Replaced deprecated np.in1d with np.isin

Author: jakobwes

ibicus/debias/_isimip.py

@@ -1382,7 +1382,7 @@ def apply_location(
                     years_cm_future=years_cm_future[indices_window_cm_future],
                 )[
                     np.logical_and(
-                        np.in1d(
+                        np.isin(
                             indices_window_cm_future, indices_bias_corrected_values
                         ),
                         get_mask_for_unique_subarray(indices_window_cm_future),

ibicus/evaluate/metrics.py

@@ -190,7 +190,7 @@ def _check_completeness_of_time_categories_and_warn(thresholds, threshold_scope)
         if threshold_scope == "day":
             days_of_year = np.arange(1, 367)
             if not all(
-                mask_days_of_year_in_quantiles := np.in1d(
+                mask_days_of_year_in_quantiles := np.isin(
                     days_of_year, list(thresholds.keys())
                 )
             ):
@@ -201,7 +201,7 @@ def _check_completeness_of_time_categories_and_warn(thresholds, threshold_scope)
         elif threshold_scope == "month":
             months = np.arange(1, 13)
             if not all(
-                mask_months_in_quantiles := np.in1d(months, list(thresholds.keys()))
+                mask_months_in_quantiles := np.isin(months, list(thresholds.keys()))
             ):
                 warnings.warn(
                     "Not all months present inside the dataset used for initialisation. Not threshold defined for months %s"
@@ -210,7 +210,7 @@ def _check_completeness_of_time_categories_and_warn(thresholds, threshold_scope)
         elif threshold_scope == "season":
             seasons = np.array(["Spring", "Summer", "Autumn", "Winter"])
             if not all(
-                mask_seasons_in_quantiles := np.in1d(seasons, list(thresholds.keys()))
+                mask_seasons_in_quantiles := np.isin(seasons, list(thresholds.keys()))
             ):
                 warnings.warn(
                     "Not all seasons present inside the dataset used for initialisation. Not threshold defined for seasons %s"
@@ -349,7 +349,7 @@ def _get_mask_higher_or_lower(self, x, threshold_value, higher_or_lower, time=No
 
             time = ThresholdMetric._get_time_group_by_scope(time, self.threshold_scope)
 
-            if not np.all(np.in1d(time, list(threshold_value.keys()))):
+            if not np.all(np.isin(time, list(threshold_value.keys()))):
                 raise ValueError(
                     "time contains values for %ss for which no thresholds exist in self.threshold_value"
                     % self.threshold_scope

ibicus/utils/_running_window_mode.py

@@ -165,7 +165,7 @@ def get_if_in_chosen_years(years, chosen_years):
         chosen_years : np.ndarray
             Array of chosen years.
         """
-        return np.in1d(years, chosen_years)
+        return np.isin(years, chosen_years)
 
     def use(self, years):
         """
@@ -337,7 +337,7 @@ def get_indices_vals_in_window(
         )
         window_range[window_range == 0] = 366
 
-        return np.where(np.in1d(days_of_year, window_range))[0]
+        return np.where(np.isin(days_of_year, window_range))[0]
 
     def get_indices_vals_to_adjust(
         self, days_of_year: np.ndarray, window_center: int
@@ -358,12 +358,12 @@ def get_indices_vals_to_adjust(
         )
         window_range = window_range[(window_range >= 0) & (window_range <= 366)]
 
-        return np.where(np.in1d(days_of_year, window_range))[0]
+        return np.where(np.isin(days_of_year, window_range))[0]
 
     @staticmethod
     def get_mask_vals_to_adjust_in_window(indices_window, indices_vals_to_correct):
         return np.logical_and(
-            np.in1d(indices_window, indices_vals_to_correct),
+            np.isin(indices_window, indices_vals_to_correct),
             get_mask_for_unique_subarray(indices_window),
         )
 

tests/test_running_window_mode.py

@@ -156,7 +156,7 @@ def _test_all_bias_corrected_and_length_each_window(
         assert len(np.unique(debiased_years)) == len(debiased_years)
 
         # Check that all years are given
-        assert all(np.in1d(years, debiased_years))
+        assert all(np.isin(years, debiased_years))
 
     def test_use(self):
         for step_length in range(1, 10):
@@ -215,7 +215,7 @@ def _test_all_bias_corrected_and_length_each_window(
             indices_vals_in_window = window.get_indices_vals_in_window(
                 days_of_year_dates, window_center
             )
-            assert np.all(np.in1d(indices_vals_to_debias, indices_vals_in_window))
+            assert np.all(np.isin(indices_vals_to_debias, indices_vals_in_window))
 
             n_occurrences = (days_of_year_dates == window_center).sum()
             if length > 365: