# python - text用法 - 如何迭代这个n维数据集?

## python plot标题 (1)

``value = dataset[i,j,k,l]``

``shape = [4,5,2,6]``

`shape`的值代表尺寸的长度。

``````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]``````

``````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...``````

``````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您要求澄清什么`itertools.product(*[range(s) for s in shape])`实际上做。 所以我会更详细地解释它。

``````for i in range(10):
for j in range(8):
# do whatever``````

``````for i, j in itertools.product(range(10), range(8)):
#                                        ^^^^^^^^---- the inner for loop
#                             ^^^^^^^^^-------------- the outer for loop
# do whatever``````

``````# 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``````

``````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``````