Fix summarizer to include non-paid channels in contribution insights.

PiperOrigin-RevId: 840476698

Author: yeonjaepark

meridian/analysis/summarizer.py

@@ -318,7 +318,7 @@ def _create_outcome_contrib_card_html(
         chart_json=media_summary.plot_contribution_waterfall_chart().to_json(),
     )
     lead_channels = self._get_sorted_posterior_mean_metrics_df(
-        media_summary, [c.INCREMENTAL_OUTCOME]
+        media_summary, [c.INCREMENTAL_OUTCOME], include_non_paid_channels=True
     )[c.CHANNEL][:2]
     formatted_channels = [channel.title() for channel in lead_channels]
 
@@ -358,9 +358,14 @@ def _get_sorted_posterior_mean_metrics_df(
       media_summary: visualizer.MediaSummary,
       metrics: Sequence[str],
       ascending: bool = False,
+      include_non_paid_channels: bool = False,
   ) -> pd.DataFrame:
+    if include_non_paid_channels:
+      summary_metrics = media_summary.get_all_summary_metrics()
+    else:
+      summary_metrics = media_summary.get_paid_summary_metrics()
     return (
-        media_summary.get_paid_summary_metrics()[metrics]
+        summary_metrics[metrics]
         .sel(distribution=c.POSTERIOR, metric=c.MEAN)
         .drop_sel(channel=c.ALL_CHANNELS)
         .to_dataframe()

meridian/analysis/summarizer_test.py

@@ -162,6 +162,10 @@ def _stub_for_insights(self):
     self.media_summary.get_paid_summary_metrics = mock.MagicMock(
         return_value=self.media_metrics
     )
+    self.all_metrics = test_utils.generate_all_summary_metrics()
+    self.media_summary.get_all_summary_metrics = mock.MagicMock(
+        return_value=self.all_metrics
+    )
 
     frequency_data = test_utils.generate_optimal_frequency_data(
         channel_prefix='rf_ch', num_channels=2
@@ -974,12 +978,12 @@ def test_channel_contrib_card_plotters_called(self):
     )
 
   def test_channel_contrib_card_insights(self):
-    self.media_metrics[c.INCREMENTAL_OUTCOME].loc[{
+    self.all_metrics[c.INCREMENTAL_OUTCOME].loc[{
         c.CHANNEL: 'rf_ch_1',
         c.DISTRIBUTION: c.POSTERIOR,
         c.METRIC: c.MEAN,
     }] = 999999  # largest outcome
-    self.media_metrics[c.INCREMENTAL_OUTCOME].loc[{
+    self.all_metrics[c.INCREMENTAL_OUTCOME].loc[{
         c.CHANNEL: 'ch_0',
         c.DISTRIBUTION: c.POSTERIOR,
         c.METRIC: c.MEAN,

meridian/analysis/visualizer.py

@@ -1450,17 +1450,15 @@ def get_paid_summary_metrics(
 
     Args:
       aggregate_times: If `True`, aggregates the metrics across all time
-        periods.  If `False`, returns time-varying metrics.
+        periods. If `False`, returns time-varying metrics.
 
     Returns:
       An `xarray.Dataset` containing the following:
         - **Coordinates:** `channel`, `metric` (`mean`, `median`, `ci_lo`,
-        `ci_hi`),
-          `distribution` (`prior`, `posterior`)
+          `ci_hi`), `distribution` (`prior`, `posterior`)
         - **Data variables:** `impressions`, `pct_of_impressions`, `spend`,
           `pct_of_spend`, `CPM`, `incremental_outcome`, `pct_of_contribution`,
-          `roi`,
-          `effectiveness`, `mroi`.
+          `roi`, `effectiveness`, `mroi`.
     """
     return self._analyzer.summary_metrics(
         selected_times=self._selected_times,