<!-- GENERATED by tools/generators/examplesDocsEmitter.py from python/ - do not edit -->
(testmodels-matrixcontainertest)=
# matrixContainerTest.py

You can view and download this file on Github: [matrixContainerTest.py](https://github.com/jgerstmayr/EXUDYN/tree/master/python/TestModels/matrixContainerTest.py)

```{code-block} python
:linenos:

#+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# This is an EXUDYN example
#
# Details:  Simple test for MatrixContainer, similar as Examples given in Docu
#
# Author:   Johannes Gerstmayr
# Date:     2024-10-09
#
# Copyright:This file is part of Exudyn. Exudyn is free software. You can redistribute it and/or modify it under the terms of the Exudyn license. See 'LICENSE.txt' for more details.
#
#+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

import exudyn as exu

testIsActive = exu.sys.get('testIsActive', False)

import numpy as np
from scipy.sparse import csr_matrix
from exudyn import MatrixContainer

u = 0 #result
mc = MatrixContainer()

#Create MatrixContainer with dense matrix:
#matrix can be initialized with a dense matrix, using a numpy array or list of lists , e.g.:
matrix = np.eye(3)
mcDense1 = MatrixContainer(matrix)
u+= mcDense1.Convert2DenseMatrix()[0,1]
mcDense2 = MatrixContainer([[1,2],[3,4]])

u+= mcDense1.Convert2DenseMatrix()[1,0]
mcSparse = MatrixContainer(csr_matrix(np.array([[1,5],[0,7]])))
u+= mcSparse.Convert2DenseMatrix()[0,1]

#Set with dense pyArray (a numpy array): 
pyArray = np.array(matrix)
mc.SetWithDenseMatrix(pyArray, useDenseMatrix = True)
u+= mc.Convert2DenseMatrix()[1,0]

#Set empty matrix:
mc.SetWithDenseMatrix([[]], useDenseMatrix = True)

#Set with list of lists, stored as sparse matrix:
mc.SetWithDenseMatrix([[1,2],[3,4]], useDenseMatrix = False)
u+= mc.Convert2DenseMatrix()[1,0]

#Set with sparse triplets (list of lists or numpy array):
mc.SetWithSparseMatrix([[0,0,13.3],[1,1,4.2],[1,2,42.]], 
                       numberOfRows=2, numberOfColumns=3, 
                       useDenseMatrix=True)
u+= mc.Convert2DenseMatrix()[1,2]

exu.Print(mc)
#gives dense matrix:
#[[13.3  0.   0. ]
# [ 0.   4.2 42. ]]

#Set with scipy matrix:
#WARNING: only use csr_matrix
#         csc_matrix would basically run, but gives the transposed!!!
spmat = csr_matrix(matrix) 
mc.SetWithSparseMatrix(spmat) #takes rows and column format automatically
u+= mc.Convert2DenseMatrix()[1,1]

#initialize and add triplets later on
mc.Initialize(3,3,useDenseMatrix=False)
mc.AddSparseMatrix(spmat, factor=1)
#can also add smaller matrix
mc.AddSparseMatrix(csr_matrix(np.eye(2)), factor=0.5)
exu.Print('mc=',mc.Convert2DenseMatrix())
u+= mc.Convert2DenseMatrix()[0,0]

#set matrix with smaller sparse matrix than the final dimensions
mc.SetWithSparseMatrix(csr_matrix(np.array([[1,2],[3,4]])), numberOfRows=4, numberOfColumns=2)
exu.Print('mc=',mc.Convert2DenseMatrix())
u+= mc.Convert2DenseMatrix()[1,1]


result = u
exu.Print('solution of matrixContainerTest=',result)

exu.sys['testResult'] = result
```