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# download and store the data
library (osmdata)
library (dodgr0
library (bikedata)
bikedir <- "/data/data/bikes"
bikedb <- file.path (bikedir, "all_bike_data.sqlite")
cities <- bike_demographic_data ()$city

dl <- function ()
{

mpadge

# Run script anywhere in R package directory to manually run a clang pedantic check on all src files
cpp_flgs <- c_flgs <- "-Wall -pedantic -Werror"                                     
setwd (here::here ("src"))                                                          
cmd_base <- paste ("-I/usr/share/R/include -DNDEBUG",                               
                  "-I\"/usr/local/lib/R/site-library/Rcpp/include\" -fpic",         
                  "-g -O2 -fstack-protector-strong -Wformat",                       
                  "-Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -g")     
flist_c <- list.files (".", pattern = "\\.c$")                                      
for (f in flist_c)                                                                  
{                                                                                   

mpadge

This gist can be used to create test files for the bikedata package. These are ultimately stored in an .rda structure, but this removes a lot of the original text-based idiosyncracies of the raw .csv files. This script is thus necessary to convert the read.csv() results back in to the precise forms of the individual .csv files for each city.

First step is to create sample test files for each city and compress them in .zip archives. These can then be unzipped and read into R with these lines:

mpadge

devtools::load_all (".", export_all = FALSE)

## Loading osmprob

#devtools::load_all (".")
#devtools::document (".")
#devtools::check (".")

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#!/bin/bash
# AUTHORS:  Bob Rudis <bob@rudis.net> (@hrbrmstr)
#           Mark Padgham <mark.padgham@email.com>
# LICENSE: MIT + file zLICENSE
#
# Adapted by Mark Padgham from original gist of Bob Rudis

TODAY=`date +%Y-%m-%d`
TODAY_MD=`date +%B\ %d,\ %Y`
YEAR=`date +%Y`

mpadge

Compares Rcpp construction of sp::Line objects either:

1. Constructed as new objects with slots filled directly, or
2. Constructed the 'usual' way through filling the sp object with data.

In R terms, these are equivalent to:

library (sp)
# first way