use the std and eps from survey in definition of data misfit if defined (and demonstrate it with the TDEM example)

This commit is contained in:
Lindsey Heagy
2016-01-28 13:20:48 -08:00
parent f5333f35a2
commit c24416ea12
3 changed files with 15 additions and 17 deletions
+11 -17
View File
@@ -59,20 +59,6 @@ class BaseDataMisfit(object):
"""
raise NotImplementedError('This method should be overwritten.')
# TODO: implement target misfit as a property, or possibly as an inversion directive.
# def target(self, forward):
# """target(forward)
# Target for data misfit. By default this is the number of data,
# which satisfies the Discrepancy Principle.
# :rtype: float
# :return: data misfit target
# """
# prob, survey = self.splitForward(forward)
# return survey.nD
class l2_DataMisfit(BaseDataMisfit):
@@ -103,10 +89,18 @@ class l2_DataMisfit(BaseDataMisfit):
"""
if getattr(self, '_Wd', None) is None:
print 'SimPEG.l2_DataMisfit is creating default weightings for Wd.'
survey = self.survey
eps = np.linalg.norm(Utils.mkvc(survey.dobs),2)*1e-5
self._Wd = Utils.sdiag(1/(abs(survey.dobs)*survey.std+eps))
if getattr(survey,'std', None) is None:
print 'SimPEG.DataMisfit.l2_DataMisfit assigning default std of 5%'
survey.std = 0.05
if getattr(survey, 'eps', None) is None:
print 'SimPEG.DataMisfit.l2_DataMisfit assigning default eps of 1e-5 * ||dobs||'
survey.eps = np.linalg.norm(Utils.mkvc(survey.dobs),2)*1e-5
self._Wd = Utils.sdiag(1/(abs(survey.dobs)*survey.std+survey.eps))
return self._Wd
@Wd.setter
+3
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@@ -53,7 +53,10 @@ def run(plotIt=True):
# create observed data
std = 0.05
survey.dobs = survey.makeSyntheticData(mtrue,std)
survey.std = std
survey.eps = 1e-5*np.linalg.norm(survey.dobs)
if plotIt:
import matplotlib.pyplot as plt
+1
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@@ -205,6 +205,7 @@ class BaseSurvey(object):
__metaclass__ = Utils.SimPEGMetaClass
std = None #: Estimated Standard Deviations
eps = None #: Estimated Noise Floor
dobs = None #: Observed data
dtrue = None #: True data, if data is synthetic
mtrue = None #: True model, if data is synthetic