small change to support higher numpy versions

pyproject.toml

@@ -0,0 +1,3 @@
+[build-system]
+requires = ["setuptools>=40.6.0", "wheel", "numpy", "scipy"]
+build-backend = "setuptools.build_meta"

sliced/base.py

@@ -116,7 +116,7 @@ def slice_y(y, n_slices=10):
             slice_partition.append(n_samples_seen)
 
     # turn partitions into an indicator
-    slice_indicator = np.ones(y.shape[0], dtype=np.int)
+    slice_indicator = np.ones(y.shape[0], dtype=int)
     for j, (start_idx, end_idx) in enumerate(
             zip(slice_partition, slice_partition[1:])):
 

sliced/externals/sklearn_partial.py

@@ -14,7 +14,6 @@
 
 import numpy as np
 import scipy.sparse as sp
-from numpy.core.numeric import ComplexWarning
 
 
 class NotFittedError(ValueError, AttributeError):
@@ -368,13 +367,15 @@ def check_array(array, accept_sparse=False, dtype="numeric", order=None,
         # dtype to the function converts complex to real dtype,
         # thereby passing the test made in the lines following the scope
         # of warnings context manager.
-        with warnings.catch_warnings():
-            try:
-                warnings.simplefilter('error', ComplexWarning)
-                array = np.asarray(array, dtype=dtype, order=order)
-            except ComplexWarning:
-                raise ValueError("Complex data not supported\n"
-                                 "{}\n".format(array))
+        #with warnings.catch_warnings():
+        #    try:
+        #        warnings.simplefilter('error', ComplexWarning)
+        #        array = np.asarray(array, dtype=dtype, order=order)
+        #    except ComplexWarning:
+        #        raise ValueError("Complex data not supported\n"
+        #                         "{}\n".format(array))
+
+        # skip for numpy 2
 
         # It is possible that the np.array(..) gave no warning. This happens
         # when no dtype conversion happened, for example dtype = None. The