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Commit dfda968

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MAINT replace cnp.ndarray with memory views in _fast_dict (#25754)
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+23
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‎sklearn/utils/_fast_dict.pyx

Copy file name to clipboardExpand all lines: sklearn/utils/_fast_dict.pyx
+7-13Lines changed: 7 additions & 13 deletions
Original file line numberDiff line numberDiff line change
@@ -12,13 +12,6 @@ from libcpp.map cimport map as cpp_map
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import numpy as np
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# Import the C-level symbols of numpy
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cimport numpy as cnp
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# Numpy must be initialized. When using numpy from C or Cython you must
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# _always_ do that, or you will have segfaults
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cnp.import_array()
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#DTYPE = np.float64
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#ctypedef cnp.float64_t DTYPE_t
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@@ -35,8 +28,11 @@ cnp.import_array()
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cdef class IntFloatDict:
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38-
def __init__(self, cnp.ndarray[ITYPE_t, ndim=1] keys,
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cnp.ndarray[DTYPE_t, ndim=1] values):
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def __init__(
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self,
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ITYPE_t[:] keys,
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DTYPE_t[:] values,
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):
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cdef int i
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cdef int size = values.size
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# Should check that sizes for keys and values are equal, and
@@ -91,10 +87,8 @@ cdef class IntFloatDict:
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The values of the data points
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"""
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cdef int size = self.my_map.size()
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cdef cnp.ndarray[ITYPE_t, ndim=1] keys = np.empty(size,
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dtype=np.intp)
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cdef cnp.ndarray[DTYPE_t, ndim=1] values = np.empty(size,
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dtype=np.float64)
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keys = np.empty(size, dtype=np.intp)
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values = np.empty(size, dtype=np.float64)
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self._to_arrays(keys, values)
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return keys, values
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‎sklearn/utils/tests/test_fast_dict.py

Copy file name to clipboardExpand all lines: sklearn/utils/tests/test_fast_dict.py
+16Lines changed: 16 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -1,6 +1,7 @@
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""" Test fast_dict.
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"""
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import numpy as np
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from numpy.testing import assert_array_equal, assert_allclose
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from sklearn.utils._fast_dict import IntFloatDict, argmin
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@@ -29,3 +30,18 @@ def test_int_float_dict_argmin():
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values = np.arange(100, dtype=np.float64)
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d = IntFloatDict(keys, values)
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assert argmin(d) == (0, 0)
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def test_to_arrays():
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# Test that an IntFloatDict is converted into arrays
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# of keys and values correctly
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keys_in = np.array([1, 2, 3], dtype=np.intp)
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values_in = np.array([4, 5, 6], dtype=np.float64)
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d = IntFloatDict(keys_in, values_in)
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keys_out, values_out = d.to_arrays()
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assert keys_out.dtype == keys_in.dtype
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assert values_in.dtype == values_out.dtype
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assert_array_equal(keys_out, keys_in)
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assert_allclose(values_out, values_in)

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