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Merge pull request #354 from simpeg/dev

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Two new examples.
This commit is contained in:
Lindsey Heagy
2016-06-29 09:46:33 -07:00
committed by GitHub
parent 6d6e7fc8bd 394dc9106a
commit ecbdd90f63
13 changed files with 251 additions and 90 deletions
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.gitignore
+1
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@@ -40,3 +40,4 @@ nosetests.xml
docs/_build/
Makefile
docs/warnings.txt
.DS_Store
SimPEG/Directives.py
+26 -13
View File
@@ -253,8 +253,7 @@ class SaveOutputDictEveryIteration(SaveEveryIteration):
class Update_IRLS(InversionDirective):
eps_min = None
eps_p = None
eps_q = None
eps = None
norms = [2.,2.,2.,2.]
factor = None
gamma = None
@@ -263,6 +262,7 @@ class Update_IRLS(InversionDirective):
f_old = None
f_min_change = 1e-2
beta_tol = 5e-2
prctile = 95
# Solving parameter for IRLS (mode:2)
IRLSiter = 0
@@ -297,9 +297,22 @@ class Update_IRLS(InversionDirective):
print "Convergence with smooth l2-norm regularization: Start IRLS steps..."
self.mode = 2
print self.eps_p, self.eps_q, self.norms
self.reg.eps_p = self.eps_p
self.reg.eps_q = self.eps_q
# Either use the supplied epsilon, or fix base on distribution of
# model values
if getattr(self, 'reg.eps', None) is None:
self.reg.eps_p = np.percentile(np.abs(self.invProb.curModel),self.prctile)
else:
self.reg.eps_p = self.eps[0]
if getattr(self, 'reg.eps', None) is None:
self.reg.eps_q = np.percentile(np.abs(self.reg.regmesh.cellDiffxStencil*(self.reg.mapping * self.invProb.curModel)),self.prctile)
else:
self.reg.eps_q = self.eps[1]
print "L[p qx qy qz]-norm : " + str(self.reg.norms)
print "eps_p: " + str(self.reg.eps_p) + " eps_q: " + str(self.reg.eps_q)
self.reg.norms = self.norms
self.coolingFactor = 1.
self.coolingRate = 1
@@ -343,14 +356,14 @@ class Update_IRLS(InversionDirective):
else:
self.f_old = phim_new
# Cool the threshold parameter if required
if getattr(self, 'factor', None) is not None:
eps = self.reg.eps / self.factor
if getattr(self, 'eps_min', None) is not None:
self.reg.eps = np.max([self.eps_min,eps])
else:
self.reg.eps = eps
# # Cool the threshold parameter if required
# if getattr(self, 'factor', None) is not None:
# eps = self.reg.eps / self.factor
#
# if getattr(self, 'eps_min', None) is not None:
# self.reg.eps = np.max([self.eps_min,eps])
# else:
# self.reg.eps = eps
# Get phi_m at the end of current iteration
self.phi_m_last = self.invProb.phi_m_last
SimPEG/Examples/DC_Analytic_Dipole.py
+2 -2
View File
@@ -1,7 +1,7 @@
from SimPEG import *
import SimPEG.EM.Static.DC as DC
def run(plotIt=False):
def run(plotIt=True):
cs = 25.
hx = [(cs,7, -1.3),(cs,21),(cs,7, 1.3)]
hy = [(cs,7, -1.3),(cs,21),(cs,7, 1.3)]
@@ -65,4 +65,4 @@ def run(plotIt=False):
if __name__ == '__main__':
print run(plotIt=True)
print run()
SimPEG/Examples/Inversion_IRLS.py
+7 -29
View File
@@ -42,55 +42,33 @@ def run(N=100, plotIt=True):
survey = Survey.LinearSurvey()
survey.pair(prob)
survey.dobs = prob.fields(mtrue) + std_noise * np.random.randn(nk)
#survey.makeSyntheticData(mtrue, std=std_noise)
wd = np.ones(nk) * std_noise
#print survey.std[0]
#M = prob.mesh
# Distance weighting
wr = np.sum(prob.G**2.,axis=0)**0.5
wr = ( wr/np.max(wr) )
# reg = Regularization.Simple(mesh)
# reg.mref = mref
# reg.cell_weights = wr
#
dmis = DataMisfit.l2_DataMisfit(survey)
dmis.Wd = 1./wd
#
# opt = Optimization.ProjectedGNCG(maxIter=20,lower=-2.,upper=2., maxIterCG= 10, tolCG = 1e-4)
# invProb = InvProblem.BaseInvProblem(dmis, reg, opt)
# invProb.curModel = m0
#
# beta = Directives.BetaSchedule(coolingFactor=2, coolingRate=1)
# target = Directives.TargetMisfit()
#
betaest = Directives.BetaEstimate_ByEig()
# inv = Inversion.BaseInversion(invProb, directiveList=[beta, betaest, target])
#
#
# mrec = inv.run(m0)
# ml2 = mrec
# print "Final misfit:" + str(invProb.dmisfit.eval(mrec))
#
# # Switch regularization to sparse
# phim = invProb.phi_m_last
# phid = invProb.phi_d
reg = Regularization.Sparse(mesh)
reg.mref = mref
reg.cell_weights = wr
reg.mref = np.zeros(mesh.nC)
eps_p = 5e-2
eps_q = 5e-2
norms = [0., 0., 2., 2.]
opt = Optimization.ProjectedGNCG(maxIter=100 ,lower=-2.,upper=2., maxIterLS = 20, maxIterCG= 10, tolCG = 1e-3)
invProb = InvProblem.BaseInvProblem(dmis, reg, opt)
update_Jacobi = Directives.Update_lin_PreCond()
IRLS = Directives.Update_IRLS( norms=norms, eps_p=eps_p, eps_q=eps_q)
# Set the IRLS directive, penalize the lowest 25 percentile of model values
# Start with an l2-l2, then switch to lp-norms
norms = [0., 0., 2., 2.]
IRLS = Directives.Update_IRLS( norms=norms, prctile = 25, maxIRLSiter = 15, minGNiter=3)
inv = Inversion.BaseInversion(invProb, directiveList=[IRLS,betaest,update_Jacobi])
SimPEG/Examples/Maps_ComboMaps.py
+62
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@@ -0,0 +1,62 @@
from SimPEG import Mesh, Maps, np
def run(plotIt=True):
"""
Maps: ComboMaps
===============
We will use an example where we want a 1D layered earth as
our model, but we want to map this to a 2D discretization to do our forward
modeling. We will also assume that we are working in log conductivity still,
so after the transformation we want to map to conductivity space.
To do this we will introduce the vertical 1D map (:class:`SimPEG.Maps.SurjectVertical1D`),
which does the first part of what we just described. The second part will be
done by the :class:`SimPEG.Maps.ExpMap` described above.
.. code-block:: python
:linenos:
M = Mesh.TensorMesh([7,5])
v1dMap = Maps.SurjectVertical1D(M)
expMap = Maps.ExpMap(M)
myMap = expMap * v1dMap
m = np.r_[0.2,1,0.1,2,2.9] # only 5 model parameters!
sig = myMap * m
If you noticed, it was pretty easy to combine maps. What is even cooler is
that the derivatives also are made for you (if everything goes right).
Just to be sure that the derivative is correct, you should always run the test
on the mapping that you create.
"""
M = Mesh.TensorMesh([7,5])
v1dMap = Maps.SurjectVertical1D(M)
expMap = Maps.ExpMap(M)
myMap = expMap * v1dMap
m = np.r_[0.2,1,0.1,2,2.9] # only 5 model parameters!
sig = myMap * m
if not plotIt: return
import matplotlib.pyplot as plt
figs, axs = plt.subplots(1,2)
axs[0].plot(m, M.vectorCCy, 'b-o')
axs[0].set_title('Model')
axs[0].set_ylabel('Depth, y')
axs[0].set_xlabel('Value, $m_i$')
axs[0].set_xlim(0,3)
axs[0].set_ylim(0,1)
clbar = plt.colorbar(M.plotImage(sig,ax=axs[1],grid=True,gridOpts=dict(color='grey'))[0])
axs[1].set_title('Physical Property')
axs[1].set_ylabel('Depth, y')
clbar.set_label('$\sigma = \exp(\mathbf{P}m)$')
plt.tight_layout()
plt.show()
if __name__ == '__main__':
run()
SimPEG/Examples/Maps_Mesh2Mesh.py
+41
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@@ -0,0 +1,41 @@
from SimPEG import Mesh, Maps, Utils
def run(plotIt=True):
"""
Maps: Mesh2Mesh
===============
This mapping allows you to go from one mesh to another.
"""
M = Mesh.TensorMesh([100,100])
h1 = Utils.meshTensor([(6,7,-1.5),(6,10),(6,7,1.5)])
h1 = h1/h1.sum()
M2 = Mesh.TensorMesh([h1,h1])
V = Utils.ModelBuilder.randomModel(M.vnC, seed=79, its=50)
v = Utils.mkvc(V)
modh = Maps.Mesh2Mesh([M,M2])
modH = Maps.Mesh2Mesh([M2,M])
H = modH * v
h = modh * H
if not plotIt: return
import matplotlib.pyplot as plt
ax = plt.subplot(131)
M.plotImage(v, ax=ax)
ax.set_title('Fine Mesh (Original)')
ax = plt.subplot(132)
M2.plotImage(H,clim=[0,1],ax=ax)
ax.set_title('Course Mesh')
ax = plt.subplot(133)
M.plotImage(h,clim=[0,1],ax=ax)
ax.set_title('Fine Mesh (Interpolated)')
plt.show()
if __name__ == '__main__':
run()
SimPEG/Examples/Utils_surface2ind_topo.py
+1 -1
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@@ -2,7 +2,7 @@ from SimPEG import *
from SimPEG.Utils import surface2ind_topo
def run(plotIt=False, nx=5, ny=5):
def run(plotIt=True, nx=5, ny=5):
"""
Utils: surface2ind_topo
SimPEG/Examples/__init__.py
+3 -1
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@@ -10,6 +10,8 @@ import EM_TDEM_1D_Inversion
import FLOW_Richards_1D_Celia1990
import Inversion_IRLS
import Inversion_Linear
import Maps_ComboMaps
import Maps_Mesh2Mesh
import Mesh_Basic_ForwardDC
import Mesh_Basic_PlotImage
import Mesh_Basic_Types
@@ -22,7 +24,7 @@ import MT_1D_ForwardAndInversion
import MT_3D_Foward
import Utils_surface2ind_topo
__examples__ = ["DC_Analytic_Dipole", "DC_Forward_PseudoSection", "EM_FDEM_1D_Inversion", "EM_FDEM_Analytic_MagDipoleWholespace", "EM_Schenkel_Morrison_Casing", "EM_TDEM_1D_Inversion", "FLOW_Richards_1D_Celia1990", "Inversion_IRLS", "Inversion_Linear", "Mesh_Basic_ForwardDC", "Mesh_Basic_PlotImage", "Mesh_Basic_Types", "Mesh_Operators_CahnHilliard", "Mesh_QuadTree_Creation", "Mesh_QuadTree_FaceDiv", "Mesh_QuadTree_HangingNodes", "Mesh_Tensor_Creation", "MT_1D_ForwardAndInversion", "MT_3D_Foward", "Utils_surface2ind_topo"]
__examples__ = ["DC_Analytic_Dipole", "DC_Forward_PseudoSection", "EM_FDEM_1D_Inversion", "EM_FDEM_Analytic_MagDipoleWholespace", "EM_Schenkel_Morrison_Casing", "EM_TDEM_1D_Inversion", "FLOW_Richards_1D_Celia1990", "Inversion_IRLS", "Inversion_Linear", "Maps_ComboMaps", "Maps_Mesh2Mesh", "Mesh_Basic_ForwardDC", "Mesh_Basic_PlotImage", "Mesh_Basic_Types", "Mesh_Operators_CahnHilliard", "Mesh_QuadTree_Creation", "Mesh_QuadTree_FaceDiv", "Mesh_QuadTree_HangingNodes", "Mesh_Tensor_Creation", "MT_1D_ForwardAndInversion", "MT_3D_Foward", "Utils_surface2ind_topo"]
##### AUTOIMPORTS #####
SimPEG/Maps.py
+3 -1
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@@ -502,7 +502,9 @@ class InjectActiveCells(IdentityMap):
if Utils.isScalar(valInactive):
self.valInactive = np.ones(self.nC)*float(valInactive)
else:
self.valInactive = valInactive.copy()
self.valInactive = np.ones(self.nC)
self.valInactive[self.indInactive] = valInactive.copy()
self.valInactive[self.indActive] = 0
inds = np.nonzero(self.indActive)[0]
docs/content/api_core/api_Maps.rst
+4 -43
View File
@@ -63,26 +63,8 @@ done by the :class:`SimPEG.Maps.ExpMap` described above.
.. plot::
from SimPEG import *
import matplotlib.pyplot as plt
M = Mesh.TensorMesh([7,5])
v1dMap = Maps.SurjectVertical1D(M)
expMap = Maps.ExpMap(M)
myMap = expMap * v1dMap
m = np.r_[0.2,1,0.1,2,2.9] # only 5 model parameters!
sig = myMap * m
figs, axs = plt.subplots(1,2)
axs[0].plot(m, M.vectorCCy, 'b-o')
axs[0].set_title('Model')
axs[0].set_ylabel('Depth, y')
axs[0].set_xlabel('Value, $m_i$')
axs[0].set_xlim(0,3)
axs[0].set_ylim(0,1)
clbar = plt.colorbar(M.plotImage(sig,ax=axs[1],grid=True,gridOpts=dict(color='grey'))[0])
axs[1].set_title('Physical Property')
axs[1].set_ylabel('Depth, y')
clbar.set_label('$\sigma = \exp(\mathbf{P}m)$')
plt.tight_layout()
from SimPEG import Examples
Examples.Maps_ComboMaps.run()
If you noticed, it was pretty easy to combine maps. What is even cooler is
that the derivatives also are made for you (if everything goes right).
@@ -167,31 +149,10 @@ Map 2D Cross-Section to 3D Model
Mesh to Mesh Map
----------------
.. plot::
from SimPEG import *
import matplotlib.pyplot as plt
M = Mesh.TensorMesh([100,100])
h1 = Utils.meshTensor([(6,7,-1.5),(6,10),(6,7,1.5)])
h1 = h1/h1.sum()
M2 = Mesh.TensorMesh([h1,h1])
V = Utils.ModelBuilder.randomModel(M.vnC, seed=79, its=50)
v = Utils.mkvc(V)
modh = Maps.Mesh2Mesh([M,M2])
modH = Maps.Mesh2Mesh([M2,M])
H = modH * v
h = modh * H
ax = plt.subplot(131)
M.plotImage(v, ax=ax)
ax.set_title('Fine Mesh (Original)')
ax = plt.subplot(132)
M2.plotImage(H,clim=[0,1],ax=ax)
ax.set_title('Course Mesh')
ax = plt.subplot(133)
M.plotImage(h,clim=[0,1],ax=ax)
ax.set_title('Fine Mesh (Interpolated)')
plt.show()
from SimPEG import Examples
Examples.Maps_Mesh2Mesh.run()
.. autoclass:: SimPEG.Maps.Mesh2Mesh
docs/content/examples/Inversion_IRLS.rst
+26
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@@ -0,0 +1,26 @@
.. _examples_Inversion_IRLS:
.. --------------------------------- ..
.. ..
.. THIS FILE IS AUTO GENEREATED ..
.. ..
.. SimPEG/Examples/__init__.py ..
.. ..
.. --------------------------------- ..
Inversion: Linear Problem
=========================
Here we go over the basics of creating a linear problem and inversion.
.. plot::
from SimPEG import Examples
Examples.Inversion_IRLS.run()
.. literalinclude:: ../../../SimPEG/Examples/Inversion_IRLS.py
:language: python
:linenos:
docs/content/examples/Maps_ComboMaps.rst
+48
View File
@@ -0,0 +1,48 @@
.. _examples_Maps_ComboMaps:
.. --------------------------------- ..
.. ..
.. THIS FILE IS AUTO GENEREATED ..
.. ..
.. SimPEG/Examples/__init__.py ..
.. ..
.. --------------------------------- ..
Maps: ComboMaps
===============
We will use an example where we want a 1D layered earth as
our model, but we want to map this to a 2D discretization to do our forward
modeling. We will also assume that we are working in log conductivity still,
so after the transformation we want to map to conductivity space.
To do this we will introduce the vertical 1D map (:class:`SimPEG.Maps.SurjectVertical1D`),
which does the first part of what we just described. The second part will be
done by the :class:`SimPEG.Maps.ExpMap` described above.
.. code-block:: python
:linenos:
M = Mesh.TensorMesh([7,5])
v1dMap = Maps.SurjectVertical1D(M)
expMap = Maps.ExpMap(M)
myMap = expMap * v1dMap
m = np.r_[0.2,1,0.1,2,2.9] # only 5 model parameters!
sig = myMap * m
If you noticed, it was pretty easy to combine maps. What is even cooler is
that the derivatives also are made for you (if everything goes right).
Just to be sure that the derivative is correct, you should always run the test
on the mapping that you create.
.. plot::
from SimPEG import Examples
Examples.Maps_ComboMaps.run()
.. literalinclude:: ../../../SimPEG/Examples/Maps_ComboMaps.py
:language: python
:linenos:
docs/content/examples/Maps_Mesh2Mesh.rst
+27
View File
@@ -0,0 +1,27 @@
.. _examples_Maps_Mesh2Mesh:
.. --------------------------------- ..
.. ..
.. THIS FILE IS AUTO GENEREATED ..
.. ..
.. SimPEG/Examples/__init__.py ..
.. ..
.. --------------------------------- ..
Maps: Mesh2Mesh
===============
This mapping allows you to go from one mesh to another.
.. plot::
from SimPEG import Examples
Examples.Maps_Mesh2Mesh.run()
.. literalinclude:: ../../../SimPEG/Examples/Maps_Mesh2Mesh.py
:language: python
:linenos: