Class SegregationModel

java.lang.Object

org.episteme.social.sociology.SegregationModel

public final class SegregationModel
extends Object

An implementation of Thomas Schelling's model of spatial segregation. demonstrating how individual preferences for similar neighbors (homophily) can lead to macro-level segregation, even with mild preferences.

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static enum	SegregationModel.AgentType	Types of agents or occupancy status in the grid.
static final record	SegregationModel.GridState	Represents a snapshot of the grid at a specific simulation step.

Method Summary

Modifier and Type	Method	Description
static Real	calculateHappiness(SegregationModel.AgentType[][] grid, Real threshold)	Calculates the percentage of agents who are currently "happy".
static Real	calculateSegregationIndex(SegregationModel.AgentType[][] grid)	Calculates the Segregation (Dissimilarity) Index.
static List<SegregationModel.GridState>	simulate(int size, Real density, Real threshold, int steps)	Runs the Schelling segregation simulation.
static String	visualize(SegregationModel.AgentType[][] grid)	Generates a string visualization of the grid.

Methods inherited from class Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Details

simulate

public static List<SegregationModel.GridState> simulate(int size,
 Real density,
 Real threshold,
 int steps)

Runs the Schelling segregation simulation.

Parameters:

size - Dimensions of the grid (size x size)

density - Fraction of cells initially occupied (0.0 to 1.0)

threshold - Minimum fraction of similar neighbors required for an agent to be "happy"

steps - Maximum number of simulation steps

Returns:

List of GridState objects representing the simulation history

calculateSegregationIndex

public static Real calculateSegregationIndex(SegregationModel.AgentType[][] grid)

Calculates the Segregation (Dissimilarity) Index. Uses a simplified block-level dissimilarity measure.

Parameters:

grid - the simulation grid

Returns:

the segregation index score

calculateHappiness

public static Real calculateHappiness(SegregationModel.AgentType[][] grid,
 Real threshold)

Calculates the percentage of agents who are currently "happy".

Parameters:

grid - the simulation grid

threshold - the happiness threshold used

Returns:

happiness rate (0.0 to 1.0)

visualize

public static String visualize(SegregationModel.AgentType[][] grid)

Generates a string visualization of the grid.

Parameters:

grid - the grid to visualize

Returns:

string representation