Merge pull request #316 from PNNL-CompBio/bug-fixes-for-api

Bug fixes for api

Author: ymahlich

coderdata/dataset/dataset.py

@@ -494,7 +494,7 @@ def format(
             values='transcriptomics',
             index='entrez_id',
             columns='improve_sample_id'
-            )
+            ).transpose()
 
     elif data_type == "mutations":
         if data.mutations is None:
@@ -516,7 +516,7 @@ def format(
             columns='improve_sample_id',
             values='exists',
             fill_value=0,
-            )
+            ).transpose()
 
     elif data_type == "copy_number":
         if data.copy_number is None:
@@ -531,7 +531,7 @@ def format(
             columns='improve_sample_id',
             values='copy_number',
             aggfunc='mean',
-            )
+            ).transpose()
         if copy_call:
             ret = ret.apply(
                 pd.cut,
@@ -552,7 +552,7 @@ def format(
             values='proteomics',
             index='entrez_id',
             columns='improve_sample_id'
-            )
+            ).transpose()
 
     elif data_type == "experiments":
         if data.experiments is None:
@@ -936,13 +936,16 @@ def train_test_validate(
                 sss_1.split(X=df_full, y=df_full['split_class'])
             )
             df_train = df_full.iloc[idx_train]
+            df_train = df_train.drop(labels=['split_class'], axis=1)
             df_other = df_full.iloc[idx_other]
             # Splitting 'other' further into test and validate
             idx_test, idx_val = next(
                 sss_2.split(X=df_other, y=df_other['split_class'])
                 )
             df_test = df_other.iloc[idx_test]
+            df_test = df_test.drop(labels=['split_class'], axis=1)
             df_val = df_other.iloc[idx_val]
+            df_val = df_val.drop(labels=['split_class'], axis=1)
 
         # using StratifiedGroupKSplit for the stratified drug-/sample-
         # blind splits.

coderdata/download/downloader.py

@@ -68,7 +68,7 @@ def download(
             file 
             for file 
             in data['files'] 
-            if file['name'].startswith(name)
+            if file['name'].startswith(name) or 'genes' in file['name']
             ]
     else:
         filtered_files = data['files']