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

# In[1]:


import tia.analysis.ta as ta
import tia.analysis.talib_wrapper as talib
import pandas as pd
from pandas.io.data import get_data_yahoo
from tia.analysis.model import SingleAssetPortfolio, PortfolioPricer, load_yahoo_stock, PortfolioSummary
from tia.analysis.model.ret import RoiiRetCalculator
from tia.util.fmt import DynamicColumnFormatter, DynamicRowFormatter, new_dynamic_formatter
import matplotlib.pyplot as plt


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# drop adj close & volume for example sake 
msft = load_yahoo_stock('MSFT', start='1/1/2010')


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


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# build signal when 50d crosses 200d
moving_avgs = pd.DataFrame({'50': ta.sma(msft.pxs.close, 50), '200': ta.sma(msft.pxs.close, 200)})
signal = ta.cross_signal(moving_avgs['50'], moving_avgs['200']).dropna()
# keep only entry
entry_signal = signal.copy()
entry_signal[signal.shift(1) == signal]  = 0 
entry_signal = entry_signal[entry_signal != 0]
# show when the signal triggers
moving_avgs.plot(color=['b', 'k'], title='MSFT moving averages')
for i, v in entry_signal.iteritems():
    if v == -1:
        plt.plot(i, moving_avgs['50'][i], 'rv')
    else:
        plt.plot(i, moving_avgs['50'][i], 'k^')


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# Can get the set of trades created by this signal
trades = ta.Signal(signal).close_to_close(msft.pxs.close)
trades


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# construct a portfolio from the trades
port = SingleAssetPortfolio(msft, trades, ret_calc=RoiiRetCalculator())


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# Show each of the individial transactions
port.txns.frame.tail()


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# Show the position summary
port.positions.frame


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# Transaction Level Profit & Loss
port.pl.txn_frame.tail(5)


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# Daily Profit & Loss Frame
port.pl.dly_frame.tail(5)


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# Show Profit & Loss Report
DynamicColumnFormatter(port.pl.report_by_year())


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# Show Position Information
port.positions.stats


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# Ability to show different return frequencies
fig, axes = plt.subplots(4, 1, figsize=(10, 12))
ax = port.performance.dly_details.plot_ltd(ax=axes[0])
port.performance.weekly_details.plot_ltd(ax=axes[1])
port.performance.monthly_details.plot_ltd(ax=axes[2])
port.performance.quarterly_details.plot_ltd(ax=axes[3])

axes[0].set_ylabel('Daily'), axes[1].set_ylabel('Weekly')
axes[2].set_ylabel('Monthly'), axes[3].set_ylabel('Quarterly')


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# 
# Show the Return on a dollar
#
port.performance.dly_details.plot_ret_on_dollar(label='LongShort')
port.long.performance.dly_details.plot_ret_on_dollar(label='Long')
port.short.performance.dly_details.plot_ret_on_dollar(label='Short')
plt.legend(loc='upper left')


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# Show a return report
F = new_dynamic_formatter(method='col', pcts=1, trunc_dot_zeros=1)
# Ability to added custom groupps
F(port.performance.report_by_year(prior_n_yrs=2, ranges=[(2011, 2012)]))


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# Build a custom report which shows return information and position level information in single frame
RF = new_dynamic_formatter('row', pcts=1, trunc_dot_zeros=1)

summary = PortfolioSummary()
summary.include_long_short().include_win_loss()
RF(summary(port).T)


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