Debugging.

tests/test_optimize.py

@@ -50,8 +50,7 @@ class TestUpDown(TestCase):
 
         algo, config = create_predictable_zipline(
             self.zipline_test_config,
-            offset=0,
-            simulate=False
+            offset=0
         )
 
         #extract arguments
@@ -74,7 +73,9 @@ class TestUpDown(TestCase):
             "Minimum price does not equal expected maximum price."
         )
 
-        algo.run(config['trade_source'])
+        stats = algo.run(config['trade_source'])
+
+        self.assertTrue(len(stats) != 0)
 
         orders = np.asarray(algo.orders)
         max_order_idx = np.where(orders==orders.max())[0]
@@ -93,6 +94,8 @@ class TestUpDown(TestCase):
             "Algorithm did not sell when price was going to increase."
         )
 
+        from nose.tools import set_trace; set_trace()
+
 #    @skip
     def test_concavity_of_returns(self):
         """verify concave relationship between free parameter and
@@ -110,12 +113,15 @@ class TestUpDown(TestCase):
         compound_returns = np.empty(len(test_offsets))
         ziplines = []
         for i, offset in enumerate(test_offsets):
-            zipline, config = create_predictable_zipline(
+            algo, config = create_predictable_zipline(
                 self.zipline_test_config,
                 offset=offset,
             )
-            ziplines.append(zipline)
-            compound_returns[i] = zipline.get_cumulative_performance()['returns']
+            results = algo.run(config['trade_source'])
+            ziplines.append(algo)
+
+            compound_returns[i] = results.returns.sum()
+
 
         self.assertTrue(np.all(compound_returns[supposed_max] > compound_returns[np.logical_not(supposed_max)]),
             "Maximum compound returns are not where they are supposed to be."

zipline/gens/tradesimulation.py

@@ -109,12 +109,12 @@ class TradeSimulationClient(object):
             yield message
 
 class AlgorithmSimulator(object):
-    
+
     def __init__(self,
                  order_book,
                  algo,
                  algo_start):
-        
+
         # ==========
         # Algo Setup
         # ==========
@@ -205,7 +205,7 @@ class AlgorithmSimulator(object):
         # simulator so that it can fill the placed order when it
         # receives its next message.
         self.order_book.place_order(order)
-        
+
     def transform(self, stream_in):
         """
         Main generator work loop.
@@ -266,7 +266,7 @@ class AlgorithmSimulator(object):
                         del event['perf_message']
 
                         self.update_universe(event)
-                        
+
                     # Send the current state of the universe to the user's algo.
                     self.simulate_snapshot(date)
 
@@ -289,7 +289,7 @@ class AlgorithmSimulator(object):
         # Needs to be set so that we inject the proper date into algo
         # log/print lines.
         self.snapshot_dt = date
-        
+
         start_tic = datetime.now()
         with self.heartbeat_monitor:
             self.algo.handle_data(self.universe)

zipline/optimize/algorithms.py

@@ -73,7 +73,7 @@ class TradingAlgorithm(object):
         assert hasattr(self, 'source'), 'source not set.'
         assert hasattr(self, 'sids'), "sids not set."
 
-        environment = create_trading_environment()
+        environment = create_trading_environment(start=self.data.index[0], end=self.data.index[-1])
 
         # Create transforms by wrapping them into StatefulTransforms
         transforms = []
@@ -118,11 +118,16 @@ class TradingAlgorithm(object):
 
     def run(self, data, compute_risk_metrics=False):
         self.source = DataFrameSource(data, sids=self.sids)
-
+        self.data = data
         self._setup(compute_risk_metrics=compute_risk_metrics)
 
         # drain simulated_trading
-        perfs = list(self.simulated_trading)
+        perfs = []
+        for perf in self.simulated_trading:
+            from nose.tools import set_trace; set_trace()
+            perfs.append(perf)
+
+        #perfs = list(self.simulated_trading)
 
         daily_stats = self._create_daily_stats(perfs)
         return daily_stats
@@ -187,3 +192,4 @@ class BuySellAlgorithmNew(TradingAlgorithm):
 
         self.frame_count += 1
         self.incr += 1
+        from nose.tools import set_trace; set_trace()

zipline/optimize/factory.py

@@ -42,7 +42,7 @@ def create_updown_trade_source(sid, trade_count, trading_environment, base_price
     price = base_price-amplitude/2.
 
     cur = trading_environment.first_open
-    one_day = timedelta(minutes = 1)#days = 1)
+    one_day = timedelta(days = 1)
 
     #create iterator to cycle through up and down phases
     change = cycle([1,-1])
@@ -60,7 +60,7 @@ def create_updown_trade_source(sid, trade_count, trading_environment, base_price
     return df
 
 
-def create_predictable_zipline(config, offset=0, simulate=True):
+def create_predictable_zipline(config, offset=0):
     """Create a test zipline object as specified by config. The
     zipline will use the UpDown tradesource which is perfectly
     predictable.
@@ -118,10 +118,6 @@ def create_predictable_zipline(config, offset=0, simulate=True):
     config['trade_source'] = source
     config['environment'] = trading_environment
     config['simulation_style'] = SIMULATION_STYLE.FIXED_SLIPPAGE
-    config['devel'] = True
-
-    if simulate:
-        algorithm.run()
 
     return algorithm, config
 

zipline/utils/factory.py

@@ -55,12 +55,15 @@ def load_market_data():
 
     return bm_returns, tr_curves
 
-def create_trading_environment(year=2006):
+def create_trading_environment(year=2006, start=None, end=None):
     """Construct a complete environment with reasonable defaults"""
     benchmark_returns, treasury_curves = load_market_data()
 
-    start = datetime(year, 1, 1, tzinfo=pytz.utc)
-    end   = datetime(year, 12, 31, tzinfo=pytz.utc)
+    if start is None:
+        start = datetime(year, 1, 1, tzinfo=pytz.utc)
+    if end is None:
+        end   = datetime(year, 12, 31, tzinfo=pytz.utc)
+
     trading_environment = TradingEnvironment(
         benchmark_returns,
         treasury_curves,