Reputation: 755
import pandas as pd
import numpy as np
rates=(pd.read_excel("C:\Anaconda3\RateMatrix.xlsx", sheetname="Pu239Test", skiprows=0)).as_matrix() #read the matrix values from excel spreadsheet, and converts the values to a matrix
rates is a 22 x 22 matrix.
I would like to replace the diagonal elements of the Rates matrix with the sum of all other elements in the row.
For example,
rates.item(0,0) = rates.item(0,1)+rates.item(0,2)+rates.item(0,3)+....rates.item(0,21)
rates.item(1,1) = rates.item(1,0)+rates.item(1,2)+rates.item(1,3)+....rates.item(1,21)
.....
rates.item(21,21) = rates.item(21,0)+rates.item(21,2)+rates.item(21,3)+....rates.item(21,20)
I was wondering how I can do that. Thanks a lot in advance.
Upvotes: 4
Views: 2409
Reputation: 221584
Here's a vectorized approach on a NumPy array a
as input -
In [171]: a # Input array
Out[171]:
array([[ 0, 1, 2, 3, 4],
[ 5, 6, 7, 8, 9],
[10, 11, 12, 13, 14],
[15, 16, 17, 18, 19],
[20, 21, 22, 23, 24]])
# Get row and column indices of diag elements
In [172]: row,col = np.diag_indices_from(a)
# Assign the sum of each row except the diag elems into diag positions
In [173]: a[row,col] = a.sum(axis=1) - a[row,col]
# Updated array
In [174]: a
Out[174]:
array([[10, 1, 2, 3, 4],
[ 5, 29, 7, 8, 9],
[10, 11, 48, 13, 14],
[15, 16, 17, 67, 19],
[20, 21, 22, 23, 86]])
Let's manually compute the summations and cross-check against the diagonal elements -
In [175]: a[0,1] + a[0,2] + a[0,3] + a[0,4]
Out[175]: 10
In [176]: a[1,0] + a[1,2] + a[1,3] + a[1,4]
Out[176]: 29
In [177]: a[2,0] + a[2,1] + a[2,3] + a[2,4]
Out[177]: 48
In [178]: a[3,0] + a[3,1] + a[3,2] + a[3,4]
Out[178]: 67
In [179]: a[4,0] + a[4,1] + a[4,2] + a[4,3]
Out[179]: 86
Upvotes: 5