def beta_model_likelihood(r, data, data_err, beta_pars):
"""
Likelihood function for the beta model fitting
Arguments:
- `r`: radius
- `data`: curve (surface brightnes) -> data
- `data_err`: error on curve (surface brightnes) -> data
- 'beta_pars: list of beta mode parameters = [norm, rcore, beta]'
"""
from sb_utils import beta_model
model = beta_model(beta_pars, r)
l = sum(((data-model)/data_err)**2.0)
return l
def plot_sb_fit(r, c1, c1_err, beta_pars, fname):
"""
Surface brightness log-log plot with overplotted betamodel
Arguments:
- `r`: radius
- `c1 + c1_err`: curve 1 (source)
- 'beta_pars: list of beta mode parameters = [norm, rcore, beta]'
- 'fname' : figure name
"""
from sb_utils import beta_model
######################################################################
# start plot enviroment
######################################################################
# start figure
rc('axes', linewidth=1.5)
fig_obj = plt.figure()
fig_name=fname
headline_text = fig_obj.text(0.5, 0.95, '',
horizontalalignment='center',
fontproperties=matplotlib.font_manager.FontProperties(size=16))
ax1 = fig_obj.add_subplot(111) # rows/cols/num of plot
plt.subplots_adjust(hspace=0.2, wspace=0.2) # hdefault 0.2, 0.001 for touching
ymin = min(c1[where(c1>0.0)])/2.0
######################################################################
# plot data sets
plt.errorbar(r, c1, [(c1-c1_err<=0.0).choose(c1_err, c1-ymin), c1_err],
color='black',
linestyle='', # -/--/-./:
linewidth=1, # linewidth=1
marker='o', # ./o/*/+/x/^/</>/v/s/p/h/H
markerfacecolor='black',
markersize=6, # markersize=6
label=r"data" # '__nolegend__'
)
beta_mod = beta_model(beta_pars, r)
plt.plot(r, beta_mod,
color='black',
linestyle='-', # -/--/-./:
linewidth=1, # linewidth=1
marker='', # ./o/*/+/x/^/</>/v/s/p/h/H
markerfacecolor='black',
markersize=0, # markersize=6
label=r"model" # '__nolegend__'
)
######################################################################
# subplot data sets
ax1.set_xscale('log') # ['linear' | 'log' | 'symlog']
ax1.set_yscale('log') # ['linear' | 'log' | 'symlog']
# ax1.set_xlim(xmin=20.0,xmax=50.0)
ax1.set_ylim(ymin=ymin)
# subplot text sets
# ax1.set_title('plot title', fontsize=16, fontweight="bold") # fontsize=16
ax1.set_xlabel('r [arcsec]', fontsize=14, fontweight="bold") # fontsize=12
ax1.set_ylabel('surface brightness [cts/s/pix]', fontsize=14, fontweight="heavy") # fontsize=12
# legend
prop = matplotlib.font_manager.FontProperties(size=16) # size=16
ax1.legend(loc=0, prop=prop, numpoints=1)
# x - axis tick labels
for label in ax1.xaxis.get_ticklabels():
label.set_color('black')
label.set_rotation(0) # default = 0
label.set_fontsize(14) # default = 12
label.set_fontweight("normal") # [ 'normal' | 'normal' | 'heavy' | 'light' | 'ultranormal' | 'ultralight']
# y - axis tick labels
for label in ax1.yaxis.get_ticklabels():
label.set_color('black')
label.set_rotation(0) # default = 0
label.set_fontsize(14) # default = 12
label.set_fontweight("normal") # [ 'normal' | 'normal' | 'heavy' | 'light' | 'ultranormal' | 'ultralight']
# save figure
plt.savefig(fig_name)