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Fix master docs
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ebachelet committed Jun 21, 2023
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12 changes: 6 additions & 6 deletions docs/source/Examples.rst
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In short, here is a short description of the examples:

- `pyLIMA_example_1 <https://github.com/ebachelet/pyLIMA/blob/Rebranding/examples/pyLIMA_example_1.py>`_: tutorial on fitting
- `pyLIMA_example_2 <https://github.com/ebachelet/pyLIMA/blob/Rebranding/examples/pyLIMA_example_2.py>`_: introduction on how to change the default parameters
- `pyLIMA_example_3 <https://github.com/ebachelet/pyLIMA/blob/Rebranding/examples/pyLIMA_example_3.py>`_: introduction on simulation
- `pyLIMA_example_3b <https://github.com/ebachelet/pyLIMA/blob/Rebranding/examples/pyLIMA_example_3b.py>`_: simulation of observations from space
- `pyLIMA_example_4 <https://github.com/ebachelet/pyLIMA/blob/Rebranding/examples/pyLIMA_example_4.py>`_: implementation of user own objective function
- `pyLIMA_example_5 <https://github.com/ebachelet/pyLIMA/blob/Rebranding/examples/pyLIMA_example_5.py>`_: fitting a planetary event
- `pyLIMA_example_1 <https://github.com/ebachelet/pyLIMA/blob/master/examples/pyLIMA_example_1.py>`_: tutorial on fitting
- `pyLIMA_example_2 <https://github.com/ebachelet/pyLIMA/blob/master/examples/pyLIMA_example_2.py>`_: introduction on how to change the default parameters
- `pyLIMA_example_3 <https://github.com/ebachelet/pyLIMA/blob/master/examples/pyLIMA_example_3.py>`_: introduction on simulation
- `pyLIMA_example_3b <https://github.com/ebachelet/pyLIMA/blob/master/examples/pyLIMA_example_3b.py>`_: simulation of observations from space
- `pyLIMA_example_4 <https://github.com/ebachelet/pyLIMA/blob/master/examples/pyLIMA_example_4.py>`_: implementation of user own objective function
- `pyLIMA_example_5 <https://github.com/ebachelet/pyLIMA/blob/master/examples/pyLIMA_example_5.py>`_: fitting a planetary event

Have fun!

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4 changes: 2 additions & 2 deletions docs/source/NotesOnFits.rst
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Notes on fits
=============

Below are some notes, details and advices about the fits. Most of the fits methods relies on `scipy <https://scipy.org/>`_. While several algorithms are implemented, see `here <https://github.com/ebachelet/pyLIMA/tree/Rebranding/pyLIMA/fits>`_, pyLIMA relies mainly of three main fitting methods.
Below are some notes, details and advices about the fits. Most of the fits methods relies on `scipy <https://scipy.org/>`_. While several algorithms are implemented, see `here <https://github.com/ebachelet/pyLIMA/tree/master/pyLIMA/fits>`_, pyLIMA relies mainly of three main fitting methods.

Differential Evolution (DE)
---------------------------
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Priors
------
pyLIMA now includes the possibility to add user-defined priors. While they are no priors by default, uniform and gaussian priors are `available <https://github.com/ebachelet/pyLIMA/blob/Rebranding/pyLIMA/priors/parameters_priors.py>`_. Users can also define their own functions as long as they return a pdf for a given parameters as well as a rvs method, for example with a Cauchy distribution:
pyLIMA now includes the possibility to add user-defined priors. While they are no priors by default, uniform and gaussian priors are `available <https://github.com/ebachelet/pyLIMA/blob/master/pyLIMA/priors/parameters_priors.py>`_. Users can also define their own functions as long as they return a pdf for a given parameters as well as a rvs method, for example with a Cauchy distribution:


.. code-block:: python
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