centroid_sources

photutils.centroids.centroid_sources(data, xpos, ypos, box_size=11, footprint=None, mask=None, centroid_func=<function centroid_com>, **kwargs)

Calculate the centroid of sources at the defined positions.

A cutout image centered on each input position will be used to calculate the centroid position. The cutout image is defined either using the box_size or footprint keyword. The footprint keyword can be used to create a non-rectangular cutout image.

Parameters:

data2D ndarray

The 2D image data. The image should be background-subtracted.

xpos, yposfloat or array_like of float

The initial x and y pixel position(s) of the center position. A cutout image centered on this position be used to calculate the centroid.

box_sizeint or array_like of int, optional

The size of the cutout image along each axis. If box_size is a number, then a square cutout of box_size will be created. If box_size has two elements, they must be in (ny, nx) order. box_size must have odd values for both axes. Either box_size or footprint must be defined. If they are both defined, then footprint overrides box_size.

footprintbool ndarray, optional

A 2D boolean array where True values describe the local footprint region to cutout. footprint can be used to create a non-rectangular cutout image, in which case the input xpos and ypos represent the center of the minimal bounding box for the input footprint. box_size=(n, m) is equivalent to footprint=np.ones((n, m)). Either box_size or footprint must be defined. If they are both defined, then footprint overrides box_size.

mask2D bool ndarray, optional

A 2D boolean array with the same shape as data, where a True value indicates the corresponding element of data is masked.

error2D ndarray, optional

The 2D array of the 1-sigma errors of the input data. error must have the same shape as data. error will be used only if supported by the input centroid_func.

centroid_funccallable, optional

A callable object (e.g., function or class) that is used to calculate the centroid of a 2D array. The centroid_func must accept a 2D ndarray, have a mask keyword and optionally an error keyword. The callable object must return a tuple of two 1D ndarray, representing the x and y centroids. The default is centroid_com.

**kwargsdict

Any additional keyword arguments accepted by the centroid_func.

Returns:

xcentroid, ycentroidndarray

The x and y pixel position(s) of the centroids. NaNs will be returned where the centroid failed. This is usually due a box_size that is too small when using a fitting-based centroid function (e.g., centroid_1dg, centroid_2dg, or centroid_quadratic.

Examples

>>> from photutils.centroids import centroid_com, centroid_sources
>>> from photutils.datasets import make_4gaussians_image
>>> from photutils.utils import circular_footprint
>>> data = make_4gaussians_image()

>>> x_init = (25, 91, 151, 160)
>>> y_init = (40, 61, 24, 71)
>>> footprint = circular_footprint(5.0)
>>> x, y = centroid_sources(data, x_init, y_init, footprint=footprint,
...                         centroid_func=centroid_com)
>>> print(x)  
[ 24.9865905   90.84751557 150.50228056 159.74319544]
>>> print(y)  
[40.01096547 60.92509086 24.52986889 70.57971148]

import matplotlib.pyplot as plt
from photutils.centroids import centroid_com, centroid_sources
from photutils.datasets import make_4gaussians_image
from photutils.utils import circular_footprint
data = make_4gaussians_image()
x_init = (25, 91, 151, 160)
y_init = (40, 61, 24, 71)
footprint = circular_footprint(5.0)
x, y = centroid_sources(data, x_init, y_init, footprint=footprint,
                        centroid_func=centroid_com)
plt.figure(figsize=(8, 4))
plt.imshow(data, origin='lower', interpolation='nearest')
plt.scatter(x, y, marker='+', s=80, color='red', label='Centroids')
plt.legend()
plt.tight_layout()

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