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MAINT: Move analyze methods into algorithm files

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This commit is contained in:
Stewart Douglas
2015-09-10 11:36:14 -04:00
parent 723c5bb069
commit 283c959cc4
9 changed files with 161 additions and 111 deletions
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tests/test_examples.py
+1
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@@ -39,6 +39,7 @@ def example_dir():
class ExamplesTests(TestCase):
# Test algorithms as if they being executed directly from the command line.
@parameterized.expand(((os.path.basename(f).replace('.', '_'), f) for f in
glob.glob(os.path.join(example_dir(), '*.py'))))
def test_example(self, name, example):
zipline/examples/buyapple.py
+18 -12
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@@ -26,11 +26,27 @@ def handle_data(context, data):
record(AAPL=data[symbol('AAPL')].price)
# Note: this function can be removed if running
# this algorithm on quantopian.com
def analyze(context=None, results=None):
import matplotlib.pyplot as plt
# Plot the portfolio and asset data.
ax1 = plt.subplot(211)
results.portfolio_value.plot(ax=ax1)
ax1.set_ylabel('Portfolio value (USD)')
ax2 = plt.subplot(212, sharex=ax1)
results.AAPL.plot(ax=ax2)
ax2.set_ylabel('AAPL price (USD)')
# Show the plot.
plt.gcf().set_size_inches(18, 8)
plt.show()
# Note: this if-block should be removed if running
# this algorithm on quantopian.com
if __name__ == '__main__':
from datetime import datetime
import matplotlib.pyplot as plt
import pytz
from zipline.algorithm import TradingAlgorithm
from zipline.utils.factory import load_from_yahoo
@@ -48,14 +64,4 @@ if __name__ == '__main__':
identifiers=['AAPL'])
results = algo.run(data)
# Plot the portfolio and asset data.
ax1 = plt.subplot(211)
results.portfolio_value.plot(ax=ax1)
ax1.set_ylabel('Portfolio value (USD)')
ax2 = plt.subplot(212, sharex=ax1)
results.AAPL.plot(ax=ax2)
ax2.set_ylabel('AAPL price (USD)')
# Show the plot.
plt.gcf().set_size_inches(18, 8)
plt.show()
analyze(results=results)
zipline/examples/buyapple_analyze.py
-10
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@@ -1,10 +0,0 @@
import matplotlib.pyplot as plt
def analyze(context, perf):
ax1 = plt.subplot(211)
perf.portfolio_value.plot(ax=ax1)
ax2 = plt.subplot(212, sharex=ax1)
perf.AAPL.plot(ax=ax2)
plt.gcf().set_size_inches(18, 8)
plt.show()
zipline/examples/dual_ema_talib.py
+44 -17
View File
@@ -65,35 +65,62 @@ def handle_data(context, data):
sell=sell)
# Note: this function can be removed if running
# this algorithm on quantopian.com
def analyze(context=None, results=None):
import matplotlib.pyplot as plt
import logbook
logbook.StderrHandler().push_application()
log = logbook.Logger('Algorithm')
fig = plt.figure()
ax1 = fig.add_subplot(211)
results.portfolio_value.plot(ax=ax1)
ax1.set_ylabel('Portfolio value (USD)')
ax2 = fig.add_subplot(212)
ax2.set_ylabel('Price (USD)')
# If data has been record()ed, then plot it.
# Otherwise, log the fact that no data has been recorded.
if 'AAPL' in results and 'short_ema' in results and 'long_ema' in results:
results[['AAPL', 'short_ema', 'long_ema']].plot(ax=ax2)
ax2.plot(results.ix[results.buy].index, results.short_ema[results.buy],
'^', markersize=10, color='m')
ax2.plot(results.ix[results.sell].index,
results.short_ema[results.sell],
'v', markersize=10, color='k')
plt.legend(loc=0)
plt.gcf().set_size_inches(18, 8)
else:
msg = 'AAPL, short_ema and long_ema data not captured using record().'
ax2.annotate(msg, xy=(0.1, 0.5))
log.info(msg)
plt.show()
# Note: this if-block should be removed if running
# this algorithm on quantopian.com
if __name__ == '__main__':
from datetime import datetime
import logbook
import matplotlib.pyplot as plt
import pytz
from zipline.algorithm import TradingAlgorithm
from zipline.utils.factory import load_from_yahoo
logbook.StderrHandler().push_application()
# Set the simulation start and end dates.
start = datetime(2014, 1, 1, 0, 0, 0, 0, pytz.utc)
end = datetime(2014, 11, 1, 0, 0, 0, 0, pytz.utc)
# Load price data from yahoo.
data = load_from_yahoo(stocks=['AAPL'], indexes={}, start=start,
end=end)
# Create and run the algorithm.
algo = TradingAlgorithm(initialize=initialize, handle_data=handle_data,
identifiers=['AAPL'])
results = algo.run(data).dropna()
fig = plt.figure()
ax1 = fig.add_subplot(211, ylabel='portfolio value')
results.portfolio_value.plot(ax=ax1)
ax2 = fig.add_subplot(212)
results[['AAPL', 'short_ema', 'long_ema']].plot(ax=ax2)
ax2.plot(results.ix[results.buy].index, results.short_ema[results.buy],
'^', markersize=10, color='m')
ax2.plot(results.ix[results.sell].index, results.short_ema[results.sell],
'v', markersize=10, color='k')
plt.legend(loc=0)
plt.gcf().set_size_inches(18, 8)
plt.show()
# Plot the portfolio and asset data.
analyze(results=results)
zipline/examples/dual_moving_average.py
+43 -21
View File
@@ -62,16 +62,56 @@ def handle_data(context, data):
long_mavg=long_mavg[context.sym])
# Note: this function can be removed if running
# this algorithm on quantopian.com
def analyze(context=None, results=None):
import matplotlib.pyplot as plt
import logbook
logbook.StderrHandler().push_application()
log = logbook.Logger('Algorithm')
fig = plt.figure()
ax1 = fig.add_subplot(211)
results.portfolio_value.plot(ax=ax1)
ax1.set_ylabel('Portfolio value (USD)')
ax2 = fig.add_subplot(212)
ax2.set_ylabel('Price (USD)')
# If data has been record()ed, then plot it.
# Otherwise, log the fact that no data has been recorded.
if ('AAPL' in results and 'short_mavg' in results and
'long_mavg' in results):
results['AAPL'].plot(ax=ax2)
results[['short_mavg', 'long_mavg']].plot(ax=ax2)
trans = results.ix[[t != [] for t in results.transactions]]
buys = trans.ix[[t[0]['amount'] > 0 for t in
trans.transactions]]
sells = trans.ix[
[t[0]['amount'] < 0 for t in trans.transactions]]
ax2.plot(buys.index, results.short_mavg.ix[buys.index],
'^', markersize=10, color='m')
ax2.plot(sells.index, results.short_mavg.ix[sells.index],
'v', markersize=10, color='k')
plt.legend(loc=0)
else:
msg = 'AAPL, short_mavg & long_mavg data not captured using record().'
ax2.annotate(msg, xy=(0.1, 0.5))
log.info(msg)
plt.show()
# Note: this if-block should be removed if running
# this algorithm on quantopian.com
if __name__ == '__main__':
from datetime import datetime
import matplotlib.pyplot as plt
import pytz
from zipline.algorithm import TradingAlgorithm
from zipline.utils.factory import load_from_yahoo
# Set the simulation start and end dates
# Set the simulation start and end dates.
start = datetime(2011, 1, 1, 0, 0, 0, 0, pytz.utc)
end = datetime(2013, 1, 1, 0, 0, 0, 0, pytz.utc)
@@ -85,22 +125,4 @@ if __name__ == '__main__':
results = algo.run(data)
# Plot the portfolio and asset data.
fig = plt.figure()
ax1 = fig.add_subplot(211)
results.portfolio_value.plot(ax=ax1)
ax1.set_ylabel('Portfolio value (USD)')
ax2 = fig.add_subplot(212)
ax2.set_ylabel('Price in (USD)')
results[['AAPL', 'short_mavg', 'long_mavg']].plot(ax=ax2)
trans = results.ix[[t != [] for t in results.transactions]]
buys = trans.ix[[t[0]['amount'] > 0 for t in
trans.transactions]]
sells = trans.ix[[t[0]['amount'] < 0 for t in trans.transactions]]
ax2.plot(buys.index, results.short_mavg.ix[buys.index],
'^', markersize=10, color='m')
ax2.plot(sells.index, results.short_mavg.ix[sells.index],
'v', markersize=10, color='k')
plt.legend(loc=0)
# Show the plot.
plt.show()
analyze(results=results)
zipline/examples/dual_moving_average_analyze.py
-24
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@@ -1,24 +0,0 @@
import matplotlib.pyplot as plt
def analyze(context, perf):
fig = plt.figure()
ax1 = fig.add_subplot(211)
perf.portfolio_value.plot(ax=ax1)
ax1.set_ylabel('portfolio value in $')
ax2 = fig.add_subplot(212)
perf['AAPL'].plot(ax=ax2)
perf[['short_mavg', 'long_mavg']].plot(ax=ax2)
perf_trans = perf.ix[[t != [] for t in perf.transactions]]
buys = perf_trans.ix[[t[0]['amount'] > 0 for t in perf_trans.transactions]]
sells = perf_trans.ix[
[t[0]['amount'] < 0 for t in perf_trans.transactions]]
ax2.plot(buys.index, perf.short_mavg.ix[buys.index],
'^', markersize=10, color='m')
ax2.plot(sells.index, perf.short_mavg.ix[sells.index],
'v', markersize=10, color='k')
ax2.set_ylabel('price in $')
plt.legend(loc=0)
plt.show()
zipline/examples/olmar.py
+22 -6
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@@ -149,18 +149,34 @@ def simplex_projection(v, b=1):
w[w < 0] = 0
return w
if __name__ == '__main__':
# Note: this function can be removed if running
# this algorithm on quantopian.com
def analyze(context=None, results=None):
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(111)
results.portfolio_value.plot(ax=ax)
ax.set_ylabel('Portfolio value (USD)')
plt.show()
# Note: this if-block should be removed if running
# this algorithm on quantopian.com
if __name__ == '__main__':
# Set the simulation start and end dates.
start = datetime(2004, 1, 1, 0, 0, 0, 0, pytz.utc)
end = datetime(2008, 1, 1, 0, 0, 0, 0, pytz.utc)
# Load price data from yahoo.
data = load_from_yahoo(stocks=STOCKS, indexes={}, start=start, end=end)
data = data.dropna()
# Create and run the algorithm.
olmar = TradingAlgorithm(handle_data=handle_data,
initialize=initialize,
identifiers=STOCKS)
results = olmar.run(data)
fig = plt.figure()
ax = fig.add_subplot(111)
results.portfolio_value.plot(ax=ax)
ax.set_ylabel('portfolio value in $')
plt.show()
# Plot the portfolio data.
analyze(results=results)
zipline/examples/pairtrade.py
+33 -15
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@@ -24,6 +24,7 @@ import pytz
from zipline.algorithm import TradingAlgorithm
from zipline.transforms import batch_transform
from zipline.utils.factory import load_from_yahoo
from zipline.api import symbol
@batch_transform
@@ -74,7 +75,9 @@ class Pairtrade(TradingAlgorithm):
######################################################
# 2. Compute spread and zscore
zscore = self.compute_zscore(data, slope, intercept)
self.record(zscores=zscore)
self.record(zscores=zscore,
PEP=data[symbol('PEP')].price,
KO=data[symbol('KO')].price)
######################################################
# 3. Place orders
@@ -116,25 +119,40 @@ class Pairtrade(TradingAlgorithm):
pep_amount = self.portfolio.positions[self.PEP].amount
self.order(self.PEP, -1 * pep_amount)
if __name__ == '__main__':
logbook.StderrHandler().push_application()
start = datetime(2000, 1, 1, 0, 0, 0, 0, pytz.utc)
end = datetime(2002, 1, 1, 0, 0, 0, 0, pytz.utc)
data = load_from_yahoo(stocks=['PEP', 'KO'], indexes={},
start=start, end=end)
pairtrade = Pairtrade()
results = pairtrade.run(data)
data['spreads'] = np.nan
# Note: this function can be removed if running
# this algorithm on quantopian.com
def analyze(context=None, results=None):
ax1 = plt.subplot(211)
# TODO Bugged - indices are out of bounds
# data[[pairtrade.PEPsid, pairtrade.KOsid]].plot(ax=ax1)
plt.ylabel('price')
plt.title('PepsiCo & Coca-Cola Co. share prices')
results[['PEP', 'KO']].plot(ax=ax1)
plt.ylabel('Price (USD)')
plt.setp(ax1.get_xticklabels(), visible=False)
ax2 = plt.subplot(212, sharex=ax1)
results.zscores.plot(ax=ax2, color='r')
plt.ylabel('zscored spread')
plt.ylabel('Z-scored spread')
plt.gcf().set_size_inches(18, 8)
plt.show()
# Note: this if-block should be removed if running
# this algorithm on quantopian.com
if __name__ == '__main__':
logbook.StderrHandler().push_application()
# Set the simulation start and end dates.
start = datetime(2000, 1, 1, 0, 0, 0, 0, pytz.utc)
end = datetime(2002, 1, 1, 0, 0, 0, 0, pytz.utc)
# Load price data from yahoo.
data = load_from_yahoo(stocks=['PEP', 'KO'], indexes={},
start=start, end=end)
# Create and run the algorithm.
pairtrade = Pairtrade()
results = pairtrade.run(data)
# Plot the portfolio data.
analyze(results=results)
zipline/utils/cli.py
-6
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@@ -229,12 +229,6 @@ def run_pipeline(print_algo=True, **kwargs):
with open(algo_fname, 'r') as fd:
algo_text = fd.read()
analyze_fname = os.path.splitext(algo_fname)[0] + '_analyze.py'
if os.path.exists(analyze_fname):
with open(analyze_fname, 'r') as fd:
# Simply append
algo_text += fd.read()
if print_algo:
if PYGMENTS:
highlight(algo_text, PythonLexer(), TerminalFormatter(),