def solve(A, B):
F = Algebra();
if isinstance(A, ndarray) and isinstance(B, float):
return F.solve(A._M, B);
elif isinstance(B, ndarray) and isinstance(A, float):
return F.solve(A, B._M);
elif isinstance(A,ndarray) and isinstance(B, ndarray):
return ndarray(F.solve(A._M, B._M))
else:
return A / B
def solve(A, B):
F = Algebra()
if isinstance(A, ndarray) and isinstance(B, float):
return F.solve(A._M, B)
elif isinstance(B, ndarray) and isinstance(A, float):
return F.solve(A, B._M)
elif isinstance(A, ndarray) and isinstance(B, ndarray):
return ndarray(F.solve(A._M, B._M))
else:
return A / B
def __div__(A, B):
try:
F = Algebra()
R = F.solve(A._M, B._M)
return R
except (java.lang.IllegalArgumentException), e:
# check the error class types according to the matrix class so we can intelligently report the error.
print e.getMessage()
return None
def __div__(A, B):
try:
F = Algebra();
R = F.solve(A._M, B._M);
return R;
except (java.lang.IllegalArgumentException), e:
# check the error class types according to the matrix class so we can intelligently report the error.
print e.getMessage()
return None
def directlinearsolve():
from no.uib.cipr.matrix import Matrices, DenseMatrix, DenseVector
from cern.colt.matrix import DoubleMatrix2D, DoubleFactory2D
from cern.colt.matrix.linalg import Algebra
sz = 1000
# MTJ
x = DenseVector(sz)
t = time.time()
mat = Matrices.random(sz,sz)
b = Matrices.random(sz)
mat.solve(b,x)
print "Mtj :" + str(time.time() - t)
# Colt
alg = Algebra()
f = DoubleFactory2D.dense
t = time.time()
A = f.random(sz,sz)
b = f.random(sz,1)
x = alg.solve(A,b)
print "Colt :" + str(time.time() - t)
