Thierry Reposeur / ctools

Commit 8590d4867d39b8803424c7528d8d83cfc2728b3a

Authored by Jürgen Knödlseder
1 parent ce0042b4

Complete adding of unit tests for all example scripts

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Showing 20 changed files with 611 additions and 237 deletions
ChangeLog
  View file @8590d48
1   -2016-06-21 Juergen Knoedlseder <jurgen.knodlseder@irap.omp.eu>
  1 +2016-06-25 Juergen Knoedlseder <jurgen.knodlseder@irap.omp.eu>
2 2  
3 3 * Version 1.1.0 released
4 4 ========================
5 5  
  6 + Add unit tests for all example scripts
6 7 Handle zero parameter errors in ctulimit (#1795)
7 8 Compute counts cube weights in ctbin (#1789)
8 9 Adapt to new stacked cube interface (#1788)
... ...
1 1 New Features and Important Changes in ctools 1.1.0
2 2  
3   -21 June 2016
  3 +25 June 2016
4 4  
5 5  
6 6 Introduction
... ...
README.md
  View file @8590d48
1 1 ctools information
2 2 ==================
3   -* Version: 1.1.0.dev1 (21 June 2016)
  3 +* Version: 1.1.0.dev1 (25 June 2016)
4 4 * Author: Juergen Knoedlseder (jurgen.knodlseder@irap.omp.eu)
5 5 * GammaLib dependency: 1.1.0.dev1
6 6  
... ...
examples/README.md
  View file @8590d48
1 1 ctools examples
2 2 ===============
3 3  
4   -This folder contains Python example scripts that illustrate the
5   -usage of the ctools.
6   -
7   -`benchmark_cta_analysis.py`
8   -> This script peforms a benchmark of the various CTA analysis types
9   -> (unbinned, binned, stacked), and if matplotlib is installed, creates
10   -> a plot of the benchmark results.
11   -
12   -`check_models.py`
13   -> Checks a variety of models using an unbinned analysis.
  4 +This folder contains Python example scripts that illustrate the usage of
  5 +the ctools.
14 6  
15 7 `generate_prod3_irfs/py`
16   -> Generate Prod3 Instrument Response Functions from FITS files.
  8 +> Generates Prod3 Instrument Response Functions from FITS files.
17 9  
18 10 `make_pointings.py`
19   -> This script creates pointings for CTA surveys. For the moment the
20   -> Galactic Plane Survey (gps), the Extragalactic Survey (extgal),
21   -> the Galactic Centre Survey (gc) and the LMC survey (lmc) are
22   -> implemented. The script outputs and ASCII file that can be used by
23   -> csobsdef.
24   -
25   -`make_pull_at_sensitivity_limit.py`
26   -> This script creates pull distributions as function of energy
27   -> for a test source that is at the 5 sigma sensitivity limit for
28   -> 50h of effective observing time. It takes as input file the
29   -> output file generated using cspull.
30   -> If the Python processing module is installed the script can make
31   -> use of multiple cores and runs in parallel.
  11 +> Creates pointings for CTA surveys. For the moment the Galactic Plane
  12 +> Survey (gps), the Extragalactic Survey (extgal), the Galactic Centre
  13 +> Survey (gc) and the LMC survey (lmc) are implemented. The script outputs
  14 +> and ASCII file that can be used by csobsdef.
32 15  
33 16 `make_spectrum.py`
34   -> This script shows how to make a spectrum using obsutils.
35   -
36   -`make_survey.py`
37   -> This script simulates a CTA galactic plane survey.
  17 +> Simulates events and generates a spectrum from the using csspec.
38 18  
39 19 `make_ts_distributions.py`
40   -> This script creates TS distributions as function of energy for
41   -> an off observation of 50h effective observing time.
42   -> If the Python processing module is installed the script can make
43   -> use of multiple cores and runs in parallel.
  20 +> Creates TS distributions as function of energy for an OFF observaition
  21 +> of 50 hours effective observing time. If the Python processing module is
  22 +> installed the script can make use of multiple cores and runs in parallel.
44 23  
45 24 `pipeline_binned_disk.py`
46   -> Example pipeline for simulating events and performing a binned
47   -> analysis by saving intermediate results to disk.
  25 +> Example pipeline for simulating events and performing a binned analysis
  26 +> by saving intermediate results to disk.
48 27  
49 28 `pipeline_binned_mem.py`
50   -> Example pipeline for simulating events and performing a binned
51   -> analysis in memory. No files will be written to disk.
  29 +> Example pipeline for simulating events and performing a binned analysis
  30 +> in memory. No files will be written to disk.
52 31  
53 32 `pipeline_stacked_disk.py`
54   -> Example pipeline for simulating events and performing a stacked
55   -> analysis by saving intermediate results to disk.
  33 +> Example pipeline for simulating events and performing a stacked analysis
  34 +> by saving intermediate results to disk.
56 35  
57 36 `pipeline_stacked_mem.py`
58   -> Example pipeline for simulating events and performing a stacked
59   -> analysis in memory. No files will be written to disk.
  37 +> Example pipeline for simulating events and performing a stacked analysis
  38 +> in memory. No files will be written to disk.
60 39  
61 40 `pipeline_unbinned_disk.py`
62   -> Example pipeline for simulating events and performing an unbinned
63   -> analysis by saving intermediate results to disk.
  41 +> Example pipeline for simulating events and performing an unbinned analysis
  42 +> by saving intermediate results to disk.
64 43  
65 44 `pipeline_unbinned_mem.py`
66   -> Example pipeline for simulating events and performing an unbinned
67   -> analysis in memory. No files will be written to disk.
  45 +> Example pipeline for simulating events and performing an unbinned analysis
  46 +> in memory. No files will be written to disk.
68 47  
69 48 `show_butterfly.py`
70 49 > Displays a butterfly generated using the ctbutterfly tool.
... ... @@ -86,14 +65,10 @@ usage of the ctools.
86 65 > Displays one or several CTA response functions.
87 66  
88 67 `show_sensitivity.py`
89   -> Displays sensitivity information generated by the cssens script.
  68 +> Displays the sensitivity generated by the cssens script.
90 69  
91 70 `show_spectrum.py`
92 71 > Displays spectrum generated by the csspec script.
93 72  
94 73 `show_ts_distribution.py`
95   -> Displays Test Statistic histograms generated using the cstsdist
96   -> script.
97   -
98   -`simulate_events.py`
99   -> Simulates events and compares the simulation to the model.
  74 +> Displays Test Statistic histograms generated using the cstsdist script.
... ...
examples/make_ts_distributions.py
  View file @8590d48
1 1 #! /usr/bin/env python
2 2 # ==========================================================================
3   -# Generate TS distribution
  3 +# Generate TS distributions as function of energy for an OFF observation
4 4 #
5 5 # Copyright (C) 2011-2016 Jurgen Knodlseder
6 6 #
... ... @@ -65,7 +65,7 @@ def create_ts(loge, emin, emax, ntrials=100, duration=180000.0,
65 65 tsdist['outfile'] = outfile
66 66 tsdist['ntrials'] = ntrials
67 67 tsdist['caldb'] = 'prod2'
68   - tsdist['irf'] = 'South_0.5h'
  68 + tsdist['irf'] = 'South_50h'
69 69 tsdist['ra'] = 83.63
70 70 tsdist['dec'] = 22.01
71 71 tsdist['emin'] = emin
... ... @@ -76,7 +76,6 @@ def create_ts(loge, emin, emax, ntrials=100, duration=180000.0,
76 76 tsdist['rad'] = 5.0
77 77 tsdist['npix'] = 200
78 78 tsdist['binsz'] = 0.05
79   - #tsdist['debug'] = True
80 79  
81 80 # Optionally open the log file
82 81 if log:
... ... @@ -95,7 +94,7 @@ def create_ts(loge, emin, emax, ntrials=100, duration=180000.0,
95 94 if __name__ == '__main__':
96 95  
97 96 # Get input arguments
98   - usage = 'make_ts_distributions [-n ntrials] [-e enumbins] [-m max_threads]'
  97 + usage = 'make_ts_distributions.py [-n ntrials] [-e enumbins] [-m max_threads]'
99 98 if len(sys.argv) < 1:
100 99 print(usage)
101 100 sys.exit()
... ...
examples/show_butterfly.py
  View file @8590d48
... ... @@ -32,7 +32,7 @@ except:
32 32 # ============ #
33 33 # Script entry #
34 34 # ============ #
35   -if __name__ == "__main__":
  35 +if __name__ == '__main__':
36 36  
37 37 # Check for given butterfly file
38 38 if len(sys.argv) < 2:
... ... @@ -83,7 +83,7 @@ if __name__ == &quot;__main__&quot;:
83 83 plt.plot(line_x,line_y,color='black',ls='-')
84 84 plt.fill(butterfly_x,butterfly_y,color='green',alpha=0.5)
85 85 plt.xlabel('Energy (MeV)')
86   - plt.ylabel('E dN/dE (MeV$^{-1}$ s$^{-1}$ cm$^{-2}$)')
  86 + plt.ylabel(r'E $\times$ dN/dE (MeV$^{-1}$ s$^{-1}$ cm$^{-2}$)')
87 87  
88 88 # Show spectrum or save it into file
89 89 if len(plotfile) > 0:
... ...
examples/show_model.py
  View file @8590d48
... ... @@ -103,7 +103,7 @@ def plot_spectrum(model, emin=0.01, emax=100.0, enumbins=100, plotfile=&#39;&#39;):
103 103 # ============= #
104 104 # Script entry #
105 105 # ============= #
106   -if __name__ == "__main__":
  106 +if __name__ == '__main__':
107 107  
108 108 # Check for model filename
109 109 if len(sys.argv) < 2:
... ...
examples/show_pha.py
  View file @8590d48
... ... @@ -95,7 +95,7 @@ def show_pha(pha, plotfile=&#39;&#39;):
95 95 if __name__ == '__main__':
96 96  
97 97 # Print usage information
98   - usage = 'Usage: show_pha filename [file]'
  98 + usage = 'Usage: show_pha.py filename [file]'
99 99 if len(sys.argv) < 2:
100 100 print(usage)
101 101 sys.exit()
... ...
examples/show_pull_evolution.py
  View file @8590d48
... ... @@ -89,7 +89,7 @@ def read_pull(filename, parname):
89 89 if __name__ == '__main__':
90 90  
91 91 # Print usage information
92   - usage = 'Usage: show_pull_evolution filename parname [file]'
  92 + usage = 'Usage: show_pull_evolution.py filename parname [file]'
93 93 if len(sys.argv) < 3:
94 94 print(usage)
95 95 sys.exit()
... ...
examples/show_pull_histogram.py
  View file @8590d48
... ... @@ -90,7 +90,7 @@ def read_pull(filename, parname):
90 90 if __name__ == '__main__':
91 91  
92 92 # Print usage information
93   - usage = 'Usage: show_pull_histogram filename parname [bins] [file]'
  93 + usage = 'Usage: show_pull_histogram.py filename parname [bins] [file]'
94 94 if len(sys.argv) < 3:
95 95 print(usage)
96 96 sys.exit()
... ...
examples/show_response.py
  View file @8590d48
1 1 #! /usr/bin/env python
2 2 # ==========================================================================
3   -# This script displays one or several CTA response functions.
  3 +# Shows one or several CTA response functions.
4 4 #
5   -# Required 3rd party modules:
6   -# - matplotlib
7   -# - numpy
8   -#
9   -# Copyright (C) 2014-2015 Juergen Knoedlseder
  5 +# Copyright (C) 2014-2016 Juergen Knoedlseder
10 6 #
11 7 # This program is free software: you can redistribute it and/or modify
12 8 # it under the terms of the GNU General Public License as published by
... ... @@ -25,7 +21,13 @@
25 21 import sys
26 22 import math
27 23 import gammalib
28   -import matplotlib.pyplot as plt
  24 +try:
  25 + import matplotlib.pyplot as plt
  26 + plt.figure()
  27 + plt.close()
  28 +except:
  29 + print('This script needs the "matplotlib" module')
  30 + sys.exit()
29 31  
30 32  
31 33 # ================================== #
... ... @@ -35,11 +37,19 @@ def sigma_lima(Non, Noff, alpha=0.2):
35 37 """
36 38 Compute Eq. (17) of Li & Ma (1983).
37 39  
38   - Parameters:
39   - Non - Number of on counts
40   - Noff - Number of off counts
41   - Keywords:
42   - alpha - Ratio of on-to-off exposure
  40 + Parameters
  41 + ----------
  42 + Non : float
  43 + Number of On counts
  44 + Noff : float
  45 + Number of Off counts
  46 + alpha : float, optional
  47 + Ratio of on-to-off exposure
  48 +
  49 + Returns
  50 + -------
  51 + sigma : float
  52 + Detection significance in Gaussian sigma
43 53 """
44 54 # Compute sensitivity
45 55 alpha1 = alpha + 1.0
... ... @@ -61,11 +71,19 @@ def Non_lima(sigma, Noff, alpha=0.2):
61 71 """
62 72 Solve Eq. (17) of Li & Ma (1983) for Non
63 73  
64   - Parameters:
65   - sigma - Required significance
66   - Noff - Number of off counts
67   - Keywords:
68   - alpha - Ratio of on-to-off exposure
  74 + Parameters
  75 + ----------
  76 + sigma : float
  77 + Required detection significance in Gaussian sigma
  78 + Noff : float
  79 + Number of Off counts
  80 + alpha : float, optional
  81 + Ratio of on-to-off exposure
  82 +
  83 + Returns
  84 + -------
  85 + Non : float
  86 + Number of On counts
69 87 """
70 88 # Set initial guess for Non
71 89 S = 25.0
... ... @@ -89,9 +107,18 @@ def Non_lima(sigma, Noff, alpha=0.2):
89 107 # ======================= #
90 108 # Show one effective area #
91 109 # ======================= #
92   -def show_one_effective_area(rsp, name, color="r"):
  110 +def show_one_effective_area(rsp, name, color='r'):
93 111 """
94   - Show one effective area.
  112 + Show one effective area
  113 +
  114 + Parameters
  115 + ----------
  116 + rsp : `~gammalib.GCTAResponse`
  117 + Response function
  118 + name : str
  119 + Name of the response function
  120 + color : str, optional
  121 + Color for plot
95 122 """
96 123 # Set to figure 1
97 124 plt.figure(1)
... ... @@ -111,11 +138,11 @@ def show_one_effective_area(rsp, name, color=&quot;r&quot;):
111 138 plt.loglog(E, aeff, color+'o')
112 139  
113 140 # Set axes
114   - plt.xlabel("Energy [TeV]")
115   - plt.ylabel("Effective area [cm2]")
  141 + plt.xlabel('Energy (TeV)')
  142 + plt.ylabel(r'Effective area (cm$^{2}$)')
116 143  
117 144 # Set legend
118   - plt.legend(loc="lower right")
  145 + plt.legend(loc='lower right')
119 146  
120 147 # Return
121 148 return
... ... @@ -124,9 +151,18 @@ def show_one_effective_area(rsp, name, color=&quot;r&quot;):
124 151 # ======================== #
125 152 # Show one background rate #
126 153 # ======================== #
127   -def show_one_background_rate(rsp, name, color="r"):
  154 +def show_one_background_rate(rsp, name, color='r'):
128 155 """
129   - Show one background rate.
  156 + Show one background rate
  157 +
  158 + Parameters
  159 + ----------
  160 + rsp : `~gammalib.GCTAResponse`
  161 + Response function
  162 + name : str
  163 + Name of the response function
  164 + color : str, optional
  165 + Color for plot
130 166 """
131 167 # Set to figure 2
132 168 plt.figure(2)
... ... @@ -148,11 +184,11 @@ def show_one_background_rate(rsp, name, color=&quot;r&quot;):
148 184 plt.loglog(E, bgrate, color+'o')
149 185  
150 186 # Set axes
151   - plt.xlabel("Energy [TeV]")
152   - plt.ylabel("Background rate [events/s/MeV/sr]")
  187 + plt.xlabel('Energy (TeV)')
  188 + plt.ylabel(r'Background rate (counts s$^{-1}$ MeV$^{-1}$ sr$^{-1}$)')
153 189  
154 190 # Set legend
155   - plt.legend(loc="lower left")
  191 + plt.legend(loc='lower left')
156 192  
157 193 # Return
158 194 return
... ... @@ -161,9 +197,25 @@ def show_one_background_rate(rsp, name, color=&quot;r&quot;):
161 197 # ==================== #
162 198 # Show one sensitivity #
163 199 # ==================== #
164   -def show_one_sensitivity(rsp, name, color="r", duration=180000.0, alpha=0.2, sigma=5.0):
  200 +def show_one_sensitivity(rsp, name, color='r', duration=180000.0, alpha=0.2,
  201 + sigma=5.0):
165 202 """
166   - Show one sensitivity.
  203 + Show one sensitivity
  204 +
  205 + Parameters
  206 + ----------
  207 + rsp : `~gammalib.GCTAResponse`
  208 + Response function
  209 + name : str
  210 + Name of the response function
  211 + color : str, optional
  212 + Color for plot
  213 + duration : float, optional
  214 + Duration of observation (s)
  215 + alpha : float, optional
  216 + Ratio of on-to-off exposure
  217 + sigma : float, optional
  218 + Required detection significance in Gaussian sigma
167 219 """
168 220 # Set constants
169 221 r68_to_sigma = 0.6624305
... ... @@ -194,9 +246,9 @@ def show_one_sensitivity(rsp, name, color=&quot;r&quot;, duration=180000.0, alpha=0.2, sig
194 246 src_counts = 0.05*bgd_counts
195 247 if src_counts < 10:
196 248 src_counts = 10.0
197   - emin = gammalib.GEnergy(math.pow(10.0, logE[i]-0.1), "TeV")
198   - emax = gammalib.GEnergy(math.pow(10.0, logE[i]+0.1), "TeV")
199   - epivot = gammalib.GEnergy(math.pow(10.0, logE[i]), "TeV")
  249 + emin = gammalib.GEnergy(math.pow(10.0, logE[i]-0.1), 'TeV')
  250 + emax = gammalib.GEnergy(math.pow(10.0, logE[i]+0.1), 'TeV')
  251 + epivot = gammalib.GEnergy(math.pow(10.0, logE[i]), 'TeV')
200 252 plaw = gammalib.GModelSpectralPlaw(1.0e-6, -2.6, epivot)
201 253 conv = TeV2erg*E[i]*E[i]/plaw.flux(emin, emax)
202 254 flux[i] = conv * src_counts / (duration * aeff*0.68)
... ... @@ -206,11 +258,11 @@ def show_one_sensitivity(rsp, name, color=&quot;r&quot;, duration=180000.0, alpha=0.2, sig
206 258 plt.loglog(E, flux, color+'o')
207 259  
208 260 # Set axes
209   - plt.xlabel("Energy [TeV]")
210   - plt.ylabel("Sensitivity [erg/cm2/s]")
  261 + plt.xlabel('Energy (TeV)')
  262 + plt.ylabel(r'Sensitivity (erg cm$^{-2}$ s$^{-1}$)')
211 263  
212 264 # Set legend
213   - plt.legend(loc="upper right")
  265 + plt.legend(loc='upper right')
214 266  
215 267 # Return
216 268 return
... ... @@ -219,9 +271,22 @@ def show_one_sensitivity(rsp, name, color=&quot;r&quot;, duration=180000.0, alpha=0.2, sig
219 271 # ==================== #
220 272 # Show one sensitivity #
221 273 # ==================== #
222   -def show_one_response(rspname, dbname, name, rootdir=None, color="r"):
  274 +def show_one_response(rspname, dbname, name, rootdir=None, color='r'):
223 275 """
224 276 Show one response.
  277 +
  278 + Parameters
  279 + ----------
  280 + rspname : str
  281 + Response name
  282 + dbname : str
  283 + Database name
  284 + name : str
  285 + Name of the response function
  286 + rootdir : str, optional
  287 + Response root directory
  288 + color : str, optional
  289 + Color for plot
225 290 """
226 291 # Set-up calibration database
227 292 caldb = gammalib.GCaldb()
... ... @@ -230,7 +295,7 @@ def show_one_response(rspname, dbname, name, rootdir=None, color=&quot;r&quot;):
230 295 if gammalib.dir_exists(dbname):
231 296 caldb.rootdir(dbname)
232 297 else:
233   - caldb.open("cta", dbname)
  298 + caldb.open('cta', dbname)
234 299  
235 300 # Load response function
236 301 rsp = gammalib.GCTAResponseIrf(rspname, caldb)
... ... @@ -253,28 +318,35 @@ def show_one_response(rspname, dbname, name, rootdir=None, color=&quot;r&quot;):
253 318 # ======================== #
254 319 if __name__ == '__main__':
255 320  
  321 + # Print usage information
  322 + usage = 'Usage: show_response.py [file]'
  323 + if len(sys.argv) < 1:
  324 + print(usage)
  325 + sys.exit()
  326 +
  327 + # Check if plotting in file is requested
  328 + plotfile = ''
  329 + if len(sys.argv) == 2:
  330 + plotfile = sys.argv[1]
  331 +
256 332 # Create figures
257 333 plt.figure(1)
258   - plt.title("Effective area")
  334 + plt.title('Effective area')
259 335 plt.figure(2)
260   - plt.title("Background rate")
  336 + plt.title('Background rate')
261 337 plt.figure(3)
262   - plt.title("Sensitivity")
  338 + plt.title('Sensitivity')
263 339  
264 340 # Set response dictionary
265 341 rsps = [
266   - {'dbname': "dummy",
267   - 'rspname': "cta_dummy_irf",
268   - 'name': "Prod1 (Array E, MPIK)",
269   - 'color': "b"},
270   - {'dbname': "e",
271   - 'rspname': "IFAE20120510_50h",
272   - 'name': "Prod1 (Array E, IFAE)",
273   - 'color': "g"},
274   - {'dbname': "aar",
275   - 'rspname': "DESY20140105_50h",
276   - 'name': "Prod2 (Aar, DESY)",
277   - 'color': "r"}
  342 + {'dbname': 'irf',
  343 + 'rspname': 'cta_dummy_irf.dat',
  344 + 'name': 'Prod1 (Array E, MPIK)',
  345 + 'color': 'b'},
  346 + {'dbname': 'irf',
  347 + 'rspname': 'irf_file.fits',
  348 + 'name': 'Prod2 (Aar, IFAE)',
  349 + 'color': 'r'}
278 350 ]
279 351  
280 352 # Loop over all responses
... ... @@ -293,5 +365,8 @@ if __name__ == &#39;__main__&#39;:
293 365 # Show response
294 366 show_one_response(rspname, dbname, name, rootdir=rootdir, color=color)
295 367  
296   - # Show plot
297   - plt.show()
  368 + # Show figure
  369 + if len(plotfile) > 0:
  370 + plt.savefig(plotfile)
  371 + else:
  372 + plt.show()
... ...
examples/show_sensitivity.py
  View file @8590d48
1 1 #! /usr/bin/env python
2 2 # ==========================================================================
3   -# This script displays a differential sensitivity plot generated by cssens.
  3 +# Display differential sensitivity plot generated by cssens
4 4 #
5   -# Copyright (C) 2015 Juergen Knoedlseder
  5 +# Copyright (C) 2015-2016 Juergen Knoedlseder
6 6 #
7 7 # This program is free software: you can redistribute it and/or modify
8 8 # it under the terms of the GNU General Public License as published by
... ... @@ -23,8 +23,11 @@ import math
23 23 import gammalib
24 24 try:
25 25 import matplotlib.pyplot as plt
  26 + plt.figure()
  27 + plt.close()
26 28 except:
27   - sys.exit("This script needs matplotlib")
  29 + print('This script needs the "matplotlib" module')
  30 + sys.exit()
28 31  
29 32  
30 33 # ===================== #
... ... @@ -32,7 +35,17 @@ except:
32 35 # ===================== #
33 36 def read_sensitivity(filename):
34 37 """
35   - Read sensitivity information from CSV file.
  38 + Read sensitivity information from CSV file
  39 +
  40 + Parameters
  41 + ----------
  42 + filename : str
  43 + Name of CSV file
  44 +
  45 + Returns
  46 + -------
  47 + sensitivity : dict
  48 + Dictionary with sensitivity information
36 49 """
37 50 # Read filename
38 51 csv = gammalib.GCsv(filename,',')
... ... @@ -40,39 +53,39 @@ def read_sensitivity(filename):
40 53 # Create dictionnary
41 54 sensitivity = {}
42 55 for column in range(csv.ncols()):
43   - name = csv[0,column]
  56 + name = csv[0,column].rstrip('\r')
44 57 values = []
45 58 for row in range(csv.nrows()-1):
46 59 values.append(float(csv[row+1,column]))
47 60 sensitivity[name] = values
48 61  
49 62 # Check where file contains differential or integral sensitivity
50   - mode = "Integral"
51   - if sensitivity.has_key("emax"):
  63 + mode = 'Integral'
  64 + if sensitivity.has_key('emax'):
52 65 emax_ref = -1.0
53   - for value in sensitivity["emax"]:
  66 + for value in sensitivity['emax']:
54 67 if emax_ref < 0.0:
55 68 emax_ref = value
56 69 elif emax_ref != value:
57   - mode = "Differential"
  70 + mode = 'Differential'
58 71 break
59 72  
60 73 # Add mode
61   - sensitivity["mode"] = mode
  74 + sensitivity['mode'] = mode
62 75  
63 76 # Add linear energy values
64   - if mode == "Differential":
65   - if sensitivity.has_key("loge"):
  77 + if mode == 'Differential':
  78 + if sensitivity.has_key('loge'):
66 79 name = 'energy'
67 80 values = []
68   - for value in sensitivity["loge"]:
  81 + for value in sensitivity['loge']:
69 82 values.append(math.pow(10.0, value))
70 83 sensitivity[name] = values
71 84 else:
72   - if sensitivity.has_key("emin"):
  85 + if sensitivity.has_key('emin'):
73 86 name = 'energy'
74 87 values = []
75   - for value in sensitivity["emin"]:
  88 + for value in sensitivity['emin']:
76 89 values.append(value)
77 90 sensitivity[name] = values
78 91  
... ... @@ -83,9 +96,18 @@ def read_sensitivity(filename):
83 96 # ===================== #
84 97 # Show sensitivity data #
85 98 # ===================== #
86   -def show_sensitivity(sensitivity, filename):
  99 +def show_sensitivity(sensitivity, filename, plotfile=''):
87 100 """
88   - Plot sensitivity.
  101 + Plot sensitivity data
  102 +
  103 + Parameters
  104 + ----------
  105 + sensitivity : dict
  106 + Dictionary with sensitivity information
  107 + filename : str
  108 + Name of CSV file
  109 + plotfile : str, optional
  110 + Plot file name
89 111 """
90 112 # Build title
91 113 title = sensitivity['mode'] + ' sensitivity ('+filename+')'
... ... @@ -102,14 +124,17 @@ def show_sensitivity(sensitivity, filename):
102 124 plt.plot(sensitivity['energy'], sensitivity['sensitivity'], 'ro-')
103 125  
104 126 # Set labels
105   - plt.xlabel("Energy (TeV)")
106   - if sensitivity['mode'] == "Differential":
107   - plt.ylabel(r"E$\times$ F(E) (erg cm$^{-2}$ s$^{-1}$)")
  127 + plt.xlabel('Energy (TeV)')
  128 + if sensitivity['mode'] == 'Differential':
  129 + plt.ylabel(r'E $\times$ F(E) (erg cm$^{-2}$ s$^{-1}$)')
108 130 else:
109   - plt.ylabel(r"E$\times$ F($>$E) (erg cm$^{-2}$ s$^{-1}$)")
  131 + plt.ylabel(r'E $\times$ F($>$E) (erg cm$^{-2}$ s$^{-1}$)')
110 132  
111   - # Show plot
112   - plt.show()
  133 + # Show figure
  134 + if len(plotfile) > 0:
  135 + plt.savefig(plotfile)
  136 + else:
  137 + plt.show()
113 138  
114 139 # Return
115 140 return
... ... @@ -121,9 +146,9 @@ def show_sensitivity(sensitivity, filename):
121 146 if __name__ == '__main__':
122 147  
123 148 # Print usage information
124   - usage = "Usage: show_sensitivity [filename]"
  149 + usage = 'Usage: show_sensitivity.py [filename] [file]'
125 150 if len(sys.argv) < 1:
126   - sys.stdout.write(usage+"\n")
  151 + print(usage)
127 152 sys.exit()
128 153  
129 154 # Extract parameters
... ... @@ -131,9 +156,12 @@ if __name__ == &#39;__main__&#39;:
131 156 filename = 'sensitivity.dat'
132 157 else:
133 158 filename = sys.argv[1]
  159 + plotfile = ''
  160 + if len(sys.argv) == 3:
  161 + plotfile = sys.argv[2]
134 162  
135 163 # Read sensitivity data
136 164 sensitivity = read_sensitivity(filename)
137 165  
138 166 # Show sensitivity data
139   - show_sensitivity(sensitivity, filename)
  167 + show_sensitivity(sensitivity, filename, plotfile=plotfile)
... ...
examples/show_spectrum.py
  View file @8590d48
1 1 #! /usr/bin/env python
2 2 # ==========================================================================
3   -# This script shows a spectrum created with csspec
  3 +# Display spectrum generated by csspec
4 4 #
5 5 # Copyright (C) 2015-2016 Juergen Knoedlseder
6 6 #
... ... @@ -18,35 +18,41 @@
18 18 # along with this program. If not, see <http://www.gnu.org/licenses/>.
19 19 #
20 20 # ==========================================================================
21   -
22   -import gammalib
23 21 import sys
  22 +import gammalib
24 23 try:
25 24 import matplotlib.pyplot as plt
  25 + plt.figure()
  26 + plt.close()
26 27 except:
27   - sys.exit("This script needs matplotlib")
  28 + print('This script needs the "matplotlib" module')
  29 + sys.exit()
28 30  
29 31  
30   -# ============ #
31   -# Script entry #
32   -# ============ #
33   -if __name__ == "__main__":
34   -
35   - # Check for given spectrum file
36   - if not len(sys.argv) == 2:
37   - sys.exit("Usage: show_spectrum.py spectrum.fits")
  32 +# ============= #
  33 +# Show spectrum #
  34 +# ============= #
  35 +def show_spectrum(filename, plotfile=''):
  36 + """
  37 + Plot sensitivity data
38 38  
  39 + Parameters
  40 + ----------
  41 + filename : str
  42 + Name of spectrum FITS file
  43 + plotfile : str, optional
  44 + Plot file name
  45 + """
39 46 # Read spectrum file
40   - filename = sys.argv[1]
41 47 fits = gammalib.GFits(filename)
42 48 table = fits.table(1)
43   - c_energy = table["Energy"]
44   - c_ed = table["ed_Energy"]
45   - c_eu = table["eu_Energy"]
46   - c_flux = table["Flux"]
47   - c_eflux = table["e_Flux"]
48   - c_ts = table["TS"]
49   - c_upper = table["UpperLimit"]
  49 + c_energy = table['Energy']
  50 + c_ed = table['ed_Energy']
  51 + c_eu = table['eu_Energy']
  52 + c_flux = table['Flux']
  53 + c_eflux = table['e_Flux']
  54 + c_ts = table['TS']
  55 + c_upper = table['UpperLimit']
50 56  
51 57 # Initialise arrays to be filled
52 58 energies = []
... ... @@ -63,25 +69,22 @@ if __name__ == &quot;__main__&quot;:
63 69 nrows = table.nrows()
64 70 for row in range(nrows):
65 71  
66   - # Get TS
  72 + # Get Test Statistic, flux and flux error
67 73 ts = c_ts.real(row)
68 74 flx = c_flux.real(row)
69 75 e_flx = c_eflux.real(row)
70 76  
71   - # Switch
  77 + # If Test Statistic is larger than 9 and flux error is smaller than
  78 + # flux then append flux plots ...
72 79 if ts > 9.0 and e_flx < flx:
73   -
74   - # Add information
75 80 energies.append(c_energy.real(row))
76 81 flux.append(c_flux.real(row))
77 82 ed_engs.append(c_ed.real(row))
78 83 eu_engs.append(c_eu.real(row))
79 84 e_flux.append(c_eflux.real(row))
80 85  
81   - #
  86 + # ... otherwise append upper limit
82 87 else:
83   -
84   - # Add information
85 88 ul_energies.append(c_energy.real(row))
86 89 ul_flux.append(c_upper.real(row))
87 90 ul_ed_engs.append(c_ed.real(row))
... ... @@ -91,8 +94,39 @@ if __name__ == &quot;__main__&quot;:
91 94 plt.figure()
92 95 plt.loglog()
93 96 plt.grid()
94   - plt.errorbar(energies, flux, yerr=e_flux, xerr=[ed_engs, eu_engs], fmt='ro')
95   - plt.errorbar(ul_energies, ul_flux, xerr=[ul_ed_engs, ul_eu_engs], yerr=1.0e-11, uplims=True, fmt='ro')
96   - plt.xlabel("Energy (TeV)")
97   - plt.ylabel(r"E dN/dE (erg cm$^{-2}$ s$^{-1}$)")
98   - plt.show()
  97 + plt.errorbar(energies, flux, yerr=e_flux, xerr=[ed_engs, eu_engs],
  98 + fmt='ro')
  99 + plt.errorbar(ul_energies, ul_flux, xerr=[ul_ed_engs, ul_eu_engs],
  100 + yerr=1.0e-11, uplims=True, fmt='ro')
  101 + plt.xlabel('Energy (TeV)')
  102 + plt.ylabel(r'E $\times$ dN/dE (erg cm$^{-2}$ s$^{-1}$)')
  103 +
  104 + # Show figure
  105 + if len(plotfile) > 0:
  106 + plt.savefig(plotfile)
  107 + else:
  108 + plt.show()
  109 +
  110 + # Return
  111 + return
  112 +
  113 +
  114 +# ======================== #
  115 +# Main routine entry point #
  116 +# ======================== #
  117 +if __name__ == '__main__':
  118 +
  119 + # Print usage information
  120 + usage = 'Usage: show_spectrum.py filename [file]'
  121 + if len(sys.argv) < 2:
  122 + print(usage)
  123 + sys.exit()
  124 +
  125 + # Extract parameters
  126 + filename = sys.argv[1]
  127 + plotfile = ''
  128 + if len(sys.argv) == 3:
  129 + plotfile = sys.argv[2]
  130 +
  131 + # Show spectrum
  132 + show_spectrum(filename, plotfile=plotfile)
... ...
examples/show_ts_distribution.py
  View file @8590d48
1 1 #! /usr/bin/env python
2 2 # ==========================================================================
3   -# This script displays the TS distribution values generated using cstsdist.
  3 +# Display TS distribution generated by cstsdist
4 4 #
5   -# Required 3rd party modules:
6   -# - matplotlib
7   -# - numpy
8   -#
9   -# Copyright (C) 2011 Jurgen Knodlseder
  5 +# Copyright (C) 2011-2016 Jurgen Knodlseder
10 6 #
11 7 # This program is free software: you can redistribute it and/or modify
12 8 # it under the terms of the GNU General Public License as published by
... ... @@ -22,20 +18,42 @@
22 18 # along with this program. If not, see <http://www.gnu.org/licenses/>.
23 19 #
24 20 # ==========================================================================
25   -import matplotlib.mlab as mlab
26   -import matplotlib.pyplot as plt
27   -import numpy as np
28 21 import sys
29 22 import csv
30 23 import math
  24 +try:
  25 + import matplotlib.pyplot as plt
  26 + import matplotlib.mlab as mlab
  27 + plt.figure()
  28 + plt.close()
  29 +except:
  30 + print('This script needs the "matplotlib" module')
  31 + sys.exit()
  32 +try:
  33 + import numpy as np
  34 +except:
  35 + print('This script needs the "numpy" module')
  36 + sys.exit()
31 37  
32 38  
33 39 # ==================== #
34 40 # Read TS distribution #
35 41 # ==================== #
36   -def read_ts(filename, tsname="TS"):
  42 +def read_ts(filename, tsname='TS'):
37 43 """
38   - Read TS distribution values from CSV file.
  44 + Read TS distribution values from CSV file
  45 +
  46 + Parameters
  47 + ----------
  48 + filename : str
  49 + Name of CSV file
  50 + tsname : str, optional
  51 + Column name of TS
  52 +
  53 + Returns
  54 + -------
  55 + a : `numpy.array`
  56 + Array of TS values
39 57 """
40 58 # Initialise list
41 59 values = []
... ... @@ -53,9 +71,9 @@ def read_ts(filename, tsname=&quot;TS&quot;):
53 71 try:
54 72 index = row.index(tsname)
55 73 except:
56   - sys.stdout.write('ERROR: Column "TS" not found in file\n')
57   - sys.stdout.write(row+"\n")
58   - raise NameError("TS")
  74 + print('ERROR: Column "'+tsname+'" not found in file')
  75 + print(row)
  76 + raise NameError(tsname)
59 77  
60 78 # Handle data rows
61 79 else:
... ... @@ -76,7 +94,17 @@ def read_ts(filename, tsname=&quot;TS&quot;):
76 94 # =========== #
77 95 def erf(x):
78 96 """
79   - Compute error function.
  97 + Compute error function
  98 +
  99 + Parameters
  100 + ----------
  101 + x : float
  102 + Value
  103 +
  104 + Returns
  105 + -------
  106 + erf(-x) : float
  107 + Error function
80 108 """
81 109 # save the sign of x
82 110 sign = 1
... ... @@ -103,9 +131,20 @@ def erf(x):
103 131 # =============================== #
104 132 # Display cumulative distribution #
105 133 # =============================== #
106   -def dist_cdf(values, nbins, title):
  134 +def dist_cdf(values, nbins, title, expect='', plotfile=''):
107 135 """
108   - Displays cumulative TS distribution and overplots expectation.
  136 + Display cumulative TS distribution and overplots expectation
  137 +
  138 + Parameters
  139 + ----------
  140 + values : float
  141 + TS values
  142 + nbins : int
  143 + Number of bins
  144 + title : str
  145 + Plot title
  146 + plotfile : str, optional
  147 + Plot file name
109 148 """
110 149 # Set range and adapt number of bins. We make sure that we have a
111 150 # histogram bin centred on 0 that will capture the TS=0 part.
... ... @@ -142,19 +181,23 @@ def dist_cdf(values, nbins, title):
142 181 hist_expect.append(norm)
143 182  
144 183 # Show expected distribution (half)
145   - l = plt.semilogy(hist_x, hist_y, 'r-', linewidth=2, label="simulations")
146   - l = plt.semilogy(hist_x, hist_expect, 'k-', linewidth=2, label="expectation")
147   - l = plt.semilogy(hist_x, hist_y, 'r-', linewidth=2)
  184 + plt.semilogy(hist_x, hist_y, 'r-', linewidth=2, label='simulations')
  185 + if expect == 'show':
  186 + plt.semilogy(hist_x, hist_expect, 'k-', linewidth=2, label='expectation')
  187 + plt.semilogy(hist_x, hist_y, 'r-', linewidth=2)
148 188  
149 189 # Set plot
150 190 plt.xlabel('TS')
151 191 plt.ylabel('Number of trials > TS')
152 192 plt.title(title)
153 193 plt.grid(True)
154   - plt.legend(loc="upper right")
  194 + plt.legend(loc='upper right')
155 195  
156   - # Show histogram
157   - plt.show()
  196 + # Show figure
  197 + if len(plotfile) > 0:
  198 + plt.savefig(plotfile)
  199 + else:
  200 + plt.show()
158 201  
159 202 # Return
160 203 return
... ... @@ -163,10 +206,20 @@ def dist_cdf(values, nbins, title):
163 206 # ======================================== #
164 207 # Display probability density distribution #
165 208 # ======================================== #
166   -def dist_pdf(values, nbins, title):
  209 +def dist_pdf(values, nbins, title, expect='', plotfile=''):
167 210 """
168   - Display probability density TS distribution and overplots
169   - expectation.
  211 + Display probability density TS distribution and overplots expectation
  212 +
  213 + Parameters
  214 + ----------
  215 + values : float
  216 + TS values
  217 + nbins : int
  218 + Number of bins
  219 + title : str
  220 + Plot title
  221 + plotfile : str, optional
  222 + Plot file name
170 223 """
171 224 # Set range and adapt number of bins. We make sure that we have a
172 225 # histogram bin centred on 0 that will capture the TS=0 part.
... ... @@ -180,9 +233,9 @@ def dist_pdf(values, nbins, title):
180 233 # Create histogram
181 234 n, bins, patches = plt.hist(values, nbins, range=[min_value, max_value],
182 235 align='mid', facecolor='green',
183   - log=True, label="simulations")
  236 + log=True, label='simulations')
184 237  
185   - # Create expected distribution (onyl for positive TS). We compute the
  238 + # Create expected distribution (only for positive TS). We compute the
186 239 # full and half of the distribution, as for positively constrained
187 240 # quantities half of the values have TS=0
188 241 x = []
... ... @@ -202,17 +255,24 @@ def dist_pdf(values, nbins, title):
202 255 y_half.append(0.5*y)
203 256  
204 257 # Show expected distribution (half)
205   - l = plt.semilogy(x, y_half, 'ro', linewidth=2, label="expectation")
  258 + if expect == 'show':
  259 + plt.semilogy(x, y_half, 'ro', linewidth=2, label='expectation')
206 260  
207 261 # Set plot
208 262 plt.xlabel('TS')
209 263 plt.ylabel('Number of trials')
210 264 plt.title(title)
211 265 plt.grid(True)
212   - plt.legend(loc="upper right")
  266 + plt.legend(loc='upper right')
213 267  
214   - # Show histogram
215   - plt.show()
  268 + # Show figure
  269 + if len(plotfile) > 0:
  270 + plt.savefig(plotfile)
  271 + else:
  272 + plt.show()
  273 +
  274 + # Return
  275 + return
216 276  
217 277  
218 278 # ======================== #
... ... @@ -221,26 +281,22 @@ def dist_pdf(values, nbins, title):
221 281 if __name__ == '__main__':
222 282  
223 283 # Print usage information
224   - usage = "Usage: show_ts_distribution filename" \
225   - " [-n bins] [-c column] [-t title] [-p plot]"
  284 + usage = 'Usage: show_ts_distribution.py filename' \
  285 + ' [-n bins] [-c column] [-t title] [-p plot] [-f file]'
226 286 if len(sys.argv) < 2:
227   - sys.stdout.write(usage+"\n")
  287 + print(usage)
228 288 sys.exit()
229 289  
230 290 # Extract parameters
231 291 filename = sys.argv[1]
232 292  
233   - # Set default parameters
234   - nbins = 30
235   - tsname = "TS"
236   - title = "TS distribution"
237   - plot = "pdf"
238   -
239 293 # Parameter dictionnary
240   - pars = [{'option': '-n', 'value': nbins},
241   - {'option': '-c', 'value': tsname},
242   - {'option': '-t', 'value': title},
243   - {'option': '-p', 'value': plot}]
  294 + pars = [{'option': '-n', 'value': 30},
  295 + {'option': '-c', 'value': 'TS'},
  296 + {'option': '-t', 'value': 'TS distribution'},
  297 + {'option': '-p', 'value': 'pdf'},
  298 + {'option': '-e', 'value': ''},
  299 + {'option': '-f', 'value': ''}]
244 300  
245 301 # Gather parameters from command line
246 302 i = 2
... ... @@ -254,27 +310,29 @@ if __name__ == &#39;__main__&#39;:
254 310 try:
255 311 par['value'] = sys.argv[i]
256 312 except:
257   - sys.stdout.write(usage+"\n")
  313 + print(usage)
258 314 sys.exit()
259 315 else:
260   - sys.stdout.write(usage+"\n")
  316 + print(usage)
261 317 sys.exit()
262 318  
263 319 # Next item
264 320 i += 1
265 321  
266 322 # Recover parameters
267   - nbins = int(pars[0]['value'])
268   - tsname = pars[1]['value']
269   - title = pars[2]['value']
270   - plot = pars[3]['value']
  323 + nbins = int(pars[0]['value'])
  324 + tsname = pars[1]['value']
  325 + title = pars[2]['value']
  326 + plot = pars[3]['value']
  327 + expect = pars[4]['value']
  328 + plotfile = pars[5]['value']
271 329  
272 330 # Read values from CSV file
273 331 values = read_ts(filename, tsname=tsname)
274   - sys.stdout.write(len(values), "values read.\n")
  332 + print('%d values read.' % len(values))
275 333  
276 334 # Show histogram
277   - if plot == "pdf":
278   - dist_pdf(values, nbins, title)
  335 + if plot == 'pdf':
  336 + dist_pdf(values, nbins, title, expect=expect, plotfile=plotfile)
279 337 else:
280   - dist_cdf(values, nbins, title)
  338 + dist_cdf(values, nbins, title, expect=expect, plotfile=plotfile)
... ...
test/README.md
  View file @8590d48
1   -
2 1 ctools unit test
3 2 ================
4 3  
5 4 This folder contains files used for ctools unit testing.
6   -test_cscripts.sh
... ...
test/data/sensitivity.dat 0 → 100644
  View file @8590d48
  1 +loge,emin,emax,crab_flux,photon_flux,energy_flux,sensitivity
  2 +-1.51402150412,0.02,0.0468734582318,0.144989163852,6.60543533444e-10,3.05652923293e-11,3.56378721075e-11
  3 +-1.14412450369,0.0468734582318,0.109856054331,0.0561134683318,7.24745374549e-11,7.85976500012e-12,9.16416230711e-12
  4 +-0.774227503252,0.109856054331,0.257466658709,0.0315037806261,1.15354211075e-11,2.93193651747e-12,3.41851723554e-12
  5 +-0.404330502818,0.257466658709,0.603417633655,0.0244879762385,2.54200331885e-12,1.51423828719e-12,1.76553948308e-12
  6 +-0.0344335023848,0.603417633655,1.41421356237,0.022256802649,6.54995675049e-13,9.14436478628e-13,1.0661952755e-12
  7 +0.335463498049,1.41421356237,3.31445401734,0.0250217133244,2.08758967789e-13,6.83057479879e-13,7.96416891675e-13
  8 +0.705360498482,3.31445401734,7.76799609716,0.042333217441,1.00129446033e-13,7.67840339358e-13,8.95270214276e-13
  9 +1.07525749892,7.76799609716,18.2056420303,0.0929194773185,6.23074149979e-14,1.11981387734e-12,1.30565686449e-12
  10 +1.44515449935,18.2056420303,42.6680700645,0.14972962577,2.8463818009e-14,1.19893673197e-12,1.39791085453e-12
  11 +1.81505149978,42.6680700645,100.0,0.382388032371,2.06082989569e-14,2.03442769003e-12,2.37205890421e-12
... ...
test/data/spectrum.fits 0 → 100644
View file @8590d48
No preview for this file type
test/data/ts.dat 0 → 100644
  View file @8590d48
  1 +TS,LogL_bgm,LogL_all,Nevents,Npred_bkg,Npred_all,Crab_Prefactor,Unc_Crab_Prefactor,CTABackgroundModel_Prefactor,Unc_CTABackgroundModel_Prefactor,CTABackgroundModel_Index,Unc_CTABackgroundModel_Index
  2 +21858.52363364247,164117.78313692164,153188.5213201004,22947.0,22946.99999940957,22946.999182570653,5.793209910482599e-16,9.843787551860997e-18,0.9961007850466849,0.01197837072408249,-0.002988471615299611,0.007462197925324776
  3 +22254.447332882788,165680.6922036114,154553.46853717,23099.0,23098.999999613512,23098.998093109363,5.834991758798705e-16,9.870580046002392e-18,1.0126678419515491,0.011967610062684665,0.004782477384744285,0.007316347479857281
  4 +21669.561687524547,165499.35987704716,154664.57903328488,23134.0,23133.99999969615,23133.999315025623,5.759131518978944e-16,9.8078414532141e-18,1.0105363690914626,0.011967661087729033,-0.00017543331960004447,0.0073220367405137776
  5 +20586.996292978816,164330.2704312009,154036.77228471148,22897.0,22896.999999836524,22896.997968569693,5.555266953291272e-16,9.65303499566792e-18,1.0126646529020689,0.011972560615151874,0.005782431464096715,0.007323711254845693
  6 +21217.911190702056,163471.7261244653,152862.77052911426,22869.0,22868.999999925014,22868.99897334564,5.70225985492044e-16,9.781422622377391e-18,0.9910189865469351,0.011911721710682954,-0.006124951668038474,0.007435839123654169
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... ...
test/dev/README.md 0 → 100644
  View file @8590d48
  1 +Developer test scripts
  2 +======================
  3 +
  4 +This folder contains scripts that are used for various testing purposes
  5 +during code development. None of the scripts actually needs to work, they
  6 +may actually be outdated, but could still be useful for further testing
  7 +if needed.
  8 +
  9 +`benchmark_cta_analysis.py`
  10 +> This script peforms a benchmark of the various CTA analysis types
  11 +> (unbinned, binned, stacked), and if matplotlib is installed, creates
  12 +> a plot of the benchmark results.
  13 +
  14 +`check_models.py`
  15 +> Checks a variety of models using an unbinned analysis.
  16 +
  17 +`make_pull_at_sensitivity_limit.py`
  18 +> This script creates pull distributions as function of energy
  19 +> for a test source that is at the 5 sigma sensitivity limit for
  20 +> 50h of effective observing time. It takes as input file the
  21 +> output file generated using cspull.
  22 +> If the Python processing module is installed the script can make
  23 +> use of multiple cores and runs in parallel.
  24 +
  25 +`make_survey.py`
  26 +> This script simulates a CTA galactic plane survey.
  27 +
  28 +`simulate_events.py`
  29 +> Simulates events and compares the simulation to the model.
  30 +
... ...
test/test_examples.py
  View file @8590d48
... ... @@ -104,6 +104,10 @@ class Test(gammalib.GPythonTestSuite):
104 104 self.append(self.test_show_pha, 'Test show_pha.py')
105 105 self.append(self.test_show_pull_evolution, 'Test show_pull_evolution.py')
106 106 self.append(self.test_show_pull_histogram, 'Test show_pull_histogram.py')
  107 + self.append(self.test_show_response, 'Test test_show_response.py')
  108 + self.append(self.test_show_sensitivity, 'Test test_show_sensitivity.py')
  109 + self.append(self.test_show_spectrum, 'Test test_show_spectrum.py')
  110 + self.append(self.test_show_ts_distribution, 'Test show_ts_distribution.py')
107 111  
108 112 # Return
109 113 return
... ... @@ -253,7 +257,8 @@ class Test(gammalib.GPythonTestSuite):
253 257 """
254 258 # Execute script
255 259 self._execute_python('show_butterfly',
256   - args='data/butterfly.txt example_butterfly.eps')
  260 + args='data/butterfly.txt '
  261 + 'example_show_butterfly.eps')
257 262  
258 263 #TODO: Do any testing
259 264  
... ... @@ -267,7 +272,7 @@ class Test(gammalib.GPythonTestSuite):
267 272 """
268 273 # Execute script
269 274 self._execute_python('show_model',
270   - args='data/crab.xml Crab example_model.eps')
  275 + args='data/crab.xml Crab example_show_model.eps')
271 276  
272 277 #TODO: Do any testing
273 278  
... ... @@ -280,7 +285,8 @@ class Test(gammalib.GPythonTestSuite):
280 285 Test show_pha
281 286 """
282 287 # Execute script
283   - self._execute_python('show_pha', args='data/pha.fits example_pha.eps')
  288 + self._execute_python('show_pha',
  289 + args='data/pha.fits example_show_pha.eps')
284 290  
285 291 #TODO: Do any testing
286 292  
... ... @@ -295,7 +301,7 @@ class Test(gammalib.GPythonTestSuite):
295 301 # Execute script
296 302 self._execute_python('show_pull_evolution',
297 303 args='data/pull.dat Pull_Crab_Prefactor '
298   - 'example_pull_evolution.eps')
  304 + 'example_show_pull_evolution.eps')
299 305  
300 306 #TODO: Do any testing
301 307  
... ... @@ -310,7 +316,65 @@ class Test(gammalib.GPythonTestSuite):
310 316 # Execute script
311 317 self._execute_python('show_pull_histogram',
312 318 args='data/pull.dat Pull_Crab_Prefactor 50 '
313   - 'example_pull_histogram.eps')
  319 + 'example_show_pull_histogram.eps')
  320 +
  321 + #TODO: Do any testing
  322 +
  323 + # Return
  324 + return
  325 +
  326 + # Test show_response
  327 + def test_show_response(self):
  328 + """
  329 + Test show_response
  330 + """
  331 + # Execute script
  332 + self._execute_python('show_response', args='example_show_response.eps')
  333 +
  334 + #TODO: Do any testing
  335 +
  336 + # Return
  337 + return
  338 +
  339 + # Test show_sensitivity
  340 + def test_show_sensitivity(self):
  341 + """
  342 + Test show_sensitivity
  343 + """
  344 + # Execute script
  345 + self._execute_python('show_sensitivity',
  346 + args='data/sensitivity.dat '
  347 + 'example_show_sensitivity.eps')
  348 +
  349 + #TODO: Do any testing
  350 +
  351 + # Return
  352 + return
  353 +
  354 + # Test show_spectrum
  355 + def test_show_spectrum(self):
  356 + """
  357 + Test show_spectrum
  358 + """
  359 + # Execute script
  360 + self._execute_python('show_spectrum',
  361 + args='data/spectrum.fits '
  362 + 'example_show_spectrum.eps')
  363 +
  364 + #TODO: Do any testing
  365 +
  366 + # Return
  367 + return
  368 +
  369 + # Test show_ts_distribution
  370 + def test_show_ts_distribution(self):
  371 + """
  372 + Test show_ts_distribution
  373 + """
  374 + # Execute script
  375 + self._execute_python('show_ts_distribution',
  376 + args='data/ts.dat -n 100 '
  377 + '-f example_show_ts_distribution.eps')
314 378  
315 379 #TODO: Do any testing
316 380  
... ...