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#69 Removed most solvers, replaced by wrappers.

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rowanc1
2014-05-16 18:33:57 -07:00
parent 1f0e37d773
commit f3170a8a7f
11 changed files with 92 additions and 670 deletions
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SimPEG/Utils/SolverUtils.py
+29 -18
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@@ -2,10 +2,20 @@ import numpy as np
from matutils import mkvc
import warnings
def DSolverWrap(fun, factorize=True, destroy = False, checkAccuracy=True, accuracyTol=1e-6):
def _checkAccuracy(A, b, X, accuracyTol):
nrm = np.linalg.norm(mkvc(A*X - b), np.inf)
nrm_b = np.linalg.norm(mkvc(b), np.inf)
if nrm_b > 0:
nrm /= nrm_b
if nrm > accuracyTol:
msg = '### SolverWarning ###: Accuracy on solve is above tolerance: %e > %e' % (nrm, accuracyTol)
print msg
warnings.warn(msg, RuntimeWarning)
def DSolverWrap(fun, factorize=True, checkAccuracy=True, accuracyTol=1e-6):
def __init__(self, A, **kwargs):
self.A = A.tocsc()
self.kwargs = kwargs
if factorize:
@@ -28,27 +38,27 @@ def DSolverWrap(fun, factorize=True, destroy = False, checkAccuracy=True, accura
X[:,i] = fun(self.A, b[:,i], **self.kwargs)
if checkAccuracy:
nrm = np.linalg.norm(mkvc(self.A*X - b)) / np.linalg.norm(mkvc(b))
if nrm > accuracyTol:
msg = '### SolverWarning ###: Accuracy on solve is above tolerance: %e > %e' % (nrm, accuracyTol)
print msg
warnings.warn(msg, RuntimeWarning)
_checkAccuracy(self.A, b, X, accuracyTol)
return X
def clean(self):
if destroy == True:
if hasattr(self.solver, 'clean'):
return self.solver.clean()
else:
return True
return type(fun.__name__, (object,), {"__init__": __init__, "solve": solve, "clean": clean})
def __mul__(self, val):
if type(val) is np.ndarray:
return self.solve(val)
raise TypeError('Can only multiply by a numpy array.')
return type(fun.__name__, (object,), {"__init__": __init__, "solve": solve, "clean": clean, "__mul__": __mul__})
def ISolverWrap(fun, checkAccuracy=True, accuracyTol=1e-5):
def __init__(self, A, **kwargs):
self.A = A.tocsc()
self.A = A
self.kwargs = kwargs
def solve(self, b):
@@ -74,11 +84,12 @@ def ISolverWrap(fun, checkAccuracy=True, accuracyTol=1e-5):
X[:,i] = out
if checkAccuracy:
nrm = np.linalg.norm(mkvc(self.A*X - b)) / np.linalg.norm(mkvc(b))
if nrm > accuracyTol:
msg = '### SolverWarning ###: Accuracy on solve is above tolerance: %e > %e' % (nrm, accuracyTol)
print msg
warnings.warn(msg, RuntimeWarning)
_checkAccuracy(self.A, b, X, accuracyTol)
return X
return type(fun.__name__, (object,), {"__init__": __init__, "solve": solve})
def __mul__(self, val):
if type(val) is np.ndarray:
return self.solve(val)
raise TypeError('Can only multiply by a numpy array.')
return type(fun.__name__, (object,), {"__init__": __init__, "solve": solve, "__mul__": __mul__})