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

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

.. _sphx_glr_auto_examples_plot_intro_to_grids.py:


Intro to Grids
==============

A basic introduction to the `GridSpectra` class.

.. GENERATED FROM PYTHON SOURCE LINES 7-13

.. code-block:: Python


    import numpy as np
    import matplotlib.pyplot as plt

    from GridPolator import GridSpectra








.. GENERATED FROM PYTHON SOURCE LINES 14-30

Let's create our own grid
-------------------------

Let's think of something that can be created programically but it also simple to visualize.
Imagine the class of functions:

.. math::
    y = a x (x-b)

There are two parameters, :math:`a` and :math:`b`, and the graph always passes through
the origin.

Suppose we want to know the value of this function with :math:`a ~ [-3,3]` and
:math:`b ~[-5,5]`.
Suppose also that each "spectrum" has some expensive physics in it, so we don't want to calculate too many,
but a high resolution in :math:`x` is okay.

.. GENERATED FROM PYTHON SOURCE LINES 30-42

.. code-block:: Python


    a = np.linspace(-3, 3, 7)
    b = np.linspace(-5, 5, 9)
    x = np.linspace(1, 10, 1000)

    spec = np.zeros(shape=(len(a), len(b), len(x)))

    for i,_a in enumerate(a):
        for j,_b in enumerate(b):
            _s = _a * x * (x - _b)
            spec[i, j, :] = _s








.. GENERATED FROM PYTHON SOURCE LINES 43-47

Initialize the interpolator
----------------------------

We now pass all of this information to the `GridSpectra` class.

.. GENERATED FROM PYTHON SOURCE LINES 47-58

.. code-block:: Python


    g = GridSpectra(
        native_wl=x,
        params={
            'a': a,
            'b': b
        },
        spectra=spec,
        impl='scipy' # or 'jax', see docs for more
    )








.. GENERATED FROM PYTHON SOURCE LINES 59-64

Evaluate
--------

We pass the interpolator a new wavelength grid along with new parameters and it will interpolate
to give us a new spectrum.

.. GENERATED FROM PYTHON SOURCE LINES 64-89

.. code-block:: Python


    new_wl = np.linspace(2,8,50)
    __a = 1.5
    __b = -2.3
    new_spec = g.evaluate(
        (
            np.array([__a]),
            np.array([__b])
            ),
        new_wl
    )[0]
    true_spec = __a * new_wl * (new_wl - __b)

    fig,axes = plt.subplots(2,1,figsize=(5,6))
    ax = axes[0]
    rax = axes[1]
    fig.subplots_adjust(left=0.3)
    ax.plot(new_wl, new_spec, label='interpolated',c='xkcd:rose pink')
    ax.plot(new_wl, true_spec, label='true',c='xkcd:azure')
    rax.plot(new_wl, (new_spec - true_spec)/true_spec*1e6, label='difference (ppm)',c='xkcd:golden rod')
    ax.set_xlabel('wavelength')
    rax.set_xlabel('wavelength')
    ax.set_ylabel('flux')
    rax.set_ylabel('residual (ppm)')
    _=ax.legend()



.. image-sg:: /auto_examples/images/sphx_glr_plot_intro_to_grids_001.png
   :alt: plot intro to grids
   :srcset: /auto_examples/images/sphx_glr_plot_intro_to_grids_001.png
   :class: sphx-glr-single-img






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

   **Total running time of the script:** (0 minutes 0.225 seconds)


.. _sphx_glr_download_auto_examples_plot_intro_to_grids.py:

.. only:: html

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

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

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

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

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


.. only:: html

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

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