import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

%load_ext autoreload
%autoreload 2

%matplotlib inline

%precision 2
pd.set_option('display.precision', 3)

import ndl,sim
from zt import ztnbinom

from IPython.parallel import Client

rc = Client(profile='home')
dview = rc.direct_view()
dview.block = True
lview = rc.load_balanced_view()
lview.block = True
rc.ids

%%px

import sys
sys.path = ['/home1/malouf/learning'] + sys.path
import sim
#from sim import Simulation

def cues(N):
    card = ztnbinom.rvs(3,.6)
    feats = range(card) + ['exactly%d'%card]
    return [feats,codeFunc(card)]    

ns = [ztnbinom.rvs(3,.6) for i in xrange(10000)]
data = np.zeros((max(ns)))
for i in ns:
    data[i-1] += 1
data

data = pd.DataFrame(data,columns=['Frequency'],index=range(1,len(data)+1))
data['Cues'] = [range(1,i+1) + ['exactly%d'%i] for i in data.index]
data['Number'] = data.index
data

%%time
r = sim.experiment(data, P=200, view=lview)

sim.all_results(r)

data['Cues'] = [['background'] + cues for cues in data['Cues']]
data

%%time
r2 = sim.experiment(data, P=200, view=lview)
sim.all_results(r2)

ns = [ztnbinom.rvs(3,.45) for i in xrange(10000)]
data2 = np.zeros((max(ns)))
for i in ns:
    data2[i-1] += 1
data2 = pd.DataFrame(data2,columns=['Frequency'],index=range(1,len(data2)+1))
data2['Cues'] = [range(1,i+1) + ['exactly%d'%i] for i in data2.index]
data2['Number'] = data2.index
data2

%%time
r3 = sim.experiment(data, P=200, view=lview)
sim.all_results(r3)