lib.Qcoaddition module

class lib.Qcoaddition.FocalPlane(tt, tod, az, el, thk)[source]

Bases: object

Instance to display data on the FP (assuming Technical Demonstrator)

Methods

create_subplots(tes, asic, ax, **kwargs)

Method to make many subplots for each TES.

create_subplots_healpix(tes, asic, m, ...)

Method to make many subplots for each TES with healpix projection.
create_subplots(tes, asic, ax, **kwargs)[source]

Method to make many subplots for each TES.

create_subplots_healpix(tes, asic, m, center, reso, ax, fig, **kwargs)[source]

Method to make many subplots for each TES with healpix projection.

class lib.Qcoaddition.MySplineFitting(xin, yin, covarin, nbspl, logspace=False)[source]

Bases: object

Methods

__call__(x)

Call self as a function.

get_spline_tofit

with_alpha
get_spline_tofit(xspline, index, xx)[source]
with_alpha(x, alpha)[source]
class lib.Qcoaddition.Pip1Tes(tt, tod, az, el, thk)[source]

Bases: object

Instance to treat TES one by one.

Methods

decorel_azel([nbins, n_el, degree, nbspl])

Method to remove correlation in azimuth.

healpix_map_([nside, countcut, unseen_val])

Method to project data on the sky using coaddition.

identify_scans(inthk, az, el[, tt, ...])

This function identifies and assign numbers the various regions of a back-and-forth scanning using the housepkeeping time, az, el

run([remove_drift, remove_offset, decorel, ...])

Main method to run the pipeline.

get_chunks

linear_rescale_chunks
decorel_azel(nbins=50, n_el=30, degree=None, nbspl=10)[source]

Method to remove correlation in azimuth.

get_chunks(value)[source]
healpix_map_(nside=128, countcut=0, unseen_val=-1.6375e+30)[source]

Method to project data on the sky using coaddition.

identify_scans(inthk, az, el, tt=None, median_size=101, thr_speedmin=0.1, plotrange=[0, 1000])[source]
This function identifies and assign numbers the various regions of a back-and-forth scanning using the housepkeeping time, az, el

  • a numbering for each back & forth scan

  • a region to remove at the end of each scan (bad data due to FLL reset, slowingg down of the moiunt, possibly HWP rotation

  • is the scan back or forth ?

It optionnaly iinterpolate this information to the TOD sampling iif provided.

Parameters:

  • input

  • thk (np.array()) – time samples (seconds) for az and el at the housekeeeping sampling rate

  • az (np.array()) – azimuth in degrees at the housekeeping sampling rate

  • el (np.array()) – elevation in degrees at the housekeeping sampling rate

  • tt (Optional : np.array()) – None buy default, if not None: time samples (seconds) at the TOD sampling rate Then. the output will also containe az,el and scantype interpolated at TOD sampling rate

  • thr_speedmin (Optional : float) – Threshold for angular velocity to be considered as slow

  • doplot ([Optional] : Boolean) – If True displays some useeful plot

  • output

  • scantype_hk (np.array(int)) – type of scan for each sample at housekeeping sampling rate: * 0 = speed to slow - Bad data * n = scanning towards positive azimuth * -n = scanning towards negative azimuth where n is the scan number (starting at 1)

  • azt ([optional] np.array()) – azimuth (degrees) at the TOD sampling rate

  • elt ([optional] np.array()) – elevation (degrees) at the TOD sampling rate

  • scantype ([optiona] np.array()) – same as scantype_hk, but interpolated at TOD sampling rate

linear_rescale_chunks(chunks, sz=1000)[source]
run(remove_drift=False, remove_offset=False, decorel=False, healpix_map=False)[source]

Main method to run the pipeline.

class lib.Qcoaddition.PipAllTes(tt, tod, az, el, thk)[source]

Bases: object

Instance to analyse and display all TES.

Methods

run([remove_drift, remove_offset, decorel, ...])

Method to run loop for all TES. You can add useful arguments using **kwargs keyword.
run(remove_drift=False, remove_offset=False, decorel=False, plot_FP=False, plot_FP_healpix=False, center=None, reso=None, color=None, nside=128, **kwargs)[source]

Method to run loop for all TES. You can add useful arguments using **kwargs keyword.