Files
catalyst/zipline/utils/data.py
T
Joe Jevnik 8df1a49031 BUG: When increasing the length dynamically, the rolling panel was
getting filled with the wrong datetimes and causing errors.

Updates the logic for addressing missing datetimes and adds unit tests
for the 2 main cases (no missing datetimes, and some missing datetimes).
2014-11-11 13:29:57 -05:00

322 lines
10 KiB
Python

#
# 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.
import numpy as np
import pandas as pd
from copy import deepcopy
def _ensure_index(x):
if not isinstance(x, pd.Index):
x = pd.Index(sorted(x))
return x
class RollingPanel(object):
"""
Preallocation strategies for rolling window over expanding data set
Restrictions: major_axis can only be a DatetimeIndex for now
"""
def __init__(self,
window,
items,
sids,
cap_multiple=2,
dtype=np.float64,
date_buf=None):
self._pos = window
self._window = window
self.items = _ensure_index(items)
self.minor_axis = _ensure_index(sids)
self.cap_multiple = cap_multiple
self.dtype = dtype
self.date_buf = np.empty(self.cap, dtype='M8[ns]') \
if date_buf is None else date_buf
self.buffer = self._create_buffer()
@property
def cap(self):
return self.cap_multiple * self._window
@property
def start_index(self):
return self._pos - self._window
@property
def start_date(self):
return self.date_buf[self.start_index]
def oldest_frame(self):
"""
Get the oldest frame in the panel.
"""
return self.buffer.iloc[:, self.start_index, :]
def set_minor_axis(self, minor_axis):
self.minor_axis = _ensure_index(minor_axis)
self.buffer = self.buffer.reindex(minor_axis=self.minor_axis)
def set_items(self, items):
self.items = _ensure_index(items)
self.buffer = self.buffer.reindex(items=self.items)
def _create_buffer(self):
panel = pd.Panel(
items=self.items,
minor_axis=self.minor_axis,
major_axis=range(self.cap),
dtype=self.dtype,
)
return panel
def extend_back(self, missing_dts):
"""
Resizes the buffer to hold a new window with a new cap_multiple.
If cap_multiple is None, then the old cap_multiple is used.
"""
delta = len(missing_dts)
if not delta:
raise ValueError(
'missing_dts must be a non-empty index',
)
self._window += delta
self._pos += delta
self.date_buf = self.date_buf.copy()
self.date_buf.resize(self.cap)
self.date_buf = np.roll(self.date_buf, delta)
self.buffer = pd.concat(
[
pd.Panel(
items=self.items,
minor_axis=self.minor_axis,
major_axis=np.arange(delta * self.cap_multiple),
dtype=self.dtype,
),
self.buffer
],
axis=1,
)
self.buffer.major_axis = pd.Int64Index(range(self.cap))
# Fill the delta with the dates we calculated.
where = slice(self.start_index, self.start_index + delta)
self.date_buf[where] = missing_dts
def add_frame(self, tick, frame):
"""
"""
if self._pos == self.cap:
self._roll_data()
self.buffer.loc[:, self._pos, :] = frame.T.astype(self.dtype)
self.date_buf[self._pos] = tick
self._pos += 1
def get_current(self):
"""
Get a Panel that is the current data in view. It is not safe to persist
these objects because internal data might change
"""
where = slice(self.start_index, self._pos)
major_axis = pd.DatetimeIndex(deepcopy(self.date_buf[where]), tz='utc')
return pd.Panel(self.buffer.values[:, where, :], self.items,
major_axis, self.minor_axis, dtype=self.dtype)
def set_current(self, panel):
"""
Set the values stored in our current in-view data to be values of the
passed panel. The passed panel must have the same indices as the panel
that would be returned by self.get_current.
"""
where = slice(self.start_index, self._pos)
self.buffer.values[:, where, :] = panel.values
def current_dates(self):
where = slice(self.start_index, self._pos)
return pd.DatetimeIndex(deepcopy(self.date_buf[where]), tz='utc')
def _roll_data(self):
"""
Roll window worth of data up to position zero.
Save the effort of having to expensively roll at each iteration
"""
self.buffer.values[:, :self._window, :] = \
self.buffer.values[:, -self._window:, :]
self.date_buf[:self._window] = self.date_buf[-self._window:]
self._pos = self._window
@property
def window_length(self):
return self._window
class MutableIndexRollingPanel(object):
"""
A version of RollingPanel that exists for backwards compatibility with
batch_transform. This is a copy to allow behavior of RollingPanel to drift
away from this without breaking this class.
This code should be considered frozen, and should not be used in the
future. Instead, see RollingPanel.
"""
def __init__(self, window, items, sids, cap_multiple=2, dtype=np.float64):
self._pos = 0
self._window = window
self.items = _ensure_index(items)
self.minor_axis = _ensure_index(sids)
self.cap_multiple = cap_multiple
self.cap = cap_multiple * window
self.dtype = dtype
self.date_buf = np.empty(self.cap, dtype='M8[ns]')
self.buffer = self._create_buffer()
def _oldest_frame_idx(self):
return max(self._pos - self._window, 0)
def oldest_frame(self):
"""
Get the oldest frame in the panel.
"""
return self.buffer.iloc[:, self._oldest_frame_idx(), :]
def set_sids(self, sids):
self.minor_axis = _ensure_index(sids)
self.buffer = self.buffer.reindex(minor_axis=self.minor_axis)
def _create_buffer(self):
panel = pd.Panel(
items=self.items,
minor_axis=self.minor_axis,
major_axis=range(self.cap),
dtype=self.dtype,
)
return panel
def get_current(self):
"""
Get a Panel that is the current data in view. It is not safe to persist
these objects because internal data might change
"""
where = slice(self._oldest_frame_idx(), self._pos)
major_axis = pd.DatetimeIndex(deepcopy(self.date_buf[where]), tz='utc')
return pd.Panel(self.buffer.values[:, where, :], self.items,
major_axis, self.minor_axis, dtype=self.dtype)
def set_current(self, panel):
"""
Set the values stored in our current in-view data to be values of the
passed panel. The passed panel must have the same indices as the panel
that would be returned by self.get_current.
"""
where = slice(self._oldest_frame_idx(), self._pos)
self.buffer.values[:, where, :] = panel.values
def current_dates(self):
where = slice(self._oldest_frame_idx(), self._pos)
return pd.DatetimeIndex(deepcopy(self.date_buf[where]), tz='utc')
def _roll_data(self):
"""
Roll window worth of data up to position zero.
Save the effort of having to expensively roll at each iteration
"""
self.buffer.values[:, :self._window, :] = \
self.buffer.values[:, -self._window:, :]
self.date_buf[:self._window] = self.date_buf[-self._window:]
self._pos = self._window
def add_frame(self, tick, frame):
"""
"""
if self._pos == self.cap:
self._roll_data()
if set(frame.columns).difference(set(self.minor_axis)) or \
set(frame.index).difference(set(self.items)):
self._update_buffer(frame)
self.buffer.loc[:, self._pos, :] = frame.T.astype(self.dtype)
self.date_buf[self._pos] = tick
self._pos += 1
def _update_buffer(self, frame):
# Get current frame as we only need to care about the data that is in
# the active window
old_buffer = self.get_current()
if self._pos >= self._window:
# Don't count the last major_axis entry if we're past our window,
# since it's about to roll off the end of the panel.
old_buffer = old_buffer.iloc[:, 1:, :]
nans = pd.isnull(old_buffer)
# Find minor_axes that have only nans
# Note that minor is axis 2
non_nan_cols = set(old_buffer.minor_axis[~np.all(nans, axis=(0, 1))])
# Determine new columns to be added
new_cols = set(frame.columns).difference(non_nan_cols)
# Update internal minor axis
self.minor_axis = _ensure_index(new_cols.union(non_nan_cols))
# Same for items (fields)
# Find items axes that have only nans
# Note that items is axis 0
non_nan_items = set(old_buffer.items[~np.all(nans, axis=(1, 2))])
new_items = set(frame.index).difference(non_nan_items)
self.items = _ensure_index(new_items.union(non_nan_items))
# :NOTE:
# There is a simpler and 10x faster way to do this:
#
# Reindex buffer to update axes (automatically adds nans)
# self.buffer = self.buffer.reindex(items=self.items,
# major_axis=np.arange(self.cap),
# minor_axis=self.minor_axis)
#
# However, pandas==0.12.0, for which we remain backwards compatible,
# has a bug in .reindex() that this triggers. Using .update() as before
# seems to work fine.
new_buffer = self._create_buffer()
new_buffer.update(
self.buffer.loc[non_nan_items, :, non_nan_cols])
self.buffer = new_buffer