pymc simulated data

gistfile1.py

from pymc import *
import numpy as np
import matplotlib.pyplot as pyplot
from pprint import pprint

#-----------------------------------------------------------------------------------------
# Simulated data
#

def simulated(N, weekday_mean, weekend_mean, click_mean, conversion_rate):
    days = np.tile([0,0,0,0,0,1,1], np.ceil(N/7.))[:N]
    
    installs = np.zeros(N)
    installs[days==0] = rpoisson(weekday_mean, size=sum(days==0))
    installs[days==1] = rpoisson(weekend_mean, size=sum(days==1))
    
    # 0.1 installs per click
    clicks = rpoisson(click_mean, size=N) # clicks
    installs += [rpoisson(c*conversion_rate) for c in clicks]
    
    assert len(set(arr.shape for arr in [installs, clicks, days])) == 1
    return installs, clicks, days

installs, clicks, days = simulated(1000, 10, 20, 20, 0.1)
pyplot.bar(range(len(installs)), np.where(days==0, installs, 0), color='#339988')
pyplot.bar(range(len(installs)), np.where(days==1, installs, 0), color='#dd7766')
pyplot.plot(range(len(installs)), clicks)
pyplot.savefig("installs.png")