.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "auto_examples/ESR/calculate_covariance.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note :ref:`Go to the end ` to download the full example code .. rst-class:: sphx-glr-example-title .. _sphx_glr_auto_examples_ESR_calculate_covariance.py: Calculation of the Covariance Matrix ==================================== After rescaling plots, the covariance matrix is calculated and then plotted for a 2D Field experiment (spectra as a function of field with multiple collections or "Times") .. GENERATED FROM PYTHON SOURCE LINES 9-34 .. rst-class:: sphx-glr-horizontal * .. image-sg:: /auto_examples/ESR/images/sphx_glr_calculate_covariance_001.png :alt: covariance in B domain :srcset: /auto_examples/ESR/images/sphx_glr_calculate_covariance_001.png, /auto_examples/ESR/images/sphx_glr_calculate_covariance_001_2_00x.png 2.00x :class: sphx-glr-multi-img * .. image-sg:: /auto_examples/ESR/images/sphx_glr_calculate_covariance_002.png :alt: Covariance in U domain :srcset: /auto_examples/ESR/images/sphx_glr_calculate_covariance_002.png, /auto_examples/ESR/images/sphx_glr_calculate_covariance_002_2_00x.png 2.00x :class: sphx-glr-multi-img .. rst-class:: sphx-glr-script-out .. code-block:: none 1: covariance in B domain |||('mT', 'mT') 2: Covariance in U domain |||('kcyc/T', 'kcyc/T') | .. code-block:: Python import pyspecdata as psd fieldaxis = "$B_0$" with psd.figlist_var() as fl: for filenum, (thisfile, exp_type) in enumerate( [("230504_3p8mM_TEMPOL_stb_wt_4x.DSC", "francklab_esr/alex")] ): # TODO: Zenodo ID does not work. .YGF file is missing from the # deposition. Need to fix this. d = psd.find_file(thisfile, exp_type=exp_type, zenodo="21287247")[ "harmonic", 0 ] d.set_units(fieldaxis, "T").set_axis(fieldaxis, lambda x: x * 1e-4) d.rename("Time", "observations") d.reorder(["observations", fieldaxis]) fl.next("covariance in B domain") # we do this first, because if we were to ift to go to u domain and # then ft back, we would introduce a complex component to our data fl.image(d.C.cov_mat("observations")) d.ift(fieldaxis, shift=True) fl.next("Covariance in U domain") fl.image( d.cov_mat("observations") ) # this time, do not spin up an extra copy of the data .. rst-class:: sphx-glr-timing **Total running time of the script:** (1 minutes 16.063 seconds) .. _sphx_glr_download_auto_examples_ESR_calculate_covariance.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: calculate_covariance.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: calculate_covariance.py ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_