list comprehension替换2D矩阵中的循环 [英] list comprehension replace for loop in 2D matrix
问题描述
我尝试使用list comprehension来替换for循环。
I try to use list comprehension to replace the for loop.
原始文件是
2 3 4 5 6 3
1 2 2 4 5 5
1 2 2 2 2 4
for循环
line_number = 0
for line in file:
line_data = line.split()
Cordi[line_number, :5] = line_data
line_number += 1
输出
[[2 3 4 5 6 3]
[1 2 2 4 5 5]
[1 2 2 2 2 4]]
如果使用列表理解,我可以想到的是(我必须将数据类型更改为int,因此可以在程序的后续部分中绘制)
if use list comprehension instead, for what I can think of is (I have to change the data type to int, so it can be plotted in later part of the program)
Cordi1= [int(x) for x in line.split() for line in data]
但输出
[1, 1, 1]
但 line.split()表示数据中的行
实际上是一个列表,如果我尝试
but line.split() for line in data
is actually a list, and if I try
Cordi1 = [int(x) for x in name of the list]
它有效,为什么会发生这种情况?
it works, why this happens?
推荐答案
您已经交换了循环的顺序;它们的排序方式应该是从左到右嵌套的方式:
You have the order of your loops swapped; they should be ordered in the same way they would be nested, from left to right:
[int(x) for line in data for x in line.split()]
这循环超过数据
首先,然后对于每个行
迭代,迭代 line.split()
以生成 X
。然后,您可以从这些生成一个 flat 整数列表。
This loops over data
first, then for each line
iteration, iterates over line.split()
to produce x
. You then produce one flat list of integers from these.
但是,由于您正在尝试构建列表列表,因此需要嵌套另一个列表理解:
However, since you are trying to build a list of lists, you need to nest a list comprehension inside another:
Cordi1 = [[int(i) for i in line.split()] for line in data]
演示:
>>> data = '''\
... 2 3 4 5 6 3
... 1 2 2 4 5 5
... 1 2 2 2 2 4
... '''.splitlines()
>>> [int(x) for line in data for x in line.split()]
[2, 3, 4, 5, 6, 3, 1, 2, 2, 4, 5, 5, 1, 2, 2, 2, 2, 4]
>>> [[int(i) for i in line.split()] for line in data]
[[2, 3, 4, 5, 6, 3], [1, 2, 2, 4, 5, 5], [1, 2, 2, 2, 2, 4]]
如果你想要一个从这个多维numpy数组,您可以将上面的数据直接转换为数组或从数据创建数组然后重塑:
If you wanted a multidimensional numpy array from this, you can either convert the above directly to an array or create an array from the data then reshape:
>>> import numpy as np
>>> np.array([[int(i) for i in line.split()] for line in data])
array([[2, 3, 4, 5, 6, 3],
[1, 2, 2, 4, 5, 5],
[1, 2, 2, 2, 2, 4]])
>>> np.array([int(i) for line in data for i in line.split()]).reshape((3, 6))
array([[2, 3, 4, 5, 6, 3],
[1, 2, 2, 4, 5, 5],
[1, 2, 2, 2, 2, 4]])
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