CurveOfGrowth

class photutils.profiles.CurveOfGrowth(data, xycen, radii, *, error=None, mask=None, method='exact', subpixels=5)

Bases: ProfileBase

Class to create a curve of growth using concentric circular apertures.

The curve of growth profile represents the circular aperture flux as a function of circular radius.

Parameters:

data2D ndarray

The 2D data array. The data should be background-subtracted. Non-finite values (e.g., NaN or inf) in the data or error array are automatically masked.

xycentuple of 2 floats

The (x, y) pixel coordinate of the source center.

radii1D float ndarray

An array of the circular radii. radii must be strictly increasing with a minimum value greater than zero, and contain at least 2 values. The radial spacing does not need to be constant.

error2D 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 (see calc_total_error). error must have the same shape as the input data. Non-finite values (e.g., NaN or inf) in the data or error array are automatically masked.

mask2D bool ndarray, optional

A boolean mask with the same shape as data where a True value indicates the corresponding element of data 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 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 the subpixels 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. If subpixels=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 into subpixels**2 subpixels. This keyword is ignored unless method='subpixel'.

See also

EllipticalCurveOfGrowth, EnsquaredCurveOfGrowth, RadialProfile

Examples

>>> import numpy as np
>>> from astropy.modeling.models import Gaussian2D
>>> from photutils.centroids import centroid_2dg
>>> from photutils.datasets import make_noise_image
>>> from photutils.profiles import CurveOfGrowth

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)
>>> bkg_sig = 2.1
>>> noise = make_noise_image(data.shape, mean=0., stddev=bkg_sig, seed=0)
>>> data += noise
>>> error = np.zeros_like(data) + bkg_sig

Create the curve of growth.

>>> xycen = centroid_2dg(data)
>>> radii = np.arange(1, 26)
>>> cog = CurveOfGrowth(data, xycen, radii, error=error)

>>> print(cog.radius)
[ 1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
 25]

>>> print(cog.profile)
[ 135.14750208  514.49674293 1076.4617132  1771.53866121 2510.94382666
 3238.51695898 3907.08459943 4456.90125492 4891.00892262 5236.59326527
 5473.66400376 5643.72239573 5738.24972738 5803.31693644 5842.00525018
 5850.45854739 5855.76123671 5844.9631235  5847.72359025 5843.23189459
 5852.05251106 5875.32009699 5869.86235184 5880.64741302 5872.16333953]

>>> print(cog.profile_error)
[ 3.72215309  7.44430617 11.16645926 14.88861235 18.61076543 22.33291852
 26.05507161 29.7772247  33.49937778 37.22153087 40.94368396 44.66583704
 48.38799013 52.11014322 55.8322963  59.55444939 63.27660248 66.99875556
 70.72090865 74.44306174 78.16521482 81.88736791 85.609521   89.33167409
 93.05382717]

Plot the curve of growth.

(Source code, png, hires.png, pdf, svg)

Normalize the profile and plot the normalized curve of growth.

(Source code, png, hires.png, pdf, svg)

Plot a couple of the apertures on the data.

(Source code, png, hires.png, pdf, svg)

Attributes Summary

apertures	A list of CircularAperture objects used to measure the profile.
area	The unmasked area in each circular aperture as a function of radius as a 1D ndarray.
profile	The curve-of-growth profile as a 1D ndarray.
profile_error	The curve-of-growth profile errors as a 1D ndarray.
radius	The profile radius in pixels as a 1D ndarray.

Methods Summary

calc_ee_at_radius(radius)	Calculate the encircled energy at a given radius using a cubic interpolator based on the profile data.
calc_radius_at_ee(ee)	Calculate the radius at a given encircled energy using a cubic interpolator based on the profile data.
normalize([method])	Normalize the profile.
plot([ax])	Plot the profile.
plot_error([ax])	Plot the profile errors.
unnormalize()	Unnormalize the profile back to the original state before any calls to normalize.

Attributes Documentation

apertures

A list of CircularAperture objects used to measure the profile.

area

The unmasked area in each circular aperture as a function of radius as a 1D ndarray.

profile

The curve-of-growth profile as a 1D ndarray.

profile_error

The curve-of-growth profile errors as a 1D ndarray.

If no error array was provided, an empty array with shape (0,) is returned.

radius

The profile radius in pixels as a 1D ndarray.

This is the same as the input radii.

Note that these are the radii of the circular apertures used to measure the profile. Thus, they are the radial values that enclose the given flux. They can be used directly to measure the encircled energy/flux at a given radius.

Methods Documentation

calc_ee_at_radius(radius)

Calculate the encircled energy at a given radius using a cubic interpolator based on the profile data.

Note that this method assumes that input data has been normalized such that the total enclosed flux is 1 for an infinitely large radius. You can also use the normalize method before calling this method to normalize the profile to be 1 at the largest input radii.

Parameters:

radiusfloat or 1D ndarray

The circular radius/radii.

Returns:

eendarray

The encircled energy at each radius/radii. Returns NaN for radii outside the range of the profile data.

calc_radius_at_ee(ee)

Calculate the radius at a given encircled energy using a cubic interpolator based on the profile data.

Note that this method assumes that input data has been normalized such that the total enclosed flux is 1 for an infinitely large radius. You can also use the normalize method before calling this method to normalize the profile to be 1 at the largest input radii.

This interpolator returns values only for regions where the curve-of-growth profile is monotonically increasing.

Parameters:

eefloat or 1D ndarray

The encircled energy.

Returns:

radiusndarray

The radius at each encircled energy. Returns NaN for encircled energies outside the range of the profile data.

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 maximum value is 1.

• 'sum': The profile is normalized such that its sum (integral) is 1.

plot(ax=None, **kwargs)

Plot the profile.

Parameters:

axmatplotlib.axes.Axes or None, optional

The matplotlib axes on which to plot. If None, then the current Axes instance is used.

**kwargsdict, optional

Any keyword arguments accepted by matplotlib.pyplot.plot.

Returns:

lineslist of Line2D

A list of lines representing the plotted data.

plot_error(ax=None, **kwargs)

Plot the profile errors.

Parameters:

axmatplotlib.axes.Axes or None, optional

The matplotlib axes on which to plot. If None, then the current Axes instance is used.

**kwargsdict, optional

Any keyword arguments accepted by matplotlib.pyplot.fill_between.

Returns:

polymatplotlib.collections.PolyCollection or None

A PolyCollection containing the plotted polygons, or None if no errors were input.

unnormalize()

Unnormalize the profile back to the original state before any calls to normalize.