rss_ringoccs.calibration.resample_IQ module

Purpose:Resample I and Q from uniformly spaced time to uniformly spaced radius. This is set up to downsample from the raw resolution data.

rss_ringoccs.calibration.resample_IQ.pre_resample(rho_km, vec, freq)

Set vector sampling to be uniform with respect to radius at a spacing comparable to that of raw resolution. For ingress occultations, this step implicitly reverses the radius scale when interpolating.

Arguments

rho_km (np.ndarray):  radius in kilometers vec (np.ndarray):  a single vector component I or Q of the complex signal freq (float):radial sampling frequency

Returns

rho_grid (np.ndarray):  Radii at uniform spacing at which the signal component is resampled vec_grid (np.ndarray):  Signal resampled with respect to radius with a uniform spacing p (float):upsampling rate to be used by scipy.signal.resample_poly. This will always be unity because no upsampling is done. q (float):downsampling rate to be used by scipy.signal.resample_poly. This depends on the uniform radial sampling rate at which rho_grid and vec_grid are sampled.

rss_ringoccs.calibration.resample_IQ.resample_IQ(rho_km, IQ_c, dr_desired, verbose=False)

Resample I and Q to uniformly spaced radius. Based off of Matlab’s resample function

Arguments

rho_km (np.ndarray):  Set of ring intercept point values at initial resolution before resampling IQ_c (np.ndarray):  Frequency-corrected complex signal at initial resolution before resampling dr_desired (float):  Desired final radial sample spacing verbose (bool):Testing variable to print out the first few resampled results

Returns

rho_km_desired (np.ndarray):  array of ring radius at final desired spacing IQ_c_desired (np.ndarray):  Frequency-corrected complex signal at final desired spacing