##// END OF EJS Templates
Add tests and fixes to clearcmd extension, when using numpy.
Add tests and fixes to clearcmd extension, when using numpy.

File last commit:

r1395:1feaf0a3
r1844:6921c624
Show More
mcdriver.py
71 lines | 2.0 KiB | text/x-python | PythonLexer
#!/usr/bin/env python
# encoding: utf-8
"""Run a Monte-Carlo options pricer in parallel."""
from IPython.kernel import client
import numpy as N
from mcpricer import MCOptionPricer
tc = client.TaskClient()
rc = client.MultiEngineClient()
# Initialize the common code on the engines
rc.run('mcpricer.py')
# Push the variables that won't change
#(stock print, interest rate, days and MC paths)
rc.push(dict(S=100.0, r=0.05, days=260, paths=10000))
task_string = """\
op = MCOptionPricer(S,K,sigma,r,days,paths)
op.run()
vp, ap, vc, ac = op.vanilla_put, op.asian_put, op.vanilla_call, op.asian_call
"""
# Create arrays of strike prices and volatilities
K_vals = N.linspace(90.0,100.0,5)
sigma_vals = N.linspace(0.0, 0.2,5)
# Submit tasks
taskids = []
for K in K_vals:
for sigma in sigma_vals:
t = client.StringTask(task_string,
push=dict(sigma=sigma,K=K),
pull=('vp','ap','vc','ac','sigma','K'))
taskids.append(tc.run(t))
print "Submitted tasks: ", taskids
# Block until tasks are completed
tc.barrier(taskids)
# Get the results
results = [tc.get_task_result(tid) for tid in taskids]
# Assemble the result
vc = N.empty(K_vals.shape[0]*sigma_vals.shape[0],dtype='float64')
vp = N.empty(K_vals.shape[0]*sigma_vals.shape[0],dtype='float64')
ac = N.empty(K_vals.shape[0]*sigma_vals.shape[0],dtype='float64')
ap = N.empty(K_vals.shape[0]*sigma_vals.shape[0],dtype='float64')
for i, tr in enumerate(results):
ns = tr.ns
vc[i] = ns.vc
vp[i] = ns.vp
ac[i] = ns.ac
ap[i] = ns.ap
vc.shape = (K_vals.shape[0],sigma_vals.shape[0])
vp.shape = (K_vals.shape[0],sigma_vals.shape[0])
ac.shape = (K_vals.shape[0],sigma_vals.shape[0])
ap.shape = (K_vals.shape[0],sigma_vals.shape[0])
def plot_options(K_vals, sigma_vals, prices):
"""Make a contour plot of the option prices."""
import pylab
pylab.contourf(sigma_vals, K_vals, prices)
pylab.colorbar()
pylab.title("Option Price")
pylab.xlabel("Volatility")
pylab.ylabel("Strike Price")