Computing distances: cdist and pdist
--------------------------------------

In this example, we use the PyCVI counterparts of `pdist <https://docs.scipy.org/doc/scipy/reference/generated/scipy.spatial.distance.pdist.html>`_ and `cdist <https://docs.scipy.org/doc/scipy/reference/generated/scipy.spatial.distance.cdist.html>`_ from SciPy, namely :func:`pycvi.dist.f_pdist` and :func:`pycvi.dist.f_cdist`, to compute distance matrices with time-series data the same way these functions are used with non-time-series data. Their behavior is the same as SciPy's functions, but for time-series data, distance functions specifically designed for time-series are actually used and implemented in `aeon <https://www.aeon-toolkit.org/en/stable/>`_'.

Note that in the case of :func:`pycvi.dist.f_pdist`, a condensed distance matrix is returned (as in scipy).

.. include:: /examples/examples_reminders.rst

.. literalinclude:: ../../examples/pdist_cdist/pdist_cdist.py
   :linenos:
   :start-after: sys.stdout = fout
   :end-before: fout.close()
   :emphasize-lines: 20, 28-30, 47, 55-57

.. literalinclude:: ../../examples/pdist_cdist/output-pdist_cdist.txt
   :language: text