bigfile_fits = cat.bigfile_fits
psrlist = cat.get_off_peak_psrlist()
Edot=np.empty_like(psrlist,dtype=float)
age=np.empty_like(psrlist,dtype=float)
classification=np.empty_like(psrlist,dtype=object)
has_distance=np.empty_like(psrlist,dtype=bool)
distance=np.empty_like(psrlist,dtype=float)
for i,psr in enumerate(psrlist):
Edot[i]=cat.get_edot(psr)
age[i]=cat.get_age(psr)
classification[i] = cat.get_off_peak_classification(psr)
d=cat.get_distance(psr)
if d[0] == '<':
has_distance[i] = False
else:
distance[i] = float(d)
has_distance[i] = True
blue = 'blue' if not bw else 'grey'
red = 'red' if not bw else 'grey'
def plot(cut, **kwargs):
axes.plot(age[cut],Edot[cut]/distance[cut]**2,'.', **kwargs)
