fluxcompensator.utils.plot.MakePlots

class fluxcompensator.utils.plot.MakePlots(input_array, wav_interest=None, prefix=None, name=None, multi_cut=None, single_cut=None, set_cut=None, dpi=None)

Plots slices of the val cube from SyntheticCube a the closest slice to wav_interest or val images of SyntheticImage. The boundaries of the slice or image is ploted as well. The plot has 4 different cut levels at 100, 99, 95 and 90 percent.

Parameters:

input_array : SyntheticCube, SyntheticImage, optional

input_array also reads arrays with SyntheticCube and SyntheticImage properties.

wav_interest : float, None

  • float : wavelength close to slice in microns.
  • None : Only if input_array is SyntheticImage like

prefix : str

Name of the image. Default naming chain is switched off.

name : str

Name of image within the default naming chain to distinguish the plot files. E. g. ‘PSF_gaussian’

mulit_cut : True, None

  • True : plots chosen image slice at cuts of [100, 99, 95, 90]%.
  • None : no mulit-plot is returned.

Default is None.

single_cut : float, None

  • float : cut level for single plot of image slice between 0 and 100.
  • None : no single plot is returned.

set_cut : tuple, None

  • tuple : set_cut(v_min, v_max)
    Minimal and Maximal physical value presented in the colorbars.
  • None : no plot with minimal and maximal cut is returned.

Default is None.

dpi : None, scalar > 0

The resolution in dots per inch. None is default and will use the value savefig.dpi in the matplotlibrc file.
Returns:

cube : SyntheticCube

3D val array with SyntheticCube properties.

image : SyntheticImage

2D val array with SyntheticImage properties.

Methods

histogram_cuts([dpi]) DS9 like histograms of the cuts can be checked here.

Methods (detail)

histogram_cuts(dpi=None)

DS9 like histograms of the cuts can be checked here.

Parameters:

dpi : None, scalar > 0

The resolution in dots per inch. None is default and will use the val savefig.dpi in the matplotlibrc file.