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Fixed bugs to run noise model input #1

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Fixed bugs to run noise model input #1

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25 changes: 23 additions & 2 deletions pycecream/pycecream/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -251,7 +251,15 @@ def set_creaminpar(self):
content[idplot] = np.str(int(np.ceil(self.N_iterations / 4.0)))

#deal with multiplicative step sizes
step_multiplicative = list(self.lightcurve_input_params['noise model'].map(set(['multiplicative']).issubset))
#original way of finding the multiplicative flag in noise model. Didn't worked properly.
#returned all False flags, thus no fitting for step sizes.
#step_multiplicative = list(self.lightcurve_input_params['noise model'].map(set(['multiplicative']).issubset))

# NEW way of finding the multiplicative flag in noise model. Could be more pythonised.
step_multiplicative = []
for kk in self.lightcurve_input_params['noise model'].values:
step_multiplicative.append('multiplicative' in kk[0])

step = []
for i in range(self.count_lightcurves):
if step_multiplicative[i] is True:
Expand Down Expand Up @@ -307,16 +315,29 @@ def set_var(self):
creates the file instructing cream how to treat the extra variance parameters
(starting parameter values and step sizes)
:return:

History:
J. Hernandez Santisteban. Now it correctly sets the var parameter when added
to the noise model. Previously all were zeros and no added variance was included.
'''
f = open(self.dir_pycecream+'/'+self.dir_sim + '/cream_var.par', 'w')
# >> Juan change to check for var in noise model
step_var = []
for kk in self.lightcurve_input_params['noise model'].values:
step_var.append('var' in kk[0])
#print('>> Juan: ',step_var)
for i in range(self.count_lightcurves):
f.write('0.0 ')
if step_var[i] == True:
f.write('0.1 ')
else:
f.write('0.0 ')
f.write(np.str( self.p_extra_variance_step*
self.lightcurve_input_params['standard deviation'].values[i]) +'\n')
f.close()




def run(self):
'''
run the cream code. Make sure input above is correct first
Expand Down