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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
630d467dfc5f7b9babd369ab4716d0015355deb5 | 546fe376d00b978637ab9328ec351be8669e76ea | /HMM.DM.code/DMR.combine.R | 5377234f48da129df9f8f82b1f69130603c445ef | [] | no_license | Maria-831/HMM-DM | a67d7da9767d376ea2a14d43a291a4a8564b5194 | 502b458107e9cecfb3a9df155c796a21513e83e5 | refs/heads/master | 2021-06-01T01:32:28.829456 | 2016-03-24T04:06:06 | 2016-03-24T04:06:06 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 6,979 | r | DMR.combine.R | DMR.combine<-function( DM.type, regions, chr.DM.status.matrix, raw.CG, distance.threshold, num.CG.between, posterior.threshold, empty.CG)
{
# This function is used to further combine small regions generated from chr.DM.region.by.CG.ver3. It is called by DM.region.combine.ver2().
# 1) DM.type, the type of DM ... |
69ece038da6b11b4f298473046097170568f5bf9 | d4d2d370f8cb50e002a3489d2e2b9186651ef92f | /tests/testthat/test-config_file.R | dff2cdb383a03e42d526b986da3409d9ceff6bf3 | [] | no_license | momeara/RosettaFeatures | 2c45012b042a76b0176a0924f1cc60fe3ba06e8b | 2700b0735071971bbd2af91a6b1e7454ceeaa2a6 | refs/heads/master | 2021-01-19T03:54:05.386349 | 2017-03-24T14:07:21 | 2017-03-24T14:07:21 | 47,008,643 | 1 | 3 | null | 2016-06-16T23:00:32 | 2015-11-28T03:28:34 | R | UTF-8 | R | false | false | 687 | r | test-config_file.R | context("Configuration File")
test_that("A simple configuration file is parsed correctly", {
verbose = T
config_filename <- "test-config_file__analysis_configuration.json"
configuration <- load_config_file(config_filename, verbose=verobse)
configuration <- initialize_output_dir(configuration, verbose)
db_engin... |
f28407f4638f43ec9aed7a3f6ae3cbd07617cfac | e37c5cab4bb89439714b24f9f29e4137f0a812fc | /Shopee_Shiny/global.R | a9688532f6dde938255f0691bef1c0923ff01955 | [] | no_license | a5347354/OrderAnalysis | c3046c74e143a2868cf2e8a94ba00b68b7171edf | d531bb26f4d6143915ef51a6d6f2f44f12dd46e7 | refs/heads/master | 2020-05-14T14:52:06.361961 | 2019-04-18T03:33:47 | 2019-04-18T03:33:47 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,979 | r | global.R | library(rvest)
orders = read.csv("korean10146.shopee-order.csv")
orders = orders[,-c(1,2,3,4,11,12,13,17)]
as.character.Date(orders$訂單成立時間)
#排序
orders = orders[order(orders$訂單成立時間),]
#取出寄送方式當作類別
categories = unique(orders$寄送方式) %>% as.vector()
#產品
products = c("養樂多軟糖",
"怪獸",
"火雞辣拌麵",
... |
ed7825e9246dd584dd66d65e3d558e3adc17a5a8 | b06d3f5fc175450710c81e76370bb710698b7cda | /Day5/Shiny package in R/using_renderplot_in_shiny/ui.R | 4f526f90b66e153272fd6236d17733f087d94747 | [] | no_license | pritamnegi/Learning-R | d496a7463df345bf184ec379c6a44a72f3863288 | 8b3207c9038585457828e944f199ea44ca2cdc17 | refs/heads/master | 2021-05-06T07:21:30.187234 | 2017-12-17T07:34:35 | 2017-12-17T07:34:35 | 113,953,585 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 573 | r | ui.R | library(shiny)
fluidPage(
titlePanel(h3("Plotting iris dataset using render plot function", align="center")),
sidebarLayout(
sidebarPanel(
selectInput("var", "Select the variable name from iris data set", choices = c("Sepal.Length"=1, "Sepal.Width"=2, "Petal.Length"=3, "Petal.Width"=4)),
br(),
... |
f6945ff61c5d46c02b00381e51adeb93d24596fd | 3600d3dfcb7d6ac5b15524977d7ad36c4e94fb3e | /Plant_family_key.R | ce45619398dd2de086467f3d6f4ae77b06441fe1 | [] | no_license | HeatherKates/Interactive_plant_key | e34ccb19308cf0b982c9e4b84656db064161f9dc | 300991d4ce41e79e09a0bea3bc58b97a864d9fb8 | refs/heads/master | 2021-05-29T02:46:31.212507 | 2015-04-24T16:10:20 | 2015-04-24T16:10:20 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,577 | r | Plant_family_key.R | library(stringr)
plant_families <- read.csv(file="Plant_families_for_R.csv")
##Getting information about distribution of plant characteristics##
###################################################################
#What proportion of plant families are woody?
prop <- nrow(subset(plant_families, habit == "woody"))/(nro... |
4ddbaf6300a8b2cb514d0836b3adf8309631e035 | 5b86ed92bd925fa05f56dedfdd97f70ae95de984 | /r/trading.R | 33cf88bd9cf9ae9186eaf0c456207d95f006619f | [
"MIT"
] | permissive | j-a-m-l/.dot | c310deaf2c2b748c427d590ac7f20daa489215d2 | 2a0f527c96c3cd7956a81bcb116326480b99bcae | refs/heads/master | 2021-10-22T00:45:18.411681 | 2021-10-21T15:41:52 | 2021-10-21T15:41:52 | 4,156,546 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 642 | r | trading.R | arkBtc <- function (arkEur, btcEur) {
arkEur / btcEur
}
binanceFee <- 0.1
bitfinexFee <- 0.1
bl3pFee <- 0.25 # + 0.01€ per order
cossFee <- 0.2
krakenFee <- 0.16
livecoinFee <- 0.18
sell <- function (price, amount, fee = krakenFee) {
(100 - fee) / 100 * price * amount
}
buy <- function (price, amount, fee = krak... |
545944323b259fba864238fb9e161350198c26aa | 3556b4217c921637cc7b7566c0d1b4f9bd1316c2 | /Fonctions/optimFunction.R | d95cb16e23211b638b77edf19fe9c39527008dec | [] | no_license | ehbihenscoding/MultiFiTimeSeries | f24b47c32ec8a456e2739e5963e826a24b5f6f29 | 2300500a0546138ef6318119e05ac2d688baaac8 | refs/heads/master | 2023-04-18T16:41:52.488958 | 2022-01-10T08:07:17 | 2022-01-10T08:07:17 | 215,967,008 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,609 | r | optimFunction.R | Matern52<-function(distances){
return = (1+sqrt(5)*distances+5/3*distances^2)*exp(-sqrt(5)*distances) # OK
}
### Calcule de la dérivé pour amméliorrer l'optimisaton
Matern52der<-function(x){
return = (sqrt(5)+5/3*x)*exp(-sqrt(5)*x) + sqrt(5)*(1+sqrt(5)*x+5/3*x^2)*exp(-sqrt(5)*x) # OK
}
covMatern <- function(z,y... |
24c70fde1a9c880f9811101cde7200aad80d8051 | 768f032aebf66e19997f1d049137e55cafc93c5f | /Codes/DESBED.R | 7da1d2aeeec804882881d36633e23640988ddce7 | [] | no_license | jairpaulino/TS-DES | 6dae0f0b62510eebe1346ea22c0195b104a70e7b | e9c1c4e5e52431761adad2e04978efc45b54db8d | refs/heads/master | 2023-05-02T23:25:43.801590 | 2021-05-25T18:48:41 | 2021-05-25T18:48:41 | 322,049,364 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 8,950 | r | DESBED.R | DESBED = NULL; DESBED_01 = NULL;
DESBED_02 = NULL; DESBED_03 = NULL
DESBED_04 = NULL; DESBED_05 = NULL
m = length(y_trainData)
n = length(y_allData)
for (j in (m+1):n){#j=m+1
allCandidates = X_allData
# calcula a distMin 01
distVector = NULL
distMin = 1e10
distMinIndex = NULL
for (i in 1:m){ #i=1
... |
ca416dc96b4a4f503aec4466cbbe0bf19b26b555 | d3c5f3ea6506d8fdadeb04b4182c93803c140e09 | /code/1-basicmapping.R | ace352fcdb136be73c499dac9a05e4acc0311cf9 | [] | no_license | TravelersLab/ParliamentaryTravel | 9d80b99675f780e9672fd9c2d8c5686ec1c56329 | 1df17b2edecd1b651fd67689f7e28d5b9807c007 | refs/heads/master | 2021-07-22T17:23:35.243452 | 2017-11-03T23:26:23 | 2017-11-03T23:26:23 | 104,917,653 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 6,310 | r | 1-basicmapping.R | library(maps)
library(mapdata)
library(ggmap)
library(dplyr)
setwd("~/MEGA/TravelersLab/Parliamentary\ Travel")
# maps english boroughs
qmplot(long, lat, pBoroughs, maptype="toner-background", data = pBoroughs, color = I("red"),
zoom = 7, color = TRUE)
# Saves burgess plot
ggsave("./figures/burgessplot.png")
... |
9c6a14f5cf9bd5b424b22734c14fbbf9e0e5937f | 529802384b1e60fda0652aaa8c95d849751bb372 | /R/make_ggridges_and_get_urbanness_score_per_month.R | bf400bae151c57270d31b63bfb864e06c84467df | [] | no_license | coreytcallaghan/intra_annual_urbanness | 3095bfc224f2bca2f4fdaf09b4fcf8eb1ff75ed2 | 3270927fa90cc1195c174f61e69e61ac18c2dec4 | refs/heads/master | 2023-02-26T23:59:31.780168 | 2021-01-29T15:21:20 | 2021-01-29T15:21:20 | 226,186,531 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 5,212 | r | make_ggridges_and_get_urbanness_score_per_month.R | # This is an R script to read in
# a dataset for each species
# and make a ggridges plot by month
# and export that ggridges plot to a folder
# and at the same time make a small dataframe of
# species-urban scores by month
# and a species-urban scores by day
# the RDS files were too large to push all of them
# so I pus... |
a90978f2d3af8bd2ff7cced5973b1eeb1104b6c0 | 8866f2576324045f7f57bf02b87433bd3ed34145 | /man/get_childCodeIds.Rd | 452903080c14b56529f1527c5e64bc21c2344df3 | [] | no_license | cran/rock | 31ba91c6be5bff97c1659b3a8c3e5fbe6644f285 | 61999cb18c02680719a96b8ec3d0f33010849270 | refs/heads/master | 2022-12-26T21:02:05.960658 | 2022-12-13T11:30:02 | 2022-12-13T11:30:02 | 236,884,462 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 1,035 | rd | get_childCodeIds.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/get_childCodeIds.R, R/get_descendentCodeIds.R
\name{get_childCodeIds}
\alias{get_childCodeIds}
\alias{get_descendentCodeIds}
\title{Get the code identifiers a code's descendents}
\usage{
get_childCodeIds(
x,
parentCodeId,
retu... |
52b346b80a7d4843d00154a61281119925173566 | dd3694903aea3932387264e36e4f59e6deaa817b | /Code/OldCode/build_adjacency_matrix.R | e3113469cbd2d8aaf1ed6b11f56c6748624beaab | [] | no_license | alunmeredith/MSC-Project | 7abe183a43ba53ecf8b7b1b9b9fa7fc5ad080fc7 | 496a55d07a9c18c3ee758406b954431b999c2526 | refs/heads/master | 2020-04-12T09:44:35.778375 | 2016-09-16T13:06:57 | 2016-09-16T13:06:57 | 60,303,501 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,441 | r | build_adjacency_matrix.R | library(data.table)
library(dplyr)
library(readr)
# Load vector of patents into memory, this will be indexed against to produce adjacency matrix.
# Using data.table package to produce a vector key for binary search.
pat_index <- read_csv("../DataFiles/Cleaned/patent_cat.csv")
pat_index <- data.table(pat_index, key ... |
30364ee5c0bd11cafbc8d863b6a374a539402203 | 70fc84a220fff7fc26d6610abb2c5995e613947d | /Scripts/PlottingScripts/PlotAccentDistribution.r | d7c3ccb003ab70aa205571e293bd3e00600bad8f | [] | no_license | mohriner/flowBook | b8b33a90a3cc9ae52b66ae49abec8f15adeb4bfd | faaec23176acf7af339fdda5b119f4aa586bbbda | refs/heads/master | 2020-04-01T21:57:44.605875 | 2020-02-13T15:29:46 | 2020-02-13T15:29:46 | 153,684,015 | 13 | 1 | null | null | null | null | UTF-8 | R | false | false | 685 | r | PlotAccentDistribution.r | PlotAccentDistribution = function(v,m.range=NA){
dat = corpora %>% filter(verse==v) %>%
mutate(meas = beatIndex %/% 4)
if(!is.na(m.range[1])){
dat = dat %>% filter(meas %in% m.range)
}
BIs = dat %>% filter(accent==1) %>%
.[["beatIndex"]] %>% mod(4)
tab = table(c(BIs,seq(0,3.75,.25)))-1
names(t... |
fea7a1f4b02c9555a6f794f87c22a5263896e5e2 | 7f77551f86a4b5b9e6bacd39cacd6d170141c1fa | /homeworks/mid_exam_home.R | 75b0ad1a31824752a2d22da1ef570cec2d37b0ad | [] | no_license | ocowchun/R_Computing-_for_Business_Data_Analytics | b96722ccd04c3d2a5c507694548c5764afb354e4 | 66276ec423f0cddf53215743019202546beef8dd | refs/heads/master | 2021-01-10T20:29:05.086711 | 2015-01-16T10:40:38 | 2015-01-16T10:40:38 | 24,643,703 | 1 | 2 | null | null | null | null | UTF-8 | R | false | false | 2,259 | r | mid_exam_home.R | #Q1
heart_up=function(x){
sqrt(1-(abs(x)-1)^2)
}
heart_lo=function(x){
acos(1-abs(x))-pi
}
x=seq(-2,2,0.05)
# plot(x,heart_lo(x),ylim=c(heart_lo(0),1),type='l')
# lines(x,heart_up(x))
n=100000
machine_gun=function(n){
up_bound=max(heart_up(x))
lo_bound=min(heart_lo(x))
bullet.x=runif(n,-2,2)
bullet.y=runif(n,lo_... |
f5e1e180620c773ebe5172898f7ef6cd74139db1 | 3ffe086b3037fb330a1d48921e2b3669310f5f94 | /R/fontawesome.R | c4fb8170d98fe5b55da81c31476f1b5bf30eac02 | [] | no_license | leeper/waffle | bcbe9c873d4783ecc1ee8f461d8b8bb9c7486741 | 93c34bbac3ee827fba5e860a86deab0f1ccb911b | refs/heads/master | 2021-01-13T08:51:44.556594 | 2016-10-25T10:12:47 | 2016-10-25T15:38:00 | 71,884,593 | 4 | 0 | null | 2016-10-25T10:10:28 | 2016-10-25T10:10:28 | null | UTF-8 | R | false | false | 16,516 | r | fontawesome.R | fa_unicode <- structure(c("\uf042", "\uf170", "\uf037", "\uf039", "\uf036",
"\uf038", "\uf0f9", "\uf13d", "\uf17b", "\uf209", "\uf103",
"\uf100", "\uf101", "\uf102", "\uf107", "\uf104", "\uf105",
"\uf106", "\uf179", "\uf187", "\uf1fe", "\uf0ab", "\uf0a8",
"\uf01a", "\uf19... |
a54f43ded7f61051c1b6f7a0e8f1e525e68ed8f7 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/EcoGenetics/examples/eco.NDVI.post.Rd.R | 7d43e2e77be67ab1df3f6eb8b54ecb2e99009777 | [] | no_license | surayaaramli/typeRrh | d257ac8905c49123f4ccd4e377ee3dfc84d1636c | 66e6996f31961bc8b9aafe1a6a6098327b66bf71 | refs/heads/master | 2023-05-05T04:05:31.617869 | 2019-04-25T22:10:06 | 2019-04-25T22:10:06 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,637 | r | eco.NDVI.post.Rd.R | library(EcoGenetics)
### Name: eco.NDVI.post
### Title: Postprocessing for NDVI and MSAVI2 temporal series of Landsat 5
### and 7
### Aliases: eco.NDVI.post
### ** Examples
## Not run:
##D require(raster)
##D
##D data(tab)
##D data(eco3)
##D temp <- list()
##D
##D # we create 4 simulated rasters for the data i... |
94742b5940b07eecba368e720bc14bfc9baf9f56 | e29b10858b9b2d8995401e464f9ba4462b15a006 | /code/analysis/summaries/count_control_summaries.R | b62bb34b5d6c820ca0be6fa74a8453a2caf71900 | [
"MIT"
] | permissive | PeterNilssonBio/NilssonPernet2022 | 5de5d957b0ca80bc7bcf852a14933f0310feb27c | e0bc008eabb4005a4d3d959048c59311f80d8f08 | refs/heads/main | 2023-04-17T09:09:52.011512 | 2022-07-12T21:05:12 | 2022-07-12T21:05:12 | 512,929,667 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 573 | r | count_control_summaries.R | # Calculate per-treatment count control summary statistics.
#
# Parameters
# ----------
# count_control_beakers: data.frame
# Data frame of per-beaker larval counts
#
# Returns
# -------
# data.frame
# A data frame with a row for each treatment (per experiment).
summarize_count_control <- function(count_control_bea... |
c28e073192e7c3d63e1ffb2993dc16e56cae2685 | dfaa86a4d560c27f656c2e4ea5537413945006c6 | /competitions/caterpillar-tube-pricing/Exploratory_1.R | d1c832d15bd74709419e68f6583f09dfefa3f300 | [
"MIT"
] | permissive | fxcebx/fast-furious | c6cfa6637c1e93156e5ae8c9ef695c818d7c1037 | b974e6b71be92ad8892864794af57631291ebac1 | refs/heads/master | 2020-07-05T16:57:08.106938 | 2019-04-12T01:57:33 | 2019-04-12T01:57:33 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 10,679 | r | Exploratory_1.R | library(caret)
library(Hmisc)
library(data.table)
library(kernlab)
library(subselect)
library(plyr)
library(binhf)
library(fBasics)
library(lattice)
require(xgboost)
require(methods)
getBasePath = function (type = "data") {
ret = ""
base.path1 = ""
base.path2 = ""
if(type == "data") {
base.path1 = "C:/d... |
2992bb22640ee380293dfdfe6d3c2bf3052c304c | aedb3dd2f909bc0f06becd80ca3bbdc92a11bd09 | /man/iMUBAC.Rd | de9c23ba2829496ed13d827f18174dede18b6e23 | [
"MIT"
] | permissive | jaredmychal/iMUBAC | ec5d5a42da6439729b36c561049f33f90a244f04 | 8fb25172ecfaf2f7c6c20c2367e93b2710e2bd84 | refs/heads/master | 2023-02-05T13:15:06.171932 | 2020-12-25T17:25:45 | 2020-12-25T17:25:45 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 785 | rd | iMUBAC.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/iMUBAC.R
\docType{package}
\name{iMUBAC}
\alias{iMUBAC}
\alias{package-iMUBAC}
\title{iMUBAC: Integration of Multi-Batch Cytometry datasets.}
\description{
High-dimentional cytometry, including spectral flow cytometry and mass cytometry (CyTO... |
232799215b7c70c1a5ee00ad096b799182d02291 | dfdc779161b1802767b883d0f57db4a352db3377 | /R/afrilandcover.r | 9b482e84e1a2204b2ce323fda52c9d2e94abe28e | [
"CC-BY-4.0"
] | permissive | afrimapr/afrilearndata | fbe881ae421dd6f92d84f88482643909ae748ad9 | d8510ed4a732418c4cf1a385867604d341528ad0 | refs/heads/master | 2023-08-28T11:00:51.372188 | 2021-11-09T15:16:39 | 2021-11-09T15:16:39 | 307,471,995 | 14 | 8 | null | null | null | null | UTF-8 | R | false | false | 1,602 | r | afrilandcover.r | #' @name afrilandcover
#' @aliases afrilandcover
#' @title landcover raster for Africa, categorical, 20km resolution
#'
#' @description a \code{raster} object storing the majority landcover in 2019 for all 20km squares in Africa.
#' Categorical, 20km resolution from [MODIS](https://lpdaac.usgs.gov/products/mcd12c1v006/... |
371a9b4bcb1b86ac14fc52caf3d0a5a7406706c2 | 70bd03a1f80969e8a30dc0ef4c29c2579a788a81 | /man/read.resp.Rd | c2c0361a1365cbd0507c7b4ef293f882eb190c35 | [] | no_license | lebebr01/irtoys-2 | 68f2aa34b35a51f0fe32dc94b34c4be3cd05ff25 | c8e33faeadb83aaf3a6937a57e16b4d205dc24ce | refs/heads/master | 2021-01-23T13:29:58.776561 | 2014-09-04T21:08:36 | 2014-09-04T21:08:36 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,456 | rd | read.resp.Rd | \name{read.resp}
\alias{read.resp}
\title{Read responses from a file}
\usage{
read.resp(file, na = ".")
}
\arguments{
\item{file}{File name}
\item{na}{The symbol used to represent missing data}
}
\value{
A matrix, typically of zeroes and ones, representing the
correct or wrong responses given by persons (row... |
03fcec9ae11db7e2ed1208ee23a15fd3a366fca7 | bd55cede267ba7a9bb5737d669547971f2158a16 | /ololo.R | b7eb7a513ac242d1110454afe438a2418b9242ab | [] | no_license | llemish/reproduceable1 | 53594b704dd38b2f8399b45bc73a90555e7352b5 | 048bb2f1a204b41bf1142b20d5b4cc209d5afe95 | refs/heads/master | 2023-02-22T02:52:31.479837 | 2021-01-28T13:57:45 | 2021-01-28T13:57:45 | 332,663,862 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,023 | r | ololo.R | get_stereotype <- function(ds, dist = dist) {
# print(str(ev[[1]]))
# stop()
if (!any(ds$event_type)){
ster <- amatch(ds$EVTYPE, dict, maxDist = dist)
if (!any(is.na(ster))){
# browser()
ds$EVTYPE <- dict[ster]
ds$event_type <- T
}
}
return... |
c09cb59e78e2b23ea28337f1f9daa0ee6181eb4d | 3d9170ab762070ea7f7dd66663b134929b225076 | /colonyR/R/colParseResults.R | 9228b9c4fcd22a3a6a3f564a6c3322aa16de8b34 | [] | no_license | mdjbru-R-packages/colonyR | cb6dd5d2f49605059660e54f37fa21ef6edfaf4f | bdfdb810f1d1d3b6ba4d063490a4d4a307bf4ce9 | refs/heads/master | 2020-05-17T02:40:20.585893 | 2014-10-09T13:49:33 | 2014-10-09T13:49:33 | 24,934,659 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 782 | r | colParseResults.R | #' @title Parse results from a Colony run
#'
#' @description Parse the monitoring information and final best configuration
#' for a Colony run
#' @param file basename of the output file name given to Colony
#' @param dir directory where the run took place
#'
#' @return A list with two elements: \code{run} with the mo... |
b16c8ccf8b3218f5f38f9fb0a941fe125f4c3805 | 6870dbf72162b6a0be218579e60feb229771b67d | /colocWrapper/man/importGWASCatalogSummary.Rd | 2501e07a3a97803d3b6fbb3daae7ec0a75751312 | [
"Apache-2.0"
] | permissive | kauralasoo/colocWrapper | 49c0e73dea3a64784385520cabe6229136e9bab3 | 02a814cc3148ee94c134abfe8d97d573a7c396a2 | refs/heads/master | 2021-06-24T20:34:53.518411 | 2020-10-14T10:53:55 | 2020-10-14T10:53:55 | 133,420,295 | 1 | 0 | null | null | null | null | UTF-8 | R | false | true | 298 | rd | importGWASCatalogSummary.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/import_data.R
\name{importGWASCatalogSummary}
\alias{importGWASCatalogSummary}
\title{Import GWAS Catalog summary stats}
\usage{
importGWASCatalogSummary(summary_path)
}
\description{
Import GWAS Catalog summary stats
}
|
aa3e69ea7be85eaf6430e86956999c8f19988076 | 40509fc494148bc2e7ddfe89884146199b308e53 | /man/filterWideDF.Rd | 8f036931e2ac7f143b9396e8aab74cea29d3fa41 | [
"LicenseRef-scancode-public-domain-disclaimer",
"LicenseRef-scancode-warranty-disclaimer"
] | permissive | srcorsi-USGS/GLRItcl | f85889cff82c98d5597f78c65cc0eeca17859405 | c4250bb93f680346fa90f00abd37a36c9ca78a1c | refs/heads/master | 2020-02-26T13:46:53.490898 | 2013-12-03T04:31:18 | 2013-12-03T04:31:18 | 14,752,688 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 794 | rd | filterWideDF.Rd | \name{filterWideDF}
\alias{filterWideDF}
\title{Filter the wide dataframe by parameter code}
\usage{
filterWideDF(wideDF, PCode)
}
\arguments{
\item{wideDF}{data.frame}
\item{PCode}{string 5 digit USGS parameter code (can be a
vector)}
}
\value{
DF dataframe
}
\description{
Filter the wide dataframe by par... |
a1a495b2906c9c7f1504a33ec0eeb74475bc9862 | a3a49f8e285c685c2a80997bda0d214c53d28b18 | /man/SDG-package.Rd | 3f49e09bc089fb93e7a989e16947a2aafac61e36 | [] | no_license | jasenjov/SDG | c733aba91a74d61b8b03890e8a93750b19aa8e71 | a7c84fc21acf350eaeed7a9b60079977bdc91a24 | refs/heads/master | 2020-12-24T13:16:28.567005 | 2015-08-28T07:23:56 | 2015-08-28T07:23:56 | 41,532,953 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,702 | rd | SDG-package.Rd | \name{SDG-package}
\alias{SDG-package}
\alias{SDG}
\docType{package}
\title{
Synthetic Data Generation for the Educational Data Mining.
SDG
}
\description{
The goal of this package is to generate synthetic data. The package is very flexible while introducing parameters and very adaptive depending on the information the... |
3df47fb584e627f69b9b32650cc5df770d5baf50 | c5c7454ae3cbdf33f0635a14b0146cc9dc9e4ca2 | /man/is_infected_in_free_stall.Rd | ccb320af0a8f963162cad1cc65535df521f6f527 | [
"MIT"
] | permissive | fmsan51/blvibmjp | cc3cd507aac19903509557d66f82fb9795d7d287 | 91f7486d2bf6e96c0d731f8f1471205459524885 | refs/heads/master | 2022-12-22T15:46:22.482530 | 2020-09-02T20:21:45 | 2020-09-02T20:21:45 | 221,131,950 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 725 | rd | is_infected_in_free_stall.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/probability_function.R
\name{is_infected_in_free_stall}
\alias{is_infected_in_free_stall}
\title{Whether cows are infected in free pastures}
\usage{
is_infected_in_free_stall(n_noinf, n_inf, month, param_sim)
}
\arguments{
\item{n_noinf}{The ... |
b4d8107c2a2efedf624a21701f60f81d2000c456 | 46d7e12a345a404d1ff20fea5ff5a872c45afa3b | /R/state.R | 2353429a7dc9dee15d1b03f5fa4f0b4f13311c1d | [] | no_license | cran/lifx | 3d35b870b931eea683fb28cddb0f60db492cb4b3 | d3398d410c7bb09224c52b749c3e049f0b533675 | refs/heads/master | 2022-11-13T00:18:59.746866 | 2020-06-24T11:10:06 | 2020-06-24T11:10:06 | 276,693,816 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,538 | r | state.R | # generic state modifiers ----------------------------------------------------
#' set light state (lifx API endpoint PUT set state)
#'
#' @template param_power
#' @template param_color_name
#' @param brightness set the brightness (0-1)
#' @template param_infrared
#' @template param_duration
#' @template param_fast
#' ... |
dfe8d14ce54298609351425a84277a85ec7c85d6 | cf09008185b813e272bbe208120852ebfb277fe8 | /tidyr_script9.R | db81d05a2ba675c238d69662e30e6a6c75612f2c | [] | no_license | AnkurDesai11/datascienceJHUcoursera | efd1eedd5ab29c8835ac0cf129fa1b9e68b88719 | 4a36448fb2827d4f5048c8b21c210684cf363746 | refs/heads/master | 2023-02-09T21:29:26.288860 | 2021-01-11T04:26:39 | 2021-01-11T04:26:39 | 255,146,982 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,655 | r | tidyr_script9.R | # Append two more function calls to accomplish the following:
#
# 1. Use group_by() (from dplyr) to group the data by part and
# sex, in that order.
#
# 2. Use mutate to add two new columns, whose values will be
# automatically computed group-by-group:
#
# * total = sum(count)
# * prop = count / total
#
... |
aa0f347d5136e52d5a58e43ccac0b4df1e8d54ad | d43ee2a310dccad76d62f696fe4562e55a138b0f | /revisions/supplementary_code/lottery_model.R | d06bdb49c7dcb393a97ae6a23160abff8cbd33de | [
"BSD-2-Clause"
] | permissive | DominiqueGravel/ms_neutral_theory | d7444d2c2e9a19ac250db110b15bfc7f7dd75e8e | 7a060780002cc0bc9aeb5f42f65c4d6762663b66 | refs/heads/master | 2016-09-03T07:31:12.058294 | 2013-09-25T14:17:22 | 2013-09-25T14:17:22 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,877 | r | lottery_model.R | #######################################################################
# Individual based lottery model with spatially explicit
# dispersal and environmental heterogeneity
#
# The model collapse to a neutral model when the niche breadth tends to infinity
#
# Store the results in a time series of occupancy, a presence... |
7bd5f5995b5196c3a382c9ab27f2249c97993175 | afde039a000379e7acb65de4e73b8ac175cb01ea | /tests/testthat/test-textmodel.R | 1c8e4f9493b8734c6e98eb70cfbf1f8eacd63805 | [] | no_license | cran/newsmap | 7002da70e06e282919747c250ba9aab38ecd4bab | dbebdb0b0393edf0d7c87b3a9569fdb92e3b7a9f | refs/heads/master | 2023-04-08T10:30:21.596432 | 2023-03-16T07:50:02 | 2023-03-16T07:50:02 | 147,195,703 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 7,128 | r | test-textmodel.R | require(quanteda)
toks_test <- tokens(data_corpus_inaugural, remove_punct = TRUE)
dfmt_test <- dfm(toks_test) %>%
dfm_remove(stopwords("en"))
toks_dict_test <- tokens_lookup(toks_test, data_dictionary_newsmap_en, level = 3)
dfmt_dict_test <- dfm(toks_test)
test_that("textmodel_newsmap() works with differe... |
f2845933ffc0beeee29abf007e8c2fa0df347534 | bde0a116ee7c08e1006683dcc70e0db43150baa7 | /man/ptME.Rd | 13a52aae47f7a855ec4a0e50b74079ab70dfa894 | [] | no_license | matloff/partools | bea3382d444d3048c4522eac31601dfe378e7ebd | 14a7a8c701167280d71b2991cb03f8232ddf4f19 | refs/heads/master | 2022-10-14T13:46:31.102122 | 2022-10-13T22:31:03 | 2022-10-13T22:31:03 | 29,333,839 | 43 | 14 | null | 2022-10-13T22:31:04 | 2015-01-16T05:14:45 | R | UTF-8 | R | false | false | 1,856 | rd | ptME.Rd | \name{ptMEinit,ptMEinitSrvrs,ptMEinitCons,ptMEsend,ptMErecv,ptMEclose, ptMEtest,ptMEtestWrkr}
\alias{ptMEinit}
\alias{ptMEinitSrvrs}
\alias{ptMEinitCons}
\alias{ptMEsend}
\alias{ptMErecv}
\alias{ptMEclose}
\alias{ptMEtest}
\alias{ptMEtestWrkr}
\title{
Message-passing utilities.
}
\description{Simple MPI-like function... |
bba0694affacfbc3dcd0130ee23d5b962bd5a0db | 0257145576232d6fff7330d7bba434a31839b912 | /R/jaws_pca.R | c9dd221235404d2351c512106d948d9eb9b3d2dd | [] | no_license | ncchung/jaws | 4176c77aa53489749c88f5b59d77954e209693c8 | 6325b32b97ea2af806168ec986b3ebfc8b304696 | refs/heads/master | 2021-01-10T07:02:53.645761 | 2016-11-17T11:50:15 | 2016-11-17T11:50:15 | 49,068,052 | 3 | 1 | null | null | null | null | UTF-8 | R | false | false | 11,416 | r | jaws_pca.R | #' The Jackstraw Weighted Shrinkage Estimation Method for Sparse Loadings in Principal Component Analysis
#'
#' Estimates sparse/shrunken loadings of principal component analysis.
#' Based on statistical sginificance of association between variables and principal components,
#' the sample loadings of principal componen... |
ac0e18845016e516d4062101d4bba7f48f4a8f31 | 483a05fd21e1cd199346d5045ae16060057501d2 | /inst/tinytest/test_tiledbarray_extra.R | 01c1121442d1eeadf1fe2f4537c50375215ca7e7 | [
"MIT"
] | permissive | TileDB-Inc/TileDB-R | 34862c95815a77ba9b925f8d6e24dd362b3c617a | 71901f8c9d5de860dbe078a0e708dda8f1b9b407 | refs/heads/master | 2023-09-04T05:28:09.468320 | 2023-08-23T13:24:33 | 2023-08-23T13:24:33 | 91,851,655 | 90 | 20 | NOASSERTION | 2023-09-14T20:48:10 | 2017-05-19T23:07:10 | R | UTF-8 | R | false | false | 2,871 | r | test_tiledbarray_extra.R | library(tinytest)
library(tiledb)
exit_file("Skip for now")
isOldWindows <- Sys.info()[["sysname"]] == "Windows" && grepl('Windows Server 2008', osVersion)
if (isOldWindows) exit_file("skip this file on old Windows releases")
isMacOS <- (Sys.info()['sysname'] == "Darwin")
if (tiledb_version(TRUE) < "2.7.0") exit_file("... |
aaa578dfacfc6adfe24f5fd46396fa724e62adc7 | a9ec02af10525990255641f66ef82b24c6ae7502 | /man/soil_erosion.Rd | cb528644e17f802aad923d784d5fd9aba87aefb5 | [] | no_license | tcobian/SoilCarbon | e37bb7ff87e0edd538928f1e99a8b11e8d3c9f19 | 1eb96793ec84a3b8d6da2a3c1dbf945d6e3524c9 | refs/heads/master | 2021-02-16T04:53:18.454825 | 2020-03-16T17:13:25 | 2020-03-16T17:13:25 | 244,967,971 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 489 | rd | soil_erosion.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/soil_erosion.R
\name{soil_erosion}
\alias{soil_erosion}
\title{Soil Erosion Rates}
\usage{
soil_erosion(area, time)
}
\arguments{
\item{This}{function will take inputs of land are in units of hecatres and a unit of time in year}
}
\value{
Thi... |
04fe91807c94de51a4b7b88b87a17ca70b2d493c | 7a5810ea96d123ed70891a64a39104406a1e8429 | /190815_hichip_statistics.R | 77f6c6617f6cb33cf1f4335b8cd4c994fee7f95a | [] | no_license | wesleylcai/bmcmedgenomics2020_metastasis | 24ee04028028bcbb292f69f6cee42f8b04b4281a | 16c9a013567a08c242e2c18ee58e57bf5e4235b9 | refs/heads/master | 2020-11-24T15:13:43.451580 | 2020-08-18T11:40:32 | 2020-08-18T11:40:32 | 228,210,666 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 6,635 | r | 190815_hichip_statistics.R | # Last Updated:
# Author: Wesley Cai
# Purpose:
library(data.table)
library(ggplot2)
library(reshape2)
# load gsea
# source("/Users/wcai/Google_Drive/_Lab/Data/Bioinformatics/resources/gsea/gmt/load_gmt.R")
# load for revamp
source("/Users/wcai/Google_Drive/_Lab/Data/Bioinformatics/190720_revamp/analysis/190720_load... |
f479aa88e96e270dbd3403dc8eb96e126bf63081 | 73fca4174b7163e4e98899f416692f0ad85ed389 | /code.R | ae0f378463990f8b469b12b86f64fbf8f79b85ab | [] | no_license | akhil93/ExData_Plotting2 | 78c77a21cef54f6e2bc262760370f8c5625fb9f3 | 5c511636d5c9037d7aa2eedeb33d20db973e4571 | refs/heads/master | 2020-06-04T04:30:37.762001 | 2014-06-02T05:49:04 | 2014-06-02T05:49:04 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 5,804 | r | code.R | #Plot 1
# Let's load the given data set's
NEI <- readRDS("summarySCC_PM25.rds")
SCC <- readRDS("Source_Classification_Code.rds")
# To plot the total emissions, we need to sum all the observations of Emissions by Year. I used Aggregate() function to calculate the Total #Emissions
total_emissions <- aggregate(Emissions... |
2b99563cb08f7a46600131181c3c17050aece354 | 123c73a55e217bc720516f8a0a672e303c347b85 | /lib/TammData.r | aca00f7deff564c6b4310bd5e79e858d1470f5e7 | [
"MIT"
] | permissive | PSC-CoTC/PSC-FRAM-Admin | 6ee00d6ac50695df105ff5fd1d7c075ffb5e4970 | 0e25a69cf8f9fb98fac52f6b0a0f4d841c43b8e4 | refs/heads/master | 2021-01-10T16:06:38.000374 | 2020-02-27T23:51:06 | 2020-02-27T23:51:06 | 51,110,110 | 1 | 2 | MIT | 2019-02-11T23:05:33 | 2016-02-04T22:24:05 | HTML | UTF-8 | R | false | false | 5,092 | r | TammData.r | ################
#
# Common methods to deal with a TAMM Spreadsheet Model
#
# Nicholas Komick
# nicholas.komick@dfo-mpo.gc.ca
# January 12, 2017
# Using: http://google-styleguide.googlecode.com/svn/trunk/google-r-style.html
#
################
kDecimalRegEx <- "^[0-9]*[.]?[0-9]+([eE][-+]?[0-9]+)?$"
required.packages <... |
019ef2907aef477fe83ea65e5d93cac374c2fded | 41bc3ac7457527c3abd38891a7a5c4dc7c09b874 | /R/rpivotTable.R | 22789673fe303a2cc448aafda0a882905ae4139a | [
"MIT"
] | permissive | jcizel/rpivotTable | 282616e117b38e979afd04f0f6219f5a09cd74a8 | d23afb10c8a355f0ace664c7c8ec465c5f25e669 | refs/heads/master | 2021-01-18T07:47:12.458895 | 2015-01-30T18:41:21 | 2015-01-30T18:41:21 | 30,082,383 | 4 | 1 | null | 2015-01-30T17:15:42 | 2015-01-30T17:15:42 | null | UTF-8 | R | false | false | 1,321 | r | rpivotTable.R | #' <Add Title>
#'
#' <Add Description>
#'
#' @import htmlwidgets
#'
#' @export
##'
##' @title
##' @param data
##' @param rows
##' @param cols
##' @param vals
##' @param aggregatorName
##' @param width
##' @param height
##' @return
##' @author Enzo Martoglio
rpivotTable <- function(
data = NULL,
rows = ... |
a665f809abf0d0d285d5995a7d5d66e21951c660 | 73e638dc549babb1034d2c103aa9b6fcdc5d7322 | /examples/dl.R | 94b90a31dfc8b2c5443a80d1d1ec4acb31f3b31e | [] | no_license | yandorazhang/R2D2 | b11e8c46902949a55ab4a1a0fe4f65687c915cc0 | e734639929abb60e616c114ac7fe4e2beb5c7f9d | refs/heads/master | 2023-01-14T08:39:13.803273 | 2020-11-18T13:43:30 | 2020-11-18T13:43:30 | 282,605,509 | 6 | 0 | null | null | null | null | UTF-8 | R | false | false | 821 | r | dl.R | rho <- 0.5
# Number of predictors
p <- 25
# Number of observations
n <- 60
# Construct beta
n_nonzero <- 5
beta <- rep(0, p)
beta[11:(10 + n_nonzero)] <- stats::rt(n_nonzero, df = 3) * sqrt(0.5/(3 * n_nonzero/2))
# Construct x
sigma <- 1
times <- 1:p
H <- abs(outer(times, times, "-"))
V <- sigma * rho^H
x <- mvtnorm::r... |
d8c980169b105deaf1c3697f3bdd0216705250aa | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/ddalpha/examples/depth.space.halfspace.Rd.R | f3f0c084e147cc3b153239f3f20158dd99d2c76a | [] | no_license | surayaaramli/typeRrh | d257ac8905c49123f4ccd4e377ee3dfc84d1636c | 66e6996f31961bc8b9aafe1a6a6098327b66bf71 | refs/heads/master | 2023-05-05T04:05:31.617869 | 2019-04-25T22:10:06 | 2019-04-25T22:10:06 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 960 | r | depth.space.halfspace.Rd.R | library(ddalpha)
### Name: depth.space.halfspace
### Title: Calculate Depth Space using Halfspace Depth
### Aliases: depth.space.halfspace
### Keywords: robust multivariate nonparametric
### ** Examples
# Generate a bivariate normal location-shift classification task
# containing 20 training objects
class1 <- mvrno... |
12ed1d2dc38897a2de6afd3bb54ede737823a231 | 19cee5848f8a9bbc2d7d236258483719f49d5b97 | /scripts/archive/cell_count_3var_analysis/poststratify_3var.R | 8e1eee0f60fb97c57a0dd6ab5d7e08412e9f8799 | [] | no_license | AnthonyRentsch/DPsurveyweighting | dac945f36d99b591c4af8625607befed05dc81bc | 0bf62262f88f6187f1d27f8c003e940785ded526 | refs/heads/master | 2020-05-17T20:34:45.777499 | 2019-05-17T01:56:20 | 2019-05-17T01:56:20 | 183,946,616 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 8,840 | r | poststratify_3var.R | ###########
# Perform computation of post-stratification weights
###########
#### Set up
rm(list = ls());
setwd("~/Desktop/Bhaven/Harvard/Classes/CS208/DPsurveyweighting/"); #move working directory to the root of our DPsurveyweighting repo
# install.packages("survey")
require(plyr); require(dplyr); require(readr); req... |
ead624884e91114be2686553de3a381d9ed6a6ca | 9210c5d9b5805b2dfc9393070793b38b7905f3d7 | /bibliography.R | 6fdaba621b353394367921744d0dc6e0c28a06b6 | [] | no_license | prodakt/learning | 4d40c2666d61bb9e93cf52a5e6ea2fb3568b8077 | 69d4e931cea12da159a8b7fb7a377546cd81a2ba | refs/heads/main | 2023-02-28T17:36:36.714211 | 2021-02-01T10:13:48 | 2021-02-01T10:13:48 | 320,534,892 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,274 | r | bibliography.R | source("http://bioconductor.org/biocLite.R")
# bibtex --------------
biocLite("bibtex")
library(bibtex)
a <- read.bib("L:/Praca/Publikacje_Konferencje/TCDD.bib")
head(a)
# RISmed --------------
install.packages("RISmed")
library(RISmed)
search_topic <- 'copd'
search_query <- EUtilsSummary(search_topic... |
a7ec0d507674941ef359f69d73b05062261dd6c3 | 6f528d1394c665ccef7f5a1d39744dfd0b2568a7 | /dssat_cornCV_calib.R | fe8e60552a10ac466f5aa4530ae60d80fff7fe81 | [] | no_license | Murilodsv/DSSATcorncalibration | 6dfc39376a951606acb7cdf44461da82a05aa7da | 2c1786a86be2c70da304a1b8fe8ad39fb8591064 | refs/heads/master | 2021-09-25T18:34:48.682874 | 2021-09-14T11:55:18 | 2021-09-14T11:55:18 | 176,268,443 | 1 | 0 | null | 2019-03-18T11:24:25 | 2019-03-18T11:24:25 | null | UTF-8 | R | false | false | 8,682 | r | dssat_cornCV_calib.R | library(sirad)
library(Dasst)
library(hydroGOF)
library(optimr)
library(dfoptim)
library(FME)
library(optimx)
wd = "D:/ISmalia_DSSAT"
Obs_data = read.csv(paste(wd,"/OBS_Calib-Data_.csv",sep=""))
#-------------------------SC10 cultivar------------------------------
OBStotalDW <- round(Obs_data$Value[Obs_data$Vari=="... |
b660ee24a3d899a06694c231aa0970fa42c558cc | a0dce4c3d980e8d9678509b0278a466ca9cb5677 | /R/as.R | 34d25a941fa9015136128c198ac7b78ec20c4023 | [
"MIT"
] | permissive | TobCap/importas | 925a8799a14c0d429ceff69c5a20297ceb7972fa | 1a709aa773818a6044d712f4819d833b5fb66732 | refs/heads/master | 2020-11-27T16:04:52.460940 | 2019-12-08T14:59:33 | 2019-12-08T14:59:33 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 317 | r | as.R | #' @rdname importas
#' @param pkg A name of package
#' @param nm An abbreviated name of the package
#'
#' @examples
#' graphics %as% gr
#' gr$plot
#'
#' @aliases as
#' @export
`%as%` <- function(pkg, nm) {
assign(
deparse(substitute(nm)),
getNamespace(deparse(substitute(pkg))),
parent.frame()
)
} |
e979044c7fc769b5abe868e2ceee046715912c2d | a888137b4504ef8ce8ea170d5d13ab973853e81f | /numericalAlgorithms/SecantMethod.R | 461b56ba7e481bcf35c2c4bc036fbaab3eedc927 | [] | no_license | indrag49/Comp-phy | e4e24636945bca311c20617a7cbad62b421e53f7 | d1265044073682d4066395ad9e3e89350da6c599 | refs/heads/master | 2021-09-16T20:21:33.526597 | 2018-06-24T16:24:26 | 2018-06-24T16:24:26 | 111,316,266 | 2 | 0 | null | null | null | null | UTF-8 | R | false | false | 429 | r | SecantMethod.R | ## Author: Indranil Ghosh, Jadavpur University, Physics Department
## Secant method
f <- function(x) x*exp(x)-cos(x)
Secant <- function(x0, x1, Max, epsilon) {
k <- 1
while(k<=Max) {
f0 <- f(x0)
f1 <- f(x1)
x2 <- x1-f1*(x1-x0)/(f1-f0)
if(abs(x2 - x1)<epsilon) return (x2)
x0 <- x1
... |
e2904cc3e5deb41777a582189062a6c07d821bdb | 983f36b7bd9ea298b0553c8f9cf976d993d93e88 | /addLocationCsv.r | c894842c12561a6caf0c9113c33bd3bde1069e08 | [] | no_license | zupino/estate-analysis | 71a1f5515e6e3f2d89376e3c928c723adf53871f | aad3d7b1318aa4e035b5d2d97cafce31dae2122c | refs/heads/master | 2021-01-21T16:53:12.496709 | 2017-05-20T20:06:37 | 2017-05-20T20:06:37 | 91,913,533 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,452 | r | addLocationCsv.r | #!/usr/bin/env Rscript
args = commandArgs(trailingOnly=TRUE)
# Tool function to remove spaces on strings
trim <- function (x) gsub("^\\s+|\\s+$", "", x)
# Define function to add clean "location" column
# The format will be XXX,Stuttgart. It is used
# to group and calculate average price per area
beautyLocation <... |
003d51dce62217f641625465506141e27cb81fc5 | 146b3f63e30de7b6cccd35b27d9a830a7d3ca364 | /man/drawNormalValues.Rd | 17e0608dffbf12eed446c3d23f4ac0d32423b0a5 | [] | no_license | codeForReviewer/kMajorityRule | cc749239f3de6c883cb17847a88eba8a8794e23f | 307b53aa961a6f981c1d7776fb1ac3729ea29c03 | refs/heads/master | 2021-01-21T12:50:11.424292 | 2016-04-15T20:46:30 | 2016-04-15T20:46:30 | 30,224,968 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 704 | rd | drawNormalValues.Rd | % Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/drawNormalValues.R
\name{drawNormalValues}
\alias{drawNormalValues}
\title{drawNormalValues
Draws ui or ei values from N(groupMean, groupStandardDeviation).}
\usage{
drawNormalValues(sizeOfDraw, groupMean, groupStandardDeviation)
}
\a... |
5fbfce7dbdd846e2c095b6fcdb05aced489b52e4 | 9da7ff9073e6775a34e9432ae33f6dac36891a42 | /man/detect.change.Rd | 03078da7c0e5d24b94bca5719d1fbc42d1e87758 | [] | no_license | eik4862/Subway | 9f2cb24e611769226275aa209589042c257c42c0 | 64c672132a8619afe30338942bca560d5646a6c7 | refs/heads/master | 2023-08-15T05:16:10.235607 | 2020-05-25T17:35:02 | 2020-05-25T17:35:02 | 266,563,864 | 2 | 0 | null | null | null | null | UTF-8 | R | false | true | 1,511 | rd | detect.change.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/analysis.R
\name{detect.change}
\alias{detect.change}
\title{Change point detection}
\usage{
detect.change(data, type = c("mean", "var"), ..., plot = TRUE)
}
\arguments{
\item{data}{Time series data whose change point is to be detected.
The d... |
66c97569fcf839bad3e481a76571eaae0b8417f2 | ad4a497bec38cb4ad0e9f865d87005b9bece12a5 | /Dissertation Code 2 Imputation.R | 187ea8dd745f663253d9698557069f8ad352eef9 | [] | no_license | bartekbursa/Dissertation | f1abfa1fd4dc316ab87702957bc74425b5168a04 | 61a80d5ef401ec23aaf1a49c92a94acf02bd58eb | refs/heads/master | 2020-03-18T19:37:45.430964 | 2015-09-27T18:41:21 | 2015-09-27T18:41:21 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 29,450 | r | Dissertation Code 2 Imputation.R | #######################################################################
## R Code for Dissertation: Imputation and Setup for the Logit Model ##
#######################################################################
############# Things to do ##############
# Fix the multicollinear imputation regressions DONE
# Keep... |
6c6f5ce56c6dc6bee14ca3c5cd77999827420cae | b2eb1052fe4e9a8ce458f3c786c8449330e0c09f | /man/formatCode.Rd | 7d66d4bfbcf9e77b50ade606caffa259379e532d | [] | no_license | duncantl/XDynDocs | 9245e9c25ef5cc4b575c4a11e85552c09c1bcd43 | 6612b35323a195c2b9646a2591163092935f328f | refs/heads/master | 2023-01-09T02:51:24.797126 | 2022-12-22T17:01:08 | 2022-12-22T17:01:08 | 40,777,819 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,183 | rd | formatCode.Rd | \name{formatCode}
\alias{formatCode}
\title{Format R code for displaying in a document}
\description{
This function is used to take code as text and format it
for display in with the appropriate width - number of characters -
etc.
It is exported so that it can be called from XSL code that performs
the forma... |
5efb6818a32d874e08f2bbee312e1bddbcc20d9e | a0e7e2030de5f57222c393fb31638559954496fb | /sample.R | 61cb8d313f64eef00470afbc57467a66961e2d55 | [] | no_license | Amelia820/softcarp_report | c6436ad21e22cbb193113004e06eb6364f92906a | 03f9029efbf71b5d12e7561d13f5d4b836a2360d | refs/heads/master | 2020-08-04T04:41:33.278771 | 2019-10-01T05:00:24 | 2019-10-01T05:00:24 | 212,010,146 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 45 | r | sample.R | # comment on Steph's humour
print("hahaha")
|
fdcb0a47e9e1e3159c6ca1294845f3068829801a | a94876abe870a118f7ec2eb42362a8d05c8e049d | /raleigh/code/01-pullYelpData.R | dfef8614afd309f97b2bcedecf651e584bae3d27 | [] | no_license | CityofSyracuse/restaurant_inspections | dec5d7e0a8a0823b62cfc33fbb97f9da48a6396e | 09c870888f67dce2361104a4fb6cce62244f64c0 | refs/heads/master | 2021-01-17T15:32:32.524096 | 2017-03-02T22:22:13 | 2017-03-02T22:24:10 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,862 | r | 01-pullYelpData.R | library(httr)
library(jsonlite)
library(dplyr)
library(plyr)
library(readr)
library(data.table)
writeData <- function(yelpList, yelpCategories, writeColNames){
yelpDF <- rbindlist(yelpList, use.names=TRUE, fill=TRUE, idcol=NULL)
yelpDF <- unique(yelpDF) # delete duplicates
write.table(yelpDF, file = "yelpData.... |
f1314903dc6faf9f334c67bbbc83db46e88420b0 | 4d5cd37123da9f827a46f4b20f7dd4e4a4d1c2a0 | /construction-notes.R | 5e1d867cc606d6e43db13cffa3276805b684bc81 | [] | no_license | conjugateprior/bara-data | 2b624dea25aa0b7447331bd823edcd31948545e6 | d5673cbf2120ec97bee46464439f0cb637a2ca02 | refs/heads/master | 2020-03-29T02:18:29.156386 | 2017-06-17T19:34:39 | 2017-06-17T19:34:39 | 94,643,844 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,746 | r | construction-notes.R | # Processing notes
library(rvest)
deb <- read_html("abortion-debate-hansard.html")
mes <- html_nodes(deb, "div[class='hentry member_contribution']")
speakers <- html_attr(html_node(mes, "cite a"), "title")
voting <- list("abs"=c("Mr William Deedes", "Dr Horace King", "Sir John Hobson"),
"no"=c("Mr Ke... |
4d988c2746d90c340d4c9c62411a25ee85f40927 | 68dcbb1717f26c91fb9b4f7c1a573381ba709bfb | /R/auth.r | a2df81d27fcf33c0db5d4afacf1299ec7b3545df | [
"BSD-2-Clause"
] | permissive | wrathematics/rotp | 253645a55fac2282c1760ecf226f9a8ab6165ba8 | df3da2da5160e81e996c128e6ff842c3c1550d63 | refs/heads/master | 2021-06-06T21:56:17.676750 | 2020-06-28T17:12:47 | 2020-06-28T17:12:47 | 136,544,990 | 5 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,420 | r | auth.r | auth_from_key = function(key)
{
cat("\nCtrl+c to exit\n")
while (TRUE)
{
rem = get_remaining_time()
p = totp_wrapper(key)
p_str = sprintf("%06d", p)
while (rem > 0)
{
cat('\r', paste0(p_str, " (", sprintf("%2d", rem), " seconds remaining ", progress_bar(rem), ") "))
utils::... |
63a3baeeff835199b03895ccd042e8e859564bea | 1f29a40d0d2bb1a165dc8606f04d7bac1de795b8 | /DNC_Toolbox/Prune_Tree.R | bd27515a2722fa54a42678d92b097529df44d2e7 | [] | no_license | Gene-Weaver/Testing-Darwin-s-Naturalization-Conundrum | c23cc6a96fda3a751be6a51a77b9c5a00d263995 | f5d5023f433a5090b901020fe98395bb7baf7e86 | refs/heads/master | 2020-03-30T08:31:36.726417 | 2018-10-22T05:01:55 | 2018-10-22T05:01:55 | 151,022,058 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 253 | r | Prune_Tree.R | ###
### Prune tree tips based on an imported .csv file
###
Prune.Tree <- function(SPECIES_TO_REMOVE,TREE,SAVE_FILE){
PRUNED_TREE<-drop.tip(TREE,TREE$tip.label[SPECIES_TO_REMOVE])
write.tree(PRUNED_TREE,file=SAVE_FILE)
return(PRUNED_TREE)
}
|
3901eae15a77e1e7cd44040fcb8954dcc80cf4cf | a1e0c1014d6de2ee4034accb9cd29cacb1533b08 | /global.R | 83c1e2264edd8c6044e99cf9710200af81f75db8 | [] | no_license | NickPyll/Prime | 97e16c1a218176660c5c2fbbb17579224c13c9b6 | 5f861990b095bdf60a9a88a0c22aaae119ca4ff9 | refs/heads/master | 2021-10-21T22:02:11.242799 | 2021-10-11T13:09:48 | 2021-10-11T13:09:48 | 123,444,507 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 36 | r | global.R | library(shiny)
library(shinythemes)
|
5a2bf4a23dbe5298b3417c7e64e638fc6604cb61 | 9f958bfe7662e0cc3da82697003ab0970822535b | /man/ac_get_campaigns.Rd | 26c6f76d905f26e14c6f6ef015c6057691f7cc3b | [] | no_license | mdancho84/ractivecampaign | 23656aea4765988bfffe94eb29877414b8c09a80 | 17b14b518d95a485eabb1592ef73ed131490e3a7 | refs/heads/master | 2023-08-29T23:38:28.754582 | 2021-11-12T09:20:02 | 2021-11-12T09:20:02 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 593 | rd | ac_get_campaigns.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ac_get_campaigns.R
\name{ac_get_campaigns}
\alias{ac_get_campaigns}
\title{Retrieve all campaings}
\usage{
ac_get_campaigns()
}
\value{
tibble with campaings metadata
}
\description{
Campaigns are broadcast emails sent out to a list of contac... |
371b93229b228769fbe9f1eb5284f8ff9f4fdcf4 | 9d1ca53656d3b6d76c839eef335c82679dbc5067 | /Calculations with dataframes - 20200407.R | a224bc495f8d7bfbe9727e24d28445c78e25a774 | [] | no_license | shirewoman2/HandsOnR | 559fa449ab56e8ccec7f49ff38374a2c00a1f35e | aa3b3eca3f985e6487f93df3282b76192822414b | refs/heads/master | 2021-06-30T18:01:52.650937 | 2020-10-24T17:53:08 | 2020-10-24T17:53:08 | 165,004,072 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,622 | r | Calculations with dataframes - 20200407.R | # Calculations with dataframes - 20200407
# This script is for playing around with data.frames.
# Housekeeping -----------------------------------------------------------
library(tidyverse)
library(LaurasHelpers)
# Structures and classes of objects ---------------------------------------
data(iris)
str(iris)
uniq... |
5e8b00818fd2dc43411535ca338197ff9f96718f | 75f8a0d750aa880f5eaf72aafe9acba8746d9656 | /tutorial/scripts/graphics/plot_sin.R | c13bce42368f5e08b665c75a42c1779fa61f6764 | [] | no_license | dkhramov/iad_2020 | abe75b34c5fb422b1eb7ad320827a7253a7fb03d | 701b9eb08f65c0262808717549c369b270883a14 | refs/heads/master | 2021-02-06T22:43:27.924767 | 2020-03-20T12:19:24 | 2020-03-20T12:19:24 | 243,954,164 | 2 | 1 | null | null | null | null | UTF-8 | R | false | false | 3,423 | r | plot_sin.R | # График, составленный из элементов
x <- seq(-pi,pi,.1)
y <- sin(x)
plot.new()
plot.window(xlim = c(-pi,pi), ylim = c(-1,1))
points(x,y)
axis(1)
axis(2)
box()
title(xlab = "x")
title(ylab = "y")
# Тот же график, построенный с помощью функции высокого уровня
plot(x,y)
# Добавим заголовок и изменим метки осей координат... |
5eca603231075c7eb6c2d34c40aa3a47e8ff292e | 3761011142bbaf90bfdfb60125eee5fb540cfe61 | /man/vanmaps.Rd | 99f95bdbcbab2c61370e04c96deaff8f2a41152f | [] | no_license | tony-stone/vanmaps | 5da82df1a2be3365f22ee435ce4a0a6f19b270fd | e63a1984377fc554e69f06935015f65206339187 | refs/heads/master | 2020-07-06T06:52:52.684386 | 2016-11-22T11:48:30 | 2016-11-22T11:48:30 | 74,054,363 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 419 | rd | vanmaps.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/vanmaps.R
\docType{package}
\name{vanmaps}
\alias{vanmaps}
\alias{vanmaps-package}
\title{vanmaps: A package for producing choropleth maps at the English County
or Ambulance Service level.}
\description{
Contains National Statistics data: Cro... |
8d017377611d1f70ab43a571a402fd720fdf2d05 | 653b8ba356ed50f74a442455e409f62976b4464d | /modelAnalyzeR/man/exec_alert_counts.Rd | 78802cc7caef63c44ab4339c7e5e50eedfae917d | [
"MIT"
] | permissive | kiran1984/SCOPE-Anomaly-Detection-Case-Study | e5bcfaf981b78695f7ebebdfb8b40ed7871244c5 | 21a0bb9e16a200ba1fcf29354c544524cec9a154 | refs/heads/master | 2020-06-22T11:09:53.603581 | 2018-06-30T21:53:38 | 2018-06-30T21:53:38 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 713 | rd | exec_alert_counts.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/case_study_results.R
\name{exec_alert_counts}
\alias{exec_alert_counts}
\title{Exec Alert Counts}
\usage{
exec_alert_counts(data, beginning_dates, middle_dates, end_dates)
}
\arguments{
\item{data}{Dataframe of territory RexT results}
\item{... |
f0d32bdceca30d837bf6fc58b5588b4b291d1cc8 | f126f954a239b4bc4e6db2ced2957cfc558983a8 | /reproducibilityChallenge Q4.R | e9a046a0288f617b0622b8621caec83bde218baf | [] | no_license | dpaukner/Reproducibility-Challenge-QBio5 | 7c6b774a0247098b6c331f3f17deaecd456b92b1 | 6234270ee561095beb60c16d2a98fdc7c36c61d3 | refs/heads/master | 2020-07-23T11:57:13.727471 | 2019-09-10T22:05:13 | 2019-09-10T22:05:13 | 207,549,847 | 0 | 2 | null | null | null | null | UTF-8 | R | false | false | 236 | r | reproducibilityChallenge Q4.R | library(tidyverse)
setwd("~/Documents/BSD-QBio5/tutorials/reproducibility/data")
arth <- read.csv("cole_arthropod_data_1946.csv", stringsAsFactors = FALSE)
weev_data <- read.csv("cole_arthropod_data_1946.csv", stringsAsFactors = FALSE)
|
976caf736edcd9b52a093cb3a9221cd1ad6db425 | 82b1c5655856b660c053d18ec7ad94f3aa30a964 | /tests/testthat/test-function-boxplot_main_extensions.R | 4d252a878eb6e2580357ec9bd5ce0a663169339b | [
"MIT"
] | permissive | KWB-R/kwb.fakin | 9792dfa732a8dd1aaa8d2634630411119604757f | 17ab0e6e9a63a03c6cb40ef29ee3899c2b2724a0 | refs/heads/master | 2022-06-09T22:25:09.633343 | 2022-06-08T21:24:14 | 2022-06-08T21:24:14 | 136,065,795 | 1 | 0 | MIT | 2021-03-15T10:55:17 | 2018-06-04T18:21:30 | R | UTF-8 | R | false | false | 201 | r | test-function-boxplot_main_extensions.R | test_that("boxplot_main_extensions() works", {
f <- kwb.fakin:::boxplot_main_extensions
expect_error(f())
f(data.frame(
extension = c("docx", "xls", "docx"),
size = c(1, 2, 3)
))
})
|
ca3df25ba70299112e51e5474007b6e39cfd025b | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/billboarder/examples/bb_lollipop.Rd.R | c892b527ac4dd7d5b3eec4f0136239037f974d80 | [] | no_license | surayaaramli/typeRrh | d257ac8905c49123f4ccd4e377ee3dfc84d1636c | 66e6996f31961bc8b9aafe1a6a6098327b66bf71 | refs/heads/master | 2023-05-05T04:05:31.617869 | 2019-04-25T22:10:06 | 2019-04-25T22:10:06 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,123 | r | bb_lollipop.Rd.R | library(billboarder)
### Name: bb_lollipop
### Title: Helper for creating a lollipop chart
### Aliases: bb_lollipop
### ** Examples
# From wikipedia
sw <- data.frame(
film = c("The Force Awakens", "The Phantom Menace",
"Revenge of the Sith", "A New Hope",
"Attack of the Clones", "The Empir... |
232e3741a7a4e21aaeb9992149c9378fb840c93e | e5c43a31a082bbfec5ebbc20b34d373896721579 | /R/spartan/spartan_eg_fire_cal_out.R | 5a6fd85d6c9f37304ff668dae0ea637f75a7416d | [] | no_license | geryan/rfst | 3dde3a499651f3a1ccc736f8c6597c5972f0e17c | 0aac1f0c3b17096af0c5b0b06e1ad80ac6d709ca | refs/heads/master | 2023-05-02T12:32:51.743467 | 2021-04-27T01:26:47 | 2021-04-27T01:26:47 | 164,573,310 | 1 | 1 | null | null | null | null | UTF-8 | R | false | false | 2,974 | r | spartan_eg_fire_cal_out.R |
source("R/spartan/spartan_settings.R")
library(dplyr)
library(tibble)
library(raster)
library(rgeos)
library(sf)
library(tidyr)
source("R/functions/source.functions.R")
source.functions("R/functions")
ntimesteps <- 14
proj_path <- "/data/gpfs/projects/punim1340/eg_fc_out/"
###
eg_mask <- raster(x = "/data/gpf... |
ce0a19951240132a3952a2a45e657ed4b8b053b7 | df33630313df583aa2a48614925dc524d982f27b | /16S/spatial_analysis/NEON_sampling_effort/NEON_sampling_effort_site.level_16S.r | f1f5731c5c2e34817c8771ebc7b4c4591e19b58a | [
"MIT"
] | permissive | saracg-forks/NEFI_microbe | fa0e28587288059908a6ab144854e352eeae7443 | e59ddef4aafcefdf0aff61765a8684859daad6e0 | refs/heads/master | 2023-03-22T03:21:57.634599 | 2021-03-15T09:13:16 | 2021-03-15T09:13:16 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,570 | r | NEON_sampling_effort_site.level_16S.r | #testing for observation uncertainty at the site level for bacterial groups.
rm(list=ls())
source('paths.r')
source('NEFI_functions/tic_toc.r')
library(doParallel)
library(DirichletReg)
library(RCurl)
script <- getURL("https://raw.githubusercontent.com/colinaverill/NEFI_microbe/master/paths.r", ssl.verifypeer = FALSE... |
9ea1782f5491fd0baace6893a4fa2c46b061dc8c | 727e96e85a03cf01d46c132225e171218c8dd1e5 | /man/assessLakeProfiles.Rd | 8e3485350d2204d2455a26d1e91d5bd3d81a4b8a | [
"MIT"
] | permissive | utah-dwq/irTools | 6faf9da88514cf72b2166f48074348c00a6f2137 | da34c77f363a00767563d76112ea87004c3be0d4 | refs/heads/master | 2023-08-31T23:58:52.981989 | 2023-08-25T15:31:22 | 2023-08-25T15:31:22 | 147,577,302 | 2 | 0 | MIT | 2022-08-30T21:54:40 | 2018-09-05T20:44:04 | R | UTF-8 | R | false | true | 2,042 | rd | assessLakeProfiles.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/assessLakeProfiles.r
\name{assessLakeProfiles}
\alias{assessLakeProfiles}
\title{Run lake profile assessments}
\usage{
assessLakeProfiles(
data,
do_crit = list(`3A` = 4, `3B` = 3),
temp_crit = list(`3A` = 20, `3B` = 27),
uses_assessed... |
dd839320833576e430819573161a7e0cf5a11e5f | 05884bd8afb3222aec86c6a2b363e67ed3c64590 | /toolbox/R/safeRbind.R | ddb285f2c51001a354c4bfddf378b5d98f35d9ab | [] | no_license | nmarticorena/mineria_datos | bcfbea31e6de6f292e4404068b360638ab8a3cbb | 6e3f22c2fb79fe551a5d8c94136f495638088813 | refs/heads/master | 2020-03-09T00:36:28.806062 | 2018-06-14T03:12:35 | 2018-06-14T03:12:35 | 128,492,056 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,041 | r | safeRbind.R | #' Safe Rbind
#'
#' Recieve a list of data tables or data frames and combine them into one by columns. It fills the missing columns in a dataframe with \code{NA\'s}
#' @usage safeRbind(dataframes,\cr
#' cols = unique(do.call(c, llply(dataframes, colnames))))
#' @param dataframes a list of dataframes.
#' @param c... |
1135a8fa6c78576e9d253c6dd93b7799a4e00cc4 | ec4286470afad909542c230c7ad5563e00eca93f | /set_vars.R | 556fafbae73ca0999278fe671d569066339eb90a | [] | no_license | ether8unny/hopappmodule | 20ac85ce9d9c8a907ca5e0d24e8f4f031ade9c61 | 15d5f87fd223a23ab611b56d9875b3200c306a8b | refs/heads/master | 2020-04-03T18:01:19.122072 | 2018-10-30T22:51:29 | 2018-10-30T22:51:29 | 155,468,025 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 4,188 | r | set_vars.R | #function for dummy inventory
make_inv_db <- function(){
load("~/hopappmodule/data/inv_classes")
load("~/hopappmodule/data/prod_list")
load("~/hopappmodule/data/prod_num_list")
inv_qty <- data.table(prod_name = prod_list, prod_num = prod_num_list)
inv_qty[,eval(inv_classes[1]) := as.integer(3)]
inv_qty[... |
dccd0c232aa00025ccf60d7ea0a40d632cdb49dd | 3c5e3f9a4c5db7b26a0a2cf4c286aa8fd4edd051 | /man/shiny_rot.Rd | fd8012038fb0a5730f0e7a8ee65de30f474c4978 | [
"MIT"
] | permissive | leahpom/MATH5793POMERANTZ | f8f8f639e1f522da200f57cd242173e58d11ab1d | b8357d19142f15c9d0d7fa27c03af4a64083a352 | refs/heads/master | 2023-04-20T06:21:21.447810 | 2021-05-04T04:37:17 | 2021-05-04T04:37:17 | 335,433,107 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 2,321 | rd | shiny_rot.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/shiny_rot.R
\name{shiny_rot}
\alias{shiny_rot}
\title{Rotations and Data Plots}
\usage{
shiny_rot()
}
\value{
Table with the first six entries of the uploaded data
A scatterplot that is a ggplot2 object
A second ggplot2 scatterplot
}
\descr... |
75310e7010d5664cf7186a4ce3c7f58eeb74e9aa | b3bcb9305cb597b1840e3c09bb76b440ea769ffb | /part3.R | 8bdfd523e25d57c37a1f37e4fae0e0cc267e5144 | [] | no_license | aejb22122/sel_academy | a9b3dc75a2fa0274d954d54ba2a3f6748bc5ff4f | 4f272d60452e86598bb5fb72b80743536a2a8b9b | refs/heads/master | 2020-07-27T11:47:29.318862 | 2019-09-17T14:47:05 | 2019-09-17T14:47:05 | 209,079,727 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 14,585 | r | part3.R | # Author: Annick Eudes JB Research Manager
# Date: June 14, 2018
library(readxl)
my_data <- read_excel("my_data.xlsx")
View(my_data)
# We start by defining the columns we whant to tranform to numeric :
numerizeCol <- c("Q10:1", "Q10:2", "Q10:3", "Q10:4", "Q10:5", "Q10:6", "Q10:7", "Q10:8")
my_data[nu... |
57ed2489e9311bd1f7ff90f9329fd2fafbf879a3 | 02cb1a96eb55e557c624acc55dbedba51ad13851 | /man/table_selectBy_Status.Rd | f2fe4947affd3a103b57eb3e294d01ba22ae6b2f | [] | no_license | takewiki/mdmpkg | ee7beecf4d2f5df37c7f0a43d42d2130861a3ae7 | 65b86a2d823f9f803adf935ac0f38cccfa571f79 | refs/heads/main | 2023-05-09T22:01:06.222887 | 2021-06-08T09:11:21 | 2021-06-08T09:11:21 | 305,067,122 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 513 | rd | table_selectBy_Status.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/util.R
\name{table_selectBy_Status}
\alias{table_selectBy_Status}
\title{按状态查询表}
\usage{
table_selectBy_Status(
config = cfg_edge,
table_name = "t_icitem_view",
FStatus = "FIsDo",
FValue = 0
)
}
\arguments{
\item{config}{配置文件}
\item{... |
d27de4746538f3d5184f5beb7cdbf57861e0b966 | 72d9009d19e92b721d5cc0e8f8045e1145921130 | /evolqg/man/TestModularity.Rd | d00910145917a3a38574cd3ba1165fe49e67d64a | [] | no_license | akhikolla/TestedPackages-NoIssues | be46c49c0836b3f0cf60e247087089868adf7a62 | eb8d498cc132def615c090941bc172e17fdce267 | refs/heads/master | 2023-03-01T09:10:17.227119 | 2021-01-25T19:44:44 | 2021-01-25T19:44:44 | 332,027,727 | 1 | 0 | null | null | null | null | UTF-8 | R | false | true | 2,210 | rd | TestModularity.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/TestModularity.R
\name{TestModularity}
\alias{TestModularity}
\title{Test modularity hypothesis}
\usage{
TestModularity(
cor.matrix,
modularity.hypot,
permutations = 1000,
MHI = FALSE,
...,
landmark.dim = NULL,
withinLandmark = ... |
315d8e6df9e27f865a26de6e84f52a3ca740ad60 | c1afead7b902e231afb0939f80ab3e26e434ab8c | /fourier.R | dcb13f9fab55d4daf88090e77252568aa960ce60 | [
"MIT"
] | permissive | SantoroPablo/economic_time_series | 23af86f1eca94995935347e57b64836599cb353e | cef67f1273f2c39b642401edc5c581a8ede9f05c | refs/heads/master | 2020-04-11T20:01:44.619462 | 2018-12-11T19:58:22 | 2018-12-11T19:58:22 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,097 | r | fourier.R | #### Librerias ####
library(tidyverse)
library(lubridate)
set.seed(1)
#### Datos ####
gold = read_csv("data/GOLD_1791-2018.csv",skip = 3)
interest_rate = read_csv("data/INTERESTRATE_1857-2018.csv",skip = 1)
cpi = read_csv("data/USCPI_1774-2018.csv", skip=4)
gdp = read_csv("data/USGDP_1790... |
8dcb4ac54b4762e8b7639f05728a994556935cdd | 8527c725baba37bc75031f40093183462db7073f | /scripts/create_templates.R | cbbd33782b578ee6f993bddc5847731dadcae9ad | [
"MIT"
] | permissive | davidski/evaluator | 776aafae717d68b017e2db8ee3fef8fc98342e66 | 27d475bb06ecda7ba11feef3e219519f2d6ce404 | refs/heads/main | 2023-01-20T20:15:17.259065 | 2022-01-25T04:55:13 | 2022-01-25T04:55:19 | 57,260,994 | 142 | 47 | NOASSERTION | 2022-12-21T05:01:15 | 2016-04-28T01:36:16 | R | UTF-8 | R | false | false | 154 | r | create_templates.R | #!/usr/local/bin/r
## initialize templates
message("Creating templates...")
library(evaluator)
create_templates("/data")
message("Templates created.")
|
522b0836ada79d890967068b5e74f2eb2e8f7f08 | c6eca3d4330fa1560ada90c5dbb83264e7f04595 | /man/consensus.Rd | e4e9659502846b800ac4035a313db8a4d4ff2d57 | [] | no_license | richelbilderbeek/BALCONY | 7248a94ddfd7588a2822f33613f070efdc1a3667 | 7d26159aa93d1f56427b88e26fb5448b82246ce3 | refs/heads/master | 2022-12-31T18:55:02.309956 | 2020-10-26T09:57:29 | 2020-10-26T09:57:29 | 307,326,223 | 0 | 1 | null | 2020-10-26T09:48:50 | 2020-10-26T09:48:50 | null | UTF-8 | R | false | true | 1,239 | rd | consensus.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/conservationFuncs.R
\name{consensus}
\alias{consensus}
\title{Determine consensus sequence}
\usage{
consensus(alignment, threshold)
}
\arguments{
\item{alignment}{output of of \code{\link[seqinr]{read.alignment}} function or grouped alignment... |
e087a2b5435a112b37c250d2bf66743fa0e73979 | 879f8cc2e4662c68c2b1c0043237463c78c5ec5f | /package_management/load_package_locally.R | e77c7560b06a0303f27a214711f3d521c30f87d5 | [] | no_license | ClaraMarquardt/huhn | f063962e8ce578c2b640530de83b02268069d0f7 | 23a71e44f5e5ec62ba4b7acde8c738ab1c47559f | refs/heads/master | 2021-08-23T22:11:35.977202 | 2017-12-06T20:10:52 | 2017-12-06T20:10:52 | 101,329,780 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,336 | r | load_package_locally.R | #----------------------------------------------------------------------------#
# Purpose: Load scripts locally
# Author: Clara Marquardt
# Date: 2017
#----------------------------------------------------------------------------#
#---------------------------------------------------------------------... |
ab72f16b7abb2d3b4b453bed22811ccc14c12253 | f3405c30760de1e2e72b397e847921f8b4d96803 | /src/process.r | 1abafcc6dee62b3497e545f469bd32e2db6e3419 | [] | no_license | humodz-trabalhos-icmc/nlp.2018.1 | 84421e9976fd7d0e61224781c45c6d098f6e8263 | ce8ffc9bfe5d5db53ceaee1834ba3dd840c7cfaa | refs/heads/master | 2020-03-20T22:57:25.667318 | 2018-07-05T00:55:19 | 2018-07-05T00:55:19 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,893 | r | process.r | # process.r INPUT_DIR OUTPUT_DIR
# Reads udpipe annotated tables from INPUT_DIR and writes processed text to OUTPUT_DIR
keywords = c(
"indicado", "indicada", "recomendado", "recomendada",
"utilizado", "utilizada", "destinado", "destinada")
# Converts IDs of the form "A-B" to A
fix.token.id <- functi... |
0a53675569cac1d400ef96d7907d4e18a89b803b | 07993f771b8a0cd6a83f3e7d1ea9c58cc17d602f | /Archive/Accessing CCII netCDF files.R | b5d65535bd5166ae1a30033e43eed60e89547ecb | [] | no_license | SallyFreanOwen/insurance-and-climate | 817be05881f9bd1fcb3df1bc94ebff0a11620187 | fff9575347fe5a0d72f921f913949eebe6d4ea76 | refs/heads/master | 2021-07-08T22:21:18.497805 | 2020-07-28T03:29:35 | 2020-07-28T03:29:35 | 150,044,302 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,525 | r | Accessing CCII netCDF files.R | ### Beginning to think about extracting data from a netCDF using R
# Sally Owen
# Public Insurance Project
# November 2017
# Using the ncdf4 package:
install.packages("ncdf4")
install.packages("ncdf.tools")
install.packages("ncdf.tools")
install.packages("RNetCDF")
install.packages("chron")
install.packages("RCol... |
d2ea1331672b45f3022b557ec88ef886d5cc547d | 15e71e39f2ddf6ad7fae8e749419142573852104 | /R/binarizer.R | 0baa736db422db68d9930df6eb6125712c6d36e5 | [] | no_license | LudvigOlsen/LRO.utilities | a61eb0239f2fac91818cfd9f4a639fa2df16bd5d | b21e5d8f1491807b85a1522db149c5b4e14476b8 | refs/heads/master | 2021-01-22T18:37:50.827997 | 2020-11-05T21:57:31 | 2020-11-05T21:57:31 | 85,097,753 | 1 | 2 | null | 2017-05-14T21:33:31 | 2017-03-15T16:47:56 | R | UTF-8 | R | false | false | 2,926 | r | binarizer.R | # Binarizer
#
#' @title Binarize multiple columns at once
#' @description Binarize multiple columns of a dataframe based on a given threshold.
#'
#' \strong{binarizer} is designed to work with \link[magrittr]{\%>\%} pipelines.
#'
#' \strong{binarizer_} is a standard evalution version.
#' @param data Dataframe, tbl,... |
8533e09b651dc3e6c451ba605d29a3bdf392d9c9 | 460a928062977465774d982516ecb2b6fa5997bf | /man/slider-package.Rd | 8d11242ae9e32c92370277c44230f9c837542815 | [
"MIT"
] | permissive | erhard1/slider | ba73550842db4cadbf1248d7adcf86204273f3eb | bb0501f00918bb52f326a54434600a29cdafd190 | refs/heads/master | 2023-06-13T07:33:28.330909 | 2021-07-01T19:49:44 | 2021-07-01T19:49:44 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 812 | rd | slider-package.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/slider-package.R
\docType{package}
\name{slider-package}
\alias{slider-package}
\alias{_PACKAGE}
\title{slider: Sliding Window Functions}
\description{
Provides type-stable rolling window functions over any R data
type. Cumulative and exp... |
c255aba50d11729733c2f8b1aade268aece974e3 | 4b258f2282aa412dedaa5b5d89d33a77c2bdf430 | /man/summary.intELtest.Rd | 50249f052d464dc16da6a478f281735bad667344 | [] | no_license | news11/survELtest | 6ada624ef47bc513230398c10683be0c68cb0c24 | 578335a28dcfcee04c24a44dd031d025422afc80 | refs/heads/master | 2020-09-20T02:37:17.001049 | 2020-01-16T03:32:50 | 2020-01-16T03:32:50 | 224,186,255 | 2 | 0 | null | null | null | null | UTF-8 | R | false | true | 1,748 | rd | summary.intELtest.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/summary.intELtest.R
\name{summary.intELtest}
\alias{summary.intELtest}
\title{Summary function for intELtest object}
\usage{
\method{summary}{intELtest}(object, digits = max(3L, getOption("digits") - 3L), quiet = FALSE, ...)
}
\arguments{
\it... |
f6d37bda62f3728fa10573dae4e163f609cdb88d | 7eacb63dc1dad1483f8ca1bafd317f256f5ad860 | /Carpentry2017.R | a09026ce57261025becf1bb2f84dd77d33109ac7 | [] | no_license | espinozav/Carpentry2017 | 4f6f8a80348a34a5f00f9054be870e34b7cee165 | 125dc8a5d72edb51fffa25b67bfb83e2c6c3100a | refs/heads/master | 2021-01-22T17:39:27.916472 | 2017-08-18T23:05:46 | 2017-08-18T23:05:46 | 100,730,554 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,323 | r | Carpentry2017.R | ###DATA VIZ
library(tidyverse)
surveys_complete <- read.csv('data_output/surveys_complete.csv')
##ggplot2 ----
ggplot(data= surveys_complete, aes(x=weight, y=hindfoot_length)) + #telling we are going to be plotting off of this data, define aesthetics, plus sign adds more plotting instructions
geom_point(alpha =0.... |
a4a99349f2689d151b560721bcdd9e21f94fad48 | 520aa74848464c786cff396ad53748ee9b4b598a | /code/0_import_ebsco.R | 8ba8a43960ea984d47ee905d1abdbea952560e23 | [] | no_license | gastonbecerra/bigdata_humanidades_biblio | 1d61d2eb8a4828e6d6b4325966902e6ded1e3945 | 49e16fe63b85389499511f86676ea9c48841605f | refs/heads/main | 2023-03-10T17:02:14.063927 | 2021-03-01T23:59:35 | 2021-03-01T23:59:35 | 323,950,015 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 10,588 | r | 0_import_ebsco.R | # import dataset ebsco
# - importar metadata
# - separar / importar ocr
# - separar / importar referencias
library(tidyverse)
library(foreach)
library(xml2)
library(rvest)
library(doParallel)
library(jsonlite)
# import ebsco metadata y ocr -------------------
path <- './data/raw/ebsco_full/'
global_metadata <- da... |
7e6971618031cc49929690f9cdf2208bd02ff3cd | 686ee8bbc2e754c22304261be5ce96f58b89a079 | /plot4.R | f2b4929adde865d50bafabf8c3c37ba0b14ce6da | [] | no_license | danielstallworthmit/ExData_Plotting1 | ea10e2c90cd5c52142bbd35e2e3fde7a32bbe7cc | fd0a9c6a4c9d67a2d050081d03ac9855b094c57b | refs/heads/master | 2021-01-19T09:03:48.813817 | 2017-04-09T18:21:57 | 2017-04-09T18:21:57 | 87,720,653 | 0 | 0 | null | 2017-04-09T16:00:04 | 2017-04-09T16:00:04 | null | UTF-8 | R | false | false | 1,540 | r | plot4.R | library(data.table)
# Set up data using filtered data from plot1
data_filtered <- fread("household_consumption_filtered.csv",sep = ",",header = T)
# Add DateTime column as combination of Date and Time columns
data_filtered <- within(data_filtered, DateTime <- paste(Date, Time, sep = " "))
data_filtered$DateTime <- as.P... |
febf1f5f77eaceae17c33338fc35be4a473d68b3 | 1aefcc070be0f20b0d87a961041a4655c12d3a65 | /homework2/ui.r | 0a4990efb72d3d0b04c306c3f7b038a511713de1 | [] | no_license | swang114/msan622 | d6289573b05d788c729348e52d544e0088a993ee | 34a9a7e10c76bdf8a3ed5215e9da3d91ad53a8e1 | refs/heads/master | 2021-01-20T07:20:38.603255 | 2014-05-16T14:49:06 | 2014-05-16T14:49:06 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,789 | r | ui.r |
library(shiny)
shinyUI(
pageWithSidebar(
headerPanel("IMDB Movie Ratings"),
sidebarPanel(
radioButtons(
"mpaar",
"MPAA Rating:",
c('All','NC-17','PG','PG-13','R')
),
br(),
checkboxGroupInput(
"gen",
"Mo... |
0421e85aff236d51ce463da17788ae7df88dc3b4 | 49ff0bc7c07087584b907d08e68d398e7293d910 | /mbg/mbg_core_code/mbg_central/LBDCore/man/rake_cell_pred.Rd | 7833b3d2c095c092e1cc0cfbb72fde096103f80a | [] | no_license | The-Oxford-GBD-group/typhi_paratyphi_modelling_code | db7963836c9ce9cec3ca8da3a4645c4203bf1352 | 4219ee6b1fb122c9706078e03dd1831f24bdaa04 | refs/heads/master | 2023-07-30T07:05:28.802523 | 2021-09-27T12:11:17 | 2021-09-27T12:11:17 | 297,317,048 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 5,554 | rd | rake_cell_pred.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/rake_cell_pred.R
\name{rake_cell_pred}
\alias{rake_cell_pred}
\title{Standard Raking Function}
\usage{
rake_cell_pred(cell_pred, rake_to, reg, year_list, pop_measure,
rake_method = "linear", rake_subnational = T, crosswalk = F,
shapefile_... |
9592eb0357177cb4b21cf46643413676e373c85b | 5bd83f74cd2c7e88c0b56e25d3b9b415dcb18c06 | /man/map_edge_attributes.Rd | 2b720461cee028fe6bae9919b34368cb9069dc8b | [] | no_license | meerapatelmd/chariotViz | 123c04e6fc6b09b2ffdc9ef1eb9fa94d227ee846 | c45947a963b23f75237fe4417dd03b6f27c620d5 | refs/heads/master | 2023-07-19T21:44:18.089969 | 2021-09-04T17:30:09 | 2021-09-04T17:30:09 | 394,073,446 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 5,568 | rd | map_edge_attributes.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/map.R
\name{map_edge_attributes}
\alias{map_edge_attributes}
\title{FUNCTION_TITLE}
\usage{
map_edge_attributes(
nodes_and_edges,
fontsize = 26,
len = 5,
label_from = relationship_name,
style_from = defines_ancestry,
style_map = d... |
9cab303d2f13363b427053d0df07c77d7e20d2ec | 45bc4ef53de6d474dc28fc803b3879af6fe77e56 | /assets/R/06202015_datacience_circles.R | 2b28baf16679f30c35026ea945116b137dd53a83 | [
"MIT"
] | permissive | sumendar/simpleblog | 224c293d9d8507ac4ff82058c3246fa9ea2ad683 | 8d411491dc2fe937bf56562539a34cc2e5f8a837 | refs/heads/gh-pages | 2021-08-19T07:56:39.262150 | 2017-11-25T10:17:46 | 2017-11-25T10:17:46 | 111,040,135 | 0 | 0 | null | 2017-11-17T01:01:00 | 2017-11-17T01:00:59 | null | UTF-8 | R | false | false | 356 | r | 06202015_datacience_circles.R | # create a multi
library('ggplot2')
gg <- ggplot() + scale_x_continuous(limits=c(0,1)) + scale_y_continuous(limits=c(0,1))
for(i in 1:10) gg <- gg + geom_point(aes(x=rnorm(1, 0.5, 0.04), y=rnorm(1, 0.5, 0.04)), size=runif(1, 40, 100), color='red', alpha=.15)
plot(gg)
gg <- gg + geom_point(aes(x=.5, y=.5), size=100,... |
c549c7a46f2f58e75d2a0c73c01d007cf40457ed | 29585dff702209dd446c0ab52ceea046c58e384e | /MNS/R/gen.Network.R | 2ea27188166d3e101ed9809001bb5bd42defd8c7 | [] | no_license | ingted/R-Examples | 825440ce468ce608c4d73e2af4c0a0213b81c0fe | d0917dbaf698cb8bc0789db0c3ab07453016eab9 | refs/heads/master | 2020-04-14T12:29:22.336088 | 2016-07-21T14:01:14 | 2016-07-21T14:01:14 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,057 | r | gen.Network.R | gen.Network <-
function(method="cohort", p, Nobs, Nsub, sparsity, REsize, REprob, REnoise){
# wrapper function for generating random networks
#
# INPUT:
# - method: method to be used to simulate networks. Either "cohort" for networks as described in Monti et al 2015 or "Danaher" for networks as described i... |
89d47d8f59eac1262256ac188e17f235c1a0b16f | 289b70ac6d95d7f4585b1ac61439dfefd786fc77 | /R/estUtil.R | 084760c147630ed6606071823ec5159feac5594e | [] | no_license | syerramilli/R-sysid | f8ede18883a691e363b5ca3110c2583a5d7a426c | be2928b20b5f3e1230f292ea45166ae95cc71a23 | refs/heads/master | 2023-06-08T17:55:07.929065 | 2023-06-07T03:29:14 | 2023-06-07T03:29:14 | 29,390,663 | 3 | 2 | null | 2023-06-07T03:29:15 | 2015-01-17T12:38:48 | R | UTF-8 | R | false | false | 6,422 | r | estUtil.R | # Implementation of the Levenberg Marquardt Algorithm
levbmqdt <- function(...,obj,theta0,N,opt){
dots <- list(...)
# Optimization Parameters
tol <- opt$tol; maxIter <- opt$maxIter
d <- opt$adv$LMinit; mu <- opt$adv$LMstep
df <- N - dim(theta0)[1]
# Initialize Algorithm
i <- 0
l <- obj(theta=th... |
6ebd8c8482260cfffbde2c8717acb87493fda173 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/PAFit/examples/get_statistics.Rd.R | 4943809ac4a8b0aad3b59c86a7766bd8bf573b9e | [] | no_license | surayaaramli/typeRrh | d257ac8905c49123f4ccd4e377ee3dfc84d1636c | 66e6996f31961bc8b9aafe1a6a6098327b66bf71 | refs/heads/master | 2023-05-05T04:05:31.617869 | 2019-04-25T22:10:06 | 2019-04-25T22:10:06 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 272 | r | get_statistics.Rd.R | library(PAFit)
### Name: get_statistics
### Title: Getting summarized statistics from input data
### Aliases: get_statistics PAFit_data
### ** Examples
library("PAFit")
net <- generate_BA(N = 100 , m = 1)
net_stats <- get_statistics(net)
summary(net_stats)
|
f193ba32994bd842772f8d827917de6167aab4bf | ae987d62aee7832e529ff888f05f2886ef1634a5 | /R/dcm_multiple2singlechoice.R | 08e9ae99a632f3c3da2da696acc6ecaf598063a0 | [] | no_license | mbonoli/funcionesMBO | febcd54cd0284e645df26c91ff0318e5ecd8e043 | 5c371d0b30fdfa262c2d66495c476b61e1e2b914 | refs/heads/master | 2021-01-20T18:16:21.755333 | 2016-07-23T21:31:48 | 2016-07-23T21:31:48 | 63,553,704 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,777 | r | dcm_multiple2singlechoice.R | dcm_multiple2singlechoice<- function (datalong, choicevar="choice", chidvar="chid", taskvar, indvar) {
require(dplyr)
names(datalong)[names(datalong)==choicevar] <- "choice"
names(datalong)[names(datalong)==chidvar] <- "chid"
choiceXchid <- summarise(group_by(datalong, chid), freq=sum(choice))
# print(head(... |
4362cd8341fe3a451824891b50d9be8d93b8b909 | 093cf42c7d4bee93e30a19382f3748d1bddc5adc | /week05/datetime.R | ec08b65721e3bcf61b57e2df9c37ccd9ef01060f | [] | no_license | Huride/radsp | 262dfa0e1888c240a59771d3390c14188e778ee7 | 23e3713d1f9b3891cdae5f89b8021905b4feedbb | refs/heads/master | 2022-12-05T16:02:11.174257 | 2020-08-19T09:58:44 | 2020-08-19T09:58:44 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,621 | r | datetime.R | # "2020-03-03" "2020-03-04 23:11:34"
# "04/11/2020" "20-06-11" "2020/05/11"
# 파일에 저장되어 있는 날짜들은? 문자열.
# R이 이해할 수 있는 날짜 형식으로 변환. => 요일, 125일 후는?
# 우리 회사 형식에 맞는 문자열로 바꿔서, 저장.
d <- Sys.Date()
d
class(d)
d + 137
weekdays(d)
weekdays(d+137)
# 2020,07,22
# R의 날짜 형식 Date를 , 문자열로 변환(우리 회사 형식에 맞게)
format(d, format="%Y,... |
c6cc4e41e22b42ba164423168a7fc94b99d546ad | e5ac9d127cbb9dcba76d2f68a252380be2835942 | /community.r | 49e9f0733b15ff36d60dc5ab673e67f22cf04bb4 | [] | no_license | Arthur-Valance/Qualitative-Modeling-BarentsRISK | 0f42d3ea144c3107468954349ec0d8c342295ddf | 32de97a486e8081f56ee48b83a9cf601f339cfab | refs/heads/master | 2023-07-15T07:51:25.173983 | 2021-07-27T09:34:40 | 2021-07-27T09:34:40 | 369,253,160 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 6,242 | r | community.r | ## Need util for URLencoding
library(utils)
## Extract node labels
node.labels <- function(edges) {
levels(edges$From)
}
## Convert edge descriptions to an adjacency matrix. The
## required.groups argument determines which edge groups will appear
## in the matrix.
adjacency.matrix <- function(edges,labels=F,requ... |
28e041b402d230471fb090a3555862a9ba4b264d | b02e46514d93b138756c0a5c73e79215e99995ae | /WorldTrade.R | ba6a49136699726434f6dfc28af6ab283cd6c454 | [] | no_license | AvijeetBose/WorldTradeProject | 474d97edd29ea8c8ded43397280bcfc86e6d9bcd | 2e811c3bb12d5634380e6ff46b98c641797b8900 | refs/heads/master | 2022-11-27T06:14:59.774148 | 2020-08-07T07:35:23 | 2020-08-07T07:35:23 | 285,767,746 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,176 | r | WorldTrade.R | #install libraries
library(dplyr)
#load the dataset
WorldTradeRecord <- read.csv("D:/R-Code/Project/Raw data.csv")
#Create duplicate
TradeBusinessWorldwide <- WorldTradeRecord
#Update Column Name
names(TradeBusinessWorldwide) <- c("CountryName", "Year", "Commoditycode", "Commodity", "Flow",
... |
b0d774d8b98a40e8b9579bc67c8e01bcece5b10f | e3e3843080406b83178105f59b2f366643f545a6 | /fixChangelogLinks.R | 2811b969a4e0ad7426df75b9a8a9c12dff8029ab | [] | no_license | nickmckay/lipdverseR | c1dcdb9e6752a41a00d7f9386cf684f24f3f1f46 | 56b01e8ce33dc9f71e39bdf1c5c978f3b33d1db7 | refs/heads/master | 2023-06-07T19:16:43.787187 | 2023-05-31T18:20:31 | 2023-05-31T18:20:31 | 182,172,405 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 348 | r | fixChangelogLinks.R | #fix summary links
library(stringr)
#"../changelogSummary.html" to "changelogSummary.html"
for(i in allIndex){
ad <- readLines(i)
if(any(str_detect(ad,pattern = "../changelogSummary.html" ))){
adf <- str_replace_all(ad,pattern = "../changelogSummary.html",replacement = "changelogSummary.html")
print(i)
... |
bf3eea2d96fa2181e88809dbc38a76122d6d51c9 | 5db34fe55462f237703358e5ead7c80299de3d02 | /R/powerTransform.R | 4d7c6b65ed6945426149d5d8b8271d7aa943393e | [] | no_license | cran/tlm | 687fe4cb6d25a1086f46e61afb5faa898037f9e2 | 4a399dc84a6b38f8681ef4709c14115d89505f27 | refs/heads/master | 2021-01-17T07:11:00.175043 | 2017-04-10T12:15:19 | 2017-04-10T12:15:19 | 23,803,445 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 98 | r | powerTransform.R | powerTransform <-
function(x, power)
{
if (power == 0) xt <- log(x) else xt <- x^power
xt
}
|
9648916b5bf9b0e2b1cdec9e4184747c09369bda | 294da1183cd4ac9feac38cea527f10b9e4ea8378 | /test.R | b59b4635f1d211fcf0b87331a88266c6a74cf984 | [] | no_license | M-Atsuhiko/Result_Graphs | a6c4eb913ef1c611ce138fbd204d291dbdde0be8 | b6d92ca02b106738032ce2cd1474d09cec7e8c3c | refs/heads/master | 2021-01-01T20:05:51.186799 | 2015-02-05T15:02:43 | 2015-02-05T15:02:43 | 28,659,099 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 88 | r | test.R | a <- 1:10
b <- 11:20
c <- 21:30
test <- data.frame(a,b,c)
print(test[test$a == 2,])
|
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