Rafael H M Pereira rafapereirabr

quick code snippet to create (weighted) quantiles in R using data.table.

Create reproducible example

library(data.table)
library(Hmisc)

# create data.table
n &lt;- 100000

Calculating distance between spatial object and the nearest border

Quick example showing how to calculate the distance from each census tract to the nearest muncipality border

library(sf)
library(furrr)
library(geobr)
library(mapview)
library(magrittr)
library(data.table)

A simple reproducible Hexsticker for r5r, a package for Rapid Realistic Routing with R5 in R.

### Libraries ------------------------
remotes::install_github("GuangchuangYu/hexSticker")

library(hexSticker) # https://github.com/GuangchuangYu/hexSticker
library(ggplot2)
library(sf)


library(ggmap)
library(data.table)

# registrar Google API Key
register_google(key = 'xxxxx-xxxxxx-xxxxx-xxxxx')

	```
	library(sf)
	library(geobr)


	# sample spatial data
	df <- read_state()

	# create random pop and cases
	df$pop <- sample(1:27, 27, replace = T)


	library(geobr)
	library(sf)
	library(mapview)
	library(stringr)
	mapviewOptions(platform = 'leafgl')

	# read original census tracts
	urban_cts <- read_census_tract(year = 2000, code_tract = 'RJ', zone ='urban', simplified = F)
	rural_cts <- read_census_tract(year = 2000, code_tract = 'RJ', zone ='rural', simplified = F)

	library(googleAnalyticsR)
	library(data.table)
	library(ggplot2)
	library(dplyr)
	library(rworldmap)
	library(sf)
	options(scipen=999)

	## setup
	ga_auth()

	library(geobr)
	library(ggplot2)
	library(sf)
	library(sfheaders)

	df <- read_municipality(year=2018)
	centrd <- st_centroid(df)

	centrd <- sfheaders::sf_to_df(centrd, fill=T)
	df$position <- centrd$y + centrd$x

	library(gtfs2gps)
	library(gtfsrouter)


	# original process
	sp <- system.file("extdata/saopaulo.zip", package ="gtfs2gps")

	time_gps <- system.time(gps_gps <- gtfs2gps(sp, parallel = T, spatial_resolution = 200))

	#' Code by Rafael H. M. Pereira and Marcus Saraiva
	#'
	#' Radiation model (Simini et al 2012)
	#' Tij = Ti * ((Pi * Pj) / ((Pi + Pij) * (Pi + Pj + Pij)))
	#'
	#' Where:
	#'
	#' Tij: Avarage flux between origin i and destination j predicted by the radiation model
	#' Ti: Proportion of population in i relative to total population
	#' Pi: Absolute population in i