计算二维阵列上拒绝特殊值（知道索引） [英] Calculation on 2D array rejecting special values (knowing the indices)

问题描述

我开始在Python和... ...编码
我想要做一个二维数组的计算与拒绝特殊值（我知道它的数组中的坐标）与array_values​​reject

I'm beginning in Python and...coding... I m trying to do calculations on a 2D array with reject special values (i know its coordinates in the array) with array_valuesreject

作为例子：

import numpy as np

#A array of the points I must reject
#The first column reprensents the position in Y and the second the position in X
#of 2D array below

array_valuesreject = np.array([[1.,2.],[2.,3.], [3.,5.],[10.,2.]])

#The 2D array :

test_array = np.array([[  3051.11,   2984.85,   3059.17],
       [  3510.78,   3442.43,   3520.7 ],
       [  4045.91,   3975.03,   4058.15],
       [  4646.37,   4575.01,   4662.29],
       [  5322.75,   5249.33,   5342.1 ],
       [  6102.73,   6025.72,   6127.86],
       [  6985.96,   6906.81,   7018.22],
       [  7979.81,   7901.04,   8021.  ],
       [  9107.18,   9021.98,   9156.44],
       [ 10364.26,  10277.02,  10423.1 ],
       [ 11776.65,  11682.76,  11843.18]])


#So I would like to apply calculation on 2D array without taking account of the 
#list of coordinates defined above and i would like to keep the same dimensions array!
#(because it s represented a matrix of detectors)

#Create new_array to store values
#So I try something like that....:

new_array = numpy.zeros(shape=(test_array.shape[0],test_array.shape[1]))

for i in range(test_array.shape[0]):
    if col[i] != (array_valuesreject[i]-1):
        for j in range(test_array.shape[1]):
        if row[j] != (array_valuesreject[j]-1):
            new_array[i,j] = test_array[i,j] * 2

感谢您的帮助！

推荐答案

这是使用屏蔽数组一个很好的案例。你要掩盖你想在计算中忽略的坐标：

This is a good case to use a masked array. You have to mask the coordinates you want to ignore in the calculation:

#NOTE it is an array of integers
array_valuesreject = np.array([[1, 2], [2, 2], [3, 1], [10, 2]])
i, j = array_valuesreject.T

mask = np.zeros(test_array.shape, bool)
mask[i,j] = True
m = np.ma.array(test_array, mask=mask)

在打印屏蔽数组 M ：

masked_array(data =
 [[3051.11 2984.85 3059.17]
 [3510.78 3442.43 --]
 [4045.91 3975.03 --]
 [4646.37 -- 4662.29]
 [5322.75 5249.33 5342.1]
 [6102.73 6025.72 6127.86]
 [6985.96 6906.81 7018.22]
 [7979.81 7901.04 8021.0]
 [9107.18 9021.98 9156.44]
 [10364.26 10277.02 10423.1]
 [11776.65 11682.76 --]],
             mask =
 [[False False False]
 [False False  True]
 [False False  True]
 [False  True False]
 [False False False]
 [False False False]
 [False False False]
 [False False False]
 [False False False]
 [False False False]
 [False False  True]],
       fill_value = 1e+20)

和计算将仅在非掩蔽值来执行，以使​​得可以执行

and the calculations will only be performed for the non-masked values, such that you can do:

new_array = m * 2

要得到你想要的东西。

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