def generatePerturbation():
PERT_DX = 500.0
PERT_AMPLITUDE = 1.0e-2
x = numpy.arange(XLIM[0],
XLIM[1] + 0.1 * PERT_DX,
PERT_DX,
dtype=numpy.float64)
y = numpy.arange(YLIM[0],
YLIM[1] + 0.1 * PERT_DX,
PERT_DX,
dtype=numpy.float64)
xgrid, ygrid = numpy.meshgrid(x, y)
points = numpy.vstack((xgrid.ravel(), ygrid.ravel())).transpose()
npts = points.shape[0]
disp = PERT_AMPLITUDE * (numpy.random.rand(npts, 2) - 0.5)
disp_dot = 0 * disp
# Create writer for spatial database file
writer = createWriter(
"IsotropicLinearMaxwellPlaneStrain_VarStrain_pert.spatialdb")
writer.write({
'points':
points,
'x':
x,
'y':
y,
'coordsys':
cs,
'data_dim':
2,
'values': [
{
'name': "displacement_x",
'units': "m",
'data': disp[:, 0]
},
{
'name': "displacement_y",
'units': "m",
'data': disp[:, 1]
},
{
'name': "displacement_dot_x",
'units': "m/s",
'data': disp_dot[:, 0]
},
{
'name': "displacement_dot_y",
'units': "m/s",
'data': disp_dot[:, 1]
},
]
})
return
def generateSolution():
disp = numpy.zeros((npts, 2))
disp[:, 0] = (A * PX**2 + 2.0 * B * PX * PY + C * PY**2) * \
math.exp(-TIME / maxwellTime)
disp[:, 1] = (A * PY**2 + 2.0 * B * PX * PY + C * PX**2) * \
math.exp(-TIME / maxwellTime)
disp_dot = numpy.zeros((npts, 2))
disp_dot[:, 0] = -(A * PX**2 + 2.0 * B * PX * PY + C * PY**2) * math.exp(
-TIME / maxwellTime) / maxwellTime
disp_dot[:, 1] = -(A * PY**2 + 2.0 * B * PX * PY + C * PX**2) * math.exp(
-TIME / maxwellTime) / maxwellTime
# Create writer for spatial database file
writer = createWriter(
"IsotropicLinearMaxwellPlaneStrain_VarStrain_soln.spatialdb")
writer.write({
'points':
points,
'x':
x,
'y':
y,
'coordsys':
cs,
'data_dim':
2,
'values': [
{
'name': "displacement_x",
'units': "m",
'data': disp[:, 0]
},
{
'name': "displacement_y",
'units': "m",
'data': disp[:, 1]
},
{
'name': "displacement_dot_x",
'units': "m/s",
'data': disp_dot[:, 0]
},
{
'name': "displacement_dot_y",
'units': "m/s",
'data': disp_dot[:, 1]
},
]
})
return
def _writeSpatialdb(self):
"""Write spatial database with fault slip.
"""
llSlipInfo = {
'name': "left-lateral-slip",
'units': "m",
'data': self.faultSlip[:, 0]
}
udSlipInfo = {
'name': "reverse-slip",
'units': "m",
'data': self.faultSlip[:, 1]
}
openInfo = {
'name': "fault-opening",
'units': "m",
'data': self.faultSlip[:, 2]
}
data = {
'num-x': self.lon.shape[0],
'num-y': self.lat.shape[0],
'num-z': 1,
'points': self.grid,
'x': self.lon,
'y': self.lat,
'z': self.z,
'coordsys': self.coordsys,
'data_dim': 2,
'values': [llSlipInfo, udSlipInfo, openInfo]
}
writer = createWriter(self.dbFilename)
writer.write(data)
def generateAuxSubfields():
totalStrain_11 = (2.0 * A * PX + B * PY) * math.exp(-TIME / maxwellTime)
totalStrain_12 = (B * PX / 2.0 + B * PY / 2.0 + C * PX +
C * PY) * math.exp(-TIME / maxwellTime)
totalStrain_22 = (2.0 * A * PY + B * PX) * math.exp(-TIME / maxwellTime)
totalStrain_33 = numpy.zeros_like(totalStrain_22)
visStrain_11 = (math.exp(TIME / maxwellTime) - 1.0) * (A * PX - A * PY - B * PX + B * PY) * \
math.exp(-2.0 * TIME / maxwellTime)
visStrain_12 = (math.exp(TIME / maxwellTime) - 1.0) * (B * PX + B * PY + C * PX + C * PY) * \
math.exp(-2.0 * TIME / maxwellTime)
visStrain_22 = -(math.exp(TIME / maxwellTime) - 1.0) * (A * PX - A * PY - B * PX + B * PY) * \
math.exp(-2.0 * TIME / maxwellTime)
visStrain_33 = -(math.exp(TIME / maxwellTime) - 1.0) * (A * PX + A * PY + B * PX + B * PY) * \
math.exp(-2.0 * TIME / maxwellTime)
equil_1 = 4.0 * bulkModulus * \
(A + B) * math.exp(-TIME / maxwellTime) * \
numpy.ones(npts, dtype=numpy.float64)
equil_2 = 4.0 * bulkModulus * \
(A + B) * math.exp(-TIME / maxwellTime) * \
numpy.ones(npts, dtype=numpy.float64)
writer = createWriter(
"IsotropicLinearMaxwellPlaneStrain_VarStrain_aux.spatialdb")
writer.write({
'points':
points,
'x':
x,
'y':
y,
'coordsys':
cs,
'data_dim':
2,
'values': [
{
'name': "vs",
'units': "m/s",
'data': vs
},
{
'name': "vp",
'units': "m/s",
'data': vp
},
{
'name': "density",
'units': "kg/m**3",
'data': density
},
{
'name': "viscosity",
'units': "Pa*s",
'data': viscosity
},
{
'name': "total_strain_xx",
'units': "None",
'data': totalStrain_11
},
{
'name': "total_strain_yy",
'units': "None",
'data': totalStrain_22
},
{
'name': "total_strain_zz",
'units': "None",
'data': totalStrain_33
},
{
'name': "total_strain_xy",
'units': "None",
'data': totalStrain_12
},
{
'name': "vis_strain_xx",
'units': "None",
'data': visStrain_11
},
{
'name': "vis_strain_yy",
'units': "None",
'data': visStrain_22
},
{
'name': "vis_strain_zz",
'units': "None",
'data': visStrain_33
},
{
'name': "vis_strain_xy",
'units': "None",
'data': visStrain_12
},
{
'name': "body_force_x",
'units': "N",
'data': equil_1
},
{
'name': "body_force_y",
'units': "N",
'data': equil_2
},
]
})
return
def test_io_3d(self):
from spatialdata.spatialdb.SimpleGridAscii import createWriter
filename = "data/gridio3d.spatialdb"
x = numpy.array([-2.0, 0.0, 3.0], dtype=numpy.float64)
y = numpy.array([0.0, 1.0], dtype=numpy.float64)
z = numpy.array([-2.0, -1.0, 2.0], dtype=numpy.float64)
points = numpy.array(
[
[-2.0, 0.0, -2.0],
[-2.0, 1.0, -2.0],
[-2.0, 0.0, -1.0],
[-2.0, 1.0, -1.0],
[-2.0, 0.0, 2.0],
[-2.0, 1.0, 2.0],
[0.0, 0.0, -2.0],
[0.0, 1.0, -2.0], # query (5.7, 8.2)
[0.0, 0.0, -1.0],
[0.0, 1.0, -1.0],
[0.0, 0.0, 2.0],
[0.0, 1.0, 2.0],
[3.0, 0.0, -2.0],
[3.0, 1.0, -2.0],
[3.0, 0.0, -1.0],
[3.0, 1.0, -1.0],
[3.0, 0.0, 2.0],
[3.0, 1.0, 2.0],
],
dtype=numpy.float64)
one = numpy.array([
6.6, 5.5, 2.3, 5.7, 6.3, 3.4, 7.2, 5.7, 3.4, 5.7, 9.4, 7.2, 4.8,
9.2, 5.8, 4.7, 7.8, 2.9
],
dtype=numpy.float64)
two = numpy.array([
3.4, 6.7, 4.1, 2.0, 6.7, 6.4, 6.8, 8.2, 9.8, 2.3, 8.5, 9.3, 7.5,
8.3, 8.5, 8.9, 6.2, 8.3
],
dtype=numpy.float64)
cs = CSCart()
writer = createWriter(filename)
writer.write({
'points':
points,
'x':
x,
'y':
y,
'z':
z,
'coordsys':
cs,
'data_dim':
3,
'values': [
{
'name': "one",
'units': "m",
'data': one
},
{
'name': "two",
'units': "m",
'data': two
},
]
})
db = SimpleGridDB()
db.inventory.label = "test"
db.inventory.queryType = "nearest"
db.inventory.filename = filename
db._configure()
self._db = db
locs = numpy.array([[0.1, 0.95, -1.8]], numpy.float64)
cs = CSCart()
cs._configure()
queryVals = ["two", "one"]
dataE = numpy.array([[8.2, 5.7]], numpy.float64)
errE = [0]
db = self._db
db.open()
db.setQueryValues(queryVals)
data = numpy.zeros(dataE.shape, dtype=numpy.float64)
err = []
nlocs = locs.shape[0]
for i in range(nlocs):
e = db.query(data[i, :], locs[i, :], cs)
err.append(e)
db.close()
self.assertEqual(len(errE), len(err))
for vE, v in zip(errE, err):
self.assertEqual(vE, v)
self.assertEqual(len(dataE.shape), len(data.shape))
for dE, d in zip(dataE.shape, data.shape):
self.assertEqual(dE, d)
for vE, v in zip(numpy.reshape(dataE, -1), numpy.reshape(data, -1)):
self.assertAlmostEqual(vE, v, 6)