.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "gallery/2D/13-plot2d_f3.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

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

        :ref:`Go to the end <sphx_glr_download_gallery_2D_13-plot2d_f3.py>`
        to download the full example code

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

.. _sphx_glr_gallery_2D_13-plot2d_f3.py:


2D & 1D
======================

.. image:: ../../_static/cigvis/2D/13.png
    :alt: image
    :align: center

.. GENERATED FROM PYTHON SOURCE LINES 15-109

.. code-block:: default


    # sphinx_gallery_thumbnail_path = '_static/cigvis/2D/13.png'


    import numpy as np
    import cigvis
    from cigvis import colormap
    import matplotlib.pyplot as plt

    root = '/Volumes/T7/DATA/cigvisdata/F3/'
    seisp = root + 'seis.dat'
    saltp = root + 'salt.dat'
    hz2p = root + 'hz.dat'
    unc1p = root + 'unc1.dat'
    unc2p = root + 'unc2.dat'
    logsp = root + 'logs.dat'
    ni, nx, nt = 591, 951, 362
    shape = (ni, nx, nt)

    seis = np.memmap(seisp, np.float32, 'c', shape=shape)
    # overlay
    inter = np.memmap(root + 'overlay.dat', np.float32, 'c', shape=shape)

    salt = np.memmap(saltp, np.float32, 'c', shape=shape)
    hz2 = np.fromfile(hz2p, np.float32).reshape(ni, nx)
    unc = np.memmap(root + 'unc.dat', np.float32).reshape(shape)
    unc2 = np.fromfile(unc2p, np.float32).reshape(ni, nx).astype(np.float32)
    logs = np.fromfile(logsp, np.float32).reshape(4, 2121)

    sx2 = seis[259, :, :]
    ov2 = inter[259, :, :]
    sl2 = salt[259, :, :]
    sl2[sl2 > 0] = 1
    sl2[sl2 <= 0] = 0
    hzl = hz2[259, :]
    unl = unc2[259, :]

    w = 80
    logz = np.arange(0, 0.2 * 2121, 0.2)
    logv = logs[0][logz < nt - 1]
    logv = (logv - logv.min()) * w / np.abs(logv).max()
    logx = np.array([33] * 2121)[logz < nt - 1]
    logz = logz[logz < nt - 1]
    logxv = logx + logv - 5

    fig, axs = plt.subplots(2, 1, figsize=(8, 9))

    fg1 = {}
    fg1['img'] = cigvis.fg_image_args(
        ov2,
        alpha=0.5,
        clim=[inter.max() * 0.15, inter.max() * 0.5],
        interpolation='nearest',
    )

    cmap = colormap.custom_disc_cmap([0, 1], ['red', 'cyan'])
    cmap = colormap.set_alpha_except_min(cmap, 1, False)
    fg1['img'] += cigvis.fg_image_args(
        sl2,
        cmap=cmap,
        interpolation='nearest',
    )

    fg1['line'] = cigvis.line_args(np.arange(nx), hzl, 'blue')
    fg1['line'] += cigvis.line_args(np.arange(nx), unl, 'white')
    fg1['line'] += cigvis.line_args(logxv, logz, 'black', lw=0.6)

    cigvis.plot2d(
        sx2,
        fg=fg1,
        aspect='auto',
        xsample=[0, 0.0125],
        ysample=[0, 0.002],
        xlabel='Crossline [km]',
        ylabel='Time [s]',
        title='2D section (Inline=259)',
        ax=axs[0],
    )

    traces = sx2[:50, :].T

    cigvis.plot_multi_traces(
        traces,
        dt=0.002,
        c='black',
        fill_down=0.01,
        ax=axs[1],
        ylabel='Time [s]',
    )

    plt.tight_layout()
    plt.savefig('2Dcanvas.png', bbox_inches='tight', pad_inches=0.01, dpi=300)

    plt.show()


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

   **Total running time of the script:** (0 minutes 0.000 seconds)


.. _sphx_glr_download_gallery_2D_13-plot2d_f3.py:

.. only:: html

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




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

      :download:`Download Python source code: 13-plot2d_f3.py <13-plot2d_f3.py>`

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

      :download:`Download Jupyter notebook: 13-plot2d_f3.ipynb <13-plot2d_f3.ipynb>`


.. only:: html

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

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