# kepdiffim: difference imaging of pixels within a target mask¶

pyke.kepdiffim.kepdiffim(infile, outfile=None, plotfile=None, imscale='logarithmic', colmap='PuBu', filterlc=False, function='boxcar', cutoff=1.0, overwrite=False, verbose=False, logfile='kepdiffim.log')

kepdiffim – difference imaging of pixels within a target mask

kepdiffim plots the mean, standard deviation and chi distribution images for the mask contained within a target pixel file. The standard deviation on each pixel is defined as $$[flux - mean]^2 / [N - 1]$$. The chi distribution is $$\sqrt{[mean - flux] ^ 2 / sigma ^ 2}$$. If required, the data can be fed through a boxcar, gaussian or sinc function high bandpass filter in order to remove low frequency signal from the data. kepdiffim is a diagnostic tool for identifying source contaminants in the background or foreground of the target. It can be employed to identify pixels for inclusion or exclusion when re-extracting a Kepler light curve from target pixel files.

Parameters: infile : str The name of a MAST standard format FITS file containing Kepler Target Pixel data within the first data extension. outfile : str The name of the output FITS file. This file has four data extensions. The first called ‘FLUX’ contains an image of the pixel-by-pixel mean flux within target mask. The second contains the pixel variance image of the mask pixels over time. The third contains the standard deviation image, in this case the variance image is normalized to the median 1-$$\sigma$$ error for each pixel. The fourth extension is the pixel mask, as defined in the second extension of the target pixel file. plotfile : str Name of an optional diagnostic output plot file containing the results of kepdiffim. Typically this is a PNG format file. If no diagnostic file is required, plotfile can be None. If plotfile is None the plot will be generated but the plot will not be saved to a file. imscale : str kepdiffim can plot images with three choices of image scales. The choice is made using this argument. The options are: linear logarithmic squareroot cmap : str color intensity scheme for the image display. filter : bool If filter is True, the light curve for each pixel will be treated by a high band-pass filter to remove long-term trends from e. g. differential velocity aberration. function : str The functional form of the high pass-band filter. The options are: boxcar gauss sinc cutoff : float [days] The frequency of the high pass-band cutoff. overwrite : bool Overwrite the output file? verbose : bool Print informative messages and warnings to the shell and logfile? logfile : str Name of the logfile containing error and warning messages.

Examples

\$ kepdiffim kplr011390659-2010355172524_lpd-targ.fits.gz
--filter --function boxcar --cutoff 0.1 --plotfile kepdiffim.png
--cmap YlOrBr --imscale linear --verbose