#!/usr/bin/env python
# coding: utf-8

# In[1]:


get_ipython().run_line_magic('matplotlib', 'inline')


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startDate = datetime(2008, 1, 1)
endDate = datetime(2012, 8, 1)

def getQuotes(symbol, start, end):
    quotes = fin.quotes_historical_yahoo(symbol, start, end)
    dates, open, close, high, low, volume = zip(*quotes)

    data = {
        'open': open,
        'close': close,
        'high': high,
        'low': low,
        'volume': volume
    }

    dates = pd.Index([datetime.fromordinal(int(d)) for d in dates])
    return pd.DataFrame(data, index=dates)

data = {}
for s in ['AAPL', 'GOOG', 'INTC', 'MSFT', 'FB']:
    data[s] = getQuotes(s, startDate, endDate)
panel = pd.Panel(data)    


# In[2]:


from datetime import datetime

import pandas as pd
import numpy as np
import matplotlib.finance as fin

import ts_charting as charting
import ts_charting.lab.lab as tslab
charting.figsize(20,10)


# In[4]:


df = panel['AAPL']


# In[5]:


lab = tslab.Lab(draw=True)
fig = lab.station('AAPL')
df.tail(500).ohlc_plot()
pd.rolling_mean(df.close, 30).fplot('30 day ma', color='blue')
pd.rolling_mean(df.close, 90).fplot('90 day ma', color='red')
fig.plot_markers('gap up > 1%', (df.open / df.high.shift(1)) > 1.01, yvalues=df.open, color='lime')
fig.plot_markers('gap down > 1%', (df.open / df.low.shift(1)) < .99, yvalues=df.open, color='pink')


# ## ID3-lab
# 
# Using the same plot commands, generate a dataset for the id3lab. 
# 
# http://rawgithub.com/dalejung/id3/master/demo/lab_demo/lab_demo.html

# In[6]:


# 
lab = tslab.Lab(draw=False)
def plot(lab, symbol):
    fig = lab.station(symbol)
    df = panel[symbol]
    df.ohlc_plot()
    pd.rolling_mean(df.close, 30).fplot('30 day ma', color='blue')
    pd.rolling_mean(df.close, 90).fplot('90 day ma', color='red')
    fig.plot_markers('gap up > 1%', (df.open / df.high.shift(1)) > 1.01, yvalues=df.open, color='lime')
    fig.plot_markers('gap down > 1%', (df.open / df.low.shift(1)) < .99, yvalues=df.open, color='pink')
    
for symbol in panel.keys():
    plot(lab, symbol)


# In[7]:


with open('lab.json', 'w') as f:
    pass
    #f.write(lab.to_json())


# ## standalone pages
# 
# `ipycli` standalone with `id3lab`
# 
# **Note to nbviewers**
# 
# The actual standalone link is generated via javascript (in order to get kernel/host information available only in browser). The pics below show functionality when running on live ipython.
# 
# [Example link](https://www.evernote.com/shard/s9/sh/89b66ac6-3327-45c1-a051-bd969da7c0df/796f6fe46d3007bd4abecff788d24667/deep/0/ts-chart-id3lab-8673298.png)
# 
# [Example output:](https://www.evernote.com/shard/s9/sh/35f6322c-3360-4c57-8e68-234938f4a8ce/44a8d1db9f0d3650c145fb799987ab63/deep/0/idale.local-8888-standalone-4ac720f8-8097-51d8-9285-ac1bad518b5a-id3lab-to_html-and-1.-tmux-(ssh).png)

# In[7]:


from id3lab import ID3Lab

lab = ID3Lab()


# In[8]:


for symbol in panel.keys():
    plot(lab, symbol)
lab


# In[27]:


from ts_charting import json


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