MAINT Update submodule commit and remove cnp imports where possible

sktree/tree/_oblique_splitter.pxd

@@ -10,13 +10,12 @@
 
 import numpy as np
 
-cimport numpy as cnp
 from libcpp.vector cimport vector
 
 from .._lib.sklearn.tree._criterion cimport Criterion
 from .._lib.sklearn.tree._splitter cimport SplitRecord, Splitter
 from .._lib.sklearn.tree._utils cimport UINT32_t
-from .._lib.sklearn.utils._typedefs cimport float32_t, float64_t, intp_t
+from .._lib.sklearn.utils._typedefs cimport float32_t, float64_t, int8_t, intp_t
 from ._sklearn_splitter cimport sort
 
 

sktree/tree/_oblique_splitter.pyx

@@ -146,7 +146,7 @@ cdef class ObliqueSplitter(BaseObliqueSplitter):
         intp_t min_samples_leaf,
         float64_t min_weight_leaf,
         object random_state,
-        const cnp.int8_t[:] monotonic_cst,
+        const int8_t[:] monotonic_cst,
         float64_t feature_combinations,
         *argv
     ):
@@ -667,7 +667,7 @@ cdef class MultiViewSplitter(BestObliqueSplitter):
         intp_t min_samples_leaf,
         float64_t min_weight_leaf,
         object random_state,
-        const cnp.int8_t[:] monotonic_cst,
+        const int8_t[:] monotonic_cst,
         float64_t feature_combinations,
         const intp_t[:] feature_set_ends,
         intp_t n_feature_sets,
@@ -839,7 +839,7 @@ cdef class MultiViewObliqueSplitter(BestObliqueSplitter):
         intp_t min_samples_leaf,
         float64_t min_weight_leaf,
         object random_state,
-        const cnp.int8_t[:] monotonic_cst,
+        const int8_t[:] monotonic_cst,
         float64_t feature_combinations,
         const intp_t[:] feature_set_ends,
         intp_t n_feature_sets,

sktree/tree/manifold/_morf_splitter.pxd

@@ -10,12 +10,11 @@
 
 import numpy as np
 
-cimport numpy as cnp
 from libcpp.vector cimport vector
 
 from ..._lib.sklearn.tree._splitter cimport SplitRecord
 from ..._lib.sklearn.tree._utils cimport UINT32_t
-from ..._lib.sklearn.utils._typedefs cimport float32_t, float64_t, intp_t
+from ..._lib.sklearn.utils._typedefs cimport float32_t, float64_t, int8_t, intp_t, uint8_t
 from .._oblique_splitter cimport BestObliqueSplitter, ObliqueSplitRecord
 
 # https://github.com/cython/cython/blob/master/Cython/Includes/libcpp/algorithm.pxd
@@ -53,7 +52,7 @@ cdef class PatchSplitter(BestObliqueSplitter):
     cdef const intp_t[:] data_dims                      # The dimensions of the input data
     cdef const intp_t[:] min_patch_dims                 # The minimum size of the patch to sample in each dimension
     cdef const intp_t[:] max_patch_dims                 # The maximum size of the patch to sample in each dimension
-    cdef const cnp.uint8_t[:] dim_contiguous            # A boolean array indicating whether each dimension is contiguous
+    cdef const uint8_t[:] dim_contiguous            # A boolean array indicating whether each dimension is contiguous
 
     # TODO: check if this works and is necessary for discontiguous data
     # cdef intp_t[:] stride_offsets                # The stride offsets for each dimension

sktree/tree/manifold/_morf_splitter.pyx

@@ -7,10 +7,6 @@
 
 import numpy as np
 
-cimport numpy as cnp
-
-cnp.import_array()
-
 from cython.operator cimport dereference as deref
 from libcpp.vector cimport vector
 
@@ -124,11 +120,11 @@ cdef class BestPatchSplitter(BaseDensePatchSplitter):
         intp_t min_samples_leaf,
         float64_t min_weight_leaf,
         object random_state,
-        const cnp.int8_t[:] monotonic_cst,
+        const int8_t[:] monotonic_cst,
         float64_t feature_combinations,
         const intp_t[:] min_patch_dims,
         const intp_t[:] max_patch_dims,
-        const cnp.uint8_t[:] dim_contiguous,
+        const uint8_t[:] dim_contiguous,
         const intp_t[:] data_dims,
         bytes boundary,
         const float32_t[:, :] feature_weight,

sktree/tree/unsupervised/_unsup_oblique_splitter.pxd

@@ -1,6 +1,5 @@
 import numpy as np
 
-cimport numpy as cnp
 from libcpp.vector cimport vector
 
 from ..._lib.sklearn.tree._splitter cimport SplitRecord

sktree/tree/unsupervised/_unsup_oblique_splitter.pyx

@@ -6,10 +6,6 @@
 
 import numpy as np
 
-cimport numpy as cnp
-
-cnp.import_array()
-
 from cython.operator cimport dereference as deref
 from libcpp.vector cimport vector
 

sktree/tree/unsupervised/_unsup_splitter.pyx

@@ -6,10 +6,6 @@
 
 import numpy as np
 
-cimport numpy as cnp
-
-cnp.import_array()
-
 from libc.string cimport memcpy
 
 from ..._lib.sklearn.tree._utils cimport RAND_R_MAX, rand_int