Merge pull request #498 from Proteobench/fix-key-plot_metric

Fixes mean plotting
Proteobench · Dec 16, 2024 · 072a0af · 072a0af
2 parents 2c535e4 + 1397bb1
commit 072a0af
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Showing 4 changed files with 16 additions and 12 deletions.
diff --git a/proteobench/datapoint/quant_datapoint.py b/proteobench/datapoint/quant_datapoint.py
@@ -13,7 +13,7 @@
 import proteobench
 
 
-def filter_df_numquant_median_abs_epsilon(row: Dict[str, Any], min_quant: int = 3) -> float | None:
+def filter_df_numquant_epsilon(row: Dict[str, Any], min_quant: int = 3, metric: str = "median") -> float | None:
     """
     Extract the 'median_abs_epsilon' value from a row (assumed to be a dictionary).
 
@@ -27,7 +27,7 @@ def filter_df_numquant_median_abs_epsilon(row: Dict[str, Any], min_quant: int =
     if isinstance(list(row.keys())[0], str):
         min_quant = str(min_quant)
     if isinstance(row, dict) and min_quant in row and isinstance(row[min_quant], dict):
-        return row[min_quant].get("median_abs_epsilon")
+        return row[min_quant].get("{}_abs_epsilon".format(metric))
 
     return None
 

diff --git a/proteobench/modules/quant/quant_base/quant_base_module.py b/proteobench/modules/quant/quant_base/quant_base_module.py
@@ -12,7 +12,7 @@
 
 from proteobench.datapoint.quant_datapoint import (
     Datapoint,
-    filter_df_numquant_median_abs_epsilon,
+    filter_df_numquant_epsilon,
     filter_df_numquant_nr_prec,
 )
 from proteobench.github.gh import GithubProteobotRepo
@@ -185,7 +185,12 @@ def filter_data_point(all_datapoints: pd.DataFrame, default_val_slider: int = 3)
             A DataFrame containing the filtered data points.
         """
         all_datapoints["median_abs_epsilon"] = [
-            filter_df_numquant_median_abs_epsilon(v, min_quant=default_val_slider) for v in all_datapoints["results"]
+            filter_df_numquant_epsilon(v, min_quant=default_val_slider) for v in all_datapoints["results"]
+        ]
+
+        all_datapoints["mean_abs_epsilon"] = [
+            filter_df_numquant_epsilon(v, min_quant=default_val_slider, metric="mean")
+            for v in all_datapoints["results"]
         ]
 
         all_datapoints["nr_prec"] = [

diff --git a/proteobench/plotting/plot_quant.py b/proteobench/plotting/plot_quant.py
@@ -71,7 +71,7 @@ def plot_fold_change_histogram(result_df: pd.DataFrame, species_ratio: Dict[str,
     @staticmethod
     def plot_metric(
         benchmark_metrics_df: pd.DataFrame,
-        metric: str = "median",
+        metric: str = "Median",
         software_colors: Dict[str, str] = {
             "MaxQuant": "#377eb8",
             "AlphaPept": "#4daf4a",
@@ -165,18 +165,18 @@ def plot_metric(
         benchmark_metrics_df["hover_text"] = hover_texts
         benchmark_metrics_df["scatter_size"] = scatter_size
 
-        if metric == "median":
+        if metric == "Median":
             layout_xaxis_range = [
                 min(all_median_abs_epsilon) - min(all_median_abs_epsilon) * 0.05,
-                max(all_median_abs_epsilon) + min(all_median_abs_epsilon) * 0.05,
+                max(all_median_abs_epsilon) + max(all_median_abs_epsilon) * 0.05,
             ]
             layout_xaxis_title = (
                 "Median absolute difference between measured and expected log2-transformed fold change."
             )
-        elif metric == "mean":
+        elif metric == "Mean":
             layout_xaxis_range = [
                 min(all_mean_abs_epsilon) - min(all_mean_abs_epsilon) * 0.05,
-                max(all_mean_abs_epsilon) + min(all_mean_abs_epsilon) * 0.05,
+                max(all_mean_abs_epsilon) + max(all_mean_abs_epsilon) * 0.05,
             ]
             layout_xaxis_title = "Mean absolute difference between measured and expected log2-transformed fold change."
 
@@ -205,7 +205,7 @@ def plot_metric(
             # tmp_df["enable_match_between_runs"] = tmp_df["enable_match_between_runs"].astype(str)
             fig.add_trace(
                 go.Scatter(
-                    x=tmp_df["median_abs_epsilon"],
+                    x=tmp_df["{}_abs_epsilon".format(metric.lower())],
                     y=tmp_df["nr_prec"],
                     mode="markers" if label == "None" else "markers+text",
                     hovertext=tmp_df["hover_text"],

diff --git a/webinterface/pages/base_pages/quant.py b/webinterface/pages/base_pages/quant.py
@@ -173,8 +173,7 @@ def display_existing_results(self) -> None:
             fig_metric = PlotDataPoint.plot_metric(
                 data_points_filtered,
                 label=st.session_state[st.session_state[self.variables_quant.selectbox_id_uuid]],
-                metric=metric,
-                key="placeholder",  # TODO: add to variables
+                metric=metric
             )
             st.plotly_chart(fig_metric, use_container_width=True)
         except Exception as e: