lsst.pipe.drivers  19.0.0-7-g039c0b5+11
Classes | Functions
lsst.pipe.drivers.background Namespace Reference

Classes

class  BackgroundConfig
 
class  FocalPlaneBackground
 
class  FocalPlaneBackgroundConfig
 
class  MaskObjectsConfig
 
class  MaskObjectsTask
 
class  SkyMeasurementConfig
 
class  SkyMeasurementTask
 
class  SkyStatsConfig
 

Functions

def robustMean (array, rej=3.0)
 
def interpolate1D (method, xSample, ySample, xInterp)
 
def interpolateBadPixels (array, isBad, interpolationStyle)
 
def smoothArray (array, bad, sigma)
 

Function Documentation

◆ interpolate1D()

def lsst.pipe.drivers.background.interpolate1D (   method,
  xSample,
  ySample,
  xInterp 
)
Interpolate in one dimension

Interpolates the curve provided by `xSample` and `ySample` at
the positions of `xInterp`. Automatically backs off the
interpolation method to achieve successful interpolation.

Parameters
----------
method : `lsst.afw.math.Interpolate.Style`
    Interpolation method to use.
xSample : `numpy.ndarray`
    Vector of ordinates.
ySample : `numpy.ndarray`
    Vector of coordinates.
xInterp : `numpy.ndarray`
    Vector of ordinates to which to interpolate.

Returns
-------
yInterp : `numpy.ndarray`
    Vector of interpolated coordinates.

Definition at line 376 of file background.py.

◆ interpolateBadPixels()

def lsst.pipe.drivers.background.interpolateBadPixels (   array,
  isBad,
  interpolationStyle 
)
Interpolate bad pixels in an image array

The bad pixels are modified in the array.

Parameters
----------
array : `numpy.ndarray`
    Image array with bad pixels.
isBad : `numpy.ndarray` of type `bool`
    Boolean array indicating which pixels are bad.
interpolationStyle : `str`
    Style for interpolation (see `lsst.afw.math.Background`);
    supported values are CONSTANT, LINEAR, NATURAL_SPLINE,
    AKIMA_SPLINE.

Definition at line 415 of file background.py.

◆ robustMean()

def lsst.pipe.drivers.background.robustMean (   array,
  rej = 3.0 
)
Measure a robust mean of an array

Parameters
----------
array : `numpy.ndarray`
    Array for which to measure the mean.
rej : `float`
    k-sigma rejection threshold.

Returns
-------
mean : `array.dtype`
    Robust mean of `array`.

Definition at line 17 of file background.py.

◆ smoothArray()

def lsst.pipe.drivers.background.smoothArray (   array,
  bad,
  sigma 
)
Gaussian-smooth an array while ignoring bad pixels

It's not sufficient to set the bad pixels to zero, as then they're treated
as if they are zero, rather than being ignored altogether. We need to apply
a correction to that image that removes the effect of the bad pixels.

Parameters
----------
array : `numpy.ndarray` of floating-point
    Array to smooth.
bad : `numpy.ndarray` of `bool`
    Flag array indicating bad pixels.
sigma : `float`
    Gaussian sigma.

Returns
-------
convolved : `numpy.ndarray`
    Smoothed image.

Definition at line 849 of file background.py.