fix bugs of the 2.7.2

pyproject.toml

@@ -93,7 +93,7 @@ where = ["."]
 
 
 [tool.setuptools.package-data]
-"*" = ["*.csv", "*json", "*.yml", "*.css", "*.js", "*.png", "*.ico"]
+"*" = ["*.csv", "*json", "*.yml", "*.css", "*.js", "*.png", "*.ico", "*.ipynb", "*.html", "*.j2"]
 
 [tool.pytest.ini_options]
 pythonpath = ["."]

shapash/explainer/consistency.py

@@ -1,4 +1,3 @@
-import copy
 import itertools
 
 import matplotlib.pyplot as plt
@@ -671,13 +670,10 @@ def _update_pairwise_consistency_fig(self, fig, top_features, xaxis_title, yaxis
         """
         title = "Pairwise comparison of Consistency:"
         title += "<span style='font-size: 16px;'>\
-                 <br />How are differences in contributions distributed across features?</span>"
-        dict_t = copy.deepcopy(self._style_dict["dict_title_stability"])
-        dict_xaxis = copy.deepcopy(self._style_dict["dict_xaxis"])
-        dict_yaxis = copy.deepcopy(self._style_dict["dict_yaxis"])
-        dict_xaxis["text"] = xaxis_title
-        dict_yaxis["text"] = yaxis_title
-        dict_t["text"] = title
+                    <br />How are differences in contributions distributed across features?</span>"
+        dict_t = self._style_dict["dict_title_stability"] | {"text": title, "yref": "paper"}
+        dict_xaxis = self._style_dict["dict_xaxis"] | {"text": xaxis_title}
+        dict_yaxis = self._style_dict["dict_yaxis"] | {"text": yaxis_title}
 
         fig.layout.yaxis.update(showticklabels=True)
         fig.layout.yaxis2.update(showticklabels=False)

shapash/explainer/smart_plotter.py

@@ -1513,7 +1513,7 @@ def ordinal(n):
 
         title = f"Comparing local explanations in a neighborhood - Id: <b>{index}</b>"
         title += "<span style='font-size: 16px;'><br />How similar are explanations for closeby neighbours?</span>"
-        dict_t = self._style_dict["dict_title_stability"] | {"text": title}
+        dict_t = self._style_dict["dict_title_stability"] | {"text": title, "yref": "paper"}
         dict_xaxis = self._style_dict["dict_xaxis"] | {"text": "Normalized contribution values"}
         dict_yaxis = self._style_dict["dict_yaxis"] | {"text": ""}
 

shapash/plots/plot_bar_chart.py

@@ -83,7 +83,7 @@ def plot_bar_chart(
         if subtitle:
             title += "<br><sup>" + subtitle + "</sup>"
             topmargin += 15
-        dict_t = style_dict["dict_title"] | {"text": title}
+        dict_t = style_dict["dict_title"] | {"text": title, "yref": "paper"}
         dict_xaxis = style_dict["dict_xaxis"] | {"text": "Contribution"}
         dict_yaxis = style_dict["dict_yaxis"] | {"text": None}
         dict_local_plot_colors = style_dict["dict_local_plot_colors"] | {"text": None}

shapash/plots/plot_compacity.py

@@ -104,7 +104,7 @@ def plot_compacity(
     title += (
         "<span style='font-size: 16px;'><br />How many variables are enough to produce accurate explanations?</span>"
     )
-    dict_t = style_dict["dict_title_stability"] | {"text": title}
+    dict_t = style_dict["dict_title_stability"] | {"text": title, "yref": "paper"}
 
     fig.update_layout(
         template="none",

shapash/plots/plot_contribution.py

@@ -493,7 +493,7 @@ def _update_contributions_fig(
             title += "<br><sup>" + subtitle + "</sup>"
         else:
             title += "<br><sup>" + addnote + "</sup>"
-    dict_t = style_dict["dict_title"] | {"text": title}
+    dict_t = style_dict["dict_title"] | {"text": title, "yref": "paper"}
     dict_xaxis = style_dict["dict_xaxis"] | {"text": truncate_str(feature_name, 110)}
     dict_yaxis = style_dict["dict_yaxis"] | {"text": "Contribution"}
 
@@ -571,13 +571,15 @@ def _update_xaxis_labels(fig, xs, zoom=False):
                 k = 6
 
             # Shorten labels that exceed the threshold
-            feature_val = [x.replace(x[k + k // 2 : -k + k // 2], "...") if len(x) > 2 * k else x for x in feature_val]
+            feature_val = [
+                x.replace(x[k + k // 2 : -k + k // 2], "...") if len(x) > 2 * k + 3 else x for x in feature_val
+            ]
         else:
             k = 10
             feature_val = []
             for feature_name in xs:
                 feature_name_splited = [
-                    x.replace(x[k + k // 2 : -k + k // 2], "...") if len(x) > 2 * k else x
+                    x.replace(x[k + k // 2 : -k + k // 2], "...") if len(x) > 2 * k + 3 else x
                     for x in feature_name.split("<br />")
                 ]
                 feature_val_name = "<br />".join(feature_name_splited)

shapash/plots/plot_correlations.py

@@ -6,7 +6,7 @@
 from plotly.subplots import make_subplots
 
 from shapash.manipulation.summarize import compute_corr
-from shapash.utils.utils import compute_top_correlations_features
+from shapash.utils.utils import compute_top_correlations_features, suffix_duplicates
 
 
 def plot_correlations(
@@ -108,6 +108,21 @@ def cluster_corr(corr, degree, inplace=False):
 
         return corr[idx, :][:, idx]
 
+    # Function to compute correlation matrix and prepare top features
+    def prepare_corr_matrix(df_subset):
+        corr = compute_corr(df_subset.drop(features_to_hide, axis=1), compute_method)
+        top_features = compute_top_correlations_features(corr=corr, max_features=max_features)
+        corr = cluster_corr(corr.loc[top_features, top_features], degree=degree)
+        list_features = [col for col in corr.columns if col in top_features]
+
+        # Shorten long feature names and handle duplicates
+        k = 12
+        list_features_shorten = [
+            x.replace(x[k + k // 2 : -k + k // 2], "...") if len(x) > 2 * k + 3 else x for x in list_features
+        ]
+        list_features_shorten = suffix_duplicates(list_features_shorten)
+        return corr, list_features, list_features_shorten
+
     if features_dict is None:
         features_dict = {}
 
@@ -142,17 +157,8 @@ def cluster_corr(corr, degree, inplace=False):
         )
         # Used for the Shapash report to get train then test set
         for i, col_v in enumerate(facet_col_values):
-            corr = compute_corr(df.loc[df[facet_col] == col_v].drop(features_to_hide, axis=1), compute_method)
-
-            # Keep the same list of features for each subplot
-            if len(list_features) == 0:
-                top_features = compute_top_correlations_features(corr=corr, max_features=max_features)
-                corr = cluster_corr(corr.loc[top_features, top_features], degree=degree)
-                list_features = list(corr.columns)
-                k = 6
-                list_features_shorten = [
-                    x.replace(x[k + k // 2 : -k + k // 2], "...") if len(x) > 2 * k else x for x in list_features
-                ]
+            df_subset = df[df[facet_col] == col_v]
+            corr, list_features, list_features_shorten = prepare_corr_matrix(df_subset)
 
             fig.add_trace(
                 go.Heatmap(
@@ -174,14 +180,7 @@ def cluster_corr(corr, degree, inplace=False):
             )
 
     else:
-        corr = compute_corr(df.drop(features_to_hide, axis=1), compute_method)
-        top_features = compute_top_correlations_features(corr=corr, max_features=max_features)
-        corr = cluster_corr(corr.loc[top_features, top_features], degree=degree)
-        list_features = [col for col in corr.columns if col in top_features]
-        k = 6
-        list_features_shorten = [
-            x.replace(x[k + k // 2 : -k + k // 2], "...") if len(x) > 2 * k else x for x in list_features
-        ]
+        corr, list_features, list_features_shorten = prepare_corr_matrix(df)
 
         fig = go.Figure(
             go.Heatmap(
@@ -204,7 +203,7 @@ def cluster_corr(corr, degree, inplace=False):
     if len(list_features) < len(df.drop(features_to_hide, axis=1).columns):
         subtitle = f"Top {len(list_features)} correlations"
         title += f"<span style='font-size: 12px;'><br />{subtitle}</span>"
-    dict_t = style_dict["dict_title"] | {"text": title}
+    dict_t = style_dict["dict_title"] | {"text": title, "yref": "paper"}
 
     fig.update_layout(
         coloraxis=dict(colorscale=["rgb(255, 255, 255)"] + style_dict["init_contrib_colorscale"][5:-1]),

shapash/plots/plot_feature_importance.py

@@ -234,7 +234,7 @@ def _plot_features_import(
         else:
             title += "<br><sup>" + addnote + "</sup>"
         topmargin = topmargin + 15
-    dict_t = style_dict["dict_title"] | {"text": title}
+    dict_t = style_dict["dict_title"] | {"text": title, "yref": "paper"}
     dict_xaxis = style_dict["dict_xaxis"] | {"text": "Mean absolute Contribution"}
     dict_yaxis = style_dict["dict_yaxis"] | {"text": None}
     dict_style_bar1 = style_dict["dict_featimp_colors"][1]
@@ -357,7 +357,7 @@ def _plot_local_features_import(
         else:
             title += "<br><sup>" + addnote + "</sup>"
         topmargin = topmargin + 15
-    dict_t = style_dict["dict_title"] | {"text": title}
+    dict_t = style_dict["dict_title"] | {"text": title, "yref": "paper"}
     dict_xaxis = style_dict["dict_xaxis"] | {"text": "Mean absolute Contribution"}
     dict_yaxis = style_dict["dict_yaxis"] | {"text": None}
     dict_style_bar = {}
@@ -537,7 +537,7 @@ def _plot_feature_contributions_cumulative(
         else:
             title += "<br><sup>" + addnote + "</sup>"
         topmargin = topmargin + 15
-    dict_t = style_dict["dict_title"] | {"text": title}
+    dict_t = style_dict["dict_title"] | {"text": title, "yref": "paper"}
 
     if (isinstance(lst_feat[0], str)) & (not zoom):
         # change index to abc...abc if its length is upper than 30

shapash/plots/plot_line_comparison.py

@@ -67,7 +67,7 @@ def plot_line_comparison(
     else:
         title = "Compare plot - index : " + " ; ".join(["<b>" + str(id) + "</b>" for id in index])
         dict_xaxis["text"] = "Contributions"
-    dict_t = style_dict["dict_title"] | {"text": title}
+    dict_t = style_dict["dict_title"] | {"text": title, "yref": "paper"}
 
     if subtitle is not None:
         topmargin += 15 * height / 275

shapash/plots/plot_scatter_prediction.py

@@ -116,7 +116,7 @@ def plot_scatter_prediction(
             title += "<br><sup>" + subtitle + "</sup>"
         else:
             title += "<br><sup>" + addnote + "</sup>"
-        dict_t = style_dict["dict_title"] | {"text": title}
+        dict_t = style_dict["dict_title"] | {"text": title, "yref": "paper"}
         dict_xaxis = style_dict["dict_xaxis"] | {"text": truncate_str("True Values", 110)}
         dict_yaxis = style_dict["dict_yaxis"] | {"text": "Predicted Values"}
 

shapash/plots/plot_stability.py

@@ -172,7 +172,7 @@ def _update_stability_fig(fig, x_barlen, y_bar, style_dict, xaxis_title, yaxis_t
     """
     title = "Importance & Local Stability of explanations:"
     title += "<span style='font-size: 16px;'><br />How similar are explanations for closeby neighbours?</span>"
-    dict_t = style_dict["dict_title_stability"] | {"text": title}
+    dict_t = style_dict["dict_title_stability"] | {"text": title, "yref": "paper"}
 
     dict_xaxis = style_dict["dict_xaxis"] | {"text": xaxis_title}
     dict_yaxis = style_dict["dict_yaxis"] | {"text": yaxis_title}

shapash/utils/utils.py

@@ -12,6 +12,39 @@
 from shapash.explainer.smart_state import SmartState
 
 
+def suffix_duplicates(lst):
+    """
+    Adds suffixes (_2, _3, ...) to non-unique elements in a list to make them unique.
+
+    Args:
+        lst (list): The input list of elements (strings) which may contain duplicates.
+
+    Returns:
+        list: A new list where non-unique elements have suffixes to ensure uniqueness.
+
+    Example:
+        Input: ["feature1", "feature2", "feature1", "feature2", "feature3"]
+        Output: ["feature1", "feature2", "feature1_2", "feature2_2", "feature3"]
+    """
+
+    seen = {}
+    result = []
+
+    for item in lst:
+        if item in seen:
+            # If the item has been seen before, increment its count and add a suffix
+            seen[item] += 1
+            new_item = f"{item}_{seen[item] + 1}"
+        else:
+            # If the item is seen for the first time, add it without a suffix
+            seen[item] = 0
+            new_item = item
+
+        result.append(new_item)
+
+    return result
+
+
 def get_host_name():
     """
     Get the url of the current host