Matplotlib refactor (#2430)

Author: quaquel

docs/apis/visualization.md

@@ -19,3 +19,22 @@ For a detailed tutorial, please refer to our [Visualization Tutorial](../tutoria
    :undoc-members:
    :show-inheritance:
 ```
+
+
+## Matplotlib-based components
+
+```{eval-rst}
+.. automodule:: mesa.visualization.components.matplotlib
+   :members:
+   :undoc-members:
+   :show-inheritance:
+```
+
+## Altair-based components
+
+```{eval-rst}
+.. automodule:: mesa.visualization.components.altair
+   :members:
+   :undoc-members:
+   :show-inheritance:
+```

docs/migration_guide.md

@@ -268,9 +268,9 @@ from mesa.experimental import SolaraViz
 SolaraViz(model_cls, model_params, agent_portrayal=agent_portrayal)
 
 # new
-from mesa.visualization import SolaraViz, make_space_matplotlib
+from mesa.visualization import SolaraViz, make_space_component
 
-SolaraViz(model, components=[make_space_matplotlib(agent_portrayal)])
+SolaraViz(model, components=[make_space_component(agent_portrayal)])
 ```
 
 #### Plotting "measures"

docs/overview.md

@@ -168,11 +168,13 @@ The results are returned as a list of dictionaries, which can be easily converte
 Mesa now uses a new browser-based visualization system called SolaraViz. This allows for interactive, customizable visualizations of your models. Here's a basic example of how to set up a visualization:
 
 ```python
-from mesa.visualization import SolaraViz, make_space_matplotlib, make_plot_measure
+from mesa.visualization import SolaraViz, make_space_component, make_plot_measure
+
 
 def agent_portrayal(agent):
     return {"color": "blue", "size": 50}
 
+
 model_params = {
     "N": {
         "type": "SliderInt",
@@ -187,7 +189,7 @@ model_params = {
 page = SolaraViz(
     MyModel,
     [
-        make_space_matplotlib(agent_portrayal),
+        make_space_component(agent_portrayal),
         make_plot_measure("mean_age")
     ],
     model_params=model_params