mirror of
https://github.com/wassname/simpeg.git
synced 2026-06-28 12:11:08 +08:00
621 lines
19 KiB
Python
621 lines
19 KiB
Python
import Utils, numpy as np, scipy.sparse as sp
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class BaseRx(object):
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"""SimPEG Receiver Object"""
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locs = None #: Locations (nRx x nDim)
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knownRxTypes = None #: Set this to a list of strings to ensure that txType is known
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projGLoc = 'CC' #: Projection grid location, default is CC
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storeProjections = True #: Store calls to getP (organized by mesh)
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def __init__(self, locs, rxType, **kwargs):
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self.locs = locs
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self.rxType = rxType
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self._Ps = {}
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Utils.setKwargs(self, **kwargs)
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@property
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def rxType(self):
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"""Receiver Type"""
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return getattr(self, '_rxType', None)
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@rxType.setter
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def rxType(self, value):
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known = self.knownRxTypes
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if known is not None:
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assert value in known, "rxType must be in ['%s']" % ("', '".join(known))
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self._rxType = value
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@property
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def nD(self):
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"""Number of data in the receiver."""
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return self.locs.shape[0]
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def getP(self, mesh):
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"""
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Returns the projection matrices as a
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list for all components collected by
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the receivers.
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.. note::
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Projection matrices are stored as a dictionary listed by meshes.
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"""
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if mesh in self._Ps:
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return self._Ps[mesh]
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P = mesh.getInterpolationMat(self.locs, self.projGLoc)
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if self.storeProjections:
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self._Ps[mesh] = P
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return P
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class BaseTimeRx(BaseRx):
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"""SimPEG Receiver Object"""
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times = None #: Times when the receivers were active.
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projTLoc = 'N'
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def __init__(self, locs, times, rxType, **kwargs):
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self.times = times
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BaseRx.__init__(self, locs, rxType, **kwargs)
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@property
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def nD(self):
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"""Number of data in the receiver."""
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return self.locs.shape[0] * len(self.times)
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def getSpatialP(self, mesh):
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"""
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Returns the spatial projection matrix.
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.. note::
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This is not stored in memory, but is created on demand.
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"""
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return mesh.getInterpolationMat(self.locs, self.projGLoc)
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def getTimeP(self, timeMesh):
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"""
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Returns the time projection matrix.
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.. note::
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This is not stored in memory, but is created on demand.
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"""
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return timeMesh.getInterpolationMat(self.times, self.projTLoc)
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def getP(self, mesh, timeMesh):
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"""
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Returns the projection matrices as a
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list for all components collected by
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the receivers.
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.. note::
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Projection matrices are stored as a dictionary (mesh, timeMesh) if storeProjections is True
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"""
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if (mesh, timeMesh) in self._Ps:
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return self._Ps[(mesh, timeMesh)]
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Ps = self.getSpatialP(mesh)
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Pt = self.getTimeP(timeMesh)
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P = sp.kron(Pt, Ps)
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if self.storeProjections:
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self._Ps[(mesh, timeMesh)] = P
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return P
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class BaseTx(object):
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"""SimPEG Transmitter Object"""
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loc = None #: Location [x,y,z]
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rxList = None #: SimPEG Receiver List
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rxPair = BaseRx
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knownTxTypes = None #: Set this to a list of strings to ensure that txType is known
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def __init__(self, loc, txType, rxList, **kwargs):
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assert type(rxList) is list, 'rxList must be a list'
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for rx in rxList:
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assert isinstance(rx, self.rxPair), 'rxList must be a %s'%self.rxPair.__name__
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assert len(set(rxList)) == len(rxList), 'The rxList must be unique'
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self.loc = loc
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self.txType = txType
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self.rxList = rxList
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Utils.setKwargs(self, **kwargs)
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@property
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def txType(self):
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"""Transmitter Type"""
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return getattr(self, '_txType', None)
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@txType.setter
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def txType(self, value):
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known = self.knownTxTypes
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if known is not None:
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assert value in known, "txType must be in ['%s']" % ("', '".join(known))
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self._txType = value
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@property
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def nD(self):
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"""Number of data"""
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return self.vnD.sum()
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@property
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def vnD(self):
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"""Vector number of data"""
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return np.array([rx.nD for rx in self.rxList])
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class Data(object):
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"""Fancy data storage by Tx and Rx"""
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def __init__(self, survey, v=None):
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self.survey = survey
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self._dataDict = {}
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for tx in self.survey.txList:
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self._dataDict[tx] = {}
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if v is not None:
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self.fromvec(v)
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def _ensureCorrectKey(self, key):
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if type(key) is tuple:
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if len(key) is not 2:
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raise KeyError('Key must be [Tx, Rx]')
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if key[0] not in self.survey.txList:
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raise KeyError('Tx Key must be a transmitter in the survey.')
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if key[1] not in key[0].rxList:
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raise KeyError('Rx Key must be a receiver for the transmitter.')
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return key
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elif isinstance(key, self.survey.txPair):
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if key not in self.survey.txList:
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raise KeyError('Key must be a transmitter in the survey.')
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return key, None
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else:
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raise KeyError('Key must be [Tx] or [Tx,Rx]')
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def __setitem__(self, key, value):
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tx, rx = self._ensureCorrectKey(key)
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assert rx is not None, 'set data using [Tx, Rx]'
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assert isinstance(value, np.ndarray), 'value must by ndarray'
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assert value.size == rx.nD, "value must have the same number of data as the transmitter."
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self._dataDict[tx][rx] = Utils.mkvc(value)
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def __getitem__(self, key):
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tx, rx = self._ensureCorrectKey(key)
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if rx is not None:
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if rx not in self._dataDict[tx]:
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raise Exception('Data for receiver has not yet been set.')
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return self._dataDict[tx][rx]
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return np.concatenate([self[tx,rx] for rx in tx.rxList])
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def tovec(self):
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return np.concatenate([self[tx] for tx in self.survey.txList])
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def fromvec(self, v):
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v = Utils.mkvc(v)
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assert v.size == self.survey.nD, 'v must have the correct number of data.'
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indBot, indTop = 0, 0
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for tx in self.survey.txList:
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for rx in tx.rxList:
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indTop += rx.nD
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self[tx, rx] = v[indBot:indTop]
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indBot += rx.nD
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class Fields(object):
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"""Fancy Field Storage
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u[:,'phi'] = phi
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print u[tx0,'phi']
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"""
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knownFields = None #: Known fields, a dict with locations, e.g. {"e": "E", "phi": "CC"}
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aliasFields = None #: Aliased fields, a dict with [alias, location, function], e.g. {"b":["e","F",lambda(F,e,ind)]}
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dtype = float #: dtype is the type of the storage matrix. This can be a dictionary.
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def __init__(self, mesh, survey, **kwargs):
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self.survey = survey
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self.mesh = mesh
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Utils.setKwargs(self, **kwargs)
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self._fields = {}
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if self.knownFields is None:
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raise Exception('knownFields cannot be set to None')
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if self.aliasFields is None:
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self.aliasFields = {}
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allFields = [k for k in self.knownFields] + [a for a in self.aliasFields]
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assert len(allFields) == len(set(allFields)), 'Aliased fields and Known Fields have overlapping definitions.'
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self.startup()
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def startup(self):
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pass
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@property
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def approxSize(self):
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"""The approximate cost to storing all of the known fields."""
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sz = 0.0
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for f in self.knownFields:
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loc =self.knownFields[f]
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sz += np.array(self._storageShape(loc)).prod()*8.0/(1024**2)
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return "%e MB"%sz
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def _storageShape(self, loc):
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nTx = self.survey.nTx
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nP = {'CC': self.mesh.nC,
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'N': self.mesh.nN,
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'F': self.mesh.nF,
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'E': self.mesh.nE}[loc]
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return (nP, nTx)
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def _initStore(self, name):
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if name in self._fields:
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return self._fields[name]
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assert name in self.knownFields, 'field name is not known.'
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loc = self.knownFields[name]
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if type(self.dtype) is dict:
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dtype = self.dtype[name]
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else:
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dtype = self.dtype
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field = np.zeros(self._storageShape(loc), dtype=dtype)
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self._fields[name] = field
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return field
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def _txIndex(self, txTestList):
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if type(txTestList) is slice:
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ind = txTestList
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else:
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if type(txTestList) is not list:
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txTestList = [txTestList]
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for txTest in txTestList:
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if txTest not in self.survey.txList:
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raise KeyError('Invalid Transmitter, not in survey list.')
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ind = np.in1d(self.survey.txList, txTestList)
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return ind
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def _nameIndex(self, name, accessType):
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if type(name) is slice:
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assert name == slice(None,None,None), 'Fancy field name slicing is not supported... yet.'
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name = None
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if name is None:
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return
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if accessType=='set' and name not in self.knownFields:
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if name in self.aliasFields:
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raise KeyError("Invalid field name (%s) for setter, you can't set an aliased property"%name)
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else:
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raise KeyError('Invalid field name (%s) for setter'%name)
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elif accessType=='get' and (name not in self.knownFields and name not in self.aliasFields):
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raise KeyError('Invalid field name (%s) for getter'%name)
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return name
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def _indexAndNameFromKey(self, key, accessType):
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if type(key) is not tuple:
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key = (key,)
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if len(key) == 1:
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key += (None,)
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assert len(key) == 2, 'must be [Tx, fieldName]'
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txTestList, name = key
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name = self._nameIndex(name, accessType)
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ind = self._txIndex(txTestList)
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return ind, name
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def __setitem__(self, key, value):
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ind, name = self._indexAndNameFromKey(key, 'set')
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if name is None:
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freq = key
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assert type(value) is dict, 'New fields must be a dictionary, if field is not specified.'
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newFields = value
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elif name in self.knownFields:
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newFields = {name: value}
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else:
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raise Exception('Unknown setter')
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for name in newFields:
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field = self._initStore(name)
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self._setField(field, newFields[name], name, ind)
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def __getitem__(self, key):
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ind, name = self._indexAndNameFromKey(key, 'get')
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if name is None:
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out = {}
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for name in self._fields:
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out[name] = self._getField(name, ind)
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return out
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return self._getField(name, ind)
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def _setField(self, field, val, name, ind):
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if isinstance(val, np.ndarray) and (field.shape[1] == 1 or val.ndim == 1):
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val = Utils.mkvc(val,2)
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field[:,ind] = val
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def _getField(self, name, ind):
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if name in self._fields:
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out = self._fields[name][:,ind]
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else:
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# Aliased fields
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alias, loc, func = self.aliasFields[name]
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if type(func) is str:
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assert hasattr(self, func), 'The alias field function is a string, but it does not exist in the Fields class.'
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func = getattr(self, func)
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out = func(self._fields[alias][:,ind], ind)
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if out.shape[1] == 1:
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out = Utils.mkvc(out)
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return out
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def __contains__(self, other):
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if other in self.aliasFields:
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other = self.aliasFields[other][0]
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return self._fields.__contains__(other)
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class TimeFields(Fields):
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"""Fancy Field Storage for time domain problems
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u[:,'phi', timeInd] = phi
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print u[tx0,'phi']
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"""
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def _storageShape(self, loc):
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nP = {'CC': self.mesh.nC,
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'N': self.mesh.nN,
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'F': self.mesh.nF,
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'E': self.mesh.nE}[loc]
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nTx = self.survey.nTx
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nT = self.survey.prob.nT
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return (nP, nTx, nT + 1)
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def _indexAndNameFromKey(self, key, accessType):
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if type(key) is not tuple:
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key = (key,)
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if len(key) == 1:
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key += (None,)
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if len(key) == 2:
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key += (slice(None,None,None),)
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assert len(key) == 3, 'must be [Tx, fieldName, times]'
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txTestList, name, timeInd = key
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name = self._nameIndex(name, accessType)
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txInd = self._txIndex(txTestList)
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return (txInd, timeInd), name
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def _correctShape(self, name, ind, deflate=False):
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txInd, timeInd = ind
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if name in self.knownFields:
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loc = self.knownFields[name]
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else:
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loc = self.aliasFields[name][1]
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nP, total_nTx, total_nT = self._storageShape(loc)
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nTx = np.ones(total_nTx, dtype=bool)[txInd].sum()
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nT = np.ones(total_nT, dtype=bool)[timeInd].sum()
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shape = nP, nTx, nT
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if deflate:
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shape = tuple([s for s in shape if s > 1])
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return shape
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def _setField(self, field, val, name, ind):
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txInd, timeInd = ind
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shape = self._correctShape(name, ind)
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if Utils.isScalar(val):
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field[:,txInd,timeInd] = val
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return
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if val.size != np.array(shape).prod():
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raise ValueError('Incorrect size for data.')
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correctShape = field[:,txInd,timeInd].shape
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field[:,txInd,timeInd] = val.reshape(correctShape, order='F')
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def _getField(self, name, ind):
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txInd, timeInd = ind
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if name in self._fields:
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out = self._fields[name][:,txInd,timeInd]
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else:
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# Aliased fields
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alias, loc, func = self.aliasFields[name]
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if type(func) is str:
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assert hasattr(self, func), 'The alias field function is a string, but it does not exist in the Fields class.'
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func = getattr(self, func)
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pointerFields = self._fields[alias][:,txInd,timeInd]
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pointerShape = self._correctShape(alias, ind, deflate=True)
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pointerFields = pointerFields.reshape(pointerShape, order='F')
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if len(pointerShape) < 3:
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out = func(pointerFields, txInd)
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else: #loop over the time steps
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nT = pointerShape[2]
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out = range(nT)
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for i in range(nT):
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out[i] = func(pointerFields[:,:,i], txInd)
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out[i] = out[i][:,:,np.newaxis]
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out = np.concatenate(out, axis=2)
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shape = self._correctShape(name, ind, deflate=True)
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return out.reshape(shape, order='F')
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class BaseSurvey(object):
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"""Survey holds the observed data, and the standard deviations."""
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__metaclass__ = Utils.SimPEGMetaClass
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std = None #: Estimated Standard Deviations
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dobs = None #: Observed data
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dtrue = None #: True data, if data is synthetic
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mtrue = None #: True model, if data is synthetic
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counter = None #: A SimPEG.Utils.Counter object
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def __init__(self, **kwargs):
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Utils.setKwargs(self, **kwargs)
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txPair = BaseTx #: Transmitter Pair
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@property
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def txList(self):
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"""Transmitter List"""
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return getattr(self, '_txList', None)
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@txList.setter
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def txList(self, value):
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assert type(value) is list, 'txList must be a list'
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assert np.all([isinstance(tx, self.txPair) for tx in value]), 'All transmitters must be instances of %s' % self.txPair.__name__
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assert len(set(value)) == len(value), 'The txList must be unique'
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self._txList = value
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@property
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def prob(self):
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"""
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The geophysical problem that explains this survey, use::
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survey.pair(prob)
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"""
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return getattr(self, '_prob', None)
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@property
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def mesh(self):
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"""Mesh of the paired problem."""
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if self.ispaired:
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return self.prob.mesh
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raise Exception('Pair survey to a problem to access the problems mesh.')
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def pair(self, p):
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"""Bind a problem to this survey instance using pointers"""
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assert hasattr(p, 'surveyPair'), "Problem must have an attribute 'surveyPair'."
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assert isinstance(self, p.surveyPair), "Problem requires survey object must be an instance of a %s class."%(p.surveyPair.__name__)
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if p.ispaired:
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raise Exception("The problem object is already paired to a survey. Use prob.unpair()")
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self._prob = p
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p._survey = self
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def unpair(self):
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"""Unbind a problem from this survey instance"""
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if not self.ispaired: return
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self.prob._survey = None
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self._prob = None
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@property
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def ispaired(self): return self.prob is not None
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@property
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def nD(self):
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"""Number of data"""
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return self.vnD.sum()
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@property
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def vnD(self):
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"""Vector number of data"""
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return np.array([tx.nD for tx in self.txList])
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@property
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def nTx(self):
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"""Number of Transmitters"""
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return len(self.txList)
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@Utils.count
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@Utils.requires('prob')
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def dpred(self, m, u=None):
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"""dpred(m, u=None)
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Create the projected data from a model.
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The field, u, (if provided) will be used for the predicted data
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instead of recalculating the fields (which may be expensive!).
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.. math::
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d_\\text{pred} = P(u(m))
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Where P is a projection of the fields onto the data space.
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"""
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if u is None: u = self.prob.fields(m)
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return Utils.mkvc(self.projectFields(u))
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@Utils.count
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def projectFields(self, u):
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"""projectFields(u)
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This function projects the fields onto the data space.
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.. math::
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d_\\text{pred} = \mathbf{P} u(m)
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"""
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raise NotImplemented('projectFields is not yet implemented.')
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@Utils.count
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def projectFieldsDeriv(self, u):
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"""projectFieldsDeriv(u)
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This function s the derivative of projects the fields onto the data space.
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.. math::
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\\frac{\partial d_\\text{pred}}{\partial u} = \mathbf{P}
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"""
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raise NotImplemented('projectFields is not yet implemented.')
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@Utils.count
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def residual(self, m, u=None):
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"""residual(m, u=None)
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:param numpy.array m: geophysical model
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:param numpy.array u: fields
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:rtype: numpy.array
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:return: data residual
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|
The data residual:
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|
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.. math::
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\mu_\\text{data} = \mathbf{d}_\\text{pred} - \mathbf{d}_\\text{obs}
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"""
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return Utils.mkvc(self.dpred(m, u=u) - self.dobs)
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@property
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def isSynthetic(self):
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"Check if the data is synthetic."
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return self.mtrue is not None
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def makeSyntheticData(self, m, std=0.05, u=None):
|
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"""
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Make synthetic data given a model, and a standard deviation.
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:param numpy.array m: geophysical model
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:param numpy.array std: standard deviation
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:param numpy.array u: fields for the given model (if pre-calculated)
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"""
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if getattr(self, 'dobs', None) is not None:
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raise Exception('Survey already has dobs.')
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self.mtrue = m
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self.dtrue = self.dpred(m, u=u)
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noise = std*abs(self.dtrue)*np.random.randn(*self.dtrue.shape)
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self.dobs = self.dtrue+noise
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self.std = self.dobs*0 + std
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