class NOMADDataStore(DataStore):
"""
Data store for the NOMAD database
"""
def __init__(self):
"""@todo: to be defined """
super(NOMADDataStore, self).__init__()
self.parser = NOMADFieldsParser()
def fetch(self):
self.data = self.parser.getTable("/fields", "field%d" % self.currentField).cols.vmagnitude[:]
self.data = self.data[self.data != 0]
def __init__(self, args):
"""
Constructor, sets up variables
"""
super(App, self).__init__()
self.args = args
self.parser = NOMADFieldsParser()
self.colours = ['r', 'k', 'b']
# list of field centres
self.FieldCentre = FieldCentre
# NGTS instrument field of view
'''
Match the radius of search to the fov by equating areas
\pi r^2 = x y
r = sqrt(x * y / pi)
'''
npix = NAXIS1
pixscale = PixScale
# get the dimensions in arcminutes
x = npix * pixscale / 60.
y = npix * pixscale / 60.
self.radius = np.sqrt(x*y/np.pi)
print "Searching within a radius of %f degrees, total area: %f sq degrees" % (
self.radius / 60.,
np.pi * (self.radius / 60.)**2,
)
# set up the exposure time array
self.exptime = np.linspace(np.log10(5.), np.log10(3600.), 100)
# load the fits
fits = cPickle.load(open("fits.cpickle"))
self.brightFit = fits['bright']
self.darkFit = fits['dark']
# saturation levels
self.brightSaturLevel = self.brightFit(self.exptime)
self.darkSaturLevel = self.darkFit(self.exptime)
# plotting variables
self.xmin = self.exptime.min()
self.xmax = self.exptime.max()
class App(object):
"""
Main application object
"""
def __init__(self, args):
"""
Constructor, sets up variables
"""
super(App, self).__init__()
self.args = args
self.parser = NOMADFieldsParser()
self.colours = ['r', 'k', 'b']
# list of field centres
self.FieldCentre = FieldCentre
# NGTS instrument field of view
'''
Match the radius of search to the fov by equating areas
\pi r^2 = x y
r = sqrt(x * y / pi)
'''
npix = NAXIS1
pixscale = PixScale
# get the dimensions in arcminutes
x = npix * pixscale / 60.
y = npix * pixscale / 60.
self.radius = np.sqrt(x*y/np.pi)
print "Searching within a radius of %f degrees, total area: %f sq degrees" % (
self.radius / 60.,
np.pi * (self.radius / 60.)**2,
)
# set up the exposure time array
self.exptime = np.linspace(np.log10(5.), np.log10(3600.), 100)
# load the fits
fits = cPickle.load(open("fits.cpickle"))
self.brightFit = fits['bright']
self.darkFit = fits['dark']
# saturation levels
self.brightSaturLevel = self.brightFit(self.exptime)
self.darkSaturLevel = self.darkFit(self.exptime)
# plotting variables
self.xmin = self.exptime.min()
self.xmax = self.exptime.max()
def GetCatalogueData(self, field_id):
table_name = 'field{:d}'.format(field_id)
table = self.parser.getTable('/fields', table_name)
vmags = table.cols.vmagnitude[:]
return vmags[vmags > 0]
def run(self):
fig = plt.figure()
ax = fig.add_subplot(111)
for i, field in enumerate(self.FieldCentre):
print "Analysing field %d,%d" % (field[0], field[1])
galcoords = j20002gal(field[0], field[1])
# Fetch the list of objects
mags = self.GetCatalogueData(i + 1)
print "%d objects returned" % (mags.size,)
# Get the number of saturated stars
# Normalise to make fraction
brightNumbers = np.array([mags[mags<level].size for level in self.brightSaturLevel])
darkNumbers = np.array([mags[mags<level].size for level in self.darkSaturLevel])
if self.args.fraction:
brightNumbers = brightNumbers / float(mags.size)
darkNumbers = darkNumbers / float(mags.size)
ax.plot(10 ** self.exptime, brightNumbers, ls='--',
color=self.colours[i])
ax.plot(10 ** self.exptime, darkNumbers, ls='-',
color=self.colours[i])
ax.set_xscale('log')
if self.args.fraction:
ax.set_ylim(0, 1.1)
ax.xaxis.set_major_formatter(plt.ScalarFormatter())
ax.set_xlim(xmax=3400)
ax.set_xlabel(r'Exposure time / s')
if self.args.fraction:
ax.set_ylabel(r'Saturated stars fraction')
else:
ax.set_ylabel(r'Saturated stars')
plt.show()
def __init__(self):
"""@todo: to be defined """
super(NOMADDataStore, self).__init__()
self.parser = NOMADFieldsParser()
