Lili Yang / gammalib

Commit ddd8c148bb4b883264e7f2e41cb58d0683d285c7

Authored by Jürgen Knödlseder
1 parent e3348b38

Adapt script to actual GammaLib interface

Inline Side-by-side
Showing 8 changed files with 85 additions and 63 deletions
inst/cta/test/benchmark_irf_computation.py
  View file @ddd8c14
... ... @@ -6,7 +6,7 @@
6 6 # Monte-Carlo simulations. This script is used to validate the absolute
7 7 # normalization of the CTA response computations.
8 8 #
9   -# Copyright (C) 2014 Juergen Knoedlseder
  9 +# Copyright (C) 2014-2015 Juergen Knoedlseder
10 10 #
11 11 # This program is free software: you can redistribute it and/or modify
12 12 # it under the terms of the GNU General Public License as published by
... ... @@ -117,7 +117,7 @@ def binned_irf(model, cntmap, irf, caldb, cntref):
117 117 # =========================== #
118 118 # CTA stacked IRF computation #
119 119 # =========================== #
120   -def stacked_irf(model, cntmap, expcube, psfcube, cntref):
  120 +def stacked_irf(model, cntmap, expcube, psfcube, bkgcube, cntref):
121 121 """
122 122 Perform stacked IRF computation.
123 123 """
... ... @@ -132,9 +132,10 @@ def stacked_irf(model, cntmap, expcube, psfcube, cntref):
132 132 obs.load(cntmap)
133 133  
134 134 # Specify response for CTA observation
135   - exposure = gammalib.GCTACubeExposure(expcube)
136   - psf = gammalib.GCTACubePsf(psfcube)
137   - obs.response(exposure, psf)
  135 + exposure = gammalib.GCTACubeExposure(expcube)
  136 + psf = gammalib.GCTACubePsf(psfcube)
  137 + background = gammalib.GCTACubeBackground(bkgcube)
  138 + obs.response(exposure, psf, background)
138 139  
139 140 # Load model to describe the data from XML file
140 141 models = gammalib.GModels(model)
... ... @@ -179,6 +180,7 @@ if __name__ == '__main__':
179 180 caldb = "../caldb"
180 181 expcube = "data/expcube.fits"
181 182 psfcube = "data/psfcube.fits"
  183 + bkgcube = "data/bkgcube.fits"
182 184  
183 185 # Set tests
184 186 tests = ["point", "disk", "gauss", "shell", "ellipse", "diffuse"]
... ... @@ -235,4 +237,4 @@ if __name__ == '__main__':
235 237 binned_irf(model, cntmap, irf, gammalib.GCaldb(caldb), cntref)
236 238  
237 239 # Perform stacked computation
238   - stacked_irf(model, cntmap, expcube, psfcube, cntref)
  240 + stacked_irf(model, cntmap, expcube, psfcube, bkgcube, cntref)
... ...
inst/cta/test/benchmark_ml_fitting.py
  View file @ddd8c14
... ... @@ -3,7 +3,7 @@
3 3 # This script performs a benchmark for maximum likelihood fitting of CTA
4 4 # data.
5 5 #
6   -# Copyright (C) 2012-2014 Juergen Knoedlseder
  6 +# Copyright (C) 2012-2015 Juergen Knoedlseder
7 7 #
8 8 # This program is free software: you can redistribute it and/or modify
9 9 # it under the terms of the GNU General Public License as published by
... ... @@ -142,7 +142,7 @@ def binned_analysis(model, cntmap, irf, caldb):
142 142 # ==================== #
143 143 # CTA stacked analysis #
144 144 # ==================== #
145   -def stacked_analysis(model, cntmap, expcube, psfcube):
  145 +def stacked_analysis(model, cntmap, expcube, psfcube, bkgcube):
146 146 """
147 147 Perform stacked maximum likelihood fitting of CTA data using GammaLib
148 148 classes.
... ... @@ -166,9 +166,10 @@ def stacked_analysis(model, cntmap, expcube, psfcube):
166 166 cta_obs.load(cntmap)
167 167  
168 168 # Specify response for CTA observation
169   - exposure = gammalib.GCTACubeExposure(expcube)
170   - psf = gammalib.GCTACubePsf(psfcube)
171   - cta_obs.response(exposure, psf)
  169 + exposure = gammalib.GCTACubeExposure(expcube)
  170 + psf = gammalib.GCTACubePsf(psfcube)
  171 + background = gammalib.GCTACubeBackground(bkgcube)
  172 + cta_obs.response(exposure, psf, background)
172 173  
173 174 # Append CTA observation to observation container
174 175 obs.append(cta_obs)
... ... @@ -217,6 +218,7 @@ if __name__ == '__main__':
217 218 caldb = "../caldb"
218 219 expcube = "data/expcube.fits"
219 220 psfcube = "data/psfcube.fits"
  221 + bkgcube = "data/bkgcube.fits"
220 222  
221 223 # Set tests
222 224 tests = ["point", "disk", "gauss", "shell", "ellipse", "diffuse"]
... ... @@ -273,4 +275,4 @@ if __name__ == '__main__':
273 275 binned_analysis(model, cntmap, irf, gammalib.GCaldb(caldb))
274 276  
275 277 # Perform stacked analysis
276   - stacked_analysis(model, cntmap, expcube, psfcube)
  278 + stacked_analysis(model, cntmap, expcube, psfcube, bkgcube)
... ...
inst/cta/test/example_binned_ml_fit.py
  View file @ddd8c14
... ... @@ -115,7 +115,7 @@ def binned_analysis(model, cntmap, irf, caldb):
115 115 # ==================== #
116 116 # CTA stacked analysis #
117 117 # ==================== #
118   -def stacked_analysis(model, cntmap, expcube, psfcube):
  118 +def stacked_analysis(model, cntmap, expcube, psfcube, bkgcube):
119 119 """
120 120 Perform stacked maximum likelihood fitting of CTA data using GammaLib
121 121 classes. The function performs two fits, one with the full model and
... ... @@ -141,9 +141,10 @@ def stacked_analysis(model, cntmap, expcube, psfcube):
141 141 cta_obs.load(cntmap)
142 142  
143 143 # Specify response for CTA observation
144   - exposure = gammalib.GCTACubeExposure(expcube)
145   - psf = gammalib.GCTACubePsf(psfcube)
146   - cta_obs.response(exposure, psf)
  144 + exposure = gammalib.GCTACubeExposure(expcube)
  145 + psf = gammalib.GCTACubePsf(psfcube)
  146 + background = gammalib.GCTACubeBackground(bkgcube)
  147 + cta_obs.response(exposure, psf, background)
147 148  
148 149 # Append CTA observation to observation container
149 150 obs.append(cta_obs)
... ... @@ -225,12 +226,13 @@ if __name__ == '__main__':
225 226 cntmap = "data/crab_cntmap.fits"
226 227 expcube = "data/expcube.fits"
227 228 psfcube = "data/psfcube.fits"
  229 + bkgcube = "data/bkgcube.fits"
228 230  
229 231 # Perform binned analysis
230 232 results_binned = binned_analysis(model, cntmap, irf, gammalib.GCaldb(caldb))
231 233  
232 234 # Perform stacked analysis
233   - results_cube = stacked_analysis(model, cntmap, expcube, psfcube)
  235 + results_cube = stacked_analysis(model, cntmap, expcube, psfcube, bkgcube)
234 236  
235 237 # Print model results
236 238 #print(result)
... ...
inst/cta/test/example_make_model.py
  View file @ddd8c14
1 1 #! /usr/bin/env python
2   -# ===========================================================================================#
  2 +# ==========================================================================
3 3 # This script makes a model map from an XML file.
4   -# ===========================================================================================#
5   -from gammalib import *
  4 +#
  5 +# Copyright (C) 2015 Juergen Knoedlseder
  6 +#
  7 +# This program is free software: you can redistribute it and/or modify
  8 +# it under the terms of the GNU General Public License as published by
  9 +# the Free Software Foundation, either version 3 of the License, or
  10 +# (at your option) any later version.
  11 +#
  12 +# This program is distributed in the hope that it will be useful,
  13 +# but WITHOUT ANY WARRANTY; without even the implied warranty of
  14 +# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
  15 +# GNU General Public License for more details.
  16 +#
  17 +# You should have received a copy of the GNU General Public License
  18 +# along with this program. If not, see <http://www.gnu.org/licenses/>.
  19 +#
  20 +# ==========================================================================
  21 +import gammalib
6 22  
7 23  
8 24 # ============================ #
... ... @@ -13,16 +29,16 @@ def make_model_for_cntmap(cntmap, modname, xmlname, irf, caldb, clobber=True):
13 29 Make a model counts map from an XML model.
14 30 """
15 31 # Allocate empty CTA observation
16   - obs = GCTAObservation()
  32 + obs = gammalib.GCTAObservation()
17 33  
18 34 # Load counts map into CTA observation
19   - obs.load_binned(cntmap)
  35 + obs.load(cntmap)
20 36  
21 37 # Set response
22 38 obs.response(irf, caldb)
23 39  
24 40 # Load models from XML file
25   - models = GModels(xmlname)
  41 + models = gammalib.GModels(xmlname)
26 42  
27 43 # Loop over all bins in counts map
28 44 for event in obs.events():
... ... @@ -44,18 +60,18 @@ if __name__ == &#39;__main__&#39;:
44 60 Example illustrating how to create a model map for a counts map.
45 61 """
46 62 # Dump header
47   - print
48   - print "***************************************************"
49   - print "* Create model map for counts map using XML model *"
50   - print "***************************************************"
51   - print "... please wait for a few seconds"
  63 + print("")
  64 + print("***************************************************")
  65 + print("* Create model map for counts map using XML model *")
  66 + print("***************************************************")
  67 + print("... please wait for a few seconds")
52 68  
53 69 # Set parameters
54   - irf = "kb_E_50h_v3"
55   - caldb = "../caldb"
  70 + irf = "cta_dummy_irf"
  71 + caldb = "./caldb"
56 72 xmlname = "data/crab.xml"
57 73 cntmap = "data/crab_cntmap.fits"
58 74 modname = "model.fits"
59 75  
60 76 # Make the model
61   - make_model_for_cntmap(cntmap, modname, xmlname, irf, caldb)
  77 + make_model_for_cntmap(cntmap, modname, xmlname, irf, gammalib.GCaldb(caldb))
... ...
inst/cta/test/example_sim_photons.py
  View file @ddd8c14
... ... @@ -116,7 +116,7 @@ def show_photons(photons, xmlname, e_min, e_max, area, duration, ebins=30):
116 116  
117 117 # Plot data
118 118 plt.loglog(energy, counts, 'ro')
119   - plt.errorbar(energy, counts, error, fmt=None, ecolor='r')
  119 + plt.errorbar(energy, counts, error, ecolor='r')
120 120  
121 121 # Plot model
122 122 plt.plot(energy, model, 'b-')
... ...
inst/cta/test/example_sim_psf.py
  View file @ddd8c14
... ... @@ -89,7 +89,7 @@ def sim_psf(response, energy, r_max=0.8, rbins=1000, nmc=1000000):
89 89  
90 90 # Plot simulated data
91 91 plt.plot(delta, counts, 'ro')
92   - plt.errorbar(delta, counts, error, fmt=None, ecolor='r')
  92 + plt.errorbar(delta, counts, error, ecolor='r')
93 93  
94 94 # Plot PSF
95 95 plt.plot(delta, psf, 'b-')
... ...
inst/cta/test/test_model.py
  View file @ddd8c14
... ... @@ -174,10 +174,10 @@ def observation(ra=83.6331, dec=22.0145, emin=0.1, emax=100.0,
174 174 obs = gammalib.GCTAObservation()
175 175  
176 176 # Set response
177   - #obs.response("cta_dummy_irf", GCaldb("../caldb"))
178   - exposure = gammalib.GCTACubeExposure("data/expcube.fits")
179   - psf = gammalib.GCTACubePsf("data/psfcube.fits")
180   - obs.response(exposure, psf)
  177 + exposure = gammalib.GCTACubeExposure("data/expcube.fits")
  178 + psf = gammalib.GCTACubePsf("data/psfcube.fits")
  179 + background = gammalib.GCTACubeBackground("data/bkgcube.fits")
  180 + obs.response(exposure, psf, background)
181 181  
182 182 # Set pointing
183 183 dir = gammalib.GSkyDir()
... ... @@ -201,9 +201,6 @@ def observation(ra=83.6331, dec=22.0145, emin=0.1, emax=100.0,
201 201 obs.livetime(duration * deadc)
202 202 obs.deadc(deadc)
203 203  
204   - # Optionally show observation
205   - # print(obs)
206   -
207 204 # Return observation
208 205 return obs
209 206  
... ...
inst/mwl/test/test_python.py
  View file @ddd8c14
1 1 #! /usr/bin/env python
2 2  
3   -from gammalib import *
4   -from math import *
  3 +import gammalib
  4 +import math
  5 +#from gammalib import *
  6 +#from math import *
5 7 import os
6 8  
7 9  
... ... @@ -17,16 +19,16 @@ def extract_data(filename):
17 19 styles = ['ro', 'bo', 'go']
18 20  
19 21 # Open FITS file
20   - fits = GFits(filename)
  22 + fits = gammalib.GFits(filename)
21 23  
22 24 # Loop over all table HDUs
23 25 k = 0
24 26 for extno in range(fits.size()):
25   - if fits.at(extno).exttype() == GFitsHDU.HT_ASCII_TABLE or \
26   - fits.at(extno).exttype() == GFitsHDU.HT_BIN_TABLE:
  27 + if fits.at(extno).exttype() == gammalib.GFitsHDU.HT_ASCII_TABLE or \
  28 + fits.at(extno).exttype() == gammalib.GFitsHDU.HT_BIN_TABLE:
27 29  
28 30 # Load spectrum
29   - spectrum = GMWLSpectrum()
  31 + spectrum = gammalib.GMWLSpectrum()
30 32 spectrum.load(filename, extno)
31 33  
32 34 # Add spectral points
... ... @@ -42,7 +44,7 @@ def extract_data(filename):
42 44 y.append(yval * conv)
43 45 dy.append(yerr * conv)
44 46 plt.loglog(x, y, styles[k])
45   - plt.errorbar(x, y, dy, fmt=None, ecolor=ecolor[k])
  47 + plt.errorbar(x, y, dy, ecolor=ecolor[k])
46 48  
47 49 # Increment style counter
48 50 k = k + 1
... ... @@ -63,37 +65,38 @@ def fit_spectrum(filename, xmlname):
63 65 Fit spectrum.
64 66 """
65 67 # Load observations
66   - obs = GObservations()
67   - comptel = GMWLObservation(filename, "COMPTEL")
68   - lat = GMWLObservation(filename, "LAT")
69   - hess = GMWLObservation(filename, "HESS")
  68 + obs = gammalib.GObservations()
  69 + comptel = gammalib.GMWLObservation(filename, "COMPTEL")
  70 + lat = gammalib.GMWLObservation(filename, "LAT")
  71 + hess = gammalib.GMWLObservation(filename, "HESS")
70 72 obs.append(comptel)
71 73 obs.append(lat)
72 74 obs.append(hess)
73 75  
74 76 # Setup model
75   - models = GModels(xmlname)
  77 + models = gammalib.GModels(xmlname)
76 78 obs.models(models)
77 79  
78 80 # Perform optimization
79   - opt = GOptimizerLM()
  81 + opt = gammalib.GOptimizerLM()
80 82 opt.max_iter(1000)
81 83 obs.optimize(opt)
82   - print obs
  84 + print(obs)
83 85  
84 86 # Get model values
85 87 x = np.power(10., np.arange(-1., 8., 0.1))
86 88 y = []
87   - d = GSkyDir()
  89 + d = gammalib.GSkyDir()
88 90 d.radec_deg(83.6331, 22.0145)
89   - e = GEnergy()
90   - t = GTime()
  91 + e = gammalib.GEnergy()
  92 + t = gammalib.GTime()
91 93 for energy in x:
92 94 e.MeV(energy)
93 95 yval = 0.0
94 96 for model in obs.models():
95 97 if model.type() == "PointSource":
96   - yval += model.value(GPhoton(d, e, t)) * energy * energy * 1.6021765e-6
  98 + yval += model.value(gammalib.GPhoton(d, e, t)) * \
  99 + energy * energy * 1.6021765e-6
97 100 y.append(yval)
98 101 plt.plot(x, y)
99 102  
... ... @@ -106,10 +109,10 @@ if __name__ == &#39;__main__&#39;:
106 109 Perform testing.
107 110 """
108 111 # Dump result
109   - print
110   - print "****************************"
111   - print "* Python interface testing *"
112   - print "****************************"
  112 + print("")
  113 + print("****************************")
  114 + print("* Python interface testing *")
  115 + print("****************************")
113 116  
114 117 # Only proceed if matplotlib is available
115 118 try:
... ... @@ -131,4 +134,4 @@ if __name__ == &#39;__main__&#39;:
131 134 plt.show()
132 135  
133 136 except ImportError:
134   - print "Matplotlib is not (correctly) installed on your system."
  137 + print("Matplotlib is not (correctly) installed on your system.")
... ...