Problem.Jvec, Problem.Jtvec, Problem.fields, DataMisfit, survey.dpred take a fields object f (not a solution vector, u)

This commit is contained in:
Lindsey Heagy
2016-03-29 22:49:03 -07:00
parent 1d208a8747
commit 0a0caceaca
7 changed files with 98 additions and 104 deletions
+13 -13
View File
@@ -295,21 +295,21 @@ class BaseSurvey(object):
@Utils.count
@Utils.requires('prob')
def dpred(self, m, u=None):
"""dpred(m, u=None)
def dpred(self, m, f=None):
"""dpred(m, f=None)
Create the projected data from a model.
The field, u, (if provided) will be used for the predicted data
The fields, f, (if provided) will be used for the predicted data
instead of recalculating the fields (which may be expensive!).
.. math::
d_\\text{pred} = P(u(m))
d_\\text{pred} = P(f(m))
Where P is a projection of the fields onto the data space.
"""
if u is None: u = self.prob.fields(m)
return Utils.mkvc(self.eval(u))
if f is None: f = self.prob.fields(m)
return Utils.mkvc(self.eval(f))
@Utils.count
@@ -337,11 +337,11 @@ class BaseSurvey(object):
raise NotImplemented('eval is not yet implemented.')
@Utils.count
def residual(self, m, u=None):
"""residual(m, u=None)
def residual(self, m, f=None):
"""residual(m, f=None)
:param numpy.array m: geophysical model
:param numpy.array u: fields
:param numpy.array f: fields
:rtype: numpy.array
:return: data residual
@@ -352,14 +352,14 @@ class BaseSurvey(object):
\mu_\\text{data} = \mathbf{d}_\\text{pred} - \mathbf{d}_\\text{obs}
"""
return Utils.mkvc(self.dpred(m, u=u) - self.dobs)
return Utils.mkvc(self.dpred(m, f=f) - self.dobs)
@property
def isSynthetic(self):
"Check if the data is synthetic."
return self.mtrue is not None
def makeSyntheticData(self, m, std=0.05, u=None, force=False):
def makeSyntheticData(self, m, std=0.05, f=None, force=False):
"""
Make synthetic data given a model, and a standard deviation.
@@ -372,7 +372,7 @@ class BaseSurvey(object):
if getattr(self, 'dobs', None) is not None and not force:
raise Exception('Survey already has dobs. You can use force=True to override this exception.')
self.mtrue = m
self.dtrue = self.dpred(m, u=u)
self.dtrue = self.dpred(m, f=f)
noise = std*abs(self.dtrue)*np.random.randn(*self.dtrue.shape)
self.dobs = self.dtrue+noise
self.std = self.dobs*0 + std
@@ -381,7 +381,7 @@ class BaseSurvey(object):
class LinearSurvey(BaseSurvey):
def eval(self, u):
return u
@property
def nD(self):
return self.prob.G.shape[0]