takens for everything

takens.py

import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
from matplotlib.finance import quotes_historical_yahoo_ohlc
from random import randint
import matplotlib.cm as cmx
import matplotlib.colors as colors
date1 = (2013, 2, 1)
date2 = (2015, 7, 12)
quotes = quotes_historical_yahoo_ohlc('GE', date1, date2)
opening = [ q[1] for q in quotes[0:]]

def takens(time_serie, homothetia=1):
    q=np.array(time_serie)
    a=np.array(q)
    b=np.roll(a,1)
    c=np.roll(b,1)
    d=np.roll(c,1)
    e=np.roll(d,1)

    da=b-a
    db=c-b
    dc=d-c
    dd=e-d

    d2a=db-da
    d2b=dc-db
    d2c=dd-dc

    fig = plt.figure()
    ax = fig.gca(projection='3d')
    step=1
    jet = cm = plt.get_cmap('PRGn') 
    cNorm  = colors.Normalize(vmin=0, vmax=len(a))
    scalarMap = cmx.ScalarMappable(norm=cNorm, cmap=jet)
    max_in_data = max(d2c)
    for i in range(0,int(len(da)),step):
        color = scalarMap.to_rgba(i)
        norm = 1.0*sum(
            [d2a[i:i+step]**2,d2b[i:i+step]**2,d2c[i:i+step]**2]
        )**(.5)/(
            3*(max_in_data**2) **.5
        ) * homothetia
        #ax.plot(da[i:i+step], db[i:i+step],dc[i:i+step],
        #alpha=.2,color=color )
        ax.quiver(
            da[i:i+step], db[i:i+step], dc[i:i+step], 
            d2a[i:i+step],d2b[i:i+step],d2c[i:i+step],
            alpha=float(1.0*i/len(da)),
            length=norm,
            color = scalarMap.to_rgba(i)
        )
    plt.show()
    
takens(opening,3)
takens([ randint(0,32) for i in range(2000)],6)