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bubble-economy / flock.py

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File flock.py

 TODO:
 * Consider calculating MI between *relative* axial positions or velocities of pairs of particles over time,
   rather than branching histories, which also might work in the infinite-time limit.
-* Parallelise in something natural, such as redis or 0MQ, or ruffus. Probably ruffus + sqlite is easiest.
-
+* Parallelise in something natural, such as redis or 0MQ, or ruffus.
+* store data in sqlite for ease of processing
+* store intermediate trials in sqlite too
+* calibrate pyentropy to work out why i get large positive information between deterministic variables.
 """
 from __future__ import division
 
     if n_samples<20 and test:
         raise ValueError("%d is too small a number to bin" % n_samples)
     return int(float(n_samples/5.)**(0.5))
-