When the dts and length of cols are mismatched the writer behaves in
unintended ways. e.g. in a case where a consumer passed dts which had
minutes with no trades removed, but regular (market minute for day)
sized arrays for the data with `0`'s on minutes without trades, the non
trade minutes from cols are written to slots in the output where a trade
is intended.
Protect against this misuse by checking that all lengths are equal when
using the `write_cols` method.
Make a separate `_write_cols` method for use by both `write_cols` and
`write`, since the `write` method which takes a DataFrame has the
matched input length enforced by the DataFrame.
BUG: correctly create asset finder
MAINT: rename fixture
STY: fixes for flake8
STY: add space around assignment
MAINT: add var back to constructor
MAINT: remove unused import
MAINT: compare var with None directly
MAINT: fix merge errors
MAINT: remove record date - not needed.
MAINT: restructure dividends dataset.
MAINT: restructure dividends factors.
WIP: update dividends tests.
MAINT: correct the way to get the 'next' event frame.
Write arrays representing corresponding market opens and market closes,
which will eventually replace the `minute_index` field.
The market closes are being added for incoming work on another branch
which will use the market closes to generate a list of non-market
minutes to filter out when returning data from `unadjusted_window`.
- Use RestrictedDTypeMixin for dtype validation in
Filter/Factor/Classifier.
- Use new LatestMixin for Latest{Filter,Factor,Classifier} instead of
duplicating logic across all three.
- Always ignore return values in _validate.
- Consistently call super() first in validation mixins.
Classifiers are computations that represent grouping keys. They can be
used in conjuction with normalization functions like ``zscore`` or
``demean`` to perform normalizations over subsets of a dataset.
Notable changes:
- Added ``demean()`` and ``zscore()`` methods to ``Factor``.
- Added a classifier versions of ``Latest`` and ``CustomTermMixin``.
The .latest attribute of int64 dataset columns no produces a
classifier by default.
- Added ``Everything``, a classifier that maps all data to the same
value.
- Added ``zipline.lib.normalize``, which implements a naive, pure-Python
grouped normalize function. This will likely be moved to Cython in a
subsequent PR.
Allow comparisons like SomeFilter() & AssetExists().
Previously such comparisons would fail because & and | on Filters
explicitly checked that the other side of the operator was also a
Filter.
We now only enforce that the other side of the expression is a Term
with a dtype of bool_.
Eddie Hebert