def run(self):
coords = self.opts.coords
names = vars(self.opts).get('names', len(coords) * [''])
labels = [
n.lower().replace(' ', '_').replace('(', '').replace(')', '')
for n in names
]
for name, label, coord in zip(names, labels, coords):
glon, glat = coord[0], coord[1]
print('\t', name, '(%.2f,%.2f)' % (glon, glat))
fig, ax = plt.subplots(1, 1, figsize=(8, 8))
plotter = ugali.utils.plotting.BasePlotter(glon,
glat,
self.config,
radius=0.5)
plotter.image_kwargs.update(opt='GL', xsize=800)
plotter.drawImage(ax, invert=False)
fig.suptitle(label)
outfile = '%s_sdss_image.png' % label
plt.savefig(outfile, dpi=200)
Pipeline.run = run
pipeline = Pipeline(description, components)
pipeline.parser.add_coords(radius=True, targets=True, required=True)
pipeline.parse_args()
pipeline.execute()
outfile = join(self.outdir, base)
out = open(outfile, 'w')
out.write(yaml.dump(output))
out.close()
if 'scan' in self.opts.run:
logger.info("Running 'scan'...")
for config, name, label, coord in args:
logdir = mkdir('plots/log')
logfile = join(logdir, '%s_lnlscan.log')
cmd = 'python lnlscan.py %s --name %s --xpar %s --xbins 45 --ypar %s --ybins 45' % (
self.opts.config, name, 'age', 'metallicity')
self.batch.submit(cmd, logfile=logfile)
cmd = 'python lnlscan.py %s --name %s --xpar %s --xbins 45 --ypar %s --ybins 45' % (
self.opts.config, name, 'metallicity', 'distance_modulus')
self.batch.submit(cmd, logfile=logfile)
cmd = 'python lnlscan.py %s --name %s --xpar %s --xbins 45 --ypar %s --ybins 45' % (
self.opts.config, name, 'age', 'distance_modulus')
self.batch.submit(cmd, logfile=logfile)
Pipeline.run = run
pipeline = Pipeline(__doc__, components)
pipeline.parser.add_coords(radius=True, targets=True)
pipeline.parser.add_ncores()
pipeline.parse_args()
pipeline.execute()
#idx=np.random.randint(len(data['ts'])-1,size=400)
#idx=slice(400)
#ugali.utils.plotting.plotChernoff(data['ts'][idx])
#ugali.utils.plotting.plotChernoff(data['fit_ts'])
plt.ion()
"""
try:
fig = plt.figure()
x = range(len(data))
y = data['fit_mass']/data['stellar_mass']
yclip,lo,hi = scipy.stats.sigmaclip(y)
yerr = data['fit_mass_err']/data['stellar_mass']
plt.errorbar(x,y,yerr=yerr,fmt='o',c='k')
plt.axhline(1,ls='--',c='gray',lw=2)
plt.axhline(np.mean(yclip),ls='--',c='r',lw=2)
plt.ylim(lo,hi)
plt.ylabel("Best-Fit Mass Residual")
plt.xlabel("Simulation Number")
except:
pass
"""
Pipeline.run = run
pipeline = Pipeline(__doc__,components)
pipeline.parser.add_argument('-n','--num',default=None,type=int)
pipeline.parse_args()
pipeline.execute()
import pylab as plt