# Load matrices
db = Tools.parseMatrixFile('{}/matrices_{}.xml'.format(cmdLineArgs.matricesDir, numberOfBasisFunctions), clones)
db.update(Tools.parseMatrixFile('{}/matrices_viscoelastic.xml'.format(cmdLineArgs.matricesDir), clones))
# Determine sparsity patterns that depend on the number of mechanisms
riemannSolverSpp = np.bmat([[np.matlib.ones((9, numberOfReducedQuantities), dtype=np.float64)], [np.matlib.zeros((numberOfReducedQuantities-9, numberOfReducedQuantities), dtype=np.float64)]])
db.insert(DB.MatrixInfo('AplusT', numberOfReducedQuantities, numberOfReducedQuantities, matrix=riemannSolverSpp))
db.insert(DB.MatrixInfo('AminusT', numberOfReducedQuantities, numberOfReducedQuantities, matrix=riemannSolverSpp))
DynamicRupture.addMatrices(db, cmdLineArgs.matricesDir, order, cmdLineArgs.dynamicRuptureMethod, numberOfElasticQuantities, numberOfReducedQuantities)
Plasticity.addMatrices(db, cmdLineArgs.matricesDir, cmdLineArgs.PlasticityMethod, order)
SurfaceDisplacement.addMatrices(db, order)
# Load sparse-, dense-, block-dense-config
Tools.memoryLayoutFromFile(cmdLineArgs.memLayout, db, clones)
# Set rules for the global matrix memory order
stiffnessOrder = { 'Xi': 0, 'Eta': 1, 'Zeta': 2 }
globalMatrixIdRules = [
(r'^k(Xi|Eta|Zeta)DivMT$', lambda x: stiffnessOrder[x[0]]),
(r'^k(Xi|Eta|Zeta)DivM$', lambda x: 3 + stiffnessOrder[x[0]]),
(r'^r(\d{1})DivM$', lambda x: 6 + int(x[0])-1),
(r'^rT(\d{1})$', lambda x: 10 + int(x[0])-1),
(r'^fMrT(\d{1})$', lambda x: 14 + int(x[0])-1),
(r'^fP(\d{1})$', lambda x: 18 + (int(x[0])-1))
]
DB.determineGlobalMatrixIds(globalMatrixIdRules, db)
# Kernels
kernels = list()
mechMatrix[9:15,9+6*m:9+6*(m+1)] = np.matlib.identity(6)
tallMatrix = np.matlib.zeros((numberOfQuantities, 15))
tallMatrix[0:15,0:15] = db[clones['star'][0]].spp
starMatrix = tallMatrix * mechMatrix
for clone in clones['star']:
db.insert(DB.MatrixInfo(clone, starMatrix.shape[0], starMatrix.shape[1], starMatrix))
source = np.matlib.zeros((numberOfQuantities, numberOfQuantities))
for m in range(0, numberOfMechanisms):
r = slice(9+6*m, 9+6*(m+1))
source[r,0:6] = db['ET'].spp
source[r,r] = np.matlib.identity(6)
db.insert(DB.MatrixInfo('source', numberOfQuantities, numberOfQuantities, source))
# Load sparse-, dense-, block-dense-config
Tools.memoryLayoutFromFile(cmdLineArgs.memLayout, db, clones)
# Set rules for the global matrix memory order
stiffnessOrder = { 'Xi': 0, 'Eta': 1, 'Zeta': 2 }
globalMatrixIdRules = [
(r'^k(Xi|Eta|Zeta)DivMT$', lambda x: stiffnessOrder[x[0]]),
(r'^k(Xi|Eta|Zeta)DivM$', lambda x: 3 + stiffnessOrder[x[0]]),
(r'^fM(\d{1})$', lambda x: 6 + int(x[0])-1),
(r'^fP(\d{1})(\d{1})(\d{1})$', lambda x: 10 + (int(x[0])-1)*12 + (int(x[1])-1)*3 + (int(x[2])-1))
]
DB.determineGlobalMatrixIds(globalMatrixIdRules, db)
# Kernels
kernels = list()
db.insert(DB.MatrixInfo('timeIntegrated', numberOfBasisFunctions, numberOfQuantities))
