When using init.js
or init.py
to initialize your simulation, these standard library functions can help you easily initialize agents in predefined patterns.
Returns an array of agents at random positions within the bounds defined in topology
. Agents are generated as copies of the template
if you pass an object, or as the return value if you pass a function.
const init = (context) => {
// You can define the topology object here or in globals.json
const topology = context.globals().topology;
// Define agents without a position, since the scatter() function
// will assign random positions
const template = {
behaviors: ["move.js"],
color: "green",
};
// You can also pass a function instead of an object. This allows your agents
// to initialize certain properties stochastically
const templateFunction = () => ({
behaviors: ["move.js"],
color: Math.random() > 0.5 ? "green" : "blue",
});
// Generate the randomly scattered agents
const agents = hstd.init.scatter(100, topology, template);
const agentsFromFunction = hstd.init.scatter(100, topology, templateFunction);
return agents;
};
Returns an array of agents generated from the template
. Agents are generated as copies of the template
if you pass an object, or as the return value if you pass a function.
const init = (context) => {
const template = {
behaviors: ["move.js"],
position: [2, 10, 0],
color: "green",
};
// You can also pass a function instead of an object. This allows your agents
// to initialize certain properties stochastically
const templateFunction = () => ({
behaviors: ["move.js"],
position: [2, 10, 0],
color: Math.random() > 0.5 ? "green" : "blue",
});
// Generate the randomly scattered agents
const agents = hstd.init.stack(100, template);
const agentsFromFunction = hstd.init.stack(100, templateFunction);
return agents;
};
Returns an array of agents occupying every integer location within the bounds defined in topology
. Agents are generated as copies of the template
if you pass an object, or as the return value if you pass a function.
const init = (context) => {
// You can define the topology object here or in globals.json
const topology = context.globals().topology;
// Define agents without a position, since the grid() function
// will assign positions
const template = {
behaviors: ["move.js"],
color: "green",
};
// You can also pass a function instead of an object. This allows your agents
// to initialize certain properties stochastically
const templateFunction = () => ({
behaviors: ["move.js"],
color: Math.random() > 0.5 ? "green" : "blue",
});
// Generate the grid of agents
const agents = hstd.init.grid(topology, template);
const agentsFromFunction = hstd.init.grid(topology, templateFunction);
return agents;
};
Returns an array of agents based on a specified layout
and set of templates
. The layout
file must be a csv mapping agent types to initial positions. The templates
allow the function to determine the definition of each agent type. You can optionally specify a position offset
.
const init = (context) => {
const layout = context.data()["/layout_data.csv"];
// Note that templates don't have position, since that is assigned
// based on the layout file
const templates = {
c: {
agent_name: "crane",
behaviors: ["crane.js"],
},
f: {
agent_name: "forklift",
behaviors: ["move.js", "lift.js"],
},
w: {
agent_name: "wall",
color: "black",
},
};
// Optional position offset
const offset = [5, 5, 0];
const agents = hstd.init.createLayout(layout, templates, offset);
return agents;
};
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