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@@ -1,17 +1,27 @@
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import itertools
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+# number of spiketrains
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N=100
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+# starting time
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t_start=0 #ms
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+# end time
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t_stop=30000 #ms
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+# mean firing rate
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rate=10 #Hz
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+# bin size for calculating correlations
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binsize=2 #ms
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-assembly_sizes=[1,2,3,4,5,6]
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-# assembly_sizes='6,8'
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-correlations=[0.,0.05,0.1,0.15,0.2,0.3,0.4]
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-# correlations='0.3,0.1'
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+# number of neurons in a hub
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+assembly_sizes=[1,2,3,4,5,6] #/'6,8'
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+# mean correlation with a hub
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+correlations=[0.,0.05,0.1,0.15,0.2,0.3,0.4] #\'0.3,0.1'
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+# mean correlation in between all spiketrain pairs
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bkgr_correlation=0.
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+# method to insert correlations
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corr_method=['CPP', 'CPP'] #'pairwise_equivalent']
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-test=['ks_test']
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-seed=[0,1,2,3,4,5] #,6,7,8,9,10,11,12,13,14]
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+# name of the statistical test for comparison
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+test=['eigenangle_test', 'ks_test']
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+# random seeds
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+seed=[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14]
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seed_pairs = [f'{i[0]}-{i[1]}' for i in itertools.combinations(seed,2)]
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+# number of bins
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bin_num = int((t_stop-t_start) / binsize)
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