mirror of
https://github.com/wassname/catalyst.git
synced 2026-06-30 16:11:42 +08:00
Eddie Hebert
b3efb5eb69
Now that ndict is no longer used in any part of the system during a backtest, remove all remaining references in tests, etc.
124 lines
4.0 KiB
Python
124 lines
4.0 KiB
Python
#
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# Copyright 2013 Quantopian, Inc.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from collections import defaultdict
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from math import sqrt
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from zipline.errors import WrongDataForTransform
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from zipline.transforms.utils import EventWindow, TransformMeta
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import zipline.utils.math_utils as zp_math
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class MovingStandardDev(object):
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"""
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Class that maintains a dictionary from sids to
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MovingStandardDevWindows. For each sid, we maintain a the
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standard deviation of all events falling within the specified
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window.
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"""
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__metaclass__ = TransformMeta
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def __init__(self, market_aware=True, window_length=None, delta=None):
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self.market_aware = market_aware
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self.delta = delta
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self.window_length = window_length
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# Market-aware mode only works with full-day windows.
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if self.market_aware:
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assert self.window_length and not self.delta,\
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"Market-aware mode only works with full-day windows."
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# Non-market-aware mode requires a timedelta.
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else:
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assert self.delta and not self.window_length, \
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"Non-market-aware mode requires a timedelta."
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# No way to pass arguments to the defaultdict factory, so we
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# need to define a method to generate the correct EventWindows.
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self.sid_windows = defaultdict(self.create_window)
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def create_window(self):
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"""
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Factory method for self.sid_windows.
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"""
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return MovingStandardDevWindow(
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self.market_aware,
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self.window_length,
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self.delta
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)
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def update(self, event):
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"""
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Update the event window for this event's sid. Return a dict
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from tracked fields to moving averages.
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"""
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# This will create a new EventWindow if this is the first
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# message for this sid.
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window = self.sid_windows[event.sid]
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window.update(event)
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return window.get_stddev()
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def assert_required_fields(self, event):
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"""
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We only allow events with a price field to be run through
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the returns transform.
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"""
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if 'price' not in event:
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raise WrongDataForTransform(
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transform="StdDevEventWindow",
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fields='price')
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class MovingStandardDevWindow(EventWindow):
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"""
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Iteratively calculates standard deviation for a particular sid
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over a given time window. The expected functionality of this
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class is to be instantiated inside a MovingStandardDev.
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"""
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def __init__(self, market_aware=True, window_length=None, delta=None):
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# Call the superclass constructor to set up base EventWindow
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# infrastructure.
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EventWindow.__init__(self, market_aware, window_length, delta)
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self.sum = 0.0
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self.sum_sqr = 0.0
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def handle_add(self, event):
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self.sum += event.price
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self.sum_sqr += event.price ** 2
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def handle_remove(self, event):
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self.sum -= event.price
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self.sum_sqr -= event.price ** 2
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def get_stddev(self):
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# Sample standard deviation is undefined for a single event or
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# no events.
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if len(self) <= 1:
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return None
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else:
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average = self.sum / len(self)
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s_squared = (self.sum_sqr - self.sum * average) \
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/ (len(self) - 1)
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if zp_math.tolerant_equals(0, s_squared):
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return 0.0
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stddev = sqrt(s_squared)
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return stddev
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