numpy.ravel_multi_index()函数| Python
numpy.ravel_multi_index()
函数将索引数组的元组转换为平面索引数组,将边界模式应用于多索引。
Syntax : numpy.ravel_multi_index(multi_index, dims, mode = ‘raise’, order = ‘C)
Parameters :
multi_index : [tuple of array_like] A tuple of integer arrays, one array for each dimension.
dims : [tuple of ints] The shape of array into which the indices from multi_index apply.
mode : [{‘raise’, ‘wrap’, ‘clip’}, optional] Specifies how out-of-bounds indices are handled. Can specify either one mode or a tuple of modes, one mode per index.
‘raise’ – raise an error (default)
‘wrap’ – wrap around
‘clip’ – clip to the range
In ‘clip’ mode, a negative index that would normally wrap will clip to 0 instead.
order : [{‘C’, ‘F’}, optional] Determines whether the multi-index should be viewed as indexing in row-major (C-style) or column-major (Fortran-style) order.
Return : [ndarray] An array of indices into the flattened version of an array of dimensions dims.
代码#1:
# Python program explaining
# numpy.ravel_multi_index() function
# importing numpy as geek
import numpy as geek
arr = geek.array([[3, 6, 6], [4, 5, 1]])
gfg = geek.ravel_multi_index(arr, (7, 6))
print(gfg)
输出 :
[22 41 37]
代码#2:
# Python program explaining
# numpy.ravel_multi_index() function
# importing numpy as geek
import numpy as geek
arr = geek.array([[3, 6, 6], [4, 5, 1]])
gfg = geek.ravel_multi_index(arr, (7, 6), order = 'F')
print(gfg)
输出 :
[31 41 13]
代码#3:
# Python program explaining
# numpy.ravel_multi_index() function
# importing numpy as geek
import numpy as geek
arr = geek.array([[3, 6, 6], [4, 5, 1]])
gfg = geek.ravel_multi_index(arr, (7, 6), mode = 'clip')
print(gfg)
输出 :
[22 41 37]