fix: auc indicator layout (MAIF#81)

* fix: auc indicator layout

* feat: change main github action install method

* chore: remove requirements.dev.txt

Author: guerinclement

.github/workflows/main.yml

@@ -20,7 +20,7 @@ jobs:
       run: |
         python -m pip install --upgrade pip
         pip install build flake8 pytest
-        if [ -f requirements.dev.txt ]; then pip install -r requirements.dev.txt; fi
+        pip install .[test]
 
     - name: Lint with flake8
       run: |

eurybia/core/smartplotter.py

@@ -710,27 +710,24 @@ def generate_indicator(
         fig_value: float,
         min_gauge: float = 0.5,
         max_gauge: float = 1,
-        height: float | None = 300,
-        width: float | None = 500,
-        title: str | None = "Metric",
-    ) -> plotly.graph_objs._figure.Figure:
-        """Displays an indicator in a colorbar
-
-        Parameters
-        ----------
-        fig_value: float
-            Value to display on figure
-        min_gauge: float, (default: 0.5)
-            range min in gauge display
-        max_gauge: float, (default: 1)
-            range max in gauge display
-        height: str, optional
-            Height of the plot
-        width: str, optional
-            Width of the plot
-        title: str, optional
-            Plot title
+        height: float = 300,
+        width: float = 500,
+        title: str = "Metric",
+        image: bool = False,
+    ) -> plotly.graph_objs._figure.Figure | bytes:
+        """Generate an indicator gauge with a colorbar.
 
+        Args:
+            fig_value (float): Value to display on the gauge.
+            min_gauge (float, optional): Minimum value of the gauge range. Defaults to 0.5.
+            max_gauge (float, optional): Maximum value of the gauge range. Defaults to 1.
+            height (float, optional): Height of the plot. Defaults to 300.
+            width (float, optional): Width of the plot. Defaults to 500.
+            title (str, optional): Title of the plot. Defaults to "Metric".
+            image (bool, optional): If True, returns an image instead of a Plotly Figure. Defaults to False.
+
+        Returns:
+            plotly.graph_objs._figure.Figure | bytes: The generated figure or image.
         """
         color = sns.blend_palette(["green", "yellow", "orange", "red"], 100)
         color = color.as_hex()
@@ -764,4 +761,4 @@ def generate_indicator(
             width=width,
         )
 
-        return fig
+        return fig.to_image() if image else fig

eurybia/report/generation.py

@@ -52,9 +52,9 @@ def _get_index_panel(
         raise RuntimeError("AUC should have been set.")
     # AUC
     auc_block = dr.smartdrift.plot.generate_indicator(
-        fig_value=dr.smartdrift.auc, height=280, width=500, title="Datadrift classifier AUC"
+        fig_value=dr.smartdrift.auc, height=280, width=500, title="Datadrift classifier AUC", image=True
     )
-    auc_indicator = pn.pane.Plotly(auc_block)
+    auc_indicator = pn.pane.PNG(auc_block)
 
     # Jensen-Shannon
     if dr.smartdrift.deployed_model is not None:
@@ -68,8 +68,9 @@ def _get_index_panel(
             title="Jensen Shannon Datadrift",
             min_gauge=0,
             max_gauge=0.2,
+            image=True,
         )
-        js_indicator = pn.pane.Plotly(JS_block)
+        js_indicator = pn.pane.PNG(JS_block)
         indicators = pn.Row(auc_indicator, js_indicator)
 
     else:
@@ -218,9 +219,9 @@ def _get_data_drift_panel(dr: DriftReport) -> pn.Column:
         raise RuntimeError("AUC should have been set.")
 
     auc = dr.smartdrift.plot.generate_indicator(
-        fig_value=dr.smartdrift.auc, height=300, width=500, title="Datadrift classifier AUC"
+        fig_value=dr.smartdrift.auc, height=300, width=500, title="Datadrift classifier AUC", image=True
     )
-    blocks += [pn.pane.Plotly(auc)]
+    blocks += [pn.pane.PNG(auc)]
 
     blocks += [
         pn.pane.Markdown("## Importance of features in data drift"),
@@ -279,8 +280,9 @@ def _get_data_drift_panel(dr: DriftReport) -> pn.Column:
             title="Jensen Shannon Datadrift",
             min_gauge=0,
             max_gauge=0.2,
+            image=True,
         )
-        blocks += [pn.pane.Plotly(js_fig)]
+        blocks += [pn.pane.PNG(js_fig)]
 
     contribution_figures, contribution_labels = dr.display_model_contribution()
 

pyproject.toml

@@ -32,6 +32,7 @@ dependencies = [
     "seaborn>=0.10.1",
     "shapash>=2.0.0",
     "plotly",
+    "kaleido>=0.2.1,<1.0.0",
 ]
 
 [project.optional-dependencies] # Optional