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Include sigma av as another parameter for starwave to use. #25

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Include sigma av as another parameter for starwave to use. #25

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612e275
Update starwave.py
joycelin1123 Jul 18, 2023
f5e4803
Update starwave.py
joycelin1123 Jul 28, 2023
ef67984
Update parameters.py
joycelin1123 Jul 28, 2023
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1 change: 1 addition & 0 deletions starwave/parameters.py
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Original file line number Diff line number Diff line change
Expand Up @@ -145,6 +145,7 @@ def make_params(imf_type, sfh_type, kwargs = None): # add SFH TYPE
## ADD EXTINCTION WITH EXTINCT PACKAGE

parameters['av'] = SWParameter('av', 0, [0, 1], fixed = True)
parameters['sig_av'] = SWParameter('sig_av', 0.015, [0, 1], fixed = True)

if imf_type == 'spl':

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27 changes: 21 additions & 6 deletions starwave/starwave.py
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Expand Up @@ -147,10 +147,14 @@ def get_cmd(self, nstars, gr_dict, pdict):
input_mags = np.empty((nstars, len(self.bands)))
input_mags[:] = np.nan

exts = np.empty((nstars, len(self.bands)))
exts[:] = np.nan

masses = gr_dict['logM'].sample(nstars)
binqs = gr_dict['BinQ'].sample(nstars)
sfhs = gr_dict['SFH'].sample(nstars)
dms = gr_dict['DM'].sample(nstars)
avs = gr_dict['av'].sample(nstars)


for ii in range(nstars):
Expand All @@ -159,6 +163,7 @@ def get_cmd(self, nstars, gr_dict, pdict):
binq = binqs[ii]
age, feh = sfhs[ii]
dm = dms[ii]
av = avs[ii]

if mass < self.lim_logmass or np.isnan(age) or np.isnan(feh):
continue
Expand All @@ -167,14 +172,20 @@ def get_cmd(self, nstars, gr_dict, pdict):

input_mags[ii, :] = input_mag + dm

exts[ii,:] = np.array([extinction.ccm89(np.array([band_lambda]),av,self.Rv)[0] for band_lambda in self.band_lambdas])


nans = (np.isnan(input_mags) + (input_mags < self.trgb)).any(axis = 1)

input_mags = input_mags[~nans]

exts = exts[~nans]

BM_in = nans

if len(input_mags) == 0:
return input_mags, input_mags

exts = np.array([extinction.ccm89(np.array([band_lambda]),pdict['av'],self.Rv)[0] for band_lambda in self.band_lambdas])
input_mags += exts

idxs = self.kdtree.query(input_mags)[1][:, 0]
Expand All @@ -185,8 +196,11 @@ def get_cmd(self, nstars, gr_dict, pdict):

output_mags = output_mags[~nans]

BM_out = nans

sdict = {'masses': masses, 'binqs': binqs, 'sfhs': sfhs, 'dms': dms, 'exts': exts, 'BM_in': BM_in, 'BM_out': BM_out}

return input_mags, output_mags
return input_mags, output_mags, sdict

def make_cmd(self, mags):
"""
Expand Down Expand Up @@ -377,16 +391,17 @@ def sample_cmd(self, params, model):
gr_dict['BinQ'] = set_GR_unif(pdict['bf'])
gr_dict['SFH'] = self.set_sfh_dist(pdict, self.sfh_type)
gr_dict['DM'] = SWDist(stats.norm(loc = pdict['dm'], scale = pdict['sig_dm']))

gr_dict['av'] = SWDist(stats.norm(loc = pdict['av'], scale = pdict['sig_av']))

intensity = 10**pdict['log_int']
nstars = int(stats.poisson.rvs(intensity))

mags_in, mags_out = self.get_cmd(nstars, gr_dict, pdict)
mags_in, mags_out, sdict = self.get_cmd(nstars, gr_dict, pdict)

cmd_in = self.make_cmd(mags_in)
cmd_out = self.make_cmd(mags_out)

return cmd_in, cmd_out
return cmd_in, cmd_out, sdict

def sample_norm_cmd(self, params, model):
"""
Expand All @@ -402,7 +417,7 @@ def sample_norm_cmd(self, params, model):
list
list of two arrays, one for the noiseless CMD and one for the noisy CMD, unit-scaled
"""
in_cmd, out_cmd = self.sample_cmd(params, model)
in_cmd, out_cmd, sdict = self.sample_cmd(params, model)
if len(in_cmd) == 0 or len(out_cmd) == 0:
print('empty cmd!')
return self.dummy_cmd, self.dummy_cmd
Expand Down