.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/fit_with_bounds.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_auto_examples_fit_with_bounds.py>`
        to download the full example code

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_fit_with_bounds.py:


Fit Using Bounds
================

Adapt one of the examples from lmfit to use sympy and pyspecdata.
Eventually, we want to use parts of this in the base library, so we don't have
to retype them every time.

.. GENERATED FROM PYTHON SOURCE LINES 10-59



.. image-sg:: /auto_examples/images/sphx_glr_fit_with_bounds_001.png
   :alt: fit with bounds
   :srcset: /auto_examples/images/sphx_glr_fit_with_bounds_001.png, /auto_examples/images/sphx_glr_fit_with_bounds_001_2_00x.png 2.00x
   :class: sphx-glr-single-img


.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    ----------  logging output to /home/jmfranck/pyspecdata.0.log  ----------
    --> fit_with_bounds.py(28):pyspecdata.core             <module> 2025-01-22 14:37:19,234
    INFO: Functional Form: A*exp(-decay**2*x**2)*sin(shift + x/period)






|

.. code-block:: Python


    import matplotlib.pyplot as plt
    from numpy import exp, linspace, pi, random, sign, sin
    import sympy as sp
    from lmfit import Parameters, minimize
    from lmfit.printfuncs import report_fit
    import numpy as np
    from pyspecdata import *

    init_logging(level="debug")
    np.random.seed(15816)
    fl = figlist_var()
    A, shift, period, decay, x = sp.symbols("A shift period decay x", real=True)
    # create an empty dataset that we will drop the fake data into
    thisfit = lmfitdata(nddata(r_[0:250:1500j], "x"))
    thisfit.functional_form = (
        A * sp.sin(shift + x / period) * sp.exp(-((x * decay) ** 2))
    )
    logger.info(strm("Functional Form:", thisfit.functional_form))
    # {{{ create the "true" parameters for the fake data by pretending like
    #     the true values are a guess, and then outputting the guess data
    true_values = {"A": 14.0, "period": 5.4321, "shift": 0.12345, "decay": 0.01000}
    thisfit.set_guess(true_values)
    thisfit.settoguess()
    mydata = thisfit.eval()
    mydata.add_noise(2.8)
    # }}}
    # {{{Making guess data
    newfit = lmfitdata(mydata)
    newfit.functional_form = thisfit.functional_form
    newfit.set_guess(
        A=dict(value=13.0, max=20, min=0.0),
        shift=dict(value=0.0, max=pi / 2.0, min=-pi / 2.0),
        period=dict(value=2, max=10),
        decay=dict(value=0.02, max=0.10, min=0.00),
    )
    newfit.settoguess()
    guess = newfit.eval(100)
    # }}}
    # {{{ run the fit and generate nddata
    # again, now that this is a class, why is this not handled by the fit method?
    newfit.fit()
    # {{{plot the data with fits and guesses
    plot(mydata, "ro", label="data")
    plot(newfit.eval(100), "b", alpha=0.5, label="fit")
    plot(guess, "g--", label="guess")
    # }}}
    plt.legend()
    plt.show()


.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 0.488 seconds)


.. _sphx_glr_download_auto_examples_fit_with_bounds.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: fit_with_bounds.ipynb <fit_with_bounds.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: fit_with_bounds.py <fit_with_bounds.py>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_