关于:
numpy.ravel(array,order ='C'):返回连续的扁平化数组(具有所有input-array元素且类型相同的一维数组)。仅在需要时才进行复制。
参数:
array : [array_like]Input array. order : [C-contiguous, F-contiguous, A-contiguous; optional] C-contiguous order in memory(last index varies the fastest) C order means that operating row-rise on the array will be slightly quicker FORTRAN-contiguous order in memory (first index varies the fastest). F order means that column-wise operations will be faster. ‘A’ means to read / write the elements in Fortran-like index order if, array is Fortran contiguous in memory, C-like order otherwise
返回:
Flattened array having same type as the Input array and and order as per choice.
代码1:显示array.ravel等效于reshape(-1,order = order)
# Python Program illustrating
# numpy.ravel() method
import numpy as geek
array = geek.arange(15).reshape(3, 5)
print("Original array : \n", array)
# Outpue comes like [ 0 1 2 ..., 12 13 14]
# as it is a long output, so it is the way of
# showing outptut in Python
print("\nravel() : ", array.ravel())
# This shows array.ravel is equivalent to reshape(-1, order=order).
print("\nnumpy.ravel() == numpy.reshape(-1)")
print("Reshaping array : ", array.reshape(-1))
输出:
Original array : [[ 0 1 2 3 4] [ 5 6 7 8 9] [10 11 12 13 14]] ravel() : [ 0 1 2 ..., 12 13 14] numpy.ravel() == numpy.reshape(-1) Reshaping array : [ 0 1 2 ..., 12 13 14]
代码2:显示排序操作
# Python Program illustrating
# numpy.ravel() method
import numpy as geek
array = geek.arange(15).reshape(3, 5)
print("Original array : \n", array)
# Outpue comes like [ 0 1 2 ..., 12 13 14]
# as it is a long output, so it is the way of
# showing outptut in Python
# About :
print("\nAbout numpy.ravel() : ", array.ravel)
print("\nnumpy.ravel() : ", array.ravel())
# Maintaining both 'A' and 'F' order
print("\nMaintains A Order : ", array.ravel(order = 'A'))
# K-order preserving the ordering
# 'K' means that is neither 'A' nor 'F'
array2 = geek.arange(12).reshape(2,3,2).swapaxes(1,2)
print("\narray2 \n", array2)
print("\nMaintains A Order : ", array2.ravel(order = 'K'))
输出:
Original array : [[ 0 1 2 3 4] [ 5 6 7 8 9] [10 11 12 13 14]] About numpy.ravel() : numpy.ravel() : [ 0 1 2 ..., 12 13 14] Maintains A Order : [ 0 1 2 ..., 12 13 14] array2 [[[ 0 2 4] [ 1 3 5]] [[ 6 8 10] [ 7 9 11]]] Maintains A Order : [ 0 1 2 ..., 9 10 11]
参考文献:
https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.ravel.html#numpy.ravel
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注:本文由纯净天空筛选整理自 numpy.ravel() in Python。非经特殊声明,原始代码版权归原作者所有,本译文未经允许或授权,请勿转载或复制。