updated for chore

.gitignore

@@ -26,3 +26,7 @@ buildDockerImage.yml
 process-bigraph
 bigraph-schema
 bigraph-builder
+3.10/
+Miniforge3-Darwin-arm64.sh
+*.cpython-310.pyc
+

biosimulator_processes/processes/copasi_process.py

@@ -238,6 +238,21 @@ def update(self, inputs, interval):
         return results
 
 
+def test_process_from_document():
+    import json
+    # ensure that the process is registered
+    CORE.process_registry.register('biosimulator_processes.processes.copasi_process.CopasiProcess', CopasiProcess)
+
+    # read the document from local file:
+    five_process_fp = 'notebooks/out/five_process_composite.json'
+    with open(five_process_fp, 'r') as fp:
+        instance = json.load(fp)
+
+    workflow = Composite(config={
+        'state': instance
+    })
+
+
 def test_process():
     CORE.process_registry.register('biosimulator_processes.processes.copasi_process.CopasiProcess', CopasiProcess)
     instance = {

biosimulator_processes/steps/viz.py

@@ -0,0 +1,79 @@
+from typing import Tuple, Callable
+from dataclasses import dataclass
+import numpy as np
+import matplotlib.pyplot as plt
+from matplotlib.animation import FuncAnimation
+from process_bigraph.composite import Step
+
+
+@dataclass
+class PlotLabelConfig:
+    title: str
+    x_label: str
+    y_label: str
+
+
+class ResultsAnimation:
+    def __init__(self,
+                 x_data: np.array,
+                 y_data: np.array,
+                 plot_type_func: Callable,
+                 plot_label_config: PlotLabelConfig,
+                 **config):
+        self.x_data = x_data
+        self.y_data = y_data
+        self.plot_type_func = plot_type_func
+        self.plot_label_config = plot_label_config
+        self.config = config
+
+    def _set_axis_limits(self, ax_limit_func, data):
+        return ax_limit_func(data.min(), data.max())
+
+    def _prepare_animation(self, t):
+        plt.cla()
+        self.plot_type_func(
+            self.x_data,
+            self.y_data,
+            color=self.config.get('color', 'blue')
+        )
+
+        self._set_axis_limits(plt.xlim, self.x_data)
+        self._set_axis_limits(plt.ylim, self.y_data)
+        plt.axhline(0, color='grey', lw=0.5)
+        plt.axvline(0, color='grey', lw=0.5)
+        plt.title(self.plot_label_config.title)
+        plt.xlabel(self.plot_label_config.x_label)
+        plt.ylabel(self.plot_label_config.y_label)
+
+    def _create_animation_components(self) -> Tuple:
+        """
+        Creates a matplotlib subplot setup for animation.
+
+        Returns:
+            Tuple[matplotlib.figure.Figure, matplotlib.axes.Axes]: A tuple containing the figure and axes objects.
+        """
+        plt.rcParams["animation.html"] = "jshtml"
+        plt.rcParams['figure.dpi'] = 150  # TODO: add this to config
+        plt.ioff()
+        fig, ax = plt.subplots()
+        return fig, ax
+
+    def run(self, num_frames: int):
+        """
+        Creates and runs the animation.
+
+        Args:
+            num_frames (int): Number of frames to animate
+
+        Returns:
+            matplotlib.animation.FuncAnimation: The animation object.
+        """
+        fig, ax = self._create_animation_components()
+        return FuncAnimation(fig, self._prepare_animation, frames=num_frames)
+
+
+# TODO: Create plotting step for this
+
+
+class Plotter2d(Step):
+    pass