docs: rm spurious markings from Sphinx format

Author: amorison

docs/cookbook/nura.md

@@ -7,7 +7,7 @@ results of all cases on the same figure, compute statistics etc. The
 [`StagyyData`][stagpy.stagyydata.StagyyData] class comes in handy for that. The
 following script can be used to make a loglog plot of the Nusselt number as
 function of the Rayleigh number using all directories stored where the script
-is executed::
+is executed:
 
 ```py
 #!/usr/bin/env python3

docs/devs/index.md

@@ -24,22 +24,22 @@ repository:
 git remote add upstream [email protected]:StagPython/StagPy.git
 ```
 
-To sync your fork with the main repository, you can run the following::
+To sync your fork with the main repository, you can run the following:
 
 ```sh title="shell"
 git switch master
 git pull upstream master
 git push origin
 ```
 
-To add your own modifications, create a new branch from the tip of master::
+To add your own modifications, create a new branch from the tip of master:
 
 ```sh title="shell"
 git switch -c branch-name master
 ```
 
-where ``branch-name`` is the desired branch name.  Modify the code as desired,
-commit it, and push it on your fork::
+where `branch-name` is the desired branch name.  Modify the code as desired,
+commit it, and push it on your fork:
 
 ```sh title="shell"
 git push -u origin branch-name
@@ -52,7 +52,7 @@ Testing
 -------
 
 StagPy uses [tox for code testing](https://tox.wiki/).  Make sure it
-is installed and up to date on your system::
+is installed and up to date on your system:
 
 ```sh title="shell"
 python3 -m pip install -U tox
@@ -66,7 +66,7 @@ Documentation
 -------------
 
 The StagPy documentation is built with [MkDocs](https://www.mkdocs.org/). To
-build it locally, install the needed packages::
+build it locally, install the needed packages:
 
 ```sh title="shell"
 python3 -m pip install -r docs/requirements.txt

docs/user-guide/getting-started.md

@@ -13,7 +13,7 @@ Command line tool
 -----------------
 
 The various processing capabilities of StagPy are organized in subcommands.
-This means a minimal call to StagPy is as follow::
+This means a minimal call to StagPy is as follow:
 
 ```sh title="shell"
 stagpy <subcommand>
@@ -35,7 +35,7 @@ You can run `stagpy --help` (or `stagpy -h`) to display a help message
 describing those subcommands. You can also run `stagpy <subcommand> --help`
 to have some help on the available options for one particular sub command.
 
-A simple example would be::
+A simple example would be:
 
 ```sh title="shell"
 stagpy field -p path/to/run/ -o T-p -s 42
@@ -84,7 +84,7 @@ output data. This allows you to write your own scripts to do some specific
 processings that aren't implemented in StagPy.
 
 The interface is wrapped in the [`StagyyData`][stagpy.stagyydata.StagyyData] class.
-Instantiating and using this class is rather simple::
+Instantiating and using this class is rather simple:
 
 ```py
 from stagpy.stagyydata import StagyyData
@@ -123,7 +123,7 @@ can specify which style to use with `plot.mplstyle`, available in the command
 line interface with the `--mplstyle` option.  You can specify a
 comma-separated list to combine several styles.  For example, if you want a
 dark-background figure with a font size adapted for slides, you can use the
-following command::
+following command:
 
 ```sh title="shell"
 stagpy field --mplstyle='dark_background,stagpy-slides'

docs/user-guide/install.md

@@ -46,7 +46,7 @@ stagpy config --create
 
 You can enable command-line auto-completion if you use either bash or zsh.
 
-For bash::
+For bash:
 
 ```sh title="shell"
 # adapt path as appropriate for your system

docs/user-guide/stagyydata.md

@@ -15,7 +15,7 @@ sdat = StagyyData(Path("path/to/run/"))
 ```
 
 where `path/to/run/` is the path towards the directory containing your run
-(where the ``par`` file is). This path can be absolute or relative to the
+(where the `par` file is). This path can be absolute or relative to the
 current working directory.
 
 Snapshots and time steps
@@ -146,7 +146,7 @@ attributes defining the geometry of the problem.
 
 `cartesian`, `curvilinear`, `cylindrical`, `spherical` and `yinyang` booleans
 define the shape of the domain (`curvilinear` being the opposite of
-`cartesian`, ``True`` if `cylindrical` or `spherical` is ``True``).
+`cartesian`, `True` if `cylindrical` or `spherical` is `True`).
 
 `twod_xz`, `twod_yz`, `twod` and `threed` booleans indicate the number of
 spatial dimensions in the simulation. Note that fields are always four

stagpy/parfile.py

@@ -46,13 +46,13 @@ def _update(self, par_new: StagyyPar) -> None:
 
     @staticmethod
     def from_main_par(parfile: Path) -> StagyyPar:
-        """Read StagYY namelist ``parfile``.
+        """Read StagYY namelist `parfile`.
 
         The namelist is populated in order with:
 
-        - ``par_name_defaultparameters`` if it is defined in ``parfile``;
-        - ``par_file`` itself;
-        - ``parameters.dat`` if it can be found in the StagYY output directories.
+        - `par_name_defaultparameters` if it is defined in `parfile`;
+        - `par_file` itself;
+        - `parameters.dat` if it can be found in the StagYY output directories.
         """
         root = parfile.parent
         par_main = StagyyPar._from_file(parfile)

stagpy/stagyydata.py

@@ -274,7 +274,7 @@ class Steps:
 
     The `StagyyData.steps` attribute is an instance of this class.
     Time steps (which are [`Step`][stagpy.step.Step] instances) can be
-    accessed with the item accessor::
+    accessed with the item accessor:
 
     ```py
     sdat = StagyyData(Path("path/to/run"))
@@ -385,7 +385,7 @@ class Snaps(Steps):
 
     The `StagyyData.snaps` attribute is an instance of this class.
     Snapshots (which are [`Step`][stagpy.step.Step] instances) can be accessed
-    with the item accessor::
+    with the item accessor:
 
     ```py
     sdat = StagyyData(Path("path/to/run"))
@@ -600,7 +600,7 @@ def filter(
 
         Note that filters are only resolved when the view is iterated.
         Successive calls to :meth:`filter` compose.  For example, with this
-        code::
+        code:
 
         ```py
         view = sdat.steps[500:].filter(rprofs=True, fields=["T"])