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”)

  • covariance in B domain
  • Covariance in U domain
1: covariance in B domain |||('mT', 'mT')
2: Covariance in U domain |||('kcyc/T', 'kcyc/T')

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

Total running time of the script: (1 minutes 16.063 seconds)

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