lib.Fitting.QsynthesizedBeam module

class lib.Fitting.QsynthesizedBeam.SbModelIndepPeaks(startpars=None, ranges=None, fixpars=None, nrings=2, extra_args=None, verbose=False, common_fwhm=False, no_xy_shift=False, distortion=True)

Bases: object

Class defining the simplest Synthesized Beam model for QUBIC: - A square grid of n Gaussian Peaks with the same symmetric FWHM. - n is defined by nrings (1=>1 peak, 2=>9 peaks, …) - The square grid has a rotation angle - The amplitude of the peaks are independent - The FWHM of the peaks can be all the same or different depending on the keyword common_fwhm

If common_fwhm is True then this model is equivalent to SbModelIndepPeaksAmp

• A global distorsion to the position of the peaks is allowed

• A small shift of each peak position is allowed around the initial position

So if common_fwhm=True and no_xy_shift=True and distrotion=True this model is equivalent to SbModelIndepPeaksAmp So if common_fwhm=False and no_xy_shift=True and distortion=True this model is equivalent to SbModelIndepPeaksAmpFWHM

So Finally parameters are: [0]: Az center of the square [deg] [1]: El center of the square [deg] [2]: Interpeak distance [deg] [3]: Orientation angle [deg] [4]: X distorsion magnitude [5]: X distosion power [6]: Y distorsion magnitude [7]: Y distorsion power [8]: Average FWHM of the peaks [9+4*ipeak]: Amplitudes of the peaks [9+4*ipeak+1]: Delta FWHM of each peak to be added to the average one [deg] [9+4*ipeak+2]: X shift of the peak [deg] [9+4*ipeak+3]: Y shift of the peak [deg]

Methods

__call__(x, mypars[, return_peaks, extra_args])

Call self as a function.

print_start

print_start()

class lib.Fitting.QsynthesizedBeam.SbModelIndepPeaksAmpFWHM(startpars=None, ranges=None, fixpars=None, nrings=2, extra_args=None, verbose=False, common_fwhm=False)

Bases: object

Class defining the simplest Synthesized Beam model for QUBIC: - A square grid of n Gaussian Peaks with the same symmetric FWHM. - n is defined by nrings (1=>1 peak, 2=>9 peaks, …) - The square grid has a rotation angle - The amplitude of the peaks are independent - The FWHM of the peaks can be all the same or different depending on the keyword common_fwhm

If common_fwhm is True then this model is equivalent to SbModelIndepPeaksAmp

• A distorsion to the position of the peaks is allowed

So Finally parameters are: [0]: Az center of the square [deg] [1]: El center of the square [deg] [2]: Interpeak distance [deg] [3]: Orientation angle [deg] [4]: X distorsion magnitude [5]: X distosion power [6]: Y distorsion magnitude [7]: Y distorsion power [8]: Average FWHM of the peaks [9+2*ipeak]: Amplitudes of the peaks [9+2*ipeak+1]: Delta FWHM of each peak to be added to the average one [deg]

Methods

__call__(x, pars[, return_peaks])

Call self as a function.

print_start

print_start()

class lib.Fitting.QsynthesizedBeam.SimpleSbModel(startpars=None, ranges=None, fixpars=None, nrings=2, extra_args=None)

Bases: object

Class defining the simplest Synthesized Beam model for QUBIC: - A square grid of n Gaussian Peaks with the same symmetric FWHM. - n is defined by nrings (1=>1 peak, 2=>9 peaks, …) - The square grid has a rotation angle - The amplitude of the peaks is given by a common Primary Gaussian Beam whose FWHM and center is fit - A distorsion to the position of the peaks is allowed

So Finally parameters are: [0]: Az center of the square [deg] [1]: El center of the square [deg] [2]: Interpeak distance [deg] [3]: Orientation angle [deg] [4]: X distorsion magnitude [5]: X distosion power [6]: Y distorsion magnitude [7]: Y distorsion power [8]: FWHM of the peaks [deg] [9]: Amplitude of primary beam [10]: Az center of primary beam [deg] [11]: El center of primary beam [deg] [12]: FWHM of primary beam [deg]

Methods

__call__(x, pars[, return_peaks])

Call self as a function.

print_start

print_start()

lib.Fitting.QsynthesizedBeam.ang_dist(thph0, thph1)

lib.Fitting.QsynthesizedBeam.beeps(nbeeps)

lib.Fitting.QsynthesizedBeam.fit_sb(flatmap_init, az_init, el_init, model, newsize=70, dmax=5.0, az_center=0.0, el_center=50.0, doplot=False, resample=False, verbose=False, extra_title='', return_fitted=False, precision=None, nsiglo=1.0, nsighi=3.0, figsave=None)

lib.Fitting.QsynthesizedBeam.get_flatmap(TESNum, directory, azmin=None, azmax=None, elmin=None, elmax=None, remove=None, fitted_directory=None)

lib.Fitting.QsynthesizedBeam.get_hpmap(TESNum, directory)

lib.Fitting.QsynthesizedBeam.get_lines(lines, directory)

lib.Fitting.QsynthesizedBeam.rotate_q2m(thin, phin, angs=array([0., 1.57079633, 0.]), inverse=False)

lib.Fitting.QsynthesizedBeam.rotmatX(th)

lib.Fitting.QsynthesizedBeam.rotmatY(th)

lib.Fitting.QsynthesizedBeam.rotmatZ(th)

lib.Fitting.QsynthesizedBeam.show_flatmap(directory, TESNum, vmin=None, vmax=None, cbar=False)

lib.Fitting.QsynthesizedBeam.show_flatmaps_list(directory, TESNums, vmin=None, vmax=None, cbar=False, nx=5, tight=True)

lib.Fitting.QsynthesizedBeam.show_lines(maps, nums, min=None, max=None)

lib.Fitting.QsynthesizedBeam.thph2uv(th, ph)

lib.Fitting.QsynthesizedBeam.uv2thph(uv)