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Swap pyarpackSparseLDLT and pyarpackSparseLU tests

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SparseLU tests solves now
- complex128 non-symmetric problem
- complex64 non-symmetric general problem

SparseLDLT solves now
- float64 symmetric problem
- float32 symmetric general problem
This commit is contained in:
Fabien Péan
2023-09-14 12:12:59 +02:00
committed by Franck HOUSSEN
parent bdb881c973
commit de52ee6e32
2 changed files with 41 additions and 42 deletions
Download Patch File Download Diff File Expand all files Collapse all files
EXAMPLES/PYARPACK/pyarpackSparseLDLT.py.in
+15 -25
View File
@@ -8,7 +8,7 @@ from pyarpack import sparseLDLT as pyarpackSlv
n = 4
i = np.array([], dtype='@PYINT@')
j = np.array([], dtype='@PYINT@')
Aij = np.array([], dtype='complex128')
Aij = np.array([], dtype='float64')
for k in range(n):
for l in [k-1, k, k+1]:
if l < 0 or l > n-1:
@@ -16,27 +16,23 @@ for k in range(n):
i = np.append(i, np.@PYINT@(k)) # Casting value on append is MANDATORY or C++ won't get the expected type.
j = np.append(j, np.@PYINT@(l)) # Casting value on append is MANDATORY or C++ won't get the expected type.
if l == k:
Aij = np.append(Aij, np.complex128(complex( 200., 200.))) # Casting value on append is MANDATORY or C++ won't get the expected type.
if l == k-1:
Aij = np.append(Aij, np.complex128(complex(-101., -101.))) # Casting value on append is MANDATORY or C++ won't get the expected type.
if l == k+1:
Aij = np.append(Aij, np.complex128(complex( -99., -99.))) # Casting value on append is MANDATORY or C++ won't get the expected type.
Aij = np.append(Aij, np.float64( 200.)) # Casting value on append is MANDATORY or C++ won't get the expected type.
if l == k-1 or l == k+1:
Aij = np.append(Aij, np.float64(-100.)) # Casting value on append is MANDATORY or C++ won't get the expected type.
for k, l, Akl in zip(i, j, Aij):
print("A[", k, ",", l, "] =", Akl)
A = (n, i, j, Aij) # coo format: dimension, i 0-based indices, j 0-based indices, Aij values.
# Get and tune arpack solver.
arpackSlv = pyarpackSlv.complexDouble() # Caution: complexDouble <=> np.array(..., dtype='complex128')
arpackSlv = pyarpackSlv.double() # Caution: double <=> np.array(..., dtype='float64')
arpackSlv.verbose = 3 # Set to 0 to get a quiet solve.
arpackSlv.debug = 1 # Set to 0 to get a quiet solve.
arpackSlv.nbEV = 1
arpackSlv.nbCV = 2*arpackSlv.nbEV + 1
arpackSlv.mag = 'LM'
arpackSlv.maxIt = 200
arpackSlv.slvOffset = 0.
arpackSlv.slvScale = 1.
arpackSlv.symPb = False
arpackSlv.slvPvtThd = 1.e-6
# Solve eigen problem.
@@ -66,8 +62,8 @@ print("\n#######################################################################
n = 8
i = np.array([], dtype='@PYINT@')
j = np.array([], dtype='@PYINT@')
Aij = np.array([], dtype='complex64')
Bij = np.array([], dtype='complex64')
Aij = np.array([], dtype='float32')
Bij = np.array([], dtype='float32')
for k in range(n):
for l in [k-1, k, k+1]:
if l < 0 or l > n-1:
@@ -75,14 +71,11 @@ for k in range(n):
i = np.append(i, np.@PYINT@(k+1)) # Casting value on append is MANDATORY or C++ won't get the expected type.
j = np.append(j, np.@PYINT@(l+1)) # Casting value on append is MANDATORY or C++ won't get the expected type.
if l == k:
Aij = np.append(Aij, np.complex64(complex( 200., 200.))) # Casting value on append is MANDATORY or C++ won't get the expected type.
Bij = np.append(Bij, np.complex64(complex( 33.3, 33.3))) # Casting value on append is MANDATORY or C++ won't get the expected type.
if l == k-1:
Aij = np.append(Aij, np.complex64(complex(-101., -101.))) # Casting value on append is MANDATORY or C++ won't get the expected type.
Bij = np.append(Bij, np.complex64(complex( 16.6, 16.6))) # Casting value on append is MANDATORY or C++ won't get the expected type.
if l == k+1:
Aij = np.append(Aij, np.complex64(complex( -99., -99.))) # Casting value on append is MANDATORY or C++ won't get the expected type.
Bij = np.append(Bij, np.complex64(complex( 16.6, 16.6))) # Casting value on append is MANDATORY or C++ won't get the expected type.
Aij = np.append(Aij, np.float32( 200.)) # Casting value on append is MANDATORY or C++ won't get the expected type.
Bij = np.append(Bij, np.float32( 33.3)) # Casting value on append is MANDATORY or C++ won't get the expected type.
if l == k-1 or l == k+1:
Aij = np.append(Aij, np.float32(-100.)) # Casting value on append is MANDATORY or C++ won't get the expected type.
Bij = np.append(Bij, np.float32( 16.6)) # Casting value on append is MANDATORY or C++ won't get the expected type.
for k, l, Akl in zip(i, j, Aij):
print("A[", k, ",", l, "] =", Akl)
for k, l, Bkl in zip(i, j, Bij):
@@ -92,18 +85,15 @@ B = (n, i, j, Bij) # coo format: dimension, i 1-based indices, j 1-based indices
# Get and tune arpack solver.
arpackSlv = pyarpackSlv.complexFloat() # Caution: complexFloat <=> np.array(..., dtype='complex64')
arpackSlv = pyarpackSlv.float() # Caution: float <=> np.array(..., dtype='float32')
arpackSlv.verbose = 3 # Set to 0 to get a quiet solve.
arpackSlv.debug = 1 # Set to 0 to get a quiet solve.
arpackSlv.nbEV = 2
arpackSlv.nbCV = 2*arpackSlv.nbEV + 1
arpackSlv.mag = 'LM'
arpackSlv.maxIt = 200
arpackSlv.slvOffset = 0.
arpackSlv.slvScale = 1.
arpackSlv.slvPvtThd = 1.e-6
arpackSlv.sigmaReal = 1
arpackSlv.sigmaImag = 1
arpackSlv.symPb = False
# Solve eigen problem.
EXAMPLES/PYARPACK/pyarpackSparseLU.py.in
+26 -17
View File
@@ -2,13 +2,12 @@
import numpy as np
from pyarpack import sparseLU as pyarpackSlv
# Build laplacian.
n = 4
i = np.array([], dtype='@PYINT@')
j = np.array([], dtype='@PYINT@')
Aij = np.array([], dtype='float64')
Aij = np.array([], dtype='complex128')
for k in range(n):
for l in [k-1, k, k+1]:
if l < 0 or l > n-1:
@@ -16,23 +15,27 @@ for k in range(n):
i = np.append(i, np.@PYINT@(k)) # Casting value on append is MANDATORY or C++ won't get the expected type.
j = np.append(j, np.@PYINT@(l)) # Casting value on append is MANDATORY or C++ won't get the expected type.
if l == k:
Aij = np.append(Aij, np.float64( 200.)) # Casting value on append is MANDATORY or C++ won't get the expected type.
if l == k-1 or l == k+1:
Aij = np.append(Aij, np.float64(-100.)) # Casting value on append is MANDATORY or C++ won't get the expected type.
Aij = np.append(Aij, np.complex128(complex( 200., 200.))) # Casting value on append is MANDATORY or C++ won't get the expected type.
if l == k-1:
Aij = np.append(Aij, np.complex128(complex(-101., -101.))) # Casting value on append is MANDATORY or C++ won't get the expected type.
if l == k+1:
Aij = np.append(Aij, np.complex128(complex( -99., -99.))) # Casting value on append is MANDATORY or C++ won't get the expected type.
for k, l, Akl in zip(i, j, Aij):
print("A[", k, ",", l, "] =", Akl)
A = (n, i, j, Aij) # coo format: dimension, i 0-based indices, j 0-based indices, Aij values.
# Get and tune arpack solver.
arpackSlv = pyarpackSlv.double() # Caution: double <=> np.array(..., dtype='float64')
arpackSlv = pyarpackSlv.complexDouble() # Caution: complexDouble <=> np.array(..., dtype='complex128')
arpackSlv.verbose = 3 # Set to 0 to get a quiet solve.
arpackSlv.debug = 1 # Set to 0 to get a quiet solve.
arpackSlv.nbEV = 1
arpackSlv.nbCV = 2*arpackSlv.nbEV + 1
arpackSlv.mag = 'LM'
arpackSlv.maxIt = 200
arpackSlv.slvPvtThd = 1.e-6
arpackSlv.slvOffset = 0.
arpackSlv.slvScale = 1.
arpackSlv.symPb = False
# Solve eigen problem.
@@ -62,8 +65,8 @@ print("\n#######################################################################
n = 8
i = np.array([], dtype='@PYINT@')
j = np.array([], dtype='@PYINT@')
Aij = np.array([], dtype='float32')
Bij = np.array([], dtype='float32')
Aij = np.array([], dtype='complex64')
Bij = np.array([], dtype='complex64')
for k in range(n):
for l in [k-1, k, k+1]:
if l < 0 or l > n-1:
@@ -71,11 +74,14 @@ for k in range(n):
i = np.append(i, np.@PYINT@(k+1)) # Casting value on append is MANDATORY or C++ won't get the expected type.
j = np.append(j, np.@PYINT@(l+1)) # Casting value on append is MANDATORY or C++ won't get the expected type.
if l == k:
Aij = np.append(Aij, np.float32( 200.)) # Casting value on append is MANDATORY or C++ won't get the expected type.
Bij = np.append(Bij, np.float32( 33.3)) # Casting value on append is MANDATORY or C++ won't get the expected type.
if l == k-1 or l == k+1:
Aij = np.append(Aij, np.float32(-100.)) # Casting value on append is MANDATORY or C++ won't get the expected type.
Bij = np.append(Bij, np.float32( 16.6)) # Casting value on append is MANDATORY or C++ won't get the expected type.
Aij = np.append(Aij, np.complex64(complex( 200., 200.))) # Casting value on append is MANDATORY or C++ won't get the expected type.
Bij = np.append(Bij, np.complex64(complex( 33.3, 33.3))) # Casting value on append is MANDATORY or C++ won't get the expected type.
if l == k-1:
Aij = np.append(Aij, np.complex64(complex(-101., -101.))) # Casting value on append is MANDATORY or C++ won't get the expected type.
Bij = np.append(Bij, np.complex64(complex( 16.6, 16.6))) # Casting value on append is MANDATORY or C++ won't get the expected type.
if l == k+1:
Aij = np.append(Aij, np.complex64(complex( -99., -99.))) # Casting value on append is MANDATORY or C++ won't get the expected type.
Bij = np.append(Bij, np.complex64(complex( 16.6, 16.6))) # Casting value on append is MANDATORY or C++ won't get the expected type.
for k, l, Akl in zip(i, j, Aij):
print("A[", k, ",", l, "] =", Akl)
for k, l, Bkl in zip(i, j, Bij):
@@ -85,15 +91,18 @@ B = (n, i, j, Bij) # coo format: dimension, i 1-based indices, j 1-based indices
# Get and tune arpack solver.
arpackSlv = pyarpackSlv.float() # Caution: float <=> np.array(..., dtype='float32')
arpackSlv = pyarpackSlv.complexFloat() # Caution: complexFloat <=> np.array(..., dtype='complex64')
arpackSlv.verbose = 3 # Set to 0 to get a quiet solve.
arpackSlv.debug = 1 # Set to 0 to get a quiet solve.
arpackSlv.nbEV = 2
arpackSlv.nbCV = 2*arpackSlv.nbEV + 1
arpackSlv.mag = 'LM'
arpackSlv.maxIt = 200
arpackSlv.slvPvtThd = 1.e-6
arpackSlv.slvOffset = 0.
arpackSlv.slvScale = 1.
arpackSlv.sigmaReal = 1
arpackSlv.sigmaImag = 1
arpackSlv.symPb = False
# Solve eigen problem.
@@ -113,4 +122,4 @@ for val, vec in zip(arpackSlv.val, arpackSlv.vec):
print("eigen value:", val)
print("eigen vector:")
for v in range(n):
print(vec[v])
print(vec[v])