Merge addition of unit tests that exercise examples.

Also, multiple fixes to examples that the unit tests uncovered.

etc/requirements_dev.txt

@@ -12,3 +12,7 @@ pyflakes==0.6.1
 # Documentation Conversion
 
 pyandoc==0.0.1
+
+# Example scripts that are run during unit tests use the following:
+
+matplotlib==1.2.1

tests/test_examples.py

@@ -0,0 +1,54 @@
+#
+# Copyright 2013 Quantopian, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# This code is based on a unittest written by John Salvatier:
+# https://github.com/pymc-devs/pymc/blob/pymc3/tests/test_examples.py
+
+# Disable plotting
+#
+import matplotlib
+matplotlib.use('Agg')
+
+from os import path
+import os
+import fnmatch
+import imp
+
+
+def test_examples():
+    os.chdir(example_dir())
+    for fname in all_matching_files('.', '*.py'):
+        yield check_example, fname
+
+
+def all_matching_files(d, pattern):
+    def addfiles(fls, dir, nfiles):
+        nfiles = fnmatch.filter(nfiles, pattern)
+        nfiles = [path.join(dir, f) for f in nfiles]
+        fls.extend(nfiles)
+
+    files = []
+    path.walk(d, addfiles, files)
+    return files
+
+
+def example_dir():
+    import zipline
+    d = path.dirname(zipline.__file__)
+    return path.join(path.abspath(d), 'examples/')
+
+
+def check_example(p):
+    imp.load_source('__main__', path.basename(p))

zipline/examples/buyapple.py

@@ -15,6 +15,8 @@
 # limitations under the License.
 
 import matplotlib.pyplot as plt
+from datetime import datetime
+import pytz
 
 from zipline.algorithm import TradingAlgorithm
 from zipline.utils.factory import load_from_yahoo
@@ -29,8 +31,15 @@ class BuyApple(TradingAlgorithm):  # inherit from TradingAlgorithm
 
 
 if __name__ == '__main__':
-    data = load_from_yahoo(stocks=['AAPL'], indexes={})
+    start = datetime(2008, 1, 1, 0, 0, 0, 0, pytz.utc)
+    end = datetime(2010, 1, 1, 0, 0, 0, 0, pytz.utc)
+    data = load_from_yahoo(stocks=['AAPL'], indexes={}, start=start,
+                           end=end)
     simple_algo = BuyApple()
     results = simple_algo.run(data)
-    results.portfolio_value.plot()
+
+    ax1 = plt.subplot(211)
+    results.portfolio_value.plot(ax=ax1)
+    ax2 = plt.subplot(212, sharex=ax1)
+    data.AAPL.plot(ax=ax2)
     plt.show()

zipline/examples/dual_moving_average.py

@@ -20,6 +20,9 @@ from zipline.algorithm import TradingAlgorithm
 from zipline.transforms import MovingAverage
 from zipline.utils.factory import load_from_yahoo
 
+from datetime import datetime
+import pytz
+
 
 class DualMovingAverage(TradingAlgorithm):
     """Dual Moving Average Crossover algorithm.
@@ -30,7 +33,7 @@ class DualMovingAverage(TradingAlgorithm):
     momentum).
 
     """
-    def initialize(self, short_window=200, long_window=400):
+    def initialize(self, short_window=20, long_window=40):
         # Add 2 mavg transforms, one with a long window, one
         # with a short window.
         self.add_transform(MovingAverage, 'short_mavg', ['price'],
@@ -63,16 +66,20 @@ class DualMovingAverage(TradingAlgorithm):
                     sell=self.sell)
 
 if __name__ == '__main__':
-    data = load_from_yahoo(stocks=['AAPL'], indexes={})
+    start = datetime(1990, 1, 1, 0, 0, 0, 0, pytz.utc)
+    end = datetime(1991, 1, 1, 0, 0, 0, 0, pytz.utc)
+    data = load_from_yahoo(stocks=['AAPL'], indexes={}, start=start,
+                           end=end)
+
     dma = DualMovingAverage()
     results = dma.run(data)
-    print results.short_mavg
+
     fig = plt.figure()
-    ax1 = fig.add_subplot(211)
+    ax1 = fig.add_subplot(211, ylabel='portfolio value')
     results.portfolio_value.plot(ax=ax1)
 
     ax2 = fig.add_subplot(212)
-    data['AAPL'].plot(ax=ax2)
+    data['AAPL'].plot(ax=ax2, color='r')
     results[['short_mavg', 'long_mavg']].plot(ax=ax2)
 
     ax2.plot(results.ix[results.buy].index, results.short_mavg[results.buy],

zipline/examples/olmar.py

@@ -1,12 +1,13 @@
 import sys
 import logbook
-import datetime
 import numpy as np
+from datetime import datetime
+import pytz
 
 from zipline.algorithm import TradingAlgorithm
 from zipline.transforms import MovingAverage
-from zipline.utils.factory import load_bars_from_yahoo
-from zipline.finance import slippage, commission
+from zipline.utils.factory import load_from_yahoo
+from zipline.finance import commission
 
 zipline_logging = logbook.NestedSetup([
     logbook.NullHandler(level=logbook.DEBUG, bubble=True),
@@ -38,11 +39,6 @@ class OLMAR(TradingAlgorithm):
         self.add_transform(MovingAverage, 'mavg', ['price'],
                            window_length=window_length)
 
-        no_delay = datetime.timedelta(minutes=0)
-        slip = slippage.VolumeShareSlippage(volume_limit=0.25,
-                                            price_impact=0,
-                                            delay=no_delay)
-        self.set_slippage(slip)
         self.set_commission(commission.PerShare(cost=0))
 
     def handle_data(self, data):
@@ -157,7 +153,11 @@ def simplex_projection(v, b=1):
 
 if __name__ == '__main__':
     import pylab as pl
-    data = load_bars_from_yahoo(stocks=STOCKS, indexes={})
+    start = datetime(2004, 1, 1, 0, 0, 0, 0, pytz.utc)
+    end = datetime(2008, 1, 1, 0, 0, 0, 0, pytz.utc)
+    data = load_from_yahoo(stocks=STOCKS, indexes={}, start=start,
+                           end=end)
+    data = data.dropna()
     olmar = OLMAR()
     results = olmar.run(data)
     results.portfolio_value.plot()

zipline/examples/pairtrade.py

@@ -17,6 +17,8 @@
 import matplotlib.pyplot as plt
 import numpy as np
 import statsmodels.api as sm
+from datetime import datetime
+import pytz
 
 from zipline.algorithm import TradingAlgorithm
 from zipline.transforms import batch_transform
@@ -29,7 +31,7 @@ def ols_transform(data, sid1, sid2):
     via Ordinary Least Squares between two SIDs.
     """
     p0 = data.price[sid1]
-    p1 = sm.add_constant(data.price[sid2])
+    p1 = sm.add_constant(data.price[sid2], prepend=True)
     slope, intercept = sm.OLS(p0, p1).fit().params
 
     return slope, intercept
@@ -53,7 +55,6 @@ class Pairtrade(TradingAlgorithm):
 
     def initialize(self, window_length=100):
         self.spreads = []
-        self.zscores = []
         self.invested = 0
         self.window_length = window_length
         self.ols_transform = ols_transform(refresh_period=self.window_length,
@@ -65,12 +66,12 @@ class Pairtrade(TradingAlgorithm):
         params = self.ols_transform.handle_data(data, 'PEP', 'KO')
         if params is None:
             return
-        slope, intercept = params
+        intercept, slope = params
 
         ######################################################
         # 2. Compute spread and zscore
         zscore = self.compute_zscore(data, slope, intercept)
-        self.zscores.append(zscore)
+        self.record(zscores=zscore)
 
         ######################################################
         # 3. Place orders
@@ -112,12 +113,14 @@ class Pairtrade(TradingAlgorithm):
         self.order('PEP', -1 * pep_amount)
 
 if __name__ == '__main__':
-    data = load_from_yahoo(stocks=['PEP', 'KO'], indexes={})
+    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
-    data.spreads[pairtrade.window_length:] = pairtrade.spreads
 
     ax1 = plt.subplot(211)
     data[['PEP', 'KO']].plot(ax=ax1)
@@ -125,7 +128,7 @@ if __name__ == '__main__':
     plt.setp(ax1.get_xticklabels(), visible=False)
 
     ax2 = plt.subplot(212, sharex=ax1)
-    data.spreads.plot(ax=ax2, color='r')
-    plt.ylabel('spread')
+    results.zscores.plot(ax=ax2, color='r')
+    plt.ylabel('zscored spread')
 
     plt.show()

zipline/finance/performance.py

@@ -622,7 +622,9 @@ class PerformancePeriod(object):
 
     def update_last_sale(self, event):
         is_trade = event.type == zp.DATASOURCE_TYPE.TRADE
-        if event.sid in self.positions and is_trade:
+        has_price = not np.isnan(event.price)
+        # isnan check will keep the last price if its not present
+        if (event.sid in self.positions) and is_trade and has_price:
             self.positions[event.sid].last_sale_price = event.price
             index = self.index_for_position(event.sid)
             self._position_last_sale_prices[index] = event.price