GMNS is the "General Modeling Network Specification." GMNS itself is supported by the Zephyr Transport Foundation and is being developed here:
This is a JavaScript/TypeScript implementation of a GMNS reader. It allows you to read GMNS networks from your JavaScript code and convert them to a standard GeoJSON object usable anywhere that GeoJSON is spoken!
Load GMNS networks:
- from a .zipfile containing all GMNS tables
- from a folder containing the raw .csv tables
Convert GMNS:
- to GeoJSON format
As a courtesy, this package also contains a Python script which converts a MATSIM network.xml file into GMNS format. To convert your MATSIM network.xml to a zipped GMNS network file, first run:
python3 create-gmns-network.py
npm install @simwrapper/gmns// ESM
import GMNS from '@simwrapper/gmns'
// CommonJS
const GMNS = require('@simwrapper/gmns')
const network = GMNS.load('mynetwork.gmns.zip')
const geojson = GMNS.toGeojson(network)
console.log(geojson) // Output: { "type": "FeatureCollection", "features": [...]}Load a GMNS file from a path or from an already-loaded Blob object.
Returns a GMNSNetwork object, which contains
-
paththe file path from which the network was loaded -
configparameters loaded from config.csv -
tobject which contains all of the .csv tables that were found in the zip file or folder.
Parameters:
path Required. can be a valid .zip file, a valid folder path containing the various CSV files, or sometimes a path directly to the GMNS config.csv file itself (but this only works with certain web servers). Even if you pass in the data directly (see below), this path string is used for identifying the dataset.
data Optional. Pass in an ArrayBuffer, Blob object, Uint8Array, or Promise to one of those datatypes with the .zip file content. The data will be used directly instead of loading from the net or disk.
Returns a GeoJSON-compatible object with the network content. Currently only the nodes and link tables are read, and optionally if a geometry table exists, then the link geometries will also be present.
MIT