Modif

Author: Gsaes

HISTORY.rst

@@ -1,9 +1,10 @@
 =======
 History
 =======
-0.0.12 (2023-05-31)
+0.0.13 (2023-06-07)
 -------------------
 
+* Refacto cross validation
 * Fix Readme
 * Add test utils.plot
 

qolmat/utils/data.py

@@ -1,6 +1,5 @@
 import os
 import zipfile
-from datetime import datetime
 from math import pi
 from typing import List, Optional
 from urllib import request
@@ -13,7 +12,6 @@
 
 def download_data(zipname: str, urllink: str, datapath: str = "data/") -> List[pd.DataFrame]:
     path_zip = os.path.join(datapath)
-    print("Download data")
     if not os.path.exists(path_zip + ".zip"):
         if not os.path.exists(datapath):
             os.mkdir(datapath)

tests/utils/test_data.py

@@ -29,6 +29,16 @@
     [[1, 2], [3, np.nan], [np.nan, 6]], columns=["a", "b"], index=index_preprocess
 )
 
+urllink = "https://archive.ics.uci.edu/ml/machine-learning-databases/00501/"
+zipname = "PRSA2017_Data_20130301-20170228"
+
+
+# @pytest.mark.parametrize("zipname, urllink", [(zipname, urllink)])
+# def test_utils_data_download_data(zipname: str, urllink: str, mocker: MockerFixture) -> None:
+#     mocker.patch("urllib.request.urlretrieve")
+#     mocker.patch("zipfile.ZipFile")
+#     list_df_result = data.download_data(zipname, urllink)
+
 
 @pytest.mark.parametrize("name_data", ["Beijing", "Artificial", "Bug"])
 def test_utils_data_get_data(name_data: str, mocker: MockerFixture) -> None:
@@ -67,11 +77,15 @@ def test_utils_data_add_holes(df: pd.DataFrame) -> None:
 
 
 @pytest.mark.parametrize("name_data", ["Beijing"])
-def test_utils_data_get_data_corrupted(name_data: str) -> None:
+def test_utils_data_get_data_corrupted(name_data: str, mocker: MockerFixture) -> None:
+    mock_download = mocker.patch("qolmat.utils.data.download_data", return_value=[df])
+    mocker.patch("qolmat.utils.data.preprocess_data", return_value=df_preprocess)
     df_out = data.get_data_corrupted()
-    size_df_out = df_out.shape
-    n = size_df_out[0] * size_df_out[1]
-    np.testing.assert_allclose(df_out.isna().sum().sum() / n, 0.2, atol=0.1)
+    df_result = pd.DataFrame(
+        [[1, 2], [np.nan, np.nan], [np.nan, 6]], columns=["a", "b"], index=index_preprocess
+    )
+    assert mock_download.call_count == 1
+    pd.testing.assert_frame_equal(df_result, df_out)
 
 
 @pytest.mark.parametrize("df", [df_preprocess])