import pylab as P
import numpy as np
from lande.utilities.plotting import plot_points
from lande.utilities import pubplot
from lande.fermi.pipeline.pwncat2.interp.bigfile import PulsarCatalogLoader
pubplot.set_latex_defaults()
bw = pubplot.get_bw()
cat=PulsarCatalogLoader(
bigfile_filename='$lat2pc/BigFile/Pulsars_BigFile_v20130214170325.fits',
off_peak_auxiliary_filename='$lat2pc/OffPeak/auxiliary/off_peak_auxiliary_table.fits')
psrlist = cat.get_off_peak_psrlist()
fig = P.figure(None,(6,6))
axes = fig.add_subplot(111)
axes.set_xscale("log")
axes.set_yscale("log")
classification=np.empty_like(psrlist,dtype=object)
Edot=np.empty_like(psrlist,dtype=float)
luminosity=np.empty_like(psrlist,dtype=float)
luminosity_error_statistical=np.empty_like(psrlist,dtype=float)
luminosity_lower_error_systematic=np.empty_like(psrlist,dtype=float)
from os.path import join, expandvars
import matplotlib.font_manager
from matplotlib.ticker import MaxNLocator
import numpy as np
import h5py
import pylab as P
from matplotlib.lines import Line2D
from lande.utilities.pubplot import set_latex_defaults,get_bw,save
from lande.utilities.plotting import label_axes
set_latex_defaults()
bw=get_bw()
merged = expandvars(join('$w44simdata/','v33', 'merged.hdf5'))
results = h5py.File(merged, 'r')
ts_point = np.asarray(results['TS_Point'])
ll_point = np.asarray(results['ll_Point'])
ll_gaussian = np.asarray(results['ll_Gaussian'])
ll_disk = np.asarray(results['ll_Disk'])
ll_elliptical_disk = np.asarray(results['ll_EllipticalDisk'])
ll_elliptical_ring = np.asarray(results['ll_EllipticalRing'])
fig=P.figure(None, figsize=(6,6))
def histogram(axes, data,**kwargs):
bins = 30
