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函数在数组的单个列中的每一行上迭代工作-numpy

[英]Function working iteratively over each row in an individual column of an array - numpy

I'm looking to change all the values in an array using the following formula: 我正在寻找使用以下公式更改数组中的所有值:

new_value = old_value * elec_space - elec_space

A complicating issue is that all values above 48 within the array will be increased by two, as 49 & 50 will never exist in the original array (infile, shown below). 一个复杂的问题是,数组中所有高于48的值都将增加2,因为原始数组中不存在49和50(infile,如下所示)。 This means that any value above 48 will have to have 2 subtracted from it before performing the above calculation. 这意味着在执行上述计算之前,任何大于48的值都必须减去2。

Original values: 原始值:

elec_space = 0.5

infile = 
[[41,   42,   43,   44]
 [41,   42,   44,   45]
 [41,   43,   45,   47]
 [44,   45,   46,   47]
 [44,   45,   47,   48]
 [44,   46,   48,   52]
 [47,   48,   51,   52]
 [47,   48,   52,   53]
 [47,   51,   53,   55]]

Desired values: 所需值:

infile =
[[ 20,  20.5,   21,  21.5]
 [ 20,  20.5,  21.5,  22]
 [ 20    21,    22,   23]
 [21.5,  22,   22.5,  23]
 [21.5   22,    23,  23.5]
 [21.5, 22.5,  23.5, 24.5]
 [ 23,  23.5,   24,  24.5]
 [ 23,  23.5,  24.5,  25]
 [ 23,   24,    25,   26]]

I've tried: 我试过了:

def remove_missing(infile):
    if infile > 48:
        return (infile - 2) * elec_space - elec_space
    else:
        return infile * elec_space - elec_space
A = remove_missing(infile[:,0])
B = remove_missing(infile[:,1])
M = remove_missing(infile[:,2])
N = remove_missing(infile[:,3])
infile = np.column_stack((A, B, M, N))

And: 和:

def remove_missing(infile):
    return (infile - 2) * elec_space - elec_space if infile > 50 else infile * elec_space - elec_space
A = remove_missing(infile[:,0])
B = remove_missing(infile[:,1])
M = remove_missing(infile[:,2])
N = remove_missing(infile[:,3])

But got the following traceback for each of them: 但是,它们每个都有以下回溯:

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-181-dcc8e29a527f> in <module>()
      4     else:
      5         return infile * elec_space - elec_space
----> 6 A = remove_missing(infile[:,0])
      7 B = remove_missing(infile[:,1])
      8 M = remove_missing(infile[:,2])

<ipython-input-181-dcc8e29a527f> in remove_missing(infile)
      1 def remove_missing(infile):
----> 2     if infile > 48:
      3         return (infile - 2) * elec_space - elec_space
      4     else:
      5         return infile * elec_space - elec_space

ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all() 




---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-180-c407ec4fa95d> in <module>()
      2     return (infile - 2) * elec_space - elec_space if infile > 50 else infile * elec_space - elec_space
      3 
----> 4 A = remove_missing(infile[:,0])
      5 B = remove_missing(infile[:,1])
      6 M = remove_missing(infile[:,2])

<ipython-input-180-c407ec4fa95d> in remove_missing(infile)
      1 def remove_missing(infile):
----> 2     return (infile - 2) * elec_space - elec_space if infile > 50 else infile * elec_space - elec_space
      3 
      4 A = remove_missing(infile[:,0])
      5 B = remove_missing(infile[:,1])

ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

I don't think a.any or a.all are the right options, as I want the function to run iteratively for each row in the column of the array, not to alter all values based on one of the values being over 48. 我不认为a.any或a.all是正确的选项,因为我希望函数针对数组列中的每一行迭代运行,而不是基于超过48个值之一来更改所有值。

Has anyone got any pointers on how best to tackle this, please? 请问有人对如何最好地解决这个问题有什么建议吗?

一种替代方法是从结果中减去大于48元素1 ,如下所示:

(infile - 2*(infile>48))* elec_space - elec_space

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