Fixing examples.

docs/examples/kernel/mcpricer.py

@@ -1,42 +1,43 b''
 import numpy as N
 from math import *
 
 class MCOptionPricer(object):
     def __init__(self, S=100.0, K=100.0, sigma=0.25, r=0.05, days=260, paths=10000):
         self.S = S
         self.K = K
         self.sigma = sigma
         self.r = r
         self.days = days
         self.paths = paths
         self.h = 1.0/self.days
         self.const1 = exp((self.r-0.5*self.sigma**2)*self.h)
         self.const2 = self.sigma*sqrt(self.h)
         
     def run(self):
         stock_price = self.S*N.ones(self.paths, dtype='float64')
         stock_price_sum = N.zeros(self.paths, dtype='float64')
         for j in range(self.days):
             growth_factor = self.const1*N.exp(self.const2*N.random.standard_normal(self.paths))
             stock_price = stock_price*growth_factor
             stock_price_sum = stock_price_sum + stock_price
         stock_price_avg = stock_price_sum/self.days
         zeros = N.zeros(self.paths, dtype='float64')
         r_factor = exp(-self.r*self.h*self.days)
         self.vanilla_put = r_factor*N.mean(N.maximum(zeros,self.K-stock_price))
         self.asian_put = r_factor*N.mean(N.maximum(zeros,self.K-stock_price_avg))
         self.vanilla_call = r_factor*N.mean(N.maximum(zeros,stock_price-self.K))
         self.asian_call = r_factor*N.mean(N.maximum(zeros,stock_price_avg-self.K))
 
 
 def main():
     op = MCOptionPricer()
     op.run()
     print "Vanilla Put Price = ", op.vanilla_put
     print "Asian Put Price = ", op.asian_put
     print "Vanilla Call Price = ", op.vanilla_call
     print "Asian Call Price = ", op.asian_call
 
 
 if __name__ == '__main__':
     main()
+

docs/examples/kernel/rmt.ipy

@@ -1,57 +1,57 b''
 #-------------------------------------------------------------------------------
 # 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))
+    # import pylab
+    # pylab.hist(parallelDiffs(rc,matsize,matsize))