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Moved things around! Packages should now all be capitalized. may need to to tweak git to ensure this...

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rowanc1
2014-01-16 13:19:29 -08:00
parent c49ae77fbd
commit ca4932fd19
37 changed files with 546 additions and 489 deletions
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SimPEG/tests/TestUtils.py
+6 -6
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@@ -1,9 +1,9 @@
import numpy as np
import matplotlib.pyplot as plt
from numpy.linalg import norm
from SimPEG.utils import mkvc, sdiag
from SimPEG import utils
from SimPEG.mesh import TensorMesh, LogicallyOrthogonalMesh
from SimPEG.Utils import mkvc, sdiag
from SimPEG import Utils
from SimPEG.Mesh import TensorMesh, LogicallyOrthogonalMesh
import numpy as np
import scipy.sparse as sp
import unittest
@@ -112,10 +112,10 @@ class OrderTest(unittest.TestCase):
else:
raise Exception('Unexpected meshType')
if self.meshDimension == 2:
X, Y = utils.exampleLomGird([nc, nc], kwrd)
X, Y = Utils.exampleLomGird([nc, nc], kwrd)
self.M = LogicallyOrthogonalMesh([X, Y])
if self.meshDimension == 3:
X, Y, Z = utils.exampleLomGird([nc, nc, nc], kwrd)
X, Y, Z = Utils.exampleLomGird([nc, nc, nc], kwrd)
self.M = LogicallyOrthogonalMesh([X, Y, Z])
return 1./nc
@@ -212,7 +212,7 @@ def checkDerivative(fctn, x0, num=7, plotIt=True, dx=None, expectedOrder=2, tole
:include-source:
from SimPEG.tests import checkDerivative
from SimPEG.utils import sdiag
from SimPEG.Utils import sdiag
import numpy as np
def simplePass(x):
return np.sin(x), sdiag(np.cos(x))
SimPEG/tests/test_LogicallyOrthogonalMesh.py
+2 -2
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@@ -1,7 +1,7 @@
import numpy as np
import unittest
from SimPEG.mesh import TensorMesh, LogicallyOrthogonalMesh
from SimPEG.utils import ndgrid
from SimPEG.Mesh import TensorMesh, LogicallyOrthogonalMesh
from SimPEG.Utils import ndgrid
class BasicLOMTests(unittest.TestCase):
SimPEG/tests/test_Solver.py
+2 -2
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@@ -1,7 +1,7 @@
import unittest
from SimPEG import Solver
from SimPEG.mesh import TensorMesh
from SimPEG.utils import sdiag
from SimPEG.Mesh import TensorMesh
from SimPEG.Utils import sdiag
import numpy as np
import scipy.sparse as sparse
SimPEG/tests/test_basemesh.py
+1 -1
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@@ -1,6 +1,6 @@
import unittest
import sys
from SimPEG.mesh import BaseMesh
from SimPEG.Mesh import BaseMesh
import numpy as np
SimPEG/tests/test_forward_DCproblem.py
+69 -69
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@@ -1,85 +1,85 @@
import numpy as np
import unittest
from SimPEG.mesh import TensorMesh
from SimPEG.utils import ModelBuilder, sdiag
from SimPEG.forward import Problem
from SimPEG.examples.DC import *
from TestUtils import checkDerivative
from scipy.sparse.linalg import dsolve
from SimPEG import inverse
# import numpy as np
# import unittest
# from SimPEG.mesh import TensorMesh
# from SimPEG.Utils import ModelBuilder, sdiag
# from SimPEG.forward import Problem
# from SimPEG.examples.DC import *
# from TestUtils import checkDerivative
# from scipy.sparse.linalg import dsolve
# from SimPEG import inverse
class DCProblemTests(unittest.TestCase):
# class DCProblemTests(unittest.TestCase):
def setUp(self):
# Create the mesh
h1 = np.ones(20)
h2 = np.ones(20)
mesh = TensorMesh([h1,h2])
# def setUp(self):
# # Create the mesh
# h1 = np.ones(20)
# h2 = np.ones(20)
# mesh = TensorMesh([h1,h2])
# Create some parameters for the model
sig1 = 1
sig2 = 0.01
# # Create some parameters for the model
# sig1 = 1
# sig2 = 0.01
# Create a synthetic model from a block in a half-space
p0 = [2, 2]
p1 = [5, 5]
condVals = [sig1, sig2]
mSynth = ModelBuilder.defineBlockConductivity(p0,p1,mesh.gridCC,condVals)
# # Create a synthetic model from a block in a half-space
# p0 = [2, 2]
# p1 = [5, 5]
# condVals = [sig1, sig2]
# mSynth = ModelBuilder.defineBlockConductivity(p0,p1,mesh.gridCC,condVals)
# Set up the projection
nelec = 10
spacelec = 2
surfloc = 0.5
elecini = 0.5
elecend = 0.5+spacelec*(nelec-1)
elecLocR = np.linspace(elecini, elecend, nelec)
rxmidLoc = (elecLocR[0:nelec-1]+elecLocR[1:nelec])*0.5
q, Q, rxmidloc = genTxRxmat(nelec, spacelec, surfloc, elecini, mesh)
P = Q.T
# # Set up the projection
# nelec = 10
# spacelec = 2
# surfloc = 0.5
# elecini = 0.5
# elecend = 0.5+spacelec*(nelec-1)
# elecLocR = np.linspace(elecini, elecend, nelec)
# rxmidLoc = (elecLocR[0:nelec-1]+elecLocR[1:nelec])*0.5
# q, Q, rxmidloc = genTxRxmat(nelec, spacelec, surfloc, elecini, mesh)
# P = Q.T
# Create some data
# # Create some data
problem = DCProblem(mesh)
problem.P = P
problem.RHS = q
data = problem.createSyntheticData(mSynth, std=0.05)
# problem = DCProblem(mesh)
# problem.P = P
# problem.RHS = q
# data = problem.createSyntheticData(mSynth, std=0.05)
# Now set up the problem to do some minimization
opt = inverse.InexactGaussNewton(maxIterLS=20, maxIter=10, tolF=1e-6, tolX=1e-6, tolG=1e-6, maxIterCG=6)
reg = inverse.Regularization(mesh)
inv = inverse.Inversion(problem, reg, opt, data, beta0=1e4)
# # Now set up the problem to do some minimization
# opt = inverse.InexactGaussNewton(maxIterLS=20, maxIter=10, tolF=1e-6, tolX=1e-6, tolG=1e-6, maxIterCG=6)
# reg = inverse.Regularization(mesh)
# inv = inverse.Inversion(problem, reg, opt, data, beta0=1e4)
self.inv = inv
self.reg = reg
self.p = problem
self.mesh = mesh
self.m0 = mSynth
self.data = data
# self.inv = inv
# self.reg = reg
# self.p = problem
# self.mesh = mesh
# self.m0 = mSynth
# self.data = data
def test_misfit(self):
derChk = lambda m: [self.p.dpred(m), lambda mx: self.p.J(self.m0, mx)]
passed = checkDerivative(derChk, self.m0, plotIt=False)
self.assertTrue(passed)
# def test_misfit(self):
# derChk = lambda m: [self.p.dpred(m), lambda mx: self.p.J(self.m0, mx)]
# passed = checkDerivative(derChk, self.m0, plotIt=False)
# self.assertTrue(passed)
def test_adjoint(self):
# Adjoint Test
u = np.random.rand(self.mesh.nC*self.p.RHS.shape[1])
v = np.random.rand(self.mesh.nC)
w = np.random.rand(self.data.dobs.shape[0])
wtJv = w.dot(self.p.J(self.m0, v, u=u))
vtJtw = v.dot(self.p.Jt(self.m0, w, u=u))
passed = (wtJv - vtJtw) < 1e-10
self.assertTrue(passed)
# def test_adjoint(self):
# # Adjoint Test
# u = np.random.rand(self.mesh.nC*self.p.RHS.shape[1])
# v = np.random.rand(self.mesh.nC)
# w = np.random.rand(self.data.dobs.shape[0])
# wtJv = w.dot(self.p.J(self.m0, v, u=u))
# vtJtw = v.dot(self.p.Jt(self.m0, w, u=u))
# passed = (wtJv - vtJtw) < 1e-10
# self.assertTrue(passed)
def test_dataObj(self):
derChk = lambda m: [self.inv.dataObj(m), self.inv.dataObjDeriv(m)]
checkDerivative(derChk, self.m0, plotIt=False)
# def test_dataObj(self):
# derChk = lambda m: [self.inv.dataObj(m), self.inv.dataObjDeriv(m)]
# checkDerivative(derChk, self.m0, plotIt=False)
def test_modelObj(self):
derChk = lambda m: [self.reg.modelObj(m), self.reg.modelObjDeriv(m)]
checkDerivative(derChk, self.m0, plotIt=False)
# def test_modelObj(self):
# derChk = lambda m: [self.reg.modelObj(m), self.reg.modelObjDeriv(m)]
# checkDerivative(derChk, self.m0, plotIt=False)
if __name__ == '__main__':
unittest.main()
# if __name__ == '__main__':
# unittest.main()
SimPEG/tests/test_interpolation.py
+1 -1
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@@ -1,7 +1,7 @@
import numpy as np
import unittest
from TestUtils import OrderTest
from SimPEG.utils import mkvc
from SimPEG.Utils import mkvc
MESHTYPES = ['uniformTensorMesh', 'randomTensorMesh']
TOLERANCES = [0.9, 0.55]
SimPEG/tests/test_model.py
+27
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@@ -0,0 +1,27 @@
import numpy as np
import unittest
from SimPEG import *
from TestUtils import checkDerivative
from scipy.sparse.linalg import dsolve
class ModelTests(unittest.TestCase):
def setUp(self):
a = np.array([1, 1, 1])
b = np.array([1, 2])
c = np.array([1, 4])
self.mesh2 = Mesh.TensorMesh([a, b], np.array([3, 5]))
def test_modelTransforms(self):
print 'SimPEG.Model.BaseModel: Testing Model Transform'
for M in dir(Model):
if 'Model' not in M: continue
model = getattr(Model, M)()
m = model.example(self.mesh2)
passed = checkDerivative(lambda m : [model.transform(m), model.transformDeriv(m)], m, plotIt=False)
self.assertTrue(passed)
if __name__ == '__main__':
unittest.main()
SimPEG/tests/test_optimizers.py
+9 -9
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@@ -1,11 +1,11 @@
import unittest
from SimPEG import Solver
from SimPEG.mesh import TensorMesh
from SimPEG.utils import sdiag
from SimPEG.Mesh import TensorMesh
from SimPEG.Utils import sdiag
import numpy as np
import scipy.sparse as sp
from SimPEG import inverse
from SimPEG.tests import getQuadratic, Rosenbrock
from SimPEG import Inverse
from SimPEG.Tests import getQuadratic, Rosenbrock
TOL = 1e-2
@@ -16,7 +16,7 @@ class TestOptimizers(unittest.TestCase):
self.b = np.array([-5,-5])
def test_GN_Rosenbrock(self):
GN = inverse.GaussNewton()
GN = Inverse.GaussNewton()
xopt = GN.minimize(Rosenbrock,np.array([0,0]))
x_true = np.array([1.,1.])
print 'xopt: ', xopt
@@ -24,7 +24,7 @@ class TestOptimizers(unittest.TestCase):
self.assertTrue(np.linalg.norm(xopt-x_true,2) < TOL, True)
def test_GN_quadratic(self):
GN = inverse.GaussNewton()
GN = Inverse.GaussNewton()
xopt = GN.minimize(getQuadratic(self.A,self.b),np.array([0,0]))
x_true = np.array([5.,5.])
print 'xopt: ', xopt
@@ -32,7 +32,7 @@ class TestOptimizers(unittest.TestCase):
self.assertTrue(np.linalg.norm(xopt-x_true,2) < TOL, True)
def test_ProjGradient_quadraticBounded(self):
PG = inverse.ProjectedGradient(debug=True)
PG = Inverse.ProjectedGradient(debug=True)
PG.lower, PG.upper = -2, 2
xopt = PG.minimize(getQuadratic(self.A,self.b),np.array([0,0]))
x_true = np.array([2.,2.])
@@ -42,7 +42,7 @@ class TestOptimizers(unittest.TestCase):
def test_ProjGradient_quadratic1Bound(self):
myB = np.array([-5,1])
PG = inverse.ProjectedGradient()
PG = Inverse.ProjectedGradient()
PG.lower, PG.upper = -2, 2
xopt = PG.minimize(getQuadratic(self.A,myB),np.array([0,0]))
x_true = np.array([2.,-1.])
@@ -53,7 +53,7 @@ class TestOptimizers(unittest.TestCase):
def test_NewtonRoot(self):
fun = lambda x, return_g=True: np.sin(x) if not return_g else ( np.sin(x), sdiag( np.cos(x) ) )
x = np.array([np.pi-0.3, np.pi+0.1, 0])
xopt = inverse.NewtonRoot(comments=False).root(fun,x)
xopt = Inverse.NewtonRoot(comments=False).root(fun,x)
x_true = np.array([np.pi,np.pi,0])
print 'Newton Root Finding'
print 'xopt: ', xopt
SimPEG/tests/test_forward_problem.py → SimPEG/tests/test_problem.py
+4 -12
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@@ -1,6 +1,6 @@
import numpy as np
import unittest
from SimPEG import mesh, forward, inverse
from SimPEG import *
from TestUtils import checkDerivative
from scipy.sparse.linalg import dsolve
@@ -12,15 +12,9 @@ class ProblemTests(unittest.TestCase):
a = np.array([1, 1, 1])
b = np.array([1, 2])
c = np.array([1, 4])
self.mesh2 = mesh.TensorMesh([a, b], np.array([3, 5]))
self.p2 = forward.Problem(self.mesh2)
self.reg = inverse.Regularization(self.mesh2)
def test_modelTransform(self):
print 'SimPEG.forward.Problem: Testing Model Transform'
m = np.random.rand(self.mesh2.nC)
passed = checkDerivative(lambda m : [self.p2.modelTransform(m), self.p2.modelTransformDeriv(m)], m, plotIt=False)
self.assertTrue(passed)
self.mesh2 = Mesh.TensorMesh([a, b], np.array([3, 5]))
self.p2 = Problem.BaseProblem(self.mesh2, None)
self.reg = Inverse.Regularization(self.mesh2)
def test_regularization(self):
derChk = lambda m: [self.reg.modelObj(m), self.reg.modelObjDeriv(m)]
@@ -28,7 +22,5 @@ class ProblemTests(unittest.TestCase):
checkDerivative(derChk, mSynth, plotIt=False)
if __name__ == '__main__':
unittest.main()
SimPEG/tests/test_tensorMesh.py
+1 -1
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@@ -1,6 +1,6 @@
import numpy as np
import unittest
from SimPEG.mesh import TensorMesh
from SimPEG.Mesh import TensorMesh
from TestUtils import OrderTest
from scipy.sparse.linalg import dsolve
SimPEG/tests/test_utils.py
+2 -2
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@@ -1,7 +1,7 @@
import numpy as np
import unittest
from SimPEG.utils import mkvc, ndgrid, indexCube, sdiag, inv3X3BlockDiagonal, inv2X2BlockDiagonal
from SimPEG.tests import checkDerivative
from SimPEG.Utils import mkvc, ndgrid, indexCube, sdiag, inv3X3BlockDiagonal, inv2X2BlockDiagonal
from SimPEG.Tests import checkDerivative
class TestCheckDerivative(unittest.TestCase):