refining the batch transform interface:

- removed use_panel
  - default for refresh_period is now 0
  - refresh_period will only affect the recreation of the datapanel
  - user's transform method is invoked on every call to batch transform

zipline/test_algorithms.py

@@ -342,12 +342,6 @@ class BatchTransformAlgorithm(TradingAlgorithm):
             clean_nans=True
         )
 
-        self.return_ticks = return_data(
-            refresh_period=self.refresh_period,
-            window_length=self.window_length,
-            create_panel=False
-        )
-
         self.return_not_full = return_data(
             refresh_period=0,
             window_length=self.window_length,
@@ -372,8 +366,6 @@ class BatchTransformAlgorithm(TradingAlgorithm):
         self.history_return_args.append(
             self.return_args_batch.handle_data(
                 data, *self.args, **self.kwargs))
-        self.history_return_ticks.append(
-            self.return_ticks.handle_data(data))
         self.history_return_not_full.append(
             self.return_not_full.handle_data(data))
         self.uses_ufunc.handle_data(data)

zipline/transforms/utils.py

@@ -313,7 +313,7 @@ class BatchTransform(EventWindow):
 
     def __init__(self,
                  func=None,
-                 refresh_period=None,
+                 refresh_period=0,
                  window_length=None,
                  clean_nans=True,
                  sids=None,
@@ -368,6 +368,7 @@ class BatchTransform(EventWindow):
         self.window_length = window_length
         self.trading_days_since_update = 0
         self.trading_days_total = 0
+        self.window = None
 
         self.full = False
         self.last_dt = None
@@ -512,8 +513,14 @@ class BatchTransform(EventWindow):
 
         if self.updated:
             # Create new pandas panel
-            data = self.get_data()
-            self.cached = self.compute_transform_value(data, *args, **kwargs)
+            self.window = self.get_data()
+
+        if self.window:
+            self.cached = self.compute_transform_value(
+                self.window,
+                *args,
+                **kwargs
+            )
 
         return self.cached