gausam

<?php

/**
 * This recipe adds billing fields to the Membership Profile page.
 *
 * It is intended for use with the Register Helper Add On:
 * https://www.paidmembershipspro.com/add-ons/pmpro-register-helper-add-checkout-and-profile-fields/
 * 
 * You can add this recipe to your site by creating a custom plugin
 * or using the Code Snippets plugin available for free in the WordPress repository.

jasonsychau

# a combination of
# https://stackoverflow.com/questions/1815606/determine-path-of-the-executing-script/15373917#15373917
# https://stackoverflow.com/questions/1815606/determine-path-of-the-executing-script/7585599#7585599
# https://stackoverflow.com/questions/47044068/get-the-path-of-current-script/47045368#47045368
# https://stackoverflow.com/questions/53512868/how-to-automatically-include-filepath-in-r-markdown-document/53516876#53516876
stub <- function() {}
thisPath <- function() {
  cmdArgs <- commandArgs(trailingOnly = FALSE)
  if (length(grep("^-f$", cmdArgs)) > 0) {
    # R console option

andrewheiss

library(tidyverse)

# Make yard size, the presence/absence of a home garden, and attitudes toward the 
# environment all correlated with each other. Home garden will be binary, so I split 
# it based on some threshold later. Attitudes toward the environment will be on a 
# scale of 1-10, so I rescale and ceiling it later

mu <- c(yard_size = 20000, home_garden = 30, attitude_env = 70)
stddev <- c(yard_size = 10000, home_garden = 15, attitude_env = 40)

mkearney

## load rtweet
library(rtweet)

## store bounding box coordinates for state of nevada
nv <- c(-120.00647, 35.00186, -114.03965, 42.00221)

## initialize output vector and Midwestern 'ope' counter
s <- list()
ope <- 0L

hadley

# What's the most natural way to express this code in base R?
library(dplyr, warn.conflicts = FALSE)
mtcars %>%
  group_by(cyl) %>%
  summarise(mean = mean(disp), n = n())
#> # A tibble: 3 x 3
#>     cyl  mean     n
#>   <dbl> <dbl> <int>
#> 1     4  105.    11
#> 2     6  183.     7

mine-cetinkaya-rundel

# theme options based on hour of day -------------------------------------------
# based on https://github.com/rstudio/rstudio/issues/1579
setHook("rstudio.sessionInit", function(chooseTheme) {
  if (chooseTheme) {
    if (as.numeric(format(as.POSIXct(Sys.time(), format = "%H:%M:%S"), "%H")) %in% c(0:5, 21:23)) {
      if (rstudioapi::getThemeInfo()$editor != "Solarized Dark") rstudioapi::applyTheme("Solarized Dark")
    } else {
      if (rstudioapi::getThemeInfo()$editor != "Solarized Light") rstudioapi::applyTheme("Solarized Light")
    }
  }

DarwinAwardWinner

local({

    ## Put everything in a separate environment and attach that
    ## environment. Re-use the existing one from the search path it
    ## it's available, so that re-executing this file doesn't add a
    ## new environment to the search path every time.
    custom_env <- tryCatch(as.environment("rct_custom_env"),
                           error=function(...) {
                               attach(NULL, name="rct_custom_env")
                               as.environment("rct_custom_env")

UncleCJ

How to use Gephi to visualize from Wikidata

I'm a long-time fan of the graph visualization tool Gephi and since Wikimania 2019 I got involved with Wikidata. I was aware of the Gephi plugin "Semantic Web Importer", but when I check it out, I only find old tutorials connecting to DBpedia, not Wikidata:

• "Visualising Related Entries in Wikipedia Using Gephi" by Tony Hirst, 2012-07-03
• "Let’s Play Gephi: Dbpedia, RDF, Sparql and your favorite Actors" by Matthieu Totet, 2015-10-06
• ["Gephi tutorials: Semantic Web Importer" by Matthieu

sbalci

# Find Packages Used in a Project Using Regular Expressions RegEx

list_of_Rmd_R <- c(
    list.files(path = here::here(),
               pattern = "\\.Rmd|.R$", # find files ending with .Rmd and .R
               full.names = TRUE
    ),
    
    list.files(path = here::here("childRmd"),
               pattern = "\\.Rmd|.R$",

sbalci

When you use knit_expand it appears that the inclusion of the Rmd is done on the first pass, and then the complete document evaluated. This means that a Rmd block referenced in loop with knit_expand will only evaluate changing variables at their last value.

This can be worked around by passing the literal value of the variable at the time of the knit_expand with {{var}} syntax.

This is documented in the knitr_expand docs, but less clear (to an R noob like me) for embedded documents rather than strings.