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MAINT Use newest NumPy C API in tree._criterion #25615

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Merged
merged 2 commits into from
Feb 19, 2023
Merged

MAINT Use newest NumPy C API in tree._criterion #25615

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2e9b3be
MAINT Use newest NumPy C API in tree._criterion
thomasjpfan Feb 15, 2023
abdd8e5
FIX Use pointer for children
thomasjpfan Feb 15, 2023
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1 change: 1 addition & 0 deletions setup.py
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Original file line number Diff line number Diff line change
Expand Up @@ -110,6 +110,7 @@
"sklearn.svm._libsvm",
"sklearn.svm._libsvm_sparse",
"sklearn.svm._newrand",
"sklearn.tree._criterion",
"sklearn.tree._splitter",
"sklearn.tree._tree",
"sklearn.tree._utils",
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28 changes: 15 additions & 13 deletions sklearn/tree/_criterion.pyx
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Expand Up @@ -889,6 +889,8 @@ cdef class MAE(RegressionCriterion):

cdef cnp.ndarray left_child
cdef cnp.ndarray right_child
cdef void** left_child_ptr
cdef void** right_child_ptr
cdef DOUBLE_t[::1] node_medians

def __cinit__(self, SIZE_t n_outputs, SIZE_t n_samples):
Expand Down Expand Up @@ -923,6 +925,9 @@ cdef class MAE(RegressionCriterion):
self.left_child[k] = WeightedMedianCalculator(n_samples)
self.right_child[k] = WeightedMedianCalculator(n_samples)

self.left_child_ptr = <void**> cnp.PyArray_DATA(self.left_child)
self.right_child_ptr = <void**> cnp.PyArray_DATA(self.right_child)

cdef int init(
self,
const DOUBLE_t[:, ::1] y,
Expand Down Expand Up @@ -950,11 +955,8 @@ cdef class MAE(RegressionCriterion):
self.weighted_n_samples = weighted_n_samples
self.weighted_n_node_samples = 0.

cdef void** left_child
cdef void** right_child

left_child = <void**> self.left_child.data
right_child = <void**> self.right_child.data
cdef void** left_child = self.left_child_ptr
cdef void** right_child = self.right_child_ptr

for k in range(self.n_outputs):
(<WeightedMedianCalculator> left_child[k]).reset()
Expand Down Expand Up @@ -991,8 +993,8 @@ cdef class MAE(RegressionCriterion):
cdef DOUBLE_t value
cdef DOUBLE_t weight

cdef void** left_child = <void**> self.left_child.data
cdef void** right_child = <void**> self.right_child.data
cdef void** left_child = self.left_child_ptr
cdef void** right_child = self.right_child_ptr

self.weighted_n_left = 0.0
self.weighted_n_right = self.weighted_n_node_samples
Expand Down Expand Up @@ -1024,8 +1026,8 @@ cdef class MAE(RegressionCriterion):

cdef DOUBLE_t value
cdef DOUBLE_t weight
cdef void** left_child = <void**> self.left_child.data
cdef void** right_child = <void**> self.right_child.data
cdef void** left_child = self.left_child_ptr
cdef void** right_child = self.right_child_ptr

# reverse reset the WeightedMedianCalculators, right should have no
# elements and left should have all elements.
Expand All @@ -1049,8 +1051,8 @@ cdef class MAE(RegressionCriterion):
cdef const DOUBLE_t[:] sample_weight = self.sample_weight
cdef const SIZE_t[:] sample_indices = self.sample_indices

cdef void** left_child = <void**> self.left_child.data
cdef void** right_child = <void**> self.right_child.data
cdef void** left_child = self.left_child_ptr
cdef void** right_child = self.right_child_ptr

cdef SIZE_t pos = self.pos
cdef SIZE_t end = self.end
Expand Down Expand Up @@ -1147,8 +1149,8 @@ cdef class MAE(RegressionCriterion):
cdef DOUBLE_t impurity_left = 0.0
cdef DOUBLE_t impurity_right = 0.0

cdef void** left_child = <void**> self.left_child.data
cdef void** right_child = <void**> self.right_child.data
cdef void** left_child = self.left_child_ptr
cdef void** right_child = self.right_child_ptr

for k in range(self.n_outputs):
median = (<WeightedMedianCalculator> left_child[k]).get_median()
Expand Down