mangadap.proc.spatialbinning module¶
Binning!
- License:
- Copyright (c) 2015, SDSS-IV/MaNGA Pipeline Group
- Licensed under BSD 3-clause license - see LICENSE.rst
- Source location:
- $MANGADAP_DIR/python/mangadap/proc/spatialbins.py
- Imports and python version compliance:
from __future__ import division from __future__ import print_function from __future__ import absolute_import from __future__ import unicode_literals import sys if sys.version > '3': long = int import numpy from scipy import sparse from astropy.io import fits from vorbin.voronoi_2d_binning import voronoi_2d_binning from ..par.parset import ParSet from ..util.geometry import SemiMajorAxisCoo from ..util.covariance import Covariance
- Class usage examples:
- Add examples
- Revision history:
- 01 Apr 2016: Implementation begun by K. Westfall (KBW)22 May 2018: (KBW) Import vorbin package version of voronoi_2d_binning
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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, pa, ell, radius_scale, radii, log_step)[source]¶ Bases:
mangadap.par.parset.ParSet
Class with parameters used by the radial binning algorithm. See
mangadap.par.parset.ParSet
for attributes.Parameters: - center (numpy.ndarray or 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 (OBJRA,OBJDEC).
- pa (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 (float) – Sets the ellipticity (1-b/a) of the isophotal ellipse use to define the elliptical bins.
- radius_scale (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 (numpy.ndarray or 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.
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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)[source]¶ Bases:
mangadap.par.parset.ParSet
Class with parameters used by the square binning algorithm. See
mangadap.par.parset.ParSet
for attributes.Parameters: binsz (float) – Sets 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, signal, noise, covar)[source]¶ Bases:
mangadap.par.parset.ParSet
Class with parameters used by the Voronoi binning algorithm. See
mangadap.par.parset.ParSet
for attributes.Parameters: - key (str) – Keyword to distinguish the assessment method.
- target_snr (float) – The target S/N for each bin.
- signal (array-like) – The array of signal measurements for each on-sky position to bin.
- noise (array-like) – 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.
- (float, numpy.ndarray, (covar) –
mangadap.util.Covariance
, scipy.sparse.spmatrix): Covariance matrix or calibration normalization. For the latter, the value is used to renormalize the noise according to the following equation:where \(N_{\rm bin}\) is the number of binned spaxels and \(\alpha\) is the value provided. See
mangadap.contrib.voronoi_2d_binning._sn_func()
.
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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.