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Moved system info into its own utility, so we can use in in test suite too.
Moved system info into its own utility, so we can use in in test suite too.

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rmt.ipy
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#-------------------------------------------------------------------------------
# Driver code that the client runs.
#-------------------------------------------------------------------------------
# To run this code start a controller and engines using:
# ipcluster -n 2
# Then run the scripts by doing irunner rmt.ipy or by starting ipython and
# doing run rmt.ipy.
from rmtkernel import *
from IPython.kernel import client
def wignerDistribution(s):
"""Returns (s, rho(s)) for the Wigner GOE distribution."""
return (numpy.pi*s/2.0) * numpy.exp(-numpy.pi*s**2/4.)
def generateWignerData():
s = numpy.linspace(0.0,4.0,400)
rhos = wignerDistribution(s)
return s, rhos
def serialDiffs(num, N):
diffs = ensembleDiffs(num, N)
normalizedDiffs = normalizeDiffs(diffs)
return normalizedDiffs
def parallelDiffs(rc, num, N):
nengines = len(rc.get_ids())
num_per_engine = num/nengines
print "Running with", num_per_engine, "per engine."
rc.push(dict(num_per_engine=num_per_engine, N=N))
rc.execute('diffs = ensembleDiffs(num_per_engine, N)')
# gather blocks always for now
pr = rc.gather('diffs')
return pr.r
# Main code
if __name__ == '__main__':
rc = client.MultiEngineClient()
print "Distributing code to engines..."
r = rc.run('rmtkernel.py')
rc.block = False
# Simulation parameters
nmats = 100
matsize = 30
%timeit -n1 -r1 serialDiffs(nmats,matsize)
%timeit -n1 -r1 parallelDiffs(rc, nmats, matsize)
# Uncomment these to plot the histogram
# import pylab
# pylab.hist(parallelDiffs(rc,matsize,matsize))