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 |
|---|---|---|---|---|---|---|---|---|---|
vblpcmdrawpie <- function(center,radius,probs,n=50,colours=1:length(probs))
{
x <- c(0,cumsum(probs)/sum(probs))
dx <- diff(x)
np <- length(probs)
for (i in 1:np)
{
t2p <- 2 * pi * seq(x[i], x[i + 1], length = n)
xc <- center[1] + c(cos(t2p), 0) * radius
yc <- center[2] + c(sin(t2p), 0) * radius
... | /R/plot_network.R | no_license | cran/VBLPCM | R | false | false | 3,068 | r | vblpcmdrawpie <- function(center,radius,probs,n=50,colours=1:length(probs))
{
x <- c(0,cumsum(probs)/sum(probs))
dx <- diff(x)
np <- length(probs)
for (i in 1:np)
{
t2p <- 2 * pi * seq(x[i], x[i + 1], length = n)
xc <- center[1] + c(cos(t2p), 0) * radius
yc <- center[2] + c(sin(t2p), 0) * radius
... |
library(tidymodels)
stack_train <- readRDS("data/c2_train.rds")
stack_recipe <- recipe(remote ~ ., data = stack_train) %>%
step_downsample(remote)
## Build a logistic regression model
glm_spec <- ___ %>%
set_engine("glm")
## Start a workflow (recipe only)
stack_wf <- ___ %>%
add_recipe(stack_recipe)
#... | /exercises/exc_02_11_1.R | permissive | snowdj/supervised-ML-case-studies-course | R | false | false | 470 | r | library(tidymodels)
stack_train <- readRDS("data/c2_train.rds")
stack_recipe <- recipe(remote ~ ., data = stack_train) %>%
step_downsample(remote)
## Build a logistic regression model
glm_spec <- ___ %>%
set_engine("glm")
## Start a workflow (recipe only)
stack_wf <- ___ %>%
add_recipe(stack_recipe)
#... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/AA_Generics.R
\name{simulationFilter}
\alias{simulationFilter}
\title{Create \linkS4class{SimulationFilter} class}
\usage{
simulationFilter(product = "character", ...)
}
\arguments{
\item{product}{One of "directions", "rb3D", "images".}
\ite... | /man/simulationFilter.Rd | no_license | kitbenjamin/daRt | R | false | true | 473 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/AA_Generics.R
\name{simulationFilter}
\alias{simulationFilter}
\title{Create \linkS4class{SimulationFilter} class}
\usage{
simulationFilter(product = "character", ...)
}
\arguments{
\item{product}{One of "directions", "rb3D", "images".}
\ite... |
# Exercise 4: practicing with dplyr
# Install the `"nycflights13"` package. Load (`library()`) the package.
# You'll also need to load `dplyr`
install.packages("nycflights13")
library(nycflights13)
library(dplyr)
# The data frame `flights` should now be accessible to you.
# Use functions to inspect it: how many rows... | /chapter-11-exercises/exercise-4/exercise.R | permissive | gtjrrui/book-exercises | R | false | false | 2,332 | r | # Exercise 4: practicing with dplyr
# Install the `"nycflights13"` package. Load (`library()`) the package.
# You'll also need to load `dplyr`
install.packages("nycflights13")
library(nycflights13)
library(dplyr)
# The data frame `flights` should now be accessible to you.
# Use functions to inspect it: how many rows... |
#----------------------------------------------------------------------
# Purpose: This test exercises the RF model downloaded as java code
# for the dhisttest data set. It checks whether the generated
# java correctly splits categorical predictors into non-
# contiguous groups at each no... | /h2o-r/tests/testdir_javapredict/runit_DRF_javapredict_smallcat.R | permissive | tamseo/h2o-3 | R | false | false | 1,573 | r | #----------------------------------------------------------------------
# Purpose: This test exercises the RF model downloaded as java code
# for the dhisttest data set. It checks whether the generated
# java correctly splits categorical predictors into non-
# contiguous groups at each no... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/blocks.pop.R
\docType{data}
\name{blocks.pop}
\alias{blocks}
\alias{blocks.pop}
\alias{pop}
\title{pop: Over 11 million Census Bureau 2010 block-level values in a single data.frame}
\format{A vector with 11078297 elements (Census 2010 blocks)... | /man/blocks.pop.Rd | no_license | Geschwindigkeitsbegrenzung/UScensus2010blocks | R | false | true | 2,657 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/blocks.pop.R
\docType{data}
\name{blocks.pop}
\alias{blocks}
\alias{blocks.pop}
\alias{pop}
\title{pop: Over 11 million Census Bureau 2010 block-level values in a single data.frame}
\format{A vector with 11078297 elements (Census 2010 blocks)... |
##### For moderation regime, take first 13 years as training and last 5 years as test =>
##### cutoff year is 2004 (~72% share in training set).
#####
##### For zirp regume, take first 5 years as training and last 2 years as test =>
##### cutoff year is 2013 (~71% share in training set).
# Import regime data (... | /Programs/R/moderation_zirp.R | no_license | jiantinker/forecasting-US10Y | R | false | false | 10,342 | r | ##### For moderation regime, take first 13 years as training and last 5 years as test =>
##### cutoff year is 2004 (~72% share in training set).
#####
##### For zirp regume, take first 5 years as training and last 2 years as test =>
##### cutoff year is 2013 (~71% share in training set).
# Import regime data (... |
# cut interval: n groups with equal range
# cut number: n groups with equal observations
# cut width: n groups with width
| /helpers.R | no_license | aravindhebbali/ggplot_xplorerr | R | false | false | 123 | r | # cut interval: n groups with equal range
# cut number: n groups with equal observations
# cut width: n groups with width
|
# Defines shiny bindings
shiny_input_bindings <- new.env(parent = emptyenv())
list2env(list(
'shiny.textInput' = list(
binding = "shiny.textInput",
update_function = "shiny::updateTextInput"
),
'shiny.textAreaInput' = list(
binding = "shiny.textareaInput",
update_function = "shiny::updateTextArea... | /dipsaus/R/shiny-inputbindings.R | no_license | akhikolla/TestedPackages-NoIssues | R | false | false | 7,708 | r | # Defines shiny bindings
shiny_input_bindings <- new.env(parent = emptyenv())
list2env(list(
'shiny.textInput' = list(
binding = "shiny.textInput",
update_function = "shiny::updateTextInput"
),
'shiny.textAreaInput' = list(
binding = "shiny.textareaInput",
update_function = "shiny::updateTextArea... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/svm_code.R
\name{plotperf}
\alias{plotperf}
\title{Performance plots for the approximation of an SVM model.}
\usage{
plotperf(mymodel, mydata, indy, mytestdata, type = "all", filename)
}
\arguments{
\item{mymodel}{Element of class \c... | /man/plotperf.Rd | no_license | mariakalimeri/VRPM | R | false | true | 3,198 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/svm_code.R
\name{plotperf}
\alias{plotperf}
\title{Performance plots for the approximation of an SVM model.}
\usage{
plotperf(mymodel, mydata, indy, mytestdata, type = "all", filename)
}
\arguments{
\item{mymodel}{Element of class \c... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/parameters.R
\name{parameters}
\alias{parameters}
\title{Parameters}
\usage{
parameters(...)
}
\arguments{
\item{...}{\code{\link{Parameter-class}} objects.}
}
\value{
\code{\link{Parameters-class}} object.
}
\description{
Create a new collec... | /man/parameters.Rd | no_license | prioritizr/prioritizrutils | R | false | true | 670 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/parameters.R
\name{parameters}
\alias{parameters}
\title{Parameters}
\usage{
parameters(...)
}
\arguments{
\item{...}{\code{\link{Parameter-class}} objects.}
}
\value{
\code{\link{Parameters-class}} object.
}
\description{
Create a new collec... |
#' Check species names against spp2exclude and spp2include
#'
#' Check species names in a data frame. First, rows whose species name matches any in spp2exclude
#' are automatically removed from the data frame. Then remaining rows are checked
#' against spp2include: if any species name does not match spp2include, an err... | /R/check_spnames.R | permissive | Pakillo/exclosures-Almoraima | R | false | false | 1,347 | r | #' Check species names against spp2exclude and spp2include
#'
#' Check species names in a data frame. First, rows whose species name matches any in spp2exclude
#' are automatically removed from the data frame. Then remaining rows are checked
#' against spp2include: if any species name does not match spp2include, an err... |
######################################
# 11.10.2016
# Multiple Linear Regression (MLR) example
# BISC 481
######################################
## Install and initialize packages
install.packages("ggplot2")
install.packages("grid")
library(ggplot2)
library(grid)
## Theme
my.theme <- theme(
plot.margin = unit(c(0.1... | /High Thoroughput in vitro data analysis.R | no_license | rhyunyp/BISC481-assignment | R | false | false | 1,187 | r | ######################################
# 11.10.2016
# Multiple Linear Regression (MLR) example
# BISC 481
######################################
## Install and initialize packages
install.packages("ggplot2")
install.packages("grid")
library(ggplot2)
library(grid)
## Theme
my.theme <- theme(
plot.margin = unit(c(0.1... |
library(wavethresh)
### Name: PsiJ
### Title: Compute discrete autocorrelation wavelets.
### Aliases: PsiJ
### Keywords: manip
### ** Examples
#
# Let us create the discrete autocorrelation wavelets for the Haar wavelet.
# We shall create up to scale 4.
#
PsiJ(-4, filter.number=1, family="DaubExPhase")
#Computing P... | /data/genthat_extracted_code/wavethresh/examples/PsiJ.rd.R | no_license | surayaaramli/typeRrh | R | false | false | 3,136 | r | library(wavethresh)
### Name: PsiJ
### Title: Compute discrete autocorrelation wavelets.
### Aliases: PsiJ
### Keywords: manip
### ** Examples
#
# Let us create the discrete autocorrelation wavelets for the Haar wavelet.
# We shall create up to scale 4.
#
PsiJ(-4, filter.number=1, family="DaubExPhase")
#Computing P... |
library(dplyr)
library(lubridate)
#Import data
power_data <- read_delim("household_power_consumption.txt", delim = ";") %>%
filter(Date %in% c("2/2/2007", "1/2/2007")) %>%
mutate(DateTime = dmy_hms(paste(Date,as.character(Time))))
png(filename = "plot1.png", width = 504, height = 504)
with(power_data,hist(Globa... | /plot1.R | no_license | MottledOne/ExData_Plotting1 | R | false | false | 452 | r | library(dplyr)
library(lubridate)
#Import data
power_data <- read_delim("household_power_consumption.txt", delim = ";") %>%
filter(Date %in% c("2/2/2007", "1/2/2007")) %>%
mutate(DateTime = dmy_hms(paste(Date,as.character(Time))))
png(filename = "plot1.png", width = 504, height = 504)
with(power_data,hist(Globa... |
##' @export
id <- function(object,...) UseMethod("id")
##' Extract different 'id' of neuro netCDF files
##'
##' @title Extract different 'id' of neuro netCDF files
##' @param object netCDF filename
##' @param ... Additional low level argument parsed on to lower level functions
##' @author Klaus K. Holst
##' @S3method ... | /R/id.R | no_license | kkholst/neurocdf | R | false | false | 644 | r | ##' @export
id <- function(object,...) UseMethod("id")
##' Extract different 'id' of neuro netCDF files
##'
##' @title Extract different 'id' of neuro netCDF files
##' @param object netCDF filename
##' @param ... Additional low level argument parsed on to lower level functions
##' @author Klaus K. Holst
##' @S3method ... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/glue_operations.R
\name{glue_batch_create_partition}
\alias{glue_batch_create_partition}
\title{Creates one or more partitions in a batch operation}
\usage{
glue_batch_create_partition(CatalogId, DatabaseName, TableName,
PartitionInputList)... | /paws/man/glue_batch_create_partition.Rd | permissive | johnnytommy/paws | R | false | true | 2,450 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/glue_operations.R
\name{glue_batch_create_partition}
\alias{glue_batch_create_partition}
\title{Creates one or more partitions in a batch operation}
\usage{
glue_batch_create_partition(CatalogId, DatabaseName, TableName,
PartitionInputList)... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/GOsummer.R
\name{GOsummer}
\alias{GOsummer}
\title{GOsummer is the function that you can use to do summerization on the myGO object.}
\usage{
GOsummer(mygo, Type, Term)
}
\arguments{
\item{mygo, Type, Term}{Type is the ontology type: MF, BP, ... | /DraOnto.db/man/GOsummer.Rd | no_license | xpingli/DraOnto.db | R | false | true | 1,747 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/GOsummer.R
\name{GOsummer}
\alias{GOsummer}
\title{GOsummer is the function that you can use to do summerization on the myGO object.}
\usage{
GOsummer(mygo, Type, Term)
}
\arguments{
\item{mygo, Type, Term}{Type is the ontology type: MF, BP, ... |
library("tidyverse")
library("tidyr")
library("stringr")
library("dplyr")
library("tibble")
library("readr")
library("ggplot2")
library("dplyr")
x = read_csv("eddypro.csv", skip = 1, na =c("","NA","-9999","-9999.0"), comment=c("["))
x = x[-1,]
x
glimpse(x)
x = select(x, -(roll))
x<-x[,c(-1,-3,-9,-12,-15,-1... | /test1.R | no_license | alexissolovev24/MathMod | R | false | false | 2,061 | r | library("tidyverse")
library("tidyr")
library("stringr")
library("dplyr")
library("tibble")
library("readr")
library("ggplot2")
library("dplyr")
x = read_csv("eddypro.csv", skip = 1, na =c("","NA","-9999","-9999.0"), comment=c("["))
x = x[-1,]
x
glimpse(x)
x = select(x, -(roll))
x<-x[,c(-1,-3,-9,-12,-15,-1... |
CMADE <- function(par, fn, ..., lower, upper, control=list()) {
library("ringbuffer")
## Function to check the presence of options in the arguments specified by the user
# @name - argument name
# @default - default value of the argument
# RETURN: value specified by user if the given argument name found,... | /CEC2017/CMADE-v12/CMADEv12.R | no_license | Jagorius/EvolutionAlgorithms | R | false | false | 16,221 | r | CMADE <- function(par, fn, ..., lower, upper, control=list()) {
library("ringbuffer")
## Function to check the presence of options in the arguments specified by the user
# @name - argument name
# @default - default value of the argument
# RETURN: value specified by user if the given argument name found,... |
## Put comments here that give an overall description of what your
## functions do
## Creating a list with functions defined in an environment
## where data are saved.
makeCacheMatrix <- function(x = matrix()) {
ivr <- NULL
set <- function(y) {
x <<- y
ivr <<- NULL
}
get <- function() x
inv... | /cachematrix.R | no_license | archelangelo/ProgrammingAssignment2 | R | false | false | 742 | r | ## Put comments here that give an overall description of what your
## functions do
## Creating a list with functions defined in an environment
## where data are saved.
makeCacheMatrix <- function(x = matrix()) {
ivr <- NULL
set <- function(y) {
x <<- y
ivr <<- NULL
}
get <- function() x
inv... |
get_council_le <- function(data, input){
reactive({
req(input$select_sex)
req(input$select_year)
data %>%
filter(council_name != "Scotland Wide",
sex %in% input$select_sex,
year == input$select_year,
simd_quintiles == "All") %>%
... | /life_ex_tab_functions/4_get_council_le.R | no_license | hgw2/scotland_health_group_project | R | false | false | 383 | r | get_council_le <- function(data, input){
reactive({
req(input$select_sex)
req(input$select_year)
data %>%
filter(council_name != "Scotland Wide",
sex %in% input$select_sex,
year == input$select_year,
simd_quintiles == "All") %>%
... |
library(dplyr)
library(ggplot2)
library(ggthemes)
library(rpart)
library(rpart.plot)
dataset <- read.csv(file.choose())
# Conhecendo os dados
dim(dataset)
str(dataset)
summary(dataset)
dataset$userid <- NULL # Remove o ID
# Alterando o nome das colunas
colnames(dataset) <- c('Idade', 'Dia', 'Ano', 'Mês', 'Sexo',
... | /analise_de_dados_do_facebook/analise_de_dados_facebook.R | no_license | murilo-cremon/R-Lang | R | false | false | 4,007 | r | library(dplyr)
library(ggplot2)
library(ggthemes)
library(rpart)
library(rpart.plot)
dataset <- read.csv(file.choose())
# Conhecendo os dados
dim(dataset)
str(dataset)
summary(dataset)
dataset$userid <- NULL # Remove o ID
# Alterando o nome das colunas
colnames(dataset) <- c('Idade', 'Dia', 'Ano', 'Mês', 'Sexo',
... |
rm(list = ls())
library(dplyr)
library(leaflet)
library(leaflet.extras)
library(rgdal)
library(mapview)
library(sf)
setwd("C:/Users/REACH/Dropbox (SSD REACH)/REACH South Sudan upscale/34_WFP/11_WFP_IACWG")
coordinates <- read.csv('8. Dashboard/r_dashboard/app_plot/coordinates.csv')
jmmi <- read.csv('7. JMMI ... | /app_plot/4_Practice/Leaflet_CWG.R | no_license | JonathanBuckleyREACHSSD/SSD-JMMI-Draft | R | false | false | 5,989 | r | rm(list = ls())
library(dplyr)
library(leaflet)
library(leaflet.extras)
library(rgdal)
library(mapview)
library(sf)
setwd("C:/Users/REACH/Dropbox (SSD REACH)/REACH South Sudan upscale/34_WFP/11_WFP_IACWG")
coordinates <- read.csv('8. Dashboard/r_dashboard/app_plot/coordinates.csv')
jmmi <- read.csv('7. JMMI ... |
library(dplyr)
library(here)
setwd(paste0(here(), "/LER_inputs/"))
oneday <- filter(manual_buoy_temptst, datetime == "1986-07-03 12:00:00")
oneday$Water_Temperature_celsius <- 4
oneday$datetime <- as.POSIXct("1975-01-01 12:00:00", format = "%Y-%m-%d %H:%M:%S")
write.csv(oneday, row.names = FALSE, file = "ic_hi... | /scripts/stepthrough/step_1_input_data/s1.5_initial_conditions.R | no_license | jacob8776/sunapee_LER_projections | R | false | false | 1,614 | r |
library(dplyr)
library(here)
setwd(paste0(here(), "/LER_inputs/"))
oneday <- filter(manual_buoy_temptst, datetime == "1986-07-03 12:00:00")
oneday$Water_Temperature_celsius <- 4
oneday$datetime <- as.POSIXct("1975-01-01 12:00:00", format = "%Y-%m-%d %H:%M:%S")
write.csv(oneday, row.names = FALSE, file = "ic_hi... |
#######################################################This code is for running INLA Spatial models #######################################################
#######################################################set seed to get similar results#######################################################
#####################... | /code/inla_spatial_temporal_morbidity.R | no_license | emilyrfl/SDSS-Datahack-2019 | R | false | false | 11,313 | r | #######################################################This code is for running INLA Spatial models #######################################################
#######################################################set seed to get similar results#######################################################
#####################... |
##############################################################
# Getting and Cleaning Data Course
# Final Programming Assignment
##############################################################
library(dplyr)
library(tidyr)
# 1. Read in traing and test sets
# feature names (note: remove "meanFreq")
feat_names <- read.t... | /run_analysis.R | no_license | frankzyx/Getting_and_cleaning_data__Coursera | R | false | false | 1,731 | r | ##############################################################
# Getting and Cleaning Data Course
# Final Programming Assignment
##############################################################
library(dplyr)
library(tidyr)
# 1. Read in traing and test sets
# feature names (note: remove "meanFreq")
feat_names <- read.t... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/get_facets.R
\name{get_facets}
\alias{get_facets}
\title{Get Dataverse facets}
\usage{
get_facets(dataverse, key = Sys.getenv("DATAVERSE_KEY"),
server = Sys.getenv("DATAVERSE_SERVER"), ...)
}
\arguments{
\item{dataverse}{A character string ... | /man/get_facets.Rd | permissive | wibeasley/dataverse-client-r | R | false | true | 1,734 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/get_facets.R
\name{get_facets}
\alias{get_facets}
\title{Get Dataverse facets}
\usage{
get_facets(dataverse, key = Sys.getenv("DATAVERSE_KEY"),
server = Sys.getenv("DATAVERSE_SERVER"), ...)
}
\arguments{
\item{dataverse}{A character string ... |
#' Vector of evaluated parameters in the simulation study that will be summarised
#' using the rsimsum package
#' @return vector of length 12 with the names of the to be evaluated parameters
#' and the name of their monte carlo standerd error
eval_param_rsimsum <- function(){
eval_param_rsimsum <- c("bias",
... | /R/sumsim.R | no_license | LindaNab/simexvsmecor | R | false | false | 6,218 | r | #' Vector of evaluated parameters in the simulation study that will be summarised
#' using the rsimsum package
#' @return vector of length 12 with the names of the to be evaluated parameters
#' and the name of their monte carlo standerd error
eval_param_rsimsum <- function(){
eval_param_rsimsum <- c("bias",
... |
# Emi Tanaka (@statsgen) and Garrick Aden-Buie (@grrrck) and Evangeline Reynolds (@EvaMaeRey)
# have contributed to this code
# how to solve "no visible binding for global variable" note
utils::globalVariables(
c('func', '.', 'raw_code', 'non_seq', 'func', '.','raw_code', '.',
'replacements','line','code','highligh... | /R/a_create_test_code.R | permissive | brshallo/flipbookr | R | false | false | 4,314 | r | # Emi Tanaka (@statsgen) and Garrick Aden-Buie (@grrrck) and Evangeline Reynolds (@EvaMaeRey)
# have contributed to this code
# how to solve "no visible binding for global variable" note
utils::globalVariables(
c('func', '.', 'raw_code', 'non_seq', 'func', '.','raw_code', '.',
'replacements','line','code','highligh... |
library(rvest)
res_ptt_get <- read_html('https://www.ptt.cc/bbs/hotboards.html',encoding = "big5")
ptt_nodes <- html_nodes(res_ptt_get, xpath = '//div[@class="board-title"]')
html_text(ptt_nodes) %>% head() | /Week2/Simple_Crawer/post_PPT_title.r | no_license | d336643/2018_CSX_RProject | R | false | false | 206 | r | library(rvest)
res_ptt_get <- read_html('https://www.ptt.cc/bbs/hotboards.html',encoding = "big5")
ptt_nodes <- html_nodes(res_ptt_get, xpath = '//div[@class="board-title"]')
html_text(ptt_nodes) %>% head() |
# library(R2admb)
setwd("C:/admb/admb101-gcc452-win64/examples/admb/SnapInner2015")
area="nw" # HERE set area="ea" or "nw" or "sw"
plot.out=0 # HERE set =0 or 1 for screen or =2 for tiff output
# ====================================================================================================
dat <- read... | /InnGulfFdata.R | no_license | peterfish55/InnerBaysnapper | R | false | false | 19,903 | r | # library(R2admb)
setwd("C:/admb/admb101-gcc452-win64/examples/admb/SnapInner2015")
area="nw" # HERE set area="ea" or "nw" or "sw"
plot.out=0 # HERE set =0 or 1 for screen or =2 for tiff output
# ====================================================================================================
dat <- read... |
######
##### Mothur output files and resulting modified files:
# - alpha diversity measures --> xanthan_name_summary.txt
# - input file is a summary file of alpha diversity measures created in mothur
# - output file combines these with metadata
# - xanthan_name.final.0.03.cons.taxonomy --> xanthan_name.taxonomy.... | /Code/mothur_preanalysis_file_processing_cefoperazone.R | no_license | mschnizlein/xg_microbiota | R | false | false | 13,268 | r | ######
##### Mothur output files and resulting modified files:
# - alpha diversity measures --> xanthan_name_summary.txt
# - input file is a summary file of alpha diversity measures created in mothur
# - output file combines these with metadata
# - xanthan_name.final.0.03.cons.taxonomy --> xanthan_name.taxonomy.... |
setwd("/Users/chiewluanl/RProject/ExData_Plotting1")
library(httr)
if(!file.exists("./data")){
dir.create("./data")
fileUrl <- "https://d396qusza40orc.cloudfront.net/exdata%2Fdata%2Fhousehold_power_consumption.zip"
download.file(fileUrl,destfile="./data/household_power_consumption.zip",method="curl")
unzip(z... | /Plot2.R | no_license | chiewluanl/ExData_Plotting1 | R | false | false | 972 | r | setwd("/Users/chiewluanl/RProject/ExData_Plotting1")
library(httr)
if(!file.exists("./data")){
dir.create("./data")
fileUrl <- "https://d396qusza40orc.cloudfront.net/exdata%2Fdata%2Fhousehold_power_consumption.zip"
download.file(fileUrl,destfile="./data/household_power_consumption.zip",method="curl")
unzip(z... |
# Problem: Does a employee level 6.5 earn 160 k?
# 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$Salary, SplitRatio = ... | /Part 2 - Regression/Section 9 - Random Forest Regression/forest_regression.R | no_license | Kostevski/ML-scripts | R | false | false | 1,345 | r | # Problem: Does a employee level 6.5 earn 160 k?
# Importing the dataset
dataset = read.csv('Position_Salaries.csv')
dataset = dataset[2:3]
# Splitting the dataset into the Training set and Test set
# # install.packages('caTools')
# library(caTools)
# set.seed(123)
# split = sample.split(dataset$Salary, SplitRatio = ... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/mosek-solver.R
\docType{methods}
\name{status_map,MOSEK-method}
\alias{status_map,MOSEK-method}
\title{MOSEK Status Map}
\usage{
\S4method{status_map}{MOSEK}(solver, status)
}
\arguments{
\item{solver}{A \linkS4class{MOSEK} object.}
\item{st... | /man/MOSEK-status_map.Rd | permissive | aszekMosek/CVXR | R | false | true | 699 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/mosek-solver.R
\docType{methods}
\name{status_map,MOSEK-method}
\alias{status_map,MOSEK-method}
\title{MOSEK Status Map}
\usage{
\S4method{status_map}{MOSEK}(solver, status)
}
\arguments{
\item{solver}{A \linkS4class{MOSEK} object.}
\item{st... |
{
set.seed(42782)
tic()
# DC implementation
source("20200705-DCDR-Functions.R")
# getRES function is now relocated to a separate file (20200720-Algos-code.R)
source("20200720-Algos-code.R")
# regression models for GLM / AIPW
if (estimateWithMore == T){
out_path <- "/Users/garethalex/Desktop/Hu... | /Code/20200904-run-sim-code.R | no_license | mengeks/drml-plasmode | R | false | false | 2,925 | r | {
set.seed(42782)
tic()
# DC implementation
source("20200705-DCDR-Functions.R")
# getRES function is now relocated to a separate file (20200720-Algos-code.R)
source("20200720-Algos-code.R")
# regression models for GLM / AIPW
if (estimateWithMore == T){
out_path <- "/Users/garethalex/Desktop/Hu... |
#' Country names
#'
#' Convert country names to echarts format.
#'
#' @param data Data.frame in which to find column names.
#' @param input,output Input and output columns.
#' @param type Passed to \link[countrycode]{countrycode} \code{origin} parameter.
#' @param ... Any other parameter to pass to \link[countrycode]{c... | /R/helpers.R | no_license | cran/echarts4r | R | false | false | 8,496 | r | #' Country names
#'
#' Convert country names to echarts format.
#'
#' @param data Data.frame in which to find column names.
#' @param input,output Input and output columns.
#' @param type Passed to \link[countrycode]{countrycode} \code{origin} parameter.
#' @param ... Any other parameter to pass to \link[countrycode]{c... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/rcax_escdata.R
\name{rcax_escdata}
\alias{rcax_escdata}
\title{Get EscData table}
\usage{
rcax_escdata(
tablename = "EscData",
flist = NULL,
qlist = NULL,
cols = NULL,
sortcols = c("countdate", "refid"),
type = c("data.frame", "co... | /man/rcax_escdata.Rd | permissive | nwfsc-math-bio/rCAX | R | false | true | 2,350 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/rcax_escdata.R
\name{rcax_escdata}
\alias{rcax_escdata}
\title{Get EscData table}
\usage{
rcax_escdata(
tablename = "EscData",
flist = NULL,
qlist = NULL,
cols = NULL,
sortcols = c("countdate", "refid"),
type = c("data.frame", "co... |
# Stream residence time of salmon
# 2015-07-10 CJS Update with split; ggplot2; lsmemans; contrasts etc
# The stream residence of time was measured for individually tagged fish in
# a number of YearFs.
# Example of a two factor CRD analysis of variance with unbalanced data
options(useFancyQuotes=FALS... | /Sampling_Regression_Experiment_Design_and_Analysis/residence.r | no_license | burakbayramli/books | R | false | false | 6,918 | r |
# Stream residence time of salmon
# 2015-07-10 CJS Update with split; ggplot2; lsmemans; contrasts etc
# The stream residence of time was measured for individually tagged fish in
# a number of YearFs.
# Example of a two factor CRD analysis of variance with unbalanced data
options(useFancyQuotes=FALS... |
## Caching the inverse of a Matrix
## Matrix inversion is computationally expensive to be performed repeatedly.
## Therefore the functions in this program calculates the inverse and stores in
## the cache. This data is accessed whenever the inverse is called.
## Creates a matrix object that can cache its inver... | /cachematrix.R | no_license | chidam181/ProgrammingAssignment2 | R | false | false | 1,619 | r | ## Caching the inverse of a Matrix
## Matrix inversion is computationally expensive to be performed repeatedly.
## Therefore the functions in this program calculates the inverse and stores in
## the cache. This data is accessed whenever the inverse is called.
## Creates a matrix object that can cache its inver... |
#!/usr/bin/Rscript
# seqstats_density.R
# Density plots for sequencing stats.
#
# Author: Daniel A Cuevas (dcuevas08.at.gmail.com)
# Created on 23 Nov 2016
# Updated on 20 Mar 2017
# Import necessary packages
# These may need to be installed first
if ("getopt" %in% rownames(installed.packages()) == F) {
install.pa... | /scripts/seqstats/seqstats_density.R | no_license | Adrian-Cantu/cf_pipeline | R | false | false | 5,686 | r | #!/usr/bin/Rscript
# seqstats_density.R
# Density plots for sequencing stats.
#
# Author: Daniel A Cuevas (dcuevas08.at.gmail.com)
# Created on 23 Nov 2016
# Updated on 20 Mar 2017
# Import necessary packages
# These may need to be installed first
if ("getopt" %in% rownames(installed.packages()) == F) {
install.pa... |
testlist <- list(data = structure(c(-3.879448322712e+260, NaN), .Dim = 1:2), q = 6.95335580945396e-310)
result <- do.call(biwavelet:::rcpp_row_quantile,testlist)
str(result) | /biwavelet/inst/testfiles/rcpp_row_quantile/libFuzzer_rcpp_row_quantile/rcpp_row_quantile_valgrind_files/1610556855-test.R | no_license | akhikolla/updated-only-Issues | R | false | false | 178 | r | testlist <- list(data = structure(c(-3.879448322712e+260, NaN), .Dim = 1:2), q = 6.95335580945396e-310)
result <- do.call(biwavelet:::rcpp_row_quantile,testlist)
str(result) |
library(photobiologyWavebands)
### Name: Orange
### Title: Constructor of orange waveband
### Aliases: Orange
### ** Examples
Orange()
Orange("ISO")
| /data/genthat_extracted_code/photobiologyWavebands/examples/Orange.Rd.R | no_license | surayaaramli/typeRrh | R | false | false | 157 | r | library(photobiologyWavebands)
### Name: Orange
### Title: Constructor of orange waveband
### Aliases: Orange
### ** Examples
Orange()
Orange("ISO")
|
# old rasters from Greg 2015 I think.
# rastersOLD <- prepInputs(
# url = "https://drive.google.com/file/d/1DN31xcXh97u6v8NaVcy0O3vzKpLpld69/view?usp=sharing",
# fun = "raster::stack",
# #rasterToMatch = masterRaster, useGDAL = FALSE) # this was Eliot's
# destinationPath = 'inputs')
#
# stackIan <- p... | /buildingAgeRaster1985.R | no_license | cboisvenue/CBM_dataPrep_RIApresentDayTempError | R | false | false | 26,811 | r |
# old rasters from Greg 2015 I think.
# rastersOLD <- prepInputs(
# url = "https://drive.google.com/file/d/1DN31xcXh97u6v8NaVcy0O3vzKpLpld69/view?usp=sharing",
# fun = "raster::stack",
# #rasterToMatch = masterRaster, useGDAL = FALSE) # this was Eliot's
# destinationPath = 'inputs')
#
# stackIan <- p... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/reaction.R
\name{reaction}
\alias{reaction}
\title{Define a reaction}
\usage{
reaction(propensity, effect, name = NA_character_)
}
\arguments{
\item{propensity}{\verb{[character/formula]} A character or formula representation of the propensit... | /man/reaction.Rd | no_license | rcannood/GillespieSSA2 | R | false | true | 1,692 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/reaction.R
\name{reaction}
\alias{reaction}
\title{Define a reaction}
\usage{
reaction(propensity, effect, name = NA_character_)
}
\arguments{
\item{propensity}{\verb{[character/formula]} A character or formula representation of the propensit... |
# 10.27 In Class Assignment
library(ISLR)
library(MASS)
library(boot)
set.seed(1)
help("sample")
train = sample(392,196)
lm.fit <- lm(mpg~horsepower, data = Auto, subset = train)
attach(Auto)
mean((mpg-predict(lm.fit,Auto))[-train]^2)
lm.fit2 <- lm(mpg~poly(horsepower,2), data = Auto, subset = train... | /group3lab1_randomforest1.R | no_license | ArnoZhang47/DataAnalytics2020_YuxiangZhang | R | false | false | 2,668 | r | # 10.27 In Class Assignment
library(ISLR)
library(MASS)
library(boot)
set.seed(1)
help("sample")
train = sample(392,196)
lm.fit <- lm(mpg~horsepower, data = Auto, subset = train)
attach(Auto)
mean((mpg-predict(lm.fit,Auto))[-train]^2)
lm.fit2 <- lm(mpg~poly(horsepower,2), data = Auto, subset = train... |
# Plot model outputs and fit
library(postjags)
library(ggplot2)
library(dplyr)
library(cowplot)
# logit and antilogit functions
logit <- function(x) {
log(x/(1-x))
}
ilogit <- function(x){
exp(x) / (1 + exp(x))
}
# read in data
load("../../../../cleaned_data/cover_mono.Rdata") # cover_mono
# convert to proportion... | /models/cover/forbs/mono/Forbs_plots.R | permissive | cct-datascience/rangeland-restore | R | false | false | 9,462 | r | # Plot model outputs and fit
library(postjags)
library(ggplot2)
library(dplyr)
library(cowplot)
# logit and antilogit functions
logit <- function(x) {
log(x/(1-x))
}
ilogit <- function(x){
exp(x) / (1 + exp(x))
}
# read in data
load("../../../../cleaned_data/cover_mono.Rdata") # cover_mono
# convert to proportion... |
#==============Load the packages================
library(tseries)
library(vars)
library(tidyverse)
library(e1071)
#==============Load the data====================
setwd('D:/Fall Semester/SYS6018/sysproject/Data')
corn<-read.csv('Corn.csv')
source('Metrics.R')
#==============Data Transformations==============... | /SYS6018 Final Project/Individual Product Models/Group 1 products (time series models also performed)/SVM/cornsvm.R | no_license | alizaidia/SysProject | R | false | false | 2,569 | r | #==============Load the packages================
library(tseries)
library(vars)
library(tidyverse)
library(e1071)
#==============Load the data====================
setwd('D:/Fall Semester/SYS6018/sysproject/Data')
corn<-read.csv('Corn.csv')
source('Metrics.R')
#==============Data Transformations==============... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/funcs_add_new_data_series.R
\name{rbinddatasetNMR}
\alias{rbinddatasetNMR}
\title{Row-bind two datasets for NMR with slight changes, check duplicated keys, set
order}
\usage{
rbinddatasetNMR(dt_master, dt_new)
}
\arguments{
\item{dt_master}{m... | /man/rbinddatasetNMR.Rd | permissive | unicef-drp/CME.assistant | R | false | true | 511 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/funcs_add_new_data_series.R
\name{rbinddatasetNMR}
\alias{rbinddatasetNMR}
\title{Row-bind two datasets for NMR with slight changes, check duplicated keys, set
order}
\usage{
rbinddatasetNMR(dt_master, dt_new)
}
\arguments{
\item{dt_master}{m... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/has_intercept.R
\name{has_intercept}
\alias{has_intercept}
\title{Find out whether a model includes an intercept}
\usage{
has_intercept(model)
}
\arguments{
\item{model}{a model object.}
}
\value{
logical. \code{TRUE} if the intercept is pres... | /man/has_intercept.Rd | no_license | RymerLab/remef | R | false | true | 457 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/has_intercept.R
\name{has_intercept}
\alias{has_intercept}
\title{Find out whether a model includes an intercept}
\usage{
has_intercept(model)
}
\arguments{
\item{model}{a model object.}
}
\value{
logical. \code{TRUE} if the intercept is pres... |
getComposingPrimes <- function (primes, vec.primes)
{
if(is.null(primes))
return(NULL)
a <- strsplit(primes, split = " & ")
b <- strsplit(vec.primes, split = " & ")
d <- numeric(length(vec.primes))
for (i in 1:length(primes)){
d <- d + sapply(b, function (x, y) ifelse(
all(x %in% y) && (length(x... | /R/getComposingPrimes.R | no_license | holgerschw/logicFS | R | false | false | 443 | r | getComposingPrimes <- function (primes, vec.primes)
{
if(is.null(primes))
return(NULL)
a <- strsplit(primes, split = " & ")
b <- strsplit(vec.primes, split = " & ")
d <- numeric(length(vec.primes))
for (i in 1:length(primes)){
d <- d + sapply(b, function (x, y) ifelse(
all(x %in% y) && (length(x... |
### Code for reading data and plot1
library(dplyr)
library(pryr)
library(data.table)
library(tidyr)
library(lubridate)
# Download of data and keep under the directory-----------------------------------------------
url <- "https://d396qusza40orc.cloudfront.net/exdata%2Fdata%2Fhousehold_power_consumption.zip"
f <... | /plot3.r | no_license | karthyram/ExData_Plotting1 | R | false | false | 2,389 | r | ### Code for reading data and plot1
library(dplyr)
library(pryr)
library(data.table)
library(tidyr)
library(lubridate)
# Download of data and keep under the directory-----------------------------------------------
url <- "https://d396qusza40orc.cloudfront.net/exdata%2Fdata%2Fhousehold_power_consumption.zip"
f <... |
library("nleqslv")
# Dennis & Schnabel,1996,"Numerical methods for unconstrained optimization and nonlinear equations", SIAM
# example 6.5.1 page 149
dslnex <- function(x) {
y <- numeric(2)
y[1] <- x[1]^2 + x[2]^2 - 2
y[2] <- exp(x[1]-1) + x[2]^3 - 2
y
}
xstart <- c(2,0.5)
fstart <- dslnex(xstart)
... | /tests/dslnexCN.R | no_license | cran/nleqslv | R | false | false | 1,228 | r |
library("nleqslv")
# Dennis & Schnabel,1996,"Numerical methods for unconstrained optimization and nonlinear equations", SIAM
# example 6.5.1 page 149
dslnex <- function(x) {
y <- numeric(2)
y[1] <- x[1]^2 + x[2]^2 - 2
y[2] <- exp(x[1]-1) + x[2]^3 - 2
y
}
xstart <- c(2,0.5)
fstart <- dslnex(xstart)
... |
#' Create PNG file from plottable object
#'
#' \code{to_pdf} plots an object directly into one ore multiple PDF files.
#'
#' @param x object to plot.
#' @param name name used for output file(s), might be extended if multiple plots
#' are generated and no ending is needed (e.g. 'my_file').
#' @param ... further... | /R/to_png.R | permissive | kkmann/describr | R | false | false | 2,919 | r | #' Create PNG file from plottable object
#'
#' \code{to_pdf} plots an object directly into one ore multiple PDF files.
#'
#' @param x object to plot.
#' @param name name used for output file(s), might be extended if multiple plots
#' are generated and no ending is needed (e.g. 'my_file').
#' @param ... further... |
##
## Write the result of a Redshift sql query to a dataframe
##
library(RPostgreSQL)
library(uuid)
ReadSqlResults <- function(con, sql.query, aws.access.key, aws.secret.key, s3.bucket, redshift.iam.role) {
path <- paste0("data/tmp/", UUIDgenerate())
print("Running SQL query")
# Escape single quotes in the que... | /db.R | no_license | abrenaut/redshift-r-quick-read | R | false | false | 1,340 | r | ##
## Write the result of a Redshift sql query to a dataframe
##
library(RPostgreSQL)
library(uuid)
ReadSqlResults <- function(con, sql.query, aws.access.key, aws.secret.key, s3.bucket, redshift.iam.role) {
path <- paste0("data/tmp/", UUIDgenerate())
print("Running SQL query")
# Escape single quotes in the que... |
## Matrix inversion is usually a costly computation and there
## may be some benefit to caching the inverse of a matrix rather
## than compute it repeatedly.
## This function creates a special "matrix" object that can
## cache its inverse.
makeCacheMatrix <- function(x = matrix()) {
m<-NULL
set<-function... | /cachematrix.R | no_license | irismeng/ProgrammingAssignment2 | R | false | false | 833 | r | ## Matrix inversion is usually a costly computation and there
## may be some benefit to caching the inverse of a matrix rather
## than compute it repeatedly.
## This function creates a special "matrix" object that can
## cache its inverse.
makeCacheMatrix <- function(x = matrix()) {
m<-NULL
set<-function... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ineqQuantile.R
\name{run_optim_LC}
\alias{run_optim_LC}
\title{Optimisation of a parametric Lorenz curve for several functional forms and several areas}
\usage{
run_optim_LC(ID, income_cum, population_cum, function_form)
}
\arguments{
\item{I... | /man/run_optim_LC.Rd | no_license | EnoraBelz/Inequality | R | false | true | 1,480 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ineqQuantile.R
\name{run_optim_LC}
\alias{run_optim_LC}
\title{Optimisation of a parametric Lorenz curve for several functional forms and several areas}
\usage{
run_optim_LC(ID, income_cum, population_cum, function_form)
}
\arguments{
\item{I... |
install.packages("dplyr",dependencies = TRUE)
install.packages("xlsx",dependencies = TRUE)
install.packages("ggplot2",dependencies = TRUE)
install.packages("RODBC",dependencies = TRUE)
install.packages("ztable",dependencies = TRUE)
| /AOI_INSTALL_REQUIRED_PACKAGES.R | no_license | agiannikos/Hevel | R | false | false | 232 | r | install.packages("dplyr",dependencies = TRUE)
install.packages("xlsx",dependencies = TRUE)
install.packages("ggplot2",dependencies = TRUE)
install.packages("RODBC",dependencies = TRUE)
install.packages("ztable",dependencies = TRUE)
|
#!/usr/bin/Rscript
## And now continue as before.
get_sepsis_score = function(CINCdata, myModel){
myModel <- load_sepsis_model()
## Add the column names back
colnames(CINCdata) <- c("HR", "O2Sat", "Temp", "SBP", "MAP", "DBP", "Resp", "EtCO2",
"BaseExcess", "HCO3", "FiO2", "pH", "PaCO2... | /UBCDHIL/pnc2019_22Aug/get_sepsis_score.R | permissive | Eric-Hsieh97/2019ChallengeEntries | R | false | false | 24,197 | r | #!/usr/bin/Rscript
## And now continue as before.
get_sepsis_score = function(CINCdata, myModel){
myModel <- load_sepsis_model()
## Add the column names back
colnames(CINCdata) <- c("HR", "O2Sat", "Temp", "SBP", "MAP", "DBP", "Resp", "EtCO2",
"BaseExcess", "HCO3", "FiO2", "pH", "PaCO2... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/classic.wordscores.R
\name{classic.wordscores}
\alias{classic.wordscores}
\title{Old-Style Wordscores}
\usage{
classic.wordscores(wfm, scores)
}
\arguments{
\item{wfm}{object of class wfm}
\item{scores}{reference document positions/scores}
}... | /man/classic.wordscores.Rd | no_license | markwestcott34/austin | R | false | true | 1,264 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/classic.wordscores.R
\name{classic.wordscores}
\alias{classic.wordscores}
\title{Old-Style Wordscores}
\usage{
classic.wordscores(wfm, scores)
}
\arguments{
\item{wfm}{object of class wfm}
\item{scores}{reference document positions/scores}
}... |
d <- read.csv2("data/rhc_devoir_epidemio.csv")
head(d)
str(d)
dim(d)
summary(d)
d$SADMDTE <- as.Date(d$SADMDTE,"%d/%m/%Y")
d$DSCHDTE <- as.Date(d$DSCHDTE,"%d/%m/%Y")
d$DTHDTE <- as.Date(d$DTHDTE,"%d/%m/%Y")
d$LSTCTDTE <- as.Date(d$LSTCTDTE,"%d/%m/%Y")
for (i in c("DEATH", "DTH30", "DNR1", "RESP", "CARD", "NEURO"... | /src/epid_data_management.R | no_license | feldmans/M2MSR-epid | R | false | false | 29,811 | r | d <- read.csv2("data/rhc_devoir_epidemio.csv")
head(d)
str(d)
dim(d)
summary(d)
d$SADMDTE <- as.Date(d$SADMDTE,"%d/%m/%Y")
d$DSCHDTE <- as.Date(d$DSCHDTE,"%d/%m/%Y")
d$DTHDTE <- as.Date(d$DTHDTE,"%d/%m/%Y")
d$LSTCTDTE <- as.Date(d$LSTCTDTE,"%d/%m/%Y")
for (i in c("DEATH", "DTH30", "DNR1", "RESP", "CARD", "NEURO"... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.