poppy.display_PSF(HDUlist_or_filename=None, ext=0, vmin=1e-08, vmax=0.1, scale=u'log', cmap=<matplotlib.colors.LinearSegmentedColormap object at 0x109e87910>, title=None, imagecrop=None, adjust_for_oversampling=False, normalize=u'None', crosshairs=False, markcentroid=False, colorbar=True, colorbar_orientation=u'vertical', pixelscale=u'PIXELSCL', ax=None, return_ax=False)[source]

Display nicely a PSF from a given HDUlist or filename

This is extensively configurable. In addition to making an attractive display, for interactive usage this function provides a live display of the pixel value at a given (x,y) as you mouse around the image.


HDUlist_or_filename : fits.HDUlist or string

FITS file containing image to display.

ext : int

FITS extension. default = 0

vmin, vmax : float

min and max for image display scaling

scale : str

‘linear’ or ‘log’, default is log

cmap : matplotlib.cm.Colormap instance

Colormap to use. Default is matplotlib.cm.jet

ax : matplotlib.Axes instance

Axes to display into.

title : string, optional

imagecrop : float

size of region to display (default is whole image)

normalize : string

set to ‘peak’ to normalize peak intensity =1, or to ‘total’ to normalize total flux=1. Default is no normalization.

adjust_for_oversampling : bool

rescale to conserve surface brightness for oversampled PSFs? (making this True conserves surface brightness but not total flux) default is False, to conserve total flux.

markcentroid : bool

Draw a crosshairs at the image centroid location? Centroiding is computed with the JWST-standard moving box algorithm.

colorbar : bool

Draw a colorbar?

colorbar_orientation : str

either ‘horizontal’ or ‘vertical’; default is vertical.

pixelscale : str or float

if str, interpreted as the FITS keyword name for the pixel scale in arcsec/pixels. if float, used as the pixelscale directly.

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