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rowanc1
100 lines
2.6 KiB
Python
100 lines
2.6 KiB
Python
from SimPEG import utils
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def requiresProblem(f):
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"""
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Use this to wrap a funciton::
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@requiresProblem
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def dpred(self):
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pass
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This wrapper will ensure that a problem has been bound to the data.
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If a problem is not bound an Exception will be raised, and an nice error message printed.
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"""
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extra = """
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This function requires that a problem be bound to the data.
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If a problem has not been bound, an Exception will be raised.
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To bind a problem to the Data object::
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data.setProblem(myProblem)
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"""
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from functools import wraps
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@wraps(f)
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def requiresProblemWrapper(self,*args,**kwargs):
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if getattr(self, 'prob', None) is None:
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raise Exception(extra)
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return f(self,*args,**kwargs)
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doc = requiresProblemWrapper.__doc__
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requiresProblemWrapper.__doc__ = ('' if doc is None else doc) + extra
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return requiresProblemWrapper
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class Data(object):
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"""Data holds the observed data, and the standard deviations."""
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__metaclass__ = utils.Save.Savable
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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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prob = None #: The geophysical problem that explains this data
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def __init__(self, **kwargs):
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utils.setKwargs(self, **kwargs)
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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 setProblem(self, prob):
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self.prob = prob
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@property
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def Wd(self):
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"""
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Standard deviation weighting matrix.
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By default, this is based on the norm of the data plus a noise floor.
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"""
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if getattr(self,'_Wd',None) is None:
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eps = np.linalg.norm(utils.mkvc(self.dobs),2)*1e-5
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self._Wd = 1/(abs(self.dobs)*self.std+eps)
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return self._Wd
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@Wd.setter
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def Wd(self, value):
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self._Wd = value
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@requiresProblem
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def dpred(self, m, u=None):
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if u is None: u = self.prob.field(m)
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@requiresProblem
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def residual(self, m, u=None):
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if u is None: u = self.prob.field(m)
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@requiresProblem
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def residualWeighted(self, m, u=None):
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if u is None: u = self.prob.field(m)
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@requiresProblem
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def projectField(self, m, u=None):
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"""
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Projection matrix.
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.. math::
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d_\\text{pred} = Pu(m)
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"""
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if u is None: u = self.prob.field(m)
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return self.P*u
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if __name__ == '__main__':
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d = SimPEGData()
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d.dpred()
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