Python/numpy之ravel()多维数据展平函数

Python/numpy之ravel()多维数据展平函数

可参考官方文档numpy.ravel或末尾摘抄内容

ravel()将多维数据展平为一维数据，可以选择不同的数据索引方式（见文档参数四个可选值）
使用：

>>> import numpy as np
>>> a = np.array([[1,2,3],[4,5,6]])
>>> a
array([[1, 2, 3],
       [4, 5, 6]])
>>> a.ravel()
array([1, 2, 3, 4, 5, 6])

除此外，ravel() 与flatten()都是展平数据但是有一些不同，参考另一篇Python/numpy之ravel() 与flatten()

numpy.ravel

numpy.ravel(a, order='C')[source]
Return a contiguous flattened array.
A 1-D array, containing the elements of the input, is returned. A copy is made only if needed.
As of NumPy 1.10, the returned array will have the same type as the input array. (for example, a masked array will be returned for a masked array input)
Parameters
aarray_like
Input array. The elements in a are read in the order specified by order, and packed as a 1-D array.
order{‘C’,’F’, ‘A’, ‘K’}, optional
The elements of a are read using this index order. ‘C’ means to index the elements in row-major, C-style order, with the last axis index changing fastest, back to the first axis index changing slowest. ‘F’ means to index the elements in column-major, Fortran-style order, with the first index changing fastest, and the last index changing slowest. Note that the ‘C’ and ‘F’ options take no account of the memory layout of the underlying array, and only refer to the order of axis indexing. ‘A’ means to read the elements in Fortran-like index order if a is Fortran contiguous in memory, C-like order otherwise. ‘K’ means to read the elements in the order they occur in memory, except for reversing the data when strides are negative. By default, ‘C’ index order is used.
Returns
y array_like
y is an array of the same subtype as a, with shape (a.size,). Note that matrices are special cased for backward compatibility, if a is a matrix, then y is a 1-D ndarray.