Implementation of matplotlib backend for criterion_plot()

.tools/envs/testenv-linux.yml

@@ -19,6 +19,7 @@ dependencies:
   - numpy >= 2  # run, tests
   - pandas  # run, tests
   - plotly>=6.2  # run, tests
+  - matplotlib  # run, tests
   - pybaum>=0.1.2  # run, tests
   - scipy>=1.2.1  # run, tests
   - sqlalchemy  # run, tests

.tools/envs/testenv-nevergrad.yml

@@ -17,6 +17,7 @@ dependencies:
   - numpy >= 2  # run, tests
   - pandas  # run, tests
   - plotly>=6.2  # run, tests
+  - matplotlib  # run, tests
   - pybaum>=0.1.2  # run, tests
   - scipy>=1.2.1  # run, tests
   - sqlalchemy  # run, tests

.tools/envs/testenv-numpy.yml

@@ -17,6 +17,7 @@ dependencies:
   - cloudpickle  # run, tests
   - joblib  # run, tests
   - plotly>=6.2  # run, tests
+  - matplotlib  # run, tests
   - pybaum>=0.1.2  # run, tests
   - scipy>=1.2.1  # run, tests
   - sqlalchemy  # run, tests

.tools/envs/testenv-others.yml

@@ -17,6 +17,7 @@ dependencies:
   - numpy >= 2  # run, tests
   - pandas  # run, tests
   - plotly>=6.2  # run, tests
+  - matplotlib  # run, tests
   - pybaum>=0.1.2  # run, tests
   - scipy>=1.2.1  # run, tests
   - sqlalchemy  # run, tests

.tools/envs/testenv-pandas.yml

@@ -17,6 +17,7 @@ dependencies:
   - cloudpickle  # run, tests
   - joblib  # run, tests
   - plotly>=6.2  # run, tests
+  - matplotlib  # run, tests
   - pybaum>=0.1.2  # run, tests
   - scipy>=1.2.1  # run, tests
   - sqlalchemy  # run, tests

.tools/envs/testenv-plotly.yml

@@ -17,6 +17,7 @@ dependencies:
   - joblib  # run, tests
   - numpy >= 2  # run, tests
   - pandas  # run, tests
+  - matplotlib  # run, tests
   - pybaum>=0.1.2  # run, tests
   - scipy>=1.2.1  # run, tests
   - sqlalchemy  # run, tests

environment.yml

@@ -21,6 +21,7 @@ dependencies:
   - numpy >= 2  # run, tests
   - pandas  # run, tests
   - plotly>=6.2  # run, tests
+  - matplotlib  # run, tests
   - pybaum>=0.1.2  # run, tests
   - scipy>=1.2.1  # run, tests
   - sqlalchemy  # run, tests

pyproject.toml

@@ -11,6 +11,7 @@ dependencies = [
     "numpy",
     "pandas",
     "plotly",
+    "matplotlib",
     "pybaum>=0.1.2",
     "scipy>=1.2.1",
     "sqlalchemy>=1.3",
@@ -290,6 +291,7 @@ module = [
 
     "optimagic.visualization",
     "optimagic.visualization.convergence_plot",
+    "optimagic.visualization.backends",
     "optimagic.visualization.deviation_plot",
     "optimagic.visualization.history_plots",
     "optimagic.visualization.plotting_utilities",
@@ -346,6 +348,8 @@ module = [
     "plotly.graph_objects",
     "plotly.express",
     "plotly.subplots",
+    "matplotlib",
+    "matplotlib.pyplot",
     "cyipopt",
     "nlopt",
     "bokeh",

src/optimagic/visualization/backends.py

@@ -0,0 +1,107 @@
+import abc
+from typing import Any
+
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+import plotly.express as px
+import plotly.graph_objects as go
+
+from optimagic.visualization.plotting_utilities import LineData
+
+
+class PlotBackend(abc.ABC):
+    default_template: str
+    default_palette: list
+
+    @abc.abstractmethod
+    def __init__(self, template: str | None):
+        if template is None:
+            template = self.default_template
+
+        self.template = template
+        self.figure: Any = None
+
+    @abc.abstractmethod
+    def add_lines(self, lines: list[LineData]) -> None:
+        pass
+
+    @abc.abstractmethod
+    def set_labels(self, xlabel: str | None = None, ylabel: str | None = None) -> None:
+        pass
+
+    @abc.abstractmethod
+    def set_legend_props(self, legend_props: dict[str, Any]) -> None:
+        pass
+
+
+class PlotlyBackend(PlotBackend):
+    default_template: str = "simple_white"
+    default_palette: list = px.colors.qualitative.Set2
+
+    def __init__(self, template: str | None):
+        super().__init__(template)
+        self._fig = go.Figure()
+        self._fig.update_layout(template=self.template)
+        self.figure = self._fig
+
+    def add_lines(self, lines: list[LineData]) -> None:
+        for line in lines:
+            trace = go.Scatter(
+                x=line.x,
+                y=line.y,
+                name=line.name,
+                mode="lines",
+                line_color=line.color,
+                showlegend=line.show_in_legend,
+                connectgaps=True,
+            )
+            self._fig.add_trace(trace)
+
+    def set_labels(self, xlabel: str | None = None, ylabel: str | None = None) -> None:
+        self._fig.update_layout(xaxis_title_text=xlabel, yaxis_title_text=ylabel)
+
+    def set_legend_props(self, legend_props: dict[str, Any]) -> None:
+        self._fig.update_layout(legend=legend_props)
+
+
+class MatplotlibBackend(PlotBackend):
+    default_template: str = "default"
+    default_palette: list = list(mpl.colormaps["Set2"].colors)
+
+    def __init__(self, template: str | None):
+        super().__init__(template)
+        plt.style.use(self.template)
+        self._fig, self._ax = plt.subplots()
+        self.figure = self._fig
+
+    def add_lines(self, lines: list[LineData]) -> None:
+        for line in lines:
+            self._ax.plot(
+                line.x,
+                line.y,
+                color=line.color,
+                label=line.name if line.show_in_legend else None,
+            )
+
+    def set_labels(self, xlabel: str | None = None, ylabel: str | None = None) -> None:
+        self._ax.set(xlabel=xlabel, ylabel=ylabel)
+
+    def set_legend_props(self, legend_props: dict[str, Any]) -> None:
+        self._ax.legend(**legend_props)
+
+
+PLOT_BACKEND_CLASSES = {
+    "plotly": PlotlyBackend,
+    "matplotlib": MatplotlibBackend,
+}
+
+
+def get_plot_backend_class(backend_name: str) -> type[PlotBackend]:
+    if backend_name not in PLOT_BACKEND_CLASSES:
+        msg = (
+            f"Invalid backend name '{backend_name}'. "
+            f"Supported backends are: {', '.join(PLOT_BACKEND_CLASSES.keys())}."
+        )
+        raise ValueError(msg)
+
+    return PLOT_BACKEND_CLASSES[backend_name]

src/optimagic/visualization/history_plots.py

@@ -8,36 +8,51 @@
 import plotly.graph_objects as go
 from pybaum import leaf_names, tree_flatten, tree_just_flatten, tree_unflatten
 
-from optimagic.config import PLOTLY_PALETTE, PLOTLY_TEMPLATE
+from optimagic.config import PLOTLY_TEMPLATE
 from optimagic.logging.logger import LogReader, SQLiteLogOptions
 from optimagic.optimization.algorithm import Algorithm
 from optimagic.optimization.history import History
 from optimagic.optimization.optimize_result import OptimizeResult
 from optimagic.parameters.tree_registry import get_registry
 from optimagic.typing import IterationHistory, PyTree
+from optimagic.visualization.backends import get_plot_backend_class
+from optimagic.visualization.plotting_utilities import LineData, get_palette_cycle
 
-OptimizeResultOrPath = OptimizeResult | str | Path
+BACKEND_TO_CRITERION_PLOT_LEGEND_PROPS: dict[str, dict[str, Any]] = {
+    "plotly": {
+        "yanchor": "top",
+        "xanchor": "right",
+        "y": 0.95,
+        "x": 0.95,
+    },
+    "matplotlib": {
+        "loc": "upper right",
+    },
+}
+
+
+ResultOrPath = OptimizeResult | str | Path
 
 
 def criterion_plot(
-    results: OptimizeResultOrPath
-    | list[OptimizeResultOrPath]
-    | dict[str, OptimizeResultOrPath],
+    results: ResultOrPath | list[ResultOrPath] | dict[str, ResultOrPath],
     names: list[str] | str | None = None,
     max_evaluations: int | None = None,
-    template: str = PLOTLY_TEMPLATE,
-    palette: list[str] | str = PLOTLY_PALETTE,
+    backend: str = "plotly",
+    template: str | None = None,
+    palette: list[str] | str | None = None,
     stack_multistart: bool = False,
     monotone: bool = False,
     show_exploration: bool = False,
-) -> go.Figure:
+) -> Any:
     """Plot the criterion history of an optimization.
 
     Args:
         results: A (list or dict of) optimization results with collected history.
             If dict, then the key is used as the name in a legend.
         names: Names corresponding to res or entries in res.
         max_evaluations: Clip the criterion history after that many entries.
+        backend: The backend to use for plotting. Default is "plotly".
         template: The template for the figure. Default is "plotly_white".
         palette: The coloring palette for traces. Default is "qualitative.Set2".
         stack_multistart: Whether to combine multistart histories into a single history.
@@ -51,12 +66,17 @@ def criterion_plot(
         The figure object containing the criterion plot.
 
     """
+    # ==================================================================================
+    # Get Plot Backend class
+
+    plot_cls = get_plot_backend_class(backend)
+
     # ==================================================================================
     # Process inputs
 
-    if not isinstance(palette, list):
-        palette = [palette]
-    palette_cycle = itertools.cycle(palette)
+    if palette is None:
+        palette = plot_cls.default_palette
+    palette_cycle = get_palette_cycle(palette)
 
     dict_of_optimize_results_or_paths = _harmonize_inputs_to_dict(results, names)
 
@@ -78,21 +98,19 @@ def criterion_plot(
     )
 
     # ==================================================================================
-    # Generate the plotly figure
+    # Generate the figure
 
-    plot_config = PlotConfig(
-        template=template,
-        legend={"yanchor": "top", "xanchor": "right", "y": 0.95, "x": 0.95},
-    )
+    plot = plot_cls(template)
 
-    fig = _plotly_line_plot(lines + multistart_lines, plot_config)
-    return fig
+    plot.add_lines(lines + multistart_lines)
+    plot.set_labels(xlabel="No. of criterion evaluations", ylabel="Criterion value")
+    plot.set_legend_props(BACKEND_TO_CRITERION_PLOT_LEGEND_PROPS[backend])
+
+    return plot.figure
 
 
 def _harmonize_inputs_to_dict(
-    results: OptimizeResultOrPath
-    | list[OptimizeResultOrPath]
-    | dict[str, OptimizeResultOrPath],
+    results: ResultOrPath | list[ResultOrPath] | dict[str, ResultOrPath],
     names: list[str] | str | None,
 ) -> dict[str, OptimizeResult | str | Path]:
     """Convert all valid inputs for results and names to dict[str, OptimizeResult]."""
@@ -462,26 +480,6 @@ def _get_stacked_local_histories(
     )
 
 
-@dataclass(frozen=True)
-class LineData:
-    """Data of a single line.
-
-    Attributes:
-        x: The x-coordinates of the points.
-        y: The y-coordinates of the points.
-        color: The color of the line. Default is None.
-        name: The name of the line. Default is None.
-        show_in_legend: Whether to show the line in the legend. Default is True.
-
-    """
-
-    x: np.ndarray
-    y: np.ndarray
-    color: str | None = None
-    name: str | None = None
-    show_in_legend: bool = True
-
-
 def _extract_criterion_plot_lines(
     data: list[_PlottingMultistartHistory],
     max_evaluations: int | None,
@@ -543,69 +541,13 @@ def _extract_criterion_plot_lines(
         if max_evaluations is not None and len(history) > max_evaluations:
             history = history[:max_evaluations]
 
-        _color = next(palette_cycle)
-        if not isinstance(_color, str):
-            msg = "highlight_palette needs to be a string or list of strings, but its "
-            f"entry is of type {type(_color)}."
-            raise TypeError(msg)
-
         line_data = LineData(
             x=np.arange(len(history)),
             y=history,
-            color=_color,
+            color=next(palette_cycle),
             name="best result" if plot_multistart else _data.name,
             show_in_legend=not plot_multistart,
         )
         lines.append(line_data)
 
     return lines, multistart_lines
-
-
-@dataclass(frozen=True)
-class PlotConfig:
-    """Configuration settings for figure.
-
-    Attributes:
-        template: The template for the figure.
-        legend: Configuration for the legend.
-
-    """
-
-    template: str
-    legend: dict[str, Any]
-
-
-def _plotly_line_plot(lines: list[LineData], plot_config: PlotConfig) -> go.Figure:
-    """Create a plotly line plot from the given lines and plot configuration.
-
-    Args:
-        lines: Data for lines to be plotted.
-        plot_config: Configuration for the plot.
-
-    Returns:
-        The figure object containing the lines.
-
-    """
-
-    fig = go.Figure()
-
-    for line in lines:
-        trace = go.Scatter(
-            x=line.x,
-            y=line.y,
-            name=line.name,
-            mode="lines",
-            line_color=line.color,
-            showlegend=line.show_in_legend,
-            connectgaps=True,
-        )
-        fig.add_trace(trace)
-
-    fig.update_layout(
-        template=plot_config.template,
-        xaxis_title_text="No. of criterion evaluations",
-        yaxis_title_text="Criterion value",
-        legend=plot_config.legend,
-    )
-
-    return fig