Alexander Ziegler / ctools

Commit e69cd7444bfc8da7b010647b7f56de10a8493cc2

Authored by Jürgen Knödlseder
1 parent 89694521

Add script to show CTA responses using standard interfaces.

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Showing 1 changed file with 292 additions and 0 deletions
examples/show_response.py 0 → 100755
  View file @e69cd74
  1 +#! /usr/bin/env python
  2 +# ==========================================================================
  3 +# This script displays one or several CTA response functions.
  4 +#
  5 +# Required 3rd party modules:
  6 +# - matplotlib
  7 +# - numpy
  8 +#
  9 +# Copyright (C) 2014 Juergen Knoedlseder
  10 +#
  11 +# This program is free software: you can redistribute it and/or modify
  12 +# it under the terms of the GNU General Public License as published by
  13 +# the Free Software Foundation, either version 3 of the License, or
  14 +# (at your option) any later version.
  15 +#
  16 +# This program is distributed in the hope that it will be useful,
  17 +# but WITHOUT ANY WARRANTY; without even the implied warranty of
  18 +# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
  19 +# GNU General Public License for more details.
  20 +#
  21 +# You should have received a copy of the GNU General Public License
  22 +# along with this program. If not, see <http://www.gnu.org/licenses/>.
  23 +#
  24 +# ==========================================================================
  25 +import sys
  26 +import math
  27 +import gammalib
  28 +import matplotlib.pyplot as plt
  29 +
  30 +
  31 +# ================================== #
  32 +# Compute Eq. (17) of Li & Ma (1983) #
  33 +# ================================== #
  34 +def sigma_lima(Non, Noff, alpha=0.2):
  35 + """
  36 + Compute Eq. (17) of Li & Ma (1983).
  37 +
  38 + Parameters:
  39 + Non - Number of on counts
  40 + Noff - Number of off counts
  41 + Keywords:
  42 + alpha - Ratio of on-to-off exposure
  43 + """
  44 + # Compute sensitivity
  45 + alpha1 = alpha + 1.0
  46 + sum = Non + Noff
  47 + arg1 = Non / sum
  48 + arg2 = Noff / sum
  49 + term1 = Non * math.log((alpha1/alpha)*arg1)
  50 + term2 = Noff * math.log(alpha1*arg2)
  51 + sigma = math.sqrt(2.0 * (term1 + term2))
  52 +
  53 + # Return sensitivity
  54 + return sigma
  55 +
  56 +
  57 +# ======================================== #
  58 +# Solve Eq. (17) of Li & Ma (1983) for Non #
  59 +# ======================================== #
  60 +def Non_lima(sigma, Noff, alpha=0.2):
  61 + """
  62 + Solve Eq. (17) of Li & Ma (1983) for Non
  63 +
  64 + Parameters:
  65 + sigma - Required significance
  66 + Noff - Number of off counts
  67 + Keywords:
  68 + alpha - Ratio of on-to-off exposure
  69 + """
  70 + # Set initial guess for Non
  71 + S = 25.0
  72 + Non = S + alpha*Noff
  73 +
  74 + # Compute initial sigma estimate
  75 + s = sigma_lima(Non, Noff, alpha=alpha)
  76 + delta = s - sigma
  77 +
  78 + # Iterate
  79 + while abs(delta) > 1.0e-6:
  80 + S *= sigma/s
  81 + Non = S + alpha*Noff
  82 + s = sigma_lima(Non, Noff, alpha=alpha)
  83 + delta = s - sigma
  84 +
  85 + # Return
  86 + return Non
  87 +
  88 +
  89 +# ======================= #
  90 +# Show one effective area #
  91 +# ======================= #
  92 +def show_one_effective_area(rsp, name, color="r"):
  93 + """
  94 + Show one effective area.
  95 + """
  96 + # Set to figure 1
  97 + plt.figure(1)
  98 +
  99 + # Generate logE(TeV) vector
  100 + nbins = 20
  101 + logE = [-1.7+0.2*i for i in range(nbins)]
  102 + E = [math.pow(10.0, e) for e in logE]
  103 +
  104 + # Generate effective area vector
  105 + aeff = [0.0 for i in range(nbins)]
  106 + for i in range(nbins):
  107 + aeff[i] = rsp.aeff()(logE[i])
  108 +
  109 + # Plot data
  110 + plt.loglog(E, aeff, color+'-', label=name)
  111 + plt.loglog(E, aeff, color+'o')
  112 +
  113 + # Set axes
  114 + plt.xlabel("Energy [TeV]")
  115 + plt.ylabel("Effective area [cm2]")
  116 +
  117 + # Set legend
  118 + plt.legend(loc="lower right")
  119 +
  120 + # Return
  121 + return
  122 +
  123 +
  124 +# ======================== #
  125 +# Show one background rate #
  126 +# ======================== #
  127 +def show_one_background_rate(rsp, name, color="r"):
  128 + """
  129 + Show one background rate.
  130 + """
  131 + # Set to figure 2
  132 + plt.figure(2)
  133 +
  134 + # Generate logE(TeV) vector
  135 + nbins = 20
  136 + logE = [-1.7+0.2*i for i in range(nbins)]
  137 + E = [math.pow(10.0, e) for e in logE]
  138 +
  139 + # Generate on-axis background rate vector
  140 + bgrate = [0.0 for i in range(nbins)]
  141 + for i in range(nbins):
  142 + bgrate[i] = rsp.background()(logE[i], 0.0, 0.0)
  143 + if bgrate[i] < 1.0e-10:
  144 + bgrate[i] = 0.0
  145 +
  146 + # Plot data
  147 + plt.loglog(E, bgrate, color+'-', label=name)
  148 + plt.loglog(E, bgrate, color+'o')
  149 +
  150 + # Set axes
  151 + plt.xlabel("Energy [TeV]")
  152 + plt.ylabel("Background rate [events/s/MeV/sr]")
  153 +
  154 + # Set legend
  155 + plt.legend(loc="lower left")
  156 +
  157 + # Return
  158 + return
  159 +
  160 +
  161 +# ==================== #
  162 +# Show one sensitivity #
  163 +# ==================== #
  164 +def show_one_sensitivity(rsp, name, color="r", duration=180000.0, alpha=0.2, sigma=5.0):
  165 + """
  166 + Show one sensitivity.
  167 + """
  168 + # Set constants
  169 + r68_to_sigma = 0.6624305
  170 +
  171 + # Set to figure 3
  172 + plt.figure(3)
  173 +
  174 + # Generate logE(TeV) vector
  175 + nbins = 20
  176 + logE = [-1.7+0.2*i for i in range(nbins)]
  177 + E = [math.pow(10.0, e) for e in logE]
  178 +
  179 + # Generate sensitivity vector
  180 + flux = [0.0 for i in range(nbins)]
  181 + for i in range(nbins):
  182 + ewidth = (math.pow(10.0, logE[i]+0.1) - \
  183 + math.pow(10.0, logE[i]-0.1))*1.0e6
  184 + aeff = rsp.aeff()(logE[i])
  185 + r68 = rsp.psf().delta_max(logE[i]) / 5.0 / r68_to_sigma
  186 + solidangle = gammalib.twopi * (1.0 - math.cos(r68))
  187 + bgd_counts = rsp.background()(logE[i], 0.0, 0.0) * duration * ewidth * solidangle
  188 + Noff = bgd_counts/alpha
  189 + if Noff > 0:
  190 + Non = Non_lima(sigma, Noff)
  191 + src_counts = Non - bgd_counts
  192 + flux[i] = src_counts / (aeff * duration) * E[i]*1.0e6 * gammalib.MeV2erg
  193 +
  194 + # Plot data
  195 + plt.loglog(E, flux, color+'-', label=name)
  196 + plt.loglog(E, flux, color+'o')
  197 +
  198 + # Set axes
  199 + plt.xlabel("Energy [TeV]")
  200 + plt.ylabel("Sensitivity [erg/cm2/s]")
  201 +
  202 + # Set legend
  203 + plt.legend(loc="upper right")
  204 +
  205 + # Return
  206 + return
  207 +
  208 +
  209 +# ==================== #
  210 +# Show one sensitivity #
  211 +# ==================== #
  212 +def show_one_response(rspname, dbname, name, color="r"):
  213 + """
  214 + Show one response.
  215 + """
  216 + # Set-up calibration database
  217 + caldb = gammalib.GCaldb()
  218 + if gammalib.dir_exists(dbname):
  219 + caldb.rootdir(dbname)
  220 + else:
  221 + caldb.open("cta", dbname)
  222 +
  223 + # Load response function
  224 + rsp = gammalib.GCTAResponse(rspname, caldb)
  225 +
  226 + # Show effective area
  227 + show_one_effective_area(rsp, name, color=color)
  228 +
  229 + # Show background rate
  230 + show_one_background_rate(rsp, name, color=color)
  231 +
  232 + # Show sensitivity
  233 + show_one_sensitivity(rsp, name, color=color)
  234 +
  235 + # Return
  236 + return
  237 +
  238 +
  239 +# ======================== #
  240 +# Main routine entry point #
  241 +# ======================== #
  242 +if __name__ == '__main__':
  243 + """
  244 + Display spectrum in PHA format.
  245 + """
  246 + # Print usage information
  247 + #usage = "Usage: show_pha filename" \
  248 + # " [-n bins] [-c column] [-t title] [-p plot]"
  249 + #if len(sys.argv) < 2:
  250 + # print(usage)
  251 + # sys.exit()
  252 +
  253 + # Extract parameters
  254 + #filename = sys.argv[1]
  255 +
  256 + # Create figures
  257 + plt.figure(1)
  258 + plt.title("Effective area")
  259 + plt.figure(2)
  260 + plt.title("Background rate")
  261 +
  262 + # Set response dictionary
  263 + rsps = [
  264 + {'dbname': "/usr/local/gamma/share/caldb/data/cta/dummy", \
  265 + 'rspname': "cta_dummy_irf", \
  266 + 'name': "Prod1 (Array E, MPIK)", \
  267 + 'color': "b"}, \
  268 + {'dbname': "e", \
  269 + 'rspname': "IFAE20120510_50h", \
  270 + 'name': "Prod1 (Array E, IFAE)", \
  271 + 'color': "g"}, \
  272 + {'dbname': "aar", \
  273 + 'rspname': "DESY20140105_50h", \
  274 + 'name': "Prod2 (Aar, DESY)", \
  275 + 'color': "r"} \
  276 + ]
  277 +
  278 + # Loop over all responses
  279 + for rsp in rsps:
  280 +
  281 + # Get attributes
  282 + dbname = rsp['dbname']
  283 + rspname = rsp['rspname']
  284 + color = rsp['color']
  285 + name = rsp['name']
  286 +
  287 + # Show response
  288 + show_one_response(rspname, dbname, name, color=color)
  289 +
  290 + # Show plot
  291 + plt.show()
  292 +
0 293 \ No newline at end of file
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