如何遍历此n维数据集? [英] How to iterate over this n-dimensional dataset?
问题描述
我有一个dataset
,它有4个维度(目前...),我需要对其进行迭代.
I have a dataset
which has 4 dimensions (for now...) and I need to iterate over it.
要访问dataset
中的值,请执行以下操作:
To access a value in the dataset
, I do this:
value = dataset[i,j,k,l]
现在,我可以获取dataset
的shape
:
shape = [4,5,2,6]
shape
中的值表示尺寸的长度.
The values in shape
represent the length of the dimension.
在给定维数的情况下,如何遍历数据集中的所有元素?这是一个示例:
How, given the number of dimensions, can I iterate over all the elements in my dataset? Here is an example:
for i in range(shape[0]):
for j in range(shape[1]):
for k in range(shape[2]):
for l in range(shape[3]):
print('BOOM')
value = dataset[i,j,k,l]
将来,shape
可能会更改.因此,例如,shape
可能包含10个元素,而不是当前的4个.
In the future, the shape
may change. So for example, shape
may have 10 elements rather than the current 4.
使用Python 3可以做到这一点吗?
Is there a nice and clean way to do this with Python 3?
推荐答案
您可以使用 itertools.product
遍历笛卡尔积 1 某些值(在本例中为索引):
You could use itertools.product
to iterate over the cartesian product 1 of some values (in this case the indices):
import itertools
shape = [4,5,2,6]
for idx in itertools.product(*[range(s) for s in shape]):
value = dataset[idx]
print(idx, value)
# i would be "idx[0]", j "idx[1]" and so on...
However if it's a numpy array you want to iterate over, it could be easier to use np.ndenumerate
:
import numpy as np
arr = np.random.random([4,5,2,6])
for idx, value in np.ndenumerate(arr):
print(idx, value)
# i would be "idx[0]", j "idx[1]" and so on...
1 您要求澄清itertools.product(*[range(s) for s in shape])
的实际作用.因此,我将对其进行详细说明.
1 You asked for clarification what itertools.product(*[range(s) for s in shape])
actually does. So I'll explain it in more details.
例如,您有此循环:
for i in range(10):
for j in range(8):
# do whatever
这也可以使用product
编写为:
for i, j in itertools.product(range(10), range(8)):
# ^^^^^^^^---- the inner for loop
# ^^^^^^^^^-------------- the outer for loop
# do whatever
这意味着product
只是减少独立 for循环数量的便捷方法.
That means product
is just a handy way of reducing the number of independant for-loops.
如果要将可变数量的for
-循环转换为product
,则基本上需要两个步骤:
If you want to convert a variable number of for
-loops to a product
you essentially need two steps:
# Create the "values" each for-loop iterates over
loopover = [range(s) for s in shape]
# Unpack the list using "*" operator because "product" needs them as
# different positional arguments:
prod = itertools.product(*loopover)
for idx in prod:
i_0, i_1, ..., i_n = idx # index is a tuple that can be unpacked if you know the number of values.
# The "..." has to be replaced with the variables in real code!
# do whatever
等同于:
for i_1 in range(shape[0]):
for i_2 in range(shape[1]):
... # more loops
for i_n in range(shape[n]): # n is the length of the "shape" object
# do whatever
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