使用 Cython,有没有办法编写适用于不同维度数组的快速通用函数?例如对于这个简单的去锯齿函数案例:
import numpy as np
cimport numpy as np
ctypedef np.uint8_t DTYPEb_t
ctypedef np.complex128_t DTYPEc_t
def dealiasing1D(DTYPEc_t[:, :] data,
DTYPEb_t[:] where_dealiased):
"""Dealiasing data for 1D solvers."""
cdef Py_ssize_t ik, i0, nk, n0
nk = data.shape[0]
n0 = data.shape[1]
for ik in range(nk):
for i0 in range(n0):
if where_dealiased[i0]:
data[ik, i0] = 0.
def dealiasing2D(DTYPEc_t[:, :, :] data,
DTYPEb_t[:, :] where_dealiased):
"""Dealiasing data for 2D solvers."""
cdef Py_ssize_t ik, i0, i1, nk, n0, n1
nk = data.shape[0]
n0 = data.shape[1]
n1 = data.shape[2]
for ik in range(nk):
for i0 in range(n0):
for i1 in range(n1):
if where_dealiased[i0, i1]:
data[ik, i0, i1] = 0.
def dealiasing3D(DTYPEc_t[:, :, :, :] data,
DTYPEb_t[:, :, :] where_dealiased):
"""Dealiasing data for 3D solvers."""
cdef Py_ssize_t ik, i0, i1, i2, nk, n0, n1, n2
nk = data.shape[0]
n0 = data.shape[1]
n1 = data.shape[2]
n2 = data.shape[3]
for ik in range(nk):
for i0 in range(n0):
for i1 in range(n1):
for i2 in range(n2):
if where_dealiased[i0, i1, i2]:
data[ik, i0, i1, i2] = 0.
在这里,我需要针对一维、二维和三维情况的三个函数。有没有一种好的方法来编写一个可以为所有(合理的)维度完成工作的函数?
PS:在这里,我尝试使用 memoryviews,但我不确定这是正确的方法。我很惊讶命令if where_dealiased[i0]: data[ik, i0] = 0.
生成的带注释的 html 中的行不是白色的cython -a
。有什么不对?