added tests for multivariate

Author: enriquea

fslite/tests/test_multivariate_methods.py

@@ -0,0 +1,122 @@
+import pandas as pd
+
+from fslite.fs.fdataframe import FSDataFrame
+from fslite.fs.multivariate import FSMultivariate
+from fslite.utils.datasets import get_tnbc_data_path
+
+
+# test multivariate_filter method with 'm_corr' method
+def test_multivariate_filter_corr_strict_mode():
+    """
+    Test multivariate_filter method with 'm_corr' method.
+    :return: None
+    """
+
+    # import tsv as pandas DataFrame
+    df = pd.read_csv(get_tnbc_data_path(), sep="\t")
+
+    # create FSDataFrame instance
+    fs_df = FSDataFrame(df=df, sample_col="Sample", label_col="label")
+
+    # create FSMultivariate instance
+    fs_multivariate = FSMultivariate(fs_method="m_corr",
+                                     selection_mode="strict",
+                                     selection_threshold=0.75)
+
+    fsdf_filtered = fs_multivariate.select_features(fs_df)
+
+    assert fs_df.count_features() == 500
+    assert fsdf_filtered.count_features() == 239
+
+    # Export the filtered DataFrame as Pandas DataFrame
+    df_filtered = fsdf_filtered.to_pandas()
+    df_filtered.to_csv("filtered_tnbc_data.csv", index=False)
+
+
+# test multivariate_filter method with 'm_corr' method in approximate mode
+def test_multivariate_filter_corr_approximate_mode():
+    """
+    Test multivariate_filter method with 'm_corr' method in approximate mode.
+    :return: None
+    """
+
+    # import tsv as pandas DataFrame
+    df = pd.read_csv(get_tnbc_data_path(), sep="\t")
+
+    # create FSDataFrame instance
+    fs_df = FSDataFrame(df=df, sample_col="Sample", label_col="label")
+
+    # create FSMultivariate instance
+    fs_multivariate = FSMultivariate(fs_method="m_corr",
+                                     selection_mode="approximate",
+                                     selection_threshold=0.75)
+
+    fsdf_filtered = fs_multivariate.select_features(fs_df)
+
+    assert fs_df.count_features() == 500
+
+    # test if number of features selected is within the expected range [240-260]
+    assert 240 <= fsdf_filtered.count_features() <= 260
+
+    # Export the filtered DataFrame as Pandas DataFrame
+    df_filtered = fsdf_filtered.to_pandas()
+    df_filtered.to_csv("filtered_tnbc_data.csv", index=False)
+
+
+# test multivariate_filter method with 'variance' method
+def test_multivariate_filter_variance_percentile_mode():
+    """
+    Test multivariate_filter method with 'variance' method.
+    :return: None
+    """
+
+    # import tsv as pandas DataFrame
+    df = pd.read_csv(get_tnbc_data_path(), sep="\t")
+
+    # create FSDataFrame instance
+    fs_df = FSDataFrame(df=df, sample_col="Sample", label_col="label")
+
+    # create FSMultivariate instance
+    fs_multivariate = FSMultivariate(fs_method="variance",
+                                     selection_mode="percentile",
+                                     selection_threshold=0.2)
+
+    fsdf_filtered = fs_multivariate.select_features(fs_df)
+
+    assert fs_df.count_features() == 500
+    assert fsdf_filtered.count_features() == 400
+
+    # Export the filtered DataFrame as Pandas DataFrame
+    df_filtered = fsdf_filtered.to_pandas()
+    df_filtered.to_csv("filtered_tnbc_data.csv", index=False)
+
+
+# test multivariate_filter method with 'variance' method in k_best mode
+def test_multivariate_filter_variance_k_best_mode():
+    """
+    Test multivariate_filter method with 'variance' method in k_best mode.
+    :return: None
+    """
+
+    # import tsv as pandas DataFrame
+    df = pd.read_csv(get_tnbc_data_path(), sep="\t")
+
+    # create FSDataFrame instance
+    fs_df = FSDataFrame(df=df, sample_col="Sample", label_col="label")
+
+    # create FSMultivariate instance
+    fs_multivariate = FSMultivariate(fs_method="variance",
+                                     selection_mode="k_best",
+                                     selection_threshold=68100000.0
+                                     # TODO: check this value (should be normalized variance?)
+                                     )
+
+    fsdf_filtered = fs_multivariate.select_features(fs_df)
+
+    assert fs_df.count_features() == 500
+    assert fsdf_filtered.count_features() == 87
+
+    # Export the filtered DataFrame as Pandas DataFrame
+    df_filtered = fsdf_filtered.to_pandas()
+    df_filtered.to_csv("filtered_tnbc_data.csv", index=False)
+