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#!/usr/bin/env python
from xtcav.GenerateLasingOffReference import *
GLOC=GenerateLasingOffReference();
GLOC.experiment='amoc8114'
GLOC.runs='86'
GLOC.maxshots=1401
GLOC.nb=1
GLOC.islandSplitMethodislandsplitmethod = 'contourLabelscipyLabel'       # see documentation below for how to set this parameter
GLOC.groupsize=5             # see documentation below for how to set this parameter
GLOC.SetValidityRange(86,91) # delete second run number argument to have the validity range be open-ended ("end")
GLOC.Generate();

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-groupsize: 5 is a good number. Increasing this number will make better references, but they may also make them less accurate, as you would be averaging a larger number of profiles. If you decide to increase this number by a factor, then I would also increase n by the same factor, so in the end the total number of reference is the same. (see also thoughts from Tim Maxwell below).

-islandSplitMethodislandsplitmethod: Several image processing algorithms have been created to separate bunches that appear on the same image. Each algorithm is advantageous in certain types of conditions and thus it might be worth trying all of them and see what achieves the best results.  The defaults parameter is 'scipylabel'. If one does not set islandSplitMethod to islandsplitmethod to anything, the parameter will be set to 'scipylabel'. If one would like to change from the default , one can use GLOC.islandSplitMethod islandsplitmethod = 'contourLabel'.  'scipylabel' calls the scipy label function to label contiguous regions. 'contourlabel' tries to adjust a threshold until two large groups are found, grouping together pixels using an opencv contour method. 

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