Gams2js NPM | npm.io

gams2js 🐬

A GAMS output file parser for JavaScript

This simple script parses the results of a GAMS job (called output/listing file) and turns them into a JavaScript object.

The parser can be used in combination with the neos-js package for solving GAMS jobs on the NEOS servers, as well as for using GAMS in an Observable.

What can I use this for?

Using GAMS in a web-application (or an Observable) allows for writing didactic GAMS models, without requiring users (students, reviewers, readers) to install any additional software. Everything they need is a web browser.

This can make it easier for anyone interested in your research to understand, follow and run your model, without the additional overhead of setting up a working environment first.

Opposed to GAMS MIRO (build on Shiny), gams2js does not impose any web framework on developers. This allows for more flexible web-development (despite offering less features).

Compared to a (non cloud hosted) Jupyter Notebook, using gams2js in an Observable allows for running, and working with the results of your model without download and installing anything.

Example

const listing = `... other contents of the listing
---- VAR x  shipment quantities in cases

                      LOWER     LEVEL     UPPER    MARGINAL

Seattle  .New-York      .       50.000     +INF       .         
Seattle  .Chicago       .      300.000     +INF       .         
Seattle  .Topeka        .         .        +INF      0.036      
San-Diego.New-York      .      275.000     +INF       .         
San-Diego.Chicago       .         .        +INF      0.009      
San-Diego.Topeka        .      275.000     +INF       .      

... further contents of the listing
`

const solution = gams(listing)
// get the number of solve statements found
console.log(solution.solves.length)
// get the objective value of a particular solve
console.log(solution.solves[0].objective)
// get a dataframe (array of JS object) of the variable 'x', including all solves
const x = solution.get('x')
/* where x yields a dataframe of the format
[{
  "marginal": 0,
  "level": 50,
  "upper": Infinity,
  "lower": 0,
  "domain": ["Seattle", "New-York"],
  "name": "x",
  "description": "shipment quantities in cases"
}, {
  "marginal": 0,
  "level": 300,
  "upper": Infinity,
  "lower": 0,
  "domain": ["Seattle", "Chicago"],
  "name": "x",
  "description": "shipment quantities in cases"
},{
...
}
]
*/

// get a dataframe of the variable 'x', where the first domain is always equal 
// to 'Seattle' (including all solves)
const x = solution.get('x','Seattle')
// get a dataframe of the variable 'x', where the first domain is Seattle and 
// the second domain is Chicago, but only from the first solve statement
// remember that in JS you start countin at 0 😏
const x = solution.get('x',['Seattle','Chicago'],0)

Installation

Browser

Grab a release from the dist folder. Then, in the header include:

<script src="assets/gams2js.min.js"></script>

This exposes the global variable gams.

Node-JS

Install via npm

npm i gams2js

then

const gams = require('gams2js')
// or ES6 import
import gams from 'gams2js'

API

`gams(listing)`

Where listing is a UTF-8 encoded string containing the output of a GAMS run.

Example:

const solution = gams(listing)

The return value of the function is an object with the following properties

solves \<array>, an array of objects for each solve statement
- objective \<number>, the objective value of the solve
- line \<number>, the line number of the the solve
- modelStatus \<number>, the GAMS model status of the solve
- equations \<array>, an array of objects, each object representing a row of equation data
  - name \<string>, the GAMS identifier of the equation row
  - domain \<array>, the domain of the equation row, [] if not domain present
  - lower \<number>, the lower bound of the equation row
  - level \<number>, the solution level of the equation row
  - upper \<number>, the upper bound of the equation row
  - marginal \<number>, the marginal value of the equation row
- variables \<number>, an array of objects, each object representing a row of variable data
  - name \<string>, the GAMS identifier of the variable row
  - domain \<array>, the domain of the variable row, [] if not domain present
  - lower \<number>, the lower bound of the variable row
  - level \<number>, the solution level of the variable row
  - upper \<number>, the upper bound of the variable row
  - marginal \<number>, the marginal value of the variable row
get \<function>, see below for usage instructions

`[solution].get(symbol,[domain],[solve])`

A getter function for retrieving values from the listing.

symbol \<string, case-insensitive>, the GAMS identifier to search for, may either be a variable or equation
domain \<string/array, case-insensitive> optional, filter the identifier by a domain. If a string is passed, the first domain element is converted to an array of length 1. Empty indexes in an array act as a wildcard (e.g. '','Seattle' would allow any label for the first domain, but only Seattle for the second).
solve \<number>, optional, the array index position of the solve to limit the search for. If omitted, all solves will be queried

What are the limitations?

gams2js does not serve as a higher level GAMS API, it merely allows for accessing the results of a model run.

Opposed to the higher level GAMS APIs, which are capable of communicating with GAMS via the GAMS data eXchange format (GDX), this library relies on parsing the GAMS output file.

Parsing a GAMS output file opposed to reading a GDX comes with several limitations:

Symbol names (variable and equation names), longer than 10 characters are not supported, as they might be truncated in the listing with a ~. This makes it impossible for the parser to distinguish symbols longer than 10 characters with the same basename. While the options dispWidth = value command can be used to increase the display width for display statements, this option won't affect general variable and equation prints in the listing. Keep in mind that you can add a description for you identifiers with up to 255 characters, which will be picked up by gams2js.
When using the NEOS-Server for solving a GAMS job, non-ASCII characters (e.g. é,ä,œ) are not allowed in the GAMS model. It is therefore advised to write the models in plain english, or write an escape function for your model. Keep in mind that the results of the JavaScript encodeURI do not adhere to the GAMS naming conventions, so you need to write one yourself.
Unexpected things may occur, as parsing is done using regular expressions and string manipulation. This library is only tested against a limited number of test cases, you are invited to help expand it!

What are possible alternatives?

gams2js is still in a very early stage of development, and lacks many of the features that make GAMS a great language. Making use of syntax highlighting, code-completion, and error highlighting (all features of GAMS Studio or linter-gams) are not supported when using gams2js in an Observable. Also, sequential code execution, as well as direct interaction with GAMS symbols as in a Jupyter Notebook is not supported. For more ambitous projects (maybe outside scope of a didactic model) please have a look at the following projects:

Jupyter @ GAMS on Jupyterhub - Exceuting and communicating with GAMS in a Jupyter Notebook
GAMS MIRO - a deployment environment that allows to turn GAMS models into interactive applications.
linter-gams - A GAMS IDE build on Atom featuring interactive symbol navigation, an R-Studio like data panel, model-aware auto-completion and many more features.
Contribution
Contribution is highly appreciated 👍!
Please open an issue in case of questions / bug reports or a pull request if you implemented a new feature / bug fix.
In the latter case, please make sure to run npm test (and adapt test/test.js to your changes) and / or update the README 🙂
License
MIT @Christoph Pahmeyer
This software is crafted with :heart: at the University of Bonn - EMAS Group