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

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Author: pre-commit-ci[bot]

examples/advanced/epstein_civil_violence/epstein_civil_violence/agent.py

@@ -5,18 +5,15 @@
 
 class EpsteinAgent(mesa.experimental.cell_space.CellAgent):
     def update_neighbors(self):
-        """
-        Look around and see who my neighbors are
-        """
+        """Look around and see who my neighbors are"""
         self.neighborhood = self.cell.get_neighborhood(radius=self.vision)
 
         self.neighbors = self.neighborhood.agents
         self.empty_neighbors = [c for c in self.neighborhood if c.is_empty]
 
 
 class Citizen(EpsteinAgent):
-    """
-    A member of the general population, may or may not be in active rebellion.
+    """A member of the general population, may or may not be in active rebellion.
     Summary of rule: If grievance - risk > threshold, rebel.
 
     Attributes:
@@ -46,8 +43,8 @@ def __init__(
         threshold,
         vision,
     ):
-        """
-        Create a new Citizen.
+        """Create a new Citizen.
+
         Args:
             model: the model to which the agent belongs
             hardship: Agent's 'perceived hardship (i.e., physical or economic
@@ -73,9 +70,7 @@ def __init__(
         self.arrest_probability = None
 
     def step(self):
-        """
-        Decide whether to activate, then move if applicable.
-        """
+        """Decide whether to activate, then move if applicable."""
         if self.jail_sentence:
             self.jail_sentence -= 1
             return  # no other changes or movements if agent is in jail.
@@ -92,8 +87,7 @@ def step(self):
             self.move_to(new_cell)
 
     def update_estimated_arrest_probability(self):
-        """
-        Based on the ratio of cops to actives in my neighborhood, estimate the
+        """Based on the ratio of cops to actives in my neighborhood, estimate the
         p(Arrest | I go active).
         """
         cops_in_vision = len([c for c in self.neighbors if isinstance(c, Cop)])
@@ -111,8 +105,7 @@ def update_estimated_arrest_probability(self):
 
 
 class Cop(EpsteinAgent):
-    """
-    A cop for life.  No defection.
+    """A cop for life.  No defection.
     Summary of rule: Inspect local vision and arrest a random active agent.
 
     Attributes:
@@ -123,8 +116,8 @@ class Cop(EpsteinAgent):
     """
 
     def __init__(self, model, vision):
-        """
-        Create a new Cop.
+        """Create a new Cop.
+
         Args:
             x, y: Grid coordinates
             vision: number of cells in each direction (N, S, E and W) that
@@ -135,8 +128,7 @@ def __init__(self, model, vision):
         self.vision = vision
 
     def step(self):
-        """
-        Inspect local vision and arrest a random active agent. Move if
+        """Inspect local vision and arrest a random active agent. Move if
         applicable.
         """
         self.update_neighbors()

examples/advanced/epstein_civil_violence/epstein_civil_violence/model.py

@@ -4,8 +4,7 @@
 
 
 class EpsteinCivilViolence(mesa.Model):
-    """
-    Model 1 from "Modeling civil violence: An agent-based computational
+    """Model 1 from "Modeling civil violence: An agent-based computational
     approach," by Joshua Epstein.
     http://www.pnas.org/content/99/suppl_3/7243.full
     Attributes:
@@ -103,9 +102,7 @@ def __init__(
         self.datacollector.collect(self)
 
     def step(self):
-        """
-        Advance the model by one step and collect data.
-        """
+        """Advance the model by one step and collect data."""
         self.agents.shuffle_do("step")
         # collect data
         self.datacollector.collect(self)
@@ -115,9 +112,7 @@ def step(self):
 
     @staticmethod
     def count_type_citizens(model, condition, exclude_jailed=True):
-        """
-        Helper method to count agents by Quiescent/Active.
-        """
+        """Helper method to count agents by Quiescent/Active."""
         citizens = model.agents_by_type[Citizen]
 
         if exclude_jailed:
@@ -133,14 +128,10 @@ def count_type_citizens(model, condition, exclude_jailed=True):
 
     @staticmethod
     def count_jailed(model):
-        """
-        Helper method to count jailed agents.
-        """
+        """Helper method to count jailed agents."""
         return len([a for a in model.agents_by_type[Citizen] if a.jail_sentence > 0])
 
     @staticmethod
     def count_cops(model):
-        """
-        Helper method to count jailed agents.
-        """
+        """Helper method to count jailed agents."""
         return len(model.agents_by_type[Cop])

examples/advanced/pd_grid/analysis.ipynb

@@ -58,8 +58,7 @@
     "\n",
     "\n",
     "def draw_grid(model, ax=None):\n",
-    "    \"\"\"\n",
-    "    Draw the current state of the grid, with Defecting agents in red\n",
+    "    \"\"\"Draw the current state of the grid, with Defecting agents in red\n",
     "    and Cooperating agents in blue.\n",
     "    \"\"\"\n",
     "    if not ax:\n",
@@ -82,9 +81,7 @@
    "outputs": [],
    "source": [
     "def run_model(model):\n",
-    "    \"\"\"\n",
-    "    Run an experiment with a given model, and plot the results.\n",
-    "    \"\"\"\n",
+    "    \"\"\"Run an experiment with a given model, and plot the results.\"\"\"\n",
     "    fig = plt.figure(figsize=(12, 8))\n",
     "\n",
     "    ax1 = fig.add_subplot(231)\n",

examples/advanced/pd_grid/pd_grid/agent.py

@@ -5,8 +5,7 @@ class PDAgent(CellAgent):
     """Agent member of the iterated, spatial prisoner's dilemma model."""
 
     def __init__(self, model, starting_move=None):
-        """
-        Create a new Prisoner's Dilemma agent.
+        """Create a new Prisoner's Dilemma agent.
 
         Args:
             model: model instance
@@ -27,8 +26,8 @@ def is_cooroperating(self):
 
     def step(self):
         """Get the best neighbor's move, and change own move accordingly
-        if better than own score."""
-
+        if better than own score.
+        """
         # neighbors = self.model.grid.get_neighbors(self.pos, True, include_center=True)
         neighbors = [*list(self.cell.neighborhood.agents), self]
         best_neighbor = max(neighbors, key=lambda a: a.score)

examples/advanced/pd_grid/pd_grid/model.py

@@ -17,8 +17,7 @@ class PdGrid(mesa.Model):
     def __init__(
         self, width=50, height=50, activation_order="Random", payoffs=None, seed=None
     ):
-        """
-        Create a new Spatial Prisoners' Dilemma Model.
+        """Create a new Spatial Prisoners' Dilemma Model.
 
         Args:
             width, height: Grid size. There will be one agent per grid cell.

examples/advanced/pd_grid/pd_grid/portrayal.py

@@ -1,6 +1,5 @@
 def portrayPDAgent(agent):
-    """
-    This function is registered with the visualization server to be called
+    """This function is registered with the visualization server to be called
     each tick to indicate how to draw the agent in its current state.
     :param agent:  the agent in the simulation
     :return: the portrayal dictionary

examples/advanced/sugarscape_g1mt/app.py

@@ -1,10 +1,11 @@
 import numpy as np
 import solara
 from matplotlib.figure import Figure
-from mesa.visualization import SolaraViz, make_plot_measure
 from sugarscape_g1mt.model import SugarscapeG1mt
 from sugarscape_g1mt.trader_agents import Trader
 
+from mesa.visualization import SolaraViz, make_plot_measure
+
 
 def SpaceDrawer(model):
     def portray(g):

examples/advanced/sugarscape_g1mt/run.py

@@ -1,12 +1,13 @@
 import sys
 
 import matplotlib.pyplot as plt
-import mesa
 import networkx as nx
 import pandas as pd
 from sugarscape_g1mt.model import SugarscapeG1mt
 from sugarscape_g1mt.server import server
 
+import mesa
+
 
 # Analysis
 def assess_results(results, single_agent):

examples/advanced/sugarscape_g1mt/sugarscape_g1mt/model.py

@@ -1,7 +1,8 @@
 from pathlib import Path
 
-import mesa
 import numpy as np
+
+import mesa
 from mesa.experimental.cell_space import OrthogonalVonNeumannGrid
 
 from .resource_agents import Resource
@@ -10,23 +11,19 @@
 
 # Helper Functions
 def flatten(list_of_lists):
-    """
-    helper function for model datacollector for trade price
+    """Helper function for model datacollector for trade price
     collapses agent price list into one list
     """
     return [item for sublist in list_of_lists for item in sublist]
 
 
 def geometric_mean(list_of_prices):
-    """
-    find the geometric mean of a list of prices
-    """
+    """Find the geometric mean of a list of prices"""
     return np.exp(np.log(list_of_prices).mean())
 
 
 def get_trade(agent):
-    """
-    For agent reporters in data collector
+    """For agent reporters in data collector
 
     return list of trade partners and None for other agents
     """
@@ -37,9 +34,7 @@ def get_trade(agent):
 
 
 class SugarscapeG1mt(mesa.Model):
-    """
-    Manager class to run Sugarscape with Traders
-    """
+    """Manager class to run Sugarscape with Traders"""
 
     def __init__(
         self,
@@ -125,8 +120,7 @@ def __init__(
             )
 
     def step(self):
-        """
-        Unique step function that does staged activation of sugar and spice
+        """Unique step function that does staged activation of sugar and spice
         and then randomly activates traders
         """
         # step Resource agents

examples/advanced/sugarscape_g1mt/sugarscape_g1mt/resource_agents.py

@@ -2,8 +2,7 @@
 
 
 class Resource(FixedAgent):
-    """
-    Resource:
+    """Resource:
     - contains an amount of sugar and spice
     - grows 1 amount of sugar at each turn
     - grows 1 amount of spice at each turn
@@ -18,8 +17,7 @@ def __init__(self, model, max_sugar, max_spice, cell):
         self.cell = cell
 
     def step(self):
-        """
-        Growth function, adds one unit of sugar and spice each step up to
+        """Growth function, adds one unit of sugar and spice each step up to
         max amount
         """
         self.sugar_amount = min([self.max_sugar, self.sugar_amount + 1])