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import unittest | ||
from pymatsolver import Pardiso | ||
from pydiso.mkl_solver import ( | ||
get_mkl_pardiso_max_threads, | ||
PardisoTypeConversionWarning | ||
) | ||
try: | ||
from pymatsolver import Pardiso | ||
from pydiso.mkl_solver import ( | ||
get_mkl_pardiso_max_threads, | ||
PardisoTypeConversionWarning | ||
) | ||
except ImportError: | ||
Pardiso = None | ||
import numpy as np | ||
import scipy.sparse as sp | ||
import os | ||
|
||
TOL = 1e-10 | ||
|
||
if Pardiso: | ||
class TestPardiso(unittest.TestCase): | ||
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||
class TestPardiso(unittest.TestCase): | ||
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def setUp(self): | ||
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nSize = 100 | ||
A = sp.rand(nSize, nSize, 0.05, format='csr', random_state=100) | ||
A = A + sp.spdiags(np.ones(nSize), 0, nSize, nSize) | ||
A = A.T*A | ||
A = A.tocsr() | ||
np.random.seed(1) | ||
sol = np.random.rand(nSize, 5) | ||
rhs = A.dot(sol) | ||
|
||
self.A = A | ||
self.rhs = rhs | ||
self.sol = sol | ||
|
||
def test(self): | ||
rhs = self.rhs | ||
sol = self.sol | ||
Ainv = Pardiso(self.A, is_symmetric=True) | ||
for i in range(3): | ||
self.assertLess(np.linalg.norm(Ainv * rhs[:, i] - sol[:, i]), TOL) | ||
self.assertLess(np.linalg.norm(Ainv * rhs - sol, np.inf), TOL) | ||
|
||
def test_refactor(self): | ||
rhs = self.rhs | ||
sol = self.sol | ||
A = self.A | ||
Ainv = Pardiso(A, is_symmetric=True) | ||
for i in range(3): | ||
self.assertLess(np.linalg.norm(Ainv * rhs[:, i] - sol[:, i]), TOL) | ||
self.assertLess(np.linalg.norm(Ainv * rhs - sol, np.inf), TOL) | ||
|
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# scale rows and collumns | ||
D = sp.diags(np.random.rand(A.shape[0]) + 1.0) | ||
A2 = D.T @ A @ D | ||
|
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rhs2 = A2 @ sol | ||
Ainv.factor(A2) | ||
for i in range(3): | ||
self.assertLess(np.linalg.norm(Ainv * rhs2[:, i] - sol[:, i]), TOL) | ||
self.assertLess(np.linalg.norm(Ainv * rhs2 - sol, np.inf), TOL) | ||
|
||
def test_T(self): | ||
rhs = self.rhs | ||
sol = self.sol | ||
Ainv = Pardiso(self.A, is_symmetric=True) | ||
|
||
with self.assertWarns(PardisoTypeConversionWarning): | ||
AinvT = Ainv.T | ||
x = AinvT * rhs | ||
def setUp(self): | ||
|
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nSize = 100 | ||
A = sp.rand(nSize, nSize, 0.05, format='csr', random_state=100) | ||
A = A + sp.spdiags(np.ones(nSize), 0, nSize, nSize) | ||
A = A.T*A | ||
A = A.tocsr() | ||
np.random.seed(1) | ||
sol = np.random.rand(nSize, 5) | ||
rhs = A.dot(sol) | ||
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self.A = A | ||
self.rhs = rhs | ||
self.sol = sol | ||
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def test(self): | ||
rhs = self.rhs | ||
sol = self.sol | ||
Ainv = Pardiso(self.A, is_symmetric=True) | ||
for i in range(3): | ||
self.assertLess(np.linalg.norm(Ainv * rhs[:, i] - sol[:, i]), TOL) | ||
self.assertLess(np.linalg.norm(Ainv * rhs - sol, np.inf), TOL) | ||
|
||
def test_refactor(self): | ||
rhs = self.rhs | ||
sol = self.sol | ||
A = self.A | ||
Ainv = Pardiso(A, is_symmetric=True) | ||
for i in range(3): | ||
self.assertLess(np.linalg.norm(x[:, i] - sol[:, i]), TOL) | ||
self.assertLess(np.linalg.norm(x - sol, np.inf), TOL) | ||
self.assertLess(np.linalg.norm(Ainv * rhs[:, i] - sol[:, i]), TOL) | ||
self.assertLess(np.linalg.norm(Ainv * rhs - sol, np.inf), TOL) | ||
|
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# scale rows and collumns | ||
D = sp.diags(np.random.rand(A.shape[0]) + 1.0) | ||
A2 = D.T @ A @ D | ||
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rhs2 = A2 @ sol | ||
Ainv.factor(A2) | ||
for i in range(3): | ||
self.assertLess(np.linalg.norm(Ainv * rhs2[:, i] - sol[:, i]), TOL) | ||
self.assertLess(np.linalg.norm(Ainv * rhs2 - sol, np.inf), TOL) | ||
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def test_T(self): | ||
rhs = self.rhs | ||
sol = self.sol | ||
Ainv = Pardiso(self.A, is_symmetric=True) | ||
|
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with self.assertWarns(PardisoTypeConversionWarning): | ||
AinvT = Ainv.T | ||
x = AinvT * rhs | ||
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for i in range(3): | ||
self.assertLess(np.linalg.norm(x[:, i] - sol[:, i]), TOL) | ||
self.assertLess(np.linalg.norm(x - sol, np.inf), TOL) | ||
|
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def test_n_threads(self): | ||
max_threads = get_mkl_pardiso_max_threads() | ||
print(f'testing setting n_threads to 1 and {max_threads}') | ||
Ainv = Pardiso(self.A, is_symmetric=True, n_threads=1) | ||
self.assertEqual(Ainv.n_threads, 1) | ||
|
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Ainv2 = Pardiso(self.A, is_symmetric=True, n_threads=max_threads) | ||
self.assertEqual(Ainv2.n_threads, max_threads) | ||
self.assertEqual(Ainv2.n_threads, Ainv.n_threads) | ||
|
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Ainv.n_threads = 1 | ||
self.assertEqual(Ainv.n_threads, 1) | ||
self.assertEqual(Ainv2.n_threads, Ainv.n_threads) | ||
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with self.assertRaises(TypeError): | ||
Ainv.n_threads = "2" | ||
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class TestPardisoNotSymmetric(unittest.TestCase): | ||
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def setUp(self): | ||
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nSize = 100 | ||
A = sp.rand(nSize, nSize, 0.05, format='csr', random_state=100) | ||
A = A + sp.spdiags(np.ones(nSize), 0, nSize, nSize) | ||
A = A.tocsr() | ||
np.random.seed(1) | ||
sol = np.random.rand(nSize, 5) | ||
rhs = A.dot(sol) | ||
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self.A = A | ||
self.rhs = rhs | ||
self.sol = sol | ||
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def test(self): | ||
rhs = self.rhs | ||
sol = self.sol | ||
Ainv = Pardiso(self.A, is_symmetric=True, check_accuracy=True) | ||
self.assertRaises(Exception, lambda: Ainv * rhs) | ||
Ainv.clean() | ||
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Ainv = Pardiso(self.A) | ||
for i in range(3): | ||
self.assertLess(np.linalg.norm(Ainv * rhs[:, i] - sol[:, i]), TOL) | ||
self.assertLess(np.linalg.norm(Ainv * rhs - sol, np.inf), TOL) | ||
Ainv.clean() | ||
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class TestPardisoFDEM(unittest.TestCase): | ||
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def setUp(self): | ||
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base_path = os.path.join(os.path.split(os.path.abspath(__file__))[0], 'fdem') | ||
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data = np.load(os.path.join(base_path, 'A_data.npy')) | ||
indices = np.load(os.path.join(base_path, 'A_indices.npy')) | ||
indptr = np.load(os.path.join(base_path, 'A_indptr.npy')) | ||
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self.A = sp.csr_matrix((data, indices, indptr), shape=(13872, 13872)) | ||
self.rhs = np.load(os.path.join(base_path, 'RHS.npy')) | ||
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def test(self): | ||
rhs = self.rhs | ||
Ainv = Pardiso(self.A, check_accuracy=True) | ||
sol = Ainv * rhs | ||
with self.assertWarns(PardisoTypeConversionWarning): | ||
sol = Ainv * rhs.real | ||
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class TestPardisoComplex(unittest.TestCase): | ||
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def setUp(self): | ||
nSize = 100 | ||
A = sp.rand(nSize, nSize, 0.05, format='csr', random_state=100) | ||
A.data = A.data + 1j*np.random.rand(A.nnz) | ||
A = A.T.dot(A) + sp.spdiags(np.ones(nSize), 0, nSize, nSize) | ||
A = A.tocsr() | ||
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np.random.seed(1) | ||
sol = np.random.rand(nSize, 5) + 1j*np.random.rand(nSize, 5) | ||
rhs = A.dot(sol) | ||
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self.A = A | ||
self.rhs = rhs | ||
self.sol = sol | ||
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def test_n_threads(self): | ||
max_threads = get_mkl_pardiso_max_threads() | ||
print(f'testing setting n_threads to 1 and {max_threads}') | ||
Ainv = Pardiso(self.A, is_symmetric=True, n_threads=1) | ||
self.assertEqual(Ainv.n_threads, 1) | ||
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Ainv2 = Pardiso(self.A, is_symmetric=True, n_threads=max_threads) | ||
self.assertEqual(Ainv2.n_threads, max_threads) | ||
self.assertEqual(Ainv2.n_threads, Ainv.n_threads) | ||
|
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Ainv.n_threads = 1 | ||
self.assertEqual(Ainv.n_threads, 1) | ||
self.assertEqual(Ainv2.n_threads, Ainv.n_threads) | ||
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with self.assertRaises(TypeError): | ||
Ainv.n_threads = "2" | ||
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class TestPardisoNotSymmetric(unittest.TestCase): | ||
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def setUp(self): | ||
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nSize = 100 | ||
A = sp.rand(nSize, nSize, 0.05, format='csr', random_state=100) | ||
A = A + sp.spdiags(np.ones(nSize), 0, nSize, nSize) | ||
A = A.tocsr() | ||
np.random.seed(1) | ||
sol = np.random.rand(nSize, 5) | ||
rhs = A.dot(sol) | ||
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self.A = A | ||
self.rhs = rhs | ||
self.sol = sol | ||
|
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def test(self): | ||
rhs = self.rhs | ||
sol = self.sol | ||
Ainv = Pardiso(self.A, is_symmetric=True, check_accuracy=True) | ||
self.assertRaises(Exception, lambda: Ainv * rhs) | ||
Ainv.clean() | ||
|
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Ainv = Pardiso(self.A) | ||
for i in range(3): | ||
self.assertLess(np.linalg.norm(Ainv * rhs[:, i] - sol[:, i]), TOL) | ||
self.assertLess(np.linalg.norm(Ainv * rhs - sol, np.inf), TOL) | ||
Ainv.clean() | ||
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||
|
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class TestPardisoFDEM(unittest.TestCase): | ||
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def setUp(self): | ||
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base_path = os.path.join(os.path.split(os.path.abspath(__file__))[0], 'fdem') | ||
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data = np.load(os.path.join(base_path, 'A_data.npy')) | ||
indices = np.load(os.path.join(base_path, 'A_indices.npy')) | ||
indptr = np.load(os.path.join(base_path, 'A_indptr.npy')) | ||
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self.A = sp.csr_matrix((data, indices, indptr), shape=(13872, 13872)) | ||
self.rhs = np.load(os.path.join(base_path, 'RHS.npy')) | ||
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def test(self): | ||
rhs = self.rhs | ||
Ainv = Pardiso(self.A, check_accuracy=True) | ||
sol = Ainv * rhs | ||
with self.assertWarns(PardisoTypeConversionWarning): | ||
sol = Ainv * rhs.real | ||
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class TestPardisoComplex(unittest.TestCase): | ||
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def setUp(self): | ||
nSize = 100 | ||
A = sp.rand(nSize, nSize, 0.05, format='csr', random_state=100) | ||
A.data = A.data + 1j*np.random.rand(A.nnz) | ||
A = A.T.dot(A) + sp.spdiags(np.ones(nSize), 0, nSize, nSize) | ||
A = A.tocsr() | ||
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np.random.seed(1) | ||
sol = np.random.rand(nSize, 5) + 1j*np.random.rand(nSize, 5) | ||
rhs = A.dot(sol) | ||
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self.A = A | ||
self.rhs = rhs | ||
self.sol = sol | ||
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def test(self): | ||
rhs = self.rhs | ||
sol = self.sol | ||
Ainv = Pardiso(self.A, is_symmetric=True) | ||
for i in range(3): | ||
self.assertLess(np.linalg.norm(Ainv * rhs[:, i] - sol[:, i]), TOL) | ||
self.assertLess(np.linalg.norm(Ainv * rhs - sol, np.inf), TOL) | ||
Ainv.clean() | ||
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def test_T(self): | ||
rhs = self.rhs | ||
sol = self.sol | ||
Ainv = Pardiso(self.A, is_symmetric=True) | ||
with self.assertWarns(PardisoTypeConversionWarning): | ||
AinvT = Ainv.T | ||
x = AinvT * rhs | ||
def test(self): | ||
rhs = self.rhs | ||
sol = self.sol | ||
Ainv = Pardiso(self.A, is_symmetric=True) | ||
for i in range(3): | ||
self.assertLess( | ||
np.linalg.norm(x[:, i] - sol[:, i]), TOL | ||
) | ||
self.assertLess(np.linalg.norm(x - sol, np.inf), TOL) | ||
self.assertLess(np.linalg.norm(Ainv * rhs[:, i] - sol[:, i]), TOL) | ||
self.assertLess(np.linalg.norm(Ainv * rhs - sol, np.inf), TOL) | ||
Ainv.clean() | ||
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def test_T(self): | ||
rhs = self.rhs | ||
sol = self.sol | ||
Ainv = Pardiso(self.A, is_symmetric=True) | ||
with self.assertWarns(PardisoTypeConversionWarning): | ||
AinvT = Ainv.T | ||
x = AinvT * rhs | ||
for i in range(3): | ||
self.assertLess( | ||
np.linalg.norm(x[:, i] - sol[:, i]), TOL | ||
) | ||
self.assertLess(np.linalg.norm(x - sol, np.inf), TOL) | ||
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if __name__ == '__main__': | ||
unittest.main() |