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

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

.. _sphx_glr_auto_examples_generate_oscilloscope_PSD.py:


Generate a PSD from Oscilloscope Data
=====================================
Here, data containing the noise signal acquired on the oscilloscope is
converted to a power spectral density and convolved to display a smooth
spectra illustrating the noise power.

.. GENERATED FROM PYTHON SOURCE LINES 8-55



.. image-sg:: /auto_examples/images/sphx_glr_generate_oscilloscope_PSD_001.png
   :alt: PSD acquired on oscilloscope
   :srcset: /auto_examples/images/sphx_glr_generate_oscilloscope_PSD_001.png
   :class: sphx-glr-single-img


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

 .. code-block:: none

    You didn't set units for capture before saving the data!!!
    1: PSD acquired on oscilloscope |||MHz







|

.. code-block:: Python

    from numpy import r_
    from pyspecdata import figlist_var, find_file
    from pylab import diff, sqrt, ylim, ylabel
    import re

    lambda_G = 0.1e6  # Width for Gaussian convolution
    filename = "240328_RX_GDS_2mV_analytic.h5"
    nodename = "accumulated_240328"
    with figlist_var() as fl:
        # Load data according to the filename and nodename
        s = find_file(
            re.escape(filename),
            expno=nodename,
            exp_type="ODNP_NMR_comp/noise_tests",
        )
        # Calculate $t_{acq}$
        acq_time = diff(s.getaxis("t")[r_[0, -1]])[0]
        s.ft("t")  # V_p√s/√Hz
        # Instantaneous V_p*√s/√Hz -> V_rms√s/√Hz
        s /= sqrt(2)
        # {{{ equation 21
        s = abs(s) ** 2  # Take mod squared to convert to energy
        #                  V_rms^2 s/Hz
        s.mean("capture")  # Average over all captures
        s /= acq_time  # Convert to power V_rms^2/Hz = W
        s /= 50  # Divide by impedance -> W/Hz
        # }}}
        s.set_units("t", "Hz")
        # Plot unconvolved PSD on a semilog plot
        fl.next("PSD acquired on oscilloscope")
        fl.plot(
            s["t":(0, 49e6)],
            color="blue",
            alpha=0.1,
            plottype="semilogy",
        )
        # Convolve using the lambda_G specified above
        s.convolve("t", lambda_G, enforce_causality=False)
        # Plot the convolved PSD on the semilog plot with the unconvolved
        fl.plot(
            s["t":(0, 49e6)],
            color="blue",
            alpha=0.3,
            plottype="semilogy",
        )
        ylim(1e-18, 1e-13)  # set y limits
        ylabel(r"$S(\nu)$ / (W/Hz)")


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

   **Total running time of the script:** (0 minutes 1.171 seconds)


.. _sphx_glr_download_auto_examples_generate_oscilloscope_PSD.py:

.. only:: html

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

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

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

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

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


.. only:: html

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

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