make w2w compatible with numpy 2.0

matthiasdemuzere · Jul 1, 2024 · 4809cc6 · 4809cc6
1 parent 84f7d80
commit 4809cc6
Showing 1 changed file with 7 additions and 7 deletions.
diff --git a/w2w/w2w.py b/w2w/w2w.py
@@ -676,7 +676,7 @@ def _get_lcz_arr(src_data: xr.DataArray, info: Info) -> NDArray[np.int_]:
 
     # Get mask of selected built LCZs
     lcz_urb_mask = xr.DataArray(
-        np.in1d(src_data, info.BUILT_LCZ).reshape(src_data.shape),
+        np.isin(src_data, info.BUILT_LCZ).reshape(src_data.shape),
         dims=src_data.dims,
         coords=src_data.coords,
     )
@@ -846,7 +846,7 @@ def _hgt_resampler(
 
 def _get_truncated_normal_sample(
     lcz_i: int, ucp_table: pd.DataFrame, SAMPLE_SIZE: int = 100000
-) -> NDArray[np.float_]:
+) -> NDArray[np.floating[Any]]:
     '''Helper function to return bounded normal distribution sample'''
 
     # Create instance of a truncated normal distribution
@@ -867,7 +867,7 @@ def _get_truncated_normal_sample(
 
 def _check_hi_values(
     lcz_i: int,
-    hi_sample: NDArray[np.float_],
+    hi_sample: NDArray[np.floating[Any]],
     ucp_table: pd.DataFrame,
     ERROR_MARGIN: float,
 ) -> None:
@@ -977,7 +977,7 @@ def _hi_resampler(
     RESAMPLE_TYPE: str,
     ucp_table: pd.DataFrame,
     HI_THRES_MIN: int = 5,
-) -> Tuple[NDArray[np.float_], float]:
+) -> Tuple[NDArray[np.floating[Any]], float]:
     '''Helper function to resample ucp HI_URB2D_URB2D data to WRF grid'''
 
     # Read gridded LCZ data
@@ -1048,7 +1048,7 @@ def _lcz_resampler(
     info: Info,
     frc_urb2d: xr.DataArray,
     LCZ_NAT_MASK: bool,
-) -> Tuple[NDArray[np.bool_], NDArray[np.float_]]:
+) -> Tuple[NDArray[np.bool_], NDArray[np.floating[Any]]]:
     '''Helper function to resample lcz classes to WRF grid using majority'''
 
     # Read gridded LCZ data
@@ -1098,7 +1098,7 @@ def _adjust_greenfrac_landusef(
     # GREENFRAC is set as average / month from GREENFRAC
     # of original urban pixels
     wrf_urb = xr.DataArray(
-        np.in1d(dst_data_orig['LU_INDEX'][0, :, :].values, [urban_cat]).reshape(
+        np.isin(dst_data_orig['LU_INDEX'][0, :, :].values, [urban_cat]).reshape(
             dst_data_orig['LU_INDEX'][0, :, :].shape
         ),
         dims=dst_data_orig['LU_INDEX'][0, :, :].dims,
@@ -1579,7 +1579,7 @@ def checks_and_cleaning(info: Info, ucp_table: pd.DataFrame, nbui_max: float) ->
             'LF_URB2D': {'index': 96, 'range': [0, 5]},
         }
 
-        def _check_range(darr: NDArray[np.float_], exp_range: List[int]) -> int:
+        def _check_range(darr: NDArray[np.floating[Any]], exp_range: List[int]) -> int:
             total_len = len(darr)
             sel_len = ((darr >= exp_range[0]) & (darr <= exp_range[1])).sum(axis=0)