MoffatModel2

class mpdaf.MUSE.MoffatModel2(fwhm_pol, beta_pol, lbrange, pixstep, field=0)[source]

Bases: mpdaf.MUSE.FSFModel

Attributes Summary

model
name

Methods Summary

from_header(hdr, pixstep[, field]) Read FSF parameters from a FITS header
from_hstconv(cube, hstimages[, lbrange]) Compute FSF by convolution of HST images
from_psfrec(rawfilename) Compute FSF parameters from GLAO MUSE PSF reconstruction
from_starfit(cube, pos[, size, nslice, …]) Fit a FSF model on a point source cube: input datacube pos: (dec,ra) location of the source in deg size: size of region to extract around the source in arcsec nslice: number of wavelength slices to used fwhmdeg: degre for polynomial fit of FWHM(lbda) betadeg: degre for polynomial fit of Beta(lbda) lbdarange: (lbda1,lbda2) tuple of reference wavelength for normalisation return an FSF object and intermediate fitting results as .fit attribute
get_2darray(self, lbda, shape[, center]) Return FSF 2D array at the given wavelength.
get_3darray(self, lbda, shape[, center]) Return FSF cube at the given wavelengths.
get_beta(self, lbda) Return beta for the given wavelengths.
get_cube(self, wave, wcs[, center]) Return FSF cube at the given wavelengths.
get_fwhm(self, lbda[, unit]) Return FWHM for the given wavelengths.
get_image(self, lbda, wcs[, center]) Return FSF image at the given wavelength.
info(self)
read(cube[, field, pixstep]) Read the FSF model from a file, cube, or header.
to_header(self[, hdr, field_idx]) Write FSF parameters to a FITS header

Attributes Documentation

model = 2
name = 'Circular MOFFAT beta=poly(lbda) fwhm=poly(lbda)'

Methods Documentation

classmethod from_header(hdr, pixstep, field=0)[source]

Read FSF parameters from a FITS header

classmethod from_hstconv(cube, hstimages, lbrange=(5000, 9000), **kwargs)

Compute FSF by convolution of HST images

classmethod from_psfrec(rawfilename)[source]

Compute FSF parameters from GLAO MUSE PSF reconstruction

classmethod from_starfit(cube, pos, size=5, nslice=20, fwhmdeg=3, betadeg=3, lbrange=(5000, 9000))[source]

Fit a FSF model on a point source cube: input datacube pos: (dec,ra) location of the source in deg size: size of region to extract around the source in arcsec nslice: number of wavelength slices to used fwhmdeg: degre for polynomial fit of FWHM(lbda) betadeg: degre for polynomial fit of Beta(lbda) lbdarange: (lbda1,lbda2) tuple of reference wavelength for normalisation return an FSF object and intermediate fitting results as .fit attribute

get_2darray(self, lbda, shape, center=None)

Return FSF 2D array at the given wavelength.

get_3darray(self, lbda, shape, center=None)

Return FSF cube at the given wavelengths.

get_beta(self, lbda)[source]

Return beta for the given wavelengths.

get_cube(self, wave, wcs, center=None)

Return FSF cube at the given wavelengths.

get_fwhm(self, lbda, unit='arcsec')[source]

Return FWHM for the given wavelengths.

get_image(self, lbda, wcs, center=None)

Return FSF image at the given wavelength.

info(self)[source]
classmethod read(cube, field=None, pixstep=None)

Read the FSF model from a file, cube, or header.

Parameters:
cube : str, mpdaf.obj.Cube, or astropy.io.fits.Header

Must contain a header with a FSF model.

field : int

Field number to read, otherwise all models are read.

to_header(self, hdr=None, field_idx=0)[source]

Write FSF parameters to a FITS header