ryCh005.py

# -*- coding: utf-8 -*-
"""
Created on Tue May 10 14:15:38 2016

@author: csie3
financial data is here:

https://www.franklin.com.tw/Fund/NavHistory/101
===> f101.csv

"""

import pandas   as pd
import pylab    as pl
import thinkdsp as td
import numpy    as np


def serial_corr(wave, lag=1):
    N = len(wave)
    y1 = wave.ys[lag:]
    y2 = wave.ys[:N-lag]
    corr = np.corrcoef(y1, y2, ddof=0)[0, 1]
    return corr


def autocorr(wave):
    """Computes and plots the autocorrelation function.

    wave: Wave
    """
    lags = range(len(wave.ys))#//2)
    corrs = [serial_corr(wave, lag) for lag in lags]
    return lags, corrs

import numpy as np

def movingAverage(x, length):
    y= np.convolve(x, np.ones(length)/length)
    y= y[:len(x)]
    return y



def ryAutoCorr(fn):
    
    df= pd.read_csv(fn) #'f101.csv')#,  parse_dates=[0])
    ys= df.淨值.values
    
    ys= ys[-1::-1]
    
    wv= td.Wave(ys)
    
    corr= serial_corr(wv)
    
    R= autocorr(wv)
    
    pl.subplot(3,1,1)
    pl.plot(ys)
    
    pl.title(fn)
    
    pl.grid()
    
    pl.subplot(3,1,2)
    pl.plot(R[0], R[1])
    
    pl.grid()
    
    ma100=   movingAverage(wv.ys, 100)
    pl.subplot(3,1,3)    
    pl.plot(ma100)
    
    
fL= ['f101.csv']#,'f102.csv','f103.csv']

for fn in fL:
    pl.figure()
    ryAutoCorr(fn)