* BLD: Try github actions again
* new requirements for p36
* fix code different across numpy versions
* silence the correct warnings for tests to run
* MAINT: Use loc instead of deprecated ix
* comment out windows for now
Co-authored-by: Richard Frank <rich@quantopian.com>
Avoid making an extra copy of non-C-contiguous arrays when factorizing inputs
to LabelArray. This requires taking care to ensure that we use the same memory
order both when ravelling and unravelling the input arrays.
- Adds a `map` method to `LabelArray` that maps a unary function over
the categories of a LabelArray, shrinking the underyling codes if
possible.
- Adds a new `.relabel` method to string-dtype classifiers that maps a
unary function over the unique elements of the underlying LabelArray.
This is useful for things like cleaning noisy label data.
- Fixes a bug where __setitem__ was not called when setting with a slice
on Python 2 (__setslice__ was called instead), which caused strange
behavior when setting an empty string. This is fixed by overriding
__setslice__ and forwarding to __setitem__.
- Fixes a bug where __getitem__ returned an instance of np.void when
returning a scalar. We now correctly return an entry from our
categoricals.
- Adds a new class, ``LabelArray``, which is a subclass of np.ndarray.
LabelArray is conceptually similar to pandas.Categorical, in that it
stores data with many duplicate values as indices into an array of
unique values. For string data with many duplicates (e.g. time-series
of tickers or or industry classifications), this provides multiple
orders of magnitude of improvement when doing string operations,
especially string comparison/matching operations.
- Adds a new generic object "specialization" for `AdjustedArrayWindow`,
and a corresponding ObjectOverwrite adjustment.
- Adds a new ``postprocess`` method to ``zipline.pipeline.term.Term``.
This method is called on the final result of any pipeline expression
after screen filtering has occurred. The default implementation of
``postprocess`` is identity, but Classifier overrides it to coerce
string columns into pandas.Categoricals before presenting them to the
user.
