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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
3b559f97c5b1021fc613f7745cbbc8e0d9ff2cd6 | f08cd32750b98a195a67fdff699f0a835a2e615f | /Image_Processing/knit/knit.R | 2000039c86b4bc5df8e7681528be27e0fb7d5504 | [
"MIT"
] | permissive | katharynduffy/LandCarbonAdvances | cb4f498561a8893625db5104df1042f7972ed93a | 591fc6480db4be32f89a487429e354819bac11a1 | refs/heads/master | 2020-05-21T02:31:54.089833 | 2019-05-21T16:10:11 | 2019-05-21T16:10:11 | 185,880,339 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 383 | r | knit.R | ## this file is to run by the isntructor to preapre the teaching materials
library(knitr)
wd <- getwd()
setwd('Image_Processing/')
rmd_files <- dir(pattern = '*.Rmd', full.names = TRUE)
for(ii in 1:length(rmd_files)){
knit(rmd_files[ii])
purl(rmd_files[ii])
}
code_files <- dir(pattern = '*.R$')
file.rename(fr... |
7efd5614d25464b0a5329c5d6b6acff1db8ce870 | 874878b7cb5361362ce01d6c98f86723304bb605 | /body_cam.R | 91253d0ae5caa79744bdfa104a298deb5c3e5bbf | [] | no_license | ConnerArdman/Police-Shootings | f648f4dd0b6a4a64a5065b6834875ab6d0680726 | 90b3fa8dfc60d91e58cc78cec663a7b1afcf9660 | refs/heads/master | 2022-01-25T19:46:25.916229 | 2019-07-04T00:23:12 | 2019-07-04T00:23:12 | 109,912,977 | 0 | 2 | null | null | null | null | UTF-8 | R | false | false | 4,576 | r | body_cam.R | library(dplyr)
library(ggplot2)
library(plotly)
shooting.data <- read.csv("data.csv", stringsAsFactors = FALSE)
# Count how many shootings are in the dataset.
total.shootings <- nrow(shooting.data)
# Seperating data based off whether officer had bodycam
bodycam.false <- shooting.data %>% filter(body_camera == "False... |
2204a5ec16ea534f398c55b7fc608ced09918406 | e9291a6e2fffd64065f61c7e2a9c8a1a6878779b | /tests/testthat.R | 641bd270454ea1f31276d0f9910c4b21dcc3ec3a | [] | no_license | dmenne/dknitprintr | bd92bc9ea38c734831fa7f33a30b1e058b3d513c | 3150de1817ac5db04f68e2d5473bbaa7e36d4d0d | refs/heads/master | 2020-06-14T10:39:17.869977 | 2019-08-02T07:32:44 | 2019-08-02T07:32:44 | 75,197,639 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 65 | r | testthat.R | library(testthat)
library(Dknitprintr)
test_check("Dknitprintr")
|
c69d1681287abd51b442dfabd36a9ef6381bec47 | 714e7c6736a2e3d8fd07634427c4a8bb3cef2d61 | /man/save_plot.Rd | bb4250aedc1e1bd5c556fc26e39b64aace4aaaba | [
"MIT"
] | permissive | flaneuse/llamar | da7cb58a03b2adbffb6b2fe2e57f3ffeede98afb | ea46e2a9fcb72be872518a51a4550390b952772b | refs/heads/master | 2021-01-18T00:10:00.797724 | 2017-10-24T13:41:21 | 2017-10-24T13:41:21 | 48,335,371 | 0 | 1 | null | null | null | null | UTF-8 | R | false | true | 1,124 | rd | save_plot.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/save_plot.R
\name{save_plot}
\alias{save_plot}
\title{Simple wrapper to ggsave}
\usage{
save_plot(filename, plot = last_plot(), saveBoth = FALSE, width = NA,
height = NA, units = "in", scale = 1)
}
\arguments{
\item{filename}{string contain... |
a4b8a3f45d23d97c1ff5e6708d4126a2f9ca8444 | 379a039dabc2404fec00d6bebffe0bf30ed473c0 | /man/cmmb.Rd | 9474d09f5b78b2719384f8c2f814875b5ea6a0ac | [] | no_license | mbsohn/cmmb | 7708ca784af3ad787331e70e2635d0550847ae2e | b92a3b32e4e39b8ac82220e14ce8ea63bc0bccee | refs/heads/master | 2023-06-16T08:43:30.055622 | 2021-07-05T20:14:33 | 2021-07-05T20:14:33 | 382,963,057 | 2 | 1 | null | null | null | null | UTF-8 | R | false | false | 3,062 | rd | cmmb.Rd | \name{cmmb}
\alias{cmmb}
\title{
Compositional Mediation Model for Binary Outcomes
}
\description{
Estimate direct and indirect effects of treatment on binary outcomes transmitted through compositional mediators
}
\usage{
cmmb(Y, M, tr, X, n.cores=NULL, n.boot=2000, ci.method="empirical",
p.value=FALSE, ForSA=FALS... |
c8227f18b97073286ab6221a14be13793cebe830 | 02db52e1ab4453e85f03c4d7dd19274626033dbd | /man/presentation.Rd | 2502a05ee08ee41fdb7502b1cd996487461b2ad7 | [] | no_license | riverlee/reports | def177c335b880bc0345de4a6d4a2984ea07f3fa | 26ea8b52f2a5d4f92c70fa9101eac648aa432038 | refs/heads/master | 2021-01-15T21:03:15.405664 | 2013-08-30T18:07:03 | 2013-08-30T18:07:03 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,618 | rd | presentation.Rd | \name{presentation}
\alias{presentation}
\title{Presentation Template}
\usage{
presentation(presentation = "presentation",
type = c("rnw", "rmd"), theme = "Madrid",
bib.loc = getOption("bib.loc"),
name = getOption("name.reports"),
github.user = getOption("github.user"),
sources = getOption("source... |
aae37572fd59020f63f239318827743d2552be15 | bf8c5c249994cc9df1684cbd402cb33a5439e681 | /man/randomize_trt2.Rd | 29c13157a9f3158b4669e044d95c36e32654ce8a | [] | no_license | cran/TwoArmSurvSim | 607eb6819ca04c9fb8d24d26c3cc5c6e31a00682 | 51d1274128f054bb6ded6d588679dcdbf9671dc9 | refs/heads/master | 2023-03-08T04:10:35.616291 | 2021-02-26T07:50:06 | 2021-02-26T07:50:06 | 323,359,862 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 527 | rd | randomize_trt2.Rd | \name{randomize_trt2}
\alias{randomize_trt2}
\title{Generate Block Randomized Treatment Label Based on Covariates Matrix for Two Arm Trial}
\usage{
randomize_trt2(cov_mat=cov_mat,blocksize=blocksize,rand_ratio=c(1,1))
}
\arguments{
\item{cov_mat}{Covariates matrix. }
\item{blocksize}{Randomization... |
efd5edea12e8d0a536b9ad64d32696b085ba2f0d | 2de9deb099bc4379d78df2efef50ded7916d4558 | /doc/mindev.R | ec3fb867be75adb9c7dff56cc9ebcad010b49d59 | [] | no_license | ablejec/StatPred | a2d4992cf097ff02514828a8ada55a082c57e7db | f46754f21e74109a1733654304f07a407b4fe4b4 | refs/heads/master | 2021-01-19T10:11:14.403418 | 2013-01-18T21:54:32 | 2013-01-18T21:54:32 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 6,885 | r | mindev.R | ###################################################
### chunk number 1:
###################################################
options(width=70)
set.seed(1234)
library(Hmisc)
#library(xlsReadWrite)
###################################################
### chunk number 2: gmean
############################################... |
6f87f3ddaf547eb1445c4b886247ee9aa4c49149 | d4599d2a5faeaa5e40994b8486e6becc59141fe1 | /man/auto.var.Rd | b37b2364cbb38b9aef873598042b2eca0a30fb03 | [] | no_license | Allisterh/forecast-pimfc | 6a61c568768a792babc49ba1f27cc89997c63cfa | 928986ec4932e7247fff857da58e53733ee00cd4 | refs/heads/master | 2023-03-16T23:02:45.366133 | 2017-03-13T23:35:45 | 2017-03-13T23:35:45 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 1,123 | rd | auto.var.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/autovar.R
\name{auto.var}
\alias{auto.var}
\title{Fit best VAR model to multivariate time series}
\usage{
auto.var(y, max.p = 6, ic = c("SC", "HQ", "AIC", "FPE"), seasonal = TRUE)
}
\arguments{
\item{y}{A multivariate time series}
\item{max.... |
518439e21e04cba18927f51642c2a70a7fba0b9e | 2d16a85f93eec6d13ddd32f3f12036058f440014 | /man/PS06.Rd | ddfee36a47030ac253e3cbd6a8e3238966fbaa1b | [
"MIT"
] | permissive | A-moosh/foofactors | d7ffc434d6450f072368c788558f601b05a640cf | 41046d93adf048ba004352a367097d681d85089e | refs/heads/master | 2023-04-12T09:27:13.683460 | 2021-05-13T20:09:57 | 2021-05-13T20:09:57 | 367,161,628 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 428 | rd | PS06.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/Untitled.R
\docType{data}
\name{PS06}
\alias{PS06}
\title{Medicaid Expenditure 2019.}
\format{
A dataframe with 51 rows and 4 variables:
}
\source{
\url{https://github.com/GeoDaCenter/opioid-policy-scan/blob/master/data_final/PS06_2019_S.csv}... |
cb820262dca290a8af9d06376b4379fa046231d3 | 9fa290918b0cc0b319d02f421763bbefa398e60d | /R/na.as.R | c5bc367f3973c7c3eb6d3e76f1f5deeba534bd87 | [] | no_license | cran/misty | 634e5bd6bf5e317fa1f4ee1f586d5572a4e47875 | 1a42b63704bf9daf2d920312bc1f04204bac85b4 | refs/heads/master | 2023-08-31T19:04:33.782877 | 2023-08-24T07:30:05 | 2023-08-24T09:31:21 | 239,395,613 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 5,822 | r | na.as.R | #' Replace Missing Values With User-Specified Values
#'
#' This function replaces \code{NA} in a vector, factor, matrix or data frame with
#' user-specified values in the argument \code{value}.
#'
#' @param x a vector, factor, matrix or data frame.
#' @param value a numeric value or character stri... |
66a968f6e3dbd1cd9e10368a0453bbd90ee16a7e | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/mudfold/examples/Plato7.Rd.R | 0bfc1af8c3223e6844fb73b67150838c0654da3a | [] | 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 | 194 | r | Plato7.Rd.R | library(mudfold)
### Name: Plato7
### Title: Plato's Seven Works
### Aliases: Plato7
### Keywords: datasets
### ** Examples
## Not run:
##D data(Plato7)
##D str(Plato7)
## End(Not run)
|
d1db29ba987e7a256c0f4862295795c8dced4a2b | f7408683a4b9f3ea36e6c56588f257eba9761e12 | /man/pffr.Rd | 3783caa92f38cba0d75e78fa6f11c750e678d6fc | [] | no_license | refunders/refund | a12ad139bc56f4c637ec142f07a78657727cc367 | 93cb2e44106f794491c7008970760efbfc8a744f | refs/heads/master | 2023-07-21T21:00:06.028918 | 2023-07-17T20:52:08 | 2023-07-17T20:52:08 | 30,697,953 | 42 | 22 | null | 2023-06-27T15:17:47 | 2015-02-12T10:41:27 | R | UTF-8 | R | false | true | 13,351 | rd | pffr.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/pffr.R
\name{pffr}
\alias{pffr}
\title{Penalized flexible functional regression}
\usage{
pffr(
formula,
yind,
data = NULL,
ydata = NULL,
algorithm = NA,
method = "REML",
tensortype = c("ti", "t2"),
bs.yindex = list(bs = "ps", ... |
52e8f1e2b0bf49b0568c35e94244c8cc0a3d63c7 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/PabonLasso/examples/BOR1.Rd.R | 7d7dd23d64e4895984f1b0a1f69fb8c2884be33d | [] | 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 | 256 | r | BOR1.Rd.R | library(PabonLasso)
### Name: BOR1
### Title: Is a vector of Bed Occupation Rates at the beginning of study
### Aliases: BOR1
### Keywords: datasets
### ** Examples
BOR1=c(72.54,48.86,42.77,40.81,60,28.61,20.29,12.84,100,47.07,78.51,45,49,20,88,90)
|
e20c7adff4e1572d62e1e476b08c5c09e0bde7e7 | 91dca679488c1a409cdbad5f7df34e3430f47ab2 | /lib/visual.lib.R | 71ba261a64dd8a3220adbf09869106dbaaa7051e | [] | no_license | joelescobar01/investmentStrategy | 3eb81247690c2c25316cc1b7583a88329acfe738 | e698282c4f17ea7dee9a9979cf800af7bdd78220 | refs/heads/master | 2023-01-07T17:10:53.886611 | 2020-11-11T15:02:02 | 2020-11-11T15:02:02 | 256,921,472 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,680 | r | visual.lib.R | library(TTR)
library(tidyverse)
library(tidyquant)
library(ggplot2)
zoom.last_n <- function( stockTbbl, n=14 ){
zoom <-
coord_cartesian(xlim=c(
nth(stockTbbl$date,n=-1)-days(n),
nth(stockTbbl$date,n=-1))
)
return( zoom )
}
max.pl... |
aef6ee37c61a54cf6ca09f0ea4232f174292fdd9 | c45fefaa8779071f3875cc9f43ea2e0b9dfedcd4 | /tests/testthat/test-formats.R | 463cb9b7db56f83272439be0bd2232c67e1cac44 | [] | no_license | noamross/texttable | e937a2a9b703b6505158c71b7a08f10703b8d4df | d1b17d3dcda4c47047863096154cb8fc54643a3b | refs/heads/master | 2016-09-14T01:32:45.610086 | 2016-04-19T15:34:40 | 2016-04-19T15:34:40 | 56,542,149 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,061 | r | test-formats.R |
# Test all the file types that pandoc lists as inputs
test_files = list.files(pattern = "table.*[^R]$")
test_files = test_files[-grep("(odt|latex|haddock)", test_files)]
cat("\nPandoc version:", as.character(rmarkdown::pandoc_version()), "\n\n")
context("Format checking")
for (file_name in test_files) {
file_typ... |
1cfff138c29c2591aeea1fcccb10016430c46615 | 9f1a721907110eae0ea02c0ff9f91e9c28ccdade | /panels/weather/weather.r | 41b06f8b44d984efb1b0e9a6cb8835ada6530a7b | [] | no_license | DavidRickmann/ShipInterface | 3ee88e5065cb62846da2e6937d722e2abb9b6316 | a24ca461acceab0ea8a9fc7391e6d6421eb84310 | refs/heads/master | 2022-11-11T17:22:51.181628 | 2020-06-30T22:27:00 | 2020-06-30T22:27:00 | 273,696,702 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,329 | r | weather.r | library(lcars)
library(ggplot2)
#This wrapper is required until shiny v1.5 is released.
moduleServer <- function(id, module) {
callModule(module, id)
}
#write a standard nav button function
#get the colours from the theme?
#allow assignation of standard colours in the config
weatherpanelUI <- function(id) {
... |
358a2f16dc3f169d3ff19cf1fedb87a18e542603 | 0fd8fdaad36db1be77563597f1efef5044aabb92 | /ui.R | 9a45fd2df9a61245cfd948e103fdc4ec83d806b7 | [] | no_license | nkdhruw/ShinyXploreR | 1ae05eba67e76ef01be0bf25ff457f8467989926 | dd4c6994fbebe7f3e8303ece6683191d57225033 | refs/heads/master | 2020-06-12T01:11:21.846824 | 2019-06-30T17:50:43 | 2019-06-30T17:50:43 | 194,147,576 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,503 | r | ui.R | library(shiny)
library(shinymaterial)
library(DT)
ui <- material_page(
title = "XploreR",
nav_bar_color = "teal lighten-1",
material_side_nav(
fixed = TRUE,
image_source = 'side_bar.jpg',
material_row(
material_column(
width = 10,
shiny::tags$h6('Load example dataset'),
... |
117f9b229d0c3b38ef5d072fc0a3786e33577ede | 4be23c83eeedc01670ee6e79c295ff9b2ae187d3 | /man/split_rows_by.Rd | 6d9a6a9cb1417341578699dc190b6065278f3539 | [
"MIT",
"Apache-2.0"
] | permissive | jcheng5/rtables | 8b0f708d791118189cc76287945acfcacc3c0dd9 | 5b552c69488faa064e2209b4ff3291ba39feaee4 | refs/heads/main | 2023-08-12T22:53:04.445497 | 2021-09-23T00:11:23 | 2021-09-23T00:11:23 | 411,396,687 | 0 | 0 | NOASSERTION | 2021-09-30T19:13:22 | 2021-09-28T18:28:42 | null | UTF-8 | R | false | true | 4,230 | rd | split_rows_by.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/colby_constructors.R
\name{split_rows_by}
\alias{split_rows_by}
\title{Add Rows according to levels of a variable}
\usage{
split_rows_by(
lyt,
var,
labels_var = var,
split_label = var,
split_fun = NULL,
format = NULL,
nested = T... |
802c00a1fd990de92b0141643a0b96aa802c743d | b67ce7f77bca2b817a80c0888897655e426b88cc | /R/bblocks.R | ec8721a19df917041bb45dabfbb0cd217709ead8 | [
"MIT"
] | permissive | saragong/bblocks | babef5d3648ada67549f020cb624045fc8ea12e6 | a604fa99c9f7520f0c02f688964217391565fff6 | refs/heads/master | 2020-07-13T17:37:16.170420 | 2019-08-29T21:11:18 | 2019-08-29T21:11:18 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,866 | r | bblocks.R | # bblocks.R
#' @export
bblocks <- function(data, min_block_size, blockby) {
# build blocks --------------------
data$block_id <- ""
num_tags <- 0
covariates <- unique(names(blockby))
num_obs <- nrow(data)
num_covar <- length(covariates)
num_specif <- length(blockby)
# iterate through covariates
f... |
0206155be22942b5a3e7a04bc3dc40cc77d61723 | 4627cdc23e3f0d22867110ed1215ff85754de6c2 | /ads_romania.R | 2b004b1f8b49446d1324f214550e226ba2bf1cb0 | [] | no_license | ethanarsht/romania-dashboard | 94443667b066b7dda61fbd5f2f436f1b36f9e78c | f27be0283bf0f84237440cfab18b0cc7a3ccac08 | refs/heads/master | 2023-02-18T04:58:16.834513 | 2021-01-15T17:37:47 | 2021-01-15T17:37:47 | 323,613,083 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,167 | r | ads_romania.R | library(Radlibrary)
library(aws.s3)
library(config)
library(readr)
c <- config::get('aws')
Sys.setenv(
"AWS_ACCESS_KEY_ID" = c$id,
"AWS_SECRET_ACCESS_KEY" = c$password,
"AWS_DEFAULT_REGION" = c$region
)
query <- adlib_build_query(
ad_active_status = 'ALL',
ad_reached_countries = 'RO',
ad_type = c("POLITI... |
3e803f9483b1ded6b56f3d9c2375ac4412ff49f1 | 8c0087ce6ae51911ca2954bb316a060978a60cea | /utils/waic.r | 5a9b82c42126597d1e7ac05acbc9bcd3d3a834e2 | [] | no_license | davide-burba/Bayesian_Project | 3e904fe1a34493f96788fe231a13a23e1b431cee | b475d6e114565fd0261883ff1a4212f94ab3b659 | refs/heads/master | 2021-10-09T13:08:59.290225 | 2018-12-28T15:56:44 | 2018-12-28T15:56:44 | 111,917,446 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 978 | r | waic.r | #
# This script evaluates the WAIC (and AIC) value; doesn't work well, use
# something else preferably
#
#EDITABLE VALUES:
n=5000 # number of iterations
names(data.out)[1059]
beta_pos_interval=1:12
sigma_pos=1059
p=length(unique(Patient))
Mfinal=matrix(0,n,p)
Y=RNFL_average
d=dim(Z)[2]
numerosity<-as.integ... |
6f0c29646983572e41c2a19546e4b5cc0adfb177 | f9712c631d00c7a6369c593b823002f3962ef2a3 | /man/BuildRFClassifier.Rd | 5a37a52a24f34389c2d3133f3486911ce7c06499 | [] | no_license | roryk/seurat | 2c3ee6601aaede077d327bf852fd2fde4ca49c8e | e1eae2da82ada2211e84fbc471615e8d3921b539 | refs/heads/master | 2020-12-11T01:45:01.591510 | 2017-01-11T21:32:08 | 2017-01-11T21:32:08 | 54,148,919 | 0 | 0 | null | 2016-03-17T20:22:54 | 2016-03-17T20:22:54 | null | UTF-8 | R | false | true | 703 | rd | BuildRFClassifier.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/seurat.R
\name{BuildRFClassifier}
\alias{BuildRFClassifier}
\title{Build Random Forest Classifier}
\usage{
BuildRFClassifier(object, training.genes = NULL, training.classes = NULL,
verbose = TRUE, ...)
}
\arguments{
\item{object}{Seurat obj... |
95477a2f8753e61c4a4750bf62af1ef866663976 | 62464fa0d0f7c4d07b61216c25da80d42612b49f | /R/PoisMixClusWrapper.R | ac391284bcd18ca3d4dd4f51a3ce6eab8c19ecf7 | [] | no_license | melinaGALL/melinaGALL.github.io | beed0cd99d903319ec1d010c29100cd3710352d9 | 734219e1263e9c1a7bdffc5cf0a17e21c9af5b2e | refs/heads/master | 2020-05-15T09:38:34.780905 | 2013-09-24T16:07:06 | 2013-09-24T16:07:06 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,962 | r | PoisMixClusWrapper.R | PoisMixClusWrapper <- function(y, u, gmin = 1, gmax, conds, lib.size = TRUE, lib.type = "TMM",
gmin.init.type = "small-em", init.runs = 5, split.init = TRUE, alg.type = "EM", cutoff = 10e-6, iter = 1000,
fixed.lambda = NA, equal.proportions = FALSE, verbose = FALSE)
{
all.results <- vector("list", length = gmax ... |
66fa49df68cba9e2c64ad8bca968f38039ee799f | 339532c1047f1c4654692339478ada6c90f0420e | /ui/ui-tab-inputdata.R | 6e64bde81d958ef55d229fb0f646d3dddf8e9c4d | [] | no_license | marcottelab/pepliner | 1647a5541830b4f23f82295c5471b5e54c0ae4d1 | 2e21bf81d56bacdcc9c6ee75bb3cdce3a8213de4 | refs/heads/master | 2021-01-01T18:52:08.640836 | 2018-07-27T20:37:57 | 2018-07-27T20:37:57 | 98,455,138 | 3 | 0 | null | null | null | null | UTF-8 | R | false | false | 9,121 | r | ui-tab-inputdata.R | ## ==================================================================================== ##
# Pepliner: App for visualizing protein elution data
#
# Modified 2018 from the original GNUpl3 by Claire D. McWhitei <claire.mcwhite@utexas.edu>
# Original Copyright (C) 2016 Jessica Minnier, START Shiny Transcriptome Anal... |
8f2496a25ef8a80e99a18900340958bb758717a7 | 152a54991ed04bfc5d647592a38b687eb6d02289 | /man/plot_magic_carpet.Rd | 9b54c36ec8d4008dbca520949b3db9474fc59a09 | [] | no_license | gloverd2/codeBase | dd8a64c711ad98b0902955e585015d03442b5bbf | 897da7d36b7bbe964c7d5e870e8eda918b59eb08 | refs/heads/master | 2023-05-05T20:19:55.512739 | 2021-06-02T08:29:16 | 2021-06-02T08:29:16 | 277,748,509 | 0 | 0 | null | 2020-11-30T11:03:33 | 2020-07-07T07:33:27 | HTML | UTF-8 | R | false | true | 2,381 | rd | plot_magic_carpet.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/plot_magic_carpet.R
\name{plot_magic_carpet}
\alias{plot_magic_carpet}
\title{plot_magic_carpet}
\usage{
plot_magic_carpet(
feature,
feature_name,
incumbent_pred,
proposed_pred,
weight = rep(1, length(feature)),
n_bins = 10,
rat... |
dcaed474d5d1b830f7993b6a24222036076aa930 | 0f423767bc2eed0feee6dddd1709603ea3ebde72 | /table2_nnt.R | 2c490f3e8e60f034f7ea86594bd56b3f7cc9eb14 | [] | no_license | lbhund/Git_LQAS_Design_Uncertainty | 71c81c64da01bc047a461e79c6550e51ffa28e24 | db76abddb94d0a8880c79f475c0b355eb08ca424 | refs/heads/master | 2016-09-06T05:31:37.296826 | 2014-11-04T23:07:43 | 2014-11-04T23:07:43 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,721 | r | table2_nnt.R |
library(xtable)
#! LOAD IN OUTPUT FROM EXAMPLE 2 - NNT !#
load("C:/Users/lhund/Dropbox/PROJECTS/LQAS/SensSpec/output/designs2.Rda")
load("C:/Users/lhund/Dropbox/PROJECTS/LQAS/SensSpec/output/l2.Rda")
load("C:/Users/lhund/Dropbox/PROJECTS/LQAS/SensSpec/output/e2.Rda")
load("C:/Users/lhund/Dropbox/PROJECTS/LQAS/SensSpe... |
04f3a9ce9c414c1073adcfef9280849ddd0208dd | 22d114d86d77cbc042f1f651ee6b8feabb2f5149 | /man/read_source.Rd | 95bd1e57daeec4d863b4c24ea7aa6c4a32c9a078 | [
"MIT"
] | permissive | lidavidm/arrowbench | 544b8030ae203c2274a6c4c8a6c5ea1d76fc246b | ca08ea96678962c462dd8049511e72fbb6f3e9da | refs/heads/main | 2023-04-09T23:26:06.203856 | 2021-04-13T22:51:41 | 2021-04-13T22:51:41 | 358,266,146 | 0 | 0 | NOASSERTION | 2021-04-15T13:18:41 | 2021-04-15T13:18:40 | null | UTF-8 | R | false | true | 328 | rd | read_source.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ensure-source.R
\name{read_source}
\alias{read_source}
\title{Read a known source}
\usage{
read_source(file, ...)
}
\arguments{
\item{file}{file to read}
\item{...}{extra arguments to pass}
}
\value{
the source
}
\description{
Read a known s... |
659098e45f6e78a6fbe3dae75936f13ad55ddcc7 | 0bff7b092713ddf7a6ccdd22dd6c95eb4e9cec32 | /Doing/A hands-on introduction to statistics with R/Introduction to R/Chapter01 - Intro to basics/ex4.R | 6e2db5550bd5083cde8253697368162358052561 | [] | no_license | Selaginella99/coursera | 2aca2dd2fa65d1217b31e0f9b228e865a42064eb | 95a7da5814a8164dd932bc7963fffa1719f905d3 | refs/heads/master | 2021-01-18T02:29:57.199101 | 2015-05-14T14:47:46 | 2015-05-14T14:47:46 | 35,336,115 | 0 | 0 | null | 2015-05-09T16:36:00 | 2015-05-09T16:35:59 | null | UTF-8 | R | false | false | 125 | r | ex4.R | # Assign the value 5 to the variable called my_apples
my_apples = 5
# Print out the value of the variable my_apples
my_apples |
b2083bd13212a82c1a6acaf844ae50b01d34aa81 | 22f8b2957929cb4d2d69d8619d9c17ab62ea952e | /5147-R-assignment.R | b245af9fb99ed2a8d1d8de2e19bd50cb0d97a89e | [] | no_license | hsinhuibiga/R---data-analysis | 30bcea7b0171f4564541033028b060d3223192e6 | 6de4ab91ce01c7df5901b61749bfc76eebee7d7a | refs/heads/master | 2021-05-26T02:31:35.865524 | 2020-04-08T09:44:20 | 2020-04-08T09:44:20 | 254,017,620 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 5,023 | r | 5147-R-assignment.R | # student:HsinHui Lin 28464176 Mon 18:00 tutorial
require(ggplot2)
library(ggmap)
library(datasets)
library(leaflet)
#----Task 1----------------------------------------------------------------#
#read the csv file in to the data
data = read.csv("assignment-02-data-formated.csv")
#print the data
data
#---Task 2 ------... |
8223b72b287b697a977e81b3028109186ca9337d | cb2df211142e20ea1dd3b39eee92cfb03458db39 | /ABLIRC/bin/plot/volcano.r | 35ce8d13d390bc8bc7786b78782187eeeb6dd86d | [
"MIT"
] | permissive | ablifedev/ABLIRC | 4c9f1efa0f92a2a08ddcc142fad8eab670f83d33 | 875278b748a8e22ada2c76c3c76dbf970be4a6a4 | refs/heads/master | 2021-01-13T11:32:05.398582 | 2019-10-18T03:35:36 | 2019-10-18T03:35:36 | 81,188,219 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 12,563 | r | volcano.r | #!/usr/bin/env Rscript
####################################################################################
### Copyright (C) 2015-2019 by ABLIFE
####################################################################################
####################################################################################... |
72c3809b76369f4ae8bb4c26271f12c5cace30c3 | 1f29b675ec689b85e9b5362bb2c068eb549727f2 | /plot1.R | 3c7fd08c3b1795193f918a42f1b5ac11e63b2dff | [] | no_license | rusteyz/ExData_Plotting1 | 1fe7fa676e4c366c8b1194d16c21743ddf00c78e | b6fcb2a9b8a7cb7a424c30256410e248696d1e4c | refs/heads/master | 2021-01-16T22:16:17.209224 | 2014-07-14T00:39:46 | 2014-07-14T00:39:46 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 632 | r | plot1.R | ## plot1.R
setwd("/Users/amrastog/datasciencecoursera/ExploratoryDataAnalysis")
## Read data
data = read.table("household_power_consumption.txt", na.string='?',sep=';',header=TRUE)
data$Date=strptime(paste(data$Date,data$Time), "%d/%m/%Y %H:%M:%S")
data=subset(data, (data$Date>=strptime("2007-02-01","%Y-%... |
c43b6c30ca845c704efd54544bebeb96c04e6d02 | 8dbe523b5cd123fb95bdcb97dac806d482af566f | /man/pass.message.Rd | 0d3be202c044dfcc6f8b10b71288d79359f7c638 | [] | no_license | npetraco/CRFutil | b5ca67b73afdab9dc64712fc709fe08a8fbce849 | 50ef4ca06b7ab11ac1d54472a87e7854beb07cec | refs/heads/master | 2023-01-22T10:53:55.149603 | 2023-01-06T02:03:47 | 2023-01-06T02:03:47 | 135,449,204 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 464 | rd | pass.message.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/sum.product_util.R
\name{pass.message}
\alias{pass.message}
\title{Pass a message over an edge on a factor graph}
\usage{
pass.message(
start.node,
end.node,
factor.graph,
pots.list,
mailboxes.list,
printQ = F
)
}
\arguments{
\ite... |
46a9e1e466aa5fb8f4ed49a5ea7f20cd878d75c1 | 2cf4177233c5ed00d23614db585196c2f3db1077 | /plotting/plot3.R | 33b927cf8ad3093b67e3a05afda2c9d3b1fb718a | [] | no_license | lightkuriboh/ExData_Plotting1 | 3ef046571ccb91b4817a5554a92675d791b50202 | 37b4d3d80486b79c201ff99658d4c61f2ca96c4d | refs/heads/master | 2022-11-10T23:41:53.861541 | 2020-07-13T09:40:12 | 2020-07-13T09:40:12 | 279,043,557 | 0 | 0 | null | 2020-07-12T10:44:05 | 2020-07-12T10:44:04 | null | UTF-8 | R | false | false | 1,130 | r | plot3.R |
library(sqldf)
data_path <- 'raw_data/household_power_consumption.txt'
start_date <- as.Date('2007-02-01')
end_date <- as.Date('2007-02-02')
my_data <- read.csv(data_path, sep = ';')
my_data <- subset(my_data, as.Date(my_data$Date, format = '%d/%m/%Y') >= start_date &
as.Date(my_data$Date, for... |
38c8aed6ba4067e8ff4317779a339c78ecca2b1a | 56b1c1c707c1412c7cbf14e081980a37736fe83d | /NormalPlotting/man/normalplot.Rd | d1a898a9993db6132aebcb9ea579c999b5381a85 | [] | no_license | sbillystewartsw/Plotting | abe36271a181d0d2c24c1e76c17c2cb0494d769e | 71e26e35f57dd201e8e5c63b0bd936c034340f0c | refs/heads/main | 2023-01-04T22:37:29.524138 | 2020-11-06T21:09:11 | 2020-11-06T21:09:11 | 310,699,558 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 488 | rd | normalplot.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/normalplot.R
\name{normalplot}
\alias{normalplot}
\title{Plot a normal distribution}
\usage{
normalplot(mu = 1, sd = 1)
}
\arguments{
\item{mu}{is the mean of the distribution (default = 1)}
\item{sd}{is the standard deviation of the distrib... |
a2c1289208b4dfb75503dee44bf894a4727d1c9a | 41cc7cc09f184dd49ec17669b96708a245599047 | /R/general_functions.R | e7f4cf75eff23a116d384a060185f6cbab4f41bd | [] | no_license | ddeweerd/ComhubbeR | 1a475168a4f2da0ec091590e0cd2782e2d9cf2dc | ad49d100345ce472d91e7bad420bc74b24f3deda | refs/heads/master | 2023-04-03T09:01:24.188664 | 2021-03-26T10:13:50 | 2021-03-26T10:13:50 | 344,760,538 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,292 | r | general_functions.R | #' @import tidyverse
#' @import magrittr
#' @import tigress
#' @import minet
#' @import dplyr
#' @import reshape2
#' @import reticulate
transpose_expression_data <- function(comhub_object){
comhub_object$python_object$expression_data %>%
t(.) %>%
as.data.frame(.)
}
melt_result <- function(net, comhub_objec... |
37ba9fa19865ab50c28b1df6763c3c84f0cce3eb | 17ef71e1eabf7ab93f0fec321f427b576b90a264 | /R/felm.old.R | 94cc96f5dcc82b54024e6153a89e357e592bf765 | [] | no_license | sgaure/lfe | aa326228816f4a36828d8bfb44ec8523208c8643 | 79a10e4b68d79bce8c287d15e238505ddcc1a92e | refs/heads/master | 2023-04-12T03:26:21.204881 | 2019-12-13T12:05:34 | 2019-12-13T12:05:34 | 138,496,051 | 55 | 12 | null | 2021-11-17T14:37:01 | 2018-06-24T16:05:08 | R | UTF-8 | R | false | false | 5,371 | r | felm.old.R | # $Id: felm.old.R 1655 2015-03-18 18:51:06Z sgaure $
felm.old <- function(formula,fl,data) {
mf <- match.call(expand.dots = FALSE)
if(missing(fl)) {
# we should rather parse the formula tree
# find the terms involving G
trm <- terms(formula,special='G')
feidx <- attr(trm,'specials')$G-1
festr <... |
6bc047b8c0bacfb424b631011298956357d32700 | 514130ee03008826e5df1902c8c4ce2b35344bfe | /man/format_table.Rd | 61dc1ffd28e6a3f291bc15f0f27afef567020af5 | [
"MIT"
] | permissive | agstudy/formattable | cfbad16719ee5315fa6ebe219b2a1f10da685052 | 8fb808aaa33518247c85548ab6fe0015c0943da9 | refs/heads/master | 2021-01-13T06:48:47.471565 | 2015-10-30T06:06:39 | 2015-10-30T06:06:39 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 2,889 | rd | format_table.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/formattable.R
\name{format_table}
\alias{format_table}
\title{Format a data frame with formatter functions}
\usage{
format_table(x, formatters = list(), format = c("markdown", "pandoc"),
align = "r", ..., row.names = rownames(x), check.rows... |
2b64a6075b940e343807c435dfaa26b5b6c21dff | 21acdc9cee7b9ff65a2412d133cf0d28e1800a22 | /man/MenuSofi.Rd | 8cabfe212576d14f8e20cb716bb951efab4cab13 | [] | no_license | cran/Sofi | 9f2ae4d99bd3b29e440f5835623c69aa2b99c861 | b8e7e69e906a40548a298bd28e940e1860f26e63 | refs/heads/master | 2021-01-17T14:47:56.905700 | 2016-04-10T00:49:47 | 2016-04-10T00:49:47 | 37,902,002 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 553 | rd | MenuSofi.Rd | \name{SofiWebsite}
\alias{SofiWebsite}
\alias{Estadistica1}
\alias{Estadistica2}
\alias{Estadistica3}
\alias{Estadistica4}
\alias{Estadistica5}
\alias{Estadistica6}
\alias{Estadistica7}
\encoding{UTF-8}
\title{
Funciones de \pkg{Sofi} creadas para ser usadas en el lanzador Paper para más información visita... |
4ca6278c3dea09e9fd995c253e22687857b3f826 | 53a9ea36ab32e5768f0c6e1f4c4f0135c1b65e46 | /de_countTables_comparison.R | 9ae4547f9357af5be00b6ed644552f68f488ffde | [] | no_license | barrantesisrael/Dual_RNAseq_review_analysis | 220bea938ddc154f9ad8fa6243bacfc678f194d1 | 468fa5e4f1fecdd2f5bd8f084d59bba2a45ff798 | refs/heads/main | 2023-03-28T11:23:38.473519 | 2021-03-30T10:06:58 | 2021-03-30T10:06:58 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 20,673 | r | de_countTables_comparison.R | #!/de_countTables_comparison.R
#The script takes a group of count tables and identifies its differential expressed (DE) elements with DESeq2, edgeR, and NOISeq at different values of cut-off, replicates, and adjusted p-values.
#Then, it compares the identified DE elements to a list furnished by the user.
#Then, it plo... |
0c24daab11dc6185b9a16f7131a1313e431d8fc1 | 741794f5f03f3f7f832d85e7c10aa7f32948010c | /data-raw/scripts/crosswalk ISCO 88 ISCO 08.R | bb5f34011446fbe69653acf2befed0125729764f | [
"MIT"
] | permissive | Guidowe/occupationcross | 7e634a2ed08ed83e1b630184606c66b6240c2a52 | aea616fb4a5a89867db87b0acd0adf3244bfa12d | refs/heads/master | 2023-04-19T04:59:35.516557 | 2022-08-26T13:08:51 | 2022-08-26T13:08:51 | 287,028,618 | 8 | 1 | null | null | null | null | UTF-8 | R | false | false | 2,167 | r | crosswalk ISCO 88 ISCO 08.R | ####funciones y librerias#####
library(tidyverse)
library(readxl)
library(stringr)
library(foreign)
#Funcion propia para aleatorizar. Específica para esto, la voy a aplicar al final
sample.isco <- function(df) {
sample(df$`ISCO-88 code`,size = 1)
}
####Carga de Base LFS y Crosswalk#####
crosstable_isco08_isco88... |
cff7576912c2ec0aa93c581e6423c0e842826663 | 23529ed1c1c1181f63cb68ea1a4fd43b3204054d | /Scripts/ChromoPainter/Run_ChromoPainter_Barcode.R | c91f6df9b4fd17604b526720c7c9ae8e303ce1d3 | [] | no_license | aimeertaylor/QuantLocalPfConnIBD | 3dd17631a7e3217a61d29ed92d2e55677aebdf61 | 56af8211c721f8ab8d1ccd09afcadf9ceec53f47 | refs/heads/master | 2022-01-19T23:44:03.968154 | 2019-05-22T16:57:38 | 2019-05-22T16:57:38 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,609 | r | Run_ChromoPainter_Barcode.R | ##################################################################################################
# Script to run ChromoPainter on Barcode data
# Takes 31 secs
##################################################################################################
rm(list = ls())
# load data in IBD file format
BarcodeData ... |
10634d711fc8315657e81f3484328b4fbe6f6218 | 73c9b3c52db44bca119ecd3585ff38db1e9c05b1 | /man/vectors3d.Rd | 2fcbed1014b0a6b1fac04c3f4a1b24638ce8bb23 | [] | no_license | friendly/matlib | a360f4f975ae351ce1a5298c7697b460c4ba8dcd | 13bb6ef45f9832d4bc96e70acc5e879e5f0c5c90 | refs/heads/master | 2023-08-30T13:23:26.679177 | 2023-08-25T17:29:23 | 2023-08-25T17:29:23 | 45,190,492 | 72 | 19 | null | 2023-03-16T19:30:18 | 2015-10-29T15:01:24 | R | UTF-8 | R | false | true | 3,251 | rd | vectors3d.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/vectors3d.R
\name{vectors3d}
\alias{vectors3d}
\title{Draw 3D vectors}
\usage{
vectors3d(
X,
origin = c(0, 0, 0),
headlength = 0.035,
ref.length = NULL,
radius = 1/60,
labels = TRUE,
cex.lab = 1.2,
adj.lab = 0.5,
frac.lab = ... |
a5b659560231902d1b1341c5be9d34e2ef0c0d71 | 5b7812ad30e9d0bf3627b120e05eabb9818590e7 | /Matt multiple csvs.R | b08ebd54c0af6aaa87f018db5c1ea478860d32d5 | [] | no_license | annam21/School | 53db458b16e351cb64e4f53c37a91903dedf5ac1 | b49b5e6ba27c1ae9118b0ba9c51944c0f1c84857 | refs/heads/master | 2021-01-12T11:52:11.599333 | 2019-04-25T01:27:18 | 2019-04-25T01:27:18 | 69,594,738 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 623 | r | Matt multiple csvs.R | # Multiple csv's to Matt
# Anna Moeller
# 10/25/2018
# Load packages
library(tidyverse)
# All the file paths (full path)
filepaths <- list.files(, full.names = T) # fill in here
# Pull in all the csvs into a tibble
dat <- tibble(File = filepaths) %>%
# This is an example of how to extract certain things f... |
208551c5a67b2d52fa25923cfefdf4491fee4cfd | da05dfd4e59fc3a9c25087f40b87142a7902564c | /Simulation1_v2June2017.R | 8ad0bfafaecc4ed0db007ef37794a49081bc7406 | [
"MIT"
] | permissive | ehsanx/HierarchicalTMLE | 165043828434ee8c2fc1a6803a4d5318ecc24e5f | 1eae53cfa9d5a9738c748f1c3c67476827862dfd | refs/heads/master | 2022-02-28T19:05:26.131712 | 2019-10-17T13:27:17 | 2019-10-17T13:27:17 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 7,199 | r | Simulation1_v2June2017.R | #-----------------------------#-----------------------------#-----------------------------#-----------------------------
# R code to generate simulated data and implement the hierarchical TMLEs
# described in Balzer et al: "A New Approach to Hierarchical Data Analysis:
# Targeted Maximum Likelihood Estimation of Clu... |
d41a20c44804bf62736aa8641f4dd7f252bf3d1e | 6bca977d67101a6274457ca850517ee41cf06c45 | /plot_functions/plot.meth.distribution.R | 99172e08b9a45e7efc35ac74c9f3a2762a07d9b4 | [] | no_license | AAlhendi1707/preinvasive | bedcf1f1eca93ab9ae4b44bf32e4d0f9947a1fad | e683fa79ad76d0784437eba4b267fb165b7c9ae4 | refs/heads/master | 2022-01-06T18:25:52.919615 | 2019-01-18T09:39:42 | 2019-01-18T09:39:42 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,082 | r | plot.meth.distribution.R | ########################################################################################################
# Methylation Distributions
########################################################################################################
plot.meth.distribution <- function(filename){
# Density plot of MVPs in cancer v... |
45df24834d167a9644d37471a40716e21bf5da66 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/sensitivitymw/examples/multrnks.Rd.R | 4cbcc6b299fc8b45f2598a4baa7ca5970a86c5d6 | [] | 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 | 177 | r | multrnks.Rd.R | library(sensitivitymw)
### Name: multrnks
### Title: Approximate scores for ranks.
### Aliases: multrnks
### ** Examples
multrnks(1:10)
multrnks(1:10,m1=12,m2=20,m=20)
|
a68e7b8c4b42471073867d32191b0660bdf8b760 | 2aeb79f35732ccddfa1642f17122194b1caeac08 | /LPT_model_output_analysis/bathyMaps.R | 958ca099b5986ce0142e9cc799cb77804ca2001e | [] | no_license | jwongala/Lagrangian-particle-tracking-model | b91bbec04919255101f76b8a160220f00ea14cf6 | 148ed040dc87a027c3ea8d47eb8b9e28518eebcf | refs/heads/master | 2023-06-20T06:10:04.804586 | 2021-07-20T19:00:35 | 2021-07-20T19:00:35 | 298,403,858 | 1 | 1 | null | 2020-10-20T18:04:58 | 2020-09-24T21:57:07 | R | UTF-8 | R | false | false | 3,255 | r | bathyMaps.R | ### The purpose of this script is to create maps of the LPT model output using bathymetry maps.
### Jennifer Wong-Ala
### 20201106
####################################################################
### clear the workspace
rm(list=ls())
####################################################################
### load ... |
dfc9c6b435e418288d4c2d054b70b4e62d1210dc | 7e239d4369ccf25368e06aff0e1b51272a8a1457 | /.ipynb_checkpoints/my_first_script-checkpoint.R | 0040a4ce21dfd18fd762a0da1fecf891512385e0 | [] | no_license | oscarm524/aws_ML_demos | 16e029a884c2c9cd2d11ecdc2c10fb33bdf0aeba | 82986fa30a5d25275b30f2b289f35d27ece46f77 | refs/heads/main | 2023-02-12T04:25:33.180170 | 2021-01-11T20:02:36 | 2021-01-11T20:02:36 | 306,625,035 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 37 | r | my_first_script-checkpoint.R | x <- rnorm(100)
y <- 3*x + rnorm(100) |
8e79eceb8c118c60536c125c5ed8bf3122f6ab93 | ac79d0e10669802dc128caf6f1c935a543b71a72 | /scripts/cleanup-2012.r | cddb186cd0c97d28e3fad6612a69a83f928b84dc | [] | no_license | infotroph/efrhizo | 2ab0f931a8fe9cbcbede794aca539fc9120526e9 | 8783e81d50aa2d7a09fff7cd3456c7728161653b | refs/heads/master | 2020-12-26T04:15:27.176785 | 2017-06-27T03:21:58 | 2017-06-27T03:21:58 | 46,886,036 | 1 | 1 | null | 2016-08-05T06:56:26 | 2015-11-25T20:52:08 | Max | UTF-8 | R | false | false | 2,969 | r | cleanup-2012.r | require(rhizoFuncs)
raw.2012 = read.delim("../data/frametots2012.txt")
raw.2012 = make.datetimes(raw.2012)
# Delete all Loc 1 records (none show roots)
# and any misplaced frames (e.g. 9, 13)
raw.2012 = droplevels(raw.2012[raw.2012$Location %in% seq(5,120,5),])
# Censor all images that were too low-quality to trace
... |
6947e15d295e88f194f558b96749e72b0676e022 | 70098b915b6cf31d86de5f5ad4687ab4de341097 | /tests/testthat/test-check_format.R | f7e375673ff58ff8d29a9a1fcf19e2160cb0846b | [
"MIT"
] | permissive | mattoslmp/chemspiderapi | b6364443309db2f5950ed7d88fc1d050f4db3dac | 0b371791243ff44c2ff8536c1e59f08ed615ac8e | refs/heads/master | 2023-03-15T19:19:53.930291 | 2021-01-06T10:05:09 | 2021-01-06T10:05:09 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,026 | r | test-check_format.R | library(chemspiderapi)
context("check_format")
test_that("check_format() fails if no input is provided.", {
expect_error(
.check_format()
)
})
test_that("check_format() fails if NULL is provided as input.", {
expect_error(
.check_format(input = NULL)
)
})
test_that("check_format() fails if multipl... |
786580cda12383e766711057e390ea453d0cbc94 | 389410f81d53d14646a3c95ce34f48c9163ce053 | /9-developing-data-products/shiny/ui.R | d2e66b34f143e361d297de93aa0609b6e9d4a665 | [] | no_license | fattyfook2015/datasciencecoursera-1 | a40d3abae9031552a1beeeec7f953a361699e8ba | 11962a2796c862302820fc46dfa690d41373ea06 | refs/heads/master | 2021-05-30T23:40:35.770180 | 2015-08-03T15:01:12 | 2015-08-03T15:01:12 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,055 | r | ui.R | library(shiny)
shinyUI(pageWithSidebar(
headerPanel("Tuning Parameters for the Nadaraya-Watson Kernel Regression Estimator"),
sidebarPanel(
sliderInput("bw1", "Bandwidth of Smoother 1:",
min = 2, max = 10, value = 2, step = 0.5,
animate = animationOptio... |
1b9b6a4a20f7e1a5a35f5b5d501f4fad0aa0c946 | 97edcb6746069b6c6c7facbe82ed9bb4482d6e22 | /eSVD/man/dot-percent_shrinkage.Rd | 309570be090f8ae38baa6a18f2d0155bb22aed51 | [
"MIT"
] | permissive | linnykos/esvd | 7e59c5fc50f6e0bd23fcb85f1fa6aa66ea782a60 | 0b9f4d38ed20d74f1288c97f96322347ba68d08d | refs/heads/master | 2023-02-24T23:33:32.483635 | 2021-01-31T21:06:41 | 2021-01-31T21:06:41 | 129,167,224 | 2 | 2 | null | null | null | null | UTF-8 | R | false | true | 691 | rd | dot-percent_shrinkage.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/slingshot_curves.R
\name{.percent_shrinkage}
\alias{.percent_shrinkage}
\title{Determine the percentage shrinkage (a non-decreasing function)}
\usage{
.percent_shrinkage(pcurve, common_idx)
}
\arguments{
\item{pcurve}{output of \code{princurv... |
e1215e50b4106be896d4035e4b793611060de20c | 01aeb568b73063290dcb7ebad6e238d6711fee35 | /man/sce_full_Trapnell.Rd | bad3d15071c2fd40d139aaa9524bb69b04b53409 | [] | no_license | chanwkimlab/DuoClustering2018 | 06c86ac4b0538549335f5973089086f7e42719f0 | 6b68abdac141eb043e02850547212715ddfbcf4d | refs/heads/master | 2023-02-28T02:00:15.409134 | 2021-01-30T08:49:38 | 2021-01-30T08:49:38 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 6,003 | rd | sce_full_Trapnell.Rd | \name{sce_full_Trapnell}
\docType{data}
\alias{sce_full_Trapnell}
\alias{sce_filteredExpr10_Trapnell}
\alias{sce_filteredHVG10_Trapnell}
\alias{sce_filteredM3Drop10_Trapnell}
\alias{sce_full_TrapnellTCC}
\alias{sce_filteredExpr10_TrapnellTCC}
\alias{sce_filteredHVG10_TrapnellTCC}
\alias{sce_filteredM3Drop10_TrapnellTCC... |
f6271ca183340f27b53d3eddd0b9c1092979ba5c | 2a7e77565c33e6b5d92ce6702b4a5fd96f80d7d0 | /fuzzedpackages/RBesT/man/pos1S.Rd | add845d5a55143bc18ed44d701dbaf4b89180b33 | [] | no_license | akhikolla/testpackages | 62ccaeed866e2194652b65e7360987b3b20df7e7 | 01259c3543febc89955ea5b79f3a08d3afe57e95 | refs/heads/master | 2023-02-18T03:50:28.288006 | 2021-01-18T13:23:32 | 2021-01-18T13:23:32 | 329,981,898 | 7 | 1 | null | null | null | null | UTF-8 | R | false | true | 4,301 | rd | pos1S.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/pos1S.R
\name{pos1S}
\alias{pos1S}
\alias{pos1S.betaMix}
\alias{pos1S.normMix}
\alias{pos1S.gammaMix}
\title{Probability of Success for a 1 Sample Design}
\usage{
pos1S(prior, n, decision, ...)
\method{pos1S}{betaMix}(prior, n, decision, ...... |
72d23ad4007dae22894b6bf1b09dfd9c5b125b2c | fb0fdffa0ea694ece6313359582310c5f25eeb12 | /R/gevpdf.R | b6c3f097781373454a4ee0332cdf42b11470bf33 | [
"MIT"
] | permissive | rozsasarpi/Interactive-snow-map-R | f30fbba49698375dafbdbe08045af898ec3ff6f3 | b62907a29ea2150f196a53d6a2bf6c06486e17d4 | refs/heads/master | 2021-01-10T04:22:50.994881 | 2016-08-18T14:16:36 | 2016-08-18T14:16:36 | 47,183,604 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,326 | r | gevpdf.R | gevpdf = function(x, shape, scale, location) {
# parameters can be only scalars
# x can be vector
# rm(list=ls(all=TRUE))
# x = c(10, 20, -9, 5)
# shape = 0
# scale = -1
# location = 1
nx = length(x)
nshape = length(shape)
nscale = length(scale)
nlocation = length(location)
if... |
1e5e2aa95bec6ac0344e3337cec4d901b337b282 | d33a5191d950d6044e2611890a69d99de6b9418c | /SharedForest/R/Hypers.R | a7d1bdebbb75e2a3b1049f76f8b3d063fb2c6520 | [
"MIT"
] | permissive | theodds/SharedForestPaper | 84a7ab8bc669c76314aaac897bea22fc21d5a211 | 00d91f4251c73eef4dae10304bbc3196831357f7 | refs/heads/master | 2022-03-01T18:51:16.132755 | 2022-02-19T17:59:19 | 2022-02-19T17:59:19 | 188,320,078 | 3 | 0 | null | 2019-05-23T23:34:36 | 2019-05-23T23:26:32 | C++ | UTF-8 | R | false | false | 5,332 | r | Hypers.R | #' Create hyperparameter object for SoftBart
#'
#' Creates a list which holds all the hyperparameters for use with the softbart
#' command.
#'
#' @param X NxP matrix of training data covariates.
#' @param Y Nx1 vector of training data response.
#' @param group For each column of X, gives the associated group
#' @param ... |
1a2d456c1c574653b515fe72d6f1d036b2a1466b | 6eb0c9e95e7dc19d762fcf37da0b92e27eb212a5 | /DTU_ML_kursus/02450Toolbox_R/Scripts/ex5_2_1.R | 4eed08e51143c61beb7baf92d919d5e8d84161e1 | [] | no_license | AnnaLHansen/projects | 81b125e8789c2555c8a2b05c469193094e25610f | fb6fe1d268c81146fb819cf42722fe93f9af31f6 | refs/heads/master | 2021-07-19T15:29:46.507559 | 2020-09-04T12:23:31 | 2020-09-04T12:23:31 | 211,500,384 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 288 | r | ex5_2_1.R | # exercise 5.2.1
# Number of data objects
N = 100;
# Attribute values
X = c(0:(N-1));
# Noise
epsilon = rnorm(mean=0, sd=0.1, n=N);
# Model parameters
w0 = -.5;
w1 = 0.01;
# Outputs
y = w0+w1*X+epsilon;
# Make a scatter plot
plot(X, y, main="Linear regression", xlab="X", ylab="y")
|
b753a4ac0805356378bbe71dd5172461f34838ae | fd00a89804c49a9026229a778518e19b59c24f21 | /server/rScripts/argsTrain.R | 76ecfffc7648c2b6d08626c594af9513b70a3de4 | [] | no_license | yz8169/tmbq_scala_js | 44453a63b184ef59ad20cba3edd0f32b4b93a387 | f68bcac8becfe74bef12f2b120c0e6fff7cfed0c | refs/heads/master | 2020-12-08T10:39:32.869984 | 2020-01-15T06:39:53 | 2020-01-15T06:39:53 | 232,960,699 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,242 | r | argsTrain.R | # Title : TODO
# Objective : TODO
# Created by: yz
# Created on: 2018/9/26
library(pracma)
library(baseline)
name <- "TwMCA"
sampleConfig <- read.table(quote = "", "sample_config.txt", header = T, com = '', sep = "\t", check.names = F)
bat=2
colnames(sampleConfig)[2] <- "fileName"
config = subset(sampleConfig, batc... |
2af9f476c0eec7840b178374979ec519c37db6eb | 689635789d25e30767a562933f39fcba1cebecf1 | /Alpha Modelling/QuantStrat/Packages/IKReporting/man/runSharpe.Rd | 00a3fc1db398afabb2729373a05dd5ac70d5d6ea | [] | no_license | Bakeforfun/Quant | 3bd41e6080d6e2eb5e70654432c4f2d9ebb5596c | f2874c66bfe18d7ec2e6f2701796fb59ff1a0ac8 | refs/heads/master | 2021-01-10T18:23:23.304878 | 2015-08-05T12:26:30 | 2015-08-05T12:26:30 | 40,109,179 | 5 | 0 | null | 2015-08-05T12:12:09 | 2015-08-03T06:43:12 | R | UTF-8 | R | false | false | 644 | rd | runSharpe.Rd | % Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/runSharpe.R
\name{runSharpe}
\alias{runSharpe}
\title{Running Sharpe Ratio}
\usage{
runSharpe(R, n = 252, scale = NA, volFactor = 1)
}
\arguments{
\item{R}{a return series}
\item{n}{a lookback period}
\item{scale}{number of periods ... |
c196bdebce36addcf75fd13ac1bcd6b723f683de | 091211fc733515cbcd42ad63998fcf6184bf3e77 | /man/regress.Rd | 5297626901718b5743742c386f814a52ac0609c8 | [] | no_license | AndrewYRoyal/ebase | 3560e2e4e717120357b066f27fbfa094d6bb34ec | 7decc805dc80d26a77505c8c4fb87816c63a7a24 | refs/heads/master | 2022-12-22T17:23:30.440452 | 2020-09-30T12:31:43 | 2020-09-30T12:31:43 | 168,870,979 | 3 | 0 | null | null | null | null | UTF-8 | R | false | true | 210 | rd | regress.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/regression.R
\name{regress}
\alias{regress}
\title{Regression Method}
\usage{
regress(dat, ...)
}
\description{
Regression Method
}
|
1ab4631b0c04a4091e7390f3e6362b722652b6f8 | 1c44bffe9a0c2f9713f369f46878e04a48f48519 | /man/attractorScanning.Rd | 2f04623590cda1d8d7b0c1c6540928a1d3002b44 | [] | no_license | onlyevil/cafr | 7ee12d698c3bef46acbbd98530283444ed2efef7 | 41a89fbee93e85a0abc2623d69ccdaa342d26fb5 | refs/heads/master | 2021-01-25T01:08:14.234616 | 2015-11-04T19:58:48 | 2015-11-04T19:58:48 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,694 | rd | attractorScanning.Rd | \name{attractorScanning}
\alias{attractorScanning}
\title{Find all attractors in the dataset}
\description{Exhaustively search for all attractors in the dataset.}
\usage{
attractorScanning(data, a=5, maxIter=100, epsilon=1E-14, bin=6, so=3, rankBased=FALSE, negateMI=TRUE)
}
\arguments{
\item{data}{An expression ma... |
8973ba6b788512987cd30c8aa06537e77cdb65d5 | e169cdc073b991918fe4f2fcab99ffa3a7e9b0c8 | /MarcoPolo/app.R | 93e98369e50958cc6f852b4b7d4759afa7ebacfb | [] | no_license | hollipista/DataScienceCapstone | 79a993d44791138f90e7c3718e6701f478630611 | 52d755f16cf662fc34016c0b80a35e6001a2dea2 | refs/heads/main | 2023-04-08T06:56:31.020292 | 2021-04-22T20:18:30 | 2021-04-22T20:18:30 | 349,172,186 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 6,425 | r | app.R | library(shiny)
load(file='n_gram_prob.RData')
library(tibble)
library(dplyr)
library(tidytext)
library(tidyr)
library(shinythemes)
predict_uni <- function() {
#print('uni')
max_prob = max(UG$prob)
candidates=UG[UG$prob==max_prob,]
return(sample(candidates$word1,1))
}
predict_bi <- function(w1) {
#... |
f30503b4388433e30e2eba14e46008313abec9da | 0426f02d23e02ec70640b88e4859abb6cc1ad019 | /wycena_BS.R | d9ca67695f271db2e33883a079a52188f529271f | [] | no_license | frdanconia/time_series_tests | 8083afab5672e57a7f4158a6f664a9d931be187f | 362a5ea1efd8835e2a55a124c42e46669af073fa | refs/heads/master | 2022-04-02T12:44:50.672796 | 2020-01-27T20:36:25 | 2020-01-27T20:36:25 | 236,589,056 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,064 | r | wycena_BS.R | # Wycena europejskiej opcji kupna wzorem Blacka-Scholesa
wycena_BS <- function(K,S0=1,sigma=1,r=0,T=1){
y1 <- (log(S0/K)+T*(r+sigma^2/2))/(sigma*sqrt(T))
y2 <- (log(S0/K)+T*(r-sigma^2/2))/(sigma*sqrt(T))
C <- S0*pnorm(y1) - K*exp(-r*T)*pnorm(y2)
return(C)
}
# Cena sprawiedliwa w zaleznoaci od r,sigma,K.
rate ... |
f9b6d435ad360d2249904b02fffc5bce216c1b3e | 2a7e77565c33e6b5d92ce6702b4a5fd96f80d7d0 | /fuzzedpackages/oppr/R/print.R | 2c7cf1c4cd26a4050ddd048428081f4fa471bf17 | [] | no_license | akhikolla/testpackages | 62ccaeed866e2194652b65e7360987b3b20df7e7 | 01259c3543febc89955ea5b79f3a08d3afe57e95 | refs/heads/master | 2023-02-18T03:50:28.288006 | 2021-01-18T13:23:32 | 2021-01-18T13:23:32 | 329,981,898 | 7 | 1 | null | null | null | null | UTF-8 | R | false | false | 1,281 | r | print.R | #' @include internal.R
NULL
#' Print
#'
#' Display information about an object.
#'
#' @param x Any object.
#'
#' @param ... not used.
#'
#' @return None.
#'
#' @seealso \code{\link[base]{print}}.
#'
#' @name print
#'
#' @aliases print,Id-method print,tbl_df-method
#'
#' @examples
#' a <- 1:4
#' print(a)
NULL
#' @rdna... |
bfb65cb376c091a0a5be580401f358215ba01aa8 | a932a56ebe8a8b224ce254cffd54317ea004060c | /code.R | 41541468603d37d789f69a19ae30c7dc7737b151 | [] | no_license | nm1874/week12_workshop | 5f43da1aed45ea254fc3419d3e3c693479303b00 | ca19e59dee080267155cf2e6a343939df4d884ea | refs/heads/main | 2023-01-29T12:48:55.030214 | 2020-12-08T15:57:57 | 2020-12-08T15:57:57 | 319,688,434 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 955 | r | code.R | #1.
F<-function(v) v[1]*v[3]-v[2]^2
v0 <- c(4,2,1)
g<-function(v) c(v[1]^2, v[1]*v[2]^2, v[2]^4)
v1<-c(2, 1)
#a)
Dg <- jacobian(g, v1); Dg
#since the basis is the image of Dg
#the basis is c(4,1,0) c(0,4,4)
#b) #since the basis of the image is in the kernel of dF
DF <- grad(F, v0); DF
DF%*%Dg[,1]
DF%*%Dg[,2]
... |
f7060d1aa657b011df92ef416a8f363d31a326b2 | 0e2f1ad8be855562a48a7f4961a91dd4a4b1a9e7 | /amplicon_metacoder_mal_DNA.R | 1830d521171b7d64128a7d34751351dd92371e80 | [] | no_license | ngeraldi/Global_ocean_genome_analysis | 7ba1b2c2250dc476e4a662c8b7ff6bcae9b07f88 | 08a64c282c9f638c184a9807629d47f2c5c9ef3d | refs/heads/master | 2020-04-30T14:39:27.083026 | 2020-01-16T13:28:53 | 2020-01-16T13:28:53 | 176,897,506 | 2 | 0 | null | null | null | null | UTF-8 | R | false | false | 8,674 | r | amplicon_metacoder_mal_DNA.R | library(dplyr)
library(tidyr)
library(metacoder) #
################################################################################
# get otu table and standardise
#source("/Users/geraldn/Dropbox/Documents/KAUST/eDNA/DMAP/R/Scripts/amplicon_stats_tara_source.R")
source("/Users/geraldn/Dropbox/Documents/KAUST/eDNA/DM... |
9a37111354950bf67cb3b2bedee1e2ecf8e1b665 | 79a79ac668a49b0902488839a3d9d8d32a988847 | /man/average_clust.Rd | 5166ec8327a466cb9b2abcdd9107d03db84d83d6 | [] | no_license | cran/convergEU | 86b7ad6d02dd825e88f88b950a1c4acb844c6b1a | 5767b1d9e19178488b8095a44e0da8bde885780c | refs/heads/master | 2023-03-04T02:55:52.942150 | 2023-02-18T07:50:02 | 2023-02-18T07:50:02 | 247,519,134 | 0 | 1 | null | null | null | null | UTF-8 | R | false | true | 2,029 | rd | average_clust.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/average_clust.R
\name{average_clust}
\alias{average_clust}
\title{Unweighted average of countries}
\usage{
average_clust(myTB, timeName = "time", cluster = "EU27")
}
\arguments{
\item{myTB}{time by member states dataset.}
\item{timeName}{nam... |
bc0249dd3442388a7d1bf78cf2b8a7ae53b6869e | 42affdb459e72da8ee1249514b8690a139a718fc | /cMeansMembershipSummary.R | ccf2161d2afb128cf0f53e6fd3c1422a5e62b0f3 | [] | no_license | lucarri/Fuzzy-c-means-SNAC-K | 8f04cec93a0fbf90a9d504afe9fefa1a2cdb0c98 | e0451ff3e6111a7b38388f4187817eb67a9befef | refs/heads/main | 2023-05-05T20:46:07.481473 | 2021-06-03T16:38:04 | 2021-06-03T16:38:04 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,042 | r | cMeansMembershipSummary.R | cMeansMembershipSummary <- function(mca,num.clusters,repetitions,m)
{
library(snow)
library(foreach)
library(doSNOW)
library(e1071)
#Empty data frame to store clusterization per repetition
#membership.current <- data.frame(array(0,dim=c(nrow(mca$ind$coord),num.clusters,repetitions))
membershi... |
6ac097e4170ddc8230b867c4a068a0375b7d2c60 | 3e39e913510eb38fd1fd29fdad918d9c583f993c | /double_robust2/DR_500_2ver.R | 5bdf599f337c3b4be052cdcd57f63ef51457b420 | [] | no_license | Yu-Zhou/Double | 80e3a98f755571d8da007862a091e56f460e328a | 0eb14fb6ee786045db31a126528449b76c7af258 | refs/heads/master | 2021-01-19T06:36:16.158284 | 2015-03-02T19:38:32 | 2015-03-02T19:38:32 | 31,485,050 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,704 | r | DR_500_2ver.R | ## double robust estimator two covariates
#
source("basic2.R")
sigma = 0.05 #global parameter
n = 500 #global parameter
sum_names <- c("intercept","X1","X2","hatQ")
p_level <- 1
eta_range <- 1:3
sq<-rep(0,3)
pop.size<-800
it.num<-7
nvars<-length(sq)
Domains<-cbind(rep(-1,nvars),rep(1,nvars))
sim_function <- function... |
0f9136e40581b7d14c9da43f187e07f49009247e | 9b9e21fea61870f3458bec92ee25a5a9f10345c3 | /man/makeGstatCmd.Rd | eb400b7b0bec83466a718aff66736ea642693be9 | [] | no_license | brendo1001/GSIF | dd46bc744309a970ef5622f1af423e179bf1d3d7 | 12ed85244a1ca46212033f0ecc16f8cd0303ea64 | refs/heads/master | 2021-01-14T09:18:33.661687 | 2014-01-15T00:00:00 | 2014-01-15T00:00:00 | 18,876,903 | 2 | 2 | null | null | null | null | ISO-8859-2 | R | false | false | 3,891 | rd | makeGstatCmd.Rd | \name{makeGstatCmd}
\alias{makeGstatCmd}
\encoding{latin1}
\title{Make a gstat command script}
\description{Generates a command script based on the regression model and variogram. This can then be used to run predictions/simulations by using the pre-compiled binary \code{gstat.exe}.}
\usage{
makeGstatCmd(formString, vg... |
62176bb3e3537b67123abe5870fab57fd6ba979f | ef1188cbd0cfdbe4a1620b9292c72b2437fdeb4c | /cachematrix.R | 11369c791da66dc3600ccf3499bcac28eda60f36 | [] | no_license | mbbayside/ProgrammingAssignment2 | 9236dd26049260a48ae82156b7ad01e1a2e10367 | 9161ca6bb551fac62a52d2cb507db37cb5bf68b3 | refs/heads/master | 2021-01-18T17:45:55.016200 | 2015-03-14T18:28:59 | 2015-03-14T18:28:59 | 32,122,315 | 0 | 0 | null | 2015-03-13T02:44:35 | 2015-03-13T02:44:35 | null | UTF-8 | R | false | false | 3,703 | r | cachematrix.R | ## This set of functions supports calculating and caching the inverse of a
## matrix. This is useful for pre-calculating the matrix inverse (a potentially
## costly computation) when this inverse is to be used repetitively.
##
## -- Function makeCacheMatrix:
## Create an object that manages a specified matrix... |
a2db300af16f170db1d7f928c5072f30bfab609c | 1aed97642180d78ed826ac55ecdf2ed5a0b7e300 | /Nurse_Project/Hormone.R | fcd5a1781b949a0fe2cd0712a492ea1daee9fd60 | [] | no_license | xutaosjtu/Nurse-project | e5ccf903237aa41ed6cf6bc72d244f31790e1cfc | 3c51c7c1e3a98711a8b5ef09b5c4796e2b7e4d80 | refs/heads/master | 2021-01-25T05:34:51.672983 | 2014-07-14T08:00:25 | 2014-07-14T08:00:25 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 10,522 | r | Hormone.R | hormone = read.csv("data/Hormone data_sul.csv" )
colnames(hormone)[10:12] = c("Melatonin", "Cortisol", "Estradiol")
hormone = hormone[order(hormone$SW_Nr, hormone$Probennahme_Dat, hormone$Proben_Nr),]
#hormone$Probennahme_Uhr = hormone$Probennahme_Uhr*24
hormone$Probennahme_Dat=as.character(hormone$Probennahme_Dat)
h... |
8c8998b1bcd74be2edbdffc4f654d38dd7a066d7 | 0889a42eb6c854a6a69606759431b994d03e3667 | /shiny_asteroids/ui.r | a75982d8309aa2a7c37b602a646441466dd52877 | [] | no_license | nachocab/stats_seminar_talk_2014 | c7b130721fac07f7164588de21462d0485f25330 | d35d5ab026cdb26934161893cb9f71b975941d6a | refs/heads/master | 2021-01-19T03:11:27.391371 | 2014-04-07T14:47:25 | 2014-04-07T14:47:25 | 18,366,315 | 1 | 1 | null | null | null | null | UTF-8 | R | false | false | 302 | r | ui.r | shinyUI(pageWithSidebar(
headerPanel("Asteroid flybys"),
sidebarPanel(
sliderInput("distance", "Distance (LD)", min = 0, max = 5, step = .1, value = c(0,5)),
sliderInput("date", "Year", min = 2000, max = 2100, value = c(2000,2100))
),
mainPanel(
plotOutput("asteroids_plot")
)
))
|
562778dd95cc55610eddd91d8dcc6fd8df33576b | 68eb16486b156005533d1de33ab26e54f75d5d66 | /Course 7- Linear Regression/Week2/RegPred.R | 2e2c4ac3e7ea4986730146a1a7b2607b10e8f876 | [] | no_license | shovitraj/DataScienceSpecialization-JHU | b69559b08d2b85ca5e2d2a355a76bf3b588f736b | 538b4d90cdced90d271fc2e9b2e8b0efc376705c | refs/heads/main | 2023-08-22T16:38:03.361482 | 2021-09-20T00:01:49 | 2021-09-20T00:01:49 | 408,240,482 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 641 | r | RegPred.R | library(UsingR)
data(diamond)
library(ggplot2)
diamond
table(diamond$carat)
g=ggplot(diamond, aes(x=carat, y=price))
g= g + xlab("Mass(carats)")
g= g + ylab("Price(SIN $)")
g = g + geom_point(size = 7, colour = "black", alpha=0.5)
g = g + geom_point(size = 5, colour = "blue", alpha=0.2)
g = g + geom_smooth(method = "lm... |
06d000e0f7f58eb77d3e3b77b8fc783d6ab23135 | 360df3c6d013b7a9423b65d1fac0172bbbcf73ca | /FDA_Pesticide_Glossary/fenamidone.R | 5df0c2ae40d60472752098269ef27788fd36ded6 | [
"MIT"
] | permissive | andrewdefries/andrewdefries.github.io | 026aad7bd35d29d60d9746039dd7a516ad6c215f | d84f2c21f06c40b7ec49512a4fb13b4246f92209 | refs/heads/master | 2016-09-06T01:44:48.290950 | 2015-05-01T17:19:42 | 2015-05-01T17:19:42 | 17,783,203 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 216 | r | fenamidone.R | library("knitr")
library("rgl")
#knit("fenamidone.Rmd")
#markdownToHTML('fenamidone.md', 'fenamidone.html', options=c("use_xhml"))
#system("pandoc -s fenamidone.html -o fenamidone.pdf")
knit2html('fenamidone.Rmd')
|
601aaf6267a2a1c283f5b5eaf3b4939f41602d44 | 73df6be0fec5bac3ec5ca552438568a663e769e3 | /R/FunctionsForGenes.R | 65a3ae14de1284c3209c6da20c02efd766864f43 | [] | no_license | kasaha1/kasaBasicFunctions | 1fecefd905520ce5e0ad7de07d8f8c66fda9e6d3 | d572d2953842cbc82d98ad2730a18dd90c7a1dd7 | refs/heads/master | 2022-07-13T09:37:40.737163 | 2022-06-27T05:18:33 | 2022-06-27T05:18:33 | 90,565,815 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,947 | r | FunctionsForGenes.R | #' The checking the data clean
#'
#' @param x input dataframe
#' @return results from checking
#' @export
kasa.dataCleaning <- function(x){
res <- list()
res$classes <- sapply(x,function(y) class(y))
res$na<- sapply(x,function(y) sum(is.na(y)))
res$unique <- sapply(x, function(y) length(unique(y)))
res$dulpli... |
1c493127e86b9c3c9628885c6b6fb9810a22dfad | 958b135d6d988a1d3977a45a4ec71a4ea6c4d607 | /R/code/other_code_files/find_kdp_optimal_params.R | efa2a8ba1bc9a809b32163e69c8791939b4c45d5 | [] | no_license | VaibhavBehl/Kaggle_how_much_did_it_rain_ii | 8967bd2f112562abf2a25d9e0d6a13b527defe05 | 2a2cfe542f1c608c955716bf524a676b062c9e08 | refs/heads/master | 2021-01-10T15:25:03.555803 | 2015-12-31T22:12:02 | 2015-12-31T22:12:02 | 48,843,149 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 995 | r | find_kdp_optimal_params.R | #to find optimal params for when using both Z and Zdr
source("utility_functions.R")
#original values
trgData <- trData[, .(
target = mean(Expected)
), Id]
tempfun <- function() {
c<-0
aiseq <- seq(2,9)*10
aiseq <- c(aiseq,1,100)
#aiseq <- c(40.6)
biseq <- seq(0,1)/10
biseq <- c(biseq, 100)
#biseq <- c(0.945)... |
a62b62bc136fe37b4e482e5bc3aadce689b8fa11 | 8d26d0d664bd1b19970f7793bfec7d57f1728338 | /run_monocle.R | ea3e7223b07d3c2e320d34aa7717a50680f838b8 | [] | no_license | fanli-gcb/Core.RNAseq | 497ebc7eca807050e57cf0dd62cbdff46e769fe0 | bbce62cb3b1b0ffffbc7df93324318d766c686aa | refs/heads/master | 2021-01-10T12:10:18.781827 | 2018-10-09T22:16:24 | 2018-10-09T22:16:24 | 53,674,054 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 3,542 | r | run_monocle.R | #!/usr/bin/Rscript
# load required packages
library(monocle)
library(reshape2)
library(ggplot2)
args <- commandArgs(T)
if (length(args) < 4) {
cat("USAGE: ./run_monocle.R fpkm_table_file sample_sheet_file gene_attr_file out_pdf\n")
q()
}
fpkm_table_file <- args[1]
sample_sheet_file <- args[2]
gene_attr_file <- arg... |
c2b4e5cad31e967441b8ee0a6c55a0bc57d70b2f | 71f8f811fbfd86a99f3025994e7d969c3342b484 | /Plot4.R | def8f7a512271722f0f2b6b8124e3464e29438b1 | [] | no_license | danishtamboli123/EPA-National-Emissions | 97f3c7e4aa726b2e67c3f595c17ecfe726cf1ee3 | 55974ceccd40bb218443ac2783fc5df7974a0ae9 | refs/heads/master | 2022-11-26T01:40:00.305034 | 2020-07-15T22:25:07 | 2020-07-15T22:25:07 | 279,719,128 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,490 | r | Plot4.R | # Check for if Zip has been Downloaded,else to download.
if(!file.exists("EPA_national_emissions.zip")){
download.file("https://d396qusza40orc.cloudfront.net/exdata%2Fdata%2FNEI_data.zip","EPA_national_emissions.zip")
}
# Check for if Zip has been Unzipped,else to unzip.
if(!file.exists("EPA_national_emissions")){
... |
9081f04e8380595c6af898d2a04fff065196066c | d8978ecd115f95d9e4f6d987d54c2cb6541a6bf4 | /code/4_analyzeData/wrds/sizeAvailabilityAllMods.R | 42b7d5cfee16955bb53983d892ea2bf3c3e22afc | [] | no_license | emallickhossain/WarehouseClubs | f0eaab1b645e13654de655c2f13e47aa72b02a42 | 7867171cdb3ca3fe32ec778dd8043d538ab1f6ef | refs/heads/master | 2021-06-28T05:37:21.813087 | 2020-09-16T21:49:48 | 2020-09-16T21:49:48 | 149,994,881 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,691 | r | sizeAvailabilityAllMods.R | # Computes size availability of all non-food products in 2016
library(data.table)
library(ggplot2)
library(ggthemes)
yrs <- 2016
threads <- 8
path <- "/scratch/upenn/hossaine/nielsen_extracts/RMS/2016/"
zipImpute <- fread("/scratch/upenn/hossaine/zipImpute.csv",
select = c("zipImpute", "store_code_uc... |
06bba3b55636d5c0327d0d0646fc9ca3eeacf6b0 | a7c8cd3a56abe2ee6113e97028964804b28a6119 | /hw2/Presentation/m_estimation.R | caf09b511e019f4c2d27a940ab861740eee21b89 | [] | no_license | UmbertoJr/Stochastics_Process | d0c709f1a48f6c076f1cb91046327cdf7acec4b8 | a828917027a4d681867e7ecca46ce15ab2683dce | refs/heads/master | 2021-05-04T01:38:55.592174 | 2018-07-18T21:51:03 | 2018-07-18T21:51:03 | 120,361,580 | 4 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,183 | r | m_estimation.R | sethuraman.cost <- function(number.obs, M){
n <- 5000
y <- rnorm(n)
thet <- rbeta(n,shape1 = 1, shape2 = M)
prob <- rep(0,n)
prob[1] <- thet[1]
for(i in 2:n){
prob[i]<- thet[i]*prod(1 - thet[1:i-1])
}
dat <- sample(y,size= number.obs, prob=prob,replace=T)
return(dat)
}
function.M <- function(obs... |
7986d458877e714e12ac62ee98e722b425387676 | 6f07dccb7e29b191dde05af2c0d7eca21a521c60 | /within_ancestry/calc_frac_snps.R | ac64f8a8f2944a0fbea2a891c67669ffbe4ce774 | [] | no_license | squisquater/bees | 8f0619235cc0c9b126e97d71fa88675ae6384ddb | 0a93371f52528e2f2c2a4c572a3e9e5a5262ee6e | refs/heads/master | 2022-11-29T07:02:59.160548 | 2020-08-11T05:48:35 | 2020-08-11T05:48:35 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 887 | r | calc_frac_snps.R | # what is the snp density genomewide?
chr_length_tot <- sum(read.table("../data/honeybee_genome/chr.lengths")$V2)
gaps_tot <- read.table("../data/honeybee_genome/gaps.bed") %>%
mutate(length = V3 - V2) %>%
summarise(tot = sum(length)) %>%
unlist(.)
n_snps <- 3510834 # from wc -l chr.var.sites
# genome_size <- chr... |
71d6b9bd9b9d7f7a4e236b5cfe718ee0aeee5ac4 | ce597bcf02a6b10f739f093b4a786ed9e64276af | /tests/testthat/test-factor_creation.R | fe9c965485440613c79432896889b8634905ff32 | [
"MIT"
] | permissive | jonmcalder/refactor | 55a8a96b3430dcab4217fffb8c843b4010a274a8 | ecf6e4b35f2b60b9f4084fd62d460fb472d64e26 | refs/heads/master | 2021-06-18T18:42:56.870677 | 2020-11-13T15:11:24 | 2020-11-13T15:11:24 | 66,887,343 | 3 | 2 | null | 2017-08-12T15:05:10 | 2016-08-29T23:08:07 | R | UTF-8 | R | false | false | 3,446 | r | test-factor_creation.R | context("cfactor")
case1 <- cfactor(rep("x", 5))
case2 <- cfactor(letters, labels = "letter")
case3 <- cfactor(sample(letters, size = 400, replace = TRUE), levels = letters)
# regex ordering used
hard_to_dectect <- c("EUR 21 - EUR 22", "EUR 100 - 101",
"EUR 1 - EUR 10", "EUR 11 - EUR 20")
case4 <... |
c57beb5f54c754aa99a34ddff515202230e129ed | 6ceab1bf9c435b523d2f8e7e9440da39770d741b | /R/f7-download.R | e6c793022bcc95634c4ed3319714ac73e34a99df | [] | no_license | RinteRface/shinyMobile | a8109cd39c85e171db893d1b3f72d5f1a04f2c62 | 86d36f43acf701b6aac42d716adc1fae4f8370c6 | refs/heads/master | 2023-07-25T16:28:41.026349 | 2022-11-25T17:04:29 | 2022-11-25T17:04:29 | 139,186,586 | 328 | 92 | null | 2023-03-26T05:58:53 | 2018-06-29T19:13:06 | R | UTF-8 | R | false | false | 1,448 | r | f7-download.R | #' Create a download button
#'
#' Use these functions to create a download button;
#' when clicked, it will initiate a browser download. The
#' filename and contents are specified by the corresponding
#' shiny downloadHandler() defined in the server function.
#'
#' @param outputId The name of the output slot that the d... |
aea2f76bd2a22c6866d771693f1d6ee923d1dc1e | 6ad68090db6626c3e1c648047d57437337fb75ae | /src/an1/04.r | eaf51aea7b3b329d2efd56decf4b879cff9cc3c9 | [] | no_license | int28h/RTasks | 8764ba7fb8f06eb1b7e09d1dc4dd3a26458d12d6 | 88c39bb8e6b34c8743e16182e33ec5935ef3598f | refs/heads/master | 2022-06-17T18:06:26.464545 | 2022-06-03T22:40:50 | 2022-06-03T22:40:50 | 116,028,292 | 9 | 2 | null | null | null | null | UTF-8 | R | false | false | 1,394 | r | 04.r | # Воспользуемся встроенными данными airquality. В новую переменную сохраните subset исходных данных,
# оставив наблюдения только для месяцев 7, 8 и 9.
#
# При помощи функции aggregate рассчитайте количество непропущенных наблюдений по переменной Ozone в 7, 8 и 9 месяце.
# Для определения количества наблюдений исполь... |
3d5d5d5de50ca6100558d92388ee025b2d5aa805 | f317887c7d83e62235ba2cf19065dcef9244f645 | /man/prTable.Rd | 8507d68451552d9554df78ceffad9ec04ea62b72 | [] | no_license | rrprf/tablesgg | 3fec64842266f8a7f28e29899d31c673b5dad09c | 1a60f894869326b34eff1804c9378a1c05e78a79 | refs/heads/master | 2023-05-07T14:12:05.102317 | 2021-06-03T14:45:34 | 2021-06-03T14:45:34 | 318,291,905 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 680 | rd | prTable.Rd | % Auto-generated documentation for function prTable
% 2021-06-02 11:12:19
\name{prTable}
\alias{prTable}
\title{Create or Update a Fully Styled Table Ready for Plotting }
\description{
Create or update a \code{prTable} object, a fully styled (plot-ready)
table. This is an S3 generic. It and its methods are interna... |
61f158693cf1ea19f2e10d4a96b2a5d7b1cd0ad9 | 77157987168fc6a0827df2ecdd55104813be77b1 | /MGDrivE/inst/testfiles/calcCos/libFuzzer_calcCos/calcCos_valgrind_files/1612726553-test.R | 299a08c2aa005a44831391573500e7148a82bc21 | [] | no_license | akhikolla/updatedatatype-list2 | e8758b374f9a18fd3ef07664f1150e14a2e4c3d8 | a3a519440e02d89640c75207c73c1456cf86487d | refs/heads/master | 2023-03-21T13:17:13.762823 | 2021-03-20T15:46:49 | 2021-03-20T15:46:49 | 349,766,184 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 200 | r | 1612726553-test.R | testlist <- list(latLongs = structure(c(NaN, 4.48309463911336e-120, 1.64928503582928e-260, Inf), .Dim = c(2L, 2L)), r = 8.29692097078716e-317)
result <- do.call(MGDrivE::calcCos,testlist)
str(result) |
ee0490c60f6711c89d7ccbc67457f99de993a8f4 | cd21058c61cba55e8135def0dec1980d77f00ec0 | /Zmisc/man/n_percent_format.Rd | 6cabe0704dbe75c40b87e7f4faa682c4423c2792 | [] | no_license | Zus/zmisc | f37488c732a45bb12331fd8c832bb1497aa4e3cd | 4ec3303676606d968db478f6ef9ee0b880597a2f | refs/heads/master | 2021-01-01T05:14:41.954778 | 2018-09-21T07:07:24 | 2018-09-21T07:07:24 | 56,401,646 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 412 | rd | n_percent_format.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/utility.R
\name{n_percent_format}
\alias{n_percent_format}
\title{format text to be used in Rmd's mostly}
\usage{
n_percent_format(tabl, event = "1")
}
\arguments{
\item{event}{the way events are coded}
\item{a}{matrix with observations and ... |
bcc2ca6b8464245b1c7cdfd32fdba3a430aef234 | 00e7438f79f95ffab664390a0cbacaf407f4433b | /Merging Disease System Files/for_John_merge_all_files.R | f75559c5364f13d37986a57127b280ff6e3e3aa3 | [] | no_license | Key2-Success/HeartBD2K | 95b410f2b7233419650e6972058112532a7223d8 | 21ad025c40a396707e97dede993ac8c8b393bf13 | refs/heads/master | 2018-12-14T19:51:21.941506 | 2018-09-13T22:38:29 | 2018-09-13T22:38:29 | 108,905,096 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 5,028 | r | for_John_merge_all_files.R | library(dplyr)
library(stringi)
# read in all files
filenames <- list.files(path = "Kitu/College/Junior Year/Extracurriculars/Data Science Research Internship/John's Data/Merge All/",
pattern = "*.Rdata", full.names = TRUE)
for (i in 1:31)
{
load(filenames[i])
}
# merge all... |
8c7d51beec8b11ad16e00666ad62369edef35301 | 247946f5456e093a7fe49f57e722477ac9dc010e | /R/plot_pvals.R | d7f2027465fe590dea8e32e5a6f6ce3ab0b67800 | [
"MIT"
] | permissive | jdreyf/jdcbioinfo | b718d7e53f28dc15154d3a62b67075e84fbfa59b | 1ce08be2c56688e8b3529227e166ee7f3f514613 | refs/heads/master | 2023-08-17T20:50:23.623546 | 2023-08-03T12:19:28 | 2023-08-03T12:19:28 | 208,874,588 | 3 | 1 | null | null | null | null | UTF-8 | R | false | false | 2,068 | r | plot_pvals.R | #' Plot p-values
#'
#' Plot p-values
#'
#' @param pvals A matrix of p-values.
#' @param name Name of the plot file.
#' @param width Width of the plot.
#' @param height Height of the plot.
#' @return NULL
plot_pvals <- function(pvals, name=NA, width=8, height=7) {
stopifnot(pvals>=0, pvals<=1)
pvals <- t(pvals)
... |
96d038540735fb2b63bb8a689dd47365b42466be | 27912a635b637c2cb729e257cf5f2277887c8f35 | /7.MCMC/code/basicMCMC.R | 13d3d1b019878d34f9bbaed6cd9b745f03e1a3ec | [] | no_license | timothyfrasier/stats-2019 | 75e45292360fcbc088b6cc7dd45a1a344524d3ff | 2d74d63af0ac71217b7a3e95a27605a8744cc57b | refs/heads/master | 2020-04-15T06:04:20.335414 | 2019-03-28T09:06:06 | 2019-03-28T09:06:06 | 164,447,800 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 2,959 | r | basicMCMC.R | ###############################
# Code for teaching MCMC #
# Methods #
# #
# Requires: #
# The number of steps to take #
###############################
#-----------------------------#
# Basic Chain (No Peaks) #
#-----------------------------#... |
c676bf86841b254cc10a2be6110af66e352c769e | d2f9feb944e8b4315b79e10ac9bf569857aeef2b | /engine/simple_html_checker.R | 298f1efd3a274025620001911f5179ec99b2c7dd | [] | no_license | alucas69/CanvasQuizR | 9c73b9dbe0999f52576ce8066fcd836512900717 | de189a1df9ca3b65d144586f4396e5abb5cad91b | refs/heads/master | 2022-11-06T21:32:17.298853 | 2020-07-02T09:51:54 | 2020-07-02T09:51:54 | 272,904,014 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,213 | r | simple_html_checker.R | # only checks for stray "<" or ">"
simple_html_checker= function(vs_text) {
text= paste(vs_text, collapse = " ")
maxlen= stri_length(text)
# count < and > and <...>
position1= stri_locate_all(text, regex = ">")[[1]]
number_gt= nrow(position1) - is.na(position1[1,1])
position1= stri_locate_all(text, regex = ... |
ec0529072250828d09c663b4610183b97d9ac0f1 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/pheno/examples/connectedSets.Rd.R | 10a44bc1f68a1edb0c392c664642c600df8a75e5 | [] | 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 | 192 | r | connectedSets.Rd.R | library(pheno)
### Name: connectedSets
### Title: Connected sets in a matrix
### Aliases: connectedSets
### Keywords: design models
### ** Examples
data(Simple)
connectedSets(Simple)
|
345d9cf47027dfdafe21733e17dc43f30d38da21 | c67ed6bfca50b35228ef31a477865e0063701836 | /site_visit/CFQ_plots.R | a022206c0bef0c9c63e0b897ac0bec377c5f6b90 | [] | no_license | joetidwell/QES2 | 1bbfdbc4d5e901162064e14f2c37a8df58b8e350 | 1f2741e27c8ce7a58c486473f15d980236c70a55 | refs/heads/master | 2020-12-24T16:49:56.005345 | 2015-12-09T17:50:29 | 2015-12-09T17:50:29 | 32,096,494 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 9,605 | r | CFQ_plots.R | library(ggplot2)
library(foreach)
library(doMC)
registerDoMC()
source("~/ACE/global_vars.R")
source(file.path(kRootPath, "util", "load_data.R"), chdir=T)
source(file.path(kRootPath, "fitting", "interval_fitting_funcs.R"), chdir=T)
source(file.path(kRootPath, "forecast", "method_consensus_dist.R"), chdir=T)
theme_set(... |
5d16c43f93eba8ce83d63d91fc0bad96793686e3 | 4320dcc8598eb1bf08ee2ebd71dcd2558fb579d8 | /man/gn_search_all.Rd | e87616b19c0e1b18d7d13ff19b1a9ddb7c609198 | [] | no_license | jacob-ogre/us.geonames | 74716ee395fc44aa4b472ff0b71b4f2a35e593aa | 94b2f8b5a8adb415c8c351312685a545e6aabf09 | refs/heads/master | 2021-01-20T10:29:47.349100 | 2017-10-24T18:36:08 | 2017-10-24T18:36:08 | 100,292,189 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 756 | rd | gn_search_all.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/search.R
\name{gn_search_all}
\alias{gn_search_all}
\title{Search a file f for all geonames using \link{fastmatch}}
\usage{
gn_search_all(text, ngram_min = 1, ngram_max = 7)
}
\arguments{
\item{text}{Text to be searched for geonames; should b... |
c879df3e54561d047520d3239360290fb5d1f803 | f5171500752e258406718a0d2f33e027e97e9225 | /Simulators/Hardware/scripts/mf.gen.r | 8a761010c7821a6288ade024e1db249f73932d2b | [] | no_license | UFCCMT/behavioural_emulation | 03e0c84db0600201ccb29a843a4998dcfc17b92a | e5fa2f1262d7a72ab770d919cc3b9a849a577267 | refs/heads/master | 2021-09-25T17:55:33.428634 | 2018-10-24T15:55:37 | 2018-10-24T15:55:37 | 153,633,006 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,245 | r | mf.gen.r | wd <- "C:/Users/Krishna/Desktop/Research/BEO_TILE/memory files/8x8 for threads 0,1,6,7/appBEOs"
in.file <- "appBEO_iROM_0.txt"
out.file <- "appBEO_iROM_0.mif"
setwd(wd)
getwd()
mif.gen <- function(in.file, out.file){
require(compositions)
op.w <- 4
tag.w <- 6
did.w <- 10
stime.w <- 12
ntime.w <- 16
a... |
bc79eca5a55c1957dcba8d27667d2ab3e7c29664 | 165edd6be58684759ba6d45da6b121997ca768c9 | /plot3.R | 2adb5221a8938327088ec106a72d6e5701a0b29e | [] | no_license | xinyudong93/ExData_Plotting1 | ce095af380cabd9b46fa3017616c2a244ee422e7 | 64b3887819f7ba14d3b29495dfdb89b0b40b0216 | refs/heads/master | 2023-08-21T19:15:31.904381 | 2014-11-07T15:26:27 | 2014-11-07T15:26:27 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 864 | r | plot3.R | householdtable<-read.table("household_power_consumption.txt",stringsAsFactor=FALSE,sep=";",header=TRUE)
extractedSet<-householdtable$Date=='1/2/2007'|householdtable$Date=='2/2/2007'
subSet<-householdtable[extractedSet,]
png("plot3.png")
plot(as.difftime(paste(subSet$Date,subSet$Time),"%d/%m/%Y %H:%M:%S"),as.numeric(sub... |
522afdcb127dbb12073016eb850b0794abffb507 | c903ed6ec9e5181ca7e045f288a8e40410d18934 | /man/clean.Rd | 05a33153caed7cbf7d1107b42d7feb34ca26829d | [] | no_license | hrbrmstr/subtools | df92a1e75f18e734950ee247a295f0ed21cf41d4 | ff4469d9302f90ff1fa4c0182aeb61633d0f411e | refs/heads/master | 2020-06-01T11:05:54.669427 | 2019-06-07T15:13:23 | 2019-06-07T15:13:23 | 190,758,490 | 0 | 0 | null | 2019-06-07T14:35:59 | 2019-06-07T14:35:58 | null | UTF-8 | R | false | true | 961 | rd | clean.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/clean_subtitles.R
\name{cleanTags}
\alias{cleanTags}
\alias{cleanCaptions}
\alias{cleanPatterns}
\title{Clean subtitles}
\usage{
cleanTags(x, format = "srt", clean.empty = TRUE)
cleanCaptions(x, clean.empty = TRUE)
cleanPatterns(x, pattern,... |
552bd4c806dccfa712c40ff0f37cf67296d34632 | c201d8f03eb195d1c16dc7e7bdbd5eb1777aaa79 | /man/process_comments.Rd | 9860e44eda4623138652a5eaf516812e1aa06930 | [
"MIT"
] | permissive | lizbethvj/search_reddit | 824f44c04790b9ff8c66d0ec080e13e3f2eaf51a | 74491dd77006d1f68d310076d39aac22b2ed00bf | refs/heads/master | 2023-04-12T07:21:33.792490 | 2021-05-03T22:50:59 | 2021-05-03T22:50:59 | 360,658,537 | 0 | 0 | null | 2021-05-02T19:30:29 | 2021-04-22T19:23:25 | R | UTF-8 | R | false | true | 574 | rd | process_comments.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/process_comments.R
\name{process_comments}
\alias{process_comments}
\title{Process Comments for tidytext}
\usage{
process_comments(comments, other_stop_words = "gt")
}
\arguments{
\item{comments}{data frame, result of \code{extract_comments} ... |
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