.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/fit_complex.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_complex.py>`
        to download the full example code

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

.. _sphx_glr_auto_examples_fit_complex.py:


Fit complex data
================

Using lmfitdata, fit a complex data set.

.. GENERATED FROM PYTHON SOURCE LINES 8-68



.. image-sg:: /auto_examples/images/sphx_glr_fit_complex_001.png
   :alt: fit complex
   :srcset: /auto_examples/images/sphx_glr_fit_complex_001.png, /auto_examples/images/sphx_glr_fit_complex_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_complex.py(25):pyspecdata.core             <module> 2025-01-22 14:37:23,110
    INFO: Functional Form: A*exp(-6.28318530717959*I*nu*t)*exp(-pi*R*Abs(t))






|

.. 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)
    A, R, nu, t = sp.symbols("A R nu t", real=True)
    # create an empty dataset that we will drop the fake data into
    thisfit = lmfitdata(nddata(r_[-1:1:1001j], "t"))
    thisfit.functional_form = (
        A * sp.exp(-1j * 2 * pi * nu * t) * sp.exp(-R * sp.pi * abs(t))
    )
    logger.info(strm("Functional Form:", thisfit.functional_form))
    # {{{ if you set only_real to True, it previously worked -- this
    #     example demonstrates that this also works when set to False
    only_real = False
    if only_real:
        thisfit.functional_form = sp.re(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, "R": 10, "nu": 25}
    thisfit.set_guess(true_values)
    mydata = thisfit.settoguess().eval()
    mydata.add_noise(0.1)
    fig, (ax1, ax2) = plt.subplots(2, 1)
    plot(mydata, "r", label="data", ax=ax1)
    plot(mydata.imag, "r", label="data", ax=ax2)
    # }}}
    # {{{ set up the fit object using the "simulated" data
    newfit = lmfitdata(mydata.C)
    newfit.functional_form = thisfit.functional_form
    newfit.set_guess(
        A=dict(value=13.0, max=20, min=0.0),
        R=dict(value=3, max=1000, min=0),
        nu=dict(value=20),
    )
    # }}}
    # {{{ show the guess
    guess = newfit.settoguess().eval()
    # }}}
    # {{{ 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(newfit.eval(), "b", alpha=0.5, label="fit", ax=ax1)
    plot(guess, "g--", label="guess", ax=ax1)
    plt.ylabel("real components")
    plt.legend()
    plot(newfit.eval().imag, "b", alpha=0.5, label="fit", ax=ax2)
    plot(guess.imag, "g--", label="guess", ax=ax2)
    plt.ylabel("imag components")
    plt.legend()
    # }}}
    plt.show()


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

   **Total running time of the script:** (0 minutes 0.455 seconds)


.. _sphx_glr_download_auto_examples_fit_complex.py:

.. only:: html

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

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

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

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

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


.. only:: html

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

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