#Falk wants to have not only the CNO isotopes
#in the paper but also the elements; here you can choose both


import nugrid_set as set

cycles=20*[[1,-1,200]]
dum_iso_num=5000


import sys
sys.setrecursionlimit(50000)


mesaonly=True
mcut='fryer'
###the option mcut='ye' needs changes below, because of different save dir
exp_type='delay'
isotopes=True #isotopes or elements? also adapt iso or ele arrays below
plot_log=True

color=['r','b','g','k']
marker_type=['o','p','s','D']
line_style=['--','-','-.',':']

xmin=1
xmax=25

if isotopes==True:
	isotopes=['allstable']
	elements=[]
else:
	elements=['allstable']
	isotopes=[]

isotopes=["C-12","N-14","O-16"] 
#elements=["C","N","O"]
wind_only=False
pre_exp=False
exp_only=False

path='/apod2/NuGrid/data/set1ext/'
###############set1.2 mesa

expdir=path+'/set1.2/ppd_exp/'
setdir=path+'/set1.2/ppd_wind/'

setse=set.mppnp_set(rundir=setdir)

if mcut == 'ye':
        fallback_masses=[12,15,20,25];fallback_coords=[2.07,4.3,6.46,8.9]
else:
        fallback_masses=[];fallback_coords=[]

setse.get_stellar_ejecta(cycles=cycles,isotopes=isotopes,elements=elements,yields_output=False,GCE_tables=False,plots=True,exp_dir=expdir,exp_type=exp_type,pre_exp=pre_exp,exp_only=exp_only,wind_only=wind_only,plot_log=plot_log,color=dum_iso_num*['r'],marker_type=dum_iso_num*['o'],line_style=dum_iso_num*['--'],markersize=dum_iso_num*[8],line_width=dum_iso_num*[8],title='',label='',withlabel=True)

####################set1.1 mesa

expdir=path+'/set1.1/ppd_exp/'
setdir=path+'/set1.1/ppd_wind/'


setse=set.mppnp_set(rundir=setdir)

if  mcut == 'ye':
        fallback_masses=[12,15,20,25];fallback_coords=[2.12,3.12,4.97,2.6]
else:
        fallback_masses=[];fallback_coords=[]

setse.get_stellar_ejecta(cycles=cycles,isotopes=isotopes,elements=elements,yields_output=False,GCE_tables=False,plots=True,exp_dir=expdir,exp_type=exp_type,pre_exp=pre_exp,exp_only=exp_only,wind_only=wind_only,plot_log=plot_log,color=dum_iso_num*['b'],marker_type=dum_iso_num*['p'],line_style=dum_iso_num*['-'],markersize=dum_iso_num*[8],line_width=dum_iso_num*[8],title='',label='',withlabel=True)

####################set1.3a

expdir=path+'/set1.3a/ppd_exp/'
setdir=path+'/set1.3a/ppd_wind/'


setse=set.mppnp_set(rundir=setdir)

if  mcut == 'ye':
        fallback_masses=[12,15,20,25];fallback_coords=[1.71,2.01,2.55,1.99]
else:
        fallback_masses=[];fallback_coords=[]

setse.get_stellar_ejecta(cycles=cycles,isotopes=isotopes,elements=elements,yields_output=False,GCE_tables=False,plots=True,exp_dir=expdir,exp_type=exp_type,pre_exp=pre_exp,exp_only=exp_only,wind_only=wind_only,plot_log=plot_log,color=dum_iso_num*['g'],marker_type=dum_iso_num*['s'],line_style=dum_iso_num*['-.'],markersize=dum_iso_num*[8],line_width=dum_iso_num*[8],title='',label='',withlabel=True)

####################set1.4a

expdir=path+'/set1.4a/ppd_exp/'
setdir=path+'/set1.4a/ppd_wind/'


setse=set.mppnp_set(rundir=setdir)

if  mcut == 'ye':
        fallback_masses=[12,15,20,25];fallback_coords=[1.71,1.79,2.39,2.02]
else:
        fallback_masses=[];fallback_coords=[]

setse.get_stellar_ejecta(cycles=cycles,isotopes=isotopes,elements=elements,yields_output=False,GCE_tables=False,plots=True,exp_dir=expdir,exp_type=exp_type,pre_exp=pre_exp,exp_only=exp_only,wind_only=wind_only,plot_log=plot_log,color=dum_iso_num*['k'],marker_type=dum_iso_num*['D'],line_style=dum_iso_num*[':'],markersize=dum_iso_num*[8],line_width=dum_iso_num*[8],title='',label='',withlabel=True)

####################set1.5a

expdir=path+'/set1.5a/ppd_exp/'
setdir=path+'/set1.5a/ppd_wind/'

setse=set.mppnp_set(rundir=setdir)

if  mcut == 'ye':
        fallback_masses=[12,15,20,25];fallback_coords=[1.71,1.79,2.39,2.02]
else:
        fallback_masses=[];fallback_coords=[]

setse.get_stellar_ejecta(cycles=cycles,isotopes=isotopes,elements=elements,yields_output=False,GCE_tables=False,plots=True,exp_dir=expdir,exp_type=exp_type,pre_exp=pre_exp,exp_only=exp_only,wind_only=wind_only,plot_log=plot_log,color=dum_iso_num*['m'],marker_type=dum_iso_num*['v'],line_style=dum_iso_num*['--'],markersize=dum_iso_num*[8],line_width=dum_iso_num*[8],title='',label='',withlabel=True)



##################### Plotting

figures=[manager.canvas.figure for manager in matplotlib._pylab_helpers.Gcf.get_all_fig_managers()]
print 'calculatoin done'
print 'Save figures...'

props = dict(boxstyle='square', facecolor='w', alpha=1)
i=0
for fig in figures:
	if not i==0:
		plt.legend().set_visible(False)
	i=i+1
        isotope=fig.get_label()
        name=isotope+"_prodfac"
        fig=plt.figure(isotope);
        ax = fig.add_subplot(111)
        ax.text(0.85, 0.92, isotope, transform=ax.transAxes, fontsize=16,verticalalignment='top', bbox=props)
        plt.xlim(xmin,xmax)
	#fig.set_size_inches(18.5,10.5)
	#plt.show()
        plt.xscale('log')
        plt.ylabel('Overproduction factor')
	if isotope == 'C-12':
		plt.ylim(5e-2,1e4)
		plt.legend().set_visible(False)
		plt.savefig('C-12_prodfac_zdep.png')
	elif isotope == 'N-14':
		plt.legend().set_visible(False)
		plt.ylim(5e-1,1e4)
		plt.savefig('N-14_prodfac_zdep.png')
	else:
		plt.legend(loc=2,fontsize=15)
		plt.ylim(1e-1,1e4)
		plt.savefig('O-16_prodfac_zdep.png')