[英]Can you use if-else statement inside braces for an array in Python?
I'm wondering if there is a nice way to use an if-else statement inside braces of an array in Python to assign values. 我想知道是否有很好的方法在Python数组的括号内使用if-else语句来分配值。 What I would like is something like: 我想要的是这样的:
A = #some 2D array of length m by n, already initialized
A = np.float64(A)
val = someValue #any number, pick a number
A = [[val for j in range(n) if A[i][j] < val, else A[i][j]=A[i][j]] for i in range(m)]
Is there a nice way to do this? 有没有很好的方法可以做到这一点? Alternatively, if numpy has a faster way to compute this that would be equally as good, if not better. 另外,如果numpy有更快的方法来计算,那同样好,甚至更好。
The longer way to do what I am trying to achieve would be something like 做我想达到的目标的更长的方法是
for i in range(m):
for j in range(n):
if A[i][j] < val:
A[i][j] = val
The desired output is to set any values below a threshold to that threshold. 期望的输出是将低于阈值的任何值设置为该阈值。 I can do simpler if-statements with a 1D array such as 我可以使用一维数组执行更简单的if语句,例如
myArray = [otherArray[i] for i in range(theRange) if otherArray[i]>=value and otherArray[i]<=anotherValue]
This 1D example is not what I want. 这个一维示例不是我想要的。 It's just an example of the type of coding block I'm looking for. 这只是我要寻找的编码块类型的一个示例。 It seems to be quicker at processing against the traditional if-else statements. 与传统的if-else语句相比,它似乎处理起来更快。
With numpy arrays we try avoid iteration (list comprehension). 对于numpy数组,我们尝试避免迭代(列表理解)。 Sometimes it is needed, but in this case it is not: 有时是必需的,但在这种情况下,它不是:
In [403]: A=np.arange(16).reshape(4,4)
In [404]: A1=A.astype(np.float64) # better syntax for converting to float
In [405]: A1
Out[405]:
array([[ 0., 1., 2., 3.],
[ 4., 5., 6., 7.],
[ 8., 9., 10., 11.],
[ 12., 13., 14., 15.]])
A boolean array that shows where the test is True/False: 一个布尔数组,显示测试在哪里正确/错误:
In [406]: A1<5
Out[406]:
array([[ True, True, True, True],
[ True, False, False, False],
[False, False, False, False],
[False, False, False, False]], dtype=bool)
We can index with such a mask: 我们可以使用这样的掩码进行索引:
In [407]: A1[A1<5]=5
In [408]: A1
Out[408]:
array([[ 5., 5., 5., 5.],
[ 5., 5., 6., 7.],
[ 8., 9., 10., 11.],
[ 12., 13., 14., 15.]])
np.where
(and np.nonzero
) return indices where the condition is True; np.where
(和np.nonzero
)返回条件为True的索引; where
has a version that operates like the ternary operator (on each element): where
具有一个像三元运算符一样运行的版本(在每个元素上):
In [410]: np.where(A<5,5,A)
Out[410]:
array([[ 5, 5, 5, 5],
[ 5, 5, 6, 7],
[ 8, 9, 10, 11],
[12, 13, 14, 15]])
We can also clip
with np.maximum
: 我们还可以使用np.maximum
clip
:
In [411]: np.maximum(A,5)
Out[411]:
array([[ 5, 5, 5, 5],
[ 5, 5, 6, 7],
[ 8, 9, 10, 11],
[12, 13, 14, 15]])
In [417]: A.clip(5,None)
Out[417]:
array([[ 5, 5, 5, 5],
[ 5, 5, 6, 7],
[ 8, 9, 10, 11],
[12, 13, 14, 15]])
Python's one-line ternary operator syntax looks like this Python的单行三元运算符语法如下所示
variable = a if CONDITION else b
You can place this inside a list comprehension as well. 您也可以将其放在列表理解中。 It's not clear what val
is in your example, but I'm assuming it's a value you specified beforehand. 目前尚不清楚您的示例中的val
是什么,但我假设它是您事先指定的值。
val = 2
A = [[val if A[i][j] < val else A[i][j] for j in range(n)] for i in range(m)]
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