cppSim

This package is in its early versions of development, it aims at providing a set of fast, efficient functions to perform Gravity models in the context of spatial interaction modelling. Currently, the doubly constrained model is implemented and future versions will aim to implement origin and destination constraints as well. It was developed in the context of studying commuter flows by active travel (cycling & walking ) in Great Britain as part of a project at CASA, UCL.

Installation

Not yet on CRAN, so please install the development version of cppSim with:

# install.packages("devtools")
devtools::install_github("ischlo/cppSim")

Built in data sets

The package comes with sample data sets that allow to test the functions right away as well as see the type of input that is recommended.

• flows_test : using the official census data in England from 2011, it’s a 983x983 matrix representing the flows of cyclists and pedestrians from each to each MSOA in London.
• distance_test : the distances between centroids of MSOAs. Computed with the London road network from OpenStreetMap and using the cppRouting package.

Example

Using the built-in data sets flows_test and distance_test, we can run a test by following the example This is a basic example which shows you how to solve a common problem:

library(cppSim)
## basic example code

data("flows_test")
data("distance_test")


model_test <- run_model(flows = flows_test
                        ,distance = distance_test)

Performance

Compared to the equivalent functions implemented in pure R, it runs about x10 faster.

#>      test replications elapsed relative user.self sys.self user.child sys.child
#> 2     cpp           10   3.257    1.000     3.046    0.184          0         0
#> 1 regular           10  34.201   10.501    31.887    1.970          0         0