sigma_clipped_stats¶

astropy.stats.
sigma_clipped_stats
(data, mask=None, mask_value=None, sigma=3.0, sigma_lower=None, sigma_upper=None, maxiters=5, cenfunc='median', stdfunc='std', std_ddof=0, axis=None, grow=False)[source]¶ Calculate sigmaclipped statistics on the provided data.
 Parameters
 dataarray_like or
MaskedArray
Data array or object that can be converted to an array.
 mask
numpy.ndarray
(bool), optional A boolean mask with the same shape as
data
, where aTrue
value indicates the corresponding element ofdata
is masked. Masked pixels are excluded when computing the statistics. mask_valuefloat, optional
A data value (e.g.,
0.0
) that is ignored when computing the statistics.mask_value
will be masked in addition to any inputmask
. sigmafloat, optional
The number of standard deviations to use for both the lower and upper clipping limit. These limits are overridden by
sigma_lower
andsigma_upper
, if input. The default is 3. sigma_lowerfloat or
None
, optional The number of standard deviations to use as the lower bound for the clipping limit. If
None
then the value ofsigma
is used. The default isNone
. sigma_upperfloat or
None
, optional The number of standard deviations to use as the upper bound for the clipping limit. If
None
then the value ofsigma
is used. The default isNone
. maxitersint or
None
, optional The maximum number of sigmaclipping iterations to perform or
None
to clip until convergence is achieved (i.e., iterate until the last iteration clips nothing). If convergence is achieved prior tomaxiters
iterations, the clipping iterations will stop. The default is 5. cenfunc{‘median’, ‘mean’} or callable, optional
The statistic or callable function/object used to compute the center value for the clipping. If set to
'median'
or'mean'
then having the optional bottleneck package installed will result in the best performance. If using a callable function/object and theaxis
keyword is used, then it must be callable that can ignore NaNs (e.g.,numpy.nanmean
) and has anaxis
keyword to return an array with axis dimension(s) removed. The default is'median'
. stdfunc{‘std’} or callable, optional
The statistic or callable function/object used to compute the standard deviation about the center value. If set to
'std'
then having the optional bottleneck package installed will result in the best performance. If using a callable function/object and theaxis
keyword is used, then it must be callable that can ignore NaNs (e.g.,numpy.nanstd
) and has anaxis
keyword to return an array with axis dimension(s) removed. The default is'std'
. std_ddofint, optional
The delta degrees of freedom for the standard deviation calculation. The divisor used in the calculation is
N  std_ddof
, whereN
represents the number of elements. The default is 0. axis
None
or int or tuple of int, optional The axis or axes along which to sigma clip the data. If
None
, then the flattened data will be used.axis
is passed to thecenfunc
andstdfunc
. The default isNone
. growfloat or
False
, optional Radius within which to mask the neighbouring pixels of those that fall outwith the clipping limits (only applied along
axis
, if specified). As an example, for a 2D image a value of 1 will mask the nearest pixels in a cross pattern around each deviant pixel, while 1.5 will also reject the nearest diagonal neighbours and so on.
 dataarray_like or
 Returns
 mean, median, stddevfloat
The mean, median, and standard deviation of the sigmaclipped data.
See also