Fix some documentation bugs

Jürgen Knödlseder
1 parent 02cfa05d
Showing 22 changed files with 29 additions and 30 deletions
doc/source/users/reference_manual/cstsdist.rst
doc/source/users/tutorials/1dc/first_fitting.rst
doc/source/users/tutorials/1dc/first_improving.rst
doc/source/users/tutorials/1dc/first_stacked.rst
doc/source/users/tutorials/howto/comptel/howto_comptel_fitting.rst
doc/source/users/tutorials/howto/fermi/howto_fermi_fitting.rst
doc/source/users/tutorials/howto/howto_display.rst
doc/source/users/tutorials/howto/howto_edisp.rst
doc/source/users/tutorials/howto/howto_exclude.rst
doc/source/users/tutorials/howto/howto_extent.rst
doc/source/users/tutorials/howto/howto_lightcurve.rst
doc/source/users/tutorials/howto/howto_phasecurve.rst
doc/source/users/tutorials/howto/howto_ts.rst
doc/source/users/tutorials/howto/howto_tsmap.rst
doc/source/users/tutorials/howto/howto_ulimit.rst
doc/source/users/tutorials/howto/howto_vo.rst
doc/source/users/tutorials/howto/index.rst
doc/source/users/tutorials/quickstart/butterfly.rst
doc/source/users/tutorials/quickstart/onoff.rst
doc/source/users/tutorials/quickstart/residual_map.rst
@@ -15,7 +15,7 @@ sets. The Test Statistics is defined as twice the log-likelihood difference
 that is obtained when fitting simulated data with and without a given
 source model component.
-:red:`cstsdist` will create an ASCII file in comma-separated value (CSV) format,
+:ref:`cstsdist` will create an ASCII file in comma-separated value (CSV) format,
 containing one row per TS computation. The first row is a header row providing
 the column names. The following rows give the TS value, the log-likelihood 
 values of the fit with or without the source, the number of observed and 
@@ -16,7 +16,7 @@ Fitting the model components to the counts cube
      scripts for result display that use the ``matplotlib`` Python module can be
      found in the
      ``$CTOOLS/share/examples/python``
-     folder (see :ref:`how to display results<1dc_howto_display>`).
+     folder (see :ref:`how to display results<howto_display>`).
 Now you are ready to fit the model to the counts cube and to determine its
 maximum likelihood parameters.
@@ -96,7 +96,7 @@ components for these additional sources in the
 :ref:`model definition file <glossary_moddef>`
 in order to reduce the fit residuals.
 An example for such an exercise is shown
-:ref:`here <1dc_howto_extent>`.
+:ref:`here <howto_extent>`.
 .. figure:: first_skymap_residual_iem.png
    :width: 400px
@@ -14,7 +14,7 @@ Stacking the data
      since for many cases the effect of the energy dispersion is negligible,
      and taking energy dispersion into account is computationally intensive. If
      you want to learn how to take the energy dispersion into account please
-     read :ref:`this section<1dc_howto_edisp>`.
+     read :ref:`this section <howto_edisp>`.
 To analyse the selected observations, we recommend to stack the events into
 a counts cube. You do this using the :ref:`ctbin` tool:
@@ -70,13 +70,12 @@ the counts cube, which considerably reduces the number of User parameters
 that are queried by the tool.
 .. note::
-
    The binning of the exposure cube does not need to correspond to the binning
    of the counts cube. In any case, exposure values will be determined by
    interpolation from the values stored in the exposure cube file. The same
    is true for the point spread function and background cubes that are
    described below, or the energy dispersion cube that is described
-   :ref:`here<1dc_howto_edisp>`.
+   :ref:`here <howto_edisp>`.
 Next, :ref:`ctpsfcube` computes the weighted Point Spread Function of the
 stacked counts cube.
@@ -185,7 +185,7 @@ fitted values, and where the statistical uncertainties were added using the
 ``error`` attribute. To investigate how the fit went you should inspect the
 log file ``ctlike.log`` that was also created by :ref:`ctlike`:
-.. code-block:: bash
+.. code-block:: none
    2017-08-26T22:05:05: +=================================+
    2017-08-26T22:05:05: | Maximum likelihood optimisation |
@@ -90,7 +90,7 @@ fitted values, and where the statistical uncertainties were added using the
 ``error`` attribute. To investigate how the fit went you should inspect the
 log file ``ctlike.log`` that was also created by :ref:`ctlike`:
-.. code-block:: bash
+.. code-block:: none
    2017-08-26T10:35:10: +=================================+
    2017-08-26T10:35:10: | Maximum likelihood optimisation |
@@ -193,7 +193,7 @@ using the Fermi-LAT Science Tools.
    when the tool is applied to the same test data. As you will see below,
    the fitted model parameters are basically identical.
-   .. code-block:: bash
+   .. code-block:: none
       Extragalactic_diffuse:
       Normalization: 1
@@ -240,7 +240,7 @@ using the Fermi-LAT Science Tools.
    This results in
-   .. code-block:: bash
+   .. code-block:: none
       2017-08-26T13:05:12: === GModelSky ===
       2017-08-26T13:05:12:  Name ......................: Vela
-.. _1dc_howto_display:
+.. _howto_display:
 How to display the results?
 ---------------------------
-.. _1dc_howto_edisp:
+.. _howto_edisp:
 How to take the energy dispersion into account?
 -----------------------------------------------
-.. _1dc_howto_exclude:
+.. _howto_exclude:
 How to exclude bins from a counts cube?
 ---------------------------------------
-.. _1dc_howto_extent:
+.. _howto_extent:
 How to determine the extension of a source?
 -------------------------------------------
@@ -55,7 +55,7 @@ For illustration, an excerpt of the :ref:`ctlike` log file is shown below.
 The disk with of ``Src003`` has been fitted to 0.335 +/- 0.003 degrees.
 The source is detected with a TS value of 5393.8.
-.. code-block:: bash
+.. code-block:: none
    2017-08-25T19:37:47: === GModelSky ===
    2017-08-25T19:37:47:  Name ......................: Src003
@@ -121,7 +121,7 @@ of 5665.7 which is considerably larger than the TS value of 5393.8 that is found
 above for the radial disk model.
 Below an excerpt of the :ref:`ctlike` log file:
-.. code-block:: bash
+.. code-block:: none
    2017-08-25T20:32:55: === GModelSky ===
    2017-08-25T20:32:55:  Name ......................: Src003
-.. _1dc_howto_ligthcurve:
+.. _howto_ligthcurve:
 How to generate a light curve?
 ------------------------------
-.. _1dc_howto_phasecurve:
+.. _howto_phasecurve:
 How to generate a phase curve of a pulsar?
 ------------------------------------------
-.. _1dc_howto_ts:
+.. _howto_ts:
 How to compute the signifiance of a source?
 -------------------------------------------
-.. _1dc_howto_tsmap:
+.. _howto_tsmap:
 How to generate a Test Statistic map?
 -------------------------------------
-.. _1dc_howto_ulimit:
+.. _howto_ulimit:
 How to compute upper limits?
 ----------------------------
-.. _1dc_howto_vo:
+.. _howto_vo:
 How to use Virtual Observatory tools with ctools?
 -------------------------------------------------
-.. _1dc_howto:
+.. _howto:
 Analysis cookbook
 =================
@@ -63,8 +63,8 @@ A graphical display of the results is shown below:
    Python module. You can find these scripts in the
    ``$CTOOLS/share/examples/python`` folder.
-   Read the section about :ref:`sec_plotting` to learn more about the
-   available scripts. The plot above was generated using:
+   Read :ref:`howto_display` to learn more about the available scripts. The
+   plot above was generated using:
    .. code-block:: bash
@@ -127,7 +127,7 @@ the On region and the Off regions, ``onoff_on.reg`` and
 a skymap where you can see the pointing direction along with the position of
 the On and Off regions.
-.. figure:: onoff.png
+.. figure:: onoff.jpg
    :width: 400px
    :align: center
@@ -38,7 +38,7 @@ the residual counts map. The image is displayed below using
 kernel smoothing applied. Obviously, there are no significant residuals, which
 indicates that the model fit was satisfactory.
-.. figure:: residuals.jpg
+.. figure:: residual_map.jpg
    :width: 400px
    :align: center
@@ -43,7 +43,7 @@ the ctool or cscript followed by the ``--help`` option:
 ctools includes also a Python module that declares every ctool as a
 Python class. The following example illustrates the usage:
-.. code-block:: python
+.. code-block:: bash
    $ python
    >>> import ctools
@@ -57,7 +57,7 @@ ctools comprise also cscripts, which are Python scripts that have the same
 user interface as the ctools binaries. cscripts can be started from the 
 command line or used as Python classes, as illustrated below:
-.. code-block:: python
+.. code-block:: bash
    $ python
    >>> import cscripts
@@ -281,7 +281,7 @@ Diffuse source
      ``Normalization`` can be replaced by ``Prefactor``.
   .. note::
-     You may add the ``normalize="0"``to the spatial model tag to avoid the
+     You may add the ``normalize="0"`` to the spatial model tag to avoid the
      normalization of the diffuse map to an integral of unity
      .. code-block:: xml