🙈 fix tests

tests/test_features_feature_collection.py

@@ -54,7 +54,7 @@ def test_single_series_group_by_feature_collection(dummy_group_data, group_by):
     if "consecutive" in group_by:  # group_by_consecutive
         result_data_counts = res_df.groupby("store")["number_sold__sum__w=manual"].sum()
     else:  # group_by_all
-        result_data_counts = res_df["number_sold__sum"]
+        result_data_counts = res_df["number_sold__sum__w=manual"]
 
     for index in data_counts.index:
         assert data_counts[index] == result_data_counts[index]
@@ -104,7 +104,7 @@ def test_group_by_feature_collection_with_warnings(dummy_group_data, group_by):
     if "consecutive" in group_by:  # group_by_consecutive
         result_data_counts = res_df.groupby("store")["number_sold__sum__w=manual"].sum()
     else:  # group_by_all
-        result_data_counts = res_df["number_sold__sum"]
+        result_data_counts = res_df["number_sold__sum__w=manual"]
 
     for index in data_counts.index:
         assert data_counts[index] == result_data_counts[index]
@@ -160,15 +160,14 @@ def test_single_series_multiple_features_group_by(dummy_group_data, group_by, n_
     data_count_min = dummy_group_data.groupby("store")["number_sold"].min()
     data_count_max = dummy_group_data.groupby("store")["number_sold"].max()
 
-    postfix = "__w=manual" if "consecutive" in group_by else ""
     grouped_res_df_sum = (
-        res_df.reset_index().groupby("store")["number_sold__sum" + postfix].sum()
+        res_df.reset_index().groupby("store")["number_sold__sum__w=manual"].sum()
     )
     grouped_res_df_min = (
-        res_df.reset_index().groupby("store")["number_sold__amin" + postfix].min()
+        res_df.reset_index().groupby("store")["number_sold__amin__w=manual"].min()
     )
     grouped_res_df_max = (
-        res_df.reset_index().groupby("store")["number_sold__amax" + postfix].max()
+        res_df.reset_index().groupby("store")["number_sold__amax__w=manual"].max()
     )
 
     def assert_results(data, res_data):
@@ -210,11 +209,10 @@ def sum_2(x: np.ndarray, y: np.ndarray) -> float:
 
     assert_frame_equal(concatted_df, res_df)
 
-    postfix = "__w=manual" if "consecutive" in group_by else ""
     assert all(
-        res_df["number_sold__sum" + postfix].values
-        + res_df["product__sum" + postfix].values
-        == res_df["number_sold|product__sum_2" + postfix].values
+        res_df["number_sold__sum__w=manual"].values
+        + res_df["product__sum__w=manual"].values
+        == res_df["number_sold|product__sum_2__w=manual"].values
     )
 
 
@@ -247,10 +245,9 @@ def test_group_by_with_nan_values(dummy_group_data, group_by):
 
     assert_frame_equal(concatted_df, res_df)
 
-    postfix = "__w=manual" if "consecutive" in group_by else ""
     assert (
         dummy_group_data["number_sold"].sum()
-        > res_df["number_sold__sum" + postfix].sum()
+        > res_df["number_sold__sum__w=manual"].sum()
     )
 
 
@@ -307,15 +304,13 @@ def test_group_by_with_unequal_lengths(group_by):
     res_list2 = fc.calculate(
         [s_group2, s_val2], return_df=True, n_jobs=1, **{group_by: "user_id"}
     )
-    col = "count__nansum"
-    col += "__w=manual" if "consecutive" in group_by else ""
     correct_res_list = fc.calculate(
         [s_group, s_val2], return_df=True, n_jobs=1, **{group_by: "user_id"}
     )
 
     for c in res_list.columns:
         # compare (compare_col) only with nan-safe col in case of group_by_all
-        compare_col = c if "consecutive" in group_by else col
+        compare_col = c if "consecutive" in group_by else "count__nansum__w=manual"
         assert np.all(
             res_list[c]
             == res_list2.loc[res_list.index, compare_col].astype(res_list.dtypes[c])
@@ -346,10 +341,8 @@ def test_group_by_non_aligned_indices(group_by):
     ).reset_index()
     grouped_non_nan_df_sums = non_nan_df.groupby("groups").sum()
 
-    col = "count__nansum"
-    col += "__w=manual" if "consecutive" in group_by else ""
     new_res_list = pd.DataFrame(
-        {"groups": res_list["user_id"], "values": res_list[col]}
+        {"groups": res_list["user_id"], "values": res_list["count__nansum__w=manual"]}
     )
     new_res_list = new_res_list.set_index("groups")
 
@@ -395,9 +388,7 @@ def test_group_by_with_numeric_index(group_by):
     s_df = pd.DataFrame({"groups": s_group, "values": s_val})
 
     data_counts = s_df.groupby("groups")["values"].sum()
-    col = "count__nansum"
-    col += "__w=manual" if "consecutive" in group_by else ""
-    result_data_counts = res_df.groupby("user_id")[col].sum()
+    result_data_counts = res_df.groupby("user_id")["count__nansum__w=manual"].sum()
 
     for index in data_counts.index:
         assert data_counts[index] == result_data_counts[index]