Commit a5bf3bfd authored by Theo Steininger's avatar Theo Steininger

Fixed EnsembleLikelihood

parent 24ff68bf
......@@ -49,7 +49,7 @@ class EnsembleLikelihood(Likelihood):
# compute quantities for OAS estimator
mu = np.vdot(u_val, u_val)/n
alpha = (np.einsum(u_val, [0, 1], u_val, [2, 0])**2).sum()
alpha = (np.einsum(u_val, [0, 1], u_val, [2, 1])**2).sum()
numerator = alpha + mu**2
denominator = (k + 1) / (alpha - (mu**2)/n)
......
......@@ -27,7 +27,7 @@ class Observable(Field):
return self._ensemble_mean
def _to_hdf5(self, hdf5_group):
if hasattr(self, _ensemble_mean):
if hasattr(self, '_ensemble_mean'):
return_dict = {'ensemble_mean': self._ensemble_mean}
else:
return_dict = {}
......
......@@ -35,7 +35,7 @@ class Hammurapy(Observer):
self.basic_parameters = {'B_ran_mem_lim': '6',
'obs_shell_index_numb': '1',
'total_shell_numb': '3',
'total_shell_numb': '1',
'vec_size_R': '500',
'max_radius': '30',
'max_z': '15',
......@@ -76,6 +76,7 @@ class Hammurapy(Observer):
errlog = temp_process.communicate()[1]
# check if there were some errors
if errlog == '':
self.logger.debug("Successfully removed temporary folder.")
break
else:
self.logger.warning('Could not delete %s' % path)
......@@ -169,7 +170,7 @@ class Hammurapy(Observer):
parameter_dict = self.basic_parameters.copy()
# set the parameters for a numerical run
parameter_dict['B_field_interp'] = 'F'
parameter_dict['B_field_interp'] = 'T'
parameter_dict['use_B_analytic'] = 'F'
self._build_parameter_dict(
......
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