mirror of
https://github.com/wassname/catalyst.git
synced 2026-06-29 21:24:16 +08:00
jfkirk
116 lines
3.4 KiB
Python
116 lines
3.4 KiB
Python
"""
|
|
Base class for FFC unit tests.
|
|
"""
|
|
from functools import wraps
|
|
from unittest import TestCase
|
|
|
|
from numpy import arange, prod
|
|
from numpy.random import randn, seed as random_seed
|
|
from pandas import date_range, Int64Index, DataFrame
|
|
from six import iteritems
|
|
|
|
from zipline.finance.trading import TradingEnvironment
|
|
from zipline.modelling.engine import SimpleFFCEngine
|
|
from zipline.modelling.graph import TermGraph
|
|
from zipline.utils.test_utils import make_simple_asset_info, ExplodingObject
|
|
from zipline.utils.tradingcalendar import trading_day
|
|
|
|
|
|
def with_defaults(**default_funcs):
|
|
"""
|
|
Decorator for providing dynamic default values for a method.
|
|
|
|
Usages:
|
|
|
|
@with_defaults(foo=lambda self: self.x + self.y)
|
|
def func(self, foo):
|
|
...
|
|
|
|
If a value is passed for `foo`, it will be used. Otherwise the function
|
|
supplied to `with_defaults` will be called with `self` as an argument.
|
|
"""
|
|
def decorator(f):
|
|
@wraps(f)
|
|
def method(self, *args, **kwargs):
|
|
for name, func in iteritems(default_funcs):
|
|
if name not in kwargs:
|
|
kwargs[name] = func(self)
|
|
return f(self, *args, **kwargs)
|
|
return method
|
|
return decorator
|
|
|
|
|
|
with_default_shape = with_defaults(shape=lambda self: self.default_shape)
|
|
|
|
|
|
class BaseFFCTestCase(TestCase):
|
|
|
|
def setUp(self):
|
|
self.__calendar = date_range('2014', '2015', freq=trading_day)
|
|
self.__assets = assets = Int64Index(arange(1, 20))
|
|
|
|
# Set up env for test
|
|
env = TradingEnvironment()
|
|
env.write_data(
|
|
equities_df=make_simple_asset_info(
|
|
assets,
|
|
self.__calendar[0],
|
|
self.__calendar[-1],
|
|
))
|
|
self.__finder = env.asset_finder
|
|
self.__mask = self.__finder.lifetimes(self.__calendar[-10:])
|
|
|
|
@property
|
|
def default_shape(self):
|
|
"""Default shape for methods that build test data."""
|
|
return self.__mask.shape
|
|
|
|
def run_terms(self, terms, initial_workspace, mask=None):
|
|
"""
|
|
Compute the given terms, seeding the workspace of our FFCEngine with
|
|
`initial_workspace`.
|
|
|
|
Parameters
|
|
----------
|
|
terms : dict
|
|
Mapping from termname -> term object.
|
|
|
|
Returns
|
|
-------
|
|
results : dict
|
|
Mapping from termname -> computed result.
|
|
"""
|
|
engine = SimpleFFCEngine(
|
|
ExplodingObject(),
|
|
self.__calendar,
|
|
self.__finder,
|
|
)
|
|
mask = mask if mask is not None else self.__mask
|
|
return engine.compute_chunk(TermGraph(terms), mask, initial_workspace)
|
|
|
|
def build_mask(self, array):
|
|
ndates, nassets = array.shape
|
|
return DataFrame(
|
|
array,
|
|
# Use the **last** N dates rather than the first N so that we have
|
|
# space for lookbacks.
|
|
index=self.__calendar[-ndates:],
|
|
columns=self.__assets[:nassets],
|
|
dtype=bool,
|
|
)
|
|
|
|
@with_default_shape
|
|
def arange_data(self, shape, dtype=float):
|
|
"""
|
|
Build a block of testing data from numpy.arange.
|
|
"""
|
|
return arange(prod(shape), dtype=dtype).reshape(shape)
|
|
|
|
@with_default_shape
|
|
def randn_data(self, seed, shape):
|
|
"""
|
|
Build a block of testing data from numpy.random.randn.
|
|
"""
|
|
random_seed(seed)
|
|
return randn(*shape)
|