Merge pull request #109 from knutfrode/dev

Small updates of documentation

Author: knutfrode

docs/source/index.rst

@@ -35,7 +35,7 @@ Remember to re-install each time you have done an edit during the development pr
 Usage
 -----
 
-*TrajAn* is an `Xarry extension <https://docs.xarray.dev/en/stable/>`_. On drifter (or trajectory) datasets you can use the `.traj` accessor on `xarray.Dataset <https://docs.xarray.dev/en/stable/generated/xarray.Dataset.html>`_ s. In order to register the accessor _trajan_ needs to be imported:
+*TrajAn* is an `Xarry extension <https://docs.xarray.dev/en/stable/internals/extending-xarray.html>`_. On drifter (or trajectory) datasets you can use the `.traj` accessor on `xarray.Dataset <https://docs.xarray.dev/en/stable/generated/xarray.Dataset.html>`_ s. In order to register the accessor, _trajan_ needs to be imported:
 
 .. code-block:: python
 
@@ -54,7 +54,12 @@ Usage
 
 Trajectory datasets from different models and observations tend to have many small differences. TrajAn expects the dataset to be `CF-compliant <http://cfconventions.org/Data/cf-conventions/cf-conventions-1.10/cf-conventions.html#trajectory-data>`_. However, the standard does leave some room for interpretation.
 
-Generally, TrajAn supports two types of data layout: 1) trajectories sampled at different times (unstructured or irregular grid, almost every dataset from real observations. And 2) trajectories sampled at uniform (or a regular grid, typical the output from a model). We often refer to the first type as _2D_ since time is a function of trajectory and observation, while the second type is _1D_ and time is only a function of observation. __TrajAn__ will detect which type of dataset you have and you will have access to the appropriate methods for the type data layout.
+Generally, TrajAn supports two types of data layout:
+  1) trajectories sampled at different times (unstructured or irregular grid), almost every dataset from real observations.
+  2) trajectories sampled at uniform (or regular) grid, typical the output from a model.
+
+We refer to the first type as _2D_ since time is a function of trajectory and observation, while the second type is _1D_ and time is only a function of observation.
+__TrajAn__ will detect which type of dataset you have and you will have access to the appropriate methods for the type data layout.
 
 While the first type (_2D_) is more general it often limits analysis that require trajectories to be sampled at the same points, you can therefor convert a _2D_ dataset to _1D_ by using :meth:`trajan.traj2d.Traj2d.gridtime`.