RadialProfile¶
- class photutils.profiles.RadialProfile(data, xycen, radii, *, error=None, mask=None, method='exact', subpixels=5)[source]¶
Bases:
ProfileBase
Class to create a radial profile using concentric circular apertures.
The radial profile represents the azimuthally-averaged flux in circular annuli apertures as a function of radius.
For this class, the input radii represent the edges of the radial bins. This differs from the
RadialProfile
class, where the inputs represent the centers of the radial bins.- Parameters:
- data2D
numpy.ndarray
The 2D data array. The data should be background-subtracted. Non-finite values (e.g., NaN or inf) in the
data
orerror
array are automatically masked.- xycentuple of 2 floats
The
(x, y)
pixel coordinate of the source center.- edge_radii1D float
numpy.ndarray
An array of radii defining the edges of the radial bins.
edge_radii
must be strictly increasing with a minimum value greater than or equal to zero, and contain at least 2 values. The radial spacing does not need to be constant. The outputradius
attribute will be defined at the bin centers.- error2D
numpy.ndarray
, optional The 1-sigma errors of the input
data
.error
is assumed to include all sources of error, including the Poisson error of the sources (seecalc_total_error
) .error
must have the same shape as the inputdata
. Non-finite values (e.g., NaN or inf) in thedata
orerror
array are automatically masked.- mask2D bool
numpy.ndarray
, optional A boolean mask with the same shape as
data
where aTrue
value indicates the corresponding element ofdata
is masked. Masked data are excluded from all calculations.- method{‘exact’, ‘center’, ‘subpixel’}, optional
The method used to determine the overlap of the aperture on the pixel grid:
'exact'
(default): The the exact fractional overlap of the aperture and each pixel is calculated. The aperture weights will contain values between 0 and 1.'center'
: A pixel is considered to be entirely in or out of the aperture depending on whether its center is in or out of the aperture. The aperture weights will contain values only of 0 (out) and 1 (in).'subpixel'
: A pixel is divided into subpixels (see thesubpixels
keyword), each of which are considered to be entirely in or out of the aperture depending on whether its center is in or out of the aperture. Ifsubpixels=1
, this method is equivalent to'center'
. The aperture weights will contain values between 0 and 1.
- subpixelsint, optional
For the
'subpixel'
method, resample pixels by this factor in each dimension. That is, each pixel is divided intosubpixels**2
subpixels. This keyword is ignored unlessmethod='subpixel'
.
- data2D
See also
Notes
If the minimum of
edge_radii
is zero, then a circular aperture with radius equal toedge_radii[1]
will be used for the innermost aperture.Examples
>>> import numpy as np >>> from astropy.modeling.models import Gaussian2D >>> from astropy.visualization import simple_norm >>> from photutils.centroids import centroid_quadratic >>> from photutils.datasets import make_noise_image >>> from photutils.profiles import RadialProfile
Create an artificial single source. Note that this image does not have any background.
>>> gmodel = Gaussian2D(42.1, 47.8, 52.4, 4.7, 4.7, 0) >>> yy, xx = np.mgrid[0:100, 0:100] >>> data = gmodel(xx, yy) >>> error = make_noise_image(data.shape, mean=0., stddev=2.4, seed=123) >>> data += error
Create the radial profile.
>>> xycen = centroid_quadratic(data, xpeak=48, ypeak=52) >>> edge_radii = np.arange(26) >>> rp = RadialProfile(data, xycen, edge_radii, error=error, mask=None)
>>> print(rp.radius) [ 0.5 1.5 2.5 3.5 4.5 5.5 6.5 7.5 8.5 9.5 10.5 11.5 12.5 13.5 14.5 15.5 16.5 17.5 18.5 19.5 20.5 21.5 22.5 23.5 24.5]
>>> print(rp.profile) [ 4.15632243e+01 3.93402079e+01 3.59845746e+01 3.15540506e+01 2.62300757e+01 2.07297033e+01 1.65106801e+01 1.19376723e+01 7.75743772e+00 5.56759777e+00 3.44112671e+00 1.91350281e+00 1.17092981e+00 4.22261078e-01 9.70256904e-01 4.16355795e-01 1.52328707e-02 -6.69985111e-02 4.15522650e-01 2.48494731e-01 4.03348112e-01 1.43482678e-01 -2.62777461e-01 7.30653622e-02 7.84616804e-04]
>>> print(rp.profile_error) [1.69588246 0.81797694 0.61132694 0.44670831 0.49499835 0.38025361 0.40844702 0.32906672 0.36466713 0.33059274 0.29661894 0.27314739 0.25551933 0.27675376 0.25553986 0.23421017 0.22966813 0.21747036 0.23654884 0.22760386 0.23941711 0.20661313 0.18999134 0.17469024 0.19527558]
Plot the radial profile.
(
Source code
,png
,hires.png
,pdf
,svg
)Normalize the profile and plot the normalized radial profile.
(
Source code
,png
,hires.png
,pdf
,svg
)Plot two of the annulus apertures on the data.
(
Source code
,png
,hires.png
,pdf
,svg
)Fit a 1D Gaussian to the radial profile and return the Gaussian model.
>>> rp.gaussian_fit <Gaussian1D(amplitude=41.54880743, mean=0., stddev=4.71059406)>
>>> print(rp.gaussian_fwhm) 11.09260130738712
Plot the fitted 1D Gaussian on the radial profile.
(
Source code
,png
,hires.png
,pdf
,svg
)Attributes Summary
A list of the circular annulus apertures used to measure the radial profile.
The unmasked area in each circular annulus (or aperture) as a function of radius as a 1D
ndarray
.The fitted 1D Gaussian to the radial profile as a
Gaussian1D
model.The full-width at half-maximum (FWHM) in pixels of the 1D Gaussian fitted to the radial profile.
The fitted 1D Gaussian profile to the radial profile as a 1D
ndarray
.The radial profile as a 1D
ndarray
.The radial profile errors as a 1D
ndarray
.The profile radius (bin centers) in pixels as a 1D
ndarray
.Methods Summary
normalize
([method])Normalize the profile.
plot
([ax])Plot the profile.
plot_error
([ax])Plot the profile errors.
Attributes Documentation
- apertures¶
A list of the circular annulus apertures used to measure the radial profile.
If the
min_radius
is less than or equal to half theradius_step
, then a circular aperture with radius equal tomin_radius + 0.5 * radius_step
will be used for the innermost aperture.
- area¶
The unmasked area in each circular annulus (or aperture) as a function of radius as a 1D
ndarray
.
- gaussian_fit¶
The fitted 1D Gaussian to the radial profile as a
Gaussian1D
model.
- gaussian_fwhm¶
The full-width at half-maximum (FWHM) in pixels of the 1D Gaussian fitted to the radial profile.
- radius¶
The profile radius (bin centers) in pixels as a 1D
ndarray
.The returned radius values are defined as the arithmetic means of the input radial-bins edges (
radii
).For logarithmically-spaced input
radii
, one could instead use a radius array defined using the geometric mean of the bin edges, i.e.np.sqrt(radii[:-1] * radii[1:])
.
Methods Documentation
- normalize(method='max')¶
Normalize the profile.
- Parameters:
- method{‘max’, ‘sum’}, optional
The method used to normalize the profile:
‘max’ (default): The profile is normalized such that its peak value is 1.
‘sum’: The profile is normalized such that its sum (integral) is 1.
- plot(ax=None, **kwargs)¶
Plot the profile.
- Parameters:
- ax
matplotlib.axes.Axes
orNone
, optional The matplotlib axes on which to plot. If
None
, then the currentAxes
instance is used.- **kwargs
dict
Any keyword arguments accepted by
matplotlib.pyplot.plot
.
- ax
- Returns:
- lineslist of
Line2D
A list of lines representing the plotted data.
- lineslist of
- plot_error(ax=None, **kwargs)¶
Plot the profile errors.
- Parameters:
- ax
matplotlib.axes.Axes
orNone
, optional The matplotlib axes on which to plot. If
None
, then the currentAxes
instance is used.- **kwargs
dict
Any keyword arguments accepted by
matplotlib.pyplot.fill_between
.
- ax
- Returns:
- lines
matplotlib.collections.PolyCollection
A
PolyCollection
containing the plotted polygons.
- lines