Metrics Plotting

src/paretobench/metrics.py

@@ -20,6 +20,10 @@ class Metric(BaseModel):
     def name(self):
         raise NotImplementedError
 
+    def get_plot_label(self) -> str:
+        """Returns label for y axis of plots with the metric."""
+        raise NotImplementedError
+
     def __call__(self, pop: Population, problem: Union[Problem, str]):
         """
         Evaluate the metric.
@@ -78,6 +82,9 @@ def __call__(self, pop: Population, problem: Union[Problem, str]):
     def name(self):
         return "igd"
 
+    def get_plot_label(self) -> str:
+        return "IGD"
+
 
 class Hypervolume(Metric):
     """
@@ -157,6 +164,9 @@ def __call__(self, pop: Population, problem: Union[Problem, str]):
     def name(self):
         return "hypervolume"
 
+    def get_plot_label(self) -> str:
+        return "Hypervolume"
+
 
 @dataclass
 class EvalMetricsJob:

src/paretobench/plotting/__init__.py

@@ -8,6 +8,7 @@
     history_obj_scatter,
     history_dvar_pairs,
 )
+from .metrics import plot_metric_history
 
 __all__ = [
     "population_dvar_pairs",
@@ -16,4 +17,5 @@
     "history_obj_animation",
     "history_obj_scatter",
     "history_dvar_pairs",
+    "plot_metric_history",
 ]

src/paretobench/plotting/metrics.py

@@ -0,0 +1,57 @@
+import matplotlib.pyplot as plt
+from typing import Literal
+
+from paretobench.containers import History
+from paretobench.metrics import Metric, eval_metrics
+
+
+def plot_metric_history(
+    hist: History,
+    metric: Metric,
+    x_axis: Literal["fevals", "generation"] = "fevals",
+    fig: plt.Figure | None = None,
+    ax: plt.Axes | None = None,
+):
+    """
+    Evaluate and plot evolution of a metric across the populations within a `History` object.
+
+    Parameters
+    ----------
+    hist : History
+        The genetic algorithm history to plot
+    metric : Metric
+        The metric to evaluate and plot
+    x_axis : Literal["fevals", "generation"]
+        What value to use for x-axis in plot
+    fig : plt.Figure | None
+        Matplotlib figure if plotting to user-provided figure (must also specify axis)
+    ax : plt.Axes | None
+        Matplotlib axis to place plot into (must also specify figure)
+
+    Returns
+    -------
+    plt.Figure, plt.Axes
+        The matplotlib figure and axis the data was plotted to
+    """
+    # Calculate the metrics from the history object
+    df = eval_metrics(hist, metric)
+
+    if fig is None or ax is None:
+        fig, ax = plt.subplots()
+
+    # Grab the x values and axis label
+    if x_axis == "fevals":
+        x_vals = df["fevals"]
+        xlabel = "Function Evaluations"
+    elif x_axis == "generation":
+        x_vals = df["pop_idx"]
+        xlabel = "Generation"
+    else:
+        raise ValueError(f"Unrecognized value for `x_axis`: {x_vals}")
+
+    # Plot the data
+    ax.plot(x_vals, df[metric.name])
+    ax.set_xlabel(xlabel)
+    ax.set_ylabel(metric.get_plot_label())
+
+    return fig, ax