mangadap.proc.spatialbinning module¶
Binning!
Revision history¶
01 Apr 2016: Implementation begun by K. Westfall (KBW)22 May 2018: (KBW) Import vorbin package version of voronoi_2d_binning
Copyright © 2019, SDSS-IV/MaNGA Pipeline Group
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class
mangadap.proc.spatialbinning.
GlobalBinning
[source]¶ Bases:
mangadap.proc.spatialbinning.SpatialBinning
Class that performs the global binning.
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class
mangadap.proc.spatialbinning.
RadialBinning
(par=None)[source]¶ Bases:
mangadap.proc.spatialbinning.SpatialBinning
Class that performs the radial binning.
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_r_start_step
(r)[source]¶ Bin starting radii are:
rs = self.par['radii'][0] re = self.par['radii'][1] nr = int(self.par['radii'][2]) starting_radii = numpy.logspace(numpy.log10(rs), numpy.log10(re), num=nr, endpoint=False) if self.par['log_step'] else numpy.linspace(rs, re, num=nr, endpoint=False)
For ending radii, just swap rs and re above
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class
mangadap.proc.spatialbinning.
RadialBinningPar
(center=None, pa=None, ell=None, radius_scale=None, radii=None, log_step=None)[source]¶ Bases:
mangadap.par.parset.KeywordParSet
Class with parameters used by the radial binning algorithm. See
mangadap.par.parset.ParSet
for attributes.The defined parameters are:
Key Type Options Default Description center
ndarray, list A two-element array defining the center to use in the definition of the elliptical bins. This is defined as a sky-right offset in arcseconds from the nominal center of the object. pa
int, float Sets the position angle, defined from N through E of the major axis of the isophotal ellipse used to define the elliptical bins. ell
int, float Sets the ellipticity (1-b/a) of the isophotal ellipse use to define the elliptical bins. radius_scale
int, float Defines a scale factor to use when defining the radial bins. For example, you might want to scale to the a certain number of effective radii or physical scale in kpc. For no scale, use 1.0. radii
ndarray, list A three-element array defining the starting and ending radius for the bin edges and the number of bins to create. If the starting radius is -1, the inner-most radius is set to 0 when not using log bins or 0.1 arcsec when using logarithmically spaced bins. If the ending radius is -1, the outer-most radius is set by the spaxel at the largest radius. log_step
bool A flag that the radial bins should be a geometric series. -
fromheader
(hdr)[source]¶ Copy the information from the header.
hdr (astropy.io.fits.Header): Header object to write to.
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toheader
(hdr)[source]¶ Copy some of the parameters to a header.
Parameters: hdr (astropy.io.fits.Header) – Header object to write to. Returns: Edited header object Return type: astropy.io.fits.Header Raises: TypeError
– Raised if input is not an astropy.io.fits.Header object.
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class
mangadap.proc.spatialbinning.
SpatialBinning
(bintype, par=None)[source]¶ Bases:
object
Base class for spatially binning data.
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class
mangadap.proc.spatialbinning.
SquareBinning
(par=None)[source]¶ Bases:
mangadap.proc.spatialbinning.SpatialBinning
Class to perform binning of full cube in square apertures Length of aperture side is given in arcsec with binsz
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class
mangadap.proc.spatialbinning.
SquareBinningPar
(binsz=None)[source]¶ Bases:
mangadap.par.parset.KeywordParSet
Class with parameters used by the square binning algorithm. See
mangadap.par.parset.ParSet
for attributes.The defined parameters are:
Key Type Options Default Description binsz
float Desired bin size in arcsec -
fromheader
(hdr)[source]¶ Copy the information from the header.
hdr (astropy.io.fits.Header): Header object to write to.
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toheader
(hdr)[source]¶ Copy some of the parameters to a header.
Parameters: hdr (astropy.io.fits.Header) – Header object to write to. Returns: Edited header object Return type: astropy.io.fits.Header Raises: TypeError
– Raised if input is not an astropy.io.fits.Header object.
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class
mangadap.proc.spatialbinning.
VoronoiBinning
(par=None)[source]¶ Bases:
mangadap.proc.spatialbinning.SpatialBinning
Class that wraps the contributed voronoi binning code.
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sn_calculation_calibrate_noise
(index, signal, noise)[source]¶ Calculate the S/N using a calibration of the S/N following:
\[N_{\rm calib} = N_{\rm nominal} (1 + \alpha\ \log N_{\rm bin})\]where \(N_{\rm bin}\) is the number of binned spaxels and \(\alpha\) is an empirically derived constant used to adjust the noise for the affects of covariance.
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class
mangadap.proc.spatialbinning.
VoronoiBinningPar
(target_snr=None, signal=None, noise=None, covar=None)[source]¶ Bases:
mangadap.par.parset.KeywordParSet
Class with parameters used by the Voronoi binning algorithm.
See
mangadap.par.parset.ParSet
for attributes. See vorbin for the main algorithm.The defined parameters are:
Key Type Options Default Description target_snr
int, float The target S/N for each bin. signal
ndarray, list The array of signal measurements for each on-sky position to bin. noise
ndarray, list The array of noise measurements for each on-sky position to bin. If not provided, covar
must be provided and be a full covariance matrix.covar
float, ndarray, Covariance, spmatrix Covariance matrix or calibration normalization. For the latter, the value is used to renormalize using \(n_{\rm calib} = n_{\rm nominal} (1 + \alpha\ \log\ N_{\rm bin})\), where \(N_{\rm bin}\) is the number of binned spaxels and \(\alpha\) is the value provided. -
fromheader
(hdr)[source]¶ Copy the information from the header.
hdr (astropy.io.fits.Header): Header object to write to.
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toheader
(hdr)[source]¶ Copy some of the parameters to a header.
Parameters: hdr (astropy.io.fits.Header) – Header object to write to. Returns: Edited header object Return type: astropy.io.fits.Header Raises: TypeError
– Raised if input is not an astropy.io.fits.Header object.
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