.. only:: html

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

        Click :ref:`here <sphx_glr_download_examples_2D_simulation(crystalline)_plot_4_DAS_Coesite.py>`     to download the full example code or to run this example in your browser via Binder
    .. rst-class:: sphx-glr-example-title

    .. _sphx_glr_examples_2D_simulation(crystalline)_plot_4_DAS_Coesite.py:


Coesite, 17O (I=5/2) DAS
^^^^^^^^^^^^^^^^^^^^^^^^^

17O (I=5/2) Dynamic-angle spinning (DAS) simulation.

The following is a dynamic angle spinning (DAS) simulation of Coesite. Coesite has
five crystallographic :math:`^{17}\text{O}` sites. In the following, we use the
:math:`^{17}\text{O}` EFG tensor information from Grandinetti `et. al.` [#f1]_


.. code-block:: python

    import matplotlib as mpl
    import matplotlib.pyplot as plt
    import mrsimulator.signal_processing as sp
    import mrsimulator.signal_processing.apodization as apo
    from mrsimulator import Simulator
    from mrsimulator.methods import Method2D

    # global plot configuration
    font = {"size": 9}
    mpl.rc("font", **font)
    mpl.rcParams["figure.figsize"] = [4.25, 3.0]








Create the Simulator object and load the spin systems database or url address.


.. code-block:: python

    sim = Simulator()

    # load the spin systems from url.
    filename = "https://sandbox.zenodo.org/record/687656/files/coesite.mrsys"
    sim.load_spin_systems(filename)








Use the generic 2D method, `Method2D`, to simulate a DAS spectrum by customizing the
method parameters, as shown below. Note, the Method2D method simulates an infinite
spinning speed spectrum.


.. code-block:: python

    das = Method2D(
        channels=["17O"],
        magnetic_flux_density=11.7,  # in T
        spectral_dimensions=[
            {
                "count": 256,
                "spectral_width": 5e3,  # in Hz
                "reference_offset": 0,  # in Hz
                "label": "DAS isotropic dimension",
                "events": [
                    {"fraction": 0.5, "rotor_angle": 37.38 * 3.14159 / 180},
                    {"fraction": 0.5, "rotor_angle": 79.19 * 3.14159 / 180},
                ],
            },
            # The last spectral dimension block is the direct-dimension
            {
                "count": 256,
                "spectral_width": 2e4,  # in Hz
                "reference_offset": 0,  # in Hz
                "label": "MAS dimension",
                "events": [{"rotor_angle": 54.735 * 3.14159 / 180}],
            },
        ],
    )
    sim.methods = [das]  # add the method.








Run the simulation


.. code-block:: python

    sim.run()








The plot of the simulation.


.. code-block:: python

    data = sim.methods[0].simulation
    ax = plt.subplot(projection="csdm")
    cb = ax.imshow(data / data.max(), aspect="auto", cmap="gist_ncar_r")
    plt.colorbar(cb)
    ax.invert_xaxis()
    ax.invert_yaxis()
    plt.tight_layout()
    plt.show()




.. image:: /examples/2D_simulation(crystalline)/images/sphx_glr_plot_4_DAS_Coesite_001.png
    :alt: plot 4 DAS Coesite
    :class: sphx-glr-single-img





Add post-simulation signal processing.


.. code-block:: python

    processor = sp.SignalProcessor(
        operations=[
            # Gaussian convolution along both dimensions.
            sp.IFFT(dim_index=(0, 1)),
            apo.Gaussian(FWHM="0.3 kHz", dim_index=0),
            apo.Gaussian(FWHM="0.15 kHz", dim_index=1),
            sp.FFT(dim_index=(0, 1)),
        ]
    )
    processed_data = processor.apply_operations(data=data)
    processed_data /= processed_data.max()








The plot of the simulation after signal processing.


.. code-block:: python

    ax = plt.subplot(projection="csdm")
    cb = ax.imshow(processed_data.real, cmap="gist_ncar_r", aspect="auto")
    plt.colorbar(cb)
    ax.invert_xaxis()
    ax.invert_yaxis()
    plt.tight_layout()
    plt.show()




.. image:: /examples/2D_simulation(crystalline)/images/sphx_glr_plot_4_DAS_Coesite_002.png
    :alt: plot 4 DAS Coesite
    :class: sphx-glr-single-img





.. [#f1] Grandinetti, P. J., Baltisberger, J. H., Farnan, I., Stebbins, J. F.,
      Werner, U. and Pines, A.
      Solid-State :math:`^{17}\text{O}` Magic-Angle and Dynamic-Angle Spinning NMR
      Study of the :math:`\text{SiO}_2` Polymorph Coesite, J. Phys. Chem. 1995,
      **99**, *32*, 12341-12348.
      `DOI: 10.1021/j100032a045 <https://doi.org/10.1021/j100032a045>`_


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

   **Total running time of the script:** ( 0 minutes  1.269 seconds)


.. _sphx_glr_download_examples_2D_simulation(crystalline)_plot_4_DAS_Coesite.py:


.. only :: html

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


  .. container:: binder-badge

    .. image:: images/binder_badge_logo.svg
      :target: https://mybinder.org/v2/gh/DeepanshS/mrsimulator/master?urlpath=lab/tree/docs/_build/html/../../notebooks/examples/2D_simulation(crystalline)/plot_4_DAS_Coesite.ipynb
      :alt: Launch binder
      :width: 150 px


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

     :download:`Download Python source code: plot_4_DAS_Coesite.py <plot_4_DAS_Coesite.py>`



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

     :download:`Download Jupyter notebook: plot_4_DAS_Coesite.ipynb <plot_4_DAS_Coesite.ipynb>`


.. only:: html

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

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