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test_Richards_empirical.py
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test_Richards_empirical.py
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from __future__ import print_function
import unittest
import numpy as np
from discretize.Tests import checkDerivative
from SimPEG import Mesh
from SimPEG import Maps
from SimPEG.FLOW import Richards
TOL = 1E-8
np.random.seed(2)
class TestModels(unittest.TestCase):
def test_haverkamp_theta_u(self):
mesh = Mesh.TensorMesh([50])
hav = Richards.Empirical.Haverkamp_theta(mesh)
passed = checkDerivative(
lambda u: (hav(u), hav.derivU(u)),
np.random.randn(50),
plotIt=False
)
self.assertTrue(passed, True)
def test_haverkamp_theta_m(self):
mesh = Mesh.TensorMesh([50])
idnmap = Maps.IdentityMap(nP=mesh.nC)
seeds = {
'theta_r': np.random.rand(mesh.nC),
'theta_s': np.random.rand(mesh.nC),
'alpha': np.random.rand(mesh.nC),
'beta': np.random.rand(mesh.nC),
}
opts = [
('theta_r',
dict(theta_rMap=idnmap), 1),
('theta_s',
dict(theta_sMap=idnmap), 1),
('alpha',
dict(alphaMap=idnmap), 1),
('beta',
dict(betaMap=idnmap), 1),
]
u = np.random.randn(mesh.nC)
for name, opt, nM in opts:
van = Richards.Empirical.Haverkamp_theta(mesh, **opt)
x0 = np.concatenate([seeds[n] for n in name.split('-')])
def fun(m):
van.model = m
return van(u), van.derivM(u)
print('Haverkamp_theta test m deriv: ', name)
passed = checkDerivative(
fun,
x0,
plotIt=False
)
self.assertTrue(passed, True)
def test_vangenuchten_theta_u(self):
mesh = Mesh.TensorMesh([50])
van = Richards.Empirical.Vangenuchten_theta(mesh)
passed = checkDerivative(
lambda u: (van(u), van.derivU(u)),
np.random.randn(50),
plotIt=False
)
self.assertTrue(passed, True)
def test_vangenuchten_theta_m(self):
mesh = Mesh.TensorMesh([50])
idnmap = Maps.IdentityMap(nP=mesh.nC)
seeds = {
'theta_r': np.random.rand(mesh.nC),
'theta_s': np.random.rand(mesh.nC),
'n': np.random.rand(mesh.nC) + 1,
'alpha': np.random.rand(mesh.nC),
}
opts = [
('theta_r',
dict(theta_rMap=idnmap), 1),
('theta_s',
dict(theta_sMap=idnmap), 1),
('n',
dict(nMap=idnmap), 1),
('alpha',
dict(alphaMap=idnmap), 1),
]
u = np.random.randn(mesh.nC)
for name, opt, nM in opts:
van = Richards.Empirical.Vangenuchten_theta(mesh, **opt)
x0 = np.concatenate([seeds[n] for n in name.split('-')])
def fun(m):
van.model = m
return van(u), van.derivM(u)
print('Vangenuchten_theta test m deriv: ', name)
passed = checkDerivative(
fun,
x0,
plotIt=False
)
self.assertTrue(passed, True)
def test_haverkamp_k_u(self):
mesh = Mesh.TensorMesh([5])
hav = Richards.Empirical.Haverkamp_k(mesh)
print('Haverkamp_k test u deriv')
passed = checkDerivative(
lambda u: (hav(u), hav.derivU(u)),
np.random.randn(mesh.nC),
plotIt=False
)
self.assertTrue(passed, True)
def test_haverkamp_k_m(self):
mesh = Mesh.TensorMesh([5])
expmap = Maps.IdentityMap(nP=mesh.nC)
wires2 = Maps.Wires(('one', mesh.nC), ('two', mesh.nC))
wires3 = Maps.Wires(
('one', mesh.nC), ('two', mesh.nC), ('three', mesh.nC)
)
opts = [
('Ks',
dict(KsMap=expmap), 1),
('A',
dict(AMap=expmap), 1),
('gamma',
dict(gammaMap=expmap), 1),
('Ks-A',
dict(KsMap=expmap*wires2.one, AMap=expmap*wires2.two), 2),
('Ks-gamma',
dict(KsMap=expmap*wires2.one, gammaMap=expmap*wires2.two), 2),
('A-gamma',
dict(AMap=expmap*wires2.one, gammaMap=expmap*wires2.two), 2),
('Ks-A-gamma', dict(
KsMap=expmap*wires3.one,
AMap=expmap*wires3.two,
gammaMap=expmap*wires3.three), 3),
]
u = np.random.randn(mesh.nC)
for name, opt, nM in opts:
np.random.seed(2)
hav = Richards.Empirical.Haverkamp_k(mesh, **opt)
def fun(m):
hav.model = m
return hav(u), hav.derivM(u)
print('Haverkamp_k test m deriv: ', name)
passed = checkDerivative(
fun,
np.random.randn(mesh.nC * nM),
plotIt=False
)
self.assertTrue(passed, True)
def test_vangenuchten_k_u(self):
mesh = Mesh.TensorMesh([50])
van = Richards.Empirical.Vangenuchten_k(mesh)
print('Vangenuchten_k test u deriv')
passed = checkDerivative(
lambda u: (van(u), van.derivU(u)),
np.random.randn(mesh.nC),
plotIt=False
)
self.assertTrue(passed, True)
def test_vangenuchten_k_m(self):
mesh = Mesh.TensorMesh([50])
expmap = Maps.ExpMap(nP=mesh.nC)
idnmap = Maps.IdentityMap(nP=mesh.nC)
seeds = {
'Ks': np.random.triangular(
np.log(1e-7), np.log(1e-6), np.log(1e-5), mesh.nC
),
'I': np.random.rand(mesh.nC),
'n': np.random.rand(mesh.nC) + 1,
'alpha': np.random.rand(mesh.nC),
}
opts = [
('Ks',
dict(KsMap=expmap), 1),
('I',
dict(IMap=idnmap), 1),
('n',
dict(nMap=idnmap), 1),
('alpha',
dict(alphaMap=idnmap), 1),
]
u = np.random.randn(mesh.nC)
for name, opt, nM in opts:
van = Richards.Empirical.Vangenuchten_k(mesh, **opt)
x0 = np.concatenate([seeds[n] for n in name.split('-')])
def fun(m):
van.model = m
return van(u), van.derivM(u)
print('Vangenuchten_k test m deriv: ', name)
passed = checkDerivative(
fun,
x0,
plotIt=False
)
self.assertTrue(passed, True)
if __name__ == '__main__':
unittest.main()