal coordinate analysis using the Jensen-Shannon divergence}
\alias{esov.mds}
\title{
Principal coordinate analysis using the Jensen-Shannon divergence
}
\description{
Principal coordinate analysis using the Jensen-Shannon divergence.
}
\usage{
esov.mds(x, k = 2, eig = TRUE)
}
\arguments{
... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/explorePatentData.R
\name{summarizeColumns}
\alias{summarizeColumns}
\title{Summarize columns of a data frame}
\usage{
summarizeColumns(df, names, naOmit = FALSE)
}
\arguments{
\item{df}{A data frame of patent data.}
\item{names}{a character... | /man/summarizeColumns.Rd | no_license | lupok2001/patentr | R | false | true | 1,640 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/explorePatentData.R
\name{summarizeColumns}
\alias{summarizeColumns}
\title{Summarize columns of a data frame}
\usage{
summarizeColumns(df, names, naOmit = FALSE)
}
\arguments{
\item{df}{A data frame of patent data.}
\item{names}{a character... |
## Processing torpor data from 2015 field season to incorporate with previous torpor data
## Anusha Shankar
## Started February 22, 2016
##Packages
library(ggplot2)
library(reshape)
library(gridExtra)
library(grid)
library(wq)
library(gam)
library(foreign)
library(MASS)
library(devtools)
require(dplyr)
#library(plotfl... | /Torpor1415/Torpor2015.R | no_license | nushiamme/AShankar_hummers | R | false | false | 27,199 | r | ## Processing torpor data from 2015 field season to incorporate with previous torpor data
## Anusha Shankar
## Started February 22, 2016
##Packages
library(ggplot2)
library(reshape)
library(gridExtra)
library(grid)
library(wq)
library(gam)
library(foreign)
library(MASS)
library(devtools)
require(dplyr)
#library(plotfl... |
### 0. preparation for the data cleaning
# call libraries
library(dplyr)
library(plyr)
library(reshape2)
# download row data
fileURL <- "https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip "
download.file(fileURL, "rowdata.zip", method="curl")
# unzip row data
unzip("rowdata.zip... | /Course 3 - Getting and Cleaning Data/Course 3 - Assignments/run_analysis.R | no_license | buihongthu/datasciencespecialization | R | false | false | 2,535 | r | ### 0. preparation for the data cleaning
# call libraries
library(dplyr)
library(plyr)
library(reshape2)
# download row data
fileURL <- "https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip "
download.file(fileURL, "rowdata.zip", method="curl")
# unzip row data
unzip("rowdata.zip... |
#
#
#
context("Test that all null model methods work")
# Here we just run the code to check that it works
test_that("All null model methods work", {
# We need to increase the max number of iterations otherwise warnings are produced
options(spatialwarnings.constants.maxit = 10^(8.5))
options(spatialwarni... | /tests/testthat/test-nullfun.R | permissive | spatial-ews/spatialwarnings | R | false | false | 11,173 | r | #
#
#
context("Test that all null model methods work")
# Here we just run the code to check that it works
test_that("All null model methods work", {
# We need to increase the max number of iterations otherwise warnings are produced
options(spatialwarnings.constants.maxit = 10^(8.5))
options(spatialwarni... |
# EXERCISE: K-Means Clustering Example
iris_tbl <- copy_to(sc, iris, "iris", overwrite = TRUE)
kmeans_model <- iris_tbl %>%
ml_kmeans(k = 3, features = c("Petal_Length", "Petal_Width"))
print(kmeans_model)
# Predict associated class
predicted <- ml_predict(kmeans_model, iris_tbl) %>%
collect
table(predicted$Spe... | /reference/modeling-exercises.R | no_license | BB1464/wsds_sparklyr_workshop | R | false | false | 1,044 | r | # EXERCISE: K-Means Clustering Example
iris_tbl <- copy_to(sc, iris, "iris", overwrite = TRUE)
kmeans_model <- iris_tbl %>%
ml_kmeans(k = 3, features = c("Petal_Length", "Petal_Width"))
print(kmeans_model)
# Predict associated class
predicted <- ml_predict(kmeans_model, iris_tbl) %>%
collect
table(predicted$Spe... |
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | /r/tests/testthat/test-Array.R | permissive | vikrant1717/arrow | R | false | false | 30,038 | r | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... |
# Do transmission tree reconstruction & generate priors -----
source("R/utils.R")
# Packages
library(here)
library(treerabid) # devtools::install_github("mrajeev08/treerabid")
library(data.table)
library(lubridate)
library(dplyr)
library(lubridate)
library(magrittr)
library(foreach)
library(iterators)
library(doRNG)
... | /analysis/scripts/00_trees_priors.R | no_license | mrajeev08/dynamicSD | R | false | false | 3,863 | r | # Do transmission tree reconstruction & generate priors -----
source("R/utils.R")
# Packages
library(here)
library(treerabid) # devtools::install_github("mrajeev08/treerabid")
library(data.table)
library(lubridate)
library(dplyr)
library(lubridate)
library(magrittr)
library(foreach)
library(iterators)
library(doRNG)
... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/imports.most.R
\name{imports.most}
\alias{imports.most}
\title{Mostly imported packages}
\usage{
imports.most(imports, n = 10, year = FALSE)
}
\arguments{
\item{imports}{results of function imports()}
\item{n}{the most frequency number}
\it... | /man/imports.most.Rd | no_license | yikeshu0611/packagomatrics | R | false | true | 1,279 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/imports.most.R
\name{imports.most}
\alias{imports.most}
\title{Mostly imported packages}
\usage{
imports.most(imports, n = 10, year = FALSE)
}
\arguments{
\item{imports}{results of function imports()}
\item{n}{the most frequency number}
\it... |
library(coin)
absoluteMeanDifferences <- function(group1,group2){
return(abs(mean(group1)-mean(group2)))
}
permTest <- function(group1,group2,permutations=1000){
testStatistic <- absoluteMeanDifferences
observed <- testStatistic(group1,group2)
allValues <- c(group1,group2)
groupMemberShips <- c(rep(TRUE,l... | /permutationTest.R | no_license | rushkock/simulation_practice | R | false | false | 2,133 | r | library(coin)
absoluteMeanDifferences <- function(group1,group2){
return(abs(mean(group1)-mean(group2)))
}
permTest <- function(group1,group2,permutations=1000){
testStatistic <- absoluteMeanDifferences
observed <- testStatistic(group1,group2)
allValues <- c(group1,group2)
groupMemberShips <- c(rep(TRUE,l... |
library(TMB)
compile("birthDist.cpp","-O1 -g",DLLFLAGS="")
dyn.load(dynlib("birthDist"))
load("birthidstData.RDat")
obj <- MakeADFun(data,parameters,DLL="birthDist",checkParameterOrder = FALSE)
obj$fn()
obj$gr()
system.time(opt <- nlminb(obj$par,obj$fn,obj$gr,control = list(eval.max = 1e6,maxit = 1e6)))
rep<-sdrep... | /scripts/BirthDist3.R | no_license | NorskRegnesentral/pupR | R | false | false | 5,140 | r | library(TMB)
compile("birthDist.cpp","-O1 -g",DLLFLAGS="")
dyn.load(dynlib("birthDist"))
load("birthidstData.RDat")
obj <- MakeADFun(data,parameters,DLL="birthDist",checkParameterOrder = FALSE)
obj$fn()
obj$gr()
system.time(opt <- nlminb(obj$par,obj$fn,obj$gr,control = list(eval.max = 1e6,maxit = 1e6)))
rep<-sdrep... |
#Levels of a given vector
v = c(1, 2, 3, 3, 4, NA, 3, 2, 4, 5, NA, 5)
print("Original vector:")
print(v)
print("Levels of factor of the said vector:")
print(levels(factor(v))) | /lvlofvector.r | permissive | maansisrivastava/Practice-code-R | R | false | false | 182 | r | #Levels of a given vector
v = c(1, 2, 3, 3, 4, NA, 3, 2, 4, 5, NA, 5)
print("Original vector:")
print(v)
print("Levels of factor of the said vector:")
print(levels(factor(v))) |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/SQLContext.R
\name{tableToDF}
\alias{tableToDF}
\title{Create a SparkDataFrame from a SparkSQL table or view}
\usage{
tableToDF(tableName)
}
\arguments{
\item{tableName}{the qualified or unqualified name that designates a table or view. If a ... | /man/tableToDF.Rd | no_license | cran/SparkR | R | false | true | 902 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/SQLContext.R
\name{tableToDF}
\alias{tableToDF}
\title{Create a SparkDataFrame from a SparkSQL table or view}
\usage{
tableToDF(tableName)
}
\arguments{
\item{tableName}{the qualified or unqualified name that designates a table or view. If a ... |
test_that("redist.plot.map works", {
out <- redist.plot.map(shp = iowa, plan = iowa$cd_2010)
expect_true('ggplot' %in% class(out))
iowa_map = redist_map(iowa, existing_plan = cd_2010, pop_tol=0.01)
out <- iowa_map %>% redist.plot.map(shp = ., plan = get_existing(.))
expect_true('ggplot' %in% class(out))
... | /tests/testthat/test_plots.R | no_license | LiYao-sfu/redist | R | false | false | 969 | r | test_that("redist.plot.map works", {
out <- redist.plot.map(shp = iowa, plan = iowa$cd_2010)
expect_true('ggplot' %in% class(out))
iowa_map = redist_map(iowa, existing_plan = cd_2010, pop_tol=0.01)
out <- iowa_map %>% redist.plot.map(shp = ., plan = get_existing(.))
expect_true('ggplot' %in% class(out))
... |
\name{houseVotes}
\alias{houseVotes}
\docType{data}
\title{
Congressional Voting Records Data}
\description{
1984 United Stated Congressional Voting Records for each of the U.S. House of
Representatives Congressmen on the 16 key votes identified by the
Congressional Quarterly Almanac.
}
\usage{data(houseVot... | /man/houseVotes.Rd | no_license | cran/fclust | R | false | false | 2,200 | rd | \name{houseVotes}
\alias{houseVotes}
\docType{data}
\title{
Congressional Voting Records Data}
\description{
1984 United Stated Congressional Voting Records for each of the U.S. House of
Representatives Congressmen on the 16 key votes identified by the
Congressional Quarterly Almanac.
}
\usage{data(houseVot... |
library(nws)
### Name: batchNodeList
### Title: NodeList Functions
### Aliases: batchNodeList sgeNodeList lsfNodeList pbsNodeList
### Keywords: utilities
### ** Examples
Sys.setenv(LSB_HOSTS="node1 node2 node3")
batchNodeList()
| /data/genthat_extracted_code/nws/examples/batchNodeList.Rd.R | no_license | surayaaramli/typeRrh | R | false | false | 235 | r | library(nws)
### Name: batchNodeList
### Title: NodeList Functions
### Aliases: batchNodeList sgeNodeList lsfNodeList pbsNodeList
### Keywords: utilities
### ** Examples
Sys.setenv(LSB_HOSTS="node1 node2 node3")
batchNodeList()
|
CAAJupiter_EclipticLongitude <-
function(JD){
.Call("CAAJupiter_EclipticLongitude", JD)
}
| /R/CAAJupiter_EclipticLongitude.R | no_license | helixcn/skycalc | R | false | false | 94 | r | CAAJupiter_EclipticLongitude <-
function(JD){
.Call("CAAJupiter_EclipticLongitude", JD)
}
|
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