[ENH] add BreastCancer test

abl/data/data_converter.py

@@ -79,4 +79,22 @@ class DataConverter:
             X, gt_pseudo_label, Y = test_data
             test_data_examples = ListData(X=X, gt_pseudo_label=gt_pseudo_label, Y=Y)
         
-        return label_data_examples, train_data_examples, valid_data_examples, test_data_examples
+        return label_data_examples, train_data_examples, valid_data_examples, test_data_examples
+    
+if __name__ == '__main__':
+    from lambdaLearn.Dataset.Tabular.BreastCancer import BreastCancer
+    breast_dataset=BreastCancer(labeled_size=0.1, stratified=True, shuffle=True)
+    dataconverter = DataConverter()
+    
+    label_data, train_data, valid_data, test_data = dataconverter.convert_lambdalearn_to_tuple(breast_dataset, 0)
+    print(type(label_data).__name__, type(train_data).__name__, type(valid_data).__name__, type(test_data).__name__)
+    print(len(label_data))
+    print(len(label_data[0]), len(label_data[1]), len(label_data[2]))
+    print(label_data[0][0], label_data[1][0], label_data[2][0])
+    print()
+    
+    label_data_examples, train_data_examples, valid_data_examples, test_data_examples = dataconverter.convert_lambdalearn_to_listdata(breast_dataset, 0)
+    print(type(label_data_examples).__name__, type(train_data_examples).__name__, type(valid_data_examples).__name__, type(test_data_examples).__name__)
+    print(len(label_data_examples.X), len(label_data_examples.gt_pseudo_label), len(label_data_examples.Y))
+    label_data_example = label_data_examples[0]
+    print(label_data_example.X, label_data_example.gt_pseudo_label, label_data_example.Y)

docs/conf.py

@@ -5,6 +5,15 @@ import sys
 from docutils import nodes
 from docutils.parsers.rst import roles
 
+import re
+from sphinx.application import Sphinx
+
+def remove_noqa(app: Sphinx, what: str, name: str, obj, options, lines):
+    new_lines = []
+    for line in lines:
+        new_line = re.sub(r'\s*#\s*noqa.*$', '', line)
+        new_lines.append(new_line)
+    lines[:] = new_lines
 
 def colored_text_role(role, rawtext, text, lineno, inliner, options={}, content=[]):
     node = nodes.inline(rawtext, text, classes=[role])
@@ -86,7 +95,7 @@ texinfo_documents = [
 def setup(app):
     from sphinx.domains.python import PyField
     from sphinx.util.docfields import Field
-
+    app.connect('autodoc-process-docstring', remove_noqa)
     app.add_object_type(
         "confval",
         "confval",