ValueError:cython中的ndarray不是C连续的 [英] ValueError: ndarray is not C-contiguous in cython
问题描述
我在cython
中编写了以下函数来估计对数可能性
I have written the following function in cython
to estimate the log-likelihood
@cython.boundscheck(False)
@cython.wraparound(False)
def likelihood(double m,
double c,
np.ndarray[np.double_t, ndim=1, mode='c'] r_mpc not None,
np.ndarray[np.double_t, ndim=1, mode='c'] gtan not None,
np.ndarray[np.double_t, ndim=1, mode='c'] gcrs not None,
np.ndarray[np.double_t, ndim=1, mode='c'] shear_err not None,
np.ndarray[np.double_t, ndim=1, mode='c'] beta not None,
double rho_c,
np.ndarray[np.double_t, ndim=1, mode='c'] rho_c_sigma not None):
cdef double rscale = rscaleConstM(m, c,rho_c, 200)
cdef Py_ssize_t ngals = r_mpc.shape[0]
cdef np.ndarray[DTYPE_T, ndim=1, mode='c'] gamma_inf = Sh(r_mpc, c, rscale, rho_c_sigma)
cdef np.ndarray[DTYPE_T, ndim=1, mode='c'] kappa_inf = Kap(r_mpc, c, rscale, rho_c_sigma)
cdef double delta = 0.
cdef double modelg = 0.
cdef double modsig = 0.
cdef Py_ssize_t i
cdef DTYPE_T logProb = 0.
#calculate logprob
for i from ngals > i >= 0:
modelg = (beta[i]*gamma_inf[i] / (1 - beta[i]*kappa_inf[i]))
delta = gtan[i] - modelg
modsig = shear_err[i]
logProb = logProb -.5*(delta/modsig)**2 - logsqrt2pi - log(modsig)
return logProb
但是当我运行此函数的编译版本时,出现以下错误消息:
but when I run the compiled version of this function, I get the following error message:
File "Tools.pyx", line 3, in Tools.likelihood
def likelihood(double m,
ValueError: ndarray is not C-contiguous
我不太明白为什么会出现此问题?我将不胜感激获得任何有用的提示.
I could not quite understand why this problem occurs??!!! I will appreciate to get any useful tips.
推荐答案
在收到错误之前,请尝试打印要传递给likelihood
的numpy数组的flags
属性.您可能会看到类似的内容:
Just before you get the error, try printing the flags
attribute of the numpy array(s) you're passing to likelihood
. You'll probably see something like:
In [2]: foo.flags
Out[2]:
C_CONTIGUOUS : False
F_CONTIGUOUS : True
OWNDATA : True
WRITEABLE : True
ALIGNED : True
UPDATEIFCOPY : False
请注意在其上显示C_CONTIGUOUS : False
的位置,因为这就是问题所在.要解决此问题,只需将其转换为C顺序即可:
Note where it says C_CONTIGUOUS : False
, because that's the issue. To fix it, simply convert it to C-order:
In [6]: foo = foo.copy(order='C')
In [7]: foo.flags
Out[7]:
C_CONTIGUOUS : True
F_CONTIGUOUS : False
OWNDATA : True
WRITEABLE : True
ALIGNED : True
UPDATEIFCOPY : False
这篇关于ValueError:cython中的ndarray不是C连续的的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持IT屋!