Pierrick Martin / ctools

Commit 81c782632450fe575a3bae95887900ca27cea335

Authored by Jürgen Knödlseder
1 parent 0c22baed

Reorganise tutorials

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Showing 20 changed files with 241 additions and 280 deletions
doc/source/users/index.rst
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... ... @@ -8,9 +8,9 @@ This documentation will guide you in the process of using ctools.
8 8 .. toctree::
9 9 :maxdepth: 1
10 10  
11   - tips/index
12 11 user_manual/index
13   - tutorials/index
14 12 reference_manual/index
  13 + tips/index
  14 + tutorials/index
15 15 user_contributed/index
16 16 glossary
... ...
doc/source/users/tutorials/beyond/beyond_tsmap.rst deleted
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1   -.. _sec_tsmap:
2   -
3   -Generating a Test Statistic map
4   -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
5   -
6   -In the above examples you have always considering that you knew exactly
7   -where the source is located, but in real life situations this may not
8   -necessarily be the case.
9   -You thus need a means to search for significant excess emission in your data.
10   -One possibility to accomplish this task is to compute the Test Statistic
11   -for a specific source at a grid of trial positions.
12   -The :ref:`cttsmap` tool will do exactly that job.
13   -
14   -The Test Statistic is defined as twice the log-likelihood difference
15   -between fitting a source at a given position on top of a model or fitting
16   -no source.
17   -Roughly speaken, the square root of the Test Statistic value gives
18   -the source detection significance in Gaussian sigmas, although the
19   -exact relation depends somewhat on the formulation of the statistical
20   -problem.
21   -
22   -Here an example of how to apply the :ref:`cttsmap` tool to the two
23   -simulated observations of the Crab nebula in unbinned mode.
24   -On input you provide a source model XML file and the name of the source
25   -in the XML file that should be moved on a grid of test positions.
26   -This means that the position of the source given in the XML file is
27   -in fact ignored and replaced by the grid positions that are defined by
28   -the user parameters.
29   -In the example you defined a grid of 10 x 10 positions around the
30   -nominal position of the Crab nebula with a grid spacing of 0.02°.
31   -
32   -.. code-block:: bash
33   -
34   - $ cttsmap
35   - Input event list, counts cube or observation definition XML file [events.fits] obs.xml
36   - Calibration database [prod2]
37   - Instrument response function [South_0.5h]
38   - Test source name [Crab]
39   - Input model definition XML file [$CTOOLS/share/models/crab.xml]
40   - First coordinate of image center in degrees (RA or galactic l) (0-360) [83.63]
41   - Second coordinate of image center in degrees (DEC or galactic b) (-90-90) [22.01]
42   - Projection method (AIT|AZP|CAR|GLS|MER|MOL|SFL|SIN|STG|TAN) [CAR]
43   - Coordinate system (CEL - celestial, GAL - galactic) (CEL|GAL) [CEL]
44   - Image scale (in degrees/pixel) [0.02]
45   - Size of the X axis in pixels [200] 10
46   - Size of the Y axis in pixels [200] 10
47   - Output Test Statistic map file [tsmap.fits]
48   -
49   -:ref:`cttsmap` writes the Test Statistic map in the ``tsmap.fits`` file
50   -that contains one extension for the Test Statistic value and further
51   -extensions for the spectral parameters that have been fitted for the
52   -source at each position of the grid.
53   -The figure below show the Test Statistic map which reaches a maximum
54   -value of 42622 near the centre of the map.
55   -
56   -.. figure:: tsmap-crab.png
57   - :height: 400px
58   - :align: center
59   -
60   - *Test Statistic map of the Crab region*
61   -
62   -.. note::
63   - Similar to :ref:`ctlike` the :ref:`cttsmap` tool works either for unbinned,
64   - binned or stacked analysis. On input it takes either a single event
65   - list, a single counts cube, or an observation definition XML file that
66   - allows a joint analysis of multiple observations.
doc/source/users/tutorials/beyond/index.rst deleted
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1   -.. _sec_beyond:
2   -
3   -Beyond the first steps
4   -----------------------
5   -
6   -Now that you are familiar with the ctools basics, here are some sections
7   -to read if you intend to do more complex analyses.
8   -Once you have gone through these sections you should have a pretty complete
9   -picture about the capabilities of ctools.
10   -And you should be ready for doing your own cutting edge CTA science data
11   -analyses.
12   -
13   -.. toctree::
14   - :maxdepth: 1
15   -
16   - combining-observations
17   - stacked-analysis
18   - beyond_tsmap
19   - advanced-python-fitting
20   - beyond_irf
21   - beyond_model
doc/source/users/tutorials/beyond/tsmap-crab.png deleted
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doc/source/users/tutorials/beyond/advanced-python-fitting.ipynb renamed to doc/source/users/tutorials/howto/howto_advanced_python_fitting.ipynb
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... ... @@ -4,7 +4,7 @@
4 4 "cell_type": "markdown",
5 5 "metadata": {},
6 6 "source": [
7   - "# Advanced model manipulation and fitting in Python"
  7 + "# How to do advanced model manipulation and fitting in Python?"
8 8 ]
9 9 },
10 10 {
... ... @@ -20,7 +20,7 @@
20 20 "source": [
21 21 "In this tutorial you will learn to perform some more advanced model manipulation and fitting from Python. You can use these methods in an interactive Python session to explore your dataset and improve the known model of the sky. You can also use them in a Python pipeline to test multiple model hypotheses and select the one that is most appropriate.\n",
22 22 "\n",
23   - "As usual we start by importing the gammalib, ctools, and cscripts Python modules."
  23 + "As usual start by importing the gammalib, ctools, and cscripts Python modules."
24 24 ]
25 25 },
26 26 {
... ... @@ -38,7 +38,7 @@
38 38 "cell_type": "markdown",
39 39 "metadata": {},
40 40 "source": [
41   - "For this tutorial we will also use the matplotlib package for plotting."
  41 + "Now import the matplotlib package for plotting."
42 42 ]
43 43 },
44 44 {
... ... @@ -57,7 +57,7 @@
57 57 "source": [
58 58 "## Simulated dataset\n",
59 59 "\n",
60   - "For the tutorial we will simulate a small dataset. We start by defining the Instrument Response Function and energy range that we will use all along."
  60 + "For the tutorial you will simulate a small dataset. Start by defining the Instrument Response Function and energy range that will be used all along."
61 61 ]
62 62 },
63 63 {
... ... @@ -76,7 +76,7 @@
76 76 "cell_type": "markdown",
77 77 "metadata": {},
78 78 "source": [
79   - "Now we proceed to simulate the dataset. It consists of an hour of observations of the Crab nebula region, as usual pointed at a slightly offset position from the target. The input model is different from the one you have been using so far and contains some surprises. Don't look at it until you have completed the exercises at the end of the tutorial."
  79 + "Now proceed to simulate the dataset. It consists of an hour of observations of the Crab nebula region, as usual pointed at a slightly offset position from the target. The input model is different from the one you have been using so far and contains some surprises. Don't look at it until you have completed the exercises at the end of the tutorial."
80 80 ]
81 81 },
82 82 {
... ... @@ -105,9 +105,9 @@
105 105 "cell_type": "markdown",
106 106 "metadata": {},
107 107 "source": [
108   - "We have saved the events on disk in the file `events.fits`. In this way you can easily re-use the code below by substituting `events.fits` with your own event list of observation definition XML file.\n",
  108 + "You have saved the events on disk in the file `events.fits`. In this way you can easily re-use the code below by substituting `events.fits` with your own event list or observation definition XML file.\n",
109 109 "\n",
110   - "We will peek at the simulated dataset by displaying a skymap."
  110 + "Let's first peek at the simulated dataset by displaying a skymap."
111 111 ]
112 112 },
113 113 {
... ... @@ -150,7 +150,7 @@
150 150 }
151 151 ],
152 152 "source": [
153   - "# We slightly smooth the map for display to suppress statistical fluctuations\n",
  153 + "# Slightly smooth the map for display to suppress statistical fluctuations\n",
154 154 "skymap.skymap().smooth('GAUSSIAN',0.02)\n",
155 155 "\n",
156 156 "from matplotlib.colors import SymLogNorm\n",
... ... @@ -174,7 +174,7 @@
174 174 "source": [
175 175 "## Model fitting and residual inspection\n",
176 176 "\n",
177   - "First, we will fit the usual Crab model to the data. We will be using a 3D unbinned analysis."
  177 + "First, fit the usual Crab model to the data using a 3D unbinned analysis."
178 178 ]
179 179 },
180 180 {
... ... @@ -195,7 +195,7 @@
195 195 "cell_type": "markdown",
196 196 "metadata": {},
197 197 "source": [
198   - "As usual it is wise to look at the output from the optimizer. We will also store the best-fit minus log-likelihood value for later usage."
  198 + "As usual it is wise to look at the output from the optimizer. Store the best-fit minus log-likelihood value for later usage."
199 199 ]
200 200 },
201 201 {
... ... @@ -286,7 +286,7 @@
286 286 "source": [
287 287 "The background model reproduces well the data, since its best-fit normalization is 1 and the index/tilt is 0. The Crab nebula has a best-fit spectral index of 2.28.\n",
288 288 "\n",
289   - "To assess whether the model reproduces well the data spatially we will calculate a residual map."
  289 + "To assess whether the model reproduces well the data spatially generate a residual map."
290 290 ]
291 291 },
292 292 {
... ... @@ -313,7 +313,7 @@
313 313 "cell_type": "markdown",
314 314 "metadata": {},
315 315 "source": [
316   - "We will be inspecting several of these residual maps along the tutorial, so we define a function to plot them, and apply it to our latest run."
  316 + "To easily inspecting the residual maps along the tutorial, define a function to plot them, and apply it to the latest run."
317 317 ]
318 318 },
319 319 {
... ... @@ -323,15 +323,15 @@
323 323 "outputs": [],
324 324 "source": [
325 325 "def plot_residuals(resid):\n",
326   - " # We slightly smooth the map for display to suppress statistical fluctuations\n",
  326 + " # Slightly smooth the map for display to suppress statistical fluctuations\n",
327 327 " resid.smooth('GAUSSIAN',0.04)\n",
328   - " #plotting\n",
  328 + " # Plotting\n",
329 329 " fig = plt.figure()\n",
330 330 " ax = plt.subplot()\n",
331 331 " plt.imshow(resid.array(),origin='lower',\n",
332 332 " cmap='bwr',vmin=-3,vmax=3,\n",
333 333 " extent=[83.63+0.02*20,83.63-0.02*20,22.01-0.02*20,22.01+0.02*20])\n",
334   - " # boundaries of the coord grid\n",
  334 + " # Boundaries of the coord grid\n",
335 335 " ax.set_xlabel('R.A. (deg)')\n",
336 336 " ax.set_ylabel('Dec (deg)')\n",
337 337 " cbar = plt.colorbar()\n",
... ... @@ -364,7 +364,7 @@
364 364 "source": [
365 365 "## Adding model components\n",
366 366 "\n",
367   - "The residual map shows a cluster of positive residuals on the South-West of the Crab nebula. Is this another source? To test this hypothesis we will add a point source at the position that we can guess from the residual map."
  367 + "The residual map shows a cluster of positive residuals on the South-West of the Crab nebula. Is this another source? To test this hypothesis add a point source at the position that you can guess from the residual map."
368 368 ]
369 369 },
370 370 {
... ... @@ -382,13 +382,13 @@
382 382 "cell_type": "markdown",
383 383 "metadata": {},
384 384 "source": [
385   - "We have defined a sky model object that has three components:\n",
  385 + "You have defined a sky model object that has three components:\n",
386 386 "\n",
387 387 "- a spatial model, which is a point source at the position guessed from the residual map;\n",
388 388 "- a spectral model which is a power law with spectral index 2, and a flux which approximately 1/10 of the Crab nebula;\n",
389 389 "- a temporal model which is a constant.\n",
390 390 "\n",
391   - "We will name this source Src1, and free its position (fixed by default when a new source is created), so that we can fit it to the data."
  391 + "Name this source `Src1`, and free its position (fixed by default when a new source is created), so that you can fit it to the data:"
392 392 ]
393 393 },
394 394 {
... ... @@ -406,7 +406,7 @@
406 406 "cell_type": "markdown",
407 407 "metadata": {},
408 408 "source": [
409   - "Finally we append the new source to the model"
  409 + "Finally append the new source to the model container"
410 410 ]
411 411 },
412 412 {
... ... @@ -433,7 +433,7 @@
433 433 "cell_type": "markdown",
434 434 "metadata": {},
435 435 "source": [
436   - "and we fit the model including the new source to the data."
  436 + "and fit the model including the new source to the data."
437 437 ]
438 438 },
439 439 {
... ... @@ -449,7 +449,7 @@
449 449 "cell_type": "markdown",
450 450 "metadata": {},
451 451 "source": [
452   - "Does the addition of the new source provide a better fit to the data? We can quantify this using the test statistic (TS) given by twice the log-likelihood difference."
  452 + "Does the addition of the new source provide a better fit to the data? You can quantify this using the test statistic (TS) given by twice the log-likelihood difference."
453 453 ]
454 454 },
455 455 {
... ... @@ -475,9 +475,9 @@
475 475 "cell_type": "markdown",
476 476 "metadata": {},
477 477 "source": [
478   - "TS is expected to be distributed as a $\\chi^2$ with n degrees of freedom, where n is the additional number of degrees of freedom in the model including the new source, in our case 4 (RA, Dec, Prefactor, and Index). The integral of the $\\chi^2$ from TS to $\infty$ is the chance probability that the likelihood improved by that much due to statistical fluctuations. A large value, like the one we got, means that the chance probability is very low, thus we are likely to have found a new source.\n",
  478 + "TS is expected to be distributed as a $\\chi^2_n$ with n degrees of freedom, where n is the additional number of degrees of freedom in the model including the new source, in our case 4 (RA, Dec, Prefactor, and Index). The integral of the $\\chi^2_n$ from TS to $\infty$ is the chance probability that the likelihood improved by that much due to statistical fluctuations. A large value, like the one we got, means that the chance probability is very low, thus we are likely to have found a new source.\n",
479 479 "\n",
480   - "To make sure the new source improves the data/model agreement we will look again at the residual map."
  480 + "To make sure the new source improves the data/model agreement look again at the residual map."
481 481 ]
482 482 },
483 483 {
... ... @@ -506,7 +506,7 @@
506 506 "cell_type": "markdown",
507 507 "metadata": {},
508 508 "source": [
509   - "The addition of the new point source has flattened the spatial residuals, even though the fit is not perfect yet obviously. From now on we will fix the position of Scr1."
  509 + "The addition of the new point source has flattened the spatial residuals, even though the fit is obviously not perfect yet. From now on fix the position of `Src1`."
510 510 ]
511 511 },
512 512 {
... ... @@ -527,7 +527,7 @@
527 527 "source": [
528 528 "## Modifying the spectral models\n",
529 529 "\n",
530   - "Next we will check if the model agrees well with the data at all energies. We will start by defining a function to make and plot residual maps in separate energy ranges."
  530 + "Next check if the model agrees well with the data at all energies. Start by defining a function to make and plot residual maps in separate energy ranges."
531 531 ]
532 532 },
533 533 {
... ... @@ -583,15 +583,15 @@
583 583 ],
584 584 "source": [
585 585 "resmap_erange([[emin,1.],\n",
586   - " [1.,10.],\n",
587   - " [10.,emax]])"
  586 + " [1.,10.],\n",
  587 + " [10.,emax]])"
588 588 ]
589 589 },
590 590 {
591 591 "cell_type": "markdown",
592 592 "metadata": {},
593 593 "source": [
594   - "The most obvious problem is a negative residual cluster at the position of the Crab nebula at the highest energies. We will change the spectral model of the crab nebula and test if this improves the fit. We will use an exponentially cutoff power-law rather than a simple power law. We will use as starting values for the Prefactor and Index the current best-fit values and tentatively set the cutoff energy at 1 TeV."
  594 + "The most obvious problem is a negative residual cluster at the position of the Crab nebula at the highest energies. Change the spectral model of the Crab nebula and test if this improves the fit. Try for example an exponentially cutoff power-law rather than a simple power law. Let's use as starting values for the Prefactor and Index the current best-fit values and tentatively set the cutoff energy at 1 TeV."
595 595 ]
596 596 },
597 597 {
... ... @@ -613,7 +613,7 @@
613 613 "cell_type": "markdown",
614 614 "metadata": {},
615 615 "source": [
616   - "We will now fit the modified model to the data"
  616 + "Now fit the modified model to the data"
617 617 ]
618 618 },
619 619 {
... ... @@ -629,7 +629,7 @@
629 629 "cell_type": "markdown",
630 630 "metadata": {},
631 631 "source": [
632   - "and use TS to quantify the model improvement (in this case we have only one additional degree of freedom, the ctuoff energy)."
  632 + "and use TS to quantify the model improvement (in this case there is only one additional degree of freedom, the ctuoff energy)."
633 633 ]
634 634 },
635 635 {
... ... @@ -696,7 +696,7 @@
696 696 "cell_type": "markdown",
697 697 "metadata": {},
698 698 "source": [
699   - "The best-fit cutoff energy is 3.3 TeV, which seems consistent with the behavior in the energy-bands residual maps above. Note that this has changed significantly the Index value, that now is 1.83. We will check the residual maps again to make sure."
  699 + "The best-fit cutoff energy is 3.3 TeV, which seems consistent with the behavior in the energy-bands residual maps above. Note that this has changed significantly the Index value, that now is 1.83. Check the residual maps again to make sure that the residuals are reduced."
700 700 ]
701 701 },
702 702 {
... ... @@ -737,15 +737,15 @@
737 737 ],
738 738 "source": [
739 739 "resmap_erange([[emin,1.],\n",
740   - " [1.,10.],\n",
741   - " [10.,emax]])"
  740 + " [1.,10.],\n",
  741 + " [10.,emax]])"
742 742 ]
743 743 },
744 744 {
745 745 "cell_type": "markdown",
746 746 "metadata": {},
747 747 "source": [
748   - "Now we actually have an excess at the highest energies. In spite of the significant likelihood improvement the model is not quite perfect yet. Is there perhaps a new spectral component appearing at high energies? We will test if the addition of a power-law spectral component with a hard index (2). It will be added to the exponentially-cutoff power law in a composite spectral model."
  748 + "Now you actually have an excess at the highest energies. In spite of the significant likelihood improvement the model is not quite perfect yet. Is there perhaps a new spectral component appearing at high energies? Test if the addition of a power-law spectral component with a hard index (2) improves things. To do this, add the hard spectral component to the exponentially-cutoff power law using a composite spectral model."
749 749 ]
750 750 },
751 751 {
... ... @@ -793,7 +793,7 @@
793 793 "cell_type": "markdown",
794 794 "metadata": {},
795 795 "source": [
796   - "The likelihood improvement is again significant, but did we already find the best possible model of the sky?"
  796 + "The likelihood improvement is again significant, but is this the best possible model of the sky?"
797 797 ]
798 798 },
799 799 {
... ...
doc/source/users/tutorials/beyond/combining-observations.ipynb renamed to doc/source/users/tutorials/howto/howto_combine_observations.ipynb
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... ... @@ -4,7 +4,7 @@
4 4 "cell_type": "markdown",
5 5 "metadata": {},
6 6 "source": [
7   - "# Combining observations"
  7 + "# How to combine observations?"
8 8 ]
9 9 },
10 10 {
... ... @@ -133,7 +133,7 @@
133 133 "cell_type": "markdown",
134 134 "metadata": {},
135 135 "source": [
136   - "The file contains a single `observation_list` tag that contains two observation tags that each define an observation. Each observation has a `name`, an `id` and an `instrument` attribute. The name attribute can have any arbitrary value, and may be the same for all observations. However, **the id attribute needs to be a unique character string for any given instrument**. The instrument attribute is a case-sensitive string that identifies the instrument with which the observation was taken. Please make sure that the instrument string is set correctly so that ctools knows which instrument specific functions need to be called.\n",
  136 + "The file contains a single `observation_list` tag that contains two `observation` tags that each define an observation. Each observation has a `name`, an `id` and an `instrument` attribute. The name attribute can have any arbitrary value, and may be the same for all observations. However, **the id attribute needs to be a unique character string for any given instrument**. The instrument attribute is a case-sensitive string that identifies the instrument with which the observation was taken. Please make sure that the instrument string is set correctly so that ctools knows which instrument specific functions need to be called.\n",
137 137 "\n",
138 138 "**Note:** the instrument string for a CTA observation is unsurprisingly `CTA`. In case that you want to analyse data from an existing Imaging Air Cherenkov Telescope you can also set the instrument string to HESS, MAGIC, or VERITAS. You may also combine observations from different telescopes for a joint analysis in an observation definition file. Please recall that instrument strings are case sensitive.\n",
139 139 "\n",
... ...
doc/source/users/tutorials/beyond/beyond_irf.rst renamed to doc/source/users/tutorials/howto/howto_connect_irfs.rst
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1   -.. _sec_connecting_irf:
  1 +.. _howto_connect_irfs:
  2 +
  3 +How to connect observations to dedicated instrument response functions?
  4 +-----------------------------------------------------------------------
  5 +
  6 + .. admonition:: What you will learn
  7 +
  8 + You will learn how to **connect individual observations to dedicated
  9 + Instrument Response Functions**.
2 10  
3   -Connecting observations to dedicated instrument response functions
4   -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
5 11  
6 12 So far you used the same instrument response function for all observations.
7 13 You always specified the calibration database ``prod2`` and the instrument
... ...
doc/source/users/tutorials/beyond/resmap-bkg.png renamed to doc/source/users/tutorials/howto/howto_connect_models.png
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doc/source/users/tutorials/beyond/beyond_model.rst renamed to doc/source/users/tutorials/howto/howto_connect_models.rst
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1   -.. _sec_connecting_model:
  1 +.. _howto_connect_models:
2 2  
3   -Connecting observations to specific models
4   -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  3 +How to connecting observations to specific models?
  4 +--------------------------------------------------
  5 +
  6 + .. admonition:: What you will learn
  7 +
  8 + You will learn how to **connect individual observations to specific
  9 + model components**.
5 10  
6 11 In the previous examples there was always a single background model
7 12 component to describe the residual particle background in the
... ... @@ -68,7 +73,6 @@ tied to the ``events2.fits`` file.
68 73 </source_library>
69 74  
70 75 .. note::
71   -
72 76 **Model components in a XML file need to have a unique name.**
73 77 For this reason the components are named here ``Background_00001``
74 78 and ``Background_00002``.
... ... @@ -86,7 +90,7 @@ Obviously, the upper observation has larger residuals owing to the ten
86 90 times larger background rate that was used in the simulation of the
87 91 associated data.
88 92  
89   -.. figure:: resmap-bkg.png
  93 +.. figure:: howto_connect_models.png
90 94 :height: 400px
91 95 :align: center
92 96  
... ... @@ -128,8 +132,3 @@ This is illustrated in the model definition file below where component
128 132 </spectrum>
129 133 </source>
130 134 </source_library>
131   -
132   -
133   -
134   -
135   -
... ...
doc/source/users/tutorials/howto/howto_display.rst
  View file @81c7826
... ... @@ -21,21 +21,27 @@ included in the ctools package that rely on the
21 21 Python module. You can find these scripts in the
22 22 ``$CTOOLS/share/examples/python`` folder. The following scripts are available:
23 23  
24   - +------------------------+-----------------------------+
25   - | Script | Usage |
26   - +========================+=============================+
27   - | ``show_butterfly.py`` | Display a butterfly diagram |
28   - +------------------------+-----------------------------+
29   - | ``show_lightcurve.py`` | Display a light curve |
30   - +------------------------+-----------------------------+
31   - | ``show_obs.py`` | Display observation summary |
32   - +------------------------+-----------------------------+
33   - | ``show_pointings.py`` | Display pointing directions |
34   - +------------------------+-----------------------------+
35   - | ``show_phases.py`` | Display event phases |
36   - +------------------------+-----------------------------+
37   - | ``show_spectrum.py`` | Display a spectrum |
38   - +------------------------+-----------------------------+
  24 + +------------------------+--------------------------------------+
  25 + | Script | Usage |
  26 + +========================+======================================+
  27 + | ``show_butterfly.py`` | Display a butterfly diagram |
  28 + +------------------------+--------------------------------------+
  29 + | ``show_irf.py`` | Display Instrument Response Function |
  30 + +------------------------+--------------------------------------+
  31 + | ``show_lightcurve.py`` | Display a light curve |
  32 + +------------------------+--------------------------------------+
  33 + | ``show_obs.py`` | Display observation summary |
  34 + +------------------------+--------------------------------------+
  35 + | ``show_phases.py`` | Display event phases |
  36 + +------------------------+--------------------------------------+
  37 + | ``show_pointings.py`` | Display pointing directions |
  38 + +------------------------+--------------------------------------+
  39 + | ``show_residuals.py`` | Display spectral residuals |
  40 + +------------------------+--------------------------------------+
  41 + | ``show_spectrum.py`` | Display a spectrum |
  42 + +------------------------+--------------------------------------+
  43 +
  44 +**Do not hesitate to copy and adapt these scripts to your needs.**
39 45  
40 46 Below some usage examples and the expected output.
41 47  
... ... @@ -44,7 +50,7 @@ show_butterfly.py
44 50  
45 51 .. code-block:: bash
46 52  
47   - $ $CTOOLS/share/examples/python/show_butterfly.py butterfly_src001.txt
  53 + $ $CTOOLS/share/examples/python/show_butterfly.py butterfly.txt
48 54  
49 55 .. figure:: howto_display_butterfly.png
50 56 :width: 600px
... ... @@ -53,6 +59,20 @@ show_butterfly.py
53 59 *Butterfly diagram displayed with show_butterfly.py*
54 60  
55 61  
  62 +show_irf.py
  63 +^^^^^^^^^^^
  64 +
  65 +.. code-block:: bash
  66 +
  67 + $ $CTOOLS/share/examples/python/show_irf.py prod2 South_50h
  68 +
  69 +.. figure:: howto_display_irf.png
  70 + :width: 800px
  71 + :align: center
  72 +
  73 + *Instrument Response Function displayed with show_irf.py*
  74 +
  75 +
56 76 show_lightcurve.py
57 77 ^^^^^^^^^^^^^^^^^^
58 78  
... ... @@ -72,7 +92,7 @@ show_obs.py
72 92  
73 93 .. code-block:: bash
74 94  
75   - $ $CTOOLS/share/examples/python/show_obs.py obs_selected.xml
  95 + $ $CTOOLS/share/examples/python/show_obs.py obs.xml
76 96  
77 97 .. figure:: howto_display_obs.png
78 98 :width: 600px
... ... @@ -81,32 +101,46 @@ show_obs.py
81 101 *Observation summary displayed with show_obs.py*
82 102  
83 103  
  104 +show_phases.py
  105 +^^^^^^^^^^^^^^
  106 +
  107 +.. code-block:: bash
  108 +
  109 + $ $CTOOLS/share/examples/python/show_phases.py -n 50 events_phased.fits
  110 +
  111 +.. figure:: howto_display_phases.png
  112 + :width: 600px
  113 + :align: center
  114 +
  115 + *Event phases displayed with show_phases.py*
  116 +
  117 +
84 118 show_pointings.py
85 119 ^^^^^^^^^^^^^^^^^
86 120  
87 121 .. code-block:: bash
88 122  
89   - $ $CTOOLS/share/examples/python/show_pointings.py obs_selected.xml
  123 + $ $CTOOLS/share/examples/python/show_pointings.py obs.xml
90 124  
91 125 .. figure:: howto_display_pointings.png
92 126 :width: 600px
93 127 :align: center
94 128  
95   - *Observation summary displayed with show_pointings.py (zoomed in)*
  129 + *Pointings displayed with show_pointings.py (zoomed in)*
96 130  
97 131  
98   -show_phases.py
99   -^^^^^^^^^^^^^^
  132 +show_residuals.py
  133 +^^^^^^^^^^^^^^^^^
100 134  
101 135 .. code-block:: bash
102 136  
103   - $ $CTOOLS/share/examples/python/show_phases.py -n 50 events_phased.fits
  137 + $ $CTOOLS/share/examples/python/show_residuals.py residual.fits
104 138  
105   -.. figure:: howto_display_phases.png
  139 +.. figure:: howto_display_residuals.png
106 140 :width: 600px
107 141 :align: center
108 142  
109   - *Event phases displayed with show_phases.py*
  143 + *Spectral residuals displayed with show_residuals.py*
110 144  
111 145  
112 146 show_spectrum.py
... ... @@ -114,12 +148,10 @@ show_spectrum.py
114 148  
115 149 .. code-block:: bash
116 150  
117   - $ $CTOOLS/share/examples/python/show_spectrum.py spectrum_src001.fits
  151 + $ $CTOOLS/share/examples/python/show_spectrum.py spectrum.fits
118 152  
119 153 .. figure:: howto_display_spectrum.png
120 154 :width: 600px
121 155 :align: center
122 156  
123   - *Observation summary displayed with show_spectrum.py*
124   -
125   -
  157 + *Spectrum displayed with show_spectrum.py*
... ...
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doc/source/users/tutorials/beyond/stacked-analysis.ipynb renamed to doc/source/users/tutorials/howto/howto_stacked_analysis.ipynb
  View file @81c7826
... ... @@ -4,7 +4,7 @@
4 4 "cell_type": "markdown",
5 5 "metadata": {},
6 6 "source": [
7   - "# Performing a stacked analysis"
  7 + "# How to perform a stacked analysis?"
8 8 ]
9 9 },
10 10 {
... ... @@ -38,7 +38,7 @@
38 38 "cell_type": "markdown",
39 39 "metadata": {},
40 40 "source": [
41   - "The data and observation definition XML file obs.xml used here are those produced in the previous tutorial **Combining observations**.\n",
  41 + "The data and observation definition XML file `obs.xml` used here are those produced in the previous tutorial [How to combine observations?](howto_combine_observations.ipynb)\n",
42 42 "\n",
43 43 "## Stacking Events\n",
44 44 "\n",
... ... @@ -215,7 +215,7 @@
215 215 "cell_type": "markdown",
216 216 "metadata": {},
217 217 "source": [
218   - "The Crab source component is the same that is also present in `$CTOOLS/share/models/crab.xml` and is not modified. The background component, however, has been replaced by a model of type \"CTACubeBackground\". This model is a 3-dimensional data cube that describes the expected background rate as function of spatial position and energy. The data cube is multiplied by a power law spectrum that allows to adjust the normalization and slope of the background spectrum in the fit. This power law could be replaced by any spectral model that is found as an appropriate multiplicator to the background cube.\n",
  218 + "The Crab source component is the same that is also present in `$CTOOLS/share/models/crab.xml` and is not modified. The background component, however, has been replaced by a model of type `CTACubeBackground`. This model is a 3-dimensional data cube that describes the expected background rate as function of spatial position and energy. The data cube is multiplied by a power law spectrum that allows to adjust the normalization and slope of the background spectrum in the fit. This power law could be replaced by any spectral model that is found as an appropriate multiplicator to the background cube.\n",
219 219 "\n",
220 220 "**There is no constraint on providing the same spatial binning or the same energy binning for an exposure cube, a PSF cube, an energy dispersion cube, a background cube and a counts cube**. ctools interpolates internally all response cubes hence any arbitrary appropriate binning may be used. Using the same binning for the exposure cube, the background cube and the counts cube is only a convenience.\n",
221 221 "\n",
... ...
doc/source/users/tutorials/howto/iact/high_level.rst
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... ... @@ -266,7 +266,7 @@ In case a model cube can be provided, :ref:`csresmap` simply collapses both cube
266 266 Compute a test statistics (TS) map
267 267 ----------------------------------
268 268 The test statistics quantity is a more precise measurement of statistic than the ``SUBDIVSQRT`` option in :ref:`csresmap`.
269   -To get familiar with the concept of this procedure, :ref:`read more about TS maps <sec_tsmap>`.
  269 +To get familiar with the concept of this procedure, :ref:`read more about TS maps <howto_ts>`.
270 270  
271 271 .. code-block:: bash
272 272  
... ...
doc/source/users/tutorials/howto/index.rst
  View file @81c7826
1 1 .. _howto:
2 2  
3   -Analysis cookbook
4   -=================
  3 +ctools How-tos
  4 +==============
5 5  
6 6 The following sections teach you how to use ctools to address some typical
7   -science analysis. The sections provide examples that are based on the data
8   -distributed within the CTA Consortium for the
9   -:ref:`first CTA Data Challenge <glossary_1dc>`.
10   -These examples can be easily adapted to any data you have at your disposal.
  7 +science analysis.
  8 +
  9 +CTA data analysis
  10 +-----------------
11 11  
12 12 .. toctree::
13 13 :maxdepth: 1
14 14  
15   - howto_display
  15 + howto_combine_observations
  16 + howto_stacked_analysis
  17 + howto_advanced_python_fitting
  18 + howto_connect_irfs
  19 + howto_connect_models
16 20 howto_ts
17 21 howto_tsmap
18 22 howto_extent
... ... @@ -21,8 +25,13 @@ These examples can be easily adapted to any data you have at your disposal.
21 25 howto_lightcurve
22 26 howto_phasecurve
23 27 howto_exclude
  28 + howto_display
24 29 howto_vo
25 30  
  31 +
  32 +Analysis of data from other instruments
  33 +---------------------------------------
  34 +
26 35 .. toctree::
27 36 :maxdepth: 1
28 37  
... ...
doc/source/users/tutorials/index.rst
  View file @81c7826
... ... @@ -7,7 +7,6 @@ Tutorials
7 7 :maxdepth: 1
8 8  
9 9 quickstart/index
10   - beyond/index
11 10 howto/index
12 11 notebooks
13 12 1dc/index
... ...
doc/source/users/tutorials/notebooks.rst
  View file @81c7826
... ... @@ -15,6 +15,6 @@ it on your computer. All notebooks are also available for download from
15 15 this page.
16 16  
17 17 * :download:`Using ctools from Python <quickstart/ctools-from-python.ipynb>`
18   -* :download:`Combining observations <beyond/combining-observations.ipynb>`
19   -* :download:`Performing a stacked analysis <beyond/stacked-analysis.ipynb>`
20   -* :download:`Advanced model manipulation and fitting in Python <beyond/advanced-python-fitting.ipynb>`
  18 +* :download:`Combining observations <howto/howto_combine_observations.ipynb>`
  19 +* :download:`Performing a stacked analysis <howto/howto_stacked_analysis.ipynb>`
  20 +* :download:`Advanced model manipulation and fitting in Python <howto/howto_advanced_python_fitting.ipynb>`
... ...
doc/source/users/tutorials/quickstart/ctools-from-python.ipynb
  View file @81c7826
... ... @@ -29,10 +29,8 @@
29 29 },
30 30 {
31 31 "cell_type": "code",
32   - "execution_count": 2,
33   - "metadata": {
34   - "collapsed": true
35   - },
  32 + "execution_count": 1,
  33 + "metadata": {},
36 34 "outputs": [],
37 35 "source": [
38 36 "import gammalib\n",
... ... @@ -51,24 +49,22 @@
51 49 },
52 50 {
53 51 "cell_type": "code",
54   - "execution_count": 3,
55   - "metadata": {
56   - "collapsed": true
57   - },
  52 + "execution_count": 2,
  53 + "metadata": {},
58 54 "outputs": [],
59 55 "source": [
60 56 "sim = ctools.ctobssim()\n",
61   - "sim['inmodel'] = '${CTOOLS}/share/models/crab.xml'\n",
  57 + "sim['inmodel'] = '${CTOOLS}/share/models/crab.xml'\n",
62 58 "sim['outevents'] = 'events.fits'\n",
63   - "sim['caldb'] = 'prod2'\n",
64   - "sim['irf'] = 'South_0.5h'\n",
65   - "sim['ra'] = 83.5\n",
66   - "sim['dec'] = 22.8\n",
67   - "sim['rad'] = 5.0\n",
68   - "sim['tmin'] = '2020-01-01T00:00:00'\n",
69   - "sim['tmax'] = '2020-01-01T01:00:00'\n",
70   - "sim['emin'] = 0.03\n",
71   - "sim['emax'] = 200.0\n",
  59 + "sim['caldb'] = 'prod2'\n",
  60 + "sim['irf'] = 'South_0.5h'\n",
  61 + "sim['ra'] = 83.5\n",
  62 + "sim['dec'] = 22.8\n",
  63 + "sim['rad'] = 5.0\n",
  64 + "sim['tmin'] = '2020-01-01T00:00:00'\n",
  65 + "sim['tmax'] = '2020-01-01T01:00:00'\n",
  66 + "sim['emin'] = 0.03\n",
  67 + "sim['emax'] = 150.0\n",
72 68 "sim.execute()"
73 69 ]
74 70 },
... ... @@ -83,7 +79,7 @@
83 79 },
84 80 {
85 81 "cell_type": "code",
86   - "execution_count": 4,
  82 + "execution_count": 3,
87 83 "metadata": {},
88 84 "outputs": [
89 85 {
... ... @@ -112,7 +108,7 @@
112 108 "provided by the hidden seed parameter. Changing this parameter for\r\n",
113 109 "subsequent runs will lead to different event samples.\r\n",
114 110 "\r\n",
115   - "ctobssim performs a safety check on the maximum photon rate for all model \r\n",
  111 + "ctobssim performs a safety check on the maximum photon rate for all model\r\n",
116 112 "components to avoid that the tool locks up and requests huge memory \r\n",
117 113 "resources, which may happen if a mistake was made in setting up the input \r\n",
118 114 "model (for example if an error in the flux units is made). The maximum allowed\r\n",
... ... @@ -140,19 +136,19 @@
140 136 "\r\n",
141 137 "inmodel [file]\r\n",
142 138 " Input model XML file.\r\n",
143   - " \t \t \r\n",
  139 + "\r\n",
144 140 "caldb [string]\r\n",
145 141 " Calibration database.\r\n",
146   - " \t \t \r\n",
  142 + "\r\n",
147 143 "irf [string]\r\n",
148 144 " Instrumental response function.\r\n",
149   - " \t \t \r\n",
  145 + "\r\n",
150 146 "(edisp = no) [boolean]\r\n",
151 147 " Apply energy dispersion?\r\n",
152   - " \t \t \r\n",
  148 + "\r\n",
153 149 "outevents [file]\r\n",
154 150 " Output event list or observation definition XML file.\r\n",
155   - " \t \t \r\n",
  151 + "\r\n",
156 152 "(prefix = sim_events_) [string]\r\n",
157 153 " Prefix for event list in observation definition XML file.\r\n",
158 154 "\r\n",
... ... @@ -164,28 +160,29 @@
164 160 " parameter at the same value for repeatable simulations, or increment \r\n",
165 161 " this value for subsequent runs if non-repeatable simulations are\r\n",
166 162 " required.\r\n",
167   - " \t \t \r\n",
  163 + "\r\n",
168 164 "ra [real]\r\n",
169 165 " Right Ascension of CTA pointing (J2000, in degrees).\r\n",
170   - " \t \t \r\n",
  166 + "\r\n",
171 167 "dec [real]\r\n",
172 168 " Declination of CTA pointing (J2000, in degrees).\r\n",
173   - " \t \t \r\n",
  169 + "\r\n",
174 170 "rad [real]\r\n",
175 171 " Radius of CTA field of view (simulation cone radius) (in degrees).\r\n",
176   - " \t \t \r\n",
  172 + "\r\n",
177 173 "tmin [time]\r\n",
178 174 " Start time (UTC string, JD, MJD or MET in seconds).\r\n",
179   - " \t \t \r\n",
  175 + "\r\n",
180 176 "tmax [time]\r\n",
181 177 " Stop time (UTC string, JD, MJD or MET in seconds).\r\n",
  178 + "\r",
182 179 "\r\n",
183 180 "emin [real]\r\n",
184 181 " Lower energy limit of simulated events (in TeV).\r\n",
185   - " \t \t \r\n",
  182 + "\r\n",
186 183 "emax [real]\r\n",
187 184 " Upper energy limit of simulated events (in TeV).\r\n",
188   - " \t \t \r\n",
  185 + "\r\n",
189 186 "(deadc = 0.95) [real]\r\n",
190 187 " Average deadtime correction factor.\r\n",
191 188 "\r\n",
... ... @@ -206,23 +203,23 @@
206 203 "(chatter = 2) [integer]\r\n",
207 204 " Verbosity of the executable:\r\n",
208 205 " chatter = 0: no information will be logged\r\n",
209   - " \r\n",
  206 + "\r\n",
210 207 " chatter = 1: only errors will be logged\r\n",
211   - " \r\n",
  208 + "\r\n",
212 209 " chatter = 2: errors and actions will be logged\r\n",
213   - " \r\n",
  210 + "\r\n",
214 211 " chatter = 3: report about the task execution\r\n",
215   - " \r\n",
  212 + "\r\n",
216 213 " chatter = 4: detailed report about the task execution\r\n",
217   - " \t \t \r\n",
  214 + "\r\n",
218 215 "(clobber = yes) [boolean]\r\n",
219 216 " Specifies whether existing files should be overwritten.\r\n",
220   - " \t \t \r\n",
  217 + "\r\n",
221 218 "(debug = no) [boolean]\r\n",
222 219 " Enables debug mode. In debug mode the executable will dump any log file output to the console.\r\n",
223   - " \t \t \r\n",
  220 + "\r\n",
224 221 "(mode = ql) [string]\r\n",
225   - " Mode of automatic parameters (default is \"ql\", i.e. \"query and learn\").\r\n",
  222 + " Mode of automatic parameters (default is ql, i.e. \"query and learn\").\r\n",
226 223 "\r\n",
227 224 "(logfile = ctobssim.log) [string]\r\n",
228 225 " Name of log file.\r\n",
... ... @@ -250,10 +247,8 @@
250 247 },
251 248 {
252 249 "cell_type": "code",
253   - "execution_count": 5,
254   - "metadata": {
255   - "collapsed": true
256   - },
  250 + "execution_count": 4,
  251 + "metadata": {},
257 252 "outputs": [],
258 253 "source": [
259 254 "sim.run()"
... ... @@ -270,7 +265,7 @@
270 265 },
271 266 {
272 267 "cell_type": "code",
273   - "execution_count": 6,
  268 + "execution_count": 5,
274 269 "metadata": {},
275 270 "outputs": [
276 271 {
... ... @@ -280,7 +275,7 @@
280 275 "=== GObservations ===\n",
281 276 " Number of observations ....: 1\n",
282 277 " Number of models ..........: 2\n",
283   - " Number of observed events .: 202766\n",
  278 + " Number of observed events .: 200741\n",
284 279 " Number of predicted events : 0\n"
285 280 ]
286 281 }
... ... @@ -298,7 +293,7 @@
298 293 },
299 294 {
300 295 "cell_type": "code",
301   - "execution_count": 7,
  296 + "execution_count": 6,
302 297 "metadata": {},
303 298 "outputs": [
304 299 {
... ... @@ -307,7 +302,7 @@
307 302 "text": [
308 303 "=== GCTAObservation ===\n",
309 304 " Name ......................: \n",
310   - " Identifier ................: \n",
  305 + " Identifier ................: 000001\n",
311 306 " Instrument ................: CTA\n",
312 307 " Event file ................: events.fits\n",
313 308 " Event type ................: EventList\n",
... ... @@ -317,7 +312,7 @@
317 312 " Deadtime correction .......: 0.98\n",
318 313 " User energy range .........: undefined\n",
319 314 "=== GCTAPointing ===\n",
320   - " Pointing direction ........: (RA,Dec)=(83.63,22.01)\n",
  315 + " Pointing direction ........: (RA,Dec)=(83.5,22.8)\n",
321 316 "=== GCTAResponseIrf ===\n",
322 317 " Caldb mission .............: cta\n",
323 318 " Caldb instrument ..........: prod2\n",
... ... @@ -325,10 +320,12 @@
325 320 " Energy dispersion .........: Not used\n",
326 321 " Save energy range .........: undefined\n",
327 322 "=== GCTAEventList ===\n",
328   - " Number of events ..........: 202766 (disposed in \"events.fits\")\n",
  323 + " Number of events ..........: 200741 (disposed in \"events.fits\")\n",
329 324 " Time interval .............: 58849.0008007407 - 58849.0424674074 days\n",
330   - " Energy interval ...........: 0.03 - 200 TeV\n",
331   - " Region of interest ........: RA=83.63, DEC=22.01 [0,0] Radius=5 deg\n"
  325 + " Energy interval ...........: 0.03 - 150 TeV\n",
  326 + " Region of interest ........: RA=83.5, DEC=22.8 [0,0] Radius=5 deg\n",
  327 + "=== GSkyRegions ===\n",
  328 + " Number of regions .........: 0\n"
332 329 ]
333 330 }
334 331 ],
... ... @@ -345,14 +342,14 @@
345 342 },
346 343 {
347 344 "cell_type": "code",
348   - "execution_count": 8,
  345 + "execution_count": 7,
349 346 "metadata": {},
350 347 "outputs": [
351 348 {
352 349 "name": "stdout",
353 350 "output_type": "stream",
354 351 "text": [
355   - "Dir=RA=83.6182556152344, DEC=22.2843074798584 [0.00478756989312195,-0.000189682185722814] Energy=63.157357275486 GeV Time=315532804.699509 s (TT)\n"
  352 + "Dir=RA=83.7821807861328, DEC=22.0288944244385 [-0.0134540141482956,0.00456559645656115] Energy=36.9588024914265 GeV Time=315532804.286922 s (TT)\n"
356 353 ]
357 354 }
358 355 ],
... ... @@ -371,14 +368,14 @@
371 368 },
372 369 {
373 370 "cell_type": "code",
374   - "execution_count": 9,
  371 + "execution_count": 8,
375 372 "metadata": {},
376 373 "outputs": [
377 374 {
378 375 "data": {
379   - "image/png": 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wJWlOWPAlaU5Y8CVpTnhYpiTNAA/LHBEPyzTW9MXbqLHajudhmd2c0pGkOWHBl6Q5YcGX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\nYII=\n",
380 377 "text/plain": [
381   - "<matplotlib.figure.Figure at 0x114dbb128>"
  378 + "<matplotlib.figure.Figure at 0x108a56950>"
382 379 ]
383 380 },
384 381 "metadata": {},
... ... @@ -412,10 +409,8 @@
412 409 },
413 410 {
414 411 "cell_type": "code",
415   - "execution_count": 10,
416   - "metadata": {
417   - "collapsed": true
418   - },
  412 + "execution_count": 9,
  413 + "metadata": {},
419 414 "outputs": [],
420 415 "source": [
421 416 "like = ctools.ctlike(sim.obs())\n",
... ... @@ -437,7 +432,7 @@
437 432 },
438 433 {
439 434 "cell_type": "code",
440   - "execution_count": 11,
  435 + "execution_count": 10,
441 436 "metadata": {},
442 437 "outputs": [
443 438 {
... ... @@ -445,7 +440,7 @@
445 440 "output_type": "stream",
446 441 "text": [
447 442 "=== GOptimizerLM ===\n",
448   - " Optimized function value ..: 757618.425\n",
  443 + " Optimized function value ..: 755051.482\n",
449 444 " Absolute precision ........: 0.005\n",
450 445 " Acceptable value decrease .: 2\n",
451 446 " Optimization status .......: converged\n",
... ... @@ -469,7 +464,7 @@
469 464 },
470 465 {
471 466 "cell_type": "code",
472   - "execution_count": 12,
  467 + "execution_count": 11,
473 468 "metadata": {},
474 469 "outputs": [
475 470 {
... ... @@ -491,8 +486,8 @@
491 486 " RA .......................: 83.6331 [-360,360] deg (fixed,scale=1)\n",
492 487 " DEC ......................: 22.0145 [-90,90] deg (fixed,scale=1)\n",
493 488 " Number of spectral par's ..: 3\n",
494   - " Prefactor ................: 5.73901839854211e-16 +/- 5.75150678022232e-18 [1e-23,1e-13] ph/cm2/s/MeV (free,scale=1e-16,gradient)\n",
495   - " Index ....................: -2.46442704108736 +/- 0.00738985717701118 [-0,-5] (free,scale=-1,gradient)\n",
  489 + " Prefactor ................: 5.69396634052842e-16 +/- 6.14427401423559e-18 [1e-23,1e-13] ph/cm2/s/MeV (free,scale=1e-16,gradient)\n",
  490 + " Index ....................: -2.4703556883579 +/- 0.00792538918685176 [-0,-5] (free,scale=-1,gradient)\n",
496 491 " PivotEnergy ..............: 300000 [10000,1000000000] MeV (fixed,scale=1000000,gradient)\n",
497 492 " Number of temporal par's ..: 1\n",
498 493 " Normalization ............: 1 (relative value) (fixed,scale=1,gradient)\n",
... ... @@ -504,8 +499,8 @@
504 499 " Model type ................: \"PowerLaw\" * \"Constant\"\n",
505 500 " Number of parameters ......: 4\n",
506 501 " Number of spectral par's ..: 3\n",
507   - " Prefactor ................: 0.995734795709415 +/- 0.00725726198557001 [0.001,1000] ph/cm2/s/MeV (free,scale=1,gradient)\n",
508   - " Index ....................: -0.00198344390952578 +/- 0.00257263793207067 [-5,5] (free,scale=1,gradient)\n",
  502 + " Prefactor ................: 0.9951294839032 +/- 0.00725734189801964 [0.001,1000] ph/cm2/s/MeV (free,scale=1,gradient)\n",
  503 + " Index ....................: -0.00197954530750781 +/- 0.00257407441298647 [-5,5] (free,scale=1,gradient)\n",
509 504 " PivotEnergy ..............: 1000000 [10000,1000000000] MeV (fixed,scale=1000000,gradient)\n",
510 505 " Number of temporal par's ..: 1\n",
511 506 " Normalization ............: 1 (relative value) (fixed,scale=1,gradient)\n"
... ... @@ -520,19 +515,19 @@
520 515 "cell_type": "markdown",
521 516 "metadata": {},
522 517 "source": [
523   - "For example, in this way we can fetch the minimum of the optimized function (the opposite of the likelihood logarithm) to compare different model hypotheses."
  518 + "For example, in this way we can fetch the minimum of the optimized function (the negative of the natural logarithm of the likelihood) to compare different model hypotheses."
524 519 ]
525 520 },
526 521 {
527 522 "cell_type": "code",
528   - "execution_count": 13,
  523 + "execution_count": 12,
529 524 "metadata": {},
530 525 "outputs": [
531 526 {
532 527 "name": "stdout",
533 528 "output_type": "stream",
534 529 "text": [
535   - "757618.4249159902\n"
  530 + "755051.481962\n"
536 531 ]
537 532 }
538 533 ],
... ... @@ -550,7 +545,7 @@
550 545 },
551 546 {
552 547 "cell_type": "code",
553   - "execution_count": 14,
  548 + "execution_count": 13,
554 549 "metadata": {},
555 550 "outputs": [
556 551 {
... ... @@ -569,11 +564,11 @@
569 564 " Model components ..........: \"PointSource\" * \"PowerLaw\" * \"Constant\"\n",
570 565 " Number of parameters ......: 6\n",
571 566 " Number of spatial par's ...: 2\n",
572   - " RA .......................: 83.6334964430607 +/- 0.000614768905318078 [-360,360] deg (free,scale=1)\n",
573   - " DEC ......................: 22.0149467750683 +/- 0.000559548446961086 [-90,90] deg (free,scale=1)\n",
  567 + " RA .......................: 83.6324977668637 +/- 0.000645834980167342 [-360,360] deg (free,scale=1)\n",
  568 + " DEC ......................: 22.0156097018479 +/- 0.000603833638486857 [-90,90] deg (free,scale=1)\n",
574 569 " Number of spectral par's ..: 3\n",
575   - " Prefactor ................: 5.73898570353797e-16 +/- 5.75155055360256e-18 [1e-23,1e-13] ph/cm2/s/MeV (free,scale=1e-16,gradient)\n",
576   - " Index ....................: -2.46439956654049 +/- 0.00739170138357582 [-0,-5] (free,scale=-1,gradient)\n",
  570 + " Prefactor ................: 5.69123259664292e-16 +/- 6.14234382363775e-18 [1e-23,1e-13] ph/cm2/s/MeV (free,scale=1e-16,gradient)\n",
  571 + " Index ....................: -2.47037429659339 +/- 0.00792634862711166 [-0,-5] (free,scale=-1,gradient)\n",
577 572 " PivotEnergy ..............: 300000 [10000,1000000000] MeV (fixed,scale=1000000,gradient)\n",
578 573 " Number of temporal par's ..: 1\n",
579 574 " Normalization ............: 1 (relative value) (fixed,scale=1,gradient)\n",
... ... @@ -585,8 +580,8 @@
585 580 " Model type ................: \"PowerLaw\" * \"Constant\"\n",
586 581 " Number of parameters ......: 4\n",
587 582 " Number of spectral par's ..: 3\n",
588   - " Prefactor ................: 0.995729516865969 +/- 0.0072572344873009 [0.001,1000] ph/cm2/s/MeV (free,scale=1,gradient)\n",
589   - " Index ....................: -0.00198584806013523 +/- 0.00257264072051407 [-5,5] (free,scale=1,gradient)\n",
  583 + " Prefactor ................: 0.995120900180708 +/- 0.00725727612144389 [0.001,1000] ph/cm2/s/MeV (free,scale=1,gradient)\n",
  584 + " Index ....................: -0.00198038808966019 +/- 0.00257407550475833 [-5,5] (free,scale=1,gradient)\n",
590 585 " PivotEnergy ..............: 1000000 [10000,1000000000] MeV (fixed,scale=1000000,gradient)\n",
591 586 " Number of temporal par's ..: 1\n",
592 587 " Normalization ............: 1 (relative value) (fixed,scale=1,gradient)\n"
... ... @@ -609,20 +604,20 @@
609 604 },
610 605 {
611 606 "cell_type": "code",
612   - "execution_count": 16,
  607 + "execution_count": 14,
613 608 "metadata": {},
614 609 "outputs": [
615 610 {
616 611 "name": "stdout",
617 612 "output_type": "stream",
618 613 "text": [
619   - "1.0637600922491401\n"
  614 + "4.27571920515\n"
620 615 ]
621 616 }
622 617 ],
623 618 "source": [
624 619 "like2 = like.opt().value()\n",
625   - "ts = -2 * (like2 - like1)\n",
  620 + "ts = -2.0 * (like2 - like1)\n",
626 621 "print(ts)"
627 622 ]
628 623 },
... ... @@ -630,27 +625,34 @@
630 625 "cell_type": "markdown",
631 626 "metadata": {},
632 627 "source": [
633   - "The test statistic TS is expected to be distributed as a chi square with a number of degrees of freedom equal to the additional number of degrees of freedom of the (second) more complex model with respect to the (first) more parsimonious one, for our case two degrees of freedom. The chance probability that the likelihood improved that much because of pure statistical fluctuations is the integral from TS to infinity of the chi square with two degrees of freedom. In this case the improvement is negligible (i.e., the chance probability is very high), as expected since in the model the source is already at the true position."
  628 + "The test statistic (TS) is expected to be distributed as a $\\chi^2_n$ with a number of degrees of freedom $n$ equal to the additional number of degrees of freedom of the (second) more complex model with respect to the (first) more parsimonious one, for our case two degrees of freedom. The chance probability that the likelihood improved that much because of pure statistical fluctuations is the integral from TS to infinity of the chi square with two degrees of freedom. In this case the improvement is negligible (i.e., the chance probability is very high), as expected since in the model the source is already at the true position."
634 629 ]
  630 + },
  631 + {
  632 + "cell_type": "code",
  633 + "execution_count": null,
  634 + "metadata": {},
  635 + "outputs": [],
  636 + "source": []
635 637 }
636 638 ],
637 639 "metadata": {
638 640 "kernelspec": {
639   - "display_name": "Python 3",
  641 + "display_name": "Python 2",
640 642 "language": "python",
641   - "name": "python3"
  643 + "name": "python2"
642 644 },
643 645 "language_info": {
644 646 "codemirror_mode": {
645 647 "name": "ipython",
646   - "version": 3
  648 + "version": 2
647 649 },
648 650 "file_extension": ".py",
649 651 "mimetype": "text/x-python",
650 652 "name": "python",
651 653 "nbconvert_exporter": "python",
652   - "pygments_lexer": "ipython3",
653   - "version": "3.6.2"
  654 + "pygments_lexer": "ipython2",
  655 + "version": "2.7.11"
654 656 }
655 657 },
656 658 "nbformat": 4,
... ...
doc/source/users/user_contributed/index.rst
  View file @81c7826
... ... @@ -3,6 +3,7 @@
3 3 User Contributed Material
4 4 =========================
5 5  
6   -This section of the manual provides examples and Jupyter Notebooks contributed
7   -by ctools users.
  6 +This section provides examples and Jupyter Notebooks contributed by ctools
  7 +users. Feel free to send your material to ctools@irap.omp.eu so that it can
  8 +be integrated into the documentation.
8 9  
... ...
models/crab_beyond.xml
  View file @81c7826
... ... @@ -3,17 +3,17 @@
3 3 <source name="Crab" type="PointSource">
4 4 <spectrum type="Composite">
5 5 <spectrum type="LogParabola">
6   - <parameter name="Prefactor" scale="1e-17" value="3.0" min="1e-07" max="1000.0" free="1"/>
7   - <parameter name="Index" scale="-1" value="2.5" min="0.0" max="+5.0" free="1"/>
8   - <parameter name="Curvature" scale="-1" value="0.45" min="-5.0" max="+5.0" free="1"/>
9   - <parameter name="PivotEnergy" scale="1e6" value="1.0" min="0.01" max="1000.0" free="0"/>
  6 + <parameter name="Prefactor" scale="1e-17" value="3.0" min="1e-07" max="1000.0" free="1"/>
  7 + <parameter name="Index" scale="-1" value="2.5" min="0.0" max="+5.0" free="1"/>
  8 + <parameter name="Curvature" scale="-1" value="0.45" min="-5.0" max="+5.0" free="1"/>
  9 + <parameter name="PivotEnergy" scale="1e6" value="1.0" min="0.01" max="1000.0" free="0"/>
10 10 </spectrum>
11 11 <spectrum type="PowerLaw">
12   - <parameter name="Prefactor" scale="1e-18" value="2.9" min="1.e-7" max="1000.0" free="1"/>
13   - <parameter name="Index" scale="-1" value="2.05" min="0.0" max="+5.0" free="1"/>
14   - <parameter name="PivotEnergy" scale="1e6" value="1.0" min="0.01" max="1000.0" free="0"/>
  12 + <parameter name="Prefactor" scale="1e-18" value="2.9" min="1.e-7" max="1000.0" free="1"/>
  13 + <parameter name="Index" scale="-1" value="2.05" min="0.0" max="+5.0" free="1"/>
  14 + <parameter name="PivotEnergy" scale="1e6" value="1.0" min="0.01" max="1000.0" free="0"/>
15 15 </spectrum>
16   - </spectrum>
  16 + </spectrum>
17 17 <spatialModel type="PointSource">
18 18 <parameter name="RA" scale="1.0" value="83.6331" min="-360" max="360" free="0"/>
19 19 <parameter name="DEC" scale="1.0" value="22.0145" min="-90" max="90" free="0"/>
... ... @@ -24,7 +24,7 @@
24 24 <parameter name="Prefactor" scale="1e-15" value="1.8" min="1e-07" max="1000.0" free="1"/>
25 25 <parameter name="Index" scale="-1" value="2.35" min="0.0" max="+5.0" free="1"/>
26 26 <parameter name="CutoffEnergy" scale="1e6" value="0.3" min="0.01" max="1000.0" free="1"/>
27   - <parameter name="PivotEnergy" scale="1e6" value="0.1" min="0.01" max="1000.0" free="0"/>
  27 + <parameter name="PivotEnergy" scale="1e6" value="0.1" min="0.01" max="1000.0" free="0"/>
28 28 </spectrum>
29 29 <spatialModel type="PointSource">
30 30 <parameter name="RA" scale="1.0" value="83.72" min="-360" max="360" free="0"/>
... ...