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 |
|---|---|---|---|---|---|---|---|---|---|
berechne<- function(coocTerm, numberOfCoocs, binDTM){
coocs <- calculateCoocStatistics(coocTerm, binDTM, measure="LOGLIK")
# Display the numberOfCoocs main terms
print(coocs[1:numberOfCoocs])
resultGraph <- data.frame(from = character(), to = character(), sig = numeric(0))
# The structure of the te... | /berechne.R | no_license | tkatzer/blackrockTextAnalytics | R | false | false | 3,342 | r |
berechne<- function(coocTerm, numberOfCoocs, binDTM){
coocs <- calculateCoocStatistics(coocTerm, binDTM, measure="LOGLIK")
# Display the numberOfCoocs main terms
print(coocs[1:numberOfCoocs])
resultGraph <- data.frame(from = character(), to = character(), sig = numeric(0))
# The structure of the te... |
suppressMessages(library(CCELIM))
options(echo=TRUE) # if you want see commands in output file
args <- commandArgs(trailingOnly = TRUE)
source('settings.r')
name = paste('EXP001-', args[1], sep='')
cycle = as.integer(args[1])
jmp = jmp[cycle]
model = ReadModel("./input/Model.xls", "./input/Constraints.xls"... | /EXP001.R | permissive | tbrycekelly/Inverse_DVM | R | false | false | 656 | r | suppressMessages(library(CCELIM))
options(echo=TRUE) # if you want see commands in output file
args <- commandArgs(trailingOnly = TRUE)
source('settings.r')
name = paste('EXP001-', args[1], sep='')
cycle = as.integer(args[1])
jmp = jmp[cycle]
model = ReadModel("./input/Model.xls", "./input/Constraints.xls"... |
# Gnome R Data Miner: GNOME interface to R for Data Mining
#
# Time-stamp: <2015-11-15 09:02:15 gjw>
#
# DATA TAB
#
# Copyright (c) 2009 Togaware Pty Ltd
#
# This file is part of Rattle.
#
# Rattle is free software: you can redistribute it and/or modify it
# under the terms of the GNU General Public License as publishe... | /rattle/R/data.R | no_license | ingted/R-Examples | R | false | false | 128,889 | r | # Gnome R Data Miner: GNOME interface to R for Data Mining
#
# Time-stamp: <2015-11-15 09:02:15 gjw>
#
# DATA TAB
#
# Copyright (c) 2009 Togaware Pty Ltd
#
# This file is part of Rattle.
#
# Rattle is free software: you can redistribute it and/or modify it
# under the terms of the GNU General Public License as publishe... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/output.R
\name{interval.prob}
\alias{interval.prob}
\title{Estimate the probability of a change point in a specified interval}
\usage{
interval.prob(object, start, end)
}
\arguments{
\item{object}{the result of a call to \code{bcp()}.}
\item... | /fuzzedpackages/bcp/man/interval.prob.Rd | no_license | akhikolla/testpackages | R | false | true | 1,217 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/output.R
\name{interval.prob}
\alias{interval.prob}
\title{Estimate the probability of a change point in a specified interval}
\usage{
interval.prob(object, start, end)
}
\arguments{
\item{object}{the result of a call to \code{bcp()}.}
\item... |
#separando las palabras por espacio
splitEspacioNoticia<-strsplit(textoNoticia," ")[[1]]
#pasando todas las palabras a minusculas
splitEspacioNoticia<-tolower(splitEspacioNoticia)
#contar palabras
unlisNoticias<-unlist(splitEspacioNoticia)
tablaPalabra<-table(unlisNoticia)
#pasando la informacion a un data frame... | /Funcion de extraccion.R | no_license | angela2020/Tarea_4.4 | R | false | false | 2,084 | r | #separando las palabras por espacio
splitEspacioNoticia<-strsplit(textoNoticia," ")[[1]]
#pasando todas las palabras a minusculas
splitEspacioNoticia<-tolower(splitEspacioNoticia)
#contar palabras
unlisNoticias<-unlist(splitEspacioNoticia)
tablaPalabra<-table(unlisNoticia)
#pasando la informacion a un data frame... |
% Generated by roxygen2 (4.1.0.9001): do not edit by hand
% Please edit documentation in R/wrap_col.R
\name{wrap_col}
\alias{wrap_col}
\title{Replicate Vector to N}
\usage{
wrap_col(col, n)
}
\arguments{
\item{col}{A vector of colors.}
\item{n}{The desired length for the returned vector of colors.}
}
\description{
Thi... | /EnzymeAssay/man/wrap_col.Rd | no_license | alisandra/enzyme_assay | R | false | false | 424 | rd | % Generated by roxygen2 (4.1.0.9001): do not edit by hand
% Please edit documentation in R/wrap_col.R
\name{wrap_col}
\alias{wrap_col}
\title{Replicate Vector to N}
\usage{
wrap_col(col, n)
}
\arguments{
\item{col}{A vector of colors.}
\item{n}{The desired length for the returned vector of colors.}
}
\description{
Thi... |
#
# This module contains functions, implementing RR-related functionality:
#
# 1. General functions (dynamic chunks, etc.)
# 2. Specialized functions (creating tables/figures for various analyses)
# 3. Miscellaneous (utility) functions
##### GENERAL FUNCTIONS
## CHUNKS
# Dynamically generates knit-ready chunk code ... | /utils/knit.R | permissive | abnova/diss-floss-official | R | false | false | 6,671 | r | #
# This module contains functions, implementing RR-related functionality:
#
# 1. General functions (dynamic chunks, etc.)
# 2. Specialized functions (creating tables/figures for various analyses)
# 3. Miscellaneous (utility) functions
##### GENERAL FUNCTIONS
## CHUNKS
# Dynamically generates knit-ready chunk code ... |
testlist <- list(Rs = c(-1.9577272327571e+276, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), atmp = numeric(0), relh = c(7.41896642122422e-304, -4.29227809743625e-307, 1.81037701089217e+87, -2.93112217825115e-158, 9.03412394302482e-46, 7.31195213563656e+256, -1.939255246... | /meteor/inst/testfiles/ET0_Makkink/AFL_ET0_Makkink/ET0_Makkink_valgrind_files/1615862022-test.R | no_license | akhikolla/updatedatatype-list3 | R | false | false | 473 | r | testlist <- list(Rs = c(-1.9577272327571e+276, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), atmp = numeric(0), relh = c(7.41896642122422e-304, -4.29227809743625e-307, 1.81037701089217e+87, -2.93112217825115e-158, 9.03412394302482e-46, 7.31195213563656e+256, -1.939255246... |
library(visualize)
### Name: visualize.chisq
### Title: Visualize Chi-squared Distribution
### Aliases: visualize.chisq
### Keywords: visualize
### ** Examples
# Evaluates lower tail.
visualize.chisq(stat = 1, df = 3, section = "lower")
# Evaluates bounded region.
visualize.chisq(stat = c(1,2), df = 6, section = "... | /data/genthat_extracted_code/visualize/examples/visualize.chisq.Rd.R | no_license | surayaaramli/typeRrh | R | false | false | 412 | r | library(visualize)
### Name: visualize.chisq
### Title: Visualize Chi-squared Distribution
### Aliases: visualize.chisq
### Keywords: visualize
### ** Examples
# Evaluates lower tail.
visualize.chisq(stat = 1, df = 3, section = "lower")
# Evaluates bounded region.
visualize.chisq(stat = c(1,2), df = 6, section = "... |
#
# Copyright 2007-2015 The OpenMx Project
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable ... | /R/MxModelParameters.R | permissive | trbrick/OpenMx | R | false | false | 14,073 | r | #
# Copyright 2007-2015 The OpenMx Project
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable ... |
#importing libraries
library(Amelia)
library(outliers)
#setting working environment
setwd("/home/rajesh/Desktop/DMML_project/Datasets/1/")
#reading data and saving it into a data frame
gaming_data <- read.csv("GamingStudy_data.csv")
#getting the structure of the data frame
str(gaming_data)
#plotting missing percentage
... | /Project/Dataset1_Decision_trees/gaming_data_cleaning_code.R | no_license | rajesh95cs/machine-learning-project | R | false | false | 3,878 | r | #importing libraries
library(Amelia)
library(outliers)
#setting working environment
setwd("/home/rajesh/Desktop/DMML_project/Datasets/1/")
#reading data and saving it into a data frame
gaming_data <- read.csv("GamingStudy_data.csv")
#getting the structure of the data frame
str(gaming_data)
#plotting missing percentage
... |
/Stepik2/Task1-3.R | no_license | venkaDaria/rlang-demo | R | false | false | 847 | r | ||
library(tidyverse)
library(wordVectors)
library(tictoc)
# library(furrr)
#
# plan(multicore(workers = 3L))
# options(future.globals.maxSize = 10522669875)
# plan(sequential)
options(scipen = 99)
experiments <- read_csv("data/ms_final_experiments.csv")
translations <- read_csv("data/final_translations.csv") %>%
m... | /R/semantic_overlaps.R | permissive | kanishkamisra/cogsci2019 | R | false | false | 4,608 | r | library(tidyverse)
library(wordVectors)
library(tictoc)
# library(furrr)
#
# plan(multicore(workers = 3L))
# options(future.globals.maxSize = 10522669875)
# plan(sequential)
options(scipen = 99)
experiments <- read_csv("data/ms_final_experiments.csv")
translations <- read_csv("data/final_translations.csv") %>%
m... |
testlist <- list(data = structure(0, .Dim = c(1L, 1L)), w = structure(c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 6L)))
result <- do.call(UniIsoRegression:::pre_2d... | /UniIsoRegression/inst/testfiles/pre_2d_l2_inc/libFuzzer_pre_2d_l2_inc/pre_2d_l2_inc_valgrind_files/1612736688-test.R | no_license | akhikolla/updatedatatype-list1 | R | false | false | 349 | r | testlist <- list(data = structure(0, .Dim = c(1L, 1L)), w = structure(c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 6L)))
result <- do.call(UniIsoRegression:::pre_2d... |
############## COMMENTS ####################
### REGIMES
# 1 - EXPANSION
# 0 - RECESSION
set.seed(42)
# preparing matryx Y for GDP in USA
dftemp<-USA_GDP_ch
Y<-dftemp%>% select(c(ID,Period, Value)) %>% pivot_wider(names_from = ID,values_from = Value)
Y <- as.matrix(Y[,-1])
W<-W_USA
table(is.na(Y))
###################... | /USA_GDP_analysis.R | no_license | CocoChanelno5/Master_git | R | false | false | 13,036 | r | ############## COMMENTS ####################
### REGIMES
# 1 - EXPANSION
# 0 - RECESSION
set.seed(42)
# preparing matryx Y for GDP in USA
dftemp<-USA_GDP_ch
Y<-dftemp%>% select(c(ID,Period, Value)) %>% pivot_wider(names_from = ID,values_from = Value)
Y <- as.matrix(Y[,-1])
W<-W_USA
table(is.na(Y))
###################... |
library(tidyverse)
open_data <- read_csv('data/open_data_index_places.csv') %>%
select(name,score) %>%
rename(country=name,open_data=score) %>%
fix_adm0
| /open_data.R | no_license | ccjolley/DECA | R | false | false | 160 | r | library(tidyverse)
open_data <- read_csv('data/open_data_index_places.csv') %>%
select(name,score) %>%
rename(country=name,open_data=score) %>%
fix_adm0
|
## Let's evaluate some of the logistic model submissions
# 1. Do the priors make sense?
# 2. Do the MCMCs converge?
# 3. Do the posteriors make sense?
# 4. Do they produce good predictions?
# Names are anonymized to protect the innocent...
library(tidyverse)
library(rethinking)
## Hubert, Mack, and Chad -------... | /day-13-model-competition.R | permissive | colt-jensen/maymester-bayes-2021 | R | false | false | 11,341 | r | ## Let's evaluate some of the logistic model submissions
# 1. Do the priors make sense?
# 2. Do the MCMCs converge?
# 3. Do the posteriors make sense?
# 4. Do they produce good predictions?
# Names are anonymized to protect the innocent...
library(tidyverse)
library(rethinking)
## Hubert, Mack, and Chad -------... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/routines.R
\name{investigateAIC}
\alias{investigateAIC}
\title{Plot of simulation study}
\usage{
investigateAIC(nsim = 10000, Nsamp = 1000, seed = 1001)
}
\arguments{
\item{nsim=10000}{The number of simulation replications}
\item{... | /man/investigateAIC.Rd | no_license | SparseMSE/sparsemse | R | false | true | 2,903 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/routines.R
\name{investigateAIC}
\alias{investigateAIC}
\title{Plot of simulation study}
\usage{
investigateAIC(nsim = 10000, Nsamp = 1000, seed = 1001)
}
\arguments{
\item{nsim=10000}{The number of simulation replications}
\item{... |
\name{filter_feature_selection}
\alias{filter_feature_selection}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{
Perform selection by filter
}
\description{
Perform selection by filter using univariate filters, from caret's package.
}
\usage{
filter_feature_selection(datamat, samples.class,
func... | /man/filter_feature_selection.Rd | no_license | Neal050617/specmine | R | false | false | 1,377 | rd | \name{filter_feature_selection}
\alias{filter_feature_selection}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{
Perform selection by filter
}
\description{
Perform selection by filter using univariate filters, from caret's package.
}
\usage{
filter_feature_selection(datamat, samples.class,
func... |
library(pscl)
### Name: ideal
### Title: analysis of educational testing data and roll call data with IRT
### models, via Markov chain Monte Carlo methods
### Aliases: ideal
### Keywords: models
### ** Examples
## Not run:
##D ## long run, many iterations
##D data(s109)
##D n <- dim(s109$legis.data)[1]
##D x0 <-... | /data/genthat_extracted_code/pscl/examples/ideal.Rd.R | no_license | surayaaramli/typeRrh | R | false | false | 677 | r | library(pscl)
### Name: ideal
### Title: analysis of educational testing data and roll call data with IRT
### models, via Markov chain Monte Carlo methods
### Aliases: ideal
### Keywords: models
### ** Examples
## Not run:
##D ## long run, many iterations
##D data(s109)
##D n <- dim(s109$legis.data)[1]
##D x0 <-... |
% Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/data.R
\docType{data}
\name{CH25PR17}
\alias{CH25PR17}
\title{CH25PR17}
\format{\preformatted{'data.frame': 48 obs. of 4 variables:
$ V1: num 72 74.6 67.4 72.8 72.1 76.9 74.8 73.3 75.2 73.8 ...
$ V2: int 1 1 1 1 1 1 1 1 1 1 ...
... | /man/CH25PR17.Rd | no_license | bryangoodrich/ALSM | R | false | false | 458 | rd | % Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/data.R
\docType{data}
\name{CH25PR17}
\alias{CH25PR17}
\title{CH25PR17}
\format{\preformatted{'data.frame': 48 obs. of 4 variables:
$ V1: num 72 74.6 67.4 72.8 72.1 76.9 74.8 73.3 75.2 73.8 ...
$ V2: int 1 1 1 1 1 1 1 1 1 1 ...
... |
library(tseries)
library(forecast)
library(magrittr)
set.seed(0)
#seed beállítása, hogy ugyanazok a pszeudorandom számaink legyenek
#1. Tárolófüggvény
dgp_parameterek<-function(tslength,nofts,noise,p,d,q){
return(c(tslength,nofts,noise,p,d,q))
}
#eltárolja a szimuláció paramétereit
#2. Adatgeneráló függvény
ts_... | /EFRP_EconometricswithR_Paulovics-Plesz.R | no_license | pleszboldi/EFRP_EconometricswithR_Plesz | R | false | false | 4,232 | r | library(tseries)
library(forecast)
library(magrittr)
set.seed(0)
#seed beállítása, hogy ugyanazok a pszeudorandom számaink legyenek
#1. Tárolófüggvény
dgp_parameterek<-function(tslength,nofts,noise,p,d,q){
return(c(tslength,nofts,noise,p,d,q))
}
#eltárolja a szimuláció paramétereit
#2. Adatgeneráló függvény
ts_... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/getGraphIdsInCorpus.R
\name{getGraphIdsInCorpus}
\alias{getGraphIdsInCorpus}
\title{Deprecated synonym for getTranscriptIdsInCorpus.}
\usage{
getGraphIdsInCorpus(labbcat.url, id)
}
\arguments{
\item{labbcat.url}{URL to the LaBB-CAT instance}
... | /man/getGraphIdsInCorpus.Rd | no_license | cran/nzilbb.labbcat | R | false | true | 696 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/getGraphIdsInCorpus.R
\name{getGraphIdsInCorpus}
\alias{getGraphIdsInCorpus}
\title{Deprecated synonym for getTranscriptIdsInCorpus.}
\usage{
getGraphIdsInCorpus(labbcat.url, id)
}
\arguments{
\item{labbcat.url}{URL to the LaBB-CAT instance}
... |
# Setup dependencies ------------------------------------------
library(shiny)
source("../predictions.R")
highest_order_ngram = 5
ngram.rankings = 5
# Replace with for loop based on configured highest_order_ngram
if (!exists("ngram_1")) {
ngram_1 <<- readRDS("../files/ngram_1_3_005_3_5.rds")
}
if (!exists("ngram_... | /Ngram/server.R | no_license | FreddieK/Coursera-JHU-Capstone | R | false | false | 1,076 | r | # Setup dependencies ------------------------------------------
library(shiny)
source("../predictions.R")
highest_order_ngram = 5
ngram.rankings = 5
# Replace with for loop based on configured highest_order_ngram
if (!exists("ngram_1")) {
ngram_1 <<- readRDS("../files/ngram_1_3_005_3_5.rds")
}
if (!exists("ngram_... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/tree_numbering.R
\name{RenumberTree}
\alias{RenumberTree}
\alias{RenumberEdges}
\alias{Reorder}
\alias{Cladewise}
\alias{Cladewise.phylo}
\alias{Cladewise.list}
\alias{Cladewise.multiPhylo}
\alias{Cladewise.matrix}
\alias{ApePostor... | /fuzzedpackages/TreeTools/man/Reorder.Rd | no_license | akhikolla/testpackages | R | false | true | 7,854 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/tree_numbering.R
\name{RenumberTree}
\alias{RenumberTree}
\alias{RenumberEdges}
\alias{Reorder}
\alias{Cladewise}
\alias{Cladewise.phylo}
\alias{Cladewise.list}
\alias{Cladewise.multiPhylo}
\alias{Cladewise.matrix}
\alias{ApePostor... |
output$network_hello <- renderVisNetwork({
# minimal example
nodes <- data.frame(id = 1:3)
edges <- data.frame(from = c(1,2), to = c(1,3))
visNetwork(nodes, edges)
})
output$code_network_hello <- renderText({
'
# in server.R :
output$network_hello <- renderVisNetwork({
# minimal exa... | /packrat/lib/x86_64-pc-linux-gnu/3.2.5/visNetwork/shiny/src/server/basic_server.R | permissive | harryprince/seamonster | R | false | false | 1,913 | r | output$network_hello <- renderVisNetwork({
# minimal example
nodes <- data.frame(id = 1:3)
edges <- data.frame(from = c(1,2), to = c(1,3))
visNetwork(nodes, edges)
})
output$code_network_hello <- renderText({
'
# in server.R :
output$network_hello <- renderVisNetwork({
# minimal exa... |
#Carrega os pacotes necessários
library(tidyverse)
library(lubridate)
library(jsonlite)
library(writexl)
#Cria um vetor para armazenar as séries desejadas
Cod_Serie <- c(22099, #PIB trimestral - Dados observados - Produto Interno Bruto a preços de mercado
22083, #PIB trimestral - Dados observados - Agro... | /Get_data.R | no_license | FernandoAlvesSilveira/Get_BCB_data | R | false | false | 2,165 | r | #Carrega os pacotes necessários
library(tidyverse)
library(lubridate)
library(jsonlite)
library(writexl)
#Cria um vetor para armazenar as séries desejadas
Cod_Serie <- c(22099, #PIB trimestral - Dados observados - Produto Interno Bruto a preços de mercado
22083, #PIB trimestral - Dados observados - Agro... |
## library("graph")
set.seed(0x12a9b)
randBAMGraph <- function(numNodes = 10 , numEdges = 10)
{
df <- graph:::randFromTo(numNodes, numEdges)
df$ft$weight = seq_len(numNodes)
g <- graphBAM(df$ft, nodes = df$nodes, edgemode = "directed")
g
}
make_smallBAM <- function() {
from = c("a", "a", "a", "x"... | /inst/unitTests/graphBAM_test.R | no_license | vgpprasad91/graph | R | false | false | 50,650 | r | ## library("graph")
set.seed(0x12a9b)
randBAMGraph <- function(numNodes = 10 , numEdges = 10)
{
df <- graph:::randFromTo(numNodes, numEdges)
df$ft$weight = seq_len(numNodes)
g <- graphBAM(df$ft, nodes = df$nodes, edgemode = "directed")
g
}
make_smallBAM <- function() {
from = c("a", "a", "a", "x"... |
rm(list=ls())
########################################
## packages
########################################
library(ggplot2)
library(dplyr)
library(reshape2)
# library(nlme)
########################################
## directories
########################################
wd <- "C:\\merrill\\status_priors"
fig_dir <-... | /life_history.R | no_license | merrillrudd/status_priors | R | false | false | 21,254 | r |
rm(list=ls())
########################################
## packages
########################################
library(ggplot2)
library(dplyr)
library(reshape2)
# library(nlme)
########################################
## directories
########################################
wd <- "C:\\merrill\\status_priors"
fig_dir <-... |
# Building a Prod-Ready, Robust Shiny Application.
#
# README: each step of the dev files is optional, and you don't have to
# fill every dev scripts before getting started.
# 01_start.R should be filled at start.
# 02_dev.R should be used to keep track of your development during the project.
# 03_deploy.R should b... | /dev/01_start.R | permissive | alberto-mateos-mo/amzreviewer | R | false | false | 1,877 | r | # Building a Prod-Ready, Robust Shiny Application.
#
# README: each step of the dev files is optional, and you don't have to
# fill every dev scripts before getting started.
# 01_start.R should be filled at start.
# 02_dev.R should be used to keep track of your development during the project.
# 03_deploy.R should b... |
test_that("last modification date", {
fs::file_create("foo")
# Notes: Had to set this to GMT otherwise I was getting a one off date error
today <- lubridate::ymd(lubridate::today(tz = "GMT"))
fs::file_touch("foo", today)
touch_date <- holepunch:::last_modification_date(".")
expect_identical(today, touch_dat... | /tests/testthat/test-last_modification_date.R | permissive | choldgraf/holepunch | R | false | false | 342 | r | test_that("last modification date", {
fs::file_create("foo")
# Notes: Had to set this to GMT otherwise I was getting a one off date error
today <- lubridate::ymd(lubridate::today(tz = "GMT"))
fs::file_touch("foo", today)
touch_date <- holepunch:::last_modification_date(".")
expect_identical(today, touch_dat... |
## ---- echo = FALSE-------------------------------------------------------
library(knitr)
opts_chunk$set(tidy.opts=list(width.cutoff=60),tidy=TRUE)
knitr::opts_chunk$set(comment = "#>", collapse = TRUE)
| /vignettes/CLI_guide.R | permissive | billchenxi/BaMORC | R | false | false | 205 | r | ## ---- echo = FALSE-------------------------------------------------------
library(knitr)
opts_chunk$set(tidy.opts=list(width.cutoff=60),tidy=TRUE)
knitr::opts_chunk$set(comment = "#>", collapse = TRUE)
|
dados <- read.csv("C:/Users/James Bond/Desktop/Gitlab/dsl/programs/python/Leitos_OP/tabela_micro_OP.csv")
grafico <- lm(formula = confirmados_totais ~ poly(index_data, degree = 4, raw=T), data = dados)
summary(grafico)
#Fazendo previsoes
plot(dados$index_data, dados$confirmados_totais)
inicio =109
fim = 120
novo_d... | /Códigos boletins/Micro_OP_R.R | no_license | Gabrieldomal/Covid-19-Quadril-tero-Ferr-fero-MG | R | false | false | 1,304 | r | dados <- read.csv("C:/Users/James Bond/Desktop/Gitlab/dsl/programs/python/Leitos_OP/tabela_micro_OP.csv")
grafico <- lm(formula = confirmados_totais ~ poly(index_data, degree = 4, raw=T), data = dados)
summary(grafico)
#Fazendo previsoes
plot(dados$index_data, dados$confirmados_totais)
inicio =109
fim = 120
novo_d... |
################################################################################
# Author: Petr Keil
# Email: pkeil@seznam.cz
# Date: April 26 2018
################################################################################
# Description: Here is where model SMOOTH is used to generate predictions to the
# regular... | /R/8.0_GAM_make_predictions_to_regular_grids_at_two_grains.r | no_license | lrcai/global_tree_S | R | false | false | 15,237 | r | ################################################################################
# Author: Petr Keil
# Email: pkeil@seznam.cz
# Date: April 26 2018
################################################################################
# Description: Here is where model SMOOTH is used to generate predictions to the
# regular... |
testlist <- list(sub = NULL, NULL, NULL, NULL, num_sub = 0L, s_ = integer(0), t_ = integer(0), x_ = numeric(0))
result <- do.call(MatchIt:::pairdistsubC,testlist)
str(result) | /MatchIt/inst/testfiles/pairdistsubC/libFuzzer_pairdistsubC/pairdistsubC_valgrind_files/1612738329-test.R | no_license | akhikolla/updatedatatype-list2 | R | false | false | 179 | r | testlist <- list(sub = NULL, NULL, NULL, NULL, num_sub = 0L, s_ = integer(0), t_ = integer(0), x_ = numeric(0))
result <- do.call(MatchIt:::pairdistsubC,testlist)
str(result) |
04928cc1604ff79fcc4cf52c20bede6b tlc01-nonuniform-depth-88.qdimacs 31240 83550 | /code/dcnf-ankit-optimized/Results/QBFLIB-2018/A1/Database/Miller-Marin/trafficlight-controller/tlc01-nonuniform-depth-88/tlc01-nonuniform-depth-88.R | no_license | arey0pushpa/dcnf-autarky | R | false | false | 78 | r | 04928cc1604ff79fcc4cf52c20bede6b tlc01-nonuniform-depth-88.qdimacs 31240 83550 |
##########################
# #
# Excercise 14 #
# #
##########################
# Load libraries
library(haven)
library(forecast)
# Import the dataset
dataset <- read_sas("/your_path/quarterly.sas7bdat")
# Generate the spread as: r5 - Tbill
spread = dataset... | /chapter2/excercise14.R | no_license | XiaoShiliu611/time-series-enders-R | R | false | false | 2,453 | r | ##########################
# #
# Excercise 14 #
# #
##########################
# Load libraries
library(haven)
library(forecast)
# Import the dataset
dataset <- read_sas("/your_path/quarterly.sas7bdat")
# Generate the spread as: r5 - Tbill
spread = dataset... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/package-HDclust.R
\docType{package}
\name{HDclust-package}
\alias{HDclust-package}
\alias{HDclust}
\title{Clustering high dimensional data with Hidden Markov Model on Variable Blocks}
\description{
Clustering of high dimensional data with Hid... | /fuzzedpackages/HDclust/man/HDclust-package.Rd | no_license | akhikolla/testpackages | R | false | true | 1,191 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/package-HDclust.R
\docType{package}
\name{HDclust-package}
\alias{HDclust-package}
\alias{HDclust}
\title{Clustering high dimensional data with Hidden Markov Model on Variable Blocks}
\description{
Clustering of high dimensional data with Hid... |
computeQTrigram<-function(word2,word3,frqTblTokenz, Trigram, biGms,
totalTokens,listTokens){
searchPtn<-paste0("(^|[^a-z])(",word2,"_",word3,"_)+")
#subset known trigrams from the trigrams dfm
frqTblKnownTrigram<-dfm_select(Trigram,pattern=searchPtn,selection="keep",
... | /capstoneProject/computeQTrigram.R | no_license | Vulcan-Logic/DSC10_Capstone_Project | R | false | false | 6,460 | r | computeQTrigram<-function(word2,word3,frqTblTokenz, Trigram, biGms,
totalTokens,listTokens){
searchPtn<-paste0("(^|[^a-z])(",word2,"_",word3,"_)+")
#subset known trigrams from the trigrams dfm
frqTblKnownTrigram<-dfm_select(Trigram,pattern=searchPtn,selection="keep",
... |
#' qPCR data table from Jimenez-Dominguez et al, Sci Rep, 2021; replicate 3_A
#' (perturbations of the ERs, RARs, LCoR, and RIP140 transcriptional network)
#'
#'@format A data frame with 8 rows (modules) and 17 variables (perturbations):
#' \describe{
#' \item{Modules}{Names of the modules}
#' \item{Et}{Ethanol}... | /R/estr3_A.R | no_license | bioinfo-ircm/aiMeRA | R | false | false | 1,467 | r | #' qPCR data table from Jimenez-Dominguez et al, Sci Rep, 2021; replicate 3_A
#' (perturbations of the ERs, RARs, LCoR, and RIP140 transcriptional network)
#'
#'@format A data frame with 8 rows (modules) and 17 variables (perturbations):
#' \describe{
#' \item{Modules}{Names of the modules}
#' \item{Et}{Ethanol}... |
test_that("rbindAll() works", {
L <- list(1:3, 4:6)
y <- rbindAll(L, nameColumn = "Name")
expect_is(y, "data.frame")
expect_true("Name" %in% names(y))
expect_identical(dim(y), c(2L, 4L))
L <- list(
A = data.frame(x = 1:2, y = 2:3),
B = data.frame(x = 1:3, y = 2:4)
)
L_unnamed <- unn... | /tests/testthat/test-function-rbindAll.R | permissive | KWB-R/kwb.utils | R | false | false | 1,053 | r | test_that("rbindAll() works", {
L <- list(1:3, 4:6)
y <- rbindAll(L, nameColumn = "Name")
expect_is(y, "data.frame")
expect_true("Name" %in% names(y))
expect_identical(dim(y), c(2L, 4L))
L <- list(
A = data.frame(x = 1:2, y = 2:3),
B = data.frame(x = 1:3, y = 2:4)
)
L_unnamed <- unn... |
dt<-read.table(file="data/household_power_consumption.txt",header=TRUE,sep=";"
,colClasses=(c("character","character","numeric","numeric","numeric","numeric","numeric","numeric","numeric"))
,nrows=2075259,na.strings=c("?",""))
require("lubridate")
datetime<-parse_date_time(paste(dt$Date,dt... | /plot3.R | no_license | mcassidy04/ExData_Plotting1 | R | false | false | 1,030 | r | dt<-read.table(file="data/household_power_consumption.txt",header=TRUE,sep=";"
,colClasses=(c("character","character","numeric","numeric","numeric","numeric","numeric","numeric","numeric"))
,nrows=2075259,na.strings=c("?",""))
require("lubridate")
datetime<-parse_date_time(paste(dt$Date,dt... |
rm(list=ls()) #clear all variables
library(ggplot2); library(plyr); library(dplyr); library(car); library(reshape); library(lme4); library(cowplot); library(stringi); library(scales); library(ggrepel)
load("~/friends-and-enemies/PostScript02.RData")
setwd("~/friends-and-enemies")
# Initial setup of VOISeR data ----
#... | /03-VOISeR-Naming-FINAL.R | no_license | sahil-luthra/friends-and-enemies | R | false | false | 22,222 | r | rm(list=ls()) #clear all variables
library(ggplot2); library(plyr); library(dplyr); library(car); library(reshape); library(lme4); library(cowplot); library(stringi); library(scales); library(ggrepel)
load("~/friends-and-enemies/PostScript02.RData")
setwd("~/friends-and-enemies")
# Initial setup of VOISeR data ----
#... |
#' Data.frame of parameter values
#'
#' @inheritParams simmiad
#' @param habitat_width Length of the edge of the habitat square
#' @param population_size Number of individual plants in the population,
#' derived from the habitat size and population density
#' @author Tom Ellis
#' @return A data.frame giving parameter n... | /R/parameter_table.R | permissive | ellisztamas/simmiad | R | false | false | 1,424 | r | #' Data.frame of parameter values
#'
#' @inheritParams simmiad
#' @param habitat_width Length of the edge of the habitat square
#' @param population_size Number of individual plants in the population,
#' derived from the habitat size and population density
#' @author Tom Ellis
#' @return A data.frame giving parameter n... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/retype.R
\name{retype}
\alias{retype}
\title{Retype Variable}
\usage{
retype(df, ...)
}
\arguments{
\item{df:}{data.frame with values to typecast}
\item{...:}{unquoted list alternating variables and datatypes to convert to}
}
\value{
Data.fr... | /man/retype.Rd | no_license | ftuhin2828/dataTools | R | false | true | 708 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/retype.R
\name{retype}
\alias{retype}
\title{Retype Variable}
\usage{
retype(df, ...)
}
\arguments{
\item{df:}{data.frame with values to typecast}
\item{...:}{unquoted list alternating variables and datatypes to convert to}
}
\value{
Data.fr... |
#' Return the average timestep in days
#'
#' @param datetimes a vector of date-times in POSIXct format from which to
#' compute the average timestep
#' @param format the format in which to return the timestep. 'mean' always
#' returns one value; 'unique' may return more than one depending on the
#' variation ... | /R/mm_get_timestep.R | permissive | lsdeel/streamMetabolizer | R | false | false | 3,717 | r | #' Return the average timestep in days
#'
#' @param datetimes a vector of date-times in POSIXct format from which to
#' compute the average timestep
#' @param format the format in which to return the timestep. 'mean' always
#' returns one value; 'unique' may return more than one depending on the
#' variation ... |
#' Generation of a Square-wave Burst Signal
#'
#' This function takes in numeric arguments for a customizable, square-wave burst shape. Each oscillation cycle is separated into three phases: a primary active phase, in which the oscillator resides at peak concentration, a secondary active phase, in which the oscillator ... | /R/SquareBurst.R | no_license | cran/OscillatorGenerator | R | false | false | 7,826 | r | #' Generation of a Square-wave Burst Signal
#'
#' This function takes in numeric arguments for a customizable, square-wave burst shape. Each oscillation cycle is separated into three phases: a primary active phase, in which the oscillator resides at peak concentration, a secondary active phase, in which the oscillator ... |
CPmodelChibReg = function(
data = ySIM,
K = K,
start = list(
mu = rnorm(K,0,1),
mu2 = rnorm(K,0,1),
sigma2 = abs(rnorm(K,0,1)),
#sigma2 = c(sigma2SIM,rep(20,Kmax)),
#st = rep(1:2,each=1000)[1:1500],
st = stSIM,
beta = 0.01,
pi = rdirichlet(1,rep(1,K)) ... | /cp_chib_reg_sh_general.R | no_license | sh0406/ff | R | false | false | 8,608 | r |
CPmodelChibReg = function(
data = ySIM,
K = K,
start = list(
mu = rnorm(K,0,1),
mu2 = rnorm(K,0,1),
sigma2 = abs(rnorm(K,0,1)),
#sigma2 = c(sigma2SIM,rep(20,Kmax)),
#st = rep(1:2,each=1000)[1:1500],
st = stSIM,
beta = 0.01,
pi = rdirichlet(1,rep(1,K)) ... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/LookmlModel.r
\name{LookmlModel}
\alias{LookmlModel}
\title{LookmlModel Class}
\description{
LookmlModel Class
LookmlModel Class
}
\section{Public fields}{
\if{html}{\out{<div class="r6-fields">}}
\describe{
\item{\code{name}}{}
\item{\code... | /man/LookmlModel.Rd | permissive | grepinsight/lookr | R | false | true | 3,012 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/LookmlModel.r
\name{LookmlModel}
\alias{LookmlModel}
\title{LookmlModel Class}
\description{
LookmlModel Class
LookmlModel Class
}
\section{Public fields}{
\if{html}{\out{<div class="r6-fields">}}
\describe{
\item{\code{name}}{}
\item{\code... |
#Case Study12
# load required packages from the assignment
library(dplyr)
library(ggplot2)
library(ggmap)
library(htmlwidgets)
library(widgetframe)
#Detailed Steps
#I downloaded these packages from the assignment
library(tidyverse)
library(rnoaa)
library(xts)
library(dygraphs)
d=meteo_tidy_ghcnd("USW00014733",
... | /week_12/case_study_12.R | no_license | geo511-2020/geo511-2020-tasks-hsare | R | false | false | 791 | r | #Case Study12
# load required packages from the assignment
library(dplyr)
library(ggplot2)
library(ggmap)
library(htmlwidgets)
library(widgetframe)
#Detailed Steps
#I downloaded these packages from the assignment
library(tidyverse)
library(rnoaa)
library(xts)
library(dygraphs)
d=meteo_tidy_ghcnd("USW00014733",
... |
testlist <- list(rates = numeric(0), thresholds = numeric(0), x = c(5.18571301874972e-320, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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(grattan::IncomeTax,testlist)
str(result) | /grattan/inst/testfiles/IncomeTax/libFuzzer_IncomeTax/IncomeTax_valgrind_files/1610382265-test.R | no_license | akhikolla/updated-only-Issues | R | false | false | 282 | r | testlist <- list(rates = numeric(0), thresholds = numeric(0), x = c(5.18571301874972e-320, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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(grattan::IncomeTax,testlist)
str(result) |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/f_highermomentsIV.R
\name{higherMomentsIV}
\alias{higherMomentsIV}
\title{Fitting Linear Models with Endogenous Regressors using Lewbel's Higher Moments Approach}
\usage{
higherMomentsIV(formula, data, verbose = TRUE)
}
\arguments{
\item{form... | /man/higherMomentsIV.Rd | no_license | mmeierer/REndo | R | false | true | 7,928 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/f_highermomentsIV.R
\name{higherMomentsIV}
\alias{higherMomentsIV}
\title{Fitting Linear Models with Endogenous Regressors using Lewbel's Higher Moments Approach}
\usage{
higherMomentsIV(formula, data, verbose = TRUE)
}
\arguments{
\item{form... |
### Data Science Capstone : Course Project
### ui.R file for the Shiny app
### Github repo : https://github.com/kapilkaushik2/capstone
suppressWarnings(library(shiny))
suppressWarnings(library(markdown))
shinyUI(navbarPage("Coursera Data Science Capstone: Course Project",
tabPanel("Predict the Next ... | /Capstone/ui.R | no_license | kapilkaushik2/capstone | R | false | false | 2,190 | r | ### Data Science Capstone : Course Project
### ui.R file for the Shiny app
### Github repo : https://github.com/kapilkaushik2/capstone
suppressWarnings(library(shiny))
suppressWarnings(library(markdown))
shinyUI(navbarPage("Coursera Data Science Capstone: Course Project",
tabPanel("Predict the Next ... |
## example of gfile
## we use a stack widget with the first card to upload the file, the second
## to show some simple summary.
w <- gwindow("gfile example")
sb <- gstatusbar("Powered by gWidgetsWWW2.rapache and rapache", cont=w)
sw <- gstackwidget(cont=w)
## page 1
page1 <- gvbox(cont=sw)
ghtml("Upload a csv file ... | /inst/examples/ex-gfile.R | no_license | jverzani/gWidgetsWWW2.rapache | R | false | false | 1,067 | r | ## example of gfile
## we use a stack widget with the first card to upload the file, the second
## to show some simple summary.
w <- gwindow("gfile example")
sb <- gstatusbar("Powered by gWidgetsWWW2.rapache and rapache", cont=w)
sw <- gstackwidget(cont=w)
## page 1
page1 <- gvbox(cont=sw)
ghtml("Upload a csv file ... |
library(openxlsx)
library(reshape)
library(plyr)
#library(dplyr)
########################## Set Admin variables ##########################
#What all to do right now
Make=1
Check=0
Save=1
FinalCB <- data.frame()
#List of counterbalances with lists assigned to conditions in the order given in CondNames
ListRot <- lis... | /MakeCounterbalance/TE_MakeCounterbalance.R | no_license | mrinmayik/TemporalExpectation | R | false | false | 19,478 | r | library(openxlsx)
library(reshape)
library(plyr)
#library(dplyr)
########################## Set Admin variables ##########################
#What all to do right now
Make=1
Check=0
Save=1
FinalCB <- data.frame()
#List of counterbalances with lists assigned to conditions in the order given in CondNames
ListRot <- lis... |
## SNMM_Start_Job_By_ID(filename_job_specifications,job_ID)
SNMM_Stan_Start_Job_By_ID <- function(filename_job_specifications,job_ID)
{
require("rstan")
job_specs <- read.csv(file=filename_job_specifications,header=TRUE,sep=";")
print(job_specs)
fn_datafile <- toString(job_specs$filename[job_ID])
data_snmm_th... | /SNMM_functions.R | no_license | cwachauf/BSNMM_rstan | R | false | false | 6,308 | r | ## SNMM_Start_Job_By_ID(filename_job_specifications,job_ID)
SNMM_Stan_Start_Job_By_ID <- function(filename_job_specifications,job_ID)
{
require("rstan")
job_specs <- read.csv(file=filename_job_specifications,header=TRUE,sep=";")
print(job_specs)
fn_datafile <- toString(job_specs$filename[job_ID])
data_snmm_th... |
# Yige Wu @ WashU 2017 Jan
# plot 3D/linear distance and co-phosphorylation correlation FDRs and coefficients
# directory and library ---------------------------------------------------
# for working on Kuan's mac
baseD = "/Users/khuang/Box\ Sync/PhD/proteogenomics/CPTAC_pan3Cancer/"
# # for working on Yige's mac
# b... | /phospho_network/hotspot3d/plot_2can_phospho_corr_and_distance_single.R | no_license | ding-lab/phosphoproteomics | R | false | false | 3,813 | r | # Yige Wu @ WashU 2017 Jan
# plot 3D/linear distance and co-phosphorylation correlation FDRs and coefficients
# directory and library ---------------------------------------------------
# for working on Kuan's mac
baseD = "/Users/khuang/Box\ Sync/PhD/proteogenomics/CPTAC_pan3Cancer/"
# # for working on Yige's mac
# b... |
library(readr)
library(dplyr)
library(stringr)
library(tools)
library(TraceQC)
library(fastqcr)
library(readr)
sra <- read_csv("./data/000_SraRunTable.txt") %>%
select(Run,`Library Name`)
qc_dir <- "./fastqc/"
fastq_dir <- "./data/020_fastq_by_identifier"
for (dir in list.dirs(fastq_dir)){
fastqc(dir,qc.dir=qc_... | /hgRNA-invivo/030_run_traceQC.R | no_license | LiuzLab/TraceQC-manuscript | R | false | false | 2,958 | r | library(readr)
library(dplyr)
library(stringr)
library(tools)
library(TraceQC)
library(fastqcr)
library(readr)
sra <- read_csv("./data/000_SraRunTable.txt") %>%
select(Run,`Library Name`)
qc_dir <- "./fastqc/"
fastq_dir <- "./data/020_fastq_by_identifier"
for (dir in list.dirs(fastq_dir)){
fastqc(dir,qc.dir=qc_... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/general_use_functions.R
\name{.ls.objects}
\alias{.ls.objects}
\title{List objects + their sizes:}
\usage{
.ls.objects(pos = 1, pattern, order.by, decreasing = FALSE,
head = FALSE, n = 5)
}
\description{
https://stackoverflow.com/questions/... | /epimapAUX/man/dot-ls.objects.Rd | no_license | cboix/EPIMAP_ANALYSIS | R | false | true | 331 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/general_use_functions.R
\name{.ls.objects}
\alias{.ls.objects}
\title{List objects + their sizes:}
\usage{
.ls.objects(pos = 1, pattern, order.by, decreasing = FALSE,
head = FALSE, n = 5)
}
\description{
https://stackoverflow.com/questions/... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/equilibrium_catch.R
\name{equilibrium_catch}
\alias{equilibrium_catch}
\title{Extract equilibrium catch}
\usage{
equilibrium_catch(SS_Dir, Fishery)
}
\description{
\code{equilibrium_catch} This function extracts the expected equilibrium catch... | /man/equilibrium_catch.Rd | no_license | HaikunXu/IATTCassessment | R | false | true | 323 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/equilibrium_catch.R
\name{equilibrium_catch}
\alias{equilibrium_catch}
\title{Extract equilibrium catch}
\usage{
equilibrium_catch(SS_Dir, Fishery)
}
\description{
\code{equilibrium_catch} This function extracts the expected equilibrium catch... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/bgx.model.dt.tree.R
\name{bgx.model.dt.tree}
\alias{bgx.model.dt.tree}
\title{Parse a boosted tree model text dump}
\usage{
bgx.model.dt.tree(feature_names = NULL, model = NULL, text = NULL,
trees = NULL, use_int_id = FALSE, ...)
}
\argumen... | /man/bgx.model.dt.tree.Rd | permissive | nalzok/tsoobgx | R | false | true | 3,439 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/bgx.model.dt.tree.R
\name{bgx.model.dt.tree}
\alias{bgx.model.dt.tree}
\title{Parse a boosted tree model text dump}
\usage{
bgx.model.dt.tree(feature_names = NULL, model = NULL, text = NULL,
trees = NULL, use_int_id = FALSE, ...)
}
\argumen... |
setup(options(lifecycle_verbosity = "quiet"))
teardown(options(lifecycle_verbosity = NULL))
test_that("combine handles NULL (#1596, #3365)", {
expect_equal(combine(list(NULL, 1, 2)), c(1, 2))
expect_equal(combine(list(1, NULL, 2)), c(1, 2))
expect_equal(combine(list(1, 2, NULL)), c(1, 2))
expect_equal(combine(... | /tests/testthat/test-deprec-combine.R | permissive | earowang/dplyr | R | false | false | 6,642 | r | setup(options(lifecycle_verbosity = "quiet"))
teardown(options(lifecycle_verbosity = NULL))
test_that("combine handles NULL (#1596, #3365)", {
expect_equal(combine(list(NULL, 1, 2)), c(1, 2))
expect_equal(combine(list(1, NULL, 2)), c(1, 2))
expect_equal(combine(list(1, 2, NULL)), c(1, 2))
expect_equal(combine(... |
#' Pipe sequence data
#'
#' The function sequence of all of the packages using magrittr pipes.
#' @format a list per source file of each magrittr chain found, with character
#' vector elements of the function names in the chain.
"pipes"
| /R/pipes.R | no_license | jimhester/predpipe | R | false | false | 237 | r | #' Pipe sequence data
#'
#' The function sequence of all of the packages using magrittr pipes.
#' @format a list per source file of each magrittr chain found, with character
#' vector elements of the function names in the chain.
"pipes"
|
\name{ifreq}
\alias{ifreq}
\title{Instantaneous frequency}
\description{
This function returns the instantaneous frequency (and/or phase) of a time wave
through the computation of the analytic signal (Hilbert transform).
}
\usage{
ifreq(wave, f, phase = FALSE, threshold = NULL,
plot = TRUE, xlab = "Time (s)", y... | /man/ifreq.Rd | no_license | dbs700/seewave | R | false | false | 3,000 | rd | \name{ifreq}
\alias{ifreq}
\title{Instantaneous frequency}
\description{
This function returns the instantaneous frequency (and/or phase) of a time wave
through the computation of the analytic signal (Hilbert transform).
}
\usage{
ifreq(wave, f, phase = FALSE, threshold = NULL,
plot = TRUE, xlab = "Time (s)", y... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/get_segments.R
\name{get_pw_segments}
\alias{get_pw_segments}
\title{Utility function to get segments (as character strings) from vector with cutpoints}
\usage{
get_pw_segments(x = NULL, cuts, right = FALSE, ordered_results = TRUE)
}
\argumen... | /Rpackages/gemtcPlus/man/get_pw_segments.Rd | permissive | Diarmuid78/Global-HTA-Evidence-Open | R | false | true | 575 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/get_segments.R
\name{get_pw_segments}
\alias{get_pw_segments}
\title{Utility function to get segments (as character strings) from vector with cutpoints}
\usage{
get_pw_segments(x = NULL, cuts, right = FALSE, ordered_results = TRUE)
}
\argumen... |
#' Prediction of Quantiles for Parametric Lifetime Distributions
#'
#' @description
#' This function predicts the quantiles of a parametric lifetime distribution
#' using the (log-)location-scale parameterization.
#'
#' @details
#' For a given set of parameters and specified probabilities the quantiles
#' of the chosen... | /R/predict.R | no_license | Tim-TU/weibulltools | R | false | false | 4,102 | r | #' Prediction of Quantiles for Parametric Lifetime Distributions
#'
#' @description
#' This function predicts the quantiles of a parametric lifetime distribution
#' using the (log-)location-scale parameterization.
#'
#' @details
#' For a given set of parameters and specified probabilities the quantiles
#' of the chosen... |
testlist <- list(A = structure(c(2.46058189628247e+77, 9.53818252170339e+295, 1.22810536108214e+146, 4.12396251261199e-221, 0, 0, 0), .Dim = c(1L, 7L)), B = structure(0, .Dim = c(1L, 1L)))
result <- do.call(multivariance:::match_rows,testlist)
str(result) | /multivariance/inst/testfiles/match_rows/AFL_match_rows/match_rows_valgrind_files/1613112158-test.R | no_license | akhikolla/updatedatatype-list3 | R | false | false | 257 | r | testlist <- list(A = structure(c(2.46058189628247e+77, 9.53818252170339e+295, 1.22810536108214e+146, 4.12396251261199e-221, 0, 0, 0), .Dim = c(1L, 7L)), B = structure(0, .Dim = c(1L, 1L)))
result <- do.call(multivariance:::match_rows,testlist)
str(result) |
ABOUT CYNTHIA | /ABOUT CYNTHIA.R | no_license | cynthiacho/intro_git_live | R | false | false | 13 | r | ABOUT CYNTHIA |
# Lab 1 exercise
install.packages("gcookbook")
install.packages("ggplot2")
plot(mtcars$wt, mtcars$mpg)
library(ggplot2)
qplot(mtcars$wt, mtcars$mpg)
qplot(wt, mpg, data=mtcars)
ggplot(mtcars, aes(x = wt, y= mpg)) + geom_point()
plot(pressure$temperature, pressure$pressure, type = "l")
points(pressure$temperature, p... | /Labs/Lab 1/lab1_part_VIZ_E.R | no_license | Dtrain27/DataAnalytics2021_Dominic_Schroeder | R | false | false | 7,056 | r | # Lab 1 exercise
install.packages("gcookbook")
install.packages("ggplot2")
plot(mtcars$wt, mtcars$mpg)
library(ggplot2)
qplot(mtcars$wt, mtcars$mpg)
qplot(wt, mpg, data=mtcars)
ggplot(mtcars, aes(x = wt, y= mpg)) + geom_point()
plot(pressure$temperature, pressure$pressure, type = "l")
points(pressure$temperature, p... |
cdfGenerator <- function(data, accuracy)
{
data <- data[!is.na(data)]
accuracy <- 10^accuracy
S <- seq(0,max(data),accuracy)
cdf <- numeric(length(S))
for(i in S)
{
stat <- sum(i > data)
cdf[i] <- stat
}
cdf <- cdf[cdf!=0]
cdf <- cdf/length(S)
return(cdf)
} | /Functions/CDFGeneratorFunction.R | no_license | rmcdonnell/Daphnia-Project | R | false | false | 285 | r | cdfGenerator <- function(data, accuracy)
{
data <- data[!is.na(data)]
accuracy <- 10^accuracy
S <- seq(0,max(data),accuracy)
cdf <- numeric(length(S))
for(i in S)
{
stat <- sum(i > data)
cdf[i] <- stat
}
cdf <- cdf[cdf!=0]
cdf <- cdf/length(S)
return(cdf)
} |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/column_functions.R
\name{make_column_classes}
\alias{make_column_classes}
\title{A function to provide default names for columns and ensure that
every column has a name}
\usage{
make_column_classes(n_cols, col_classes = NULL, partial_classes ... | /man/make_column_classes.Rd | no_license | antonmalko/ibextor | R | false | true | 1,817 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/column_functions.R
\name{make_column_classes}
\alias{make_column_classes}
\title{A function to provide default names for columns and ensure that
every column has a name}
\usage{
make_column_classes(n_cols, col_classes = NULL, partial_classes ... |
source("prep_data.R")
library(party)
library(rattle)
library(rpart.plot)
train_data_Raw <- read.csv("C:/Users/shikhagarg.CORP/Downloads/ML with BD/kaggle/titanic/train.csv")
test_data_Raw <- read.csv("C:/Users/shikhagarg.CORP/Downloads/ML with BD/kaggle/titanic/test.csv")
train_data_prep <- prepare_Data(train_d... | /titanic1.R | no_license | shikhagarg0192/Kaggle_Practice | R | false | false | 1,028 | r | source("prep_data.R")
library(party)
library(rattle)
library(rpart.plot)
train_data_Raw <- read.csv("C:/Users/shikhagarg.CORP/Downloads/ML with BD/kaggle/titanic/train.csv")
test_data_Raw <- read.csv("C:/Users/shikhagarg.CORP/Downloads/ML with BD/kaggle/titanic/test.csv")
train_data_prep <- prepare_Data(train_d... |
psql_pt_config <- function(con = NULL){
if (is.null(con)){
stop("Você deve fornecer uma conexão válida")
}
q1 <- glue::glue_sql("CREATE EXTENSION unaccent",.con= con)
DBI::dbExecute(con,q1)
q2 <- glue::glue_sql("CREATE EXTENSION pg_trgm",.con = con)
DBI::dbExecute(con,q2)
q3 <- glue::glue_sql("C... | /R/psql_pt_config.R | no_license | jjesusfilho/FullTextSearch | R | false | false | 976 | r | psql_pt_config <- function(con = NULL){
if (is.null(con)){
stop("Você deve fornecer uma conexão válida")
}
q1 <- glue::glue_sql("CREATE EXTENSION unaccent",.con= con)
DBI::dbExecute(con,q1)
q2 <- glue::glue_sql("CREATE EXTENSION pg_trgm",.con = con)
DBI::dbExecute(con,q2)
q3 <- glue::glue_sql("C... |
pacman::p_load(rstan, dplyr, data.table, broom)
source("functions/JPLP_functions.R")
N_sim = 1000
dt = sim_mul_jplp(kappa = 0.8, beta = 1.2, theta = 2, n_shift = 10)
fit = stan("stan/jplp_simple.stan",
chains = 1, iter = 3000, refresh = 0,
data = dt$stan_dt, seed = 123)
f_result = pull_use("beta... | /scale_up_sim_code/JPLP.R | no_license | caimiao0714/Reliability_sim | R | false | false | 3,496 | r | pacman::p_load(rstan, dplyr, data.table, broom)
source("functions/JPLP_functions.R")
N_sim = 1000
dt = sim_mul_jplp(kappa = 0.8, beta = 1.2, theta = 2, n_shift = 10)
fit = stan("stan/jplp_simple.stan",
chains = 1, iter = 3000, refresh = 0,
data = dt$stan_dt, seed = 123)
f_result = pull_use("beta... |
# Set the working directory.
setwd("/Users/abhishek/Downloads/fashion")
#Import training data and test data
fashion_data_train <- read.csv("fashion_train.csv")
fashion_data_test <- read.csv("fashion_test.csv")
#Labeling each column with relevent name.
col_name <- c("label",sprintf("pixel%02d", seq(1,784))) #initializ... | /Code.R | no_license | abhishek-bose-cs/Image_Recogization_Using_Logistic-Regression_in_R | R | false | false | 9,530 | r | # Set the working directory.
setwd("/Users/abhishek/Downloads/fashion")
#Import training data and test data
fashion_data_train <- read.csv("fashion_train.csv")
fashion_data_test <- read.csv("fashion_test.csv")
#Labeling each column with relevent name.
col_name <- c("label",sprintf("pixel%02d", seq(1,784))) #initializ... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/test.R
\name{test-links}
\alias{test-links}
\title{Test case: links}
\description{
\if{html}{\out{<div class="r">}}\preformatted{magrittr::subtract(10, 1)
}\if{html}{\out{</div>}}\preformatted{## [1] 9
}
}
\examples{
magrittr::subtract(10, 1)... | /man/test-links.Rd | permissive | fangzhou-xie/pkgdown | R | false | true | 691 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/test.R
\name{test-links}
\alias{test-links}
\title{Test case: links}
\description{
\if{html}{\out{<div class="r">}}\preformatted{magrittr::subtract(10, 1)
}\if{html}{\out{</div>}}\preformatted{## [1] 9
}
}
\examples{
magrittr::subtract(10, 1)... |
# READ AND FORMAT DATA ------------------------------------------------------------------------------------------------
## yooo heres the path: my.peptide.data <- read_maxquant("~/Box/CellBio-GoldfarbLab/Users/Ria Jasuja/modificationSpecificPeptides.txt", "TMT10-K", "TMT10-Nterm", c("Acetyl (Protein N-term)"), "Phosp... | /R/FormatData.R | no_license | GoldfarbLab/CPTACQC | R | false | false | 5,894 | r | # READ AND FORMAT DATA ------------------------------------------------------------------------------------------------
## yooo heres the path: my.peptide.data <- read_maxquant("~/Box/CellBio-GoldfarbLab/Users/Ria Jasuja/modificationSpecificPeptides.txt", "TMT10-K", "TMT10-Nterm", c("Acetyl (Protein N-term)"), "Phosp... |
PCA_PropVar <- function(pca, numb_components = NULL, barplot = FALSE, main_plot = NULL) {
#input: - pca: object of class PCA, created by the PCA function
# - numb_components: number for principal components for which the proportional variance should be computed
# - barplot: boolean, if TRUE a barpl... | /R/PCA_PropVar.R | no_license | manuhuth/PCR-Parameter-Variance-Analysis | R | false | false | 1,169 | r | PCA_PropVar <- function(pca, numb_components = NULL, barplot = FALSE, main_plot = NULL) {
#input: - pca: object of class PCA, created by the PCA function
# - numb_components: number for principal components for which the proportional variance should be computed
# - barplot: boolean, if TRUE a barpl... |
# Pacotes ------------------------------------------------------------------
library(ggplot2)
library(tidymodels)
library(ISLR2)
# Dados -------------------------------------------------------------------
data("Hitters")
#Hitters <- na.omit(Hitters)
# base treino e teste --------------------------------------------... | /exemplos/03-cross-validation.R | no_license | curso-r/202108-intro-ml | R | false | false | 2,994 | r | # Pacotes ------------------------------------------------------------------
library(ggplot2)
library(tidymodels)
library(ISLR2)
# Dados -------------------------------------------------------------------
data("Hitters")
#Hitters <- na.omit(Hitters)
# base treino e teste --------------------------------------------... |
## SPATIAL
library(sp)
library(rgeos)
library(raster)
library(rgdal)
library(maptools)
## DATA MANAGEMENT
library(tidyverse)
library(skimr)
library(patchwork)
library(readxl)
# library(zoo)
library(pryr)
## PLOTTING
library(scales)
library(units)
library(viridis)
library(extrafont)
library(gtable)
library(grid)
libra... | /code/natl_spp_plots_raster.R | no_license | jeremyash/tree_CL | R | false | false | 13,391 | r | ## SPATIAL
library(sp)
library(rgeos)
library(raster)
library(rgdal)
library(maptools)
## DATA MANAGEMENT
library(tidyverse)
library(skimr)
library(patchwork)
library(readxl)
# library(zoo)
library(pryr)
## PLOTTING
library(scales)
library(units)
library(viridis)
library(extrafont)
library(gtable)
library(grid)
libra... |
PLOT<-function() {
#################################################################################################################################
# Step 9: Print the BRAT table, with values ----
# this should be the same as Figure 2 in the manuscipt
# run the below code (up to Step 9b) to make a crude output f... | /modules/BRATframework/R/PLOT.R | no_license | StewartResearch/BRAT_CaribouCalculations | R | false | false | 19,293 | r | PLOT<-function() {
#################################################################################################################################
# Step 9: Print the BRAT table, with values ----
# this should be the same as Figure 2 in the manuscipt
# run the below code (up to Step 9b) to make a crude output f... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/summarize.R
\name{summarize_ce}
\alias{summarize_ce}
\title{Summarize costs and effectiveness}
\usage{
summarize_ce(costs, qalys, by_grp = FALSE)
}
\arguments{
\item{costs}{Simulated costs by category (objects of class \code{\link{costs}}).}
... | /man/summarize_ce.Rd | no_license | jeff-m-sullivan/hesim | R | false | true | 1,475 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/summarize.R
\name{summarize_ce}
\alias{summarize_ce}
\title{Summarize costs and effectiveness}
\usage{
summarize_ce(costs, qalys, by_grp = FALSE)
}
\arguments{
\item{costs}{Simulated costs by category (objects of class \code{\link{costs}}).}
... |
#' Prior Definitions for \pkg{brms} Models
#'
#' Define priors for specific parameters or classes of parameters
#'
#' @param prior A character string defining a distribution in \pkg{Stan} language
#' @param class The parameter class. Defaults to \code{"b"} (fixed effects).
#' See 'Details' for other valid parameter ... | /R/priors.R | no_license | hoardboard/brms | R | false | false | 46,738 | r | #' Prior Definitions for \pkg{brms} Models
#'
#' Define priors for specific parameters or classes of parameters
#'
#' @param prior A character string defining a distribution in \pkg{Stan} language
#' @param class The parameter class. Defaults to \code{"b"} (fixed effects).
#' See 'Details' for other valid parameter ... |
# Practice Exercise 2 is about group_by(), summarise(), and ungroup().
# There is a data set called "data_gutenberg100_clean.csv" that contains
# the cleaned data (i.e., what the data should look like at the end of
# Exercise 1). Read that data into R.
#
# Use group_by() and summarise() to create a new tibble called ... | /static/dancing/practice_wrangling_02.R | no_license | djnavarro/robust-tools | R | false | false | 878 | r | # Practice Exercise 2 is about group_by(), summarise(), and ungroup().
# There is a data set called "data_gutenberg100_clean.csv" that contains
# the cleaned data (i.e., what the data should look like at the end of
# Exercise 1). Read that data into R.
#
# Use group_by() and summarise() to create a new tibble called ... |
#' @export
populateShinyApp <- function(outputDirectory = './ShinyApp',
shinyDirectory,
resultDirectory,
minCellCount = 10,
databaseName = 'sharable name of development data'){
#check inputs
if(mis... | /SimpleAbxBetterChoice_IP/SimpleABCceftriaxone/R/populateShinyApp.R | no_license | ABMI/AbxBetterChoice | R | false | false | 3,769 | r | #' @export
populateShinyApp <- function(outputDirectory = './ShinyApp',
shinyDirectory,
resultDirectory,
minCellCount = 10,
databaseName = 'sharable name of development data'){
#check inputs
if(mis... |
library(shiny)
library(data.table)
library(dplyr)
library(tidyr)
library(rsconnect)
library(readxl)
funds <- read_xlsx('vanguard.xlsx', range = 'B2:Z221')
returns <- funds %>%
filter(fund_type == 'Domestic Stock') %>%
select(fund_name, fund_type, fund_category, one_year,
five_year, ten_year, beta)
ret... | /global.R | no_license | Jello95/Project_Vanguard | R | false | false | 1,240 | r | library(shiny)
library(data.table)
library(dplyr)
library(tidyr)
library(rsconnect)
library(readxl)
funds <- read_xlsx('vanguard.xlsx', range = 'B2:Z221')
returns <- funds %>%
filter(fund_type == 'Domestic Stock') %>%
select(fund_name, fund_type, fund_category, one_year,
five_year, ten_year, beta)
ret... |
# The City of Lights
#
# Graphing marine marauding using night lights
# at the edge of the world
# load required packages
library(tidyverse) # plotting and data wrangling
library(raster) # to load raster data exported from GEE
library(sf) # vector processing + plotting
library(rnaturalearth) # fetch geographic data
l... | /analysis/city_of_lights_peru.R | no_license | khufkens/city_of_lights | R | false | false | 2,669 | r | # The City of Lights
#
# Graphing marine marauding using night lights
# at the edge of the world
# load required packages
library(tidyverse) # plotting and data wrangling
library(raster) # to load raster data exported from GEE
library(sf) # vector processing + plotting
library(rnaturalearth) # fetch geographic data
l... |
library(ape)
testtree <- read.tree("11624_0.txt")
unrooted_tr <- unroot(testtree)
write.tree(unrooted_tr, file="11624_0_unrooted.txt") | /codeml_files/newick_trees_processed_and_cleaned/11624_0/rinput.R | no_license | DaniBoo/cyanobacteria_project | R | false | false | 137 | r | library(ape)
testtree <- read.tree("11624_0.txt")
unrooted_tr <- unroot(testtree)
write.tree(unrooted_tr, file="11624_0_unrooted.txt") |
#' create_fbtrait_config
#'
#' For Android fieldbook app
#'
#' @param fieldbook a fieldbook
#' @param dictionary a dictionary
#' @importFrom magrittr '%>%'
#'
#' @return a dataframe
#' @export
create_fbtrait_config <- function(fieldbook, dictionary){
#print(str(fieldbook))
#print(str(dictionary))
fbn = names(fiel... | /R/create_fbtrait_config.R | no_license | c5sire/fbdesign | R | false | false | 2,224 | r | #' create_fbtrait_config
#'
#' For Android fieldbook app
#'
#' @param fieldbook a fieldbook
#' @param dictionary a dictionary
#' @importFrom magrittr '%>%'
#'
#' @return a dataframe
#' @export
create_fbtrait_config <- function(fieldbook, dictionary){
#print(str(fieldbook))
#print(str(dictionary))
fbn = names(fiel... |
#examining data (need to have run data set-up script beforehand)
structure(femweights)
length(femweights$Bodyweight)
#extracting specific entries
femweights[12,2]
femweights$Bodyweight[11]
#performing a function on extracted entries
mean(femweights$Bodyweight[13:24])
#working with sample(), but choosing a specific v... | /Statistics and Data Visualization/Code/Assessment 1.R | no_license | rghansen/R-course | R | false | false | 433 | r | #examining data (need to have run data set-up script beforehand)
structure(femweights)
length(femweights$Bodyweight)
#extracting specific entries
femweights[12,2]
femweights$Bodyweight[11]
#performing a function on extracted entries
mean(femweights$Bodyweight[13:24])
#working with sample(), but choosing a specific v... |
library(shiny)
library(googleVis)
library(d3heatmap)
source("helpers.R")
api_key <- "api-key=4afa5e239fc8c4847a7f7fc0b537d285:2:72422982"
base_url <- "http://api.nytimes.com/svc/events/v2/listings.json?"
coordinate <- list(nyt = "40.756146,-73.99021")
shinyServer(function(input, output, session) {
retrieve... | /server.R | no_license | SYAN83/NYT_Event_Finder | R | false | false | 6,920 | r | library(shiny)
library(googleVis)
library(d3heatmap)
source("helpers.R")
api_key <- "api-key=4afa5e239fc8c4847a7f7fc0b537d285:2:72422982"
base_url <- "http://api.nytimes.com/svc/events/v2/listings.json?"
coordinate <- list(nyt = "40.756146,-73.99021")
shinyServer(function(input, output, session) {
retrieve... |
#' Files for each hemisphere sea ice concentration (25km)
#'
#' NSIDC passive microwave sea ice concentration since 1978.
#'
#' Time series has been expanded to be daily, by infilling a date for any missing,
#' with this indicated on the `miss` column.
#'
#' @param ... ignored for now
#' @param .local_root allows local... | /R/nsidc.R | permissive | AustralianAntarcticDivision/seaice | R | false | false | 8,721 | r | #' Files for each hemisphere sea ice concentration (25km)
#'
#' NSIDC passive microwave sea ice concentration since 1978.
#'
#' Time series has been expanded to be daily, by infilling a date for any missing,
#' with this indicated on the `miss` column.
#'
#' @param ... ignored for now
#' @param .local_root allows local... |
#############################################
library("Matrix")
library("geigen")
library("rARPACK")
library(maps)
library(WDI)
library(RColorBrewer)
library("maptools")
source("Preprocess.R")
source("SpectralClustering.R")
source("Postprocess.R")
######################################################
# speCluster()... | /main.R | no_license | cont-limno/SpectralClustering4Regions | R | false | false | 4,053 | r | #############################################
library("Matrix")
library("geigen")
library("rARPACK")
library(maps)
library(WDI)
library(RColorBrewer)
library("maptools")
source("Preprocess.R")
source("SpectralClustering.R")
source("Postprocess.R")
######################################################
# speCluster()... |
#' Genomic coordinate to chromosome arm
#'
#' Returns chromosome arms for given chromosome and genomic position.
#' Currently not implemented and returns NULL.
#'
#' @param chromosome Character or numeric vector, with chromosome of genomic coordinate
#' @param position Numeric vector, with genomic position within chr... | /R/cytobands.R | permissive | arnijohnsen/arjtools | R | false | false | 1,605 | r | #' Genomic coordinate to chromosome arm
#'
#' Returns chromosome arms for given chromosome and genomic position.
#' Currently not implemented and returns NULL.
#'
#' @param chromosome Character or numeric vector, with chromosome of genomic coordinate
#' @param position Numeric vector, with genomic position within chr... |
#:# libraries
library(digest)
library(mlr)
library(OpenML)
library(farff)
#:# config
set.seed(1)
#:# data
dataset <- getOMLDataSet(data.name = "steel-plates-fault")
head(dataset$data)
#:# preprocessing
head(dataset$data)
#:# model
task = makeClassifTask(id = "task", data = dataset$data, target = "Class")
lrn = make... | /models/openml_steel-plates-fault/classification_Class/ab0c0a8e1e531620c33e4723cbd080fe/code.R | no_license | pysiakk/CaseStudies2019S | R | false | false | 713 | r | #:# libraries
library(digest)
library(mlr)
library(OpenML)
library(farff)
#:# config
set.seed(1)
#:# data
dataset <- getOMLDataSet(data.name = "steel-plates-fault")
head(dataset$data)
#:# preprocessing
head(dataset$data)
#:# model
task = makeClassifTask(id = "task", data = dataset$data, target = "Class")
lrn = make... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/read.R
\name{read}
\alias{read}
\title{Read NetCDF data from global inventories}
\source{
Read abbout EDGAR at http://edgar.jrc.ec.europa.eu and MACCITY at
http://accent.aero.jussieu.fr/MACC_metadata.php
}
\usage{
read(
file = fi... | /man/read.Rd | no_license | cran/EmissV | R | false | true | 5,015 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/read.R
\name{read}
\alias{read}
\title{Read NetCDF data from global inventories}
\source{
Read abbout EDGAR at http://edgar.jrc.ec.europa.eu and MACCITY at
http://accent.aero.jussieu.fr/MACC_metadata.php
}
\usage{
read(
file = fi... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/supervised.R
\name{mbpls}
\alias{mbpls}
\title{Multiblock Partial Least Squares - MB-PLS}
\usage{
mbpls(X, Y, ncomp = 1, scale = FALSE, ...)
}
\arguments{
\item{X}{\code{list} of input blocks.}
\item{Y}{\code{matrix} of responses.}
\item{nc... | /man/mbpls.Rd | no_license | minghao2016/multiblock | R | false | true | 2,254 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/supervised.R
\name{mbpls}
\alias{mbpls}
\title{Multiblock Partial Least Squares - MB-PLS}
\usage{
mbpls(X, Y, ncomp = 1, scale = FALSE, ...)
}
\arguments{
\item{X}{\code{list} of input blocks.}
\item{Y}{\code{matrix} of responses.}
\item{nc... |
#:# libraries
library(digest)
library(mlr)
library(OpenML)
library(farff)
#:# config
set.seed(1)
#:# data
dataset <- getOMLDataSet(data.name = "heart-statlog")
head(dataset$data)
#:# preprocessing
head(dataset$data)
#:# model
task = makeClassifTask(id = "task", data = dataset$data, target = "class")
lrn = makeLearn... | /models/openml_heart-statlog/classification_class/1619fdc149d64b6174a19c3a0af8cb26/code.R | no_license | pysiakk/CaseStudies2019S | R | false | false | 749 | r | #:# libraries
library(digest)
library(mlr)
library(OpenML)
library(farff)
#:# config
set.seed(1)
#:# data
dataset <- getOMLDataSet(data.name = "heart-statlog")
head(dataset$data)
#:# preprocessing
head(dataset$data)
#:# model
task = makeClassifTask(id = "task", data = dataset$data, target = "class")
lrn = makeLearn... |
## The following code is part of the example scripts included
## in the "Soil Organic Carbon Mapping Cookbook"
## @knitr optional-Merging
profiles <- read.csv("data/dataproc_profiles.csv")
topsoils <- read.csv("data/dataproc.csv")
# column names could be different, but the units and order has
# to be the same! Becau... | /code/optional-Merging.R | no_license | anhnguyendepocen/SOC-Mapping-Cookbook | R | false | false | 720 | r | ## The following code is part of the example scripts included
## in the "Soil Organic Carbon Mapping Cookbook"
## @knitr optional-Merging
profiles <- read.csv("data/dataproc_profiles.csv")
topsoils <- read.csv("data/dataproc.csv")
# column names could be different, but the units and order has
# to be the same! Becau... |
require(splines)
require(Matrix)
#' Spline function with 1 continuous dimension and 1 discrete dimension defined on finite Time
#'
#' Creates a functional representation for a 1 dimensional splines indexed by a discrete variable and time.
#' time is discrete and assumed to end at period T. This functional is useful f... | /R/F_SplineTime1D.r | no_license | SunRonghe/mpeccable | R | false | false | 4,001 | r |
require(splines)
require(Matrix)
#' Spline function with 1 continuous dimension and 1 discrete dimension defined on finite Time
#'
#' Creates a functional representation for a 1 dimensional splines indexed by a discrete variable and time.
#' time is discrete and assumed to end at period T. This functional is useful f... |
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