Plates

Using plate notation can be a powerful way to describe your model

What is a plate?

A plate is a group of vertices that is repeated multiple times in the network. They typically represent a concept larger than a vertex like an agent in an ABM or some observations that are associated.

How do you build them?

We’re redesigning how this is done but for now there are some handy helper functions to get you started.

Let’s say you have a class `MyData` that looks like this:

``````public static class MyData {
public double x;
public double y;

public MyData(String x, String y) {
this.x = Double.parseDouble(x);
this.y = Double.parseDouble(y);
}
}
``````

This is an example of how you could pull in data from a csv file and run linear regression, using plates to build identical sections of the graph for each line of the csv.

``````/**
* Each plate contains a linear regression model:
* VertexY = VertexX * VertexM + VertexB
* @param dataFileName The input data file defines, for each plate:
*                          - the value of the input, VertexX
*                          - the value of the observed output, VertexY
*/
public Plates buildPlates(String dataFileName) {
//Parse the csv data to MyData objects
.asRowsDefinedBy(MyData.class)

DoubleVertex m = new GaussianVertex(0, 1);
DoubleVertex b = new GaussianVertex(0, 1);
VertexLabel xLabel = new VertexLabel("x");
VertexLabel yLabel = new VertexLabel("y");

//Build plates from each line in the csv
Plates plates = new PlateBuilder<MyData>()
.fromIterator(allMyData.iterator())
.withFactory((plate, csvMyData) -> {

ConstantDoubleVertex x = new ConstantDoubleVertex(csvMyData.x).setLabel(xLabel);
DoubleVertex y = m.multiply(x).plus(b).setLabel(yLabel);

DoubleVertex yObserved = new GaussianVertex(y, 1);
yObserved.observe(csvMyData.y);

// this labels the x and y vertex for later use
})
.build();

//now you have access to the "x" from any one of the plates
DoubleTensor valueForXAtCSVLine1 = plates.asList()
.get(1) // get plate 1 which is built from csv line 1
.<DoubleVertex>get(xLabel) //get the vertex that we labelled "x" in that plate
.getValue(); //get the value from that vertex

//Now run an inference algorithm on vertex m and vertex b and you have linear regression

return plates;
}
``````