Merge pull request #607 from guillaume-vignal/feature/fix_title_height

Dynamic Title Height Adjustment for Feature Importance Plot

Author: guillaume-vignal

shapash/explainer/consistency.py

@@ -10,6 +10,7 @@
 from sklearn.manifold import MDS
 
 from shapash.style.style_utils import colors_loading, define_style, select_palette
+from shapash.utils.utils import adjust_title_height
 
 
 class Consistency:
@@ -668,10 +669,11 @@ def _update_pairwise_consistency_fig(self, fig, top_features, xaxis_title, yaxis
         auto_open: bool
             open automatically the plot
         """
+        height = max(500, 40 * len(top_features))
         title = "Pairwise comparison of Consistency:"
         title += "<span style='font-size: 16px;'>\
                     <br />How are differences in contributions distributed across features?</span>"
-        dict_t = self._style_dict["dict_title_stability"] | {"text": title, "yref": "paper"}
+        dict_t = self._style_dict["dict_title_stability"] | {"text": title, "y": adjust_title_height(height)}
         dict_xaxis = self._style_dict["dict_xaxis"] | {"text": xaxis_title}
         dict_yaxis = self._style_dict["dict_yaxis"] | {"text": yaxis_title}
 
@@ -684,7 +686,7 @@ def _update_pairwise_consistency_fig(self, fig, top_features, xaxis_title, yaxis
             yaxis_title=dict_yaxis,
             yaxis=dict(range=[-0.7, len(top_features) - 0.3]),
             yaxis2=dict(range=[-0.7, len(top_features) - 0.3]),
-            height=max(500, 40 * len(top_features)),
+            height=height,
         )
 
         fig.update_yaxes(automargin=True, zeroline=False)

shapash/explainer/multi_decorator.py

@@ -230,7 +230,7 @@ def summarize(self, s_contribs, var_dicts, xs_sorted, masks, columns_dict, featu
     def compute_features_import(self, contributions, norm=1):
         """
         Compute a relative features importance, sum of absolute values
-        \u200b\u200bof the contributions for each
+        of the contributions for each
         features importance compute in base 100
 
         Parameters

shapash/explainer/smart_explainer.py

@@ -153,7 +153,7 @@ class SmartExplainer:
     model: model object
         model used to check the different values of target estimate predict proba
     features_desc: dict
-        Dictionary that references the numbers of feature values \u200b\u200bin the x_init
+        Dictionary that references the numbers of feature values in the x_init
     features_imp: pandas.Series (regression) or list (classification)
         Features importance values
     local_neighbors: dict

shapash/explainer/smart_plotter.py

@@ -26,6 +26,7 @@
 from shapash.utils.utils import (
     add_line_break,
     add_text,
+    adjust_title_height,
     compute_digit_number,
     compute_sorted_variables_interactions_list_indices,
     maximum_difference_sort_value,
@@ -1511,9 +1512,10 @@ def ordinal(n):
             ]
         )
 
+        height = max(500, 11 * g_df.shape[0] * g_df.shape[1])
         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, "yref": "paper"}
+        dict_t = self._style_dict["dict_title_stability"] | {"text": title, "y": adjust_title_height(height)}
         dict_xaxis = self._style_dict["dict_xaxis"] | {"text": "Normalized contribution values"}
         dict_yaxis = self._style_dict["dict_yaxis"] | {"text": ""}
 
@@ -1524,7 +1526,7 @@ def ordinal(n):
             yaxis_title=dict_yaxis,
             hovermode="closest",
             barmode="group",
-            height=max(500, 11 * g_df.shape[0] * g_df.shape[1]),
+            height=height,
             legend={"traceorder": "reversed"},
             xaxis={"side": "bottom"},
         )

shapash/explainer/smart_state.py

@@ -305,7 +305,7 @@ def summarize(self, s_contrib, var_dict, x_sorted, mask, columns_dict, features_
     def compute_features_import(self, contributions, norm=1):
         """
         Compute a relative features importance, sum of absolute values
-        \u200b\u200bof the contributions for each
+        of the contributions for each
         features importance compute in base 100
         Parameters
         ----------

shapash/manipulation/summarize.py

@@ -47,7 +47,7 @@ def summarize_el(dataframe, mask, prefix):
 def compute_features_import(dataframe, norm=1):
     """
     Compute a relative features importance, sum of absolute values
-    \u200b\u200bof the contributions for each
+    of the contributions for each
     features importance compute in base 100
     Parameters
     ----------

shapash/plots/plot_bar_chart.py

@@ -1,7 +1,7 @@
 from plotly import graph_objs as go
 from plotly.offline import plot
 
-from shapash.utils.utils import add_line_break, truncate_str
+from shapash.utils.utils import add_line_break, adjust_title_height, truncate_str
 
 
 def plot_bar_chart(
@@ -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, "yref": "paper"}
+        dict_t = style_dict["dict_title"] | {"text": title, "y": adjust_title_height(height)}
         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

@@ -2,6 +2,8 @@
 from plotly.offline import plot
 from plotly.subplots import make_subplots
 
+from shapash.utils.utils import adjust_title_height
+
 
 def plot_compacity(
     features_needed, distance_reached, style_dict, approx=0.9, nb_features=5, file_name=None, auto_open=False
@@ -104,7 +106,7 @@ 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, "yref": "paper"}
+    dict_t = style_dict["dict_title_stability"] | {"text": title, "y": adjust_title_height()}
 
     fig.update_layout(
         template="none",

shapash/plots/plot_contribution.py

@@ -5,7 +5,7 @@
 from plotly import graph_objs as go
 from plotly.offline import plot
 
-from shapash.utils.utils import add_line_break, truncate_str
+from shapash.utils.utils import add_line_break, adjust_title_height, truncate_str
 from shapash.webapp.utils.utils import round_to_k
 
 
@@ -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, "yref": "paper"}
+    dict_t = style_dict["dict_title"] | {"text": title, "y": adjust_title_height(height)}
     dict_xaxis = style_dict["dict_xaxis"] | {"text": truncate_str(feature_name, 110)}
     dict_yaxis = style_dict["dict_yaxis"] | {"text": "Contribution"}
 

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, suffix_duplicates
+from shapash.utils.utils import adjust_title_height, compute_top_correlations_features, suffix_duplicates
 
 
 def plot_correlations(
@@ -203,7 +203,7 @@ def prepare_corr_matrix(df_subset):
     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, "yref": "paper"}
+    dict_t = style_dict["dict_title"] | {"text": title, "y": adjust_title_height(height)}
 
     fig.update_layout(
         coloraxis=dict(colorscale=["rgb(255, 255, 255)"] + style_dict["init_contrib_colorscale"][5:-1]),