gtsam/python/gtsam_eigency/conversions.pyx

cimport cython
import numpy as np
from numpy.lib.stride_tricks import as_strided

@cython.boundscheck(False)
cdef np.ndarray[double, ndim=2] ndarray_double_C(double *data, long rows, long cols, long row_stride, long col_stride):
    cdef double[:,:] mem_view = <double[:rows,:cols]>data
    dtype = 'double'
    cdef int itemsize = np.dtype(dtype).itemsize
    return as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[double, ndim=2] ndarray_double_F(double *data, long rows, long cols, long row_stride, long col_stride):
    cdef double[::1,:] mem_view = <double[:rows:1,:cols]>data
    dtype = 'double'
    cdef int itemsize = np.dtype(dtype).itemsize
    return as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize])

@cython.boundscheck(False)
cdef np.ndarray[double, ndim=2] ndarray_copy_double_C(const double *data, long rows, long cols, long row_stride, long col_stride):
    cdef double[:,:] mem_view = <double[:rows,:cols]>data
    dtype = 'double'
    cdef int itemsize = np.dtype(dtype).itemsize
    return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[double, ndim=2] ndarray_copy_double_F(const double *data, long rows, long cols, long row_stride, long col_stride):
    cdef double[::1,:] mem_view = <double[:rows:1,:cols]>data
    dtype = 'double'
    cdef int itemsize = np.dtype(dtype).itemsize
    return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize]))


@cython.boundscheck(False)
cdef np.ndarray[float, ndim=2] ndarray_float_C(float *data, long rows, long cols, long row_stride, long col_stride):
    cdef float[:,:] mem_view = <float[:rows,:cols]>data
    dtype = 'float'
    cdef int itemsize = np.dtype(dtype).itemsize
    return as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[float, ndim=2] ndarray_float_F(float *data, long rows, long cols, long row_stride, long col_stride):
    cdef float[::1,:] mem_view = <float[:rows:1,:cols]>data
    dtype = 'float'
    cdef int itemsize = np.dtype(dtype).itemsize
    return as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize])

@cython.boundscheck(False)
cdef np.ndarray[float, ndim=2] ndarray_copy_float_C(const float *data, long rows, long cols, long row_stride, long col_stride):
    cdef float[:,:] mem_view = <float[:rows,:cols]>data
    dtype = 'float'
    cdef int itemsize = np.dtype(dtype).itemsize
    return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[float, ndim=2] ndarray_copy_float_F(const float *data, long rows, long cols, long row_stride, long col_stride):
    cdef float[::1,:] mem_view = <float[:rows:1,:cols]>data
    dtype = 'float'
    cdef int itemsize = np.dtype(dtype).itemsize
    return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize]))


@cython.boundscheck(False)
cdef np.ndarray[long, ndim=2] ndarray_long_C(long *data, long rows, long cols, long row_stride, long col_stride):
    cdef long[:,:] mem_view = <long[:rows,:cols]>data
    dtype = 'int_'
    cdef int itemsize = np.dtype(dtype).itemsize
    return as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[long, ndim=2] ndarray_long_F(long *data, long rows, long cols, long row_stride, long col_stride):
    cdef long[::1,:] mem_view = <long[:rows:1,:cols]>data
    dtype = 'int_'
    cdef int itemsize = np.dtype(dtype).itemsize
    return as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize])

@cython.boundscheck(False)
cdef np.ndarray[long, ndim=2] ndarray_copy_long_C(const long *data, long rows, long cols, long row_stride, long col_stride):
    cdef long[:,:] mem_view = <long[:rows,:cols]>data
    dtype = 'int_'
    cdef int itemsize = np.dtype(dtype).itemsize
    return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[long, ndim=2] ndarray_copy_long_F(const long *data, long rows, long cols, long row_stride, long col_stride):
    cdef long[::1,:] mem_view = <long[:rows:1,:cols]>data
    dtype = 'int_'
    cdef int itemsize = np.dtype(dtype).itemsize
    return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize]))


@cython.boundscheck(False)
cdef np.ndarray[unsigned long, ndim=2] ndarray_ulong_C(unsigned long *data, long rows, long cols, long row_stride, long col_stride):
    cdef unsigned long[:,:] mem_view = <unsigned long[:rows,:cols]>data
    dtype = 'uint'
    cdef int itemsize = np.dtype(dtype).itemsize
    return as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[unsigned long, ndim=2] ndarray_ulong_F(unsigned long *data, long rows, long cols, long row_stride, long col_stride):
    cdef unsigned long[::1,:] mem_view = <unsigned long[:rows:1,:cols]>data
    dtype = 'uint'
    cdef int itemsize = np.dtype(dtype).itemsize
    return as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize])

@cython.boundscheck(False)
cdef np.ndarray[unsigned long, ndim=2] ndarray_copy_ulong_C(const unsigned long *data, long rows, long cols, long row_stride, long col_stride):
    cdef unsigned long[:,:] mem_view = <unsigned long[:rows,:cols]>data
    dtype = 'uint'
    cdef int itemsize = np.dtype(dtype).itemsize
    return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[unsigned long, ndim=2] ndarray_copy_ulong_F(const unsigned long *data, long rows, long cols, long row_stride, long col_stride):
    cdef unsigned long[::1,:] mem_view = <unsigned long[:rows:1,:cols]>data
    dtype = 'uint'
    cdef int itemsize = np.dtype(dtype).itemsize
    return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize]))


@cython.boundscheck(False)
cdef np.ndarray[int, ndim=2] ndarray_int_C(int *data, long rows, long cols, long row_stride, long col_stride):
    cdef int[:,:] mem_view = <int[:rows,:cols]>data
    dtype = 'int'
    cdef int itemsize = np.dtype(dtype).itemsize
    return as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[int, ndim=2] ndarray_int_F(int *data, long rows, long cols, long row_stride, long col_stride):
    cdef int[::1,:] mem_view = <int[:rows:1,:cols]>data
    dtype = 'int'
    cdef int itemsize = np.dtype(dtype).itemsize
    return as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize])

@cython.boundscheck(False)
cdef np.ndarray[int, ndim=2] ndarray_copy_int_C(const int *data, long rows, long cols, long row_stride, long col_stride):
    cdef int[:,:] mem_view = <int[:rows,:cols]>data
    dtype = 'int'
    cdef int itemsize = np.dtype(dtype).itemsize
    return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[int, ndim=2] ndarray_copy_int_F(const int *data, long rows, long cols, long row_stride, long col_stride):
    cdef int[::1,:] mem_view = <int[:rows:1,:cols]>data
    dtype = 'int'
    cdef int itemsize = np.dtype(dtype).itemsize
    return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize]))


@cython.boundscheck(False)
cdef np.ndarray[unsigned int, ndim=2] ndarray_uint_C(unsigned int *data, long rows, long cols, long row_stride, long col_stride):
    cdef unsigned int[:,:] mem_view = <unsigned int[:rows,:cols]>data
    dtype = 'uint'
    cdef int itemsize = np.dtype(dtype).itemsize
    return as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[unsigned int, ndim=2] ndarray_uint_F(unsigned int *data, long rows, long cols, long row_stride, long col_stride):
    cdef unsigned int[::1,:] mem_view = <unsigned int[:rows:1,:cols]>data
    dtype = 'uint'
    cdef int itemsize = np.dtype(dtype).itemsize
    return as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize])

@cython.boundscheck(False)
cdef np.ndarray[unsigned int, ndim=2] ndarray_copy_uint_C(const unsigned int *data, long rows, long cols, long row_stride, long col_stride):
    cdef unsigned int[:,:] mem_view = <unsigned int[:rows,:cols]>data
    dtype = 'uint'
    cdef int itemsize = np.dtype(dtype).itemsize
    return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[unsigned int, ndim=2] ndarray_copy_uint_F(const unsigned int *data, long rows, long cols, long row_stride, long col_stride):
    cdef unsigned int[::1,:] mem_view = <unsigned int[:rows:1,:cols]>data
    dtype = 'uint'
    cdef int itemsize = np.dtype(dtype).itemsize
    return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize]))


@cython.boundscheck(False)
cdef np.ndarray[short, ndim=2] ndarray_short_C(short *data, long rows, long cols, long row_stride, long col_stride):
    cdef short[:,:] mem_view = <short[:rows,:cols]>data
    dtype = 'short'
    cdef int itemsize = np.dtype(dtype).itemsize
    return as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[short, ndim=2] ndarray_short_F(short *data, long rows, long cols, long row_stride, long col_stride):
    cdef short[::1,:] mem_view = <short[:rows:1,:cols]>data
    dtype = 'short'
    cdef int itemsize = np.dtype(dtype).itemsize
    return as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize])

@cython.boundscheck(False)
cdef np.ndarray[short, ndim=2] ndarray_copy_short_C(const short *data, long rows, long cols, long row_stride, long col_stride):
    cdef short[:,:] mem_view = <short[:rows,:cols]>data
    dtype = 'short'
    cdef int itemsize = np.dtype(dtype).itemsize
    return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[short, ndim=2] ndarray_copy_short_F(const short *data, long rows, long cols, long row_stride, long col_stride):
    cdef short[::1,:] mem_view = <short[:rows:1,:cols]>data
    dtype = 'short'
    cdef int itemsize = np.dtype(dtype).itemsize
    return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize]))


@cython.boundscheck(False)
cdef np.ndarray[unsigned short, ndim=2] ndarray_ushort_C(unsigned short *data, long rows, long cols, long row_stride, long col_stride):
    cdef unsigned short[:,:] mem_view = <unsigned short[:rows,:cols]>data
    dtype = 'ushort'
    cdef int itemsize = np.dtype(dtype).itemsize
    return as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[unsigned short, ndim=2] ndarray_ushort_F(unsigned short *data, long rows, long cols, long row_stride, long col_stride):
    cdef unsigned short[::1,:] mem_view = <unsigned short[:rows:1,:cols]>data
    dtype = 'ushort'
    cdef int itemsize = np.dtype(dtype).itemsize
    return as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize])

@cython.boundscheck(False)
cdef np.ndarray[unsigned short, ndim=2] ndarray_copy_ushort_C(const unsigned short *data, long rows, long cols, long row_stride, long col_stride):
    cdef unsigned short[:,:] mem_view = <unsigned short[:rows,:cols]>data
    dtype = 'ushort'
    cdef int itemsize = np.dtype(dtype).itemsize
    return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[unsigned short, ndim=2] ndarray_copy_ushort_F(const unsigned short *data, long rows, long cols, long row_stride, long col_stride):
    cdef unsigned short[::1,:] mem_view = <unsigned short[:rows:1,:cols]>data
    dtype = 'ushort'
    cdef int itemsize = np.dtype(dtype).itemsize
    return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize]))


@cython.boundscheck(False)
cdef np.ndarray[signed char, ndim=2] ndarray_schar_C(signed char *data, long rows, long cols, long row_stride, long col_stride):
    cdef signed char[:,:] mem_view = <signed char[:rows,:cols]>data
    dtype = 'int8'
    cdef int itemsize = np.dtype(dtype).itemsize
    return as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[signed char, ndim=2] ndarray_schar_F(signed char *data, long rows, long cols, long row_stride, long col_stride):
    cdef signed char[::1,:] mem_view = <signed char[:rows:1,:cols]>data
    dtype = 'int8'
    cdef int itemsize = np.dtype(dtype).itemsize
    return as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize])

@cython.boundscheck(False)
cdef np.ndarray[signed char, ndim=2] ndarray_copy_schar_C(const signed char *data, long rows, long cols, long row_stride, long col_stride):
    cdef signed char[:,:] mem_view = <signed char[:rows,:cols]>data
    dtype = 'int8'
    cdef int itemsize = np.dtype(dtype).itemsize
    return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[signed char, ndim=2] ndarray_copy_schar_F(const signed char *data, long rows, long cols, long row_stride, long col_stride):
    cdef signed char[::1,:] mem_view = <signed char[:rows:1,:cols]>data
    dtype = 'int8'
    cdef int itemsize = np.dtype(dtype).itemsize
    return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize]))


@cython.boundscheck(False)
cdef np.ndarray[unsigned char, ndim=2] ndarray_uchar_C(unsigned char *data, long rows, long cols, long row_stride, long col_stride):
    cdef unsigned char[:,:] mem_view = <unsigned char[:rows,:cols]>data
    dtype = 'uint8'
    cdef int itemsize = np.dtype(dtype).itemsize
    return as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[unsigned char, ndim=2] ndarray_uchar_F(unsigned char *data, long rows, long cols, long row_stride, long col_stride):
    cdef unsigned char[::1,:] mem_view = <unsigned char[:rows:1,:cols]>data
    dtype = 'uint8'
    cdef int itemsize = np.dtype(dtype).itemsize
    return as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize])

@cython.boundscheck(False)
cdef np.ndarray[unsigned char, ndim=2] ndarray_copy_uchar_C(const unsigned char *data, long rows, long cols, long row_stride, long col_stride):
    cdef unsigned char[:,:] mem_view = <unsigned char[:rows,:cols]>data
    dtype = 'uint8'
    cdef int itemsize = np.dtype(dtype).itemsize
    return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[unsigned char, ndim=2] ndarray_copy_uchar_F(const unsigned char *data, long rows, long cols, long row_stride, long col_stride):
    cdef unsigned char[::1,:] mem_view = <unsigned char[:rows:1,:cols]>data
    dtype = 'uint8'
    cdef int itemsize = np.dtype(dtype).itemsize
    return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize]))


@cython.boundscheck(False)
cdef np.ndarray[np.complex128_t, ndim=2] ndarray_complex_double_C(np.complex128_t *data, long rows, long cols, long row_stride, long col_stride):
    cdef np.complex128_t[:,:] mem_view = <np.complex128_t[:rows,:cols]>data
    dtype = 'complex128'
    cdef int itemsize = np.dtype(dtype).itemsize
    return as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[np.complex128_t, ndim=2] ndarray_complex_double_F(np.complex128_t *data, long rows, long cols, long row_stride, long col_stride):
    cdef np.complex128_t[::1,:] mem_view = <np.complex128_t[:rows:1,:cols]>data
    dtype = 'complex128'
    cdef int itemsize = np.dtype(dtype).itemsize
    return as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize])

@cython.boundscheck(False)
cdef np.ndarray[np.complex128_t, ndim=2] ndarray_copy_complex_double_C(const np.complex128_t *data, long rows, long cols, long row_stride, long col_stride):
    cdef np.complex128_t[:,:] mem_view = <np.complex128_t[:rows,:cols]>data
    dtype = 'complex128'
    cdef int itemsize = np.dtype(dtype).itemsize
    return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[np.complex128_t, ndim=2] ndarray_copy_complex_double_F(const np.complex128_t *data, long rows, long cols, long row_stride, long col_stride):
    cdef np.complex128_t[::1,:] mem_view = <np.complex128_t[:rows:1,:cols]>data
    dtype = 'complex128'
    cdef int itemsize = np.dtype(dtype).itemsize
    return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize]))


@cython.boundscheck(False)
cdef np.ndarray[np.complex64_t, ndim=2] ndarray_complex_float_C(np.complex64_t *data, long rows, long cols, long row_stride, long col_stride):
    cdef np.complex64_t[:,:] mem_view = <np.complex64_t[:rows,:cols]>data
    dtype = 'complex64'
    cdef int itemsize = np.dtype(dtype).itemsize
    return as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[np.complex64_t, ndim=2] ndarray_complex_float_F(np.complex64_t *data, long rows, long cols, long row_stride, long col_stride):
    cdef np.complex64_t[::1,:] mem_view = <np.complex64_t[:rows:1,:cols]>data
    dtype = 'complex64'
    cdef int itemsize = np.dtype(dtype).itemsize
    return as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize])

@cython.boundscheck(False)
cdef np.ndarray[np.complex64_t, ndim=2] ndarray_copy_complex_float_C(const np.complex64_t *data, long rows, long cols, long row_stride, long col_stride):
    cdef np.complex64_t[:,:] mem_view = <np.complex64_t[:rows,:cols]>data
    dtype = 'complex64'
    cdef int itemsize = np.dtype(dtype).itemsize
    return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[np.complex64_t, ndim=2] ndarray_copy_complex_float_F(const np.complex64_t *data, long rows, long cols, long row_stride, long col_stride):
    cdef np.complex64_t[::1,:] mem_view = <np.complex64_t[:rows:1,:cols]>data
    dtype = 'complex64'
    cdef int itemsize = np.dtype(dtype).itemsize
    return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize]))