29 lines
1.0 KiB
Cython
29 lines
1.0 KiB
Cython
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#!python
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cimport numpy as cnp
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# Floating point/data type
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ctypedef cnp.float64_t DTYPE_t # WARNING: should match DTYPE in typedefs.pyx
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cdef enum:
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DTYPECODE = cnp.NPY_FLOAT64
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ITYPECODE = cnp.NPY_INTP
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INT32TYPECODE = cnp.NPY_INT32
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INT64TYPECODE = cnp.NPY_INT64
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# Index/integer type.
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# WARNING: ITYPE_t must be a signed integer type or you will have a bad time!
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ctypedef cnp.intp_t ITYPE_t # WARNING: should match ITYPE in typedefs.pyx
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ctypedef cnp.int32_t INT32TYPE_t # WARNING: should match INT32TYPE in typedefs.pyx
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ctypedef cnp.int64_t INT64TYPE_t # WARNING: should match INT32TYPE in typedefs.pyx
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# scipy matrices indices dtype (namely for indptr and indices arrays)
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#
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# Note that indices might need to be represented as cnp.int64_t.
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# Currently, we use Cython classes which do not handle fused types
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# so we hardcode this type to cnp.int32_t, supporting all but edge
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# cases.
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#
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# TODO: support cnp.int64_t for this case
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# See: https://github.com/scikit-learn/scikit-learn/issues/23653
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ctypedef cnp.int32_t SPARSE_INDEX_TYPE_t
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