In [24]:

    

import numpy as np
import pprint
import matplotlib.pyplot as plt


    

In [2]:

    

%matplotlib


    

    




Using matplotlib backend: MacOSX

In [63]:

    

dtp = [('frac_followed', 'f128'), ('frac_observed', 'f128')\
       ,('frac_obs_unc', 'f128')]


    

In [64]:

    

Eff = np.loadtxt('Efficiency.txt',dtype = dtp, skiprows=1)
Purity = np.loadtxt('Purity.txt',dtype = dtp, skiprows=2)


    

In [134]:

    

#pprint.pprint(Eff)
plt.close('all')


    

In [109]:

    

i_x20 = np.argmin(abs(Eff['frac_followed']-0.2))
Eff[i_x20]


    

    
Out[109]:





(0.2014925330877304, 0.5611110925674438, 0.0582939051091671)

In [90]:

    

f0, [ax0,ax1] = plt.subplots(1,2, figsize = (12,6))

ax0.errorbar(Eff['frac_followed'],Eff['frac_observed'],yerr=Eff['frac_obs_unc'])


    

    
Out[90]:





<Container object of 3 artists>

In [3]:

    

import numpy as np
import pprint
import matplotlib.pyplot as plt
dtp = [('frac_followed', 'f128'), ('frac_observed', 'f128')\
       ,('frac_obs_unc', 'f128')]
Eff = np.loadtxt('Efficiency.txt',dtype = dtp, skiprows=1)
Purity = np.loadtxt('Purity.txt',dtype = dtp, skiprows=2)

f0, [ax0,ax1] = plt.subplots(1,2, figsize = (10,6) )
ax0.plot(Eff['frac_followed'],Eff['frac_observed'], color = 'k')
ax0.plot(Eff['frac_followed'],Eff['frac_observed']+Eff['frac_obs_unc'], color = '0.55')
ax0.plot(Eff['frac_followed'],Eff['frac_observed']-Eff['frac_obs_unc'], color = '0.55')
ax0.fill_between(Eff['frac_followed'],Eff['frac_observed']-Eff['frac_obs_unc'],Eff['frac_observed']+Eff['frac_obs_unc'],color ='0.75' )
ax0.set_xlim(-0.04,1.04)
ax0.set_xlabel('Fraction of GRBs Followed Up')
ax0.set_ylim(-0.04,1.04)
ax0.set_ylabel('Fraction of high (z>4)GRBs observed')
ax0.set_title('Efficiecy', fontdict=dict(size = 16))
ax0.set_aspect('equal')
ax0.annotate('Follow up 20% of\n bursts to capture ~55%\n of high-z events', xy = (0.2,0.55), \
             xytext = (0.43,0.15),arrowprops=dict(facecolor='black', width=0.8,\
             headwidth=7, shrink=0.08))
xRand = np.linspace(0,1,11)
yRand = xRand
ax0.plot(xRand,yRand,color = 'k')
x_20 = np.ones(11)*0.2
y_20 = np.linspace(0,0.55,11)
ax0.plot(x_20,y_20, color = 'k', linestyle = 'dotted', linewidth = 2)

ax0.annotate('Random \nguessing', xy = (0.8,0.8), xytext = (0.7,0.4), \
             arrowprops= dict(facecolor = 'black', width = 1.2,headwidth=7, shrink=0.08))




ax1.plot(Purity['frac_followed'],Purity['frac_observed'], color = 'k')
ax1.plot(Purity['frac_followed'],Purity['frac_observed']+Purity['frac_obs_unc'], color = '0.55')
ax1.plot(Purity['frac_followed'],Purity['frac_observed']-Purity['frac_obs_unc'], color = '0.55')
ax1.fill_between(Purity['frac_followed'],Purity['frac_observed']-Purity['frac_obs_unc'],Purity['frac_observed']+Purity['frac_obs_unc'],color ='0.75' )
ax1.set_xlim(-0.04,1.04)
ax1.set_xlabel('Fraction of GRBs Followed Up')
ax1.set_ylim(-0.04,1.04)
ax1.set_ylabel('Fraction of high (z>4)GRBs observed')
ax1.set_title('Purity', fontdict=dict(size = 16))
ax1.set_aspect('equal')
x_20_2 = np.ones(11)*0.2
y_20_2 = np.linspace(0,0.38,11)
ax1.plot(x_20_2, y_20_2, color = 'k', linestyle = 'dotted', linewidth = 2)
ax1.annotate('If 20% of events are\n followed up, ~40% of\n them will be high-z',\
             xy = (0.2, 0.4), xytext = (0,0.76), \
             arrowprops = dict(facecolor = 'black', width = 1.2,headwidth=7, shrink=0.08))
xRand_2 = np.linspace(0,1,11)
yRand_2 = np.ones(11)*18.0/135.0
ax1.plot(xRand_2,yRand_2,color = 'k')
ax1.annotate('Random\n guessing',xy = (0.6,0.133), xytext = (0.65,0.45),\
             arrowprops = dict(facecolor = 'black', width = 1.2,headwidth=7, shrink=0.08))
#plt.show()


    

    
Out[3]:





<matplotlib.text.Annotation at 0x10686b210>

In [112]:

    

print  np.ones(10)


    

    




[ 1.  1.  1.  1.  1.  1.  1.  1.  1.  1.]

In [129]:

    

ax0.set_title()


    

    
Out[129]:





0.13333333333333333

In [131]:

    

plt.setp(ax0)


    

    




  adjustable: [ 'box' | 'datalim' | 'box-forced']         
  agg_filter: unknown
  alpha: float (0.0 transparent through 1.0 opaque)         
  anchor: unknown
  animated: [True | False]         
  aspect: unknown
  autoscale_on: unknown
  autoscalex_on: unknown
  autoscaley_on: unknown
  axes: an :class:`~matplotlib.axes.Axes` instance         
  axes_locator: unknown
  axis_bgcolor: any matplotlib color - see         :func:`~matplotlib.pyplot.colors`         
  axis_off: unknown
  axis_on: unknown
  axisbelow: [ *True* | *False* ]         
  clip_box: a :class:`matplotlib.transforms.Bbox` instance         
  clip_on: [True | False]         
  clip_path: [ (:class:`~matplotlib.path.Path`,         :class:`~matplotlib.transforms.Transform`) |         :class:`~matplotlib.patches.Patch` | None ]         
  color_cycle: unknown
  contains: a callable function         
  cursor_props: a (*float*, *color*) tuple         
  figure: unknown
  frame_on: [ *True* | *False* ]         
  gid: an id string         
  label: string or anything printable with '%s' conversion.         
  lod: [True | False]         
  navigate: [ *True* | *False* ]         
  navigate_mode: unknown
  picker: [None|float|boolean|callable]         
  position: unknown
  rasterization_zorder: unknown
  rasterized: [True | False | None]         
  snap: unknown
  subplotspec: unknown
  title: str
  transform: :class:`~matplotlib.transforms.Transform` instance         
  url: a url string         
  visible: [True | False]         
  xbound: unknown
  xlabel: str
  xlim: length 2 sequence of floats         
  xmargin: unknown
  xscale: ['linear' | 'log' | 'symlog']
  xticklabels: sequence of strings
  xticks: sequence of floats         
  ybound: unknown
  ylabel: str
  ylim: length 2 sequence of floats         
  ymargin: unknown
  yscale: ['linear' | 'log' | 'symlog']
  yticklabels: sequence of strings
  yticks: sequence of floats
  zorder: any number         

In [76]:

    

plt.close('all')


    

In [42]:

    

ax0.fill_between(Eff['frac_followed'],Eff['frac_observed']-Eff['frac_obs_unc'],Eff['frac_observed']+Eff['frac_obs_unc'],color = '0.75')


    

    
Out[42]:





<matplotlib.collections.PolyCollection at 0x106865390>

In [44]:

    

ax0.fill_between?


    

In [ ]: