In [88]:

    

from numpy import *
import pandas as pd
%matplotlib inline


    

In [89]:

    

import matplotlib.pyplot as plt
import src.mylib.mfile as mfile
from matplotlib import style


    

In [90]:

    

stop =int('101010', 2) #101010 I Ching 63 After Completion
befo =int('010101', 2) #101010 I Ching 64 Before Completion

guai =int('111110', 2) #101010 I Ching 43

qian =int('111111', 2) #101010 I Ching 01
kun  =int('000000', 2) #101010 I Ching 02


    

In [91]:

    

df = mfile.loadOneSymbol("JPY=X", "src/db/forex.db")
def dateToDouble(d):
    return (d.year * 10000.0 + d.month * 100.0 + d.day) / 10000.0


    

    




<class 'pandas.core.frame.DataFrame'>
DatetimeIndex: 70564 entries, 2017-09-14 to 2005-01-03
Data columns (total 5 columns):
Symbol    70564 non-null object
Open      70564 non-null float64
High      70564 non-null float64
Low       70564 non-null float64
Close     70564 non-null float64
dtypes: float64(4), object(1)
memory usage: 3.2+ MB
None

In [92]:

    

#df.index = df.index.map(dateToDouble)


    

In [93]:

    

df = df[['Close']]


    

In [94]:

    

df = df.head(100)


    

In [95]:

    

df = df.diff()


    

In [96]:

    

fn = lambda x: (1.0 if x > 0.0 else 0.0)


    

In [97]:

    

xx = df['Close'].apply(fn)


    

In [98]:

    

L0 = xx


    

In [99]:

    

L1 = xx.shift(-1)


    

In [100]:

    

L2 = xx.shift(-2)
L3 = xx.shift(-3)
L4 = xx.shift(-4)
L5 = xx.shift(-5)


    

In [101]:

    

yy = L0 * 32 + L1 * 16 + L2 * 8 + L3 * 4 + L4 * 2 + L5


    

In [102]:

    

style.use('ggplot')


    

In [103]:

    

plt.scatter(yy.index, yy)


    

    
Out[103]:





<matplotlib.collections.PathCollection at 0x150e6fdaf28>