refactor: Move Matplotlib-specific Solara components to separate file

mesa/experimental/components/matplotlib.py

@@ -0,0 +1,114 @@
+from typing import Optional
+
+import networkx as nx
+import solara
+from matplotlib.figure import Figure
+from matplotlib.ticker import MaxNLocator
+
+import mesa
+
+
+@solara.component
+def SpaceMatplotlib(model, agent_portrayal, dependencies: Optional[list[any]] = None):
+    space_fig = Figure()
+    space_ax = space_fig.subplots()
+    space = getattr(model, "grid", None)
+    if space is None:
+        # Sometimes the space is defined as model.space instead of model.grid
+        space = model.space
+    if isinstance(space, mesa.space.NetworkGrid):
+        _draw_network_grid(space, space_ax, agent_portrayal)
+    elif isinstance(space, mesa.space.ContinuousSpace):
+        _draw_continuous_space(space, space_ax, agent_portrayal)
+    else:
+        _draw_grid(space, space_ax, agent_portrayal)
+    space_ax.set_axis_off()
+    solara.FigureMatplotlib(space_fig, format="png", dependencies=dependencies)
+
+
+def _draw_grid(space, space_ax, agent_portrayal):
+    def portray(g):
+        x = []
+        y = []
+        s = []  # size
+        c = []  # color
+        for i in range(g.width):
+            for j in range(g.height):
+                content = g._grid[i][j]
+                if not content:
+                    continue
+                if not hasattr(content, "__iter__"):
+                    # Is a single grid
+                    content = [content]
+                for agent in content:
+                    data = agent_portrayal(agent)
+                    x.append(i)
+                    y.append(j)
+                    if "size" in data:
+                        s.append(data["size"])
+                    if "color" in data:
+                        c.append(data["color"])
+        out = {"x": x, "y": y}
+        if len(s) > 0:
+            out["s"] = s
+        if len(c) > 0:
+            out["c"] = c
+        return out
+
+    space_ax.scatter(**portray(space))
+
+
+def _draw_network_grid(space, space_ax, agent_portrayal):
+    graph = space.G
+    pos = nx.spring_layout(graph, seed=0)
+    nx.draw(
+        graph,
+        ax=space_ax,
+        pos=pos,
+        **agent_portrayal(graph),
+    )
+
+
+def _draw_continuous_space(space, space_ax, agent_portrayal):
+    def portray(space):
+        x = []
+        y = []
+        s = []  # size
+        c = []  # color
+        for agent in space._agent_to_index:
+            data = agent_portrayal(agent)
+            _x, _y = agent.pos
+            x.append(_x)
+            y.append(_y)
+            if "size" in data:
+                s.append(data["size"])
+            if "color" in data:
+                c.append(data["color"])
+        out = {"x": x, "y": y}
+        if len(s) > 0:
+            out["s"] = s
+        if len(c) > 0:
+            out["c"] = c
+        return out
+
+    space_ax.scatter(**portray(space))
+
+
+def make_plot(model, measure):
+    fig = Figure()
+    ax = fig.subplots()
+    df = model.datacollector.get_model_vars_dataframe()
+    if isinstance(measure, str):
+        ax.plot(df.loc[:, measure])
+        ax.set_ylabel(measure)
+    elif isinstance(measure, dict):
+        for m, color in measure.items():
+            ax.plot(df.loc[:, m], label=m, color=color)
+        fig.legend()
+    elif isinstance(measure, (list, tuple)):
+        for m in measure:
+            ax.plot(df.loc[:, m], label=m)
+        fig.legend()
+    # Set integer x axis
+    ax.xaxis.set_major_locator(MaxNLocator(integer=True))
+    solara.FigureMatplotlib(fig)

mesa/experimental/jupyter_viz.py

@@ -3,14 +3,11 @@
 from typing import Optional
 
 import matplotlib.pyplot as plt
-import networkx as nx
 import reacton.ipywidgets as widgets
 import solara
-from matplotlib.figure import Figure
-from matplotlib.ticker import MaxNLocator
 from solara.alias import rv
 
-import mesa
+import mesa.experimental.components.matplotlib as components_matplotlib
 
 # Avoid interactive backend
 plt.switch_backend("agg")
@@ -72,7 +69,7 @@ def ColorCard(color, layout_type):
                 rv.CardTitle(children=["Space"])
                 if space_drawer == "default":
                     # draw with the default implementation
-                    SpaceMatplotlib(
+                    components_matplotlib.SpaceMatplotlib(
                         model, agent_portrayal, dependencies=[current_step.value]
                     )
                 elif space_drawer:
@@ -85,7 +82,7 @@ def ColorCard(color, layout_type):
                     # Is a custom object
                     measure(model)
                 else:
-                    make_plot(model, measure)
+                    components_matplotlib.make_plot(model, measure)
         return main
 
     # 3. Set up UI
@@ -106,7 +103,7 @@ def render_in_jupyter():
             # 4. Space
             if space_drawer == "default":
                 # draw with the default implementation
-                SpaceMatplotlib(
+                components_matplotlib.SpaceMatplotlib(
                     model, agent_portrayal, dependencies=[current_step.value]
                 )
             elif space_drawer:
@@ -121,7 +118,7 @@ def render_in_jupyter():
                     # Is a custom object
                     measure(model)
                 else:
-                    make_plot(model, measure)
+                    components_matplotlib.make_plot(model, measure)
 
     def render_in_browser():
         # if space drawer is disabled, do not include it
@@ -182,7 +179,7 @@ def on_value_play(change):
     def do_step():
         model.step()
         previous_step.value = current_step.value
-        current_step.value = model.schedule.steps
+        current_step.value += 1
 
     def do_play():
         model.running = True
@@ -316,112 +313,6 @@ def change_handler(value, name=name):
             raise ValueError(f"{input_type} is not a supported input type")
 
 
-@solara.component
-def SpaceMatplotlib(model, agent_portrayal, dependencies: Optional[list[any]] = None):
-    space_fig = Figure()
-    space_ax = space_fig.subplots()
-    space = getattr(model, "grid", None)
-    if space is None:
-        # Sometimes the space is defined as model.space instead of model.grid
-        space = model.space
-    if isinstance(space, mesa.space.NetworkGrid):
-        _draw_network_grid(space, space_ax, agent_portrayal)
-    elif isinstance(space, mesa.space.ContinuousSpace):
-        _draw_continuous_space(space, space_ax, agent_portrayal)
-    else:
-        _draw_grid(space, space_ax, agent_portrayal)
-    space_ax.set_axis_off()
-    solara.FigureMatplotlib(space_fig, format="png", dependencies=dependencies)
-
-
-def _draw_grid(space, space_ax, agent_portrayal):
-    def portray(g):
-        x = []
-        y = []
-        s = []  # size
-        c = []  # color
-        for i in range(g.width):
-            for j in range(g.height):
-                content = g._grid[i][j]
-                if not content:
-                    continue
-                if not hasattr(content, "__iter__"):
-                    # Is a single grid
-                    content = [content]
-                for agent in content:
-                    data = agent_portrayal(agent)
-                    x.append(i)
-                    y.append(j)
-                    if "size" in data:
-                        s.append(data["size"])
-                    if "color" in data:
-                        c.append(data["color"])
-        out = {"x": x, "y": y}
-        if len(s) > 0:
-            out["s"] = s
-        if len(c) > 0:
-            out["c"] = c
-        return out
-
-    space_ax.scatter(**portray(space))
-
-
-def _draw_network_grid(space, space_ax, agent_portrayal):
-    graph = space.G
-    pos = nx.spring_layout(graph, seed=0)
-    nx.draw(
-        graph,
-        ax=space_ax,
-        pos=pos,
-        **agent_portrayal(graph),
-    )
-
-
-def _draw_continuous_space(space, space_ax, agent_portrayal):
-    def portray(space):
-        x = []
-        y = []
-        s = []  # size
-        c = []  # color
-        for agent in space._agent_to_index:
-            data = agent_portrayal(agent)
-            _x, _y = agent.pos
-            x.append(_x)
-            y.append(_y)
-            if "size" in data:
-                s.append(data["size"])
-            if "color" in data:
-                c.append(data["color"])
-        out = {"x": x, "y": y}
-        if len(s) > 0:
-            out["s"] = s
-        if len(c) > 0:
-            out["c"] = c
-        return out
-
-    space_ax.scatter(**portray(space))
-
-
-def make_plot(model, measure):
-    fig = Figure()
-    ax = fig.subplots()
-    df = model.datacollector.get_model_vars_dataframe()
-    if isinstance(measure, str):
-        ax.plot(df.loc[:, measure])
-        ax.set_ylabel(measure)
-    elif isinstance(measure, dict):
-        for m, color in measure.items():
-            ax.plot(df.loc[:, m], label=m, color=color)
-        fig.legend()
-    elif isinstance(measure, (list, tuple)):
-        for m in measure:
-            ax.plot(df.loc[:, m], label=m)
-        fig.legend()
-    # Set integer x axis
-    ax.xaxis.set_major_locator(MaxNLocator(integer=True))
-    solara.FigureMatplotlib(fig)
-
-
 def make_text(renderer):
     def function(model):
         solara.Markdown(renderer(model))

tests/test_jupyter_viz.py

@@ -82,7 +82,7 @@ def Test(user_params):
 
 
 class TestJupyterViz(unittest.TestCase):
-    @patch("mesa.experimental.jupyter_viz.SpaceMatplotlib")
+    @patch("mesa.experimental.components.matplotlib.SpaceMatplotlib")
     def test_call_space_drawer(self, mock_space_matplotlib):
         mock_model_class = Mock()
         agent_portrayal = {