Improve boid flocker model and documentation (#101)

* Improve boid flocker model

* Update Readme.md

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* Update model.py

* Update server.py

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---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

Author: coderbeta1

examples/boid_flockers/Readme.md

@@ -1,34 +1,47 @@
-# Flockers
+# Boids Flockers
+
+## Summary
 
 An implementation of Craig Reynolds's Boids flocker model. Agents (simulated birds) try to fly towards the average position of their neighbors and in the same direction as them, while maintaining a minimum distance. This produces flocking behavior.
 
 This model tests Mesa's continuous space feature, and uses numpy arrays to represent vectors. It also demonstrates how to create custom visualization components.
 
+## Installation
+
+To install the dependencies use pip and the requirements.txt in this directory. e.g.
+
+```
+    $ pip install -r requirements.txt
+```
+
 ## How to Run
 
-Launch the model:
+* To launch the visualization interactively, run ``mesa runserver`` in this directory. e.g.
+
+```
+$ mesa runserver
+```
+
+or
+
+Directly run the file ``run.py`` in the terminal. e.g.
+
 ```
-    $ python Flocker_Server.py
+    $ python run.py
 ```
 
-Then open your browser to [http://127.0.0.1:8521/](http://127.0.0.1:8521/) and press Reset, then Run.
+* Then open your browser to [http://127.0.0.1:8521/](http://127.0.0.1:8521/) and press Reset, then Run.
 
 ## Files
 
-* [flockers/model.py](flockers/model.py): Core model file; contains the BoidModel class.
-* [flockers/boid.py](flockers/boid.py): The Boid agent class.
-* [flockers/SimpleContinuousModule.py](flockers/SimpleContinuousModule.py): Defines ``SimpleCanvas``, the Python side of a custom visualization module for drawing agents with continuous positions.
-* [flockers/simple_continuous_canvas.js](flockers/simple_continuous_canvas.js): JavaScript side of the ``SimpleCanvas`` visualization module; takes the output generated by the Python ``SimpleCanvas`` element and draws it in the browser window via HTML5 canvas.
-* [flockers/server.py](flockers/server.py): Sets up the visualization; uses the SimpleCanvas element defined above
+* [boid_flockers/model.py](boid_flockers/model.py): Core model file; contains the Boid Model and Boid Agent class.
+* [boid_flockers/SimpleContinuousModule.py](boid_flockers/SimpleContinuousModule.py): Defines ``SimpleCanvas``, the Python side of a custom visualization module for drawing agents with continuous positions.
+* [boid_flockers/simple_continuous_canvas.js](boid_flockers/simple_continuous_canvas.js): JavaScript side of the ``SimpleCanvas`` visualization module; takes the output generated by the Python ``SimpleCanvas`` element and draws it in the browser window via HTML5 canvas.
+* [boid_flockers/server.py](boid_flockers/server.py): Sets up the visualization; uses the SimpleCanvas element defined above
 * [run.py](run.py) Launches the visualization.
-* [Flocker Test.ipynb](Flocker Test.ipynb): Tests the model in a Jupyter notebook.
+* [Flocker_Test.ipynb](Flocker_Test.ipynb): Tests the model in a Jupyter notebook.
 
 ## Further Reading
 
-=======
-* Launch the visualization
-```
-$ mesa runserver
-```
-* Visit your browser: http://127.0.0.1:8521/
-* In your browser hit *run*
+The following link can be visited for more information on the boid flockers model:
+https://cs.stanford.edu/people/eroberts/courses/soco/projects/2008-09/modeling-natural-systems/boids.html

examples/boid_flockers/app.py

@@ -16,8 +16,8 @@ def boid_draw(agent):
 }
 
 page = JupyterViz(
-    BoidFlockers,
-    model_params,
+    model_class=BoidFlockers,
+    model_params=model_params,
     measures=[],
     name="BoidFlockers",
     agent_portrayal=boid_draw,

examples/boid_flockers/boid_flockers/SimpleContinuousModule.py

@@ -3,11 +3,8 @@
 
 class SimpleCanvas(mesa.visualization.VisualizationElement):
     local_includes = ["boid_flockers/simple_continuous_canvas.js"]
-    portrayal_method = None
-    canvas_height = 500
-    canvas_width = 500
 
-    def __init__(self, portrayal_method, canvas_height=500, canvas_width=500):
+    def __init__(self, portrayal_method=None, canvas_height=500, canvas_width=500):
         """
         Instantiate a new SimpleCanvas
         """

examples/boid_flockers/boid_flockers/boid.py

@@ -8,7 +8,108 @@
 import mesa
 import numpy as np
 
-from .boid import Boid
+
+class Boid(mesa.Agent):
+    """
+    A Boid-style flocker agent.
+
+    The agent follows three behaviors to flock:
+        - Cohesion: steering towards neighboring agents.
+        - Separation: avoiding getting too close to any other agent.
+        - Alignment: try to fly in the same direction as the neighbors.
+
+    Boids have a vision that defines the radius in which they look for their
+    neighbors to flock with. Their speed (a scalar) and direction (a vector)
+    define their movement. Separation is their desired minimum distance from
+    any other Boid.
+    """
+
+    def __init__(
+        self,
+        unique_id,
+        model,
+        pos,
+        speed,
+        direction,
+        vision,
+        separation,
+        cohere=0.025,
+        separate=0.25,
+        match=0.04,
+    ):
+        """
+        Create a new Boid flocker agent.
+
+        Args:
+            unique_id: Unique agent identifyer.
+            pos: Starting position
+            speed: Distance to move per step.
+            direction: numpy vector for the Boid's direction of movement.
+            vision: Radius to look around for nearby Boids.
+            separation: Minimum distance to maintain from other Boids.
+            cohere: the relative importance of matching neighbors' positions
+            separate: the relative importance of avoiding close neighbors
+            match: the relative importance of matching neighbors' headings
+        """
+        super().__init__(unique_id, model)
+        self.pos = np.array(pos)
+        self.speed = speed
+        self.direction = direction
+        self.vision = vision
+        self.separation = separation
+        self.cohere_factor = cohere
+        self.separate_factor = separate
+        self.match_factor = match
+        self.neighbors = None
+
+    def cohere(self):
+        """
+        Return the vector toward the center of mass of the local neighbors.
+        """
+        cohere = np.zeros(2)
+        if self.neighbors:
+            for neighbor in self.neighbors:
+                cohere += self.model.space.get_heading(self.pos, neighbor.pos)
+            cohere /= len(self.neighbors)
+        return cohere
+
+    def separate(self):
+        """
+        Return a vector away from any neighbors closer than separation dist.
+        """
+        me = self.pos
+        them = (n.pos for n in self.neighbors)
+        separation_vector = np.zeros(2)
+        for other in them:
+            if self.model.space.get_distance(me, other) < self.separation:
+                separation_vector -= self.model.space.get_heading(me, other)
+        return separation_vector
+
+    def match_heading(self):
+        """
+        Return a vector of the neighbors' average heading.
+        """
+        match_vector = np.zeros(2)
+        if self.neighbors:
+            for neighbor in self.neighbors:
+                match_vector += neighbor.direction
+            match_vector /= len(self.neighbors)
+        return match_vector
+
+    def step(self):
+        """
+        Get the Boid's neighbors, compute the new vector, and move accordingly.
+        """
+
+        self.neighbors = self.model.space.get_neighbors(self.pos, self.vision, False)
+        self.direction += (
+            self.cohere() * self.cohere_factor
+            + self.separate() * self.separate_factor
+            + self.match_heading() * self.match_factor
+        ) / 2
+        self.direction /= np.linalg.norm(self.direction)
+        new_pos = self.pos + self.direction * self.speed
+        self.model.space.move_agent(self, new_pos)
 
 
 class BoidFlockers(mesa.Model):
@@ -39,7 +140,8 @@ def __init__(
             separation: What's the minimum distance each Boid will attempt to
                     keep from any other
             cohere, separate, match: factors for the relative importance of
-                    the three drives."""
+                    the three drives.
+        """
         super().__init__()
         self.population = population
         self.vision = vision
@@ -49,7 +151,6 @@ def __init__(
         self.space = mesa.space.ContinuousSpace(width, height, True)
         self.factors = {"cohere": cohere, "separate": separate, "match": match}
         self.make_agents()
-        self.running = True
 
     def make_agents(self):
         """
@@ -59,15 +160,15 @@ def make_agents(self):
             x = self.random.random() * self.space.x_max
             y = self.random.random() * self.space.y_max
             pos = np.array((x, y))
-            velocity = np.random.random(2) * 2 - 1
+            direction = np.random.random(2) * 2 - 1
             boid = Boid(
-                i,
-                self,
-                pos,
-                self.speed,
-                velocity,
-                self.vision,
-                self.separation,
+                unique_id=i,
+                model=self,
+                pos=pos,
+                speed=self.speed,
+                direction=direction,
+                vision=self.vision,
+                separation=self.separation,
                 **self.factors,
             )
             self.space.place_agent(boid, pos)