针对pulse-transit的工具
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dist/client/sklearn/metrics/_dist_metrics.cp310-win_amd64.pyd
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dist/client/sklearn/metrics/_dist_metrics.pxd
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cimport numpy as np
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from libc.math cimport sqrt, exp
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from ..utils._typedefs cimport DTYPE_t, ITYPE_t
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######################################################################
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# Inline distance functions
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#
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# We use these for the default (euclidean) case so that they can be
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# inlined. This leads to faster computation for the most common case
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cdef inline DTYPE_t euclidean_dist(const DTYPE_t* x1, const DTYPE_t* x2,
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ITYPE_t size) nogil except -1:
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cdef DTYPE_t tmp, d=0
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cdef np.intp_t j
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for j in range(size):
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tmp = x1[j] - x2[j]
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d += tmp * tmp
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return sqrt(d)
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cdef inline DTYPE_t euclidean_rdist(const DTYPE_t* x1, const DTYPE_t* x2,
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ITYPE_t size) nogil except -1:
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cdef DTYPE_t tmp, d=0
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cdef np.intp_t j
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for j in range(size):
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tmp = x1[j] - x2[j]
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d += tmp * tmp
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return d
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cdef inline DTYPE_t euclidean_dist_to_rdist(const DTYPE_t dist) nogil except -1:
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return dist * dist
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cdef inline DTYPE_t euclidean_rdist_to_dist(const DTYPE_t dist) nogil except -1:
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return sqrt(dist)
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######################################################################
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# DistanceMetric base class
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cdef class DistanceMetric:
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# The following attributes are required for a few of the subclasses.
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# we must define them here so that cython's limited polymorphism will work.
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# Because we don't expect to instantiate a lot of these objects, the
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# extra memory overhead of this setup should not be an issue.
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cdef DTYPE_t p
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cdef DTYPE_t[::1] vec
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cdef DTYPE_t[:, ::1] mat
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cdef ITYPE_t size
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cdef object func
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cdef object kwargs
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cdef DTYPE_t dist(self, const DTYPE_t* x1, const DTYPE_t* x2,
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ITYPE_t size) nogil except -1
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cdef DTYPE_t rdist(self, const DTYPE_t* x1, const DTYPE_t* x2,
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ITYPE_t size) nogil except -1
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cdef int pdist(self, const DTYPE_t[:, ::1] X, DTYPE_t[:, ::1] D) except -1
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cdef int cdist(self, const DTYPE_t[:, ::1] X, const DTYPE_t[:, ::1] Y,
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DTYPE_t[:, ::1] D) except -1
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cdef DTYPE_t _rdist_to_dist(self, DTYPE_t rdist) nogil except -1
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cdef DTYPE_t _dist_to_rdist(self, DTYPE_t dist) nogil except -1
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######################################################################
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# DatasetsPair base class
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cdef class DatasetsPair:
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cdef DistanceMetric distance_metric
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cdef ITYPE_t n_samples_X(self) nogil
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cdef ITYPE_t n_samples_Y(self) nogil
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cdef DTYPE_t dist(self, ITYPE_t i, ITYPE_t j) nogil
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cdef DTYPE_t surrogate_dist(self, ITYPE_t i, ITYPE_t j) nogil
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cdef class DenseDenseDatasetsPair(DatasetsPair):
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cdef:
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const DTYPE_t[:, ::1] X
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const DTYPE_t[:, ::1] Y
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ITYPE_t d
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dist/client/sklearn/metrics/_pairwise_distances_reduction.cp310-win_amd64.pyd
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dist/client/sklearn/metrics/_pairwise_distances_reduction.cp310-win_amd64.pyd
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dist/client/sklearn/metrics/_pairwise_fast.cp310-win_amd64.pyd
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dist/client/sklearn/metrics/_pairwise_fast.cp310-win_amd64.pyd
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dist/client/sklearn/metrics/cluster/_expected_mutual_info_fast.cp310-win_amd64.pyd
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dist/client/sklearn/metrics/cluster/_expected_mutual_info_fast.cp310-win_amd64.pyd
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