أداء العمليات على arrray numpy ولكن إخفاء القيم على طول قطري من هذه العمليات

Question

حيث يمكنني إجراء عمليات في المصفوفات بحيث لا يتم حساب أي شيء على القطري بحيث يتم حساب كل شيء ما عدا قطري

array ([[0.,  1.37, 1.,   1.37, 1.,   1.37, 1.]
       [1.37, 0. ,  1.37, 1.73, 2.37, 1.73, 1.37]
       [1. ,  1.37, 0. ,  1.37, 2. ,  2.37, 2. ]
       [1.37, 1.73, 1.37, 0. ,  1.37, 1.73, 2.37]
       [1. ,  2.37, 2. ,  1.37, 0. ,  1.37, 2. ]
       [1.37, 1.73, 2.37, 1.73, 1.37, 0. ,  1.37]
       [1. ,  1.37, 2. ,  2.37, 2. ,  1.37, 0. ]])

لتجنب قيمة NAN ، لكنها احتفظت بالقيمة صفر على القطر في جميع الاستجابات

Answer 1

I wonder if masked arrays might do what you want, e.g.,

import numpy as NP
A = NP.random.random_integers(0, 9, 16).reshape(4, 4)
dg = NP.r_[ [NP.nan] * 4 ]  # proper syntax is 'nan' not 'NaN'
dg = NP.diag(dg)
A += dg                     # a 4x4 array w/ NaNs down the main diagonal
NP.sum(A, axis=1)           # doesn't work, gives: array([ NaN,  NaN,  NaN,  NaN])  
from numpy import ma as MA
Am = **MA.masked_invalid**(A)
NP.sum(Am, axis=1)         # now it works (treats 'nan' as 0)

The other way to do this of is, of course, to first convert the NaNs to 0s then mask the 0s:

NP.nan_to_num(A)
MA.masked_equal(A, 0)

Finally, it's often efficient to mask and convert the NaNs in one step:

MA.fix_invalid(A)

Pretty straightforward, just keep in mind that 'ma' might not yet be in your namespace and also that these functions deal with 'NaNs' and 'infs', which is usually what you want.

Answer 2

>>> arr = [
... [0.,  1.37, 1.,   1.37, 1.,   1.37, 1.],
... [1.37, 0. ,  1.37, 1.73, 2.37, 1.73, 1.37],
... [1. ,  1.37, 0. ,  1.37, 2. ,  2.37, 2. ],
... [1.37, 1.73, 1.37, 0. ,  1.37, 1.73, 2.37],
... [1. ,  2.37, 2. ,  1.37, 0. ,  1.37, 2. ],
... [1.37, 1.73, 2.37, 1.73, 1.37, 0. ,  1.37],
... [1. ,  1.37, 2. ,  2.37, 2. ,  1.37, 0. ]
... ]
>>> for i in range(6):
...     for y in range(6):
...             if (i <> y):
...                     print arr[i][y]*arr[y][i]
...
1.8769
1.0
1.8769
1.0
1.8769
1.8769
1.8769
2.9929
5.6169
2.9929
1.0
1.8769
1.8769
4.0
5.6169
1.8769
2.9929
1.8769
1.8769
2.9929
1.0
5.6169
4.0
1.8769
1.8769
1.8769
2.9929
5.6169
2.9929
1.8769

Depends on what you need to calculate

Answer 3

Do your calculation as normal and then

myarray[arange(len(array)), arange(len(array))] = 0.

Answer 4

Can you just do the calculation as normal, then afterwards set the diagonal back to zero?