colormap_hess

gammapy.image.colormap_hess(transition=0.5, width=0.1)[source]

Colormap often used in H.E.S.S. collaboration publications.

This colormap goes black -> blue -> red -> yellow -> white.

A sharp blue -> red -> yellow transition is often used for significance images with a value of red at transition ~ 5 or transition ~ 7 so that the following effect is achieved:

  • black, blue: non-significant features, not well visible
  • red: features at the detection threshold transition
  • yellow, white: significant features, very well visible

The transition parameter is defined between 0 and 1. To calculate the value from data units an ImageNormalize instance should be used (see example below).

Parameters:

transition : float (default = 0.5)

Value of the transition to red (between 0 and 1).

width : float (default = 0.5)

Width of the blue-red color transition (between 0 and 1).

Returns:

colormap : matplotlib.colors.LinearSegmentedColormap

Colormap

Examples

>>> from gammapy.image import colormap_hess
>>> from astropy.visualization.mpl_normalize import ImageNormalize
>>> from astropy.visualization import LinearStretch
>>> normalize = ImageNormalize(vmin=-5, vmax=15, stretch=LinearStretch())
>>> transition = normalize(5)
>>> cmap = colormap_hess(transition=transition)

(png, hires.png, pdf)

../_images/gammapy-image-colormap_hess-1.png