Commit 35fceede88bafd6b65cde46aedbed7d256acae6f
1 parent
ed19ef6c
Adapt test scripts to new GCaldb interface.
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3 changed files
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13 additions
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54 deletions
inst/cta/test/example_binned_ml_fit.py
| ... | ... | @@ -2,7 +2,7 @@ |
| 2 | 2 | # ========================================================================== |
| 3 | 3 | # This script performs a binned maximum likelihood analysis of CTA data. |
| 4 | 4 | # |
| 5 | -# Copyright (C) 2012 Juergen Knoedlseder | |
| 5 | +# Copyright (C) 2012-2014 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 |
| ... | ... | @@ -109,13 +109,13 @@ if __name__ == '__main__': |
| 109 | 109 | print("... please wait for a few seconds") |
| 110 | 110 | |
| 111 | 111 | # Set parameters |
| 112 | - irf = "kb_E_50h_v3" | |
| 112 | + irf = "cta_dummy_irf" | |
| 113 | 113 | caldb = "../caldb" |
| 114 | 114 | model = "data/crab.xml" |
| 115 | 115 | cntmap = "data/crab_cntmap.fits" |
| 116 | 116 | |
| 117 | 117 | # Perform binned analysis |
| 118 | - result = binned_analysis(model, cntmap, irf, caldb) | |
| 118 | + result = binned_analysis(model, cntmap, irf, GCaldb(caldb)) | |
| 119 | 119 | |
| 120 | 120 | # Print model results |
| 121 | 121 | print(result) | ... | ... |
inst/cta/test/example_sim_psf.py
| 1 | 1 | #! /usr/bin/env python |
| 2 | 2 | # ========================================================================== |
| 3 | -# This script simulated the PSF distribution. | |
| 3 | +# This script simulates the PSF distribution. | |
| 4 | 4 | # |
| 5 | -# Based on the MAGIC spectrum of the Crab nebula, and by assuming a powerlaw, | |
| 6 | -# it will create a Monte Carlo sample of photons. | |
| 7 | -# | |
| 8 | -# If matplotlib is installed, the spectrum will be displayed on the screen. | |
| 5 | +# If matplotlib is installed, the PSF will be displayed on the screen. | |
| 9 | 6 | # |
| 10 | 7 | # -------------------------------------------------------------------------- |
| 11 | 8 | # |
| 12 | -# Copyright (C) 2013 Juergen Knoedlseder | |
| 9 | +# Copyright (C) 2013-2014 Juergen Knoedlseder | |
| 13 | 10 | # |
| 14 | 11 | # This program is free software: you can redistribute it and/or modify |
| 15 | 12 | # it under the terms of the GNU General Public License as published by |
| ... | ... | @@ -29,47 +26,9 @@ from gammalib import * |
| 29 | 26 | from math import * |
| 30 | 27 | |
| 31 | 28 | |
| 32 | -# ======================== # | |
| 33 | -# Simulate CTA observation # | |
| 34 | -# ======================== # | |
| 35 | -def simulate(xmlname, e_min, e_max, area, duration): | |
| 36 | - """ | |
| 37 | - Simulate CTA observation. | |
| 38 | - """ | |
| 39 | - # Allocate MC parameters | |
| 40 | - dir = GSkyDir() | |
| 41 | - emin = GEnergy() | |
| 42 | - emax = GEnergy() | |
| 43 | - tmin = GTime(0.0) | |
| 44 | - tmax = GTime(duration) | |
| 45 | - | |
| 46 | - # Define MC parameters | |
| 47 | - dir.radec_deg(83.6331, 22.0145) | |
| 48 | - radius = 10.0 | |
| 49 | - emin.TeV(e_min) | |
| 50 | - emax.TeV(e_max) | |
| 51 | - | |
| 52 | - # Allocate random number generator | |
| 53 | - ran = GRan() | |
| 54 | - | |
| 55 | - # Load models and extract first model | |
| 56 | - models = GModels(xmlname) | |
| 57 | - model = models[0] | |
| 58 | - print(model) | |
| 59 | - | |
| 60 | - # Simulate photons | |
| 61 | - photons = model.mc(area, dir, radius, emin, emax, tmin, tmax, ran) | |
| 62 | - | |
| 63 | - # Print photons | |
| 64 | - print(str(len(photons)) + " photons simulated.") | |
| 65 | - | |
| 66 | - # Return photons | |
| 67 | - return photons | |
| 68 | - | |
| 69 | - | |
| 70 | -# ======== # | |
| 71 | -# Show PSF # | |
| 72 | -# ======== # | |
| 29 | +# ============ # | |
| 30 | +# Simulate PSF # | |
| 31 | +# ============ # | |
| 73 | 32 | def sim_psf(response, energy, r_max=0.8, rbins=1000, nmc=1000000): |
| 74 | 33 | """ |
| 75 | 34 | Simulate PSF and show results using matplotlib (if available). |
| ... | ... | @@ -160,8 +119,8 @@ if __name__ == '__main__': |
| 160 | 119 | print("****************") |
| 161 | 120 | |
| 162 | 121 | # Load response |
| 163 | - rsp = GCTAResponse("irf_test.fits", | |
| 164 | - "../caldb/data/cta/e/bcf/000002") | |
| 122 | + rsp = GCTAResponse("irf_file.fits", | |
| 123 | + GCaldb("../caldb/data/cta/e/bcf/IFAE20120510_50h_King")) | |
| 165 | 124 | |
| 166 | 125 | # Simulate PSF |
| 167 | 126 | sim_psf(rsp, 1.0) | ... | ... |
inst/cta/test/test_model.py
| ... | ... | @@ -2,7 +2,7 @@ |
| 2 | 2 | # ========================================================================== |
| 3 | 3 | # This script tests the model computations using the CTA response function. |
| 4 | 4 | # |
| 5 | -# Copyright (C) 2011-2013 Jurgen Knodlseder | |
| 5 | +# Copyright (C) 2011-2014 Jurgen Knodlseder | |
| 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 |
| ... | ... | @@ -150,7 +150,7 @@ def observation(ra=0.0, dec=0.0, emin=0.1, emax=100.0, |
| 150 | 150 | obs = GCTAObservation() |
| 151 | 151 | |
| 152 | 152 | # Set response |
| 153 | - obs.response("kb_E_50h_v3", "../caldb") | |
| 153 | + obs.response("cta_dummy_irf", GCaldb("../caldb")) | |
| 154 | 154 | |
| 155 | 155 | # Set pointing |
| 156 | 156 | dir = GSkyDir() | ... | ... |