Veronika Vodeb / ctools

Commit 3e80f4637d56996b08fdcc83a3370e177a779a8c

Authored by Jürgen Knödlseder
1 parent 2e97e659

Update Fermi-LAT How-tos

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Showing 8 changed files with 257 additions and 219 deletions
doc/source/users/tutorials/howto/fermi/howto_fermi_errors.rst
  View file @3e80f46
... ... @@ -31,56 +31,82 @@ that was created by :ref:`cterror`. As you will see, the parameter errors
31 31 are essentially symmetric and very close to the values determined using the
32 32 covariance matrix.
33 33  
34   -.. code-block:: bash
  34 +.. code-block:: none
35 35  
36   - 2017-08-26T14:16:00: +=======================================================+
37   - 2017-08-26T14:16:00: | Compute error for source "Vela" parameter "Prefactor" |
38   - 2017-08-26T14:16:00: +=======================================================+
39   - 2017-08-26T14:16:00: Confidence level ..........: 68 %
40   - 2017-08-26T14:16:00: Log-likelihood difference .: 0.494473
41   - 2017-08-26T14:16:00: Initial factor range ......: [1e-07, 9.10916268820218]
42   - 2017-08-26T14:16:20: Lower parameter factor ....: 3.93549
43   - 2017-08-26T14:16:20: Upper parameter factor ....: 4.89285
44   - 2017-08-26T14:16:20: Error from curvature ......: 4.75365104151534e-10 ph/cm2/s/MeV
45   - 2017-08-26T14:16:20: Error from profile ........: 4.78682555317737e-10 ph/cm2/s/MeV
46   - 2017-08-26T14:16:20: Negative profile error ....: 4.20026137925122e-10 ph/cm2/s/MeV
47   - 2017-08-26T14:16:20: Positive profile error ....: 5.37338972710351e-10 ph/cm2/s/MeV
48   - 2017-08-26T14:16:20:
49   - 2017-08-26T14:16:20: +====================================================+
50   - 2017-08-26T14:16:20: | Compute error for source "Vela" parameter "Index1" |
51   - 2017-08-26T14:16:20: +====================================================+
52   - 2017-08-26T14:16:20: Confidence level ..........: 68 %
53   - 2017-08-26T14:16:20: Log-likelihood difference .: 0.494473
54   - 2017-08-26T14:16:20: Initial factor range ......: [1.03221907174349, 1.65479046234989]
55   - 2017-08-26T14:16:42: Lower parameter factor ....: 1.31121
56   - 2017-08-26T14:16:42: Upper parameter factor ....: 1.37307
57   - 2017-08-26T14:16:42: Error from curvature ......: 0.03112856953032
58   - 2017-08-26T14:16:42: Error from profile ........: 0.0309309760713872
59   - 2017-08-26T14:16:42: Negative profile error ....: 0.0322989307870749
60   - 2017-08-26T14:16:42: Positive profile error ....: 0.0295630213556994
61   - 2017-08-26T14:16:42:
62   - 2017-08-26T14:16:42: +==========================================================+
63   - 2017-08-26T14:16:42: | Compute error for source "Vela" parameter "CutoffEnergy" |
64   - 2017-08-26T14:16:42: +==========================================================+
65   - 2017-08-26T14:16:42: Confidence level ..........: 68 %
66   - 2017-08-26T14:16:42: Log-likelihood difference .: 0.494473
67   - 2017-08-26T14:16:42: Initial factor range ......: [0.001, 2.8071605417966]
68   - 2017-08-26T14:17:02: Lower parameter factor ....: 0.813181
69   - 2017-08-26T14:17:02: Upper parameter factor ....: 1.17404
70   - 2017-08-26T14:17:02: Error from curvature ......: 181.871842544747 MeV
71   - 2017-08-26T14:17:02: Error from profile ........: 180.431484426618 MeV
72   - 2017-08-26T14:17:02: Negative profile error ....: 175.261332662553 MeV
73   - 2017-08-26T14:17:02: Positive profile error ....: 185.601636190684 MeV
74   - 2017-08-26T14:17:02:
75   - 2017-08-26T14:17:02: +====================================================+
76   - 2017-08-26T14:17:02: | Compute error for source "Vela" parameter "Index2" |
77   - 2017-08-26T14:17:02: +====================================================+
78   - 2017-08-26T14:17:02: Confidence level ..........: 68 %
79   - 2017-08-26T14:17:02: Log-likelihood difference .: 0.494473
80   - 2017-08-26T14:17:02: Initial factor range ......: [0.307804018748382, 0.866425033775455]
81   - 2017-08-26T14:17:24: Lower parameter factor ....: 0.559156
82   - 2017-08-26T14:17:24: Upper parameter factor ....: 0.615141
83   - 2017-08-26T14:17:24: Error from curvature ......: 0.0279310507513537
84   - 2017-08-26T14:17:24: Error from profile ........: 0.0279924226890397
85   - 2017-08-26T14:17:24: Negative profile error ....: 0.027958327168103
86   - 2017-08-26T14:17:24: Positive profile error ....: 0.0280265182099764
  36 + 2018-01-25T20:45:22: +================================================+
  37 + 2018-01-25T20:45:22: | Compute error for source "Vela" parameter "RA" |
  38 + 2018-01-25T20:45:22: +================================================+
  39 + 2018-01-25T20:45:22: Confidence level ..........: 68 %
  40 + 2018-01-25T20:45:22: Log-likelihood difference .: 0.494473
  41 + 2018-01-25T20:45:22: Initial factor range ......: [128.819554251926, 128.851989886434]
  42 + 2018-01-25T20:45:41: Lower parameter factor ....: 128.834
  43 + 2018-01-25T20:45:41: Upper parameter factor ....: 128.837
  44 + 2018-01-25T20:45:41: Error from curvature ......: 0.00162178172537938 deg
  45 + 2018-01-25T20:45:41: Error from profile ........: 0.00169067577327553 deg
  46 + 2018-01-25T20:45:41: Negative profile error ....: 0.00165900034895117 deg
  47 + 2018-01-25T20:45:41: Positive profile error ....: 0.00172235119759989 deg
  48 + 2018-01-25T20:45:41:
  49 + 2018-01-25T20:45:41: +=================================================+
  50 + 2018-01-25T20:45:41: | Compute error for source "Vela" parameter "DEC" |
  51 + 2018-01-25T20:45:41: +=================================================+
  52 + 2018-01-25T20:45:41: Confidence level ..........: 68 %
  53 + 2018-01-25T20:45:41: Log-likelihood difference .: 0.494473
  54 + 2018-01-25T20:45:41: Initial factor range ......: [-45.1949881923928, -45.1721741961801]
  55 + 2018-01-25T20:46:01: Lower parameter factor ....: -45.1847
  56 + 2018-01-25T20:46:01: Upper parameter factor ....: -45.1824
  57 + 2018-01-25T20:46:01: Error from curvature ......: 0.00114069981063169 deg
  58 + 2018-01-25T20:46:01: Error from profile ........: 0.00116548552428952 deg
  59 + 2018-01-25T20:46:01: Negative profile error ....: 0.00115852324517363 deg
  60 + 2018-01-25T20:46:01: Positive profile error ....: 0.00117244780340542 deg
  61 + 2018-01-25T20:46:01:
  62 + 2018-01-25T20:46:01: +=======================================================+
  63 + 2018-01-25T20:46:01: | Compute error for source "Vela" parameter "Prefactor" |
  64 + 2018-01-25T20:46:01: +=======================================================+
  65 + 2018-01-25T20:46:01: Confidence level ..........: 68 %
  66 + 2018-01-25T20:46:01: Log-likelihood difference .: 0.494473
  67 + 2018-01-25T20:46:01: Initial factor range ......: [1e-07, 9.09784331905335]
  68 + 2018-01-25T20:46:45: Lower parameter factor ....: 3.93674
  69 + 2018-01-25T20:46:45: Upper parameter factor ....: 4.89558
  70 + 2018-01-25T20:46:45: Error from curvature ......: 4.74564602380296e-10 ph/cm2/s/MeV
  71 + 2018-01-25T20:46:45: Error from profile ........: 4.79421031311828e-10 ph/cm2/s/MeV
  72 + 2018-01-25T20:46:45: Negative profile error ....: 4.15456324058327e-10 ph/cm2/s/MeV
  73 + 2018-01-25T20:46:45: Positive profile error ....: 5.4338573856533e-10 ph/cm2/s/MeV
  74 + 2018-01-25T20:46:45:
  75 + 2018-01-25T20:46:45: +====================================================+
  76 + 2018-01-25T20:46:45: | Compute error for source "Vela" parameter "Index1" |
  77 + 2018-01-25T20:46:45: +====================================================+
  78 + 2018-01-25T20:46:45: Confidence level ..........: 68 %
  79 + 2018-01-25T20:46:45: Log-likelihood difference .: 0.494473
  80 + 2018-01-25T20:46:45: Initial factor range ......: [1.0323933217421, 1.65461803910864]
  81 + 2018-01-25T20:47:31: Lower parameter factor ....: 1.31084
  82 + 2018-01-25T20:47:31: Upper parameter factor ....: 1.37275
  83 + 2018-01-25T20:47:31: Error from curvature ......: 0.0311112358683271
  84 + 2018-01-25T20:47:31: Error from profile ........: 0.0309517300203693
  85 + 2018-01-25T20:47:31: Negative profile error ....: 0.032660721248488
  86 + 2018-01-25T20:47:31: Positive profile error ....: 0.0292427387922507
  87 + 2018-01-25T20:47:31:
  88 + 2018-01-25T20:47:31: +==========================================================+
  89 + 2018-01-25T20:47:31: | Compute error for source "Vela" parameter "CutoffEnergy" |
  90 + 2018-01-25T20:47:31: +==========================================================+
  91 + 2018-01-25T20:47:31: Confidence level ..........: 68 %
  92 + 2018-01-25T20:47:31: Log-likelihood difference .: 0.494473
  93 + 2018-01-25T20:47:31: Initial factor range ......: [0.001, 2.80853448949703]
  94 + 2018-01-25T20:48:14: Lower parameter factor ....: 0.81239
  95 + 2018-01-25T20:48:14: Upper parameter factor ....: 1.17294
  96 + 2018-01-25T20:48:14: Error from curvature ......: 181.899981380157 MeV
  97 + 2018-01-25T20:48:14: Error from profile ........: 180.277267463442 MeV
  98 + 2018-01-25T20:48:14: Negative profile error ....: 177.144641591912 MeV
  99 + 2018-01-25T20:48:14: Positive profile error ....: 183.409893334972 MeV
  100 + 2018-01-25T20:48:14:
  101 + 2018-01-25T20:48:14: +====================================================+
  102 + 2018-01-25T20:48:14: | Compute error for source "Vela" parameter "Index2" |
  103 + 2018-01-25T20:48:14: +====================================================+
  104 + 2018-01-25T20:48:14: Confidence level ..........: 68 %
  105 + 2018-01-25T20:48:14: Log-likelihood difference .: 0.494473
  106 + 2018-01-25T20:48:14: Initial factor range ......: [0.308028525758507, 0.866644263529458]
  107 + 2018-01-25T20:49:01: Lower parameter factor ....: 0.559037
  108 + 2018-01-25T20:49:01: Upper parameter factor ....: 0.615056
  109 + 2018-01-25T20:49:01: Error from curvature ......: 0.0279307868885475
  110 + 2018-01-25T20:49:01: Error from profile ........: 0.0280092058458762
  111 + 2018-01-25T20:49:01: Negative profile error ....: 0.028299015036004
  112 + 2018-01-25T20:49:01: Positive profile error ....: 0.0277193966557485
... ...
doc/source/users/tutorials/howto/fermi/howto_fermi_fitting.rst
  View file @3e80f46
... ... @@ -47,8 +47,8 @@ extragalactic isotropic source component.
47 47 <parameter name="Index2" scale="1.0" value="0.5" min="0.1" max="5.0" free="1"/>
48 48 </spectrum>
49 49 <spatialModel type="PointSource">
50   - <parameter name="RA" scale="1.0" value="128.84" min="-360" max="360" free="0"/>
51   - <parameter name="DEC" scale="1.0" value="-45.18" min="-90" max="90" free="0"/>
  50 + <parameter name="RA" scale="1.0" value="128.84" min="-360" max="360" free="1"/>
  51 + <parameter name="DEC" scale="1.0" value="-45.18" min="-90" max="90" free="1"/>
52 52 </spatialModel>
53 53 </source>
54 54 <source type="DiffuseSource" name="Galactic_diffuse">
... ... @@ -92,96 +92,95 @@ log file ``ctlike.log`` that was also created by :ref:`ctlike`:
92 92  
93 93 .. code-block:: none
94 94  
95   - 2017-08-26T10:35:10: +=================================+
96   - 2017-08-26T10:35:10: | Maximum likelihood optimisation |
97   - 2017-08-26T10:35:10: +=================================+
98   - 2017-08-26T10:35:12: >Iteration 0: -logL=-177232.327, Lambda=1.0e-03
99   - 2017-08-26T10:35:12: >Iteration 1: -logL=-198931.081, Lambda=1.0e-03, delta=21698.754, step=1.0e+00, max(|grad|)=-22713.401202 [CutoffEnergy:4]
100   - 2017-08-26T10:35:12: >Iteration 2: -logL=-200263.519, Lambda=1.0e-04, delta=1332.438, step=1.0e+00, max(|grad|)=-67648.133552 [CutoffEnergy:4]
101   - 2017-08-26T10:35:12: >Iteration 3: -logL=-212350.035, Lambda=1.0e-05, delta=12086.515, step=1.0e+00, max(|grad|)=23036.151920 [Index2:6]
102   - 2017-08-26T10:35:12: >Iteration 4: -logL=-213951.781, Lambda=1.0e-06, delta=1601.746, step=1.0e+00, max(|grad|)=-8297.648633 [CutoffEnergy:4]
103   - 2017-08-26T10:35:13: >Iteration 5: -logL=-215341.362, Lambda=1.0e-07, delta=1389.581, step=1.0e+00, max(|grad|)=2747.034517 [Index2:6]
104   - 2017-08-26T10:35:13: >Iteration 6: -logL=-215490.429, Lambda=1.0e-08, delta=149.067, step=1.0e+00, max(|grad|)=697.301361 [Index2:6]
105   - 2017-08-26T10:35:13: Iteration 7: -logL=-215490.429, Lambda=1.0e-09, delta=-14.065, step=1.0e+00, max(|grad|)=-1205.683279 [Index1:3] (stalled)
106   - 2017-08-26T10:35:13: Iteration 8: -logL=-215490.429, Lambda=1.0e-08, delta=-14.064, step=1.0e+00, max(|grad|)=-1205.659884 [Index1:3] (stalled)
107   - 2017-08-26T10:35:14: Iteration 9: -logL=-215490.429, Lambda=1.0e-07, delta=-14.055, step=1.0e+00, max(|grad|)=-1205.425967 [Index1:3] (stalled)
108   - 2017-08-26T10:35:14: Iteration 10: -logL=-215490.429, Lambda=1.0e-06, delta=-13.963, step=1.0e+00, max(|grad|)=-1203.090620 [Index1:3] (stalled)
109   - 2017-08-26T10:35:14: Iteration 11: -logL=-215490.429, Lambda=1.0e-05, delta=-13.066, step=1.0e+00, max(|grad|)=-1180.113526 [Index1:3] (stalled)
110   - 2017-08-26T10:35:14: Iteration 12: -logL=-215490.429, Lambda=1.0e-04, delta=-6.263, step=1.0e+00, max(|grad|)=-983.079153 [Index1:3] (stalled)
111   - 2017-08-26T10:35:14: >Iteration 13: -logL=-215496.367, Lambda=1.0e-03, delta=5.937, step=1.0e+00, max(|grad|)=-285.734284 [Index1:3]
112   - 2017-08-26T10:35:15: Iteration 14: -logL=-215496.367, Lambda=1.0e-04, delta=-8.812, step=1.0e+00, max(|grad|)=-731.894749 [Index1:3] (stalled)
113   - 2017-08-26T10:35:15: >Iteration 15: -logL=-215497.536, Lambda=1.0e-03, delta=1.169, step=1.0e+00, max(|grad|)=-153.668138 [Index1:3]
114   - 2017-08-26T10:35:15: Iteration 16: -logL=-215496.136, Lambda=1.0e-04, delta=-1.400, step=1.0e+00, max(|grad|)=-328.522942 [Index1:3] (stalled)
115   - 2017-08-26T10:35:15: >Iteration 17: -logL=-215498.376, Lambda=1.0e-03, delta=2.240, step=1.0e+00, max(|grad|)=3.257091 [Index2:6]
116   - 2017-08-26T10:35:16: >Iteration 18: -logL=-215498.383, Lambda=1.0e-04, delta=0.007, step=1.0e+00, max(|grad|)=-8.270351 [CutoffEnergy:4]
117   - 2017-08-26T10:35:16: >Iteration 19: -logL=-215498.384, Lambda=1.0e-05, delta=0.002, step=1.0e+00, max(|grad|)=0.637485 [Index2:6]
118   - 2017-08-26T10:35:16:
119   - 2017-08-26T10:35:16: +=========================================+
120   - 2017-08-26T10:35:16: | Maximum likelihood optimisation results |
121   - 2017-08-26T10:35:16: +=========================================+
122   - 2017-08-26T10:35:16: === GOptimizerLM ===
123   - 2017-08-26T10:35:16: Optimized function value ..: -215498.384
124   - 2017-08-26T10:35:16: Absolute precision ........: 0.005
125   - 2017-08-26T10:35:16: Acceptable value decrease .: 2
126   - 2017-08-26T10:35:16: Optimization status .......: converged
127   - 2017-08-26T10:35:16: Number of parameters ......: 14
128   - 2017-08-26T10:35:16: Number of free parameters .: 5
129   - 2017-08-26T10:35:16: Number of iterations ......: 19
130   - 2017-08-26T10:35:16: Lambda ....................: 1e-06
131   - 2017-08-26T10:35:16: Maximum log likelihood ....: 215498.384
132   - 2017-08-26T10:35:16: Observed events (Nobs) ...: 202330.000
133   - 2017-08-26T10:35:16: Predicted events (Npred) ..: 202318.082 (Nobs - Npred = 11.9178772509331)
134   - 2017-08-26T10:35:16: === GModels ===
135   - 2017-08-26T10:35:16: Number of models ..........: 3
136   - 2017-08-26T10:35:16: Number of parameters ......: 14
137   - 2017-08-26T10:35:16: === GModelSky ===
138   - 2017-08-26T10:35:16: Name ......................: Vela
139   - 2017-08-26T10:35:16: Instruments ...............: all
140   - 2017-08-26T10:35:16: Instrument scale factors ..: unity
141   - 2017-08-26T10:35:16: Observation identifiers ...: all
142   - 2017-08-26T10:35:16: Model type ................: PointSource
143   - 2017-08-26T10:35:16: Model components ..........: "PointSource" * "SuperExponentialCutoffPowerLaw" * "Constant"
144   - 2017-08-26T10:35:16: Number of parameters ......: 8
145   - 2017-08-26T10:35:16: Number of spatial par's ...: 2
146   - 2017-08-26T10:35:16: RA .......................: 128.84 [-360,360] deg (fixed,scale=1)
147   - 2017-08-26T10:35:16: DEC ......................: -45.18 [-90,90] deg (fixed,scale=1)
148   - 2017-08-26T10:35:16: Number of spectral par's ..: 5
149   - 2017-08-26T10:35:16: Prefactor ................: 4.3553344038324e-09 +/- 4.75309654008435e-10 [1e-16,1e-06] ph/cm2/s/MeV (free,scale=1e-09,gradient)
150   - 2017-08-26T10:35:16: Index1 ...................: -1.3435116067011 +/- 0.0311270092486095 [-0,-5] (free,scale=-1,gradient)
151   - 2017-08-26T10:35:16: CutoffEnergy .............: 988.499237722443 +/- 181.86709257978 [1,1000000] MeV (free,scale=1000,gradient)
152   - 2017-08-26T10:35:16: PivotEnergy ..............: 1000 [10,1000000] MeV (fixed,scale=1000,gradient)
153   - 2017-08-26T10:35:16: Index2 ...................: 0.587129723482927 +/- 0.0279303486200403 [0.1,5] (free,scale=1,gradient)
154   - 2017-08-26T10:35:16: Number of temporal par's ..: 1
155   - 2017-08-26T10:35:16: Normalization ............: 1 (relative value) (fixed,scale=1,gradient)
156   - 2017-08-26T10:35:16: === GModelSky ===
157   - 2017-08-26T10:35:16: Name ......................: Galactic_diffuse
158   - 2017-08-26T10:35:16: Instruments ...............: all
159   - 2017-08-26T10:35:16: Instrument scale factors ..: unity
160   - 2017-08-26T10:35:16: Observation identifiers ...: all
161   - 2017-08-26T10:35:16: Model type ................: DiffuseSource
162   - 2017-08-26T10:35:16: Model components ..........: "DiffuseMapCube" * "Constant" * "Constant"
163   - 2017-08-26T10:35:16: Number of parameters ......: 3
164   - 2017-08-26T10:35:16: Number of spatial par's ...: 1
165   - 2017-08-26T10:35:16: Normalization ............: 1 [0.1,10] (fixed,scale=1,gradient)
166   - 2017-08-26T10:35:16: Number of spectral par's ..: 1
167   - 2017-08-26T10:35:16: Normalization ............: 1.10915296009432 +/- 0.00503367301009883 [0.1,1000] (free,scale=1,gradient)
168   - 2017-08-26T10:35:16: Number of temporal par's ..: 1
169   - 2017-08-26T10:35:16: Normalization ............: 1 (relative value) (fixed,scale=1,gradient)
170   - 2017-08-26T10:35:16: === GModelSky ===
171   - 2017-08-26T10:35:16: Name ......................: Extragalactic_diffuse
172   - 2017-08-26T10:35:16: Instruments ...............: all
173   - 2017-08-26T10:35:16: Instrument scale factors ..: unity
174   - 2017-08-26T10:35:16: Observation identifiers ...: all
175   - 2017-08-26T10:35:16: Model type ................: DiffuseSource
176   - 2017-08-26T10:35:16: Model components ..........: "DiffuseIsotropic" * "FileFunction" * "Constant"
177   - 2017-08-26T10:35:16: Number of parameters ......: 3
178   - 2017-08-26T10:35:16: Number of spatial par's ...: 1
179   - 2017-08-26T10:35:16: Value ....................: 1 [0,10] (fixed,scale=1,gradient)
180   - 2017-08-26T10:35:16: Number of spectral par's ..: 1
181   - 2017-08-26T10:35:16: Normalization ............: 1 [0,1000] (fixed,scale=1,gradient)
182   - 2017-08-26T10:35:16: Number of temporal par's ..: 1
183   - 2017-08-26T10:35:16: Normalization ............: 1 (relative value) (fixed,scale=1,gradient)
184   -
  95 + 2018-01-25T20:07:55: +=================================+
  96 + 2018-01-25T20:07:55: | Maximum likelihood optimisation |
  97 + 2018-01-25T20:07:55: +=================================+
  98 + 2018-01-25T20:07:57: >Iteration 0: -logL=-177232.327, Lambda=1.0e-03
  99 + 2018-01-25T20:07:58: >Iteration 1: -logL=-198931.136, Lambda=1.0e-03, delta=21698.809, step=1.0e+00, max(|grad|)=-22717.063466 [CutoffEnergy:4]
  100 + 2018-01-25T20:07:58: >Iteration 2: -logL=-200269.888, Lambda=1.0e-04, delta=1338.753, step=1.0e+00, max(|grad|)=-67629.683771 [CutoffEnergy:4]
  101 + 2018-01-25T20:07:59: >Iteration 3: -logL=-212351.965, Lambda=1.0e-05, delta=12082.076, step=1.0e+00, max(|grad|)=23026.802421 [Index2:6]
  102 + 2018-01-25T20:07:59: >Iteration 4: -logL=-213954.259, Lambda=1.0e-06, delta=1602.294, step=1.0e+00, max(|grad|)=-8297.380912 [CutoffEnergy:4]
  103 + 2018-01-25T20:07:59: >Iteration 5: -logL=-215347.973, Lambda=1.0e-07, delta=1393.714, step=1.0e+00, max(|grad|)=2746.754042 [Index2:6]
  104 + 2018-01-25T20:08:00: >Iteration 6: -logL=-215497.807, Lambda=1.0e-08, delta=149.834, step=1.0e+00, max(|grad|)=699.848484 [Index2:6]
  105 + 2018-01-25T20:08:00: Iteration 7: -logL=-215497.807, Lambda=1.0e-09, delta=-13.845, step=1.0e+00, max(|grad|)=-1201.982875 [Index1:3] (stalled)
  106 + 2018-01-25T20:08:01: Iteration 8: -logL=-215497.807, Lambda=1.0e-08, delta=-13.844, step=1.0e+00, max(|grad|)=-1201.959647 [Index1:3] (stalled)
  107 + 2018-01-25T20:08:01: Iteration 9: -logL=-215497.807, Lambda=1.0e-07, delta=-13.835, step=1.0e+00, max(|grad|)=-1201.727401 [Index1:3] (stalled)
  108 + 2018-01-25T20:08:02: Iteration 10: -logL=-215497.807, Lambda=1.0e-06, delta=-13.744, step=1.0e+00, max(|grad|)=-1199.408717 [Index1:3] (stalled)
  109 + 2018-01-25T20:08:02: Iteration 11: -logL=-215497.807, Lambda=1.0e-05, delta=-12.858, step=1.0e+00, max(|grad|)=-1176.594021 [Index1:3] (stalled)
  110 + 2018-01-25T20:08:03: Iteration 12: -logL=-215497.807, Lambda=1.0e-04, delta=-6.126, step=1.0e+00, max(|grad|)=-980.833963 [Index1:3] (stalled)
  111 + 2018-01-25T20:08:04: >Iteration 13: -logL=-215503.803, Lambda=1.0e-03, delta=5.995, step=1.0e+00, max(|grad|)=-285.964915 [Index1:3]
  112 + 2018-01-25T20:08:04: Iteration 14: -logL=-215503.803, Lambda=1.0e-04, delta=-8.762, step=1.0e+00, max(|grad|)=-730.461326 [Index1:3] (stalled)
  113 + 2018-01-25T20:08:05: >Iteration 15: -logL=-215504.976, Lambda=1.0e-03, delta=1.173, step=1.0e+00, max(|grad|)=-153.941336 [Index1:3]
  114 + 2018-01-25T20:08:05: Iteration 16: -logL=-215503.593, Lambda=1.0e-04, delta=-1.383, step=1.0e+00, max(|grad|)=-327.368445 [Index1:3] (stalled)
  115 + 2018-01-25T20:08:06: >Iteration 17: -logL=-215505.817, Lambda=1.0e-03, delta=2.225, step=1.0e+00, max(|grad|)=3.256216 [Index2:6]
  116 + 2018-01-25T20:08:06: >Iteration 18: -logL=-215505.824, Lambda=1.0e-04, delta=0.007, step=1.0e+00, max(|grad|)=-8.190316 [CutoffEnergy:4]
  117 + 2018-01-25T20:08:06: >Iteration 19: -logL=-215505.826, Lambda=1.0e-05, delta=0.002, step=1.0e+00, max(|grad|)=0.635263 [Index2:6]
  118 + 2018-01-25T20:08:07:
  119 + 2018-01-25T20:08:07: +=========================================+
  120 + 2018-01-25T20:08:07: | Maximum likelihood optimisation results |
  121 + 2018-01-25T20:08:07: +=========================================+
  122 + 2018-01-25T20:08:07: === GOptimizerLM ===
  123 + 2018-01-25T20:08:07: Optimized function value ..: -215505.826
  124 + 2018-01-25T20:08:07: Absolute precision ........: 0.005
  125 + 2018-01-25T20:08:07: Acceptable value decrease .: 2
  126 + 2018-01-25T20:08:07: Optimization status .......: converged
  127 + 2018-01-25T20:08:07: Number of parameters ......: 14
  128 + 2018-01-25T20:08:07: Number of free parameters .: 7
  129 + 2018-01-25T20:08:07: Number of iterations ......: 19
  130 + 2018-01-25T20:08:07: Lambda ....................: 1e-06
  131 + 2018-01-25T20:08:07: Maximum log likelihood ....: 215505.826
  132 + 2018-01-25T20:08:07: Observed events (Nobs) ...: 202330.000
  133 + 2018-01-25T20:08:07: Predicted events (Npred) ..: 202318.925 (Nobs - Npred = 11.0749561789562)
  134 + 2018-01-25T20:08:07: === GModels ===
  135 + 2018-01-25T20:08:07: Number of models ..........: 3
  136 + 2018-01-25T20:08:07: Number of parameters ......: 14
  137 + 2018-01-25T20:08:07: === GModelSky ===
  138 + 2018-01-25T20:08:07: Name ......................: Vela
  139 + 2018-01-25T20:08:07: Instruments ...............: all
  140 + 2018-01-25T20:08:07: Instrument scale factors ..: unity
  141 + 2018-01-25T20:08:07: Observation identifiers ...: all
  142 + 2018-01-25T20:08:07: Model type ................: PointSource
  143 + 2018-01-25T20:08:07: Model components ..........: "PointSource" * "SuperExponentialCutoffPowerLaw" * "Constant"
  144 + 2018-01-25T20:08:07: Number of parameters ......: 8
  145 + 2018-01-25T20:08:07: Number of spatial par's ...: 2
  146 + 2018-01-25T20:08:07: RA .......................: 128.835772118429 +/- 0.00162177813558897 [-360,360] deg (free,scale=1)
  147 + 2018-01-25T20:08:07: DEC ......................: -45.1835812138884 +/- 0.00114069728792873 [-90,90] deg (free,scale=1)
  148 + 2018-01-25T20:08:07: Number of spectral par's ..: 5
  149 + 2018-01-25T20:08:07: Prefactor ................: 4.35032346821964e-09 +/- 4.73845090178596e-10 [1e-16,1e-06] ph/cm2/s/MeV (free,scale=1e-09,gradient)
  150 + 2018-01-25T20:08:07: Index1 ...................: -1.34367731366247 +/- 0.031088811599731 [-0,-5] (free,scale=-1,gradient)
  151 + 2018-01-25T20:08:07: CutoffEnergy .............: 990.275379109663 +/- 181.814299583364 [1,1000000] MeV (free,scale=1000,gradient)
  152 + 2018-01-25T20:08:07: PivotEnergy ..............: 1000 [10,1000000] MeV (fixed,scale=1000,gradient)
  153 + 2018-01-25T20:08:07: Index2 ...................: 0.587550117179991 +/- 0.0279192539614008 [0.1,5] (free,scale=1,gradient)
  154 + 2018-01-25T20:08:07: Number of temporal par's ..: 1
  155 + 2018-01-25T20:08:07: Normalization ............: 1 (relative value) (fixed,scale=1,gradient)
  156 + 2018-01-25T20:08:07: === GModelSky ===
  157 + 2018-01-25T20:08:07: Name ......................: Galactic_diffuse
  158 + 2018-01-25T20:08:07: Instruments ...............: all
  159 + 2018-01-25T20:08:07: Instrument scale factors ..: unity
  160 + 2018-01-25T20:08:07: Observation identifiers ...: all
  161 + 2018-01-25T20:08:07: Model type ................: DiffuseSource
  162 + 2018-01-25T20:08:07: Model components ..........: "DiffuseMapCube" * "Constant" * "Constant"
  163 + 2018-01-25T20:08:07: Number of parameters ......: 3
  164 + 2018-01-25T20:08:07: Number of spatial par's ...: 1
  165 + 2018-01-25T20:08:07: Normalization ............: 1 [0.1,10] (fixed,scale=1,gradient)
  166 + 2018-01-25T20:08:07: Number of spectral par's ..: 1
  167 + 2018-01-25T20:08:07: Normalization ............: 1.10941973066973 +/- 0.00503412002598653 [0.1,1000] (free,scale=1,gradient)
  168 + 2018-01-25T20:08:07: Number of temporal par's ..: 1
  169 + 2018-01-25T20:08:07: Normalization ............: 1 (relative value) (fixed,scale=1,gradient)
  170 + 2018-01-25T20:08:07: === GModelSky ===
  171 + 2018-01-25T20:08:07: Name ......................: Extragalactic_diffuse
  172 + 2018-01-25T20:08:07: Instruments ...............: all
  173 + 2018-01-25T20:08:07: Instrument scale factors ..: unity
  174 + 2018-01-25T20:08:07: Observation identifiers ...: all
  175 + 2018-01-25T20:08:07: Model type ................: DiffuseSource
  176 + 2018-01-25T20:08:07: Model components ..........: "DiffuseIsotropic" * "FileFunction" * "Constant"
  177 + 2018-01-25T20:08:07: Number of parameters ......: 3
  178 + 2018-01-25T20:08:07: Number of spatial par's ...: 1
  179 + 2018-01-25T20:08:07: Value ....................: 1 [0,10] (fixed,scale=1,gradient)
  180 + 2018-01-25T20:08:07: Number of spectral par's ..: 1
  181 + 2018-01-25T20:08:07: Normalization ............: 1 [0,1000] (fixed,scale=1,gradient)
  182 + 2018-01-25T20:08:07: Number of temporal par's ..: 1
  183 + 2018-01-25T20:08:07: Normalization ............: 1 (relative value) (fixed,scale=1,gradient)
185 184  
186 185 The fit converged after 19 iterations with spectral parameters that are
187 186 reasonably close to those found in
... ... @@ -242,13 +241,16 @@ using the Fermi-LAT Science Tools.
242 241  
243 242 .. code-block:: none
244 243  
245   - 2017-08-26T13:05:12: === GModelSky ===
246   - 2017-08-26T13:05:12: Name ......................: Vela
247   - 2017-08-26T13:05:12: Instruments ...............: all
248   - 2017-08-26T13:05:12: Test Statistic ............: 326326.556902542
  244 + 2018-01-25T20:05:57: Name ......................: Vela
  245 + 2018-01-25T20:05:57: Instruments ...............: all
  246 + 2018-01-25T20:05:57: Test Statistic ............: 326341.439917148
249 247  
250 248 which is also close to the value determined by gtlike.
251 249  
  250 +.. note::
  251 + Unlike gtlike, :ref:`ctlike` can also fit the source location. This has been
  252 + done in the example above by setting the parameter attributes to ``free="1"``.
  253 +
252 254 .. warning::
253 255 ctools supports for the moment only the fitting of point sources for
254 256 Fermi-LAT data. Other spatial shapes need to be preconvolved with the
... ...
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doc/source/users/tutorials/howto/fermi/howto_fermi_spectrum.rst
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... ... @@ -5,77 +5,44 @@ Generate a spectral energy distribution for a source
5 5  
6 6 .. admonition:: What you will learn
7 7  
8   - You will learn how to use :ref:`ctlike` to derive the spectral energy
  8 + You will learn how to use :ref:`csspec` to derive the spectral energy
9 9 density of a source from Fermi-LAT data.
10 10  
11   -So far the :ref:`csspec` script does not work for Fermi-LAT data, but you
12   -will learn here a method that you can use to derive the spectrum of any
13   -source using Fermi-LAT data. For this you first need a little Python code
14   -to transform the spectral component of the Vela source in the
15   -:ref:`model definition file <glossary_moddef>`
16   -from a super exponentially cut-off power law into a node function.
17   -You do this as follows:
18   -
19   -.. code-block:: python
20   -
21   - >>> import gammalib
22   - >>> models = gammalib.GModels('vela_results.xml')
23   - >>> energies = gammalib.GEnergies(10, gammalib.GEnergy(100.0, 'MeV'), gammalib.GEnergy(100.0, 'GeV'))
24   - >>> nodes = gammalib.GModelSpectralNodes()
25   - >>> for energy in energies:
26   - >>> nodes.append(energy, models['Vela'].spectral().eval(energy))
27   - >>> for par in nodes:
28   - >>> if 'Energy' in par.name():
29   - >>> par.fix()
30   - >>> if 'Intensity' in par.name():
31   - >>> par.min(1.0e-30)
32   - >>> models['Vela'].spectral(nodes)
33   - >>> models.save('model_nodes.xml')
34   -
35   -This will create a
36   -:ref:`model definition file <glossary_moddef>`
37   -with the following structure:
38   -
39   -.. code-block:: xml
40   -
41   - <?xml version="1.0" encoding="UTF-8" standalone="no"?>
42   - <source_library title="source library">
43   - <source name="Vela" type="PointSource">
44   - <spectrum type="NodeFunction">
45   - <node>
46   - <parameter name="Energy" value="100" scale="1" free="0" />
47   - <parameter name="Intensity" value="7.40280399439422e-08" error="0" scale="1" min="1e-30" free="1" />
48   - </node>
49   - <node>
50   - <parameter name="Energy" value="215.443469003188" scale="1" free="0" />
51   - <parameter name="Intensity" value="2.27587615163047e-08" error="0" scale="1" min="1e-30" free="1" />
52   - </node>
53   - ...
54   - </source_library>
55   -
56   -Instead of the super exponentially cut-off power law the model now contains
57   -a node function with ten intensity nodes between 100 MeV and 100 GeV, and the
58   -:ref:`ctlike` tool will now adjust the intensities of each of the nodes which
59   -will result in a spectrum. To do this type now:
  11 +To determine a spectral of the Vela pulsar you can use the :ref:`csspec`
  12 +script. To do this, type
60 13  
61 14 .. code-block:: bash
62 15  
63   - $ ctlike
64   - Input event list, counts cube or observation definition XML file [obs.xml]
65   - Input model definition XML file [models.xml] model_nodes.xml
66   - Output model definition XML file [vela_results.xml] vela_nodes_results.xml
67   -
68   -This will produce the
69   -:ref:`model definition file <glossary_moddef>`
70   -``vela_nodes_results.xml`` with the intensities of the fitted source at
71   -each energy. The results are displayed graphically below.
  16 + $ csspec
  17 + Input event list, counts cube, or observation definition XML file [events.fits] obs.xml
  18 + Input model definition XML file [$CTOOLS/share/models/crab.xml] vela_results.xml
  19 + Source name [Crab] Vela
  20 + Spectrum generation method (SLICE|NODES|AUTO) [AUTO]
  21 + Algorithm for defining energy bins (FILE|LIN|LOG) [LOG]
  22 + Start value for first energy bin in TeV [0.1] 0.0001
  23 + Stop value for last energy bin in TeV [100.0] 0.1
  24 + Number of energy bins (1-200) [20] 10
  25 + Output spectrum file [spectrum.fits]
  26 +
  27 +This will generate a logarithmically spaced spectrum composed of 10 energy bins
  28 +comprised within 100 MeV and 100 GeV. The :ref:`csspec` tool is run in the ``AUTO``
  29 +mode, which for Fermi-LAT data corresponds to the ``NODES`` method. :ref:`csspec`
  30 +will convert the Vela spectrum in the input model into a node function and fit
  31 +all intensity nodes using :ref:`ctlike`. The resulting node intensities are
  32 +then interpreted as the spectral point, and are displayed graphically below:
72 33  
73 34 .. figure:: howto_fermi_spectrum.png
74 35 :width: 600px
75 36 :align: center
76 37  
77   - *Spectrum of the Vela pulsar derived using a node function*
  38 + *Spectrum of the Vela pulsar derived using csspec*
78 39  
79 40 .. note::
80   - The ``NodeFunction`` spectral models implements a piece-wise power law
81   - that is defined by the intensity values at each node.
  41 + The figure was created using the ``show_spectrum.py`` script that is
  42 + located in the ctools example folder. The example script requires the
  43 + `matplotlib <http://matplotlib.org>`_ Python module for display.
  44 + You may reproduce the plot by typing
  45 +
  46 + .. code-block:: bash
  47 +
  48 + $ $CTOOLS/share/examples/python/show_spectrum.py spectrum.fits
... ...
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  1 +.. _howto_fermi_tsmap:
  2 +
  3 +Generate a Test Statistic map
  4 +-----------------------------
  5 +
  6 + .. admonition:: What you will learn
  7 +
  8 + You will learn how to use :ref:`cttsmap` to generate a Test Staristic
  9 + map from Fermi-LAT data.
  10 +
  11 +The Test Statistic (or maximum likelihood ratio) is a measure of the detection
  12 +significance of a gamma-ray source. By displacing the location of a test source
  13 +on a grid of positions you can generate a Test Statistic map that helps in
  14 +finding significant source and assessing the position uncertainty of a
  15 +source. You do this by using the :ref:`cttsmap` tool as follows:
  16 +
  17 +.. code-block:: bash
  18 +
  19 + $ cttsmap
  20 + Input event list, counts cube or observation definition XML file [events.fits] obs.xml
  21 + Test source name [Crab] Vela
  22 + Input model definition XML file [$CTOOLS/share/models/crab.xml] vela_results.xml
  23 + First coordinate of image center in degrees (RA or galactic l) (0-360) [83.63] 128.84
  24 + Second coordinate of image center in degrees (DEC or galactic b) (-90-90) [22.01] -45.18
  25 + Projection method (AIT|AZP|CAR|GLS|MER|MOL|SFL|SIN|STG|TAN) [CAR]
  26 + Coordinate system (CEL - celestial, GAL - galactic) (CEL|GAL) [CEL]
  27 + Image scale (in degrees/pixel) [0.02] 0.3
  28 + Size of the X axis in pixels [200] 10
  29 + Size of the Y axis in pixels [200] 10
  30 + Output Test Statistic map file [tsmap.fits]
  31 +
  32 +:ref:`cttsmap` created a 10 x 10 pixels map with a pixel size of 0.3 degrees
  33 +around the location of the Vela pulsar and saved the result in the FITS file
  34 +``tsmap.fits``. The file also contains the values of all fitted parameters
  35 +at each grid position. The Test Statistics map is displayed using
  36 +`ds9 <http://ds9.si.edu>`_ in the figure below:
  37 +
  38 +.. figure:: howto_fermi_tsmap.png
  39 + :width: 400px
  40 + :align: center
  41 +
  42 + *Test Statistic map for Fermi-LAT of the Vela pulsar*
... ...
doc/source/users/tutorials/howto/fermi/howto_fermi_ulimit.rst
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... ... @@ -44,18 +44,18 @@ specifying ``emin=0.0001 emax=0.1`` (all values are given in TeV):
44 44 .. code-block:: bash
45 45  
46 46 $ ctulimit eref=0.001 emin=0.0001 emax=0.1
47   - Input event list, counts cube or observation definition XML file [obs.xml]
48   - Source of interest [Test]
49   - Input model definition XML file [model_lat_ulimit.xml]
  47 + Input event list, counts cube or observation definition XML file [events.fits] obs.xml
  48 + Source of interest [Crab] Test
  49 + Input model definition XML file [$CTOOLS/share/models/crab.xml] models_ulimit.xml
50 50  
51 51 The results of the upper limit computation can then be extracted from the
52 52 ``ctulimit.log`` file that is created by :ref:`ctulimit`:
53 53  
54 54 .. code-block:: bash
55 55  
56   - 2017-08-26T14:37:48: +=====================+
57   - 2017-08-26T14:37:48: | Upper limit results |
58   - 2017-08-26T14:37:48: +=====================+
59   - 2017-08-26T14:37:48: Differential flux limit ...: 1.00100099727198e-13 ph/cm2/s/MeV at 0.001 TeV
60   - 2017-08-26T14:37:48: Integral flux limit .......: 9.9999999627471e-10 ph/cm2/s within [0.0001-0.1] TeV
61   - 2017-08-26T14:37:48: Energy flux limit .........: 1.10785216561628e-12 erg/cm2/s within [0.0001-0.1] TeV
  56 + 2018-01-25T20:43:02: +=====================+
  57 + 2018-01-25T20:43:02: | Upper limit results |
  58 + 2018-01-25T20:43:02: +=====================+
  59 + 2018-01-25T20:43:02: Differential flux limit ...: 1.00100099727198e-13 ph/cm2/s/MeV at 0.001 TeV
  60 + 2018-01-25T20:43:02: Integral flux limit .......: 9.9999999627471e-10 ph/cm2/s within [0.0001-0.1] TeV
  61 + 2018-01-25T20:43:02: Energy flux limit .........: 1.10785216561628e-12 erg/cm2/s within [0.0001-0.1] TeV
... ...
doc/source/users/tutorials/howto/fermi/index.rst
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... ... @@ -33,5 +33,6 @@ tutorial that is based on a simple analysis of the Vela pulsar.
33 33 howto_fermi_fitting
34 34 howto_fermi_butterfly
35 35 howto_fermi_spectrum
  36 + howto_fermi_tsmap
36 37 howto_fermi_ulimit
37 38 howto_fermi_errors
... ...