StdBackgroundRMS#

class photutils.background.StdBackgroundRMS(sigma_clip=<default: SigmaClip(sigma=3.0, maxiters=10)>)[source]#

Bases: BackgroundRMSBase

Class to calculate the background RMS in an array as the (sigma- clipped) standard deviation.

Parameters:

sigma_clipastropy.stats.SigmaClip or None, optional: A SigmaClip object that defines the sigma clipping parameters. If None then no sigma clipping will be performed.

Examples

>>> from astropy.stats import SigmaClip
>>> from photutils.background import StdBackgroundRMS
>>> data = np.arange(100)
>>> sigma_clip = SigmaClip(sigma=3.0)
>>> bkgrms = StdBackgroundRMS(sigma_clip=sigma_clip)

The background RMS value can be calculated by using the calc_background_rms method, e.g.:

>>> bkgrms_value = bkgrms.calc_background_rms(data)
>>> print(bkgrms_value)
28.86607004772212

Alternatively, the background RMS value can be calculated by calling the class instance as a function, e.g.:

>>> bkgrms_value = bkgrms(data)
>>> print(bkgrms_value)
28.86607004772212

Methods Summary

`__call__`(data[, axis, masked])	Call self as a function.
`calc_background_rms`(data[, axis, masked])	Calculate the background RMS value.

Methods Documentation

__call__(data, axis=None, masked=False)#: Call self as a function.

calc_background_rms(data, axis=None, masked=False)[source]#

Calculate the background RMS value.

Parameters:

dataarray_like or MaskedArray: The array for which to calculate the background RMS value.
axisint or None, optional: The array axis along which the background RMS is calculated. If None, then the entire array is used.
maskedbool, optional: If True, then a MaskedArray is returned. If False, then a ndarray is returned, where masked values have a value of NaN. The default is False.

Returns:

resultfloat, ndarray, or MaskedArray: The calculated background RMS value. If masked is False, then a ndarray is returned, otherwise a MaskedArray is returned. A scalar result is always returned as a float.