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Bug fixes to support functionality on Windows
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@shz9
shz9 committed Jul 30, 2024
1 parent 36bcfa6 commit 4336efb
Showing 1 changed file with 21 additions and 21 deletions.
42 changes: 21 additions & 21 deletions magenpy/stats/ld/c_utils.pyx
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Original file line number Diff line number Diff line change
Expand Up @@ -11,12 +11,17 @@

from libc.math cimport exp
from libc.stdint cimport int64_t, int32_t
from cython cimport integral, floating
from cython cimport floating
cimport cython
import numpy as np
cimport numpy as cnp


ctypedef fused indptr_type:
cnp.int32_t
cnp.int64_t


ctypedef fused noncomplex_numeric:
cnp.int8_t
cnp.int16_t
Expand All @@ -42,7 +47,7 @@ cdef extern from "ld_utils.hpp" nogil:
int threads)


cpdef ld_dot(integral[::1] ld_indptr,
cpdef ld_dot(indptr_type[::1] ld_indptr,
noncomplex_numeric[::1] ld_data,
floating[::1] vec,
floating dq_scale = 1.,
Expand All @@ -68,7 +73,7 @@ cpdef ld_dot(integral[::1] ld_indptr,
return np.asarray(out)

cpdef find_tagging_variants(int[::1] variant_indices,
integral[::1] indptr,
indptr_type[::1] indptr,
noncomplex_numeric[::1] data,
noncomplex_numeric threshold):
"""
Expand All @@ -89,7 +94,7 @@ cdef noncomplex_numeric numeric_abs(noncomplex_numeric x) noexcept nogil:
return -x
return x

cpdef prune_ld_ut(integral[::1] indptr,
cpdef prune_ld_ut(indptr_type[::1] indptr,
noncomplex_numeric[::1] data,
noncomplex_numeric r_threshold):
"""
Expand Down Expand Up @@ -136,7 +141,7 @@ cpdef prune_ld_ut(integral[::1] indptr,
@cython.wraparound(False)
@cython.nonecheck(False)
@cython.exceptval(check=False)
cpdef get_symmetrized_indptr_with_mask(integral[::1] indptr,
cpdef get_symmetrized_indptr_with_mask(indptr_type[::1] indptr,
cnp.ndarray[cnp.npy_bool, ndim=1] mask):
"""
Given an index pointer array from an upper triangular CSR matrix, this function
Expand Down Expand Up @@ -195,7 +200,7 @@ cpdef get_symmetrized_indptr_with_mask(integral[::1] indptr,
@cython.wraparound(False)
@cython.nonecheck(False)
@cython.exceptval(check=False)
cpdef get_symmetrized_indptr(integral[::1] indptr):
cpdef get_symmetrized_indptr(indptr_type[::1] indptr):
"""
Given an index pointer array from an upper triangular CSR matrix, this function
computes the equivalent indptr for the symmetric matrix and returns also the
Expand Down Expand Up @@ -245,7 +250,7 @@ cpdef get_symmetrized_indptr(integral[::1] indptr):
@cython.wraparound(False)
@cython.nonecheck(False)
@cython.exceptval(check=False)
cpdef symmetrize_ut_csr_matrix_with_mask(integral[::1] indptr,
cpdef symmetrize_ut_csr_matrix_with_mask(indptr_type[::1] indptr,
noncomplex_numeric[::1] data,
cnp.ndarray[cnp.npy_bool, ndim=1] mask,
noncomplex_numeric diag_fill_value):
Expand Down Expand Up @@ -314,7 +319,7 @@ cpdef symmetrize_ut_csr_matrix_with_mask(integral[::1] indptr,
@cython.wraparound(False)
@cython.nonecheck(False)
@cython.exceptval(check=False)
cpdef symmetrize_ut_csr_matrix(integral[::1] indptr,
cpdef symmetrize_ut_csr_matrix(indptr_type[::1] indptr,
noncomplex_numeric[::1] data,
noncomplex_numeric diag_fill_value):
"""
Expand All @@ -339,7 +344,7 @@ cpdef symmetrize_ut_csr_matrix(integral[::1] indptr,
int64_t[::1] new_indptr = new_idx[0]
int32_t[::1] leftmost_col = new_idx[1]
int32_t curr_row, curr_col, curr_row_size
int32_t curr_data_idx, new_idx_1, new_idx_2, curr_shape=indptr.shape[0]-1
int32_t curr_data_idx, new_idx_1, new_idx_2, curr_shape=indptr.shape[0] - 1
noncomplex_numeric[::1] new_data = np.empty_like(data, shape=(new_idx[0][new_indptr.shape[0] - 1], ))

with nogil:
Expand Down Expand Up @@ -370,7 +375,7 @@ cpdef symmetrize_ut_csr_matrix(integral[::1] indptr,
return np.asarray(new_data), np.asarray(new_idx[0]), np.asarray(new_idx[1])


cpdef filter_ut_csr_matrix_inplace(integral[::1] indptr,
cpdef filter_ut_csr_matrix_inplace(indptr_type[::1] indptr,
noncomplex_numeric[::1] data,
char[::1] bool_mask,
int new_size):
Expand Down Expand Up @@ -430,7 +435,7 @@ cpdef filter_ut_csr_matrix_inplace(integral[::1] indptr,
@cython.wraparound(False)
@cython.nonecheck(False)
@cython.exceptval(check=False)
cpdef generate_data_mask_ut_csr_matrix(integral[::1] indptr, char[::1] bool_mask):
cpdef generate_data_mask_ut_csr_matrix(indptr_type[::1] indptr, char[::1] bool_mask):
"""
This is a utility function to generate a mask with the purpose of filtering
the data array of upper-triangular CSR matrices. The function also generates a new
Expand Down Expand Up @@ -482,7 +487,7 @@ cpdef generate_data_mask_ut_csr_matrix(integral[::1] indptr, char[::1] bool_mask
@cython.wraparound(False)
@cython.nonecheck(False)
@cython.exceptval(check=False)
cpdef expand_ranges(integral[::1] start, integral[::1] end, int64_t output_size):
cpdef expand_ranges(indptr_type[::1] start, indptr_type[::1] end, int64_t output_size):
"""
Given a set of start and end indices, expand them into one long vector that contains
the indices between all start and end positions.
Expand All @@ -494,14 +499,9 @@ cpdef expand_ranges(integral[::1] start, integral[::1] end, int64_t output_size)
"""

cdef:
integral i, j, size=start.shape[0]
indptr_type i, j, size=start.shape[0]
int64_t out_idx = 0
integral[::1] output

if integral is int:
output = np.empty(output_size, dtype=np.int32)
else:
output = np.empty(output_size, dtype=np.int64)
indptr_type[::1] output = np.empty_like(start, shape=(output_size, ))

with nogil:
for i in range(size):
Expand All @@ -516,7 +516,7 @@ cpdef expand_ranges(integral[::1] start, integral[::1] end, int64_t output_size)
@cython.nonecheck(False)
@cython.cdivision(True)
@cython.exceptval(check=False)
cpdef find_ld_block_boundaries(integral[:] pos, int[:, :] block_boundaries):
cpdef find_ld_block_boundaries(indptr_type[:] pos, int[:, :] block_boundaries):
"""
Find the LD boundaries for the blockwise estimator of LD, i.e., the
indices of the leftmost and rightmost neighbors for each SNP.
Expand All @@ -527,7 +527,7 @@ cpdef find_ld_block_boundaries(integral[:] pos, int[:, :] block_boundaries):

cdef:
int i, j, ldb_idx, B = block_boundaries.shape[0], M = pos.shape[0]
integral block_start, block_end
indptr_type block_start, block_end
int[:] v_min = np.zeros_like(pos, dtype=np.int32)
int[:] v_max = M*np.ones_like(pos, dtype=np.int32)

Expand Down

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