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