0

我发现了这段不错的代码，我想用 Cython 重写它来学习 Cython。此外，我想绘制 python for loop、numpy 和 cython 之间的速度比较增益。这就是我目前对大约 40k 行的比较结果：

40k_rows

def sliding_window_slicing(a, no_items, item_type=0):
    """This method perfoms sliding window slicing of numpy arrays

    Parameters
    ----------
    a : numpy
        An array to be slided in subarrays
    no_items : int
        Number of sliced arrays or elements in sliced arrays
    item_type: int
        Indicates if no_items is number of sliced arrays (item_type=0) or
        number of elements in sliced array (item_type=1), by default 0

    Return
    ------
    numpy
        Sliced numpy array
    """
    if item_type == 0:
        no_slices = no_items
        no_elements = len(a) + 1 - no_slices
        if no_elements <=0:
            raise ValueError('Sliding slicing not possible, no_items is larger than ' + str(len(a)))
    else:
        no_elements = no_items                
        no_slices = len(a) - no_elements + 1
        if no_slices <=0:
            raise ValueError('Sliding slicing not possible, no_items is larger than ' + str(len(a)))

    subarray_shape = a.shape[1:]
    shape_cfg = (no_slices, no_elements) + subarray_shape
    strides_cfg = (a.strides[0],) + a.strides
    as_strided = np.lib.stride_tricks.as_strided #shorthand
    return as_strided(a, shape=shape_cfg, strides=strides_cfg)

我试过这个，但我无法决定我必须使用的数据类型：

%%cython -a 
#cython: boundscheck=False, wraparound=False, cdivision=True, nonecheck=False

import numpy as np
cimport numpy as np
cimport cython


cpdef np.ndarray cython_sliding_window_slicing(long[:,:] a, long no_items, int item_type=0):

    cdef:
        long no_slices, no_elements
        long subarray_shape
        (long,long) shape_cfg 
        np.ndarray strides_cfg

    if item_type == 0:
        no_slices = no_items
        no_elements = len(a) + 1 - no_slices

    else:
        no_elements = no_items                
        no_slices = len(a) - no_elements + 1

    subarray_shape = a.shape[1]
    shape_cfg = (no_slices, no_elements) + (subarray_shape,0)
    strides_cfg = (a.strides[0],) + a.strides
    return np.lib.stride_tricks.as_strided(a, shape=shape_cfg, strides=strides_cfg)

在我收到错误的那一刻：Expected a tuple of size 2, got tuple 我在函数上使用的数组是这样的：example_array = np.random.randint(1000,size=(40, 8))

我希望有人可以帮助并向我解释我需要更改什么以及如何调试脚本（使用 jupyter notebook？）。

谢谢你的帮助！

4

0 回答 0