djs_reject¶
-
pydl.pydlutils.math.
djs_reject
(data, model, outmask=None, inmask=None, sigma=None, invvar=None, lower=None, upper=None, maxdev=None, maxrej=None, groupdim=None, groupsize=None, groupbadpix=False, grow=0, sticky=False)[source]¶ Routine to reject points when doing an iterative fit to data.
Parameters: data :
numpy.ndarray
The data
model :
numpy.ndarray
The model, must have the same number of dimensions as
data
.outmask :
numpy.ndarray
, optionalOutput mask, generated by a previous call to
djs_reject
. If not supplied, this mask will be initialized to a mask that masks nothing. Although this parameter is technically optional, it will almost always be set.inmask :
numpy.ndarray
, optionalInput mask. Bad points are marked with a value that evaluates to
False
. Must have the same number of dimensions asdata
.sigma :
numpy.ndarray
, optionalStandard deviation of the data, used to reject points based on the values of
upper
andlower
.invvar :
numpy.ndarray
, optionalInverse variance of the data, used to reject points based on the values of
upper
andlower
. If bothsigma
andinvvar
are set,invvar
will be ignored.lower :
int
orfloat
, optionalIf set, reject points with data < model - lower * sigma.
upper :
int
orfloat
, optionalIf set, reject points with data > model + upper * sigma.
maxdev :
int
orfloat
, optionalIf set, reject points with abs(data-model) > maxdev. It is permitted to set all three of
lower
,upper
andmaxdev
.maxrej :
int
ornumpy.ndarray
, optionalMaximum number of points to reject in this iteration. If
groupsize
orgroupdim
are set to arrays, this should be an array as well.groupdim
To be documented.
groupsize
To be documented.
groupbadpix :
bool
, optionalIf set to
True
, consecutive sets of bad pixels are considered groups, overriding the values ofgroupsize
.grow :
int
, optionalIf set to a non-zero integer, N, the N nearest neighbors of rejected pixels will also be rejected.
sticky :
bool
, optionalIf set to
True
, pixels rejected in one iteration remain rejected in subsequent iterations, even if the model changes.Returns: A tuple containing a mask where rejected data values are
False
and a boolean value set toTrue
ifdjs_reject
believes there is no further rejection to be done.Raises: ValueError
If dimensions of various inputs do not match.