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

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

.. _sphx_glr_auto_examples_plot_interferogram.py:


Plot an interferogram
=====================

.. GENERATED FROM PYTHON SOURCE LINES 7-58

.. code-block:: Python


    import os
    if "SPHINX_DOC_BUILD" in os.environ:
        os.chdir(r"X:\msnoise2")

    import matplotlib
    matplotlib.use("agg")

    import matplotlib.pyplot as plt
    import numpy as np
    import pandas as pd
    from pandas.plotting import register_matplotlib_converters
    register_matplotlib_converters()

    plt.style.use("ggplot")

    from msnoise.api import connect, get_results, build_movstack_datelist, get_params, get_t_axis

    # connect to the database
    db = connect()

    # Obtain a list of dates between ``start_date`` and ``enddate``
    start, end, datelist = build_movstack_datelist(db)

    # Get the list of parameters from the DB:
    params = get_params(db)

    # Get the time axis for plotting the CCF:
    taxis = get_t_axis(db)

    # Get the results for two station, filter id=1, ZZ component, mov_stack=1 and the results as a 2D array:
    n, ccfs = get_results(db, "YA.FLR.00", "YA.FOR.00", 1, "ZZ", datelist, 1, format="matrix", params=params)

    # Convert to a pandas DataFrame object for convenience, and drop empty rows:
    df = pd.DataFrame(ccfs, index=pd.DatetimeIndex(datelist), columns=taxis)
    df = df.dropna()

    # Define the 99% percentile of the data, for visualisation purposes:
    clim = df.mean(axis="index").quantile(0.99)

    fig, ax = plt.subplots()
    plt.pcolormesh(df.columns, df.index.to_pydatetime(), df.values,
                   vmin=-clim, vmax=clim, rasterized=True)
    plt.colorbar()
    plt.title("Interferogram")
    plt.xlabel("Lag Time (s)")
    plt.ylim(df.index[0],df.index[-1])
    plt.xlim(df.columns[0], df.columns[-1])
    plt.subplots_adjust(left=0.15)




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

.. code-block:: pytb

    Traceback (most recent call last):
      File "C:\Users\thlec\Documents\PYTHON\MSNoise\examples\plot_interferogram.py", line 10, in <module>
        os.chdir(r"X:\msnoise2")
    FileNotFoundError: [WinError 3] The system cannot find the path specified: 'X:\\msnoise2'




.. GENERATED FROM PYTHON SOURCE LINES 59-60

Running a simple moving window average can be done with pandas's functions:

.. GENERATED FROM PYTHON SOURCE LINES 60-76

.. code-block:: Python



    smooth = df.rolling(5).mean()

    fig, ax = plt.subplots()
    plt.pcolormesh(smooth.columns, smooth.index.to_pydatetime(), smooth.values,
                   vmin=-clim, vmax=clim, rasterized=True)
    plt.colorbar()
    plt.title("Interferogram (smoothed over 5 days)")
    plt.xlabel("Lag Time (s)")
    plt.ylim(smooth.index[0],smooth.index[-1])
    plt.xlim(smooth.columns[0], smooth.columns[-1])
    plt.subplots_adjust(left=0.15)


    plt.show()  
    #EOF

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

   **Total running time of the script:** (0 minutes 0.003 seconds)


.. _sphx_glr_download_auto_examples_plot_interferogram.py:

.. only:: html

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

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

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

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

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


.. only:: html

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

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