pre-commit

eds_scikit/period/stays.py

@@ -6,10 +6,9 @@
 from eds_scikit.utils.checks import MissingConceptError, algo_checker, concept_checker
 from eds_scikit.utils.datetime_helpers import substract_datetime
 from eds_scikit.utils.framework import get_framework
-from eds_scikit.utils.typing import DataFrame
 from eds_scikit.utils.sort_first_koalas import sort_values_first_koalas
+from eds_scikit.utils.typing import DataFrame
 
-import pandas as pd
 
 def cleaning(
     vo,
@@ -71,6 +70,7 @@ def cleaning(
 
     return vo[~mask], vo[mask]
 
+
 @concept_checker(concepts=["STAY_ID", "CONTIGUOUS_STAY_ID"])
 def merge_visits(
     vo: DataFrame,
@@ -291,23 +291,26 @@ def get_first(
             right_index=True,
             how="inner",
         )
-
-        first_visit = sort_values_first_koalas(merged, 
-                                               by_cols=["visit_occurrence_id_2"], 
-                                               cols=[flag_name, "visit_start_datetime_1"],
-                                               ascending=False
-                                              ).rename(
+
+        first_visit = sort_values_first_koalas(
+            merged,
+            by_cols=["visit_occurrence_id_2"],
+            cols=[flag_name, "visit_start_datetime_1"],
+            ascending=False,
+        ).rename(
             columns={
                 "visit_occurrence_id_1": f"{concept_prefix}STAY_ID",
                 "visit_occurrence_id_2": "visit_occurrence_id",
-            })[[f"{concept_prefix}STAY_ID", "visit_occurrence_id"]]
-
-
+            }
+        )[
+            [f"{concept_prefix}STAY_ID", "visit_occurrence_id"]
+        ]
+
         return merged, first_visit
 
-    merged, first_contiguous_visit = get_first(merged, contiguous_only=True)    
+    merged, first_contiguous_visit = get_first(merged, contiguous_only=True)
     merged, first_visit = get_first(merged, contiguous_only=False)
-    
+
     # Concatenating merge visits with previously discarded ones
     results = fw.concat(
         [

eds_scikit/utils/sort_first_koalas.py

@@ -1,6 +1,8 @@
 def sort_values_first_koalas(dataframe, by_cols, cols, ascending=True):
     for col in cols:
         dataframe_min_max = dataframe.groupby(by_cols, as_index=False)[col]
-        dataframe_min_max = dataframe_min_max.min() if ascending else dataframe_min_max.max() 
+        dataframe_min_max = (
+            dataframe_min_max.min() if ascending else dataframe_min_max.max()
+        )
         dataframe = dataframe.merge(dataframe_min_max, on=[*by_cols, col], how="right")
     return dataframe

tests/test_sort_first_koalas.py

@@ -1,37 +1,68 @@
 import pandas as pd
-from eds_scikit.utils.sort_first_koalas import sort_values_first_koalas
-from numpy import array
 import pytest
+from numpy import array
+
 from eds_scikit.utils import framework
+from eds_scikit.utils.sort_first_koalas import sort_values_first_koalas
 from eds_scikit.utils.test_utils import assert_equal_no_order
 
 data = {
-    'A': array(['X', 'Y', 'X', 'Y', 'Y', 'Z', 'X', 'Z', 'X', 'X', 'X', 'Z', 'Y', 'Z', 'Z', 'X', 'Y', 'Y', 'Y', 'Y'], dtype='<U1'),
-    'B': array([9, 5, 4, 1, 4, 6, 1, 3, 4, 9, 2, 4, 4, 4, 8, 1, 2, 1, 5, 8]),
-    'C': array([4, 3, 8, 3, 1, 1, 5, 6, 6, 7, 9, 5, 2, 5, 9, 2, 2, 8, 4, 7]),
-    'D': array([8, 3, 1, 4, 6, 5, 5, 7, 5, 5, 4, 5, 5, 9, 5, 4, 8, 6, 6, 1]),
-    'E': array([2, 6, 4, 1, 6, 1, 2, 3, 5, 3, 1, 4, 3, 1, 8, 6, 1, 3, 8, 3])
+    "A": array(
+        [
+            "X",
+            "Y",
+            "X",
+            "Y",
+            "Y",
+            "Z",
+            "X",
+            "Z",
+            "X",
+            "X",
+            "X",
+            "Z",
+            "Y",
+            "Z",
+            "Z",
+            "X",
+            "Y",
+            "Y",
+            "Y",
+            "Y",
+        ],
+        dtype="<U1",
+    ),
+    "B": array([9, 5, 4, 1, 4, 6, 1, 3, 4, 9, 2, 4, 4, 4, 8, 1, 2, 1, 5, 8]),
+    "C": array([4, 3, 8, 3, 1, 1, 5, 6, 6, 7, 9, 5, 2, 5, 9, 2, 2, 8, 4, 7]),
+    "D": array([8, 3, 1, 4, 6, 5, 5, 7, 5, 5, 4, 5, 5, 9, 5, 4, 8, 6, 6, 1]),
+    "E": array([2, 6, 4, 1, 6, 1, 2, 3, 5, 3, 1, 4, 3, 1, 8, 6, 1, 3, 8, 3]),
 }
 
-all_inputs = [
-    pd.DataFrame(data)
-]
+all_inputs = [pd.DataFrame(data)]
 
-all_params = dict(ascending=[True, False], cols=["A", ["A", "B"]], by_cols=[["B", "C", "D"], ["C", "D"]])
+all_params = dict(
+    ascending=[True, False],
+    cols=["A", ["A", "B"]],
+    by_cols=[["B", "C", "D"], ["C", "D"]],
+)
 all_params = pd.DataFrame(all_params).to_dict("records")
 
+
 @pytest.mark.parametrize("module", ["pandas", "koalas"])
 @pytest.mark.parametrize(
     "params, inputs",
     [(params, inputs) for params, inputs in zip(all_params, all_inputs)],
 )
 def test_visit_merging(module, params, inputs):
     print(params)
-    expected_results = inputs.sort_values(params["cols"]).groupby(params["by_cols"]).first().reset_index()
+    expected_results = (
+        inputs.sort_values(params["cols"])
+        .groupby(params["by_cols"])
+        .first()
+        .reset_index()
+    )
     inputs = framework.to(module, inputs)
     results = sort_values_first_koalas(inputs, **params)
     results = framework.pandas(results)
 
-    assert_equal_no_order(
-        results, expected_results
-    )
+    assert_equal_no_order(results, expected_results)