Add values to a Scipy sparse matrix with indexes and values
numpy, python, scipy, sparse-matrix
Solution
You should use a `coo_matrix` instead, where you can change the attributes `col`, `row` and `data` of a previously created sparse matrix:
from scipy.sparse import coo_matrix
nele=30
nbus=40
col = [ 2, 3, 6]
row = [ 5, 5, 5]
val = [ 0.1 + 0.1j, 0.1 - 0.2j, 0.1 - 0.4j]
test = coo_matrix((val, (row,col)), shape=(nele, nbus), dtype=complex)
print test.col
#[2 3 6]
print test.row
#[5 5 5]
print test.data
#[ 0.1+0.1j 0.1-0.2j 0.1-0.4j]
Problem
I'm working in a program for Power System analysis and I need to work with sparse matrices. There is a routine where I fill a sparse matrix just with the following call: ``` self.A = bsr_matrix((val, (row,col)), shape=(nele, nbus), dtype=complex) ``` As this matrix won't change over time. Yet another matrix does change over time and I need to update it. Is there a way that having, for example: ``` co = [ 2, 3, 6] row = [ 5, 5, 5] val = [ 0.1 + 0.1j, 0.1 - 0.2j, 0.1 - 0.4j] ``` I can add those to a previously initialized sparse matrix? How would be the more pythonic way to do it? Thank you