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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 |
|---|---|---|---|---|---|---|---|---|---|
context("test-shapley.R")
RNGversion(vstr = "3.5.0")
test_that("Basic test functions in shapley.R", {
# Load data -----------
if (requireNamespace("MASS", quietly = TRUE)) {
data("Boston", package = "MASS")
x_var <- c("lstat", "rm", "dis", "indus")
x_train <- tail(Boston[, x_var], 50)
# Load pre... | /tests/testthat/test-a-shapley.R | permissive | stjordanis/shapr | R | false | false | 8,013 | r | context("test-shapley.R")
RNGversion(vstr = "3.5.0")
test_that("Basic test functions in shapley.R", {
# Load data -----------
if (requireNamespace("MASS", quietly = TRUE)) {
data("Boston", package = "MASS")
x_var <- c("lstat", "rm", "dis", "indus")
x_train <- tail(Boston[, x_var], 50)
# Load pre... |
#### Получение информации о пользователе сети ВКонтакте.
library(RCurl)
library(rjson)
# Параметры доступа
access_token <- "ключ_доступа_вашего_приложения"
ver <- "5.53"
# Идентификатор пользователя
uid <- "идентификатор_пользователя"
# Функция запроса к API
vk <- function( method, params ) {
if( !missing(param... | /Сбор данных в интернете/18/02-user_info.R | no_license | kn7072/R | R | false | false | 1,599 | r | #### Получение информации о пользователе сети ВКонтакте.
library(RCurl)
library(rjson)
# Параметры доступа
access_token <- "ключ_доступа_вашего_приложения"
ver <- "5.53"
# Идентификатор пользователя
uid <- "идентификатор_пользователя"
# Функция запроса к API
vk <- function( method, params ) {
if( !missing(param... |
############## data preparing for Brandon
install.packages("sqldf")
library(sqldf)
s01 <- sqldf("select pdbid, chainid from protein_annotate_onlysnp group by UniProtID")
write.table(s01, file = "unique_pdb.txt", quote = F, row.names = F)
# get uniprot with disease snp in binding site
uniprot_bs_ds <- sqldf('select Un... | /Analysis/brandon.R | permissive | ajing/SIFTS.py | R | false | false | 2,464 | r |
############## data preparing for Brandon
install.packages("sqldf")
library(sqldf)
s01 <- sqldf("select pdbid, chainid from protein_annotate_onlysnp group by UniProtID")
write.table(s01, file = "unique_pdb.txt", quote = F, row.names = F)
# get uniprot with disease snp in binding site
uniprot_bs_ds <- sqldf('select Un... |
library(ape)
testtree <- read.tree("1177_2.txt")
unrooted_tr <- unroot(testtree)
write.tree(unrooted_tr, file="1177_2_unrooted.txt") | /codeml_files/newick_trees_processed/1177_2/rinput.R | no_license | DaniBoo/cyanobacteria_project | R | false | false | 135 | r | library(ape)
testtree <- read.tree("1177_2.txt")
unrooted_tr <- unroot(testtree)
write.tree(unrooted_tr, file="1177_2_unrooted.txt") |
library(ape)
testtree <- read.tree("7705_0.txt")
unrooted_tr <- unroot(testtree)
write.tree(unrooted_tr, file="7705_0_unrooted.txt") | /codeml_files/newick_trees_processed/7705_0/rinput.R | no_license | DaniBoo/cyanobacteria_project | R | false | false | 135 | r | library(ape)
testtree <- read.tree("7705_0.txt")
unrooted_tr <- unroot(testtree)
write.tree(unrooted_tr, file="7705_0_unrooted.txt") |
rm(list=ls())
library(dplyr)
library(tidyr)
library(ggplot2)
library(testthat)
library(bbmle)
library(lme4)
library(readxl)
options(stringsAsFactors = F)
source("analysis/format_data/format_scripts.R")
source("analysis/format_data/format_functions.R")
# data
lupine_df <- read.csv( "data/lupine_all.csv")
enso ... | /analysis/vital_rates/crossvalidation/fert_cv_t0.R | no_license | AldoCompagnoni/lupine | R | false | false | 8,895 | r | rm(list=ls())
library(dplyr)
library(tidyr)
library(ggplot2)
library(testthat)
library(bbmle)
library(lme4)
library(readxl)
options(stringsAsFactors = F)
source("analysis/format_data/format_scripts.R")
source("analysis/format_data/format_functions.R")
# data
lupine_df <- read.csv( "data/lupine_all.csv")
enso ... |
source("utility.R")
require(Hmisc) # for inc function
TrainMarkov <- function(text, lookup) {
## Creates the transition probability matrix, T[i,j] is the number
## of times word j follows word i. No need to standardize since
## all functions that use T will implicity standardize
N <- length(lookup)
... | /markov.R | no_license | tpospisi/RObama | R | false | false | 798 | r | source("utility.R")
require(Hmisc) # for inc function
TrainMarkov <- function(text, lookup) {
## Creates the transition probability matrix, T[i,j] is the number
## of times word j follows word i. No need to standardize since
## all functions that use T will implicity standardize
N <- length(lookup)
... |
#####################################################################
# Directory :
# Program Name: OLS_specification.R
# Analyst : Paul Laskowski
# Last Updated: 4/3/2015
#
# Purpose:
# OLS Specification
#####################################################################
#####################################... | /Async/Week 13/OLS_specification.R | no_license | shanbrianhe/W203-Statistics-for-Data-Science | R | false | false | 6,725 | r | #####################################################################
# Directory :
# Program Name: OLS_specification.R
# Analyst : Paul Laskowski
# Last Updated: 4/3/2015
#
# Purpose:
# OLS Specification
#####################################################################
#####################################... |
library(ggplot2)
library(gridExtra) #arrangeGrob
this_base <- "fig07-02_annual-report-aspect-ratio-2"
my_data <- data.frame(
income = c(117187, 202796, 357284, 392216, 163811),
year = c(1999, 2000, 2001, 2002, 2003))
p <- ggplot(my_data, aes(x = year, y = income / 1000)) +
geom_line() +
geom_point(shape = 21... | /B_analysts_sources_github/jennybc/r-graph-catalog/fig07-02_annual-report-aspect-ratio-2.R | no_license | Irbis3/crantasticScrapper | R | false | false | 1,383 | r | library(ggplot2)
library(gridExtra) #arrangeGrob
this_base <- "fig07-02_annual-report-aspect-ratio-2"
my_data <- data.frame(
income = c(117187, 202796, 357284, 392216, 163811),
year = c(1999, 2000, 2001, 2002, 2003))
p <- ggplot(my_data, aes(x = year, y = income / 1000)) +
geom_line() +
geom_point(shape = 21... |
source("common.R")
#' plot2 is just a simple line graph of 'Global_active_power' over time with some extra
#' formatting.
#'
#' @param ylab the label to use on the y-axis. Defaults to the one needed for plot2 in the
#' assignment but can be overriden for plot4 which is slightly different.
#' @references `p... | /plot2.R | no_license | jasoma/ExData_Plotting1 | R | false | false | 682 | r | source("common.R")
#' plot2 is just a simple line graph of 'Global_active_power' over time with some extra
#' formatting.
#'
#' @param ylab the label to use on the y-axis. Defaults to the one needed for plot2 in the
#' assignment but can be overriden for plot4 which is slightly different.
#' @references `p... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/consume.R
\name{consume}
\alias{consume}
\title{Use a web service to score data in list (key=value) format.}
\usage{
consume(endpoint, ..., globalParam, retryDelay = 10, output = "output1",
.retry = 5)
}
\arguments{
\item{endpoint}{Either a... | /man/consume.Rd | no_license | Vijayreddym/AzureML | R | false | true | 10,201 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/consume.R
\name{consume}
\alias{consume}
\title{Use a web service to score data in list (key=value) format.}
\usage{
consume(endpoint, ..., globalParam, retryDelay = 10, output = "output1",
.retry = 5)
}
\arguments{
\item{endpoint}{Either a... |
source("global.R")
dashboardPage(
skin = "red",
dashboardHeader(title = "R-Lab / Milano Budget Trasparente",
titleWidth = 450),
dashboardSidebar(disable = TRUE),
dashboardBody(
navbarPage("Schede",
tabPanel("Ripartizione fondi per missione",
sidebarPanel(
... | /app/ui.R | no_license | r-lab-milano/r-lab3-shinyMilano | R | false | false | 5,326 | r | source("global.R")
dashboardPage(
skin = "red",
dashboardHeader(title = "R-Lab / Milano Budget Trasparente",
titleWidth = 450),
dashboardSidebar(disable = TRUE),
dashboardBody(
navbarPage("Schede",
tabPanel("Ripartizione fondi per missione",
sidebarPanel(
... |
MAD(mean(BMI ~ diet, data = Diets1))
Diets1.null <- do(1000) * MAD(mean(shuffle(BMI) ~ diet, data = Diets1))
head(Diets1.null, 3)
dotPlot(~ result, data = Diets1.null, n = 50, groups = (result >= 0.747))
prop(~ (result >= 0.747), data = Diets1.null)
| /inst/snippets/Exploration9.2.6.R | no_license | rpruim/ISIwithR | R | false | false | 251 | r | MAD(mean(BMI ~ diet, data = Diets1))
Diets1.null <- do(1000) * MAD(mean(shuffle(BMI) ~ diet, data = Diets1))
head(Diets1.null, 3)
dotPlot(~ result, data = Diets1.null, n = 50, groups = (result >= 0.747))
prop(~ (result >= 0.747), data = Diets1.null)
|
testlist <- list(bytes1 = integer(0), pmutation = 4.94065645841247e-323)
result <- do.call(mcga:::ByteCodeMutation,testlist)
str(result) | /mcga/inst/testfiles/ByteCodeMutation/libFuzzer_ByteCodeMutation/ByteCodeMutation_valgrind_files/1612886893-test.R | no_license | akhikolla/updatedatatype-list3 | R | false | false | 136 | r | testlist <- list(bytes1 = integer(0), pmutation = 4.94065645841247e-323)
result <- do.call(mcga:::ByteCodeMutation,testlist)
str(result) |
## Forest plot from odds/hazard ratios.
# xlabs = labels for the x axis (coordinates are flipped here so x is the vertical axis)
# title = plot title
# breaks = breaks in the y axis (correspond to spacing of the elements on the plot)
make_forest <- function (dataframe, xlabs, title, breaks) {
ymax <- max(dat... | /functions.R | no_license | zuz-bien/covid_aki | R | false | false | 5,775 | r | ## Forest plot from odds/hazard ratios.
# xlabs = labels for the x axis (coordinates are flipped here so x is the vertical axis)
# title = plot title
# breaks = breaks in the y axis (correspond to spacing of the elements on the plot)
make_forest <- function (dataframe, xlabs, title, breaks) {
ymax <- max(dat... |
\name{Bisect}
\alias{Bisect}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{
An implementation of the bisection algorithm for root finding
}
\description{
Most of the optimization is \code{Icens} have a one dimensional root-finding component. Since the quantities involved are generally restricted... | /man/Bisect.Rd | no_license | cran/glrt | R | false | false | 1,559 | rd | \name{Bisect}
\alias{Bisect}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{
An implementation of the bisection algorithm for root finding
}
\description{
Most of the optimization is \code{Icens} have a one dimensional root-finding component. Since the quantities involved are generally restricted... |
library(leaps)
library(glmnet)
library(randomForest)
fit_glm <- function (f, df, fold, k, type = NULL, use_saved = TRUE) {
modelname <- getModelName("glm", type)
model_path <- getModelPath(dataname, fold, k = k, modelname = modelname)
if (use_saved) {
if (file.exists(model_path)) {
glm_model <- read_m... | /src/subfuncs.R | no_license | stanford-policylab/simple-rules | R | false | false | 6,981 | r | library(leaps)
library(glmnet)
library(randomForest)
fit_glm <- function (f, df, fold, k, type = NULL, use_saved = TRUE) {
modelname <- getModelName("glm", type)
model_path <- getModelPath(dataname, fold, k = k, modelname = modelname)
if (use_saved) {
if (file.exists(model_path)) {
glm_model <- read_m... |
library(ape)
testtree <- read.tree("7597_0.txt")
unrooted_tr <- unroot(testtree)
write.tree(unrooted_tr, file="7597_0_unrooted.txt") | /codeml_files/newick_trees_processed/7597_0/rinput.R | no_license | DaniBoo/cyanobacteria_project | R | false | false | 135 | r | library(ape)
testtree <- read.tree("7597_0.txt")
unrooted_tr <- unroot(testtree)
write.tree(unrooted_tr, file="7597_0_unrooted.txt") |
# Load Data
NEI <- readRDS("summarySCC_PM25.rds")
SCC <- readRDS("Source_Classification_Code.rds")
# Plot
png("plot2.png")
NEI.Baltimore <- NEI[NEI$fips == "24510", ]
NEI.Baltimore.groups.sum <- with(NEI.Baltimore, tapply(Emissions, year, sum))
plot(NEI.Baltimore.groups.sum ~ names(NEI.Baltimore.groups.sum), type = ... | /plot2.R | no_license | sun33170161/ExData_Plotting2 | R | false | false | 423 | r | # Load Data
NEI <- readRDS("summarySCC_PM25.rds")
SCC <- readRDS("Source_Classification_Code.rds")
# Plot
png("plot2.png")
NEI.Baltimore <- NEI[NEI$fips == "24510", ]
NEI.Baltimore.groups.sum <- with(NEI.Baltimore, tapply(Emissions, year, sum))
plot(NEI.Baltimore.groups.sum ~ names(NEI.Baltimore.groups.sum), type = ... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data.R
\docType{data}
\name{data_dictionary_MFD}
\alias{data_dictionary_MFD}
\title{Moral Foundations Dictionary}
\format{An object of class \code{dictionary2} of length 11.}
\source{
\url{http://moralfoundations.org/othermaterials}
}
\usage{... | /man/data_dictionary_MFD.Rd | no_license | evanodell/quanteda.dictionaries | R | false | true | 1,120 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data.R
\docType{data}
\name{data_dictionary_MFD}
\alias{data_dictionary_MFD}
\title{Moral Foundations Dictionary}
\format{An object of class \code{dictionary2} of length 11.}
\source{
\url{http://moralfoundations.org/othermaterials}
}
\usage{... |
cl_trend_plot <- reactive({
validate(
need(!is.null(rawData_data$qw_data), "Click the 'Get QW Data' button")
)
plot_title <- paste(attr(qwData(), "siteInfo")[["station_nm"]],
attr(qwData(), "siteInfo")[["site_no"]], sep = "\n")
chl_plot <- trend_plot(qwData(), plot_title = plot_tit... | /inst/single_site/qw_plots.R | permissive | PatrickEslick/HASP | R | false | false | 5,086 | r | cl_trend_plot <- reactive({
validate(
need(!is.null(rawData_data$qw_data), "Click the 'Get QW Data' button")
)
plot_title <- paste(attr(qwData(), "siteInfo")[["station_nm"]],
attr(qwData(), "siteInfo")[["site_no"]], sep = "\n")
chl_plot <- trend_plot(qwData(), plot_title = plot_tit... |
#' Mutate a set of node attribute values
#' @description Within a graph's internal node data
#' frame (ndf), mutate numeric node attribute values
#' using one or more expressions. Optionally, one can
#' specify a different node attribute name and create
#' a new node attribute while retaining the original
#' node attri... | /R/mutate_node_attrs.R | no_license | applied-statistic-using-r/DiagrammeR | R | false | false | 6,967 | r | #' Mutate a set of node attribute values
#' @description Within a graph's internal node data
#' frame (ndf), mutate numeric node attribute values
#' using one or more expressions. Optionally, one can
#' specify a different node attribute name and create
#' a new node attribute while retaining the original
#' node attri... |
#filter out snp positions that have less than 4 reads to eliminate the structure I found in the data
#######
#snp<-read.table("/Users/wendy/Dropbox/Sol96_LogitRegression/Minor_Major_SNP_data.txt",header=T,sep=",")
geno.reads<-read.table("/Users/wendy/Dropbox/Sol96_LogitRegression/vcf_geno_depth_filter_200KSNP.txt",head... | /Regression_Scripts/LogisticRegression_Script.R | no_license | wendyvu216/Oil-Palm-Genetic-Diversity-and-Conservation-Program | R | false | false | 9,012 | r | #filter out snp positions that have less than 4 reads to eliminate the structure I found in the data
#######
#snp<-read.table("/Users/wendy/Dropbox/Sol96_LogitRegression/Minor_Major_SNP_data.txt",header=T,sep=",")
geno.reads<-read.table("/Users/wendy/Dropbox/Sol96_LogitRegression/vcf_geno_depth_filter_200KSNP.txt",head... |
list2matrix.bma = function(x, what, which.models=NULL) {
namesx = x$namesx
if (is.null(which.models)) which.models= 1:x$n.models
listobj = x[[what]][which.models]
which = x$which[which.models]
n.models = length(which.models)
p = length(namesx)
mat = matrix(0, nrow=n.models, ncol=p)
for (i in 1:n.mod... | /supplementaries/Mode Jumping MCMC/supplementary/examples/BAS archive/BAS/R/as.matrix.R | no_license | aliaksah/EMJMCMC2016 | R | false | false | 1,209 | r | list2matrix.bma = function(x, what, which.models=NULL) {
namesx = x$namesx
if (is.null(which.models)) which.models= 1:x$n.models
listobj = x[[what]][which.models]
which = x$which[which.models]
n.models = length(which.models)
p = length(namesx)
mat = matrix(0, nrow=n.models, ncol=p)
for (i in 1:n.mod... |
# server.R
library(dplyr)
library(shiny)
library(plotly)
# Read in data
source('./scripts/build_map.R')
df <- read.csv('./data/electoral_college.csv', stringsAsFactors = FALSE)
state_codes <- read.csv('./data/state_codes.csv', stringsAsFactors = FALSE)
# Join together state.codes and df
joined_data <- left_join(df, s... | /chapter-19-exercises/exercise-6/app_server.R | permissive | sumeetwaraich/book-exercises | R | false | false | 675 | r | # server.R
library(dplyr)
library(shiny)
library(plotly)
# Read in data
source('./scripts/build_map.R')
df <- read.csv('./data/electoral_college.csv', stringsAsFactors = FALSE)
state_codes <- read.csv('./data/state_codes.csv', stringsAsFactors = FALSE)
# Join together state.codes and df
joined_data <- left_join(df, s... |
# Race group differences in social dist variables in tempdiscsocialdist data set
# 7.14.20
# load required packages
library(here)
library(tidyverse)
library(rstatix)
# load source functions
# set hard-coded variables
# load data
if (sample == 1) {
dt <- read.csv(here::here("data", "tdsd_s1_data.csv"))
dd <- ... | /12_racial_differences.R | no_license | klsea/tempdiscsocialdist | R | false | false | 1,864 | r | # Race group differences in social dist variables in tempdiscsocialdist data set
# 7.14.20
# load required packages
library(here)
library(tidyverse)
library(rstatix)
# load source functions
# set hard-coded variables
# load data
if (sample == 1) {
dt <- read.csv(here::here("data", "tdsd_s1_data.csv"))
dd <- ... |
ReadIntercatch <- function(file){
IC <- read.table(file ,sep=",", col.names=as.character(1:33), fill=T)
HI <- subset(IC,X1=='HI')[,1:12]
names(HI) <- c("RecordType", "Country", "Year", "SeasonType", "Season", "Fleet",
"AreaType", "FishingArea", "DepthRange", "UnitEffort", "Effort",
... | /WKRDB-EST/Personal_folders/Hans/ReadIntercatch.R | no_license | ices-eg/WK_RDBES | R | false | false | 2,384 | r | ReadIntercatch <- function(file){
IC <- read.table(file ,sep=",", col.names=as.character(1:33), fill=T)
HI <- subset(IC,X1=='HI')[,1:12]
names(HI) <- c("RecordType", "Country", "Year", "SeasonType", "Season", "Fleet",
"AreaType", "FishingArea", "DepthRange", "UnitEffort", "Effort",
... |
### make plot for eaf reference ###
# load data
library(data.table)
setwd("/home/common/projects/ovine_selection/ovines_gwas_map/sheep_reference")
reference <- fread("sheep_reference.txt", head=T, stringsAsFactors=F, data.table=F)
# make table for plot
for_plot <- matrix(ncol=4, nrow=6)
for_plot[1,... | /04_do_plots_and_tables_for_reports/04b_make_plot_for_eaf_reference.R | no_license | Defrag1236/ovines_gwas_map | R | false | false | 1,485 | r | ### make plot for eaf reference ###
# load data
library(data.table)
setwd("/home/common/projects/ovine_selection/ovines_gwas_map/sheep_reference")
reference <- fread("sheep_reference.txt", head=T, stringsAsFactors=F, data.table=F)
# make table for plot
for_plot <- matrix(ncol=4, nrow=6)
for_plot[1,... |
\name{difshannonbio}
\alias{difshannonbio}
\title{ Empirical confidence interval of the bootstrap of the difference between two Shannon indices }
\description{
Computes the empirical confidence interval of the bootstrap of the difference between two Shannon indices
}
\usage{
difshannonbio(dat1, dat2, R = 1000, probs... | /pgirmess/man/difshannonbio.rd | no_license | pgiraudoux/pgirmess | R | false | false | 1,214 | rd | \name{difshannonbio}
\alias{difshannonbio}
\title{ Empirical confidence interval of the bootstrap of the difference between two Shannon indices }
\description{
Computes the empirical confidence interval of the bootstrap of the difference between two Shannon indices
}
\usage{
difshannonbio(dat1, dat2, R = 1000, probs... |
### R code from vignette source 'intro.Rnw'
### Encoding: UTF-8
###################################################
### code chunk number 1: intro.Rnw:26-27
###################################################
options(keep.source=TRUE)
###################################################
### code chunk numbe... | /REU R Workshop/REU R Workshop/W1_Intro/intro_v2.R | no_license | jwaring8/REU | R | false | false | 14,053 | r | ### R code from vignette source 'intro.Rnw'
### Encoding: UTF-8
###################################################
### code chunk number 1: intro.Rnw:26-27
###################################################
options(keep.source=TRUE)
###################################################
### code chunk numbe... |
sum_i <- function(v, i) {
if (i < 1) {
return(0)
}
j <- i
if (j > length(v)) {
j <- length(v)
}
sum(v[1]:v[j])
}
| /src/week_2/prob-1.R | permissive | haunt98/R-learn | R | false | false | 153 | r | sum_i <- function(v, i) {
if (i < 1) {
return(0)
}
j <- i
if (j > length(v)) {
j <- length(v)
}
sum(v[1]:v[j])
}
|
# R commands for working with Mr. Doyle's data
library(lubridate)
library(tidyverse)
x <- read_csv("spreadspoke_scores.csv", guess_max = 10000) %>%
mutate(schedule_week = recode(schedule_week,
"SuperBowl" = "Superbowl",
"WildCard" = "Wildcard")) %>%... | /kane.R | no_license | tianan2/Final-Project | R | false | false | 671 | r | # R commands for working with Mr. Doyle's data
library(lubridate)
library(tidyverse)
x <- read_csv("spreadspoke_scores.csv", guess_max = 10000) %>%
mutate(schedule_week = recode(schedule_week,
"SuperBowl" = "Superbowl",
"WildCard" = "Wildcard")) %>%... |
library(tidyverse)
range01 <- function(x){(x-min(x))/(max(x)-min(x))}
# alumnos -----------------------------------------------------------------
set.seed(1)
N <- 3000
x <- rnorm(N)
m <- -0.5555556
b <- 8.3333333
y <- m * x + b + rnorm(length(x))
plot(x, y, col="gray", pch=20, asp=1)
fit <- lm(y ~ x)
abline(fit, lty=... | /R/99-data.R | no_license | jbkunst/puc-introduccion-a-R | R | false | false | 2,424 | r | library(tidyverse)
range01 <- function(x){(x-min(x))/(max(x)-min(x))}
# alumnos -----------------------------------------------------------------
set.seed(1)
N <- 3000
x <- rnorm(N)
m <- -0.5555556
b <- 8.3333333
y <- m * x + b + rnorm(length(x))
plot(x, y, col="gray", pch=20, asp=1)
fit <- lm(y ~ x)
abline(fit, lty=... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/binCounts.R
\name{binCounts}
\alias{binCounts}
\title{Fast element counting in non-overlapping bins}
\usage{
binCounts(x, idxs = NULL, bx, right = FALSE, ...)
}
\arguments{
\item{x}{A \code{\link[base]{numeric}} \code{\link[base]{vector}} of ... | /man/binCounts.Rd | no_license | HenrikBengtsson/matrixStats | R | false | true | 1,953 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/binCounts.R
\name{binCounts}
\alias{binCounts}
\title{Fast element counting in non-overlapping bins}
\usage{
binCounts(x, idxs = NULL, bx, right = FALSE, ...)
}
\arguments{
\item{x}{A \code{\link[base]{numeric}} \code{\link[base]{vector}} of ... |
## Put comments here that give an overall description of what your
## functions do
## Write a short comment describing this function
## This function creates a special "matrix" object that can cache its inverse.
## x is the input matrix, defaulf value is matrix().
## set() can change the input matrix.
## get() can get... | /cachematrix.R | no_license | hanruyu/ProgrammingAssignment2 | R | false | false | 1,305 | r | ## Put comments here that give an overall description of what your
## functions do
## Write a short comment describing this function
## This function creates a special "matrix" object that can cache its inverse.
## x is the input matrix, defaulf value is matrix().
## set() can change the input matrix.
## get() can get... |
#
# Utilities needed for preprocessing & analysing NCDC weather dataset
# (Can be regularly updated)
#
# String for latitude-longitude projection (can be passed into CRS)
g_latlongProj_str <- "+proj=longlat +datum=WGS84"
# Function to remove temporary objects
## Convention: name starting with 'c_'
rmMyTemp_fn <- func... | /000_utils.R | no_license | ybaek/undergrad | R | false | false | 6,200 | r | #
# Utilities needed for preprocessing & analysing NCDC weather dataset
# (Can be regularly updated)
#
# String for latitude-longitude projection (can be passed into CRS)
g_latlongProj_str <- "+proj=longlat +datum=WGS84"
# Function to remove temporary objects
## Convention: name starting with 'c_'
rmMyTemp_fn <- func... |
\name{predict.mixGGM}
\alias{predict.mixGGM}
\title{Cluster prediction by Mixture of Gaussian Graphical Models}
\description{Cluster prediction for multivariate observations based on Mixture of Gaussian Graphical Models estimated by \code{\link{mixGGM}}.}
\usage{
\method{predict}{mixGGM}(object, newdata, \dots)
}
\... | /man/predict.mixGGM.Rd | no_license | lkampoli/mixggm | R | false | false | 1,026 | rd | \name{predict.mixGGM}
\alias{predict.mixGGM}
\title{Cluster prediction by Mixture of Gaussian Graphical Models}
\description{Cluster prediction for multivariate observations based on Mixture of Gaussian Graphical Models estimated by \code{\link{mixGGM}}.}
\usage{
\method{predict}{mixGGM}(object, newdata, \dots)
}
\... |
library("dplyr")
library("tidyverse")
library("lubridate")
rm(list=ls())
setwd(here::here("output", "measures"))
df1 <- readRDS('ab_type_pre.rds')
df2 <- readRDS('ab_type_2019.rds')
df3 <- readRDS('ab_type_2020.rds')
df4 <- readRDS('ab_type_2021.rds')
df5 <- readRDS('ab_type_2022.rds')
df2 <- bind_rows(df2)
df3 <- bi... | /analysis/plot/amoxicillin_percentage_by_age.R | permissive | opensafely/amr-uom-brit | R | false | false | 4,160 | r | library("dplyr")
library("tidyverse")
library("lubridate")
rm(list=ls())
setwd(here::here("output", "measures"))
df1 <- readRDS('ab_type_pre.rds')
df2 <- readRDS('ab_type_2019.rds')
df3 <- readRDS('ab_type_2020.rds')
df4 <- readRDS('ab_type_2021.rds')
df5 <- readRDS('ab_type_2022.rds')
df2 <- bind_rows(df2)
df3 <- bi... |
library(yorkr)
### Name: teamBowlersWicketRunsOppnAllMatches
### Title: Team bowlers wicket runs against an opposition in all matches
### Aliases: teamBowlersWicketRunsOppnAllMatches
### ** Examples
## Not run:
##D # Get all matches between India and Australia
##D matches <- getAllMatchesBetweenTeams("Australia","... | /data/genthat_extracted_code/yorkr/examples/teamBowlersWicketRunsOppnAllMatches.Rd.R | no_license | surayaaramli/typeRrh | R | false | false | 520 | r | library(yorkr)
### Name: teamBowlersWicketRunsOppnAllMatches
### Title: Team bowlers wicket runs against an opposition in all matches
### Aliases: teamBowlersWicketRunsOppnAllMatches
### ** Examples
## Not run:
##D # Get all matches between India and Australia
##D matches <- getAllMatchesBetweenTeams("Australia","... |
JACCARD.F <- function(partHard, partFuzzy, t_norm = c("minimum","product"))
{
if (missing(partHard))
stop("The hard partitions partHard must be given")
if (missing(partFuzzy))
stop("The fuzzy partitions partFuzzy must be given")
if (is.null(partHard))
stop("The hard partitions partHard is empty")
... | /R/JACCARD.F.R | no_license | bratnick/fclust | R | false | false | 763 | r | JACCARD.F <- function(partHard, partFuzzy, t_norm = c("minimum","product"))
{
if (missing(partHard))
stop("The hard partitions partHard must be given")
if (missing(partFuzzy))
stop("The fuzzy partitions partFuzzy must be given")
if (is.null(partHard))
stop("The hard partitions partHard is empty")
... |
library(xts)
library(lubridate)
library(raster)
library(ncdf4)
pct09=read.csv("WT_data/pct09.cla",sep="",header=F)
san09=read.csv("WT_data/san09_500HGT.cla",sep="",header=F)
WTS=data.frame(WT_pct09=as.factor(pct09$V5),
WT_san09=as.factor(san09$V5[1:13545])
)
rownames(WTS)=ISOdate(pct09... | /WT_init_proc.r | no_license | CLIMAIBIMETCNR/seasonal_forecast | R | false | false | 7,029 | r | library(xts)
library(lubridate)
library(raster)
library(ncdf4)
pct09=read.csv("WT_data/pct09.cla",sep="",header=F)
san09=read.csv("WT_data/san09_500HGT.cla",sep="",header=F)
WTS=data.frame(WT_pct09=as.factor(pct09$V5),
WT_san09=as.factor(san09$V5[1:13545])
)
rownames(WTS)=ISOdate(pct09... |
test_that("Hemis can be shifted apart using rglactions for non-overlapping rendering.", {
testthat::skip_on_cran(); # CRAN maintainers asked me to reduce test time on CRAN by disabling unit tests.
skip_if(tests_running_on_cran_under_macos(), message = "Skipping on CRAN under MacOS, required test data cannot be... | /tests/testthat/test-rglactions.R | permissive | adigherman/fsbrain | R | false | false | 1,220 | r |
test_that("Hemis can be shifted apart using rglactions for non-overlapping rendering.", {
testthat::skip_on_cran(); # CRAN maintainers asked me to reduce test time on CRAN by disabling unit tests.
skip_if(tests_running_on_cran_under_macos(), message = "Skipping on CRAN under MacOS, required test data cannot be... |
# Generated by using Rcpp::compileAttributes() -> do not edit by hand
# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
#' Sample from the Dirichlet distribution
#'
#' @param n number ofsample
#' @param a vector of weights
#'
#' @export
rdirichlet <- function(n, a) {
.Call(`_dist_rdirichlet`, n, a)
}
#' Sam... | /R/RcppExports.R | no_license | mkomod/dist | R | false | false | 1,428 | r | # Generated by using Rcpp::compileAttributes() -> do not edit by hand
# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
#' Sample from the Dirichlet distribution
#'
#' @param n number ofsample
#' @param a vector of weights
#'
#' @export
rdirichlet <- function(n, a) {
.Call(`_dist_rdirichlet`, n, a)
}
#' Sam... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/drugSetEnrichment.R
\name{matchStatsWithDrugSetsID}
\alias{matchStatsWithDrugSetsID}
\title{Match identifiers between data and drug sets}
\usage{
matchStatsWithDrugSetsID(
sets,
stats,
col = "values",
keyColSets = NULL,
keyColStats ... | /man/matchStatsWithDrugSetsID.Rd | permissive | nuno-agostinho/cTRAP | R | false | true | 1,435 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/drugSetEnrichment.R
\name{matchStatsWithDrugSetsID}
\alias{matchStatsWithDrugSetsID}
\title{Match identifiers between data and drug sets}
\usage{
matchStatsWithDrugSetsID(
sets,
stats,
col = "values",
keyColSets = NULL,
keyColStats ... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/qvcalc.PlackettLuce.R
\name{qvcalc.PlackettLuce}
\alias{qvcalc.PlackettLuce}
\title{Quasi Variances for Model Coefficients}
\usage{
\method{qvcalc}{PlackettLuce}(object, ref = 1, ...)
}
\arguments{
\item{object}{a \code{"PlackettLuce"} object... | /man/qvcalc.PlackettLuce.Rd | no_license | anhnguyendepocen/PlackettLuce | R | false | true | 3,623 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/qvcalc.PlackettLuce.R
\name{qvcalc.PlackettLuce}
\alias{qvcalc.PlackettLuce}
\title{Quasi Variances for Model Coefficients}
\usage{
\method{qvcalc}{PlackettLuce}(object, ref = 1, ...)
}
\arguments{
\item{object}{a \code{"PlackettLuce"} object... |
# incluir imagenes en ggplots:
# https://drmowinckels.io/blog/adding-external-images-to-plots/
# ggimage
library(tidyverse)
library(ggplot2)
library(jpeg)
library(grid)
library(ggdark)
library(showtext)
theme_set(dark_theme_grey())
metallica <- readRDS("metallica.rds")
# does not work!
# mutate(track_name = fct_ino... | /visualize.R | no_license | rlabuonora/metallica_viz | R | false | false | 4,862 | r | # incluir imagenes en ggplots:
# https://drmowinckels.io/blog/adding-external-images-to-plots/
# ggimage
library(tidyverse)
library(ggplot2)
library(jpeg)
library(grid)
library(ggdark)
library(showtext)
theme_set(dark_theme_grey())
metallica <- readRDS("metallica.rds")
# does not work!
# mutate(track_name = fct_ino... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ogbox.R
\name{roxygenTabular}
\alias{roxygenTabular}
\title{Roxygen table maker}
\usage{
roxygenTabular(df, col.names = TRUE, ...)
}
\arguments{
\item{df}{data.frame}
\item{col.names}{logica. If colnames should be included}
\item{...}{varia... | /man/roxygenTabular.Rd | permissive | oganm/ogbox | R | false | true | 384 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ogbox.R
\name{roxygenTabular}
\alias{roxygenTabular}
\title{Roxygen table maker}
\usage{
roxygenTabular(df, col.names = TRUE, ...)
}
\arguments{
\item{df}{data.frame}
\item{col.names}{logica. If colnames should be included}
\item{...}{varia... |
#' The base Choropleth object.
#' @importFrom R6 R6Class
#' @importFrom scales comma
#' @importFrom ggplot2 scale_color_continuous coord_quickmap
#' @export
Choropleth = R6Class("Choropleth",
public = list(
# the key objects for this class
user.df = NULL, # input from user
ma... | /R/choropleth.R | no_license | cardiomoon/choroplethr | R | false | false | 9,370 | r | #' The base Choropleth object.
#' @importFrom R6 R6Class
#' @importFrom scales comma
#' @importFrom ggplot2 scale_color_continuous coord_quickmap
#' @export
Choropleth = R6Class("Choropleth",
public = list(
# the key objects for this class
user.df = NULL, # input from user
ma... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/discrim_flexible.R
\name{discrim_flexible}
\alias{discrim_flexible}
\title{Flexible discriminant analysis}
\usage{
discrim_flexible(
mode = "classification",
num_terms = NULL,
prod_degree = NULL,
prune_method = NULL,
engine = "earth... | /man/discrim_flexible.Rd | permissive | tidymodels/parsnip | R | false | true | 2,265 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/discrim_flexible.R
\name{discrim_flexible}
\alias{discrim_flexible}
\title{Flexible discriminant analysis}
\usage{
discrim_flexible(
mode = "classification",
num_terms = NULL,
prod_degree = NULL,
prune_method = NULL,
engine = "earth... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/plot_fns.R
\name{plot.corRes}
\alias{plot.corRes}
\title{Plot corRes Object}
\usage{
\method{plot}{corRes}(
corRes_obj,
omicsData = NULL,
order_by = NULL,
colorbar_lim = c(NA, NA),
x_text = TRUE,
y_text = TRUE,
interactive = FAL... | /man/plot-corRes.Rd | permissive | clabornd/pmartR | R | false | true | 3,441 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/plot_fns.R
\name{plot.corRes}
\alias{plot.corRes}
\title{Plot corRes Object}
\usage{
\method{plot}{corRes}(
corRes_obj,
omicsData = NULL,
order_by = NULL,
colorbar_lim = c(NA, NA),
x_text = TRUE,
y_text = TRUE,
interactive = FAL... |
(function(e,t){function u(e){var t=o[e]={},n,r;e=e.split(/\s+/);for(n=0,r=e.length;n<r;n++){t[e[n]]=true}return t}function c(e,n,r){if(r===t&&e.nodeType===1){var i="data-"+n.replace(l,"-$1").toLowerCase();r=e.getAttribute(i);if(typeof r==="string"){try{r=r==="true"?true:r==="false"?false:r==="null"?null:s.isNumeric(r)?... | /Css/jquery_002.js | no_license | Aadil25/mvcphp | R | true | true | 324,398 | js | (function(e,t){function u(e){var t=o[e]={},n,r;e=e.split(/\s+/);for(n=0,r=e.length;n<r;n++){t[e[n]]=true}return t}function c(e,n,r){if(r===t&&e.nodeType===1){var i="data-"+n.replace(l,"-$1").toLowerCase();r=e.getAttribute(i);if(typeof r==="string"){try{r=r==="true"?true:r==="false"?false:r==="null"?null:s.isNumeric(r)?... |
% Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/mxnet_generated.R
\name{mx.symbol.LinearRegressionOutput}
\alias{mx.symbol.LinearRegressionOutput}
\title{Use linear regression for final output, this is used on final output of a net.}
\usage{
mx.symbol.LinearRegressionOutput(...)
}
... | /R-package/man/mx.symbol.LinearRegressionOutput.Rd | permissive | XinliangZhu/mxnet | R | false | false | 617 | rd | % Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/mxnet_generated.R
\name{mx.symbol.LinearRegressionOutput}
\alias{mx.symbol.LinearRegressionOutput}
\title{Use linear regression for final output, this is used on final output of a net.}
\usage{
mx.symbol.LinearRegressionOutput(...)
}
... |
## Put comments here that give an overall description of what your
## functions do
## This function creates a special "matrix" object that can cache
## its inverse.
makeCacheMatrix <- function(x = matrix()) {
inv <- NULL
set <- function(y) {
x <<- y
inv <<- NULL
}
get <- function() x
... | /cachematrix.R | no_license | LouayMalatili/ProgrammingAssignment2 | R | false | false | 1,017 | r | ## Put comments here that give an overall description of what your
## functions do
## This function creates a special "matrix" object that can cache
## its inverse.
makeCacheMatrix <- function(x = matrix()) {
inv <- NULL
set <- function(y) {
x <<- y
inv <<- NULL
}
get <- function() x
... |
context("sampler2_cpp")
test_that("sampler_cpp2", {
set.seed(4711)
N <- 1000
D <- 17
V <- 31
K <- 10
P <- 3
state_df <- data.frame(doc = sample(1:D, size = N, replace = TRUE),
type = sample(1:V, size = N, replace = TRUE),
topic = sample(1:K, size = N, rep... | /tests/testthat/test-sampler2_cpp.R | no_license | MansMeg/PerspectiveTopicModel | R | false | false | 3,598 | r | context("sampler2_cpp")
test_that("sampler_cpp2", {
set.seed(4711)
N <- 1000
D <- 17
V <- 31
K <- 10
P <- 3
state_df <- data.frame(doc = sample(1:D, size = N, replace = TRUE),
type = sample(1:V, size = N, replace = TRUE),
topic = sample(1:K, size = N, rep... |
library(bigsnpr)
gen <- function(n, m) {
I <- 1:m
p <- I / (2 * m + 1)
mat <- outer(I, I, FUN = function(i, j) {
1 / (abs(i - j) + 1)
})
bindata::rmvbin(n, p, bincorr = mat) +
bindata::rmvbin(n, p, bincorr = mat)
}
N <- 200
M <- 500
fake <- snp_fake(N, M)
G <- fake$genotypes
G[] <- rep(gen(N, M /... | /data-raw/example-missing.R | no_license | privefl/bigsnpr | R | false | false | 673 | r | library(bigsnpr)
gen <- function(n, m) {
I <- 1:m
p <- I / (2 * m + 1)
mat <- outer(I, I, FUN = function(i, j) {
1 / (abs(i - j) + 1)
})
bindata::rmvbin(n, p, bincorr = mat) +
bindata::rmvbin(n, p, bincorr = mat)
}
N <- 200
M <- 500
fake <- snp_fake(N, M)
G <- fake$genotypes
G[] <- rep(gen(N, M /... |
# ------------------------------------------------------------------
# This material is distributed under the GNU General Public License
# Version 2. You may review the terms of this license at
# http://www.gnu.org/licenses/gpl-2.0.html
#
# Copyright (c) 2012-2013, Michel Lang, Helena Kotthaus,
# TU Dortmund University... | /MachineLearningAlg/main_functions/lm.R | no_license | allr/benchR | R | false | false | 1,139 | r | # ------------------------------------------------------------------
# This material is distributed under the GNU General Public License
# Version 2. You may review the terms of this license at
# http://www.gnu.org/licenses/gpl-2.0.html
#
# Copyright (c) 2012-2013, Michel Lang, Helena Kotthaus,
# TU Dortmund University... |
#####################
# Oct 26, 2018
# Making sure that I can clone and comit R scripts with Git via the terminal
# doing this as a test
######################
setwd("Z:/GitHub/hello-world")
main.dir<-"Z:/GitHub/"
# in terminal:
git clone https://github.com/StewartResearch/hello-world.git
# now make some changes
# g... | /Hello-World.R | no_license | StewartResearch/hello-world | R | false | false | 2,705 | r | #####################
# Oct 26, 2018
# Making sure that I can clone and comit R scripts with Git via the terminal
# doing this as a test
######################
setwd("Z:/GitHub/hello-world")
main.dir<-"Z:/GitHub/"
# in terminal:
git clone https://github.com/StewartResearch/hello-world.git
# now make some changes
# g... |
library(testthat)
test_check("gmo")
| /tests/testthat.R | permissive | jan-glx/gmo | R | false | false | 36 | r | library(testthat)
test_check("gmo")
|
# Example of Machine Learning algorithm using "Decision trees"
# with R's carot package.
# MAIN IDEAS
#
# *Iteratively split variables into groups
# *Eval homogeneity with each group
# *Split again if necessary
# BASIC ALGORITHM
#
# 1.- Start with all variables in one group
# 2.- Find variable that best sep... | /8_machine/decision_trees.R | no_license | chuymtz/datasciencecoursera | R | false | false | 1,873 | r | # Example of Machine Learning algorithm using "Decision trees"
# with R's carot package.
# MAIN IDEAS
#
# *Iteratively split variables into groups
# *Eval homogeneity with each group
# *Split again if necessary
# BASIC ALGORITHM
#
# 1.- Start with all variables in one group
# 2.- Find variable that best sep... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/sagemaker_operations.R
\name{sagemaker_create_experiment}
\alias{sagemaker_create_experiment}
\title{Creates an Amazon SageMaker \emph{experiment}}
\usage{
sagemaker_create_experiment(ExperimentName, DisplayName, Description,
Tags)
}
\argum... | /cran/paws.machine.learning/man/sagemaker_create_experiment.Rd | permissive | johnnytommy/paws | R | false | true | 2,407 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/sagemaker_operations.R
\name{sagemaker_create_experiment}
\alias{sagemaker_create_experiment}
\title{Creates an Amazon SageMaker \emph{experiment}}
\usage{
sagemaker_create_experiment(ExperimentName, DisplayName, Description,
Tags)
}
\argum... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/getAllAreaData.R
\name{getAllAreaData}
\alias{getAllAreaData}
\title{Get All Area Data}
\usage{
getAllAreaData()
}
\description{
Description
}
| /man/getAllAreaData.Rd | no_license | SWS-Methodology/faoswsSeed | R | false | true | 222 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/getAllAreaData.R
\name{getAllAreaData}
\alias{getAllAreaData}
\title{Get All Area Data}
\usage{
getAllAreaData()
}
\description{
Description
}
|
% Generated by roxygen2 (4.0.1): do not edit by hand
\name{NetworkModel}
\alias{NetworkModel}
\title{Instantiates an object of class NetworkModel}
\usage{
NetworkModel(model_params = set_model_param())
}
\arguments{
\item{model_params}{[list; DEFAULT = \code{\link{set_model_param}}()] :: Model parameters}
}
\value{
[Ne... | /netcompLib/man/NetworkModel.Rd | no_license | minghao2016/netcompLib | R | false | false | 450 | rd | % Generated by roxygen2 (4.0.1): do not edit by hand
\name{NetworkModel}
\alias{NetworkModel}
\title{Instantiates an object of class NetworkModel}
\usage{
NetworkModel(model_params = set_model_param())
}
\arguments{
\item{model_params}{[list; DEFAULT = \code{\link{set_model_param}}()] :: Model parameters}
}
\value{
[Ne... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/get_more.R
\name{get_primary}
\alias{get_primary}
\title{Primary room size (primærrom)}
\usage{
get_primary(x)
}
\arguments{
\item{x}{HTML code}
}
\description{
Primary room size (primærrom)
}
| /man/get_primary.Rd | no_license | ybkamaleri/boligfinn | R | false | true | 273 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/get_more.R
\name{get_primary}
\alias{get_primary}
\title{Primary room size (primærrom)}
\usage{
get_primary(x)
}
\arguments{
\item{x}{HTML code}
}
\description{
Primary room size (primærrom)
}
|
# FUNCTIONS IN THIS FILE:
# improve
# isUnimodal
# isMonotoneR
# isMonotoneL
# isBoundedL
# isBoundedR
#*****************************************************************************************
#*** improve *****************************************************************************
#***... | /R/sharpenedKDE.R | no_license | cran/scdensity | R | false | false | 14,730 | r | # FUNCTIONS IN THIS FILE:
# improve
# isUnimodal
# isMonotoneR
# isMonotoneL
# isBoundedL
# isBoundedR
#*****************************************************************************************
#*** improve *****************************************************************************
#***... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/sdwis_enforcement_action.R
\name{sdwis_enforcement_action}
\alias{sdwis_enforcement_action}
\title{Retrieve enforcement action data from sdwis database}
\usage{
sdwis_enforcement_action(PWSID = NULL, ENFORCEMENT_ID = NULL,
ORIGINATOR_CODE =... | /man/sdwis_enforcement_action.Rd | no_license | markwh/envirofacts | R | false | true | 944 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/sdwis_enforcement_action.R
\name{sdwis_enforcement_action}
\alias{sdwis_enforcement_action}
\title{Retrieve enforcement action data from sdwis database}
\usage{
sdwis_enforcement_action(PWSID = NULL, ENFORCEMENT_ID = NULL,
ORIGINATOR_CODE =... |
#' Calculate amount excreted (typically in urine or feces)
#'
#' @param conc The concentration in the sample
#' @param volume The volume (or mass) of the sample
#' @param check Should the concentration and volume data be checked?
#' @return The amount excreted during the interval
#' @details The units for the concentr... | /R/pk.calc.urine.R | no_license | ksl31/pknca | R | false | false | 2,844 | r | #' Calculate amount excreted (typically in urine or feces)
#'
#' @param conc The concentration in the sample
#' @param volume The volume (or mass) of the sample
#' @param check Should the concentration and volume data be checked?
#' @return The amount excreted during the interval
#' @details The units for the concentr... |
#Importing Data
train <- read.csv(file.choose(), na.strings = c(""," ",NA))
#Finding missing values
sort(colSums(is.na(train)), decreasing = TRUE)
#Data Exploration
library(ggplot2)
library(dplyr)
data <- train
# Total Number of Passengers: 891
NROW(data$PassengerId)
#Total Number of Passengers - Dead:549 Live:342
t... | /Titanic.R | no_license | Hemanthkaruturi/Titanic | R | false | false | 8,910 | r | #Importing Data
train <- read.csv(file.choose(), na.strings = c(""," ",NA))
#Finding missing values
sort(colSums(is.na(train)), decreasing = TRUE)
#Data Exploration
library(ggplot2)
library(dplyr)
data <- train
# Total Number of Passengers: 891
NROW(data$PassengerId)
#Total Number of Passengers - Dead:549 Live:342
t... |
#Load required packages
library(forecast)
library(xts)
library(lubridate)
seaice<-read.csv("seaice.csv",header = TRUE,stringsAsFactors = FALSE)
str(seaice)
north_hemi<-seaice[seaice$hemisphere=='north',]
seaice$Date<-as.Date(paste(seaice$Year,seaice$Month,seaice$Day,sep = '-'))
#create initial time series object
... | /time_series_pred.R | no_license | bhisecj/Time_Series_Prediction | R | false | false | 1,680 | r | #Load required packages
library(forecast)
library(xts)
library(lubridate)
seaice<-read.csv("seaice.csv",header = TRUE,stringsAsFactors = FALSE)
str(seaice)
north_hemi<-seaice[seaice$hemisphere=='north',]
seaice$Date<-as.Date(paste(seaice$Year,seaice$Month,seaice$Day,sep = '-'))
#create initial time series object
... |
timestamp <- Sys.time()
library(caret)
library(plyr)
library(recipes)
library(dplyr)
model <- "Rborist"
## In case the package or one of its dependencies uses random numbers
## on startup so we'll pre-load the required libraries:
for(i in getModelInfo(model)[[1]]$library)
do.call("require", list(package = i))
##... | /RegressionTests/Code/Rborist.R | no_license | Weekend-Warrior/caret | R | false | false | 8,069 | r | timestamp <- Sys.time()
library(caret)
library(plyr)
library(recipes)
library(dplyr)
model <- "Rborist"
## In case the package or one of its dependencies uses random numbers
## on startup so we'll pre-load the required libraries:
for(i in getModelInfo(model)[[1]]$library)
do.call("require", list(package = i))
##... |
# #The goal of this script is to run enrichment analysi on the leading edges of different clusters
listOfFiles = list.files("03_extractedData/190321_KO-RNAseq/GSEA/leadingEdges/")
#Load transcriptome and keep only genes expressed in at least one sample.
expressedTranscriptome = read.table("01_rawData/190321_KO-RNAseq... | /05_scripts/190321_KO-RNAseq/190408_runClusterProfilerOnLeadingEdges.R | no_license | edatorre/2020_TorreEtAl_data | R | false | false | 2,441 | r | # #The goal of this script is to run enrichment analysi on the leading edges of different clusters
listOfFiles = list.files("03_extractedData/190321_KO-RNAseq/GSEA/leadingEdges/")
#Load transcriptome and keep only genes expressed in at least one sample.
expressedTranscriptome = read.table("01_rawData/190321_KO-RNAseq... |
% Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/gaussAlgebra.R
\name{linear.gAlg}
\alias{linear.gAlg}
\title{Generates a linear gAlg function}
\usage{
linear.gAlg(k, d = 1)
}
\arguments{
\item{k}{Index of the dimension in which the function is linear}
\item{d}{Dimension in which t... | /man/linear.gAlg.Rd | no_license | kmarchlewski/gaussAlgebra | R | false | false | 416 | rd | % Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/gaussAlgebra.R
\name{linear.gAlg}
\alias{linear.gAlg}
\title{Generates a linear gAlg function}
\usage{
linear.gAlg(k, d = 1)
}
\arguments{
\item{k}{Index of the dimension in which the function is linear}
\item{d}{Dimension in which t... |
# simulate gaussian rv with correlation 0.5
simulate_x = function(){
cov = matrix(c(1,0.5,0.5,1),nrow=2)
A = t(chol(cov))
e = matrix(rnorm(2),nrow=2)
x = A %*% rnorm(2)
x
}
simulate_path=function(){
T = 365-1
x1 = vector();x2 = vector()
for(i in 1:T){
x = simulate_x()
x1 = c(x1,x[1])
x2 = c(x2,x[2])
}... | /StochasticProcess/question4.R | no_license | fushuyue/Financial_Computing | R | false | false | 1,371 | r | # simulate gaussian rv with correlation 0.5
simulate_x = function(){
cov = matrix(c(1,0.5,0.5,1),nrow=2)
A = t(chol(cov))
e = matrix(rnorm(2),nrow=2)
x = A %*% rnorm(2)
x
}
simulate_path=function(){
T = 365-1
x1 = vector();x2 = vector()
for(i in 1:T){
x = simulate_x()
x1 = c(x1,x[1])
x2 = c(x2,x[2])
}... |
\name{PKMW}
\alias{PKMW}
\title{Presmoothed Kaplan-Meier weights}
\description{This function returns a vector with the presmoothed Kaplan-Meier weights.}
\usage{
PKMW(time, status)
}
\arguments{
\item{time}{ Survival time of the process.}
\item{status}{Censoring indicator of the survival time of the process; 0 if... | /man/PKMW.Rd | no_license | sestelo/survidm | R | false | false | 1,095 | rd | \name{PKMW}
\alias{PKMW}
\title{Presmoothed Kaplan-Meier weights}
\description{This function returns a vector with the presmoothed Kaplan-Meier weights.}
\usage{
PKMW(time, status)
}
\arguments{
\item{time}{ Survival time of the process.}
\item{status}{Censoring indicator of the survival time of the process; 0 if... |
# How have emissions from
# motor vehicle sources changed from 1999–2008 in Baltimore City?
# Read the data
setwd("~/40 L&G/Coursera/ExDataAnalysis/Project2")
if (!exists("NEI")) {
# Emissions Data
NEI <- readRDS(paste0(getwd() ,"/Data/summarySCC_PM25.rds"))
}
if (!exists("SCC")) {
# Source Cl... | /plot6.R | no_license | Kbushu/Pollution | R | false | false | 1,342 | r | # How have emissions from
# motor vehicle sources changed from 1999–2008 in Baltimore City?
# Read the data
setwd("~/40 L&G/Coursera/ExDataAnalysis/Project2")
if (!exists("NEI")) {
# Emissions Data
NEI <- readRDS(paste0(getwd() ,"/Data/summarySCC_PM25.rds"))
}
if (!exists("SCC")) {
# Source Cl... |
# SVR
# Importing the dataset
dataset = read.csv('Position_Salaries.csv')
dataset = dataset[2:3]
# Splitting the dataset into the Training set and Test set
# # install.packages('caTools')
# library(caTools)
# set.seed(123)
# split = sample.split(dataset$Salary, SplitRatio = 2/3)
# training_set = subset(dataset, split... | /Machine Learning A-Z- Udemy/Part 2 - Regression/Section 7 - Support Vector Regression (SVR)/svr.R | no_license | 95anantsingh/Udemy-ML-A-Z | R | false | false | 1,586 | r | # SVR
# Importing the dataset
dataset = read.csv('Position_Salaries.csv')
dataset = dataset[2:3]
# Splitting the dataset into the Training set and Test set
# # install.packages('caTools')
# library(caTools)
# set.seed(123)
# split = sample.split(dataset$Salary, SplitRatio = 2/3)
# training_set = subset(dataset, split... |
#Sam Smedinghoff
#7/27/18
#Week 3 - Lab 3
library(SDSFoundations)
post <- PostSurvey
#Question 1
post$hw_hours_diff <- post$hw_hours_HS - post$hw_hours_college
hist(post$hw_hours_diff)
t.test(post$hw_hours_HS,post$hw_hours_college,paired=T,alternative='less')
#Question 2
sleep_greek <- post$sleep_Sat[po... | /FDA2/lab03.R | no_license | smeds1/Learning | R | false | false | 490 | r | #Sam Smedinghoff
#7/27/18
#Week 3 - Lab 3
library(SDSFoundations)
post <- PostSurvey
#Question 1
post$hw_hours_diff <- post$hw_hours_HS - post$hw_hours_college
hist(post$hw_hours_diff)
t.test(post$hw_hours_HS,post$hw_hours_college,paired=T,alternative='less')
#Question 2
sleep_greek <- post$sleep_Sat[po... |
checkInputVars <- function (normalizescheme, normalclasswise, replaceNA, replaceclasswise, orglabellvls) {
errors <- vector()
if (!any(normalizescheme == c('none','ztransform', 'iqr', 'sumone'))| length(normalizescheme) != 1) {
errors[length(errors) + 1] <- 3
}
if ((!any(normalclasswise == orglabel... | /R/check.r | no_license | MATA62N/LVQTools | R | false | false | 16,076 | r | checkInputVars <- function (normalizescheme, normalclasswise, replaceNA, replaceclasswise, orglabellvls) {
errors <- vector()
if (!any(normalizescheme == c('none','ztransform', 'iqr', 'sumone'))| length(normalizescheme) != 1) {
errors[length(errors) + 1] <- 3
}
if ((!any(normalclasswise == orglabel... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/profile_functions.R
\name{edit_profile}
\alias{edit_profile}
\title{Edit your profile function}
\usage{
edit_profile()
}
\description{
Edit your profile function
}
| /man/edit_profile.Rd | no_license | Giappo/jap | R | false | true | 242 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/profile_functions.R
\name{edit_profile}
\alias{edit_profile}
\title{Edit your profile function}
\usage{
edit_profile()
}
\description{
Edit your profile function
}
|
#' Generate a PDF field guide using the ALA's field guide generator
#'
#' @references \url{http://fieldguide.ala.org.au/}
#' @param guids character: vector of GUIDs
#' @param title string: title to use in the field guide PDF
#' @param filename string: filename for the PDF document
#' @param overwrite logical: overwri... | /R/fieldguide.R | no_license | fozy81/NBN4R | R | false | false | 823 | r | #' Generate a PDF field guide using the ALA's field guide generator
#'
#' @references \url{http://fieldguide.ala.org.au/}
#' @param guids character: vector of GUIDs
#' @param title string: title to use in the field guide PDF
#' @param filename string: filename for the PDF document
#' @param overwrite logical: overwri... |
stsp<-function(data,Ntimesteps,Q)
# Function to compute the space time separation for a data set
# S=stsp(data,Ntimesteps,Q)
# data - data set
# Ntimesteps - number of time lags
# Q a row vector of quartiles, e.g. [25 50 95] to get 25th, median
# and 95th seperations
{
N<-length(data)
S=vector()
for (i in 1:Ntimesteps)... | /Hailiang-Du/stsp.R | no_license | JUJUup/SummerSchool2021_MLAS | R | false | false | 404 | r | stsp<-function(data,Ntimesteps,Q)
# Function to compute the space time separation for a data set
# S=stsp(data,Ntimesteps,Q)
# data - data set
# Ntimesteps - number of time lags
# Q a row vector of quartiles, e.g. [25 50 95] to get 25th, median
# and 95th seperations
{
N<-length(data)
S=vector()
for (i in 1:Ntimesteps)... |
### R code from vignette source 'caper.rnw'
### Encoding: UTF-8
###################################################
### code chunk number 1: setup
###################################################
library(caper)
## whilst code is being tested, load most recent versions from the pkg repository
for(f in dir('../../... | /inst/doc/caper.R | no_license | cran/caper | R | false | false | 32,542 | r | ### R code from vignette source 'caper.rnw'
### Encoding: UTF-8
###################################################
### code chunk number 1: setup
###################################################
library(caper)
## whilst code is being tested, load most recent versions from the pkg repository
for(f in dir('../../... |
# Find all wards within Zambia --------------------------------------------
# Shape files of wards in Zambia are a bit messy, so constructing a lookup table of province, district,
# constituencies, wards, and polling places
# Laura Hughes, lhughes@usaid.gov, USAID | GeoCenter
# 7 July 2017
# procedure ------------... | /ZMB_find_wards.R | permissive | tessam30/Zambia | R | false | false | 4,144 | r |
# Find all wards within Zambia --------------------------------------------
# Shape files of wards in Zambia are a bit messy, so constructing a lookup table of province, district,
# constituencies, wards, and polling places
# Laura Hughes, lhughes@usaid.gov, USAID | GeoCenter
# 7 July 2017
# procedure ------------... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/getPost.R
\name{getPost}
\alias{getPost}
\title{Extract information about a public Facebook post}
\usage{
getPost(post, token, n = 500, comments = TRUE, likes = TRUE,
n.likes = n, n.comments = n)
}
\arguments{
\item{post}{A post ID}
\item{... | /Rfacebook/man/getPost.Rd | no_license | ashgreat/Rfacebook | R | false | true | 1,993 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/getPost.R
\name{getPost}
\alias{getPost}
\title{Extract information about a public Facebook post}
\usage{
getPost(post, token, n = 500, comments = TRUE, likes = TRUE,
n.likes = n, n.comments = n)
}
\arguments{
\item{post}{A post ID}
\item{... |
### rna_seq_featureCounter.R
### Laura M. Carroll
### April 20, 2019
### input: bam files of mapped reads, saf file output by gff2saf.py script
# uncomment to install Rsubread if necessary
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("Rsubread", version = "... | /rna_seq_featureCounter.R | no_license | alexarcohn/salmonella_rnaseq | R | false | false | 11,521 | r | ### rna_seq_featureCounter.R
### Laura M. Carroll
### April 20, 2019
### input: bam files of mapped reads, saf file output by gff2saf.py script
# uncomment to install Rsubread if necessary
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("Rsubread", version = "... |
# Copyright 2019 Observational Health Data Sciences and Informatics
#
# This file is part of aspirin365
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/l... | /aspirin365/R/CohortMethod.R | permissive | rlawodud3920/CDM-Rpackage-2020 | R | false | false | 11,679 | r | # Copyright 2019 Observational Health Data Sciences and Informatics
#
# This file is part of aspirin365
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/l... |
data = read.csv("all.csv")
attach(data)
gap = dem_pct-gop_pct
fit = glm(gap ~ gdp_pct * incumbent * relec)
fit
newdata = data.frame(gdp_pct=c(2.43), incumbent=c(0), relec=c(FALSE))
predict(fit, newdata)
pcts = seq(-5,5,by=0.1)
hypdata = data.frame(gdp_pct=pcts, incumbent=rep(0,101), relec=rep(FALSE,101))
predicted = pr... | /bayesian-president/data/elections/elec.R | no_license | CoryMcCartan/election-2016 | R | false | false | 356 | r | data = read.csv("all.csv")
attach(data)
gap = dem_pct-gop_pct
fit = glm(gap ~ gdp_pct * incumbent * relec)
fit
newdata = data.frame(gdp_pct=c(2.43), incumbent=c(0), relec=c(FALSE))
predict(fit, newdata)
pcts = seq(-5,5,by=0.1)
hypdata = data.frame(gdp_pct=pcts, incumbent=rep(0,101), relec=rep(FALSE,101))
predicted = pr... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/RcppExports.R
\name{optim_Ridge}
\alias{optim_Ridge}
\title{find optimized solution for ObjectRidge function}
\usage{
optim_Ridge(theta, X, y, family, r)
}
\arguments{
\item{theta}{vector store our optimized result}
\item{X}{high dimensional... | /man/optim_Ridge.Rd | permissive | aahilgert/myTridge | R | false | true | 521 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/RcppExports.R
\name{optim_Ridge}
\alias{optim_Ridge}
\title{find optimized solution for ObjectRidge function}
\usage{
optim_Ridge(theta, X, y, family, r)
}
\arguments{
\item{theta}{vector store our optimized result}
\item{X}{high dimensional... |
## Date: 4 October, 2022
## Author: Drew Neavin
## Reason: RNA velocity on iPSC village samples for pseudotime following the Allevin tutorial https://combine-lab.github.io/alevin-tutorial/2020/alevin-velocity/
library(Biostrings)
library(BSgenome)
library(eisaR)
library(GenomicFeatures)
library(SummarizedExperiment)
l... | /scripts/hiPSC_village_3_lines/RNA_Velocity_Pseudotime/scVelo_preprocess.R | no_license | powellgenomicslab/iPSC_Village_Publication | R | false | false | 3,182 | r | ## Date: 4 October, 2022
## Author: Drew Neavin
## Reason: RNA velocity on iPSC village samples for pseudotime following the Allevin tutorial https://combine-lab.github.io/alevin-tutorial/2020/alevin-velocity/
library(Biostrings)
library(BSgenome)
library(eisaR)
library(GenomicFeatures)
library(SummarizedExperiment)
l... |
library(testthat)
library(RsNlme)
test_package("RsNlme")
| /RsNlme/tests/run_test.r | no_license | phxnlmedev/rpackages | R | false | false | 58 | r | library(testthat)
library(RsNlme)
test_package("RsNlme")
|
library(data.table)
library(prophet)
library(dplyr)
library(ggpubr)
library(Metrics)
dt=data.table(read.csv('sample_fb.csv'))
offers=data.table(read.csv('offers.csv'))
dt$Day=as.Date(as.character(dt$Day))
offers$Date=as.Date(as.character(offers$Date))
names(dt)=c('ds','y')
dt= dt[order(ds),]
############# Daily Fore... | /Forecast_GAM_v1.r | no_license | saracmbr/Code_Demo | R | false | false | 2,669 | r | library(data.table)
library(prophet)
library(dplyr)
library(ggpubr)
library(Metrics)
dt=data.table(read.csv('sample_fb.csv'))
offers=data.table(read.csv('offers.csv'))
dt$Day=as.Date(as.character(dt$Day))
offers$Date=as.Date(as.character(offers$Date))
names(dt)=c('ds','y')
dt= dt[order(ds),]
############# Daily Fore... |
## ----setup, include = FALSE----------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## ----ttest_ex1, eval=FALSE-----------------------------------------------
# # load the bain package which includes the simulated sesamesim data set
# library(bain)
# # ... | /data/genthat_extracted_code/bain/vignettes/Introduction_to_bain.R | no_license | surayaaramli/typeRrh | R | false | false | 29,011 | r | ## ----setup, include = FALSE----------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## ----ttest_ex1, eval=FALSE-----------------------------------------------
# # load the bain package which includes the simulated sesamesim data set
# library(bain)
# # ... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/basis-funs.R
\name{basis}
\alias{basis}
\title{Basis expansions for smooths}
\usage{
basis(smooth, data, knots = NULL, constraints = FALSE, ...)
}
\arguments{
\item{smooth}{a smooth specification, the result of a call to one of
\code{\link[mg... | /man/basis.Rd | permissive | romainfrancois/gratia | R | false | true | 1,503 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/basis-funs.R
\name{basis}
\alias{basis}
\title{Basis expansions for smooths}
\usage{
basis(smooth, data, knots = NULL, constraints = FALSE, ...)
}
\arguments{
\item{smooth}{a smooth specification, the result of a call to one of
\code{\link[mg... |
rm(list=ls())
datatable<-read.table("household_power_consumption.txt",
sep=";",
nrows= 2075260,
header=TRUE,
quote= "",
strip.white=TRUE,
stringsAsFactors = FALSE,
... | /plot2.R | no_license | ozkuran/ExData_Plotting1 | R | false | false | 762 | r | rm(list=ls())
datatable<-read.table("household_power_consumption.txt",
sep=";",
nrows= 2075260,
header=TRUE,
quote= "",
strip.white=TRUE,
stringsAsFactors = FALSE,
... |
# Code for computing likelihoods and posteriors
## Defining a helper function
# This function creates a data frame will all possible choices and probabilities
#associated with them, and matches it with participants' responses. This is used for computing likelihoods.
get_function <- here::here("bayesian_modeling", "... | /01_diversity_analyses/bayesian_modeling/compute_likelihoods_posteriors.R | no_license | nyu-cdsc/diversity | R | false | false | 2,915 | r | # Code for computing likelihoods and posteriors
## Defining a helper function
# This function creates a data frame will all possible choices and probabilities
#associated with them, and matches it with participants' responses. This is used for computing likelihoods.
get_function <- here::here("bayesian_modeling", "... |
# program: spuRs/resources/scripts/quad1.r
# find the zeros of a2*x^2 + a1*x + a0 = 0
# clear the workspace
rm(list=ls())
# input
a2 <- 1
a1 <- 4
a0 <- 2
# calculation
root1 <- (-a1 + sqrt(a1^2 - 4*a2*a0))/(2*a2)
root2 <- (-a1 - sqrt(a1^2 - 4*a2*a0))/(2*a2)
# output
show(c(root1, root2))
| /R Tutorials/Book spuRs/scripts/quad1.r | no_license | chengjun/Research | R | false | false | 293 | r | # program: spuRs/resources/scripts/quad1.r
# find the zeros of a2*x^2 + a1*x + a0 = 0
# clear the workspace
rm(list=ls())
# input
a2 <- 1
a1 <- 4
a0 <- 2
# calculation
root1 <- (-a1 + sqrt(a1^2 - 4*a2*a0))/(2*a2)
root2 <- (-a1 - sqrt(a1^2 - 4*a2*a0))/(2*a2)
# output
show(c(root1, root2))
|
log.val = function(beta, Xtst) {
#################### INIT
Xtst = as.matrix(Xtst)
beta = as.matrix(beta)
if(ncol(beta)>nrow(Xtst)) {Xtst = as.matrix(cbind(rep(1,nrow(Xtst)),Xtst))} ### then add intercept if necessary
prob = matrix(0,nrow=nrow(Xtst),ncol=2)
colnames(prob) = c("w1","w2")
... | /TP4/fonctions du rapport/log.val.R | no_license | mdepuydt/SY09 | R | false | false | 566 | r | log.val = function(beta, Xtst) {
#################### INIT
Xtst = as.matrix(Xtst)
beta = as.matrix(beta)
if(ncol(beta)>nrow(Xtst)) {Xtst = as.matrix(cbind(rep(1,nrow(Xtst)),Xtst))} ### then add intercept if necessary
prob = matrix(0,nrow=nrow(Xtst),ncol=2)
colnames(prob) = c("w1","w2")
... |
testlist <- list(x = structure(c(1.35248279137152e-309, 1.98730118526674e-168, 5.28313590379074e-312), .Dim = c(3L, 1L)))
result <- do.call(bravo:::colSumSq_matrix,testlist)
str(result) | /bravo/inst/testfiles/colSumSq_matrix/libFuzzer_colSumSq_matrix/colSumSq_matrix_valgrind_files/1609959947-test.R | no_license | akhikolla/updated-only-Issues | R | false | false | 186 | r | testlist <- list(x = structure(c(1.35248279137152e-309, 1.98730118526674e-168, 5.28313590379074e-312), .Dim = c(3L, 1L)))
result <- do.call(bravo:::colSumSq_matrix,testlist)
str(result) |
testlist <- list(doy = numeric(0), latitude = numeric(0), temp = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0))
result <- do.call(meteor:::ET0_ThornthwaiteWilmott,testlist)
str(result) | /meteor/inst/testfiles/ET0_ThornthwaiteWilmott/libFuzzer_ET0_ThornthwaiteWilmott/ET0_ThornthwaiteWilmott_valgrind_files/1612735241-test.R | no_license | akhikolla/updatedatatype-list3 | R | false | false | 207 | r | testlist <- list(doy = numeric(0), latitude = numeric(0), temp = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0))
result <- do.call(meteor:::ET0_ThornthwaiteWilmott,testlist)
str(result) |
Time <- c(11048,11262,11504,12418)
Pipeline <- c(0.45,0.45,0.45,0.37,0.44,0.43,0.43,0.37,0.45,
0.45,0.45,0.40,0.43,0.42,0.43,0.43,0.42,0.41,
0.41,0.35,0.41,0.42,0.42,0.42,0.46,0.46,0.46,
0.43,0.43,0.42,0.43,0.42,0.45,0.45,0.45,0.44,
0.45,0.44,0.45,0.44,0.44,0.43,... | /Complex/Complex_Model1_Lognormal_Drive.r | no_license | ISUCyclone/Pipelines | R | false | false | 1,357 | r | Time <- c(11048,11262,11504,12418)
Pipeline <- c(0.45,0.45,0.45,0.37,0.44,0.43,0.43,0.37,0.45,
0.45,0.45,0.40,0.43,0.42,0.43,0.43,0.42,0.41,
0.41,0.35,0.41,0.42,0.42,0.42,0.46,0.46,0.46,
0.43,0.43,0.42,0.43,0.42,0.45,0.45,0.45,0.44,
0.45,0.44,0.45,0.44,0.44,0.43,... |
plot4 <- function(){
library("stringr");
library("dplyr");
data <- read.csv("household_power_consumption.txt", sep = ";", header = TRUE, stringsAsFactors=FALSE, na.strings = "?");
data$Date <- as.Date(data$Date, "%d/%m/%Y");
filtered <- filter(data, Date == "2007-02-01" | Date == "2007-02-02");
... | /plot4.R | no_license | 23Mbennett/exploratory-data-anlaysis-assignment-1 | R | false | false | 1,258 | r | plot4 <- function(){
library("stringr");
library("dplyr");
data <- read.csv("household_power_consumption.txt", sep = ";", header = TRUE, stringsAsFactors=FALSE, na.strings = "?");
data$Date <- as.Date(data$Date, "%d/%m/%Y");
filtered <- filter(data, Date == "2007-02-01" | Date == "2007-02-02");
... |
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