factorgraph-viz

This is a small factor graph visualizer written in Typescript. It uses the d3-force component of D3.js.

Installation

You can install d3 (which is required at runtime) as well as the types and schema dependencies (which is required to update the code) all at once.

npm install

A pre-compiled library is provided in build/factorgraph-viz.js. You can also produce a fresh version:

npm run-script compile

Usage

You'll need to run a web server locally to serve up your factor graph data. The provided script requires python and creates a server on port 8000.

./server.sh

Visiting localhost:8000 will show index.html. The code loads the config file data/config/default.json, which in turn specifics where to look for factor graphs:

{
    // This is where factorgraph files are located. It can be a local directory
    // (like this) or the URL of a directory.
    "data_dir": "data/examples/",

    // This is a file (again, local or remote) that contains an array of
    // strings. Each string should be the name of a .json file (without the
    // .json extension) that lives in  `data_dir`. These are the factor graphs
    // available to load.
    "data_filenames": "data/options/example-list.json",

    // This is a file to load on startup. It should be relative to `data_dir`
    // and without the .json extension (just like the entries found in
    // `data_filename`)
    "startup_filename": "07-complex-size-threw_d",

    // (config continues ...)
}

New: The frontend provides autocomplete for strings (factor graph names) found in the data_filenames list. The autocomplete suggestions are clickable, which will immediately load the corresponding factor graph.

Factor graph format

In order to produce a factor graph, you must save a JSON file that matches the required format.

Specification

The code requires a JSON object with two properties, nodes and links.

• Every node needs a unique id property and a type property. The type property can be either "rv" (random variable) or "fac" (factor). For nodes with "type": "rv", their id will be displayed in text next to them. For nodes with "type": "fac", an additional property subtype can be provided, which will be displayed as text next to them. The property "focus": true can be added to any node and it will centered in the display.

• Each link must have a source and target property. Both source and target must match an id of one of the nodes.

A weights property can be added to any node or link and the code will colorize that component accordingly. The value for weights should be an array of numbers, one for each value of the relevant random variable. The code will do an argmax and colorize based on the index of the highest weight. To customize the colorization scheme, see below in customization.

See below for examples of valid factor graph JSON files.

Schema validation

To aid in creating valid factor graph JSON files, a schema file is provided in data/schema/factorgraph.json. In addition, a simple JSON schema validation tool (which uses jsonschema) is provided in build/validator.js. You can use it to check whether your files conform to the spec required by this library.

Don't forget to run npm install first.

# Check an individual file.
node build/validator.js data/schema/factorgraph.json data/examples/02-simple-onenode.json

# Check all files in a directory.
node build/validator.js data/schema/factorgraph.json data/examples/

Examples

Simple example

Here is a simple example (data/examples/03-simple-binaryfactor.json). It contains two random variables and one binary factor that connects them.

{
   "nodes": [
      {"id": "rv1", "type": "rv", "focus": true},
      {"id": "rv2", "type": "rv"},
      {"id": "fac1", "type": "fac", "subtype": "hello, world"}
   ],
   "links": [
      {"source": "rv1", "target": "fac1"},
      {"source": "fac1", "target": "rv2"}
   ]
}

Here is how the above example is rendered:

Colorized example

The following example (data/examples/04-simple-binaryfactor-color.json) provides weights for the values of the random variables. It uses three values. The colorization is based on the index of the greatest value. The default colorization scheme uses red for the first value, blue for the second, and grey for the third. This example also adds a unary factor to show that factors can also have weights (and thus colors).

{
   "nodes": [
      {"id": "rv1", "type": "rv", "weights": [0.7, 0.2, 0.1], "focus": true},
      {"id": "rv2", "type": "rv", "weights": [0.1, 0.8, 0.1]},
      {"id": "fac1", "type": "fac", "subtype": "i'm a unary factor",
         "weights":[0.75, 0.1, 0.1]},
      {"id": "fac2", "type": "fac", "subtype": "i'm a binary factor"}
   ],
   "links": [
      {"source": "rv1", "target": "fac1", "weights":[0.75, 0.1, 0.1]},
      {"source": "rv1", "target": "fac2", "weights":[0.65, 0.35, 0.1]},
      {"source": "fac2", "target": "rv2", "weights":[0.05, 0.9, 0.05]}
   ]
}

Here is how it will be rendered:

Additional examples

More examples are provided in data/examples/. They are ordered from simple to complex.

Customization

There are three places to configure factorgraph-viz without recompiling it:

1. in the config JSON file (found by default in data/config/default.json)
2. the CSS file (found by default in css/default.css)
3. the HTML file (index.html)

1. data/config/default.json

This file is where all of the configuration is loaded. It specifies where factor graph JSON files can be found, how large to render random variables and factors, the strength and location of the positioning forces that alter the layout of the factor graph, and the colorization scheme that is applied when the weights property is provided.

More detail is given about the configuration options at what they mean in the Typescript type that loads this object, which is located in src/config.ts.

2. css/default.css

Due to how SVG works, CSS cannot control the sizing of the random variables or factors (which is why those are defined in the JSON config file). However, the various strokes for the factor graph shapes and the all of the font and styling options for the text are specified in this CSS file.

3. index.html

The HTML file is minimal, so there are probably only a few reasons why you might want to configure it: (1) To change the location of d3 (by default it is expected to be found in node_modules/d3/build/d3.js), (2) to change the size of the SVG element (by default it is 800 x 600), (3) To change the CSS file loaded (by default css/default.css), (4) To change the factorgraph-viz library loaded (by default build/factorgraph-viz.js).

Contributing

There's plenty of low-hanging fruit to work on if you'd like to contribute to this project. Here are a couple ideas:

• Make an axis-specific many body force. This could help separate the nodes vertically so that the text doesn't overlap.

• Compute stats of the factor graph on-the-fly and display them

See also

• to learn more about factor graphs, check out the Structured Belief Propagation for NLP Tutorial by Matthew R. Gormley and Jason Eisner.

• py-factorgraph is a factor graph and loopy belief propagation library, written in Python.

• verbphysics is a project that uses factor graphs. It makes use of both py-factorgraph and factorgraph-viz.