Implementation of backend plotting for profile_plot (#645)

Author: r3kste

docs/source/how_to/how_to_benchmarking.ipynb

@@ -135,6 +135,18 @@
    "cell_type": "markdown",
    "id": "10",
    "metadata": {},
+   "source": [
+    ":::{note}\n",
+    "\n",
+    "For details on using other plotting backends, see [How to change the plotting backend](how_to_change_plotting_backend.ipynb).\n",
+    "\n",
+    ":::"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "11",
+   "metadata": {},
    "source": [
     "The x axis shows runtime per problem. The y axis shows the share of problems each algorithm solved within that runtime. Thus, higher and further to the left values are desirable. Higher means more problems were solved and further to the left means, the algorithm found the solutions earlier. \n",
     "\n",
@@ -150,7 +162,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "11",
+   "id": "12",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -167,7 +179,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "12",
+   "id": "13",
    "metadata": {},
    "source": [
     "## 4b. Convergence plots\n",
@@ -178,7 +190,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "13",
+   "id": "14",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -194,7 +206,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "14",
+   "id": "15",
    "metadata": {},
    "source": [
     "The further to the left and the lower the curve of an algorithm, the better that algorithm performed.\n",
@@ -205,7 +217,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "15",
+   "id": "16",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -223,7 +235,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "16",
+   "id": "17",
    "metadata": {},
    "source": [
     "## 5a. Convergence report\n",
@@ -235,7 +247,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "17",
+   "id": "18",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -251,7 +263,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "18",
+   "id": "19",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -260,18 +272,18 @@
   },
   {
    "cell_type": "markdown",
-   "id": "19",
+   "id": "20",
    "metadata": {},
    "source": [
-    "## 5b. Rank report¶\n",
+    "## 5b. Rank report\n",
     "\n",
     "The **Rank Report** shows the ranks of the algorithms for each problem; where 0 means the algorithm was the fastest on a given benchmark problem, 1 means it was the second fastest and so on. If an algorithm did not converge on a problem, the value is \"failed\". If an algorithm did encounter an error during optimization, the value is \"error\"."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "20",
+   "id": "21",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -288,7 +300,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "21",
+   "id": "22",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -297,18 +309,18 @@
   },
   {
    "cell_type": "markdown",
-   "id": "22",
+   "id": "23",
    "metadata": {},
    "source": [
-    "## 5b. Traceback report¶\n",
+    "## 5b. Traceback report\n",
     "\n",
     "The **Traceback Report** shows the tracebacks returned by the optimizers if they encountered an error during optimization. The resulting ```pd.DataFrame``` is empty if none of the optimizers terminated with an error, as in the example below."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "23",
+   "id": "24",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -318,7 +330,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "24",
+   "id": "25",
    "metadata": {},
    "outputs": [],
    "source": [

src/optimagic/visualization/backends.py

@@ -23,6 +23,8 @@ def __call__(
         height: int | None,
         width: int | None,
         legend_properties: dict[str, Any] | None,
+        margin_properties: dict[str, Any] | None,
+        horizontal_line: float | None,
     ) -> Any: ...
 
 
@@ -36,12 +38,32 @@ def _line_plot_plotly(
     height: int | None,
     width: int | None,
     legend_properties: dict[str, Any] | None,
+    margin_properties: dict[str, Any] | None,
+    horizontal_line: float | None,
 ) -> go.Figure:
     if template is None:
         template = "simple_white"
 
     fig = go.Figure()
 
+    fig.update_layout(
+        title=title,
+        xaxis_title=xlabel.format(linebreak="<br>") if xlabel else None,
+        yaxis_title=ylabel,
+        template=template,
+        height=height,
+        width=width,
+        legend=legend_properties,
+        margin=margin_properties,
+    )
+
+    if horizontal_line is not None:
+        fig.add_hline(
+            y=horizontal_line,
+            line_width=fig.layout.yaxis.linewidth or 1,
+            opacity=1.0,
+        )
+
     for line in lines:
         trace = go.Scatter(
             x=line.x,
@@ -53,18 +75,6 @@ def _line_plot_plotly(
         )
         fig.add_trace(trace)
 
-    fig.update_layout(
-        title=title,
-        xaxis_title=xlabel,
-        yaxis_title=ylabel,
-        template=template,
-        height=height,
-        width=width,
-    )
-
-    if legend_properties:
-        fig.update_layout(legend=legend_properties)
-
     return fig
 
 
@@ -78,6 +88,8 @@ def _line_plot_matplotlib(
     height: int | None,
     width: int | None,
     legend_properties: dict[str, Any] | None,
+    margin_properties: dict[str, Any] | None,
+    horizontal_line: float | None,
 ) -> "plt.Axes":
     import matplotlib.pyplot as plt
 
@@ -93,7 +105,17 @@ def _line_plot_matplotlib(
         template = "default"
 
     with plt.style.context(template):
-        fig, ax = plt.subplots(figsize=(width, height) if width and height else None)
+        px = 1 / plt.rcParams["figure.dpi"]  # pixel in inches
+        fig, ax = plt.subplots(
+            figsize=(width * px, height * px) if width and height else None
+        )
+
+        if horizontal_line is not None:
+            ax.axhline(
+                y=horizontal_line,
+                color=ax.spines["left"].get_edgecolor() or "gray",
+                linewidth=ax.spines["left"].get_linewidth() or 1.0,
+            )
 
         for line in lines:
             ax.plot(
@@ -103,9 +125,17 @@ def _line_plot_matplotlib(
                 color=line.color,
             )
 
-        ax.set(title=title, xlabel=xlabel, ylabel=ylabel)
-        if legend_properties:
-            ax.legend(**legend_properties)
+        ax.set(
+            title=title,
+            xlabel=xlabel.format(linebreak="\n") if xlabel else None,
+            ylabel=ylabel,
+        )
+
+        if legend_properties is None:
+            legend_properties = {}
+        ax.legend(**legend_properties)
+
+        fig.tight_layout()
 
     return ax
 
@@ -129,6 +159,8 @@ def line_plot(
     height: int | None = None,
     width: int | None = None,
     legend_properties: dict[str, Any] | None = None,
+    margin_properties: dict[str, Any] | None = None,
+    horizontal_line: float | None = None,
 ) -> Any:
     """Create a line plot corresponding to the specified backend.
 
@@ -144,6 +176,9 @@ def line_plot(
         height: Height of the plot (in pixels).
         width: Width of the plot (in pixels).
         legend_properties: Backend-specific properties for the legend.
+        margin_properties: Backend-specific properties for the plot margins.
+        horizontal_line: If provided, a horizontal line is drawn at the specified
+            y-value.
 
     Returns:
         A figure object corresponding to the specified backend.
@@ -178,6 +213,8 @@ def line_plot(
         height=height,
         width=width,
         legend_properties=legend_properties,
+        margin_properties=margin_properties,
+        horizontal_line=horizontal_line,
     )
 
     return fig