def test_yDirection(self):
dim=self.domain.getDim()
if dim==3:
return
u = Symbol('u',(2,), dim=dim)
q = Symbol('q', (2,2))
theta = Symbol('theta')
theta=3.141/6
q[0,0]=cos(theta)
q[0,1]=-sin(theta)
q[1,0]=sin(theta)
q[1,1]=cos(theta)
sigma = Symbol('sigma',(2,2))
p = NonlinearPDE(self.domain, u, debug=0)
epsilon = symmetric(grad(u))
# epsilon = matrixmult(matrixmult(q,epsilon0),q.transpose(1))
c00=10;c01=8;c05=0
c01=8;c11=10;c15=0
c05=0;c15=0;c55=1
sigma[0,0]=c00*epsilon[0,0]+c01*epsilon[1,1]+c05*2*epsilon[1,0]
sigma[1,1]=c01*epsilon[0,0]+c11*epsilon[1,1]+c15*2*epsilon[1,0]
sigma[0,1]=c05*epsilon[0,0]+c15*epsilon[1,1]+c55*2*epsilon[1,0]
sigma[1,0]=sigma[0,1]
# sigma0=matrixmult(matrixmult(q.transpose(1),epsilon),q)
x = self.domain.getX()
gammaD=whereZero(x[1])*[1,1]#+whereZero(x[0])*[1,0]+whereZero(x[0]-1)*[1,0]
yconstraint = FunctionOnBoundary(self.domain).getX()[1]
p.setValue(X=sigma,q=gammaD,y=[-50,0]*whereZero(yconstraint-1),r=[1,1])
v = p.getSolution(u=[0,0])
x=np.ndarray((2,))
x[0]=0.5
x[1]=0.5
loc=Locator(v.getFunctionSpace(),x)
valAtX=loc(v)
self.assertTrue(valAtX[0]>10*valAtX[1])
def test_yDirection(self):
dim=self.domain.getDim()
if dim==3:
return
u = Symbol('u',(2,), dim=dim)
q = Symbol('q', (2,2))
theta = Symbol('theta')
theta=3.141/6
q[0,0]=cos(theta)
q[0,1]=-sin(theta)
q[1,0]=sin(theta)
q[1,1]=cos(theta)
sigma = Symbol('sigma',(2,2))
p = NonlinearPDE(self.domain, u, debug=0)
epsilon = symmetric(grad(u))
# epsilon = matrixmult(matrixmult(q,epsilon0),q.transpose(1))
c00=10;c01=8;c05=0
c01=8;c11=10;c15=0
c05=0;c15=0;c55=1
sigma[0,0]=c00*epsilon[0,0]+c01*epsilon[1,1]+c05*2*epsilon[1,0]
sigma[1,1]=c01*epsilon[0,0]+c11*epsilon[1,1]+c15*2*epsilon[1,0]
sigma[0,1]=c05*epsilon[0,0]+c15*epsilon[1,1]+c55*2*epsilon[1,0]
sigma[1,0]=sigma[0,1]
# sigma0=matrixmult(matrixmult(q.transpose(1),epsilon),q)
x = self.domain.getX()
gammaD=whereZero(x[1])*[1,1]#+whereZero(x[0])*[1,0]+whereZero(x[0]-1)*[1,0]
yconstraint = FunctionOnBoundary(self.domain).getX()[1]
p.setValue(X=sigma,q=gammaD,y=[-50,0]*whereZero(yconstraint-1),r=[1,1])
v = p.getSolution(u=[0,0])
x=np.ndarray((2,))
x[0]=0.5
x[1]=0.5
loc=Locator(v.getFunctionSpace(),x)
valAtX=loc(v)
self.assertTrue(valAtX[0]>10*valAtX[1])
def getDerivative(self, m):
"""
returns the value for the derivative of the mapping for m
"""
e = exp(m[0] + self.Mr)
return (e * cos(m[1] + self.Mi)) * [[1, 0], [0, 1]] + (
e * sin(m[1] + self.Mi)) * [[0, -1], [1, 0]]
def __init__(self, domain, reference=WGS84ReferenceSystem()):
"""
set up the orthogonal coordinate transformation.
:param domain: domain in the domain of the coordinate transformation
:type domain: `esys.escript.AbstractDomain`
:param reference: the reference system
:type reference: `ReferenceSystem`
"""
DIM = domain.getDim()
super(GeodeticCoordinateTransformation,
self).__init__(domain, reference)
a = reference.getSemiMajorAxis()
f = reference.getFlattening()
f_a = reference.getAngularUnit()
f_h = reference.getHeightUnit()
x = esc.Function(domain).getX()
if DIM == 2:
phi = 0.
else:
phi = x[1] * f_a
h = x[DIM - 1] * f_h
e = esc.sqrt(2 * f - f**2)
N = a / esc.sqrt(1 - e**2 * esc.sin(phi)**2)
M = (a * (1 - e**2)) / esc.sqrt(1 - e**2 * esc.sin(phi)**2)**3
v_phi = f_a * (M + h)
v_lam = f_a * (N + h) * esc.cos(phi)
v_h = f_h
s = esc.Vector(1., esc.Function(domain))
if DIM == 2:
v = v_phi * v_h
s[0] = 1 / v_lam
s[1] = 1 / v_h
else:
v = v_phi * v_lam * v_h
s[0] = 1 / v_lam
s[1] = 1 / v_phi
s[2] = 1 / v_h
self._volumefactor = v
self._scaling_factors = s
def __init__(self, domain, reference=WGS84ReferenceSystem() ):
"""
set up the orthogonal coordinate transformation.
:param domain: domain in the domain of the coordinate transformation
:type domain: `esys.escript.AbstractDomain`
:param reference: the reference system
:type reference: `ReferenceSystem`
"""
DIM=domain.getDim()
super(GeodeticCoordinateTransformation, self).__init__(domain, reference )
a=reference.getSemiMajorAxis()
f=reference.getFlattening()
f_a=reference.getAngularUnit()
f_h=reference.getHeightUnit()
x=esc.Function(domain).getX()
if DIM == 2:
phi=0.
else:
phi=x[1] * f_a
h=x[DIM-1] * f_h
e = esc.sqrt(2*f-f**2)
N = a/esc.sqrt(1 - e**2 * esc.sin(phi)**2 )
M = ( a*(1-e**2) ) /esc.sqrt(1 - e**2 * esc.sin(phi)**2 )**3
v_phi = f_a * (M + h)
v_lam = f_a * (N + h) * esc.cos(phi)
v_h = f_h
s= esc.Vector(1., esc.Function(domain))
if DIM == 2:
v= v_phi * v_h
s[0]=1/v_lam
s[1]=1/v_h
else:
v= v_phi * v_lam * v_h
s[0]=1/v_lam
s[1]=1/v_phi
s[2]=1/v_h
self._volumefactor=v
self._scaling_factors = s
def test_SphericalTransformation3D(self):
dom=Brick(NE,NE,NE, l0=90, l1=45, l2=10.)
cs=SphericalReferenceSystem()
tf=cs.createTransformation(dom)
self.assertEqual(tf.getReferenceSystem(),cs , "wrong reference")
self.assertEqual(tf.getDomain(),dom , "wrong reference")
self.assertFalse(tf.isCartesian(), "wrong isCartesian check")
R=6378137.0
x=esys.escript.Function(dom).getX()
phi=(90.-x[1])/180.*pi
lam=x[0]/180.*pi
h=x[2]*1000.
r=h+R
v=tf.getVolumeFactor()
self.assertTrue(isinstance(v, esys.escript.Data), "wrong volume factor type")
self.assertEqual(v.getFunctionSpace(), esys.escript.Function(dom), "wrong volume factor type")
error=Lsup(v- r**2*sin(phi)*(pi/180.)**2*1000. )
self.assertTrue(error<=RTOL * R*R*(pi/180.)**2*1000., "volume factor")
s=tf.getScalingFactors()
self.assertTrue(isinstance(s, esys.escript.Data), "scaling factor type")
self.assertEqual(s.getShape(), (dom.getDim(),), "scaling factor length")
self.assertEqual(s.getFunctionSpace(), esys.escript.Function(dom), "wrong 0-th scaling factor type")
error=Lsup(s[1]-1/r/pi*180.)
self.assertTrue(error<=RTOL/R/pi*180., "0-th scaling factor")
error=Lsup(s[0]-1/(r*sin(phi))/pi*180.)
self.assertTrue(error<=RTOL/R/pi*180., "1-th scaling factor")
error=Lsup(s[2]-1./1000.)
self.assertTrue(error<=RTOL/1000., "2-th scaling factor")
def test_SphericalTransformation3D(self):
dom=Brick(NE,NE,NE, l0=90, l1=45, l2=10.)
cs=SphericalReferenceSystem()
tf=cs.createTransformation(dom)
self.assertEqual(tf.getReferenceSystem(),cs , "wrong reference")
self.assertEqual(tf.getDomain(),dom , "wrong reference")
self.assertFalse(tf.isCartesian(), "wrong isCartesian check")
R=6378137.0
x=esys.escript.Function(dom).getX()
phi=(90.-x[1])/180.*pi
lam=x[0]/180.*pi
h=x[2]*1000.
r=h+R
v=tf.getVolumeFactor()
self.assertTrue(isinstance(v, esys.escript.Data), "wrong volume factor type")
self.assertEqual(v.getFunctionSpace(), esys.escript.Function(dom), "wrong volume factor type")
error=Lsup(v- r**2*sin(phi)*(pi/180.)**2*1000. )
self.assertTrue(error<=RTOL * R*R*(pi/180.)**2*1000., "volume factor")
s=tf.getScalingFactors()
self.assertTrue(isinstance(s, esys.escript.Data), "scaling factor type")
self.assertEqual(s.getShape(), (dom.getDim(),), "scaling factor length")
self.assertEqual(s.getFunctionSpace(), esys.escript.Function(dom), "wrong 0-th scaling factor type")
error=Lsup(s[1]-1/r/pi*180.)
self.assertTrue(error<=RTOL/R/pi*180., "0-th scaling factor")
error=Lsup(s[0]-1/(r*sin(phi))/pi*180.)
self.assertTrue(error<=RTOL/R/pi*180., "1-th scaling factor")
error=Lsup(s[2]-1./1000.)
self.assertTrue(error<=RTOL/1000., "2-th scaling factor")
def getDerivative(self, m):
"""
returns the value for the derivative of the mapping for m
"""
e = exp(m[0] + self.Mr)
return (e * cos(m[1] + self.Mi)) * [[1, 0], [0, 1]] + (e * sin(m[1] + self.Mi)) * [[0, -1], [1, 0]]
def getValue(self, m):
"""
returns the value of the mapping for m
"""
return exp(m[0] + self.Mr) * (cos(m[1] + self.Mi) * [1, 0] + sin(m[1] + self.Mi) * [0, 1])
def getValue(self, m):
"""
returns the value of the mapping for m
"""
return exp(m[0] + self.Mr) * (cos(m[1] + self.Mi) * [1, 0] +
sin(m[1] + self.Mi) * [0, 1])
def __init__(self,
domain,
omega,
x,
Z,
eta=None,
w0=1.,
mu=4 * math.pi * 1e-7,
sigma0=0.01,
airLayerLevel=None,
fixAirLayer=False,
coordinates=None,
tol=1e-8,
saveMemory=False,
directSolver=True):
"""
initializes a new forward model.
:param domain: domain of the model
:type domain: `Domain`
:param omega: frequency
:type omega: positive ``float``
:param x: coordinates of measurements
:type x: ``list`` of ``tuple`` with ``float``
:param Z: measured impedance (possibly scaled)
:type Z: ``list`` of ``complex``
:param eta: spatial confidence radius
:type eta: positive ``float`` or ``list`` of positive ``float``
:param w0: confidence factors for meassurements.
:type w0: ``None`` or a list of positive ``float``
:param mu: permeability
:type mu: ``float``
:param sigma0: background conductivity
:type sigma0: ``float``
:param airLayerLevel: position of the air layer from to bottom of the domain. If
not set the air layer starts at the top of the domain
:type airLayerLevel: ``float`` or ``None``
:param fixAirLayer: fix air layer (TM mode)
:type fixAirLayer: ``bool``
:param coordinates: defines coordinate system to be used (not supported yet)
:type coordinates: `ReferenceSystem` or `SpatialCoordinateTransformation`
:param tol: tolerance of underlying PDE
:type tol: positive ``float``
:param saveMemory: if true stiffness matrix is deleted after solution
of the PDE to minimize memory use. This will
require more compute time as the matrix needs to be
reallocated at each iteration.
:type saveMemory: ``bool``
:param directSolver: if true a direct solver (rather than an iterative
solver) will be used to solve the PDE
:type directSolver: ``bool``
"""
super(MT2DBase, self).__init__()
self.__trafo = coords.makeTransformation(domain, coordinates)
if not self.getCoordinateTransformation().isCartesian():
raise ValueError(
"Non-Cartesian coordinates are not supported yet.")
if len(x) != len(Z):
raise ValueError(
"Number of data points and number of impedance values don't match."
)
if eta is None:
eta = escript.sup(domain.getSize()) * 0.45
if isinstance(eta, float) or isinstance(eta, int):
eta = [float(eta)] * len(Z)
elif not len(eta) == len(Z):
raise ValueError(
"Number of confidence radii and number of impedance values don't match."
)
if isinstance(w0, float) or isinstance(w0, int):
w0 = [float(w0)] * len(Z)
elif not len(w0) == len(Z):
raise ValueError(
"Number of confidence factors and number of impedance values don't match."
)
self.__domain = domain
self._omega_mu = omega * mu
self._ks = escript.sqrt(self._omega_mu * sigma0 / 2.)
xx = escript.Function(domain).getX()
totalS = 0
self._Z = [
escript.Scalar(0., escript.Function(domain)),
escript.Scalar(0., escript.Function(domain))
]
self._weight = escript.Scalar(0., escript.Function(domain))
for s in range(len(Z)):
chi = self.getWeightingFactor(xx, 1., x[s], eta[s])
f = escript.integrate(chi)
if f < eta[s]**2 * 0.01:
raise ValueError(
"Zero weight (almost) for data point %s. Change eta or refine mesh."
% (s, ))
w02 = w0[s] / f
totalS += w02
self._Z[0] += chi * Z[s].real
self._Z[1] += chi * Z[s].imag
self._weight += chi * w02 / (abs(Z[s])**2)
if not totalS > 0:
raise ValueError(
"Scaling of weight factors failed as sum is zero.")
DIM = domain.getDim()
z = domain.getX()[DIM - 1]
self._ztop = escript.sup(z)
self._zbottom = escript.inf(z)
if airLayerLevel is None:
airLayerLevel = self._ztop
self._airLayerLevel = airLayerLevel
# botton:
mask0 = escript.whereZero(z - self._zbottom)
r = mask0 * [
escript.exp(self._ks * (self._zbottom - airLayerLevel)) *
escript.cos(self._ks * (self._zbottom - airLayerLevel)),
escript.exp(self._ks * (self._zbottom - airLayerLevel)) *
escript.sin(self._ks * (self._zbottom - airLayerLevel))
]
#top:
if fixAirLayer:
mask1 = escript.whereNonNegative(z - airLayerLevel)
r += mask1 * [1, 0]
else:
mask1 = escript.whereZero(z - self._ztop)
r += mask1 * [
self._ks * (self._ztop - airLayerLevel) + 1, self._ks *
(self._ztop - airLayerLevel)
]
self._q = (mask0 + mask1) * [1, 1]
self._r = r
#====================================
self.__tol = tol
self._directSolver = directSolver
self._saveMemory = saveMemory
self.__pde = None
if not saveMemory:
self.__pde = self.setUpPDE()
