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Doc testing, I think that is most of them!

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This commit is contained in:
Rowan Cockett
2016-05-29 22:18:22 -07:00
parent 231e6dbc93
commit 40f0874dfb
43 changed files with 365 additions and 230 deletions
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.gitignore
+1
View File
@@ -39,3 +39,4 @@ nosetests.xml
*.sublime-workspace
docs/_build/
Makefile
docs/warnings.txt
SimPEG/DCIP/BaseDC.py
+2 -2
View File
@@ -162,8 +162,8 @@ class ProblemDC_CC(Problem.BaseProblem):
"""
Makes the matrix A(m) for the DC resistivity problem.
:param numpy.array m: model
:rtype: scipy.csc_matrix
:param numpy.ndarray m: model
:rtype: scipy.sparse.csc_matrix
:return: A(m)
.. math::
SimPEG/DCIP/BaseIP.py
+1 -1
View File
@@ -71,7 +71,7 @@ class ProblemIP(Problem.BaseProblem):
Makes the matrix A(m) for the DC resistivity problem.
:param numpy.array m: model
:rtype: scipy.csc_matrix
:rtype: scipy.sparse.csc_matrix
:return: A(m)
.. math::
SimPEG/Directives.py
+4 -4
View File
@@ -166,7 +166,7 @@ class TargetMisfit(InversionDirective):
class _SaveEveryIteration(InversionDirective):
class SaveEveryIteration(InversionDirective):
@property
def name(self):
if getattr(self, '_name', None) is None:
@@ -187,7 +187,7 @@ class _SaveEveryIteration(InversionDirective):
self._fileName = value
class SaveModelEveryIteration(_SaveEveryIteration):
class SaveModelEveryIteration(SaveEveryIteration):
"""SaveModelEveryIteration"""
def initialize(self):
@@ -197,7 +197,7 @@ class SaveModelEveryIteration(_SaveEveryIteration):
np.save('%03d-%s' % (self.opt.iter, self.fileName), self.opt.xc)
class SaveOutputEveryIteration(_SaveEveryIteration):
class SaveOutputEveryIteration(SaveEveryIteration):
"""SaveModelEveryIteration"""
def initialize(self):
@@ -211,7 +211,7 @@ class SaveOutputEveryIteration(_SaveEveryIteration):
f.write(' %3d %1.4e %1.4e %1.4e %1.4e\n'%(self.opt.iter, self.invProb.beta, self.invProb.phi_d, self.invProb.phi_m, self.opt.f))
f.close()
class SaveOutputDictEveryIteration(_SaveEveryIteration):
class SaveOutputDictEveryIteration(SaveEveryIteration):
"""SaveOutputDictEveryIteration"""
def initialize(self):
SimPEG/EM/Base.py
+4 -3
View File
@@ -20,10 +20,10 @@ class BaseEMProblem(Problem.BaseProblem):
Problem.BaseProblem.__init__(self, mesh, **kwargs)
surveyPair = Survey.BaseSurvey
dataPair = Survey.Data
surveyPair = Survey.BaseSurvey #: The survey to pair with.
dataPair = Survey.Data #: The data to pair with.
PropMap = EMPropMap
PropMap = EMPropMap #: The property mapping
Solver = SimpegSolver
solverOpts = {}
@@ -217,6 +217,7 @@ class BaseEMSurvey(Survey.BaseSurvey):
def eval(self, f):
"""
Project fields to receiver locations
:param Fields u: fields object
:rtype: numpy.ndarray
:return: data
SimPEG/EM/FDEM/FieldsFDEM.py
+14 -26
View File
@@ -6,11 +6,11 @@ from SimPEG.EM.Utils import omega
from SimPEG.Utils import Zero, Identity, sdiag
class Fields(SimPEG.Problem.Fields):
class FieldsFDEM(SimPEG.Problem.Fields):
"""
Fancy Field Storage for a FDEM survey. Only one field type is stored for
each problem, the rest are computed. The fields obejct acts like an array and is indexed by
each problem, the rest are computed. The fields object acts like an array and is indexed by
.. code-block:: python
@@ -92,7 +92,7 @@ class Fields(SimPEG.Problem.Fields):
"""
Total derivative of e with respect to the inversion model. Returns :math:`d\mathbf{e}/d\mathbf{m}` for forward and (:math:`d\mathbf{e}/d\mathbf{u}`, :math:`d\mathb{u}/d\mathbf{m}`) for the adjoint
:param Src src: sorce
:param SimPEG.EM.FDEM.SrcFDEM.BaseSrc src: source
:param numpy.ndarray du_dm_v: derivative of the solution vector with respect to the model times a vector (is None for adjoint)
:param numpy.ndarray v: vector to take sensitivity product with
:param bool adjoint: adjoint?
@@ -110,7 +110,7 @@ class Fields(SimPEG.Problem.Fields):
"""
Total derivative of b with respect to the inversion model. Returns :math:`d\mathbf{b}/d\mathbf{m}` for forward and (:math:`d\mathbf{b}/d\mathbf{u}`, :math:`d\mathb{u}/d\mathbf{m}`) for the adjoint
:param Src src: sorce
:param SimPEG.EM.FDEM.SrcFDEM.BaseSrc src: source
:param numpy.ndarray du_dm_v: derivative of the solution vector with respect to the model times a vector (is None for adjoint)
:param numpy.ndarray v: vector to take sensitivity product with
:param bool adjoint: adjoint?
@@ -128,7 +128,7 @@ class Fields(SimPEG.Problem.Fields):
"""
Total derivative of h with respect to the inversion model. Returns :math:`d\mathbf{h}/d\mathbf{m}` for forward and (:math:`d\mathbf{h}/d\mathbf{u}`, :math:`d\mathb{u}/d\mathbf{m}`) for the adjoint
:param Src src: sorce
:param SimPEG.EM.FDEM.SrcFDEM.BaseSrc src: source
:param numpy.ndarray du_dm_v: derivative of the solution vector with respect to the model times a vector (is None for adjoint)
:param numpy.ndarray v: vector to take sensitivity product with
:param bool adjoint: adjoint?
@@ -146,7 +146,7 @@ class Fields(SimPEG.Problem.Fields):
"""
Total derivative of j with respect to the inversion model. Returns :math:`d\mathbf{j}/d\mathbf{m}` for forward and (:math:`d\mathbf{j}/d\mathbf{u}`, :math:`d\mathb{u}/d\mathbf{m}`) for the adjoint
:param Src src: sorce
:param SimPEG.EM.FDEM.SrcFDEM.BaseSrc src: source
:param numpy.ndarray du_dm_v: derivative of the solution vector with respect to the model times a vector (is None for adjoint)
:param numpy.ndarray v: vector to take sensitivity product with
:param bool adjoint: adjoint?
@@ -160,11 +160,11 @@ class Fields(SimPEG.Problem.Fields):
return self._jDeriv_u(src, v, adjoint), self._jDeriv_m(src, v, adjoint)
return np.array(self._jDeriv_u(src, du_dm_v, adjoint) + self._jDeriv_m(src, v, adjoint), dtype = complex)
class Fields3D_e(Fields):
class Fields3D_e(FieldsFDEM):
"""
Fields object for Problem3D_e.
:param Mesh mesh: mesh
:param BaseMesh mesh: mesh
:param SimPEG.EM.FDEM.SurveyFDEM.Survey survey: survey
"""
@@ -180,9 +180,6 @@ class Fields3D_e(Fields):
'h' : ['eSolution','CCV','_h'],
}
def __init__(self, mesh, survey, **kwargs):
Fields.__init__(self, mesh, survey, **kwargs)
def startup(self):
self.prob = self.survey.prob
self._edgeCurl = self.survey.prob.mesh.edgeCurl
@@ -426,11 +423,11 @@ class Fields3D_e(Fields):
class Fields3D_b(Fields):
class Fields3D_b(FieldsFDEM):
"""
Fields object for Problem3D_b.
:param Mesh mesh: mesh
:param BaseMesh mesh: mesh
:param SimPEG.EM.FDEM.SurveyFDEM.Survey survey: survey
"""
@@ -446,9 +443,6 @@ class Fields3D_b(Fields):
'h' : ['bSolution','CCV','_h'],
}
def __init__(self, mesh, survey, **kwargs):
Fields.__init__(self, mesh, survey, **kwargs)
def startup(self):
self.prob = self.survey.prob
self._edgeCurl = self.survey.prob.mesh.edgeCurl
@@ -693,11 +687,11 @@ class Fields3D_b(Fields):
return Zero()
class Fields3D_j(Fields):
class Fields3D_j(FieldsFDEM):
"""
Fields object for Problem3D_j.
:param Mesh mesh: mesh
:param BaseMesh mesh: mesh
:param SimPEG.EM.FDEM.SurveyFDEM.Survey survey: survey
"""
@@ -713,9 +707,6 @@ class Fields3D_j(Fields):
'b' : ['jSolution','CCV','_b'],
}
def __init__(self, mesh, survey, **kwargs):
Fields.__init__(self, mesh, survey, **kwargs)
def startup(self):
self.prob = self.survey.prob
self._edgeCurl = self.survey.prob.mesh.edgeCurl
@@ -988,11 +979,11 @@ class Fields3D_j(Fields):
return 1./(1j * omega(src.freq)) * VI * (self._aveE2CCV * ( s_mDeriv(v) - self._edgeCurl.T * ( self._MfRhoDeriv(jSolution) * v ) ) )
class Fields3D_h(Fields):
class Fields3D_h(FieldsFDEM):
"""
Fields object for Problem3D_h.
:param Mesh mesh: mesh
:param BaseMesh mesh: mesh
:param SimPEG.EM.FDEM.SurveyFDEM.Survey survey: survey
"""
@@ -1008,9 +999,6 @@ class Fields3D_h(Fields):
'b' : ['hSolution','CCV','_b'],
}
def __init__(self, mesh, survey, **kwargs):
Fields.__init__(self, mesh, survey, **kwargs)
def startup(self):
self.prob = self.survey.prob
self._edgeCurl = self.survey.prob.mesh.edgeCurl
SimPEG/EM/FDEM/ProblemFDEM.py
+16 -16
View File
@@ -1,7 +1,7 @@
from SimPEG import Problem, Utils, np, sp, Solver as SimpegSolver
from scipy.constants import mu_0
from SurveyFDEM import Survey as SurveyFDEM
from FieldsFDEM import Fields, Fields3D_e, Fields3D_b, Fields3D_h, Fields3D_j
from FieldsFDEM import FieldsFDEM, Fields3D_e, Fields3D_b, Fields3D_h, Fields3D_j
from SimPEG.EM.Base import BaseEMProblem
from SimPEG.EM.Utils import omega
@@ -35,7 +35,7 @@ class BaseFDEMProblem(BaseEMProblem):
"""
surveyPair = SurveyFDEM
fieldsPair = Fields
fieldsPair = FieldsFDEM
def fields(self, m):
"""
@@ -65,7 +65,7 @@ class BaseFDEMProblem(BaseEMProblem):
:param numpy.array m: inversion model (nP,)
:param numpy.array v: vector which we take sensitivity product with (nP,)
:param SimPEG.EM.FDEM.Fields u: fields object
:param SimPEG.EM.FDEM.FieldsFDEM.FieldsFDEM u: fields object
:rtype numpy.array:
:return: Jv (ndata,)
"""
@@ -100,7 +100,7 @@ class BaseFDEMProblem(BaseEMProblem):
:param numpy.array m: inversion model (nP,)
:param numpy.array v: vector which we take adjoint product with (nP,)
:param SimPEG.EM.FDEM.Fields u: fields object
:param SimPEG.EM.FDEM.FieldsFDEM.FieldsFDEM u: fields object
:rtype numpy.array:
:return: Jv (ndata,)
"""
@@ -154,8 +154,8 @@ class BaseFDEMProblem(BaseEMProblem):
Evaluates the sources for a given frequency and puts them in matrix form
:param float freq: Frequency
:rtype: (numpy.ndarray, numpy.ndarray)
:return: s_m, s_e (nE or nF, nSrc)
:rtype: tuple
:return: (s_m, s_e) (nE or nF, nSrc)
"""
Srcs = self.survey.getSrcByFreq(freq)
if self._formulation is 'EB':
@@ -195,7 +195,7 @@ class Problem3D_e(BaseFDEMProblem):
which we solve for :math:`\mathbf{e}`.
:param SimPEG.Mesh mesh: mesh
:param SimPEG.Mesh.BaseMesh.BaseMesh mesh: mesh
"""
_solutionType = 'eSolution'
@@ -270,7 +270,7 @@ class Problem3D_e(BaseFDEMProblem):
Derivative of the right hand side with respect to the model
:param float freq: frequency
:param SimPEG.EM.FDEM.Src src: FDEM source
:param SimPEG.EM.FDEM.SrcFDEM.BaseSrc src: FDEM source
:param numpy.ndarray v: vector to take product with
:param bool adjoint: adjoint?
:rtype: numpy.ndarray
@@ -306,7 +306,7 @@ class Problem3D_b(BaseFDEMProblem):
.. note ::
The inverse problem will not work with full anisotropy
:param SimPEG.Mesh mesh: mesh
:param SimPEG.Mesh.BaseMesh.BaseMesh mesh: mesh
"""
_solutionType = 'bSolution'
@@ -401,7 +401,7 @@ class Problem3D_b(BaseFDEMProblem):
Derivative of the right hand side with respect to the model
:param float freq: frequency
:param SimPEG.EM.FDEM.Src src: FDEM source
:param SimPEG.EM.FDEM.SrcFDEM.BaseSrc src: FDEM source
:param numpy.ndarray v: vector to take product with
:param bool adjoint: adjoint?
:rtype: numpy.ndarray
@@ -455,7 +455,7 @@ class Problem3D_j(BaseFDEMProblem):
.. note::
This implementation does not yet work with full anisotropy!!
:param SimPEG.Mesh mesh: mesh
:param SimPEG.Mesh.BaseMesh.BaseMesh mesh: mesh
"""
_solutionType = 'jSolution'
@@ -531,8 +531,8 @@ class Problem3D_j(BaseFDEMProblem):
\mathbf{RHS} = \mathbf{C} \mathbf{M_{\mu}^e}^{-1}\mathbf{s_m} -i\omega \mathbf{s_e}
:param float freq: Frequency
:rtype: numpy.ndarray (nE, nSrc)
:return: RHS
:rtype: numpy.ndarray
:return: RHS (nE, nSrc)
"""
s_m, s_e = self.getSourceTerm(freq)
@@ -551,7 +551,7 @@ class Problem3D_j(BaseFDEMProblem):
Derivative of the right hand side with respect to the model
:param float freq: frequency
:param SimPEG.EM.FDEM.Src src: FDEM source
:param SimPEG.EM.FDEM.SrcFDEM.BaseSrc src: FDEM source
:param numpy.ndarray v: vector to take product with
:param bool adjoint: adjoint?
:rtype: numpy.ndarray
@@ -593,7 +593,7 @@ class Problem3D_h(BaseFDEMProblem):
\\left(\mathbf{C}^{\\top} \mathbf{M_{\\rho}^f} \mathbf{C} + i \omega \mathbf{M_{\mu}^e}\\right) \mathbf{h} = \mathbf{M^e} \mathbf{s_m} + \mathbf{C}^{\\top} \mathbf{M_{\\rho}^f} \mathbf{s_e}
:param SimPEG.Mesh mesh: mesh
:param SimPEG.Mesh.BaseMesh.BaseMesh mesh: mesh
"""
_solutionType = 'hSolution'
@@ -671,7 +671,7 @@ class Problem3D_h(BaseFDEMProblem):
Derivative of the right hand side with respect to the model
:param float freq: frequency
:param SimPEG.EM.FDEM.Src src: FDEM source
:param SimPEG.EM.FDEM.SrcFDEM.BaseSrc src: FDEM source
:param numpy.ndarray v: vector to take product with
:param bool adjoint: adjoint?
:rtype: numpy.ndarray
SimPEG/EM/FDEM/RxFDEM.py
+5 -5
View File
@@ -25,10 +25,10 @@ class BaseRx(SimPEG.Survey.BaseRx):
def eval(self, src, mesh, f):
"""
Project fields to recievers to get data.
Project fields to receivers to get data.
:param Source src: FDEM source
:param Mesh mesh: mesh used
:param SimPEG.EM.FDEM.SrcFDEM.BaseSrc src: FDEM source
:param BaseMesh mesh: mesh used
:param Fields f: fields object
:rtype: numpy.ndarray
:return: fields projected to recievers
@@ -44,8 +44,8 @@ class BaseRx(SimPEG.Survey.BaseRx):
"""
Derivative of projected fields with respect to the inversion model times a vector.
:param Source src: FDEM source
:param Mesh mesh: mesh used
:param SimPEG.EM.FDEM.SrcFDEM.BaseSrc src: FDEM source
:param BaseMesh mesh: mesh used
:param Fields f: fields object
:param numpy.ndarray v: vector to multiply
:rtype: numpy.ndarray
SimPEG/EM/FDEM/SrcFDEM.py
+28 -28
View File
@@ -23,8 +23,8 @@ class BaseSrc(Survey.BaseSrc):
- :math:`s_m` : magnetic source term
- :math:`s_e` : electric source term
:param Problem prob: FDEM Problem
:rtype: (numpy.ndarray, numpy.ndarray)
:param BaseFDEMProblem prob: FDEM Problem
:rtype: tuple
:return: tuple with magnetic source term and electric source term
"""
s_m = self.s_m(prob)
@@ -37,10 +37,10 @@ class BaseSrc(Survey.BaseSrc):
- :code:`s_mDeriv` : derivative of the magnetic source term
- :code:`s_eDeriv` : derivative of the electric source term
:param Problem prob: FDEM Problem
:param BaseFDEMProblem prob: FDEM Problem
:param numpy.ndarray v: vector to take product with
:param bool adjoint: adjoint?
:rtype: (numpy.ndarray, numpy.ndarray)
:rtype: tuple
:return: tuple with magnetic source term and electric source term derivatives times a vector
"""
if v is not None:
@@ -52,7 +52,7 @@ class BaseSrc(Survey.BaseSrc):
"""
Primary magnetic flux density
:param Problem prob: FDEM Problem
:param BaseFDEMProblem prob: FDEM Problem
:rtype: numpy.ndarray
:return: primary magnetic flux density
"""
@@ -64,7 +64,7 @@ class BaseSrc(Survey.BaseSrc):
"""
Primary magnetic field
:param Problem prob: FDEM Problem
:param BaseFDEMProblem prob: FDEM Problem
:rtype: numpy.ndarray
:return: primary magnetic field
"""
@@ -76,7 +76,7 @@ class BaseSrc(Survey.BaseSrc):
"""
Primary electric field
:param Problem prob: FDEM Problem
:param BaseFDEMProblem prob: FDEM Problem
:rtype: numpy.ndarray
:return: primary electric field
"""
@@ -88,7 +88,7 @@ class BaseSrc(Survey.BaseSrc):
"""
Primary current density
:param Problem prob: FDEM Problem
:param BaseFDEMProblem prob: FDEM Problem
:rtype: numpy.ndarray
:return: primary current density
"""
@@ -100,7 +100,7 @@ class BaseSrc(Survey.BaseSrc):
"""
Magnetic source term
:param Problem prob: FDEM Problem
:param BaseFDEMProblem prob: FDEM Problem
:rtype: numpy.ndarray
:return: magnetic source term on mesh
"""
@@ -110,7 +110,7 @@ class BaseSrc(Survey.BaseSrc):
"""
Electric source term
:param Problem prob: FDEM Problem
:param BaseFDEMProblem prob: FDEM Problem
:rtype: numpy.ndarray
:return: electric source term on mesh
"""
@@ -120,7 +120,7 @@ class BaseSrc(Survey.BaseSrc):
"""
Derivative of magnetic source term with respect to the inversion model
:param Problem prob: FDEM Problem
:param BaseFDEMProblem prob: FDEM Problem
:param numpy.ndarray v: vector to take product with
:param bool adjoint: adjoint?
:rtype: numpy.ndarray
@@ -133,7 +133,7 @@ class BaseSrc(Survey.BaseSrc):
"""
Derivative of electric source term with respect to the inversion model
:param Problem prob: FDEM Problem
:param BaseFDEMProblem prob: FDEM Problem
:param numpy.ndarray v: vector to take product with
:param bool adjoint: adjoint?
:rtype: numpy.ndarray
@@ -162,7 +162,7 @@ class RawVec_e(BaseSrc):
"""
Electric source term
:param Problem prob: FDEM Problem
:param BaseFDEMProblem prob: FDEM Problem
:rtype: numpy.ndarray
:return: electric source term on mesh
"""
@@ -191,7 +191,7 @@ class RawVec_m(BaseSrc):
"""
Magnetic source term
:param Problem prob: FDEM Problem
:param BaseFDEMProblem prob: FDEM Problem
:rtype: numpy.ndarray
:return: magnetic source term on mesh
"""
@@ -220,7 +220,7 @@ class RawVec(BaseSrc):
"""
Magnetic source term
:param Problem prob: FDEM Problem
:param BaseFDEMProblem prob: FDEM Problem
:rtype: numpy.ndarray
:return: magnetic source term on mesh
"""
@@ -232,7 +232,7 @@ class RawVec(BaseSrc):
"""
Electric source term
:param Problem prob: FDEM Problem
:param BaseFDEMProblem prob: FDEM Problem
:rtype: numpy.ndarray
:return: electric source term on mesh
"""
@@ -301,7 +301,7 @@ class MagDipole(BaseSrc):
"""
The primary magnetic flux density from a magnetic vector potential
:param Problem prob: FDEM problem
:param BaseFDEMProblem prob: FDEM problem
:rtype: numpy.ndarray
:return: primary magnetic field
"""
@@ -339,7 +339,7 @@ class MagDipole(BaseSrc):
"""
The primary magnetic field from a magnetic vector potential
:param Problem prob: FDEM problem
:param BaseFDEMProblem prob: FDEM problem
:rtype: numpy.ndarray
:return: primary magnetic field
"""
@@ -350,7 +350,7 @@ class MagDipole(BaseSrc):
"""
The magnetic source term
:param Problem prob: FDEM problem
:param BaseFDEMProblem prob: FDEM problem
:rtype: numpy.ndarray
:return: primary magnetic field
"""
@@ -364,7 +364,7 @@ class MagDipole(BaseSrc):
"""
The electric source term
:param Problem prob: FDEM problem
:param BaseFDEMProblem prob: FDEM problem
:rtype: numpy.ndarray
:return: primary magnetic field
"""
@@ -416,7 +416,7 @@ class MagDipole_Bfield(BaseSrc):
"""
The primary magnetic flux density from the analytic solution for magnetic fields from a dipole
:param Problem prob: FDEM problem
:param BaseFDEMProblem prob: FDEM problem
:rtype: numpy.ndarray
:return: primary magnetic field
"""
@@ -455,7 +455,7 @@ class MagDipole_Bfield(BaseSrc):
"""
The primary magnetic field from a magnetic vector potential
:param Problem prob: FDEM problem
:param BaseFDEMProblem prob: FDEM problem
:rtype: numpy.ndarray
:return: primary magnetic field
"""
@@ -466,7 +466,7 @@ class MagDipole_Bfield(BaseSrc):
"""
The magnetic source term
:param Problem prob: FDEM problem
:param BaseFDEMProblem prob: FDEM problem
:rtype: numpy.ndarray
:return: primary magnetic field
"""
@@ -479,7 +479,7 @@ class MagDipole_Bfield(BaseSrc):
"""
The electric source term
:param Problem prob: FDEM problem
:param BaseFDEMProblem prob: FDEM problem
:rtype: numpy.ndarray
:return: primary magnetic field
"""
@@ -530,7 +530,7 @@ class CircularLoop(BaseSrc):
"""
The primary magnetic flux density from a magnetic vector potential
:param Problem prob: FDEM problem
:param BaseFDEMProblem prob: FDEM problem
:rtype: numpy.ndarray
:return: primary magnetic field
"""
@@ -567,7 +567,7 @@ class CircularLoop(BaseSrc):
"""
The primary magnetic field from a magnetic vector potential
:param Problem prob: FDEM problem
:param BaseFDEMProblem prob: FDEM problem
:rtype: numpy.ndarray
:return: primary magnetic field
"""
@@ -578,7 +578,7 @@ class CircularLoop(BaseSrc):
"""
The magnetic source term
:param Problem prob: FDEM problem
:param BaseFDEMProblem prob: FDEM problem
:rtype: numpy.ndarray
:return: primary magnetic field
"""
@@ -591,7 +591,7 @@ class CircularLoop(BaseSrc):
"""
The electric source term
:param Problem prob: FDEM problem
:param BaseFDEMProblem prob: FDEM problem
:rtype: numpy.ndarray
:return: primary magnetic field
"""
SimPEG/EM/TDEM/BaseTDEM.py
+3 -3
View File
@@ -112,7 +112,7 @@ class BaseTDEMProblem(BaseTimeProblem, BaseEMProblem):
"""
:param numpy.array m: Conductivity model
:param numpy.ndarray v: vector (model object)
:param simpegEM.TDEM.FieldsTDEM f: Fields resulting from m
:param FieldsTDEM f: Fields resulting from m
:rtype: numpy.ndarray
:return: w (data object)
@@ -136,8 +136,8 @@ class BaseTDEMProblem(BaseTimeProblem, BaseEMProblem):
def Jtvec(self, m, v, f=None):
"""
:param numpy.array m: Conductivity model
:param numpy.ndarray,SimPEG.Survey.Data v: vector (data object)
:param simpegEM.TDEM.FieldsTDEM u: Fields resulting from m
:param numpy.ndarray v: vector (or a :class:`SimPEG.Survey.Data` object)
:param FieldsTDEM u: Fields resulting from m
:rtype: numpy.ndarray
:return: w (model object)
SimPEG/EM/TDEM/TDEM_b.py
+13 -13
View File
@@ -87,8 +87,8 @@ class ProblemTDEM_b(BaseTDEMProblem):
"""
:param numpy.array m: Conductivity model
:param numpy.array vec: vector (like a model)
:param simpegEM.TDEM.FieldsTDEM u: Fields resulting from m
:rtype: simpegEM.TDEM.FieldsTDEM
:param FieldsTDEM u: Fields resulting from m
:rtype: FieldsTDEM
:return: f
Multiply G by a vector
@@ -125,9 +125,9 @@ class ProblemTDEM_b(BaseTDEMProblem):
"""
:param numpy.array m: Conductivity model
:param numpy.array vec: vector (like a fields)
:param simpegEM.TDEM.FieldsTDEM u: Fields resulting from m
:rtype: np.ndarray (like a model)
:return: p
:param FieldsTDEM u: Fields resulting from m
:rtype: numpy.ndarray
:return: p (like a model)
Multiply G.T by a vector
"""
@@ -153,8 +153,8 @@ class ProblemTDEM_b(BaseTDEMProblem):
def solveAh(self, m, p):
"""
:param numpy.array m: Conductivity model
:param simpegEM.TDEM.FieldsTDEM p: Fields object
:rtype: simpegEM.TDEM.FieldsTDEM
:param FieldsTDEM p: Fields object
:rtype: FieldsTDEM
:return: y
Solve the block-matrix system \\\(\\\hat{A} \\\hat{y} = \\\hat{p}\\\):
@@ -200,8 +200,8 @@ class ProblemTDEM_b(BaseTDEMProblem):
def solveAht(self, m, p):
"""
:param numpy.array m: Conductivity model
:param simpegEM.TDEM.FieldsTDEM p: Fields object
:rtype: simpegEM.TDEM.FieldsTDEM
:param FieldsTDEM p: Fields object
:rtype: FieldsTDEM
:return: y
Solve the block-matrix system \\\(\\\hat{A}^\\\\top \\\hat{y} = \\\hat{p}\\\):
@@ -270,8 +270,8 @@ class ProblemTDEM_b(BaseTDEMProblem):
def _AhVec(self, m, vec):
"""
:param numpy.array m: Conductivity model
:param simpegEM.TDEM.FieldsTDEM vec: Fields object
:rtype: simpegEM.TDEM.FieldsTDEM
:param FieldsTDEM vec: Fields object
:rtype: FieldsTDEM
:return: f
Multiply the matrix \\\(\\\hat{A}\\\) by a fields vector where
@@ -315,8 +315,8 @@ class ProblemTDEM_b(BaseTDEMProblem):
def _AhtVec(self, m, vec):
"""
:param numpy.array m: Conductivity model
:param simpegEM.TDEM.FieldsTDEM vec: Fields object
:rtype: simpegEM.TDEM.FieldsTDEM
:param FieldsTDEM vec: Fields object
:rtype: FieldsTDEM
:return: f
Multiply the matrix \\\(\\\hat{A}\\\) by a fields vector where
SimPEG/Examples/EM_Schenkel_Morrison_Casing.py
+4 -1
View File
@@ -19,10 +19,13 @@ def run(plotIt=True):
Morrison Casing Model, and the results are used in a 2016 SEG abstract by
Yang et al.
- Schenkel, C.J., and H.F. Morrison, 1990, Effects of well casing on potential field measurements using downhole current sources: Geophysical prospecting, 38, 663-686.
.. code-block:: text
Schenkel, C.J., and H.F. Morrison, 1990, Effects of well casing on potential field measurements using downhole current sources: Geophysical prospecting, 38, 663-686.
The model consists of:
- Air: Conductivity 1e-8 S/m, above z = 0
- Background: conductivity 1e-2 S/m, below z = 0
- Casing: conductivity 1e6 S/m
SimPEG/FLOW/Richards/Empirical.py
+2 -2
View File
@@ -31,7 +31,7 @@ class NonLinearMap(object):
"""
:param numpy.array u: fields
:param numpy.array m: model
:rtype: scipy.csr_matrix
:rtype: scipy.sparse.csr_matrix
:return: derivative of transformed model
The *transform* changes the model into the physical property.
@@ -44,7 +44,7 @@ class NonLinearMap(object):
"""
:param numpy.array u: fields
:param numpy.array m: model
:rtype: scipy.csr_matrix
:rtype: scipy.sparse.csr_matrix
:return: derivative of transformed model
The *transform* changes the model into the physical property.
SimPEG/Mesh/BaseMesh.py
+12 -12
View File
@@ -34,7 +34,7 @@ class BaseMesh(object):
"""
Origin of the mesh
:rtype: numpy.array
:rtype: numpy.array
:return: x0, (dim, )
"""
return self._x0
@@ -116,7 +116,7 @@ class BaseMesh(object):
"""
Total number of edges in each direction
:rtype: numpy.array
:rtype: numpy.array
:return: [nEx, nEy, nEz], (dim, )
.. plot::
@@ -200,7 +200,7 @@ class BaseMesh(object):
"""
Face Normals
:rtype: numpy.array
:rtype: numpy.array
:return: normals, (sum(nF), dim)
"""
if self.dim == 2:
@@ -218,7 +218,7 @@ class BaseMesh(object):
"""
Edge Tangents
:rtype: numpy.array
:rtype: numpy.array
:return: normals, (sum(nE), dim)
"""
if self.dim == 2:
@@ -297,7 +297,7 @@ class BaseRectangularMesh(BaseMesh):
"""
Total number of cells in each direction
:rtype: numpy.array (dim, )
:rtype: numpy.array
:return: [nCx, nCy, nCz]
"""
return np.array([x for x in [self.nCx, self.nCy, self.nCz] if not x is None])
@@ -337,7 +337,7 @@ class BaseRectangularMesh(BaseMesh):
"""
Total number of nodes in each direction
:rtype: numpy.array (dim, )
:rtype: numpy.array
:return: [nNx, nNy, nNz]
"""
return np.array([x for x in [self.nNx, self.nNy, self.nNz] if not x is None])
@@ -347,7 +347,7 @@ class BaseRectangularMesh(BaseMesh):
"""
Number of x-edges in each direction
:rtype: numpy.array (dim, )
:rtype: numpy.array
:return: vnEx
"""
return np.array([x for x in [self.nCx, self.nNy, self.nNz] if not x is None])
@@ -357,7 +357,7 @@ class BaseRectangularMesh(BaseMesh):
"""
Number of y-edges in each direction
:rtype: numpy.array (dim, )
:rtype: numpy.array
:return: vnEy or None if dim < 2
"""
return None if self.dim < 2 else np.array([x for x in [self.nNx, self.nCy, self.nNz] if not x is None])
@@ -367,7 +367,7 @@ class BaseRectangularMesh(BaseMesh):
"""
Number of z-edges in each direction
:rtype: numpy.array (dim, )
:rtype: numpy.array
:return: vnEz or None if dim < 3
"""
return None if self.dim < 3 else np.array([x for x in [self.nNx, self.nNy, self.nCz] if not x is None])
@@ -377,7 +377,7 @@ class BaseRectangularMesh(BaseMesh):
"""
Number of x-faces in each direction
:rtype: numpy.array (dim, )
:rtype: numpy.array
:return: vnFx
"""
return np.array([x for x in [self.nNx, self.nCy, self.nCz] if not x is None])
@@ -387,7 +387,7 @@ class BaseRectangularMesh(BaseMesh):
"""
Number of y-faces in each direction
:rtype: numpy.array (dim, )
:rtype: numpy.array
:return: vnFy or None if dim < 2
"""
return None if self.dim < 2 else np.array([x for x in [self.nCx, self.nNy, self.nCz] if not x is None])
@@ -397,7 +397,7 @@ class BaseRectangularMesh(BaseMesh):
"""
Number of z-faces in each direction
:rtype: numpy.array (dim, )
:rtype: numpy.array
:return: vnFz or None if dim < 3
"""
return None if self.dim < 3 else np.array([x for x in [self.nCx, self.nCy, self.nNz] if not x is None])
SimPEG/Mesh/InnerProducts.py
+1 -2
View File
@@ -115,12 +115,11 @@ class InnerProducts(object):
:param bool doFast: do a faster implementation if available.
:param bool invProp: inverts the material property
:param bool invMat: inverts the matrix
:rtype: function
:return: dMdmu(u), the derivative of the inner product matrix (u)
Given u, dMdmu returns (nF, nC*nA)
:param np.ndarray u: vector that multiplies dMdmu
:param numpy.ndarray u: vector that multiplies dMdmu
:rtype: scipy.sparse.csr_matrix
:return: dMdmu, the derivative of the inner product matrix for a certain u
"""
SimPEG/Mesh/MeshIO.py
+22 -35
View File
@@ -6,13 +6,11 @@ class TensorMeshIO(object):
@classmethod
def readUBC(TensorMesh, fileName):
"""
Read UBC GIF 3DTensor mesh and generate 3D Tensor mesh in simpegTD
Read UBC GIF 3D tensor mesh and generate 3D TensorMesh in SimPEG.
Input:
:param fileName, path to the UBC GIF mesh file
Output:
:param SimPEG TensorMesh object
:param string fileName: path to the UBC GIF mesh file
:rtype: TensorMesh
:return: The tensor mesh for the fileName.
"""
# Interal function to read cell size lines for the UBC mesh files.
@@ -48,11 +46,9 @@ class TensorMeshIO(object):
Read VTK Rectilinear (vtr xml file) and return SimPEG Tensor mesh and model
Input:
:param vtrFileName, path to the vtr model file to write to
Output:
:return SimPEG TensorMesh object
:return SimPEG model dictionary
:param string fileName: path to the vtr model file to read
:rtype: tuple
:return: (TensorMesh, modelDictionary)
"""
# Import
@@ -102,9 +98,8 @@ class TensorMeshIO(object):
Makes and saves a VTK rectilinear file (vtr) for a simpeg Tensor mesh and model.
Input:
:param str, path to the output vtk file
:param mesh, SimPEG TensorMesh object - mesh to be transfer to VTK
:param models, dictionary of numpy.array - Name('s) and array('s). Match number of cells
:param string fileName: path to the output vtk file
:param dict models: dictionary of numpy.array - Name('s) and array('s). Match number of cells
"""
# Import
@@ -162,12 +157,9 @@ class TensorMeshIO(object):
"""
Read UBC 3DTensor mesh model and generate 3D Tensor mesh model in simpeg
Input:
:param fileName, path to the UBC GIF mesh file to read
:param mesh, TensorMesh object, mesh that coresponds to the model
Output:
:return numpy array, model with TensorMesh ordered
:param string fileName: path to the UBC GIF mesh file to read
:rtype: numpy.ndarray
:return: model with TensorMesh ordered
"""
f = open(fileName, 'r')
model = np.array(map(float, f.readlines()))
@@ -183,8 +175,7 @@ class TensorMeshIO(object):
Writes a model associated with a SimPEG TensorMesh
to a UBC-GIF format model file.
:param str fileName: File to write to
:param simpeg.Mesh.TensorMesh mesh: The mesh
:param string fileName: File to write to
:param numpy.ndarray model: The model
"""
@@ -201,8 +192,8 @@ class TensorMeshIO(object):
"""
Writes a SimPEG TensorMesh to a UBC-GIF format mesh file.
:param str fileName: File to write to
:param simpeg.Mesh.TensorMesh mesh: The mesh
:param string fileName: File to write to
:param dict models: A dictionary of the models
"""
assert mesh.dim == 3
@@ -231,9 +222,8 @@ class TreeMeshIO(object):
"""
Write UBC ocTree mesh and model files from a simpeg ocTree mesh and model.
:param str fileName: File to write to
:param simpeg.Mesh.TreeMesh mesh: The mesh
:param dictionary models: The models in a dictionary, where the keys is the name of the of the model file
:param string fileName: File to write to
:param dict models: The models in a dictionary, where the keys is the name of the of the model file
"""
# Calculate information to write in the file.
@@ -286,10 +276,9 @@ class TreeMeshIO(object):
Input:
:param str meshFile: path to the UBC GIF OcTree mesh file to read
:rtype: SimPEG.Mesh.TreeMesh
:return: The octree mesh
Output:
:return SimPEG.Mesh.TreeMesh mesh: The octree mesh
:return list of ndarray's: models as a list of numpy array's
"""
## Read the file lines
@@ -335,11 +324,9 @@ class TreeMeshIO(object):
"""
Read UBC OcTree model and get vector
Input:
:param fileName, path to the UBC GIF model file to read
Output:
:return numpy array, OcTree model
:param string fileName: path to the UBC GIF model file to read
:rtype: numpy.ndarray
:return: OcTree model
"""
if type(fileName) is list:
SimPEG/Mesh/TensorMesh.py
+4 -4
View File
@@ -198,8 +198,8 @@ class BaseTensorMesh(BaseMesh):
Determines if a set of points are inside a mesh.
:param numpy.ndarray pts: Location of points to test
:rtype numpy.ndarray
:return inside, numpy array of booleans
:rtype numpy.ndarray:
:return: inside, numpy array of booleans
"""
pts = Utils.asArray_N_x_Dim(pts, self.dim)
@@ -221,7 +221,7 @@ class BaseTensorMesh(BaseMesh):
:param numpy.ndarray loc: Location of points to interpolate to
:param str locType: What to interpolate (see below)
:rtype: scipy.sparse.csr.csr_matrix
:rtype: scipy.sparse.csr_matrix
:return: M, the interpolation matrix
locType can be::
@@ -289,7 +289,7 @@ class BaseTensorMesh(BaseMesh):
:param bool returnP: returns the projection matrices
:param bool invProp: inverts the material property
:param bool invMat: inverts the matrix
:rtype: scipy.csr_matrix
:rtype: scipy.sparse.csr_matrix
:return: M, the inner product matrix (nF, nF)
"""
assert projType in ['F', 'E'], "projType must be 'F' for faces or 'E' for edges"
SimPEG/Mesh/View.py
+1 -1
View File
@@ -560,7 +560,7 @@ class CurvView(object):
:include-source:
from SimPEG import Mesh, Utils
X, Y = Utils.exampleCurvGird([3,3],'rotate')
X, Y = Utils.meshutils.exampleLrmGrid([3,3],'rotate')
M = Mesh.CurvilinearMesh([X, Y])
M.plotGrid(showIt=True)
SimPEG/Optimization.py
+5 -5
View File
@@ -131,7 +131,7 @@ class Minimize(object):
Minimizes the function (evalFunction) starting at the location x0.
:param def evalFunction: function handle that evaluates: f, g, H = F(x)
:param callable evalFunction: function handle that evaluates: f, g, H = F(x)
:param numpy.ndarray x0: starting location
:rtype: numpy.ndarray
:return: x, the last iterate of the optimization algorithm
@@ -372,8 +372,8 @@ class Minimize(object):
Else, a modifySearchDirectionBreak call is preformed.
:param numpy.ndarray p: searchDirection
:rtype: numpy.ndarray,bool
:return: (xt, passLS)
:rtype: tuple
:return: (xt, passLS) numpy.ndarray, bool
"""
# Projected Armijo linesearch
self._LS_t = 1
@@ -408,8 +408,8 @@ class Minimize(object):
evalFunction returns a False indicating the break was not caught.
:param numpy.ndarray p: searchDirection
:rtype: numpy.ndarray,bool
:return: (xt, breakCaught)
:rtype: tuple
:return: (xt, breakCaught) numpy.ndarray, bool
"""
self.printDone(inLS=True)
print 'The linesearch got broken. Boo.'
SimPEG/PropMaps.py
+1 -1
View File
@@ -187,7 +187,7 @@ class _PropMapMetaClass(type):
attrs[attr + 'Model'] = prop._getModelProperty()
attrs[attr + 'Deriv'] = prop._getModelDerivProperty()
return type(name.replace('PropMap', 'PropModel'), (PropModel, ), attrs)
return type('PropModel', (PropModel, ), attrs)
class PropMap(object):
SimPEG/Regularization.py
+6 -6
View File
@@ -8,7 +8,7 @@ class RegularizationMesh(object):
are not necessarily true differential operators, but are constructed from
a SimPEG Mesh.
:param Mesh mesh: problem mesh
:param BaseMesh mesh: problem mesh
:param numpy.array indActive: bool array, size nC, that is True where we have active cells. Used to reduce the operators so we regularize only on active cells
"""
@@ -381,8 +381,8 @@ class BaseRegularization(object):
:param numpy.array m: geophysical model
:param numpy.array v: vector to multiply
:rtype: scipy.sparse.csr_matrix or numpy.ndarray
:return: WtW or WtW*v
:rtype: scipy.sparse.csr_matrix
:return: WtW, or if v is supplied WtW*v (numpy.ndarray)
The regularization is:
@@ -417,8 +417,8 @@ class Tikhonov(BaseRegularization):
Note if the key word argument `mrefInSmooth` is False, then mref is not
included in the smoothness contribution.
:param Mesh mesh: SimPEG mesh
:param Maps mapping: regularization mapping, takes the model from model space to the thing you want to regularize
:param BaseMesh mesh: SimPEG mesh
:param IdentityMap mapping: regularization mapping, takes the model from model space to the thing you want to regularize
:param numpy.ndarray indActive: active cell indices for reducing the size of differential operators in the definition of a regularization mesh
:param bool mrefInSmooth: (default = False) put mref in the smoothness component?
:param float alpha_s: (default 1e-6) smallness weight
@@ -438,7 +438,7 @@ class Tikhonov(BaseRegularization):
alpha_yy = Utils.dependentProperty('_alpha_yy', 0.0, ['_W', '_Wyy'], "Weight for the second derivative in the y direction")
alpha_zz = Utils.dependentProperty('_alpha_zz', 0.0, ['_W', '_Wzz'], "Weight for the second derivative in the z direction")
def __init__(self, mesh, mapping=None, indActive = None, **kwargs):
def __init__(self, mesh, mapping=None, indActive=None, **kwargs):
BaseRegularization.__init__(self, mesh, mapping=mapping, indActive=indActive, **kwargs)
@property
SimPEG/Tests.py
+1 -1
View File
@@ -237,7 +237,7 @@ def checkDerivative(fctn, x0, num=7, plotIt=True, dx=None, expectedOrder=2, tole
Compares error decay of 0th and 1st order Taylor approximation at point
x0 for a randomized search direction.
:param lambda fctn: function handle
:param callable fctn: function handle
:param numpy.array x0: point at which to check derivative
:param int num: number of times to reduce step length, h
:param bool plotIt: if you would like to plot
SimPEG/Utils/ModelBuilder.py
+13 -13
View File
@@ -7,11 +7,11 @@ def addBlock(gridCC, modelCC, p0, p1, blockProp):
"""
Add a block to an exsisting cell centered model, modelCC
:param numpy.array, gridCC: mesh.gridCC is the cell centered grid
:param numpy.array, modelCC: cell centered model
:param numpy.array, p0: bottom, southwest corner of block
:param numpy.array, p1: top, northeast corner of block
:blockProp float, blockProp: property to assign to the model
:param numpy.array gridCC: mesh.gridCC is the cell centered grid
:param numpy.array modelCC: cell centered model
:param numpy.array p0: bottom, southwest corner of block
:param numpy.array p1: top, northeast corner of block
:blockProp float blockProp: property to assign to the model
:return numpy.array, modelBlock: model with block
"""
@@ -147,7 +147,7 @@ def getIndicesSphere(center,radius,ccMesh):
if dimMesh == 1:
# Define the reference points
ind = np.abs(center[0] - ccMesh[:,0]) < radius
elif dimMesh == 2:
@@ -222,14 +222,14 @@ def layeredModel(ccMesh, layerTops, layerValues):
:param numpy.array ccMesh: cell-centered mesh
:param numpy.array layerTops: z-locations of the tops of each layer
:param numpy.array layerValue: values of the property to assign for each layer (starting at the top)
:param numpy.array layerValue: values of the property to assign for each layer (starting at the top)
:rtype: numpy.array
:return: M, layered model on the mesh
:return: M, layered model on the mesh
"""
descending = np.linalg.norm(sorted(layerTops, reverse=True) - layerTops) < 1e-20
# TODO: put an error check to make sure that there is an ordering... needs to work with inf elts
# TODO: put an error check to make sure that there is an ordering... needs to work with inf elts
# assert ascending or descending, "Layers must be listed in either ascending or descending order"
# start from bottom up
@@ -253,10 +253,10 @@ def layeredModel(ccMesh, layerTops, layerValues):
model = np.zeros(ccMesh.shape[0])
for i, top in enumerate(layerTops):
zind = z <= top
zind = z <= top
model[zind] = layerValues[i]
return model
return model
@@ -265,9 +265,9 @@ def randomModel(shape, seed=None, anisotropy=None, its=100, bounds=None):
Create a random model by convolving a kernel with a
uniformly distributed model.
:param int,tuple shape: shape of the model.
:param tuple shape: shape of the model.
:param int seed: pick which model to produce, prints the seed if you don't choose.
:param numpy.ndarray,list anisotropy: this is the (3 x n) blurring kernel that is used.
:param numpy.ndarray anisotropy: this is the (3 x n) blurring kernel that is used.
:param int its: number of smoothing iterations
:param list bounds: bounds on the model, len(list) == 2
:rtype: numpy.ndarray
SimPEG/Utils/SolverUtils.py
+7 -7
View File
@@ -13,7 +13,7 @@ def _checkAccuracy(A, b, X, accuracyTol):
warnings.warn(msg, RuntimeWarning)
def SolverWrapD(fun, factorize=True, checkAccuracy=True, accuracyTol=1e-6):
def SolverWrapD(fun, factorize=True, checkAccuracy=True, accuracyTol=1e-6, name=None):
"""
Wraps a direct Solver.
@@ -72,11 +72,11 @@ def SolverWrapD(fun, factorize=True, checkAccuracy=True, accuracyTol=1e-6):
if factorize and hasattr(self.solver, 'clean'):
return self.solver.clean()
return type(fun.__name__+'_Wrapped', (object,), {"__init__": __init__, "clean": clean, "__mul__": __mul__})
return type(name if name is not None else fun.__name__, (object,), {"__init__": __init__, "clean": clean, "__mul__": __mul__})
def SolverWrapI(fun, checkAccuracy=True, accuracyTol=1e-5):
def SolverWrapI(fun, checkAccuracy=True, accuracyTol=1e-5, name=None):
"""
Wraps an iterative Solver.
@@ -128,13 +128,13 @@ def SolverWrapI(fun, checkAccuracy=True, accuracyTol=1e-5):
def clean(self):
pass
return type(fun.__name__+'_Wrapped', (object,), {"__init__": __init__, "clean": clean, "__mul__": __mul__})
return type(name if name is not None else fun.__name__, (object,), {"__init__": __init__, "clean": clean, "__mul__": __mul__})
from scipy.sparse import linalg
Solver = SolverWrapD(linalg.spsolve, factorize=False)
SolverLU = SolverWrapD(linalg.splu, factorize=True)
SolverCG = SolverWrapI(linalg.cg)
Solver = SolverWrapD(linalg.spsolve, factorize=False, name="Solver")
SolverLU = SolverWrapD(linalg.splu, factorize=True, name="SolverLU")
SolverCG = SolverWrapI(linalg.cg, name="SolverCG")
class SolverDiag(object):
SimPEG/Utils/interputils.py
+1 -1
View File
@@ -25,7 +25,7 @@ def interpmat(locs, x, y=None, z=None):
:param numpy.ndarray x: Tensor vector of 1st dimension of grid.
:param numpy.ndarray y: Tensor vector of 2nd dimension of grid. None by default.
:param numpy.ndarray z: Tensor vector of 3rd dimension of grid. None by default.
:rtype: scipy.sparse.csr.csr_matrix
:rtype: scipy.sparse.csr_matrix
:return: Interpolation matrix
.. plot::
SimPEG/Utils/matutils.py
+6 -6
View File
@@ -27,7 +27,7 @@ def mkvc(x, numDims=1):
if isinstance(x, Zero):
return x
assert isinstance(x, np.ndarray), "Vector must be a numpy array"
if numDims == 1:
@@ -355,9 +355,9 @@ def diagEst(matFun, n, k=None, approach='Probing'):
2. Ones : random +/- 1 entries
3. Random : random vectors
:param lambda (numpy.array) matFun: matrix to estimate the diagonal of
:param int64 n: size of the vector that should be used to compute matFun(v)
:param int64 k: number of vectors to be used to estimate the diagonal
:param callable matFun: takes a (numpy.array) and multiplies it by a matrix to estimate the diagonal
:param int n: size of the vector that should be used to compute matFun(v)
:param int k: number of vectors to be used to estimate the diagonal
:param str approach: approach to be used for getting vectors
:rtype: numpy.array
:return: est_diag(A)
@@ -422,9 +422,9 @@ class Zero(object):
def __ge__(self, v):return 0 >= v
def __gt__(self, v):return 0 > v
@property
@property
def transpose(self): return Zero()
@property
def T(self): return Zero()
SimPEG/Utils/meshutils.py
+2 -2
View File
@@ -83,7 +83,7 @@ def closestPoints(mesh, pts, gridLoc='CC'):
"""
Move a list of points to the closest points on a grid.
:param simpeg.Mesh.BaseMesh mesh: The mesh
:param BaseMesh mesh: The mesh
:param numpy.ndarray pts: Points to move
:param string gridLoc: ['CC', 'N', 'Fx', 'Fy', 'Fz', 'Ex', 'Ex', 'Ey', 'Ez']
:rtype: numpy.ndarray
@@ -107,7 +107,7 @@ def ExtractCoreMesh(xyzlim, mesh, meshType='tensor'):
Extracts Core Mesh from Global mesh
:param numpy.ndarray xyzlim: 2D array [ndim x 2]
:param simpeg.Mesh.BaseMesh mesh: The mesh
:param BaseMesh mesh: The mesh
This function ouputs::
docs/Makefile
+1 -1
View File
@@ -2,7 +2,7 @@
#
# You can set these variables from the command line.
SPHINXOPTS =
SPHINXOPTS = -n -w warnings.txt
SPHINXBUILD = sphinx-build
PAPER =
BUILDDIR = _build
docs/api_ForwardProblem.rst
+34 -2
View File
@@ -67,13 +67,45 @@ The API
Problem
-------
.. autoclass:: SimPEG.Problem
.. autoclass:: SimPEG.Problem.BaseProblem
:members:
:undoc-members:
.. autoclass:: SimPEG.Problem.BaseTimeProblem
:members:
:undoc-members:
Fields
------
.. autoclass:: SimPEG.Fields.Fields
:members:
:undoc-members:
.. autoclass:: SimPEG.Fields.TimeFields
:members:
:undoc-members:
Survey
------
.. autoclass:: SimPEG.Survey
.. autoclass:: SimPEG.Survey.BaseSurvey
:members:
:undoc-members:
.. autoclass:: SimPEG.Survey.BaseSrc
:members:
:undoc-members:
.. autoclass:: SimPEG.Survey.BaseRx
:members:
:undoc-members:
.. autoclass:: SimPEG.Survey.BaseTimeRx
:members:
:undoc-members:
.. autoclass:: SimPEG.Survey.Data
:members:
:undoc-members:
docs/api_InnerProducts.rst
+1 -1
View File
@@ -266,6 +266,6 @@ These are computed for each of the 8 projections, horizontally concatenated, and
The API
-------
.. autoclass:: SimPEG.Mesh.InnerProducts
.. autoclass:: SimPEG.Mesh.InnerProducts.InnerProducts
:members:
:undoc-members:
docs/api_Inversion.rst
+3 -3
View File
@@ -3,7 +3,7 @@
InvProblem
**********
.. autoclass:: SimPEG.InvProblem
.. autoclass:: SimPEG.InvProblem.BaseInvProblem
:show-inheritance:
:members:
:undoc-members:
@@ -12,7 +12,7 @@ InvProblem
Inversion
*********
.. autoclass:: SimPEG.Inversion
.. autoclass:: SimPEG.Inversion.BaseInversion
:show-inheritance:
:members:
:undoc-members:
@@ -20,7 +20,7 @@ Inversion
Directives
**********
.. autoclass:: SimPEG.Directives
.. automodule:: SimPEG.Directives
:show-inheritance:
:members:
:undoc-members:
docs/api_Maps.rst
+4 -3
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@@ -124,6 +124,8 @@ When these are used in the inverse problem, this is extremely important!!
The API
=======
The :code:`IdentityMap` is the base class for all mappings, and it does absolutely nothing.
.. autoclass:: SimPEG.Maps.IdentityMap
:members:
:undoc-members:
@@ -132,7 +134,6 @@ The API
Common Maps
===========
Exponential Map
---------------
@@ -198,8 +199,8 @@ Mesh to Mesh Map
:undoc-members:
Some Extras
===========
Under the Hood
==============
Combo Map
---------
docs/api_Mesh.rst
+1 -1
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@@ -188,6 +188,6 @@ other types of meshes in this SimPEG framework.
The API
=======
.. autoclass:: SimPEG.Mesh.BaseMesh
.. autoclass:: SimPEG.Mesh.BaseMesh.BaseMesh
:members:
:undoc-members:
docs/api_MeshCode.rst
+37 -2
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@@ -19,7 +19,7 @@ Cylindrical Mesh
Tree Mesh
=========
.. autoclass:: SimPEG.Mesh.TreeMesh.TreeMesh
.. autoclass:: SimPEG.Mesh.TreeMesh
:members:
:undoc-members:
:show-inheritance:
@@ -30,4 +30,39 @@ Curvilinear Mesh
.. autoclass:: SimPEG.Mesh.CurvilinearMesh
:members:
:undoc-members:
:show-inheritance:
:show-inheritance:
Base Rectangular Mesh
=====================
.. autoclass:: SimPEG.Mesh.BaseMesh.BaseRectangularMesh
:members:
:undoc-members:
:show-inheritance:
Base Tensor Mesh
================
.. autoclass:: SimPEG.Mesh.TensorMesh.BaseTensorMesh
:members:
:undoc-members:
:show-inheritance:
Mesh IO
=======
.. automodule:: SimPEG.Mesh.MeshIO
:members:
:undoc-members:
:show-inheritance:
Mesh Viewing
============
.. automodule:: SimPEG.Mesh.View
:members:
:undoc-members:
:show-inheritance:
docs/api_PropMaps.rst
+29
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@@ -0,0 +1,29 @@
SimPEG PropMaps
***************
The API
=======
Property
--------
.. autoclass:: SimPEG.PropMaps.Property
:members:
:undoc-members:
PropMap
-------
.. autoclass:: SimPEG.PropMaps.PropMap
:members:
:undoc-members:
PropModel
---------
.. autoclass:: SimPEG.PropMaps.PropModel
:members:
:undoc-members:
docs/api_Utilities.rst
+1
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@@ -6,5 +6,6 @@ Utilities
api_Solver
api_Maps
api_PropMaps
api_Utils
api_Tests
docs/api_bigPicture.rst
+2 -2
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@@ -51,9 +51,9 @@ There are an overwhelming amount of choices to be made as one works through the
:alt: Framework
:align: center
The process of obtaining an acceptable model from an inversion generally requires the geophysicist to perform several iterations of the inversion workflow, rethinking and redesigning each piece of the framework to ensure it is appropriate in the current context. Inversions are experimental and empirical by nature and our software package is designed to facilitate this iterative process. To accomplish this, we have divided the inversion methodology into eight major components (See figure above). The (:class:`SimPEG.Mesh.BaseMesh`) class handles the discretization of the earth and also provides numerical operators. The forward simulation is split into two classes, the (:class:`SimPEG.Survey.BaseSurvey`) and the (:class:`SimPEG.Problem.BaseProblem`). The (:class:`SimPEG.Survey.BaseSurvey`) class handles the geometry of a geophysical problem as well as sources. The (:class:`SimPEG.Problem.BaseProblem`) class handles the simulation of the physics for the geophysical problem of interest. Although created independently, these two classes must be paired to form all of the components necessary for a geophysical forward simulation and calculation of the sensitivity. The (:class:`SimPEG.Problem.BaseProblem`) creates geophysical fields given a source from the (:class:`SimPEG.Survey.BaseSurvey`). The (:class:`SimPEG.Survey.BaseSurvey`) interpolates these fields to the receiver locations and converts them to the appropriate data type, for example, by selecting only the measured components of the field. Each of these operations may have associated derivatives with respect to the model and the computed field; these are included in the calculation of the sensitivity. For the inversion, a (:class:`SimPEG.DataMisfit.BaseDataMisfit`) is chosen to capture the goodness of fit of the predicted data and a (:class:`SimPEG.Regularization.BaseRegularization`) is chosen to handle the non-uniqueness. These inversion elements and an Optimization routine are combined into an inverse problem class (:class:`SimPEG.InvProblem.BaseInvProblem`). (:class:`SimPEG.InvProblem.BaseInvProblem`) is the mathematical statement that will be numerically solved by running an Inversion. The (:class:`SimPEG.Inversion.BaseInversion`) class handles organization and dispatch of directives between all of the various pieces of the framework.
The process of obtaining an acceptable model from an inversion generally requires the geophysicist to perform several iterations of the inversion workflow, rethinking and redesigning each piece of the framework to ensure it is appropriate in the current context. Inversions are experimental and empirical by nature and our software package is designed to facilitate this iterative process. To accomplish this, we have divided the inversion methodology into eight major components (See figure above). The :class:`SimPEG.Mesh.BaseMesh.BaseMesh` class handles the discretization of the earth and also provides numerical operators. The forward simulation is split into two classes, the :class:`SimPEG.Survey.BaseSurvey` and the :class:`SimPEG.Problem.BaseProblem`. The :class:`SimPEG.Survey.BaseSurvey` class handles the geometry of a geophysical problem as well as sources. The :class:`SimPEG.Problem.BaseProblem` class handles the simulation of the physics for the geophysical problem of interest. Although created independently, these two classes must be paired to form all of the components necessary for a geophysical forward simulation and calculation of the sensitivity. The :class:`SimPEG.Problem.BaseProblem` creates geophysical fields given a source from the :class:`SimPEG.Survey.BaseSurvey`. The :class:`SimPEG.Survey.BaseSurvey` interpolates these fields to the receiver locations and converts them to the appropriate data type, for example, by selecting only the measured components of the field. Each of these operations may have associated derivatives with respect to the model and the computed field; these are included in the calculation of the sensitivity. For the inversion, a :class:`SimPEG.DataMisfit.BaseDataMisfit` is chosen to capture the goodness of fit of the predicted data and a :class:`SimPEG.Regularization.BaseRegularization` is chosen to handle the non-uniqueness. These inversion elements and an Optimization routine are combined into an inverse problem class :class:`SimPEG.InvProblem.BaseInvProblem`. :class:`SimPEG.InvProblem.BaseInvProblem` is the mathematical statement that will be numerically solved by running an Inversion. The :class:`SimPEG.Inversion.BaseInversion` class handles organization and dispatch of directives between all of the various pieces of the framework.
The arrows in the figure above indicate what each class takes as a primary argument. For example, both the (:class:`SimPEG.Problem.BaseProblem`) and (:class:`SimPEG.Regularization.BaseRegularization`) classes take a (:class:`SimPEG.Mesh.BaseMesh`) class as an argument. The diagram does not show class inheritance, as each of the base classes outlined have many subtypes that can be interchanged. The (:class:`SimPEG.Mesh.BaseMesh`) class, for example, could be a regular Cartesian mesh (:class:`SimPEG.Mesh.TensorMesh`) or a cylindrical coordinate mesh (:class:`SimPEG.Mesh.CylMesh`), which have many properties in common. These common features, such as both meshes being created from tensor products, can be exploited through inheritance of base classes, and differences can be expressed through subtype polymorphism. Please look at the documentation here for more in-depth information.
The arrows in the figure above indicate what each class takes as a primary argument. For example, both the :class:`SimPEG.Problem.BaseProblem` and :class:`SimPEG.Regularization.BaseRegularization` classes take a :class:`SimPEG.Mesh.BaseMesh.BaseMesh` class as an argument. The diagram does not show class inheritance, as each of the base classes outlined have many subtypes that can be interchanged. The :class:`SimPEG.Mesh.BaseMesh.BaseMesh` class, for example, could be a regular Cartesian mesh :class:`SimPEG.Mesh.TensorMesh` or a cylindrical coordinate mesh :class:`SimPEG.Mesh.CylMesh`, which have many properties in common. These common features, such as both meshes being created from tensor products, can be exploited through inheritance of base classes, and differences can be expressed through subtype polymorphism. Please look at the documentation here for more in-depth information.
.. include:: ../CITATION.rst
docs/conf.py
+21
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@@ -269,3 +269,24 @@ def _supress_nonlocal_image_warn(self, msg, node):
self._warnfunc(msg, '%s:%s' % get_source_line(node))
supress_nonlocal_image_warn()
nitpick_ignore = [
('py:class', 'IdentityMap'),
('py:class', 'BaseSurvey'),
('py:class', 'BaseSrc'),
('py:class', 'BaseRx'),
('py:class', 'Survey'),
('py:class', 'FieldsFDEM'),
('py:class', 'Fields3D_e'),
('py:class', 'Fields3D_b'),
('py:class', 'Fields3D_j'),
('py:class', 'Fields3D_h'),
('py:class', 'SurveyTDEM'),
('py:class', 'SrcTDEM'),
('py:class', 'EMPropMap'),
('py:class', 'Data'),
('py:class', 'SurveyDC'),
('py:class', 'BaseMTFields'),
('py:class', 'SolverLU'),
]
docs/em/api_TDEM.rst
+1 -1
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@@ -359,7 +359,7 @@ TDEM - B formulation
Field Storage
=============
.. autoclass:: SimPEG.EM.TDEM.SurveyTDEM.FieldsTDEM
.. autoclass:: SimPEG.EM.TDEM.BaseTDEM.FieldsTDEM
:show-inheritance:
:members:
:undoc-members:
docs/em/api_basic.rst
+33
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@@ -0,0 +1,33 @@
Overview of Electromagnetics in SimPEG
**************************************
The API
=======
Physical Properties
-------------------
.. autoclass:: SimPEG.EM.Base.EMPropMap
:show-inheritance:
:members:
:undoc-members:
Problem
-------
.. autoclass:: SimPEG.EM.Base.BaseEMProblem
:show-inheritance:
:members:
:undoc-members:
Survey
------
.. autoclass:: SimPEG.EM.Base.BaseEMSurvey
:show-inheritance:
:members:
:undoc-members:
docs/em/index.rst
+3 -2
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@@ -3,13 +3,13 @@ Electromagnetics
================
`SimPEG.EM` uses SimPEG as the framework for the forward and inverse
electromagnetics geophysical problems.
electromagnetics geophysical problems.
To solve for predicted data, we follow the framework shown below. The model is
what we invert for. This is mapped to a physical property on the simulation
mesh. A source which is used to excite the system is specified. Having a model
and a source, we can solve Maxwell's equations for fields. We sample these
fields with recievers to give us predicted data.
fields with recievers to give us predicted data.
.. image:: ../images/simpegEM_noMath.png
@@ -19,6 +19,7 @@ fields with recievers to give us predicted data.
.. toctree::
:maxdepth: 2
api_basic
api_FDEM
api_TDEM
api_Utils
docs/examples/EM_Schenkel_Morrison_Casing.rst
+4 -1
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@@ -17,10 +17,13 @@ current inside a steel-cased. The model is based on the Schenkel and
Morrison Casing Model, and the results are used in a 2016 SEG abstract by
Yang et al.
- Schenkel, C.J., and H.F. Morrison, 1990, Effects of well casing on potential field measurements using downhole current sources: Geophysical prospecting, 38, 663-686.
.. code-block:: text
Schenkel, C.J., and H.F. Morrison, 1990, Effects of well casing on potential field measurements using downhole current sources: Geophysical prospecting, 38, 663-686.
The model consists of:
- Air: Conductivity 1e-8 S/m, above z = 0
- Background: conductivity 1e-2 S/m, below z = 0
- Casing: conductivity 1e6 S/m
tests/docs/test_docs.py
+11 -11
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@@ -13,9 +13,9 @@ class Doc_Test(unittest.TestCase):
doctrees_path = os.path.sep.join(self.path_to_docs.split(os.path.sep) + ['_build']+['doctrees'])
html_path = os.path.sep.join(self.path_to_docs.split(os.path.sep) + ['_build']+['html'])
check = subprocess.call(["sphinx-build", "-nW", "-b", "html", "-d",
"%s"%(doctrees_path) ,
"%s"%(self.path_to_docs),
check = subprocess.call(["sphinx-build", "-nW", "-b", "html", "-d",
"%s"%(doctrees_path) ,
"%s"%(self.path_to_docs),
"%s"%(html_path)])
assert check == 0
@@ -23,9 +23,9 @@ class Doc_Test(unittest.TestCase):
# doctrees_path = os.path.sep.join(self.path_to_docs.split(os.path.sep) + ['_build']+['doctrees'])
# latex_path = os.path.sep.join(self.path_to_docs.split(os.path.sep) + ['_build']+['latex'])
# check = subprocess.call(["sphinx-build", "-nW", "-b", "latex", "-d",
# "%s"%(doctrees_path),
# "%s"%(self.path_to_docs),
# check = subprocess.call(["sphinx-build", "-nW", "-b", "latex", "-d",
# "%s"%(doctrees_path),
# "%s"%(self.path_to_docs),
# "%s"%(latex_path)])
# assert check == 0
@@ -33,11 +33,11 @@ class Doc_Test(unittest.TestCase):
# doctrees_path = os.path.sep.join(self.path_to_docs.split(os.path.sep) + ['_build']+['doctrees'])
# link_path = os.path.sep.join(self.path_to_docs.split(os.path.sep) + ['_build'])
# check = subprocess.call(["sphinx-build", "-nW", "-b", "linkcheck", "-d",
# "%s"%(doctrees_path),
# "%s"%(self.path_to_docs),
# check = subprocess.call(["sphinx-build", "-nW", "-b", "linkcheck", "-d",
# "%s"%(doctrees_path),
# "%s"%(self.path_to_docs),
# "%s"%(link_path)])
# assert check == 0
# assert check == 0
if __name__ == '__main__':
unittest.main()
unittest.main()