Simple profiling through decorator functions. (counting and timing of functions decorated with @count and @timeIt that have a SimPEG.utils.Counter)

e.g. output:
‘’’
Counters:
  InexactGaussNewton.doEndIteration       :        6
  InexactGaussNewton.printIter            :        7
  InexactGaussNewton.scaleSearchDirection :        6

Times:                                        mean      sum
  InexactGaussNewton.findSearchDirection  : 1.55e-02, 9.29e-02,    6x
  InexactGaussNewton.minimize             : 1.10e-01, 1.10e-01,    1x
  InexactGaussNewton.modifySearchDirection: 2.89e-04, 1.73e-03,    6x
  InexactGaussNewton.projection           : 3.69e-06, 1.11e-04,   30x
  InexactGaussNewton.stoppingCriteria     : 1.16e-04, 1.51e-03,   13x
  Inversion.dataObj                       : 6.60e-05, 8.58e-04,   13x
  Inversion.dataObj2Deriv                 : 1.03e-04, 6.20e-03,   60x
  Inversion.dataObjDeriv                  : 5.06e-05, 3.54e-04,    7x
  Inversion.evalFunction                  : 7.75e-04, 1.01e-02,   13x
  Inversion.run                           : 1.10e-01, 1.10e-01,    1x
  Regularization.modelObj                 : 3.56e-04, 4.63e-03,   13x
  Regularization.modelObj2Deriv           : 1.29e-03, 7.76e-02,   60x
  Regularization.modelObjDeriv            : 5.01e-04, 3.51e-03,    7x
‘’’

SimPEG/forward/Problem.py

@@ -1,5 +1,5 @@
 import numpy as np
-from SimPEG.utils import mkvc, sdiag
+from SimPEG.utils import mkvc, sdiag, count, timeIt
 import scipy.sparse as sp
 norm = np.linalg.norm
 
@@ -37,6 +37,8 @@ class Problem(object):
         to (locally) find how model parameters change the data, and optimize!
     """
 
+    counter = None
+
     def __init__(self, mesh):
         self.mesh = mesh
 
@@ -83,6 +85,7 @@ class Problem(object):
     def dobs(self, value):
         self._dobs = value
 
+    @count
     def dpred(self, m, u=None):
         """
             Predicted data.
@@ -94,6 +97,7 @@ class Problem(object):
             u = self.field(m)
         return self.P*u
 
+    @count
     def dataResidual(self, m, u=None):
         """
             :param numpy.array m: geophysical model
@@ -113,6 +117,7 @@ class Problem(object):
 
         return self.dpred(m, u=u) - self.dobs
 
+    @timeIt
     def J(self, m, v, u=None):
         """
             :param numpy.array m: model
@@ -142,6 +147,7 @@ class Problem(object):
         """
         raise NotImplementedError('J is not yet implemented.')
 
+    @timeIt
     def Jt(self, m, v, u=None):
         """
             :param numpy.array m: model
@@ -155,6 +161,7 @@ class Problem(object):
         raise NotImplementedError('Jt is not yet implemented.')
 
 
+    @timeIt
     def J_approx(self, m, v, u=None):
         """
 
@@ -169,6 +176,7 @@ class Problem(object):
         """
         return self.J(m, v, u)
 
+    @timeIt
     def Jt_approx(self, m, v, u=None):
         """
             :param numpy.array m: model