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MAINT: incorporate string support

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STY: remove unused imports

MAINT: change dtype to object for compatibility with python3

MAINT: rename pipeline columns and constants for clarity

MAINT: rename column
This commit is contained in:
Maya Tydykov
2016-05-03 14:23:20 -04:00
parent 3d521561f5
commit 6b60e447a0
13 changed files with 185 additions and 143 deletions
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tests/pipeline/test_13d_filings.py
+33 -31
View File
@@ -17,16 +17,17 @@ from zipline.pipeline.data import _13DFilings
from zipline.pipeline.factors.events import BusinessDaysSince13DFilingsDate
from zipline.pipeline.loaders._13d_filings import _13DFilingsLoader
from zipline.pipeline.loaders.utils import (
get_values_for_date_ranges,
zip_with_floats,
zip_with_dates
)
from zipline.testing.fixtures import WithPipelineEventDataLoader
from zipline.testing.fixtures import ZiplineTestCase
date_intervals = [[None, '2014-01-04'],
['2014-01-05', '2014-01-09'],
['2014-01-10', None]]
date_intervals = [
[['2014-01-01', '2014-01-04'],
['2014-01-05', '2014-01-09'],
['2014-01-10', '2014-01-31']]
]
empty_df = pd.DataFrame(
columns=[NUM_SHARES,
@@ -40,7 +41,7 @@ empty_df[PERCENT_SHARES] = empty_df[PERCENT_SHARES].astype('float')
empty_df[TS_FIELD_NAME] = empty_df[TS_FIELD_NAME].astype('datetime64[ns]')
empty_df[DISCLOSURE_DATE] = empty_df[DISCLOSURE_DATE].astype('datetime64[ns]')
_13d_filngs_cases = [
_13d_filings_cases = [
pd.DataFrame({
NUM_SHARES: [1, 15],
PERCENT_SHARES: [10, 20],
@@ -51,19 +52,6 @@ _13d_filngs_cases = [
]
def get_expected_previous_values(zip_date_index_with_vals,
vals,
date_intervals,
dates):
return pd.DataFrame({
0: get_values_for_date_ranges(zip_date_index_with_vals,
vals,
date_intervals,
dates),
1: zip_date_index_with_vals(dates, ['NaN'] * len(dates)),
}, index=dates)
class _13DFilingsLoaderTestCase(WithPipelineEventDataLoader,
ZiplineTestCase):
"""
@@ -88,23 +76,37 @@ class _13DFilingsLoaderTestCase(WithPipelineEventDataLoader,
def get_dataset(cls):
return {sid: frame
for sid, frame
in enumerate(_13d_filngs_cases)}
in enumerate(_13d_filings_cases)}
loader_type = _13DFilingsLoader
def setup(self, dates):
cols = {}
cols[
PREVIOUS_DISCLOSURE_DATE
] = get_expected_previous_values(zip_with_dates,
['NaT', '2014-01-04', '2014-01-09'],
date_intervals, dates)
cols[PREVIOUS_NUM_SHARES] = get_expected_previous_values(
zip_with_floats, ['NaN', 1, 15], date_intervals, dates
)
cols[PREVIOUS_PERCENT_SHARES] = get_expected_previous_values(
zip_with_floats, ['NaN', 10, 20], date_intervals, dates
)
cols = {
PREVIOUS_DISCLOSURE_DATE: self.get_sids_to_frames(
zip_with_dates,
[['NaT', '2014-01-04', '2014-01-09']],
date_intervals,
dates,
'datetime64[ns]',
'NaN'
),
PREVIOUS_NUM_SHARES: self.get_sids_to_frames(
zip_with_floats,
[['NaN', 1, 15]],
date_intervals,
dates,
'float',
'NaN'
),
PREVIOUS_PERCENT_SHARES: self.get_sids_to_frames(
zip_with_floats,
[['NaN', 10, 20]],
date_intervals,
dates,
'float',
'NaN'
)
}
cols[DAYS_SINCE_PREV_DISCLOSURE] = self._compute_busday_offsets(
cols[PREVIOUS_DISCLOSURE_DATE]
)
tests/pipeline/test_buyback_auth.py
+47 -43
View File
@@ -7,27 +7,27 @@ import pandas as pd
from six import iteritems
from zipline.pipeline.common import(
BUYBACK_AMOUNT_FIELD_NAME,
BUYBACK_ANNOUNCEMENT_FIELD_NAME,
BUYBACK_TYPE_FIELD_NAME,
BUYBACK_UNIT_FIELD_NAME,
DAYS_SINCE_PREV,
PREVIOUS_BUYBACK_AMOUNT,
PREVIOUS_BUYBACK_ANNOUNCEMENT,
PREVIOUS_BUYBACK_TYPE,
PREVIOUS_BUYBACK_UNIT,
SID_FIELD_NAME,
TS_FIELD_NAME,
VALUE_FIELD_NAME,
VALUE_TYPE_FIELD_NAME,
PREVIOUS_VALUE,
PREVIOUS_VALUE_TYPE,
PREVIOUS_BUYBACK_TYPE,
)
from zipline.pipeline.data import BuybackAuthorizations
from zipline.pipeline.factors.events import BusinessDaysSinceBuybackAuth
from zipline.pipeline.loaders.buyback_auth import BuybackAuthorizationsLoader
from zipline.pipeline.loaders.blaze import BlazeBuybackAuthorizationsLoader
from zipline.pipeline.loaders.utils import (
zip_with_floats,
zip_with_dates,
get_values_for_date_ranges,
zip_with_strs)
zip_with_floats,
zip_with_strs
)
from zipline.testing.fixtures import (
WithPipelineEventDataLoader, ZiplineTestCase
)
@@ -39,16 +39,16 @@ date_intervals = [
buyback_authorizations_cases = [
pd.DataFrame({
VALUE_FIELD_NAME: [1, 15],
VALUE_TYPE_FIELD_NAME: ["$M", "Mshares"],
BUYBACK_AMOUNT_FIELD_NAME: [1, 15],
BUYBACK_UNIT_FIELD_NAME: ["$M", "Mshares"],
BUYBACK_TYPE_FIELD_NAME: ["New", "Additional"],
TS_FIELD_NAME: pd.to_datetime(['2014-01-05', '2014-01-10']),
BUYBACK_ANNOUNCEMENT_FIELD_NAME: pd.to_datetime(['2014-01-04',
'2014-01-09'])
}),
pd.DataFrame(
columns=[VALUE_FIELD_NAME,
VALUE_TYPE_FIELD_NAME,
columns=[BUYBACK_AMOUNT_FIELD_NAME,
BUYBACK_UNIT_FIELD_NAME,
BUYBACK_TYPE_FIELD_NAME,
BUYBACK_ANNOUNCEMENT_FIELD_NAME,
TS_FIELD_NAME],
@@ -57,31 +57,19 @@ buyback_authorizations_cases = [
]
def get_expected_previous_values(zip_date_index_with_vals,
dates,
vals_for_date_intervals):
return pd.DataFrame({
0: get_values_for_date_ranges(zip_date_index_with_vals,
vals_for_date_intervals,
date_intervals,
dates),
1: zip_date_index_with_vals(dates, ['NaN'] * len(dates)),
}, index=dates)
class BuybackAuthLoaderTestCase(WithPipelineEventDataLoader, ZiplineTestCase):
"""
Test for cash buyback authorizations dataset.
"""
pipeline_columns = {
PREVIOUS_VALUE:
BuybackAuthorizations.previous_value.latest,
PREVIOUS_BUYBACK_AMOUNT:
BuybackAuthorizations.previous_amount.latest,
PREVIOUS_BUYBACK_ANNOUNCEMENT:
BuybackAuthorizations.previous_date.latest,
PREVIOUS_VALUE_TYPE:
BuybackAuthorizations.previous_value_type.latest,
PREVIOUS_BUYBACK_UNIT:
BuybackAuthorizations.previous_unit.latest,
PREVIOUS_BUYBACK_TYPE:
BuybackAuthorizations.previous_buyback_type.latest,
BuybackAuthorizations.previous_type.latest,
DAYS_SINCE_PREV:
BusinessDaysSinceBuybackAuth(),
}
@@ -100,23 +88,38 @@ class BuybackAuthLoaderTestCase(WithPipelineEventDataLoader, ZiplineTestCase):
def setup(self, dates):
cols = {
PREVIOUS_VALUE: self.get_sids_to_frames(zip_with_floats,
[['NaN', 1, 15]],
date_intervals,
dates),
PREVIOUS_BUYBACK_AMOUNT: self.get_sids_to_frames(zip_with_floats,
[['NaN', 1, 15]],
date_intervals,
dates,
'float',
'NaN'),
PREVIOUS_BUYBACK_ANNOUNCEMENT: self.get_sids_to_frames(
zip_with_dates,
[['NaT', '2014-01-04', '2014-01-09']],
date_intervals,
dates),
PREVIOUS_VALUE_TYPE: self.get_sids_to_frames(
zip_with_strs, [["", "$M", "Mshares"]], date_intervals, dates
dates,
'datetime64[ns]',
'NaN'
),
PREVIOUS_BUYBACK_UNIT: self.get_sids_to_frames(
zip_with_strs,
[[None, "$M", "Mshares"]],
date_intervals,
dates,
'category',
None
),
PREVIOUS_BUYBACK_TYPE: self.get_sids_to_frames(
zip_with_strs, [["", "New", "Additional"]], date_intervals,
dates
zip_with_strs,
[[None, "New", "Additional"]],
date_intervals,
dates,
'category',
None
)
}
cols[DAYS_SINCE_PREV] = self._compute_busday_offsets(
cols[PREVIOUS_BUYBACK_ANNOUNCEMENT]
)
@@ -137,10 +140,10 @@ class BlazeBuybackAuthLoaderTestCase(BuybackAuthLoaderTestCase):
pd.DataFrame({
BUYBACK_ANNOUNCEMENT_FIELD_NAME:
frame[BUYBACK_ANNOUNCEMENT_FIELD_NAME],
VALUE_FIELD_NAME:
frame[VALUE_FIELD_NAME],
VALUE_TYPE_FIELD_NAME:
frame[VALUE_TYPE_FIELD_NAME],
BUYBACK_AMOUNT_FIELD_NAME:
frame[BUYBACK_AMOUNT_FIELD_NAME],
BUYBACK_UNIT_FIELD_NAME:
frame[BUYBACK_UNIT_FIELD_NAME],
BUYBACK_TYPE_FIELD_NAME:
frame[BUYBACK_TYPE_FIELD_NAME],
TS_FIELD_NAME:
@@ -152,7 +155,8 @@ class BlazeBuybackAuthLoaderTestCase(BuybackAuthLoaderTestCase):
class BlazeBuybackAuthLoaderNotInteractiveTestCase(
BlazeBuybackAuthLoaderTestCase):
BlazeBuybackAuthLoaderTestCase
):
"""Test case for passing a non-interactive symbol and a dict of resources.
"""
def pipeline_event_loader_args(self, dates):
tests/pipeline/test_consensus_estimates.py
+9 -3
View File
@@ -301,8 +301,12 @@ class ConsensusEstimatesLoaderTestCase(WithNextAndPreviousEventDataLoader,
def setup(self, dates):
cols = {
PREVIOUS_RELEASE_DATE:
self.get_expected_previous_event_dates(dates),
NEXT_RELEASE_DATE: self.get_expected_next_event_dates(dates)
self.get_expected_previous_event_dates(
dates, 'datetime64[ns]', 'NaN'
),
NEXT_RELEASE_DATE: self.get_expected_next_event_dates(
dates, 'datetime64[ns]', 'NaN'
)
}
for field_name in field_name_to_expected_col:
cols[field_name] = self.get_sids_to_frames(
@@ -310,7 +314,9 @@ class ConsensusEstimatesLoaderTestCase(WithNextAndPreviousEventDataLoader,
self.prev_date_intervals
if field_name.startswith("previous")
else self.next_date_intervals,
dates
dates,
'float',
'NaN'
)
return cols
tests/pipeline/test_dividends.py
+18 -9
View File
@@ -206,10 +206,11 @@ class DividendsByAnnouncementDateTestCase(WithPipelineEventDataLoader,
amounts = [['NaN', 1, 15], ['NaN', 7, 13], ['NaN', 3, 1], ['NaN', 23]]
cols = {
PREVIOUS_ANNOUNCEMENT: self.get_sids_to_frames(
zip_with_dates, announcement_dates, date_intervals, dates
zip_with_dates, announcement_dates, date_intervals, dates,
'datetime64[ns]', 'NaN'
),
PREVIOUS_AMOUNT: self.get_sids_to_frames(
zip_with_floats, amounts, date_intervals, dates
zip_with_floats, amounts, date_intervals, dates, 'float', 'NaN'
),
}
@@ -281,16 +282,20 @@ class DividendsByExDateTestCase(WithPipelineEventDataLoader, ZiplineTestCase):
NEXT_EX_DATE: self.get_sids_to_frames(
zip_with_dates, next_ex_and_pay_dates, next_date_intervals,
dates,
'datetime64[ns]', 'NaN'
),
PREVIOUS_EX_DATE: self.get_sids_to_frames(
zip_with_dates, prev_ex_and_pay_dates, prev_date_intervals,
dates
dates,
'datetime64[ns]', 'NaN'
),
NEXT_AMOUNT: self.get_sids_to_frames(
zip_with_floats, next_amounts, next_date_intervals, dates
zip_with_floats, next_amounts, next_date_intervals, dates,
'float', 'NaN'
),
PREVIOUS_AMOUNT: self.get_sids_to_frames(
zip_with_floats, prev_amounts, prev_date_intervals, dates
zip_with_floats, prev_amounts, prev_date_intervals, dates,
'float', 'NaN'
)
}
@@ -360,17 +365,21 @@ class DividendsByPayDateTestCase(WithPipelineEventDataLoader, ZiplineTestCase):
return {
NEXT_PAY_DATE: self.get_sids_to_frames(
zip_with_dates, next_ex_and_pay_dates, next_date_intervals,
dates
dates,
'datetime64[ns]', 'NaN'
),
PREVIOUS_PAY_DATE: self.get_sids_to_frames(
zip_with_dates, prev_ex_and_pay_dates, prev_date_intervals,
dates
dates,
'datetime64[ns]', 'NaN'
),
NEXT_AMOUNT: self.get_sids_to_frames(
zip_with_floats, next_amounts, next_date_intervals, dates
zip_with_floats, next_amounts, next_date_intervals, dates,
'float', 'NaN'
),
PREVIOUS_AMOUNT: self.get_sids_to_frames(
zip_with_floats, prev_amounts, prev_date_intervals, dates
zip_with_floats, prev_amounts, prev_date_intervals, dates,
'float', 'NaN'
)
}
tests/pipeline/test_earnings.py
+5 -2
View File
@@ -51,9 +51,12 @@ class EarningsCalendarLoaderTestCase(WithNextAndPreviousEventDataLoader,
def setup(self, dates):
cols = {
PREVIOUS_ANNOUNCEMENT: self.get_expected_previous_event_dates(
dates
dates,
'datetime64[ns]', 'NaN'
),
NEXT_ANNOUNCEMENT: self.get_expected_next_event_dates(
dates, 'datetime64[ns]', 'NaN'
),
NEXT_ANNOUNCEMENT: self.get_expected_next_event_dates(dates),
}
cols[DAYS_TO_NEXT] = self._compute_busday_offsets(
cols[NEXT_ANNOUNCEMENT]
zipline/pipeline/common.py
+11 -12
View File
@@ -4,12 +4,13 @@ Common constants for Pipeline.
ACTUAL_VALUE_FIELD_NAME = 'actual_value'
AD_FIELD_NAME = 'asof_date'
ANNOUNCEMENT_FIELD_NAME = 'announcement_date'
CASH_FIELD_NAME = 'cash'
CASH_AMOUNT_FIELD_NAME = 'cash_amount'
COUNT_FIELD_NAME = 'count'
BUYBACK_AMOUNT_FIELD_NAME = 'buyback_amount'
BUYBACK_ANNOUNCEMENT_FIELD_NAME = 'buyback_date'
BUYBACK_TYPE_FIELD_NAME = 'buyback_type'
BUYBACK_UNIT_FIELD_NAME = 'buyback_unit'
CASH_AMOUNT_FIELD_NAME = 'cash_amount'
CASH_FIELD_NAME = 'cash'
COUNT_FIELD_NAME = 'count'
DAYS_SINCE_PREV = 'days_since_prev'
DAYS_SINCE_PREV_DISCLOSURE = 'days_since_prev_disclosure'
DAYS_SINCE_PREV_DIVIDEND_ANNOUNCEMENT = 'days_since_prev_dividend_announcement'
@@ -26,36 +27,36 @@ MEAN_FIELD_NAME = 'mean'
NEXT_AMOUNT = 'next_amount'
NEXT_ANNOUNCEMENT = 'next_announcement'
NEXT_COUNT = 'next_count'
NEXT_EX_DATE = 'next_ex_date'
NEXT_FISCAL_QUARTER = 'next_fiscal_quarter'
NEXT_FISCAL_YEAR = 'next_fiscal_year'
NEXT_EX_DATE = 'next_ex_date'
NEXT_HIGH = 'next_high'
NEXT_LOW = 'next_low'
NEXT_MEAN = 'next_mean'
NEXT_PAY_DATE = 'next_pay_date'
NUM_SHARES = 'number_shares'
NEXT_RELEASE_DATE = 'next_release_date'
NEXT_STANDARD_DEVIATION = 'next_standard_deviation'
NUM_SHARES = 'number_shares'
PAY_DATE_FIELD_NAME = 'pay_date'
PERCENT_SHARES = 'percent_shares'
PREVIOUS_ACTUAL_VALUE = 'previous_actual_value'
PREVIOUS_AMOUNT = 'previous_amount'
PREVIOUS_ANNOUNCEMENT = 'previous_announcement'
PREVIOUS_BUYBACK_AMOUNT = 'previous_value'
PREVIOUS_BUYBACK_ANNOUNCEMENT = 'previous_buyback_announcement'
PREVIOUS_BUYBACK_CASH = 'previous_buyback_cash'
PREVIOUS_BUYBACK_SHARE_COUNT = 'previous_buyback_share_count'
PREVIOUS_DISCLOSURE_DATE = 'previous_disclosure_date'
PREVIOUS_COUNT = 'previous_count'
PREVIOUS_BUYBACK_TYPE = 'previous_buyback_type'
PREVIOUS_VALUE = 'previous_value'
PREVIOUS_VALUE_TYPE = 'previous_value_type'
PREVIOUS_BUYBACK_UNIT = 'previous_value_type'
PREVIOUS_COUNT = 'previous_count'
PREVIOUS_DISCLOSURE_DATE = 'previous_disclosure_date'
PREVIOUS_EX_DATE = 'previous_ex_date'
PREVIOUS_NUM_SHARES = 'previous_number_shares'
PREVIOUS_FISCAL_QUARTER = 'previous_fiscal_quarter'
PREVIOUS_FISCAL_YEAR = 'previous_fiscal_year'
PREVIOUS_HIGH = 'previous_high'
PREVIOUS_LOW = 'previous_low'
PREVIOUS_MEAN = 'previous_mean'
PREVIOUS_NUM_SHARES = 'previous_number_shares'
PREVIOUS_PAY_DATE = 'previous_pay_date'
PREVIOUS_PERCENT_SHARES = 'previous_percentage'
PREVIOUS_RELEASE_DATE = 'previous_release_date'
@@ -65,5 +66,3 @@ SHARE_COUNT_FIELD_NAME = 'share_count'
SID_FIELD_NAME = 'sid'
STANDARD_DEVIATION_FIELD_NAME = 'standard_deviation'
TS_FIELD_NAME = 'timestamp'
VALUE_FIELD_NAME = 'value'
VALUE_TYPE_FIELD_NAME = 'value_type'
zipline/pipeline/data/buyback_auth.py
+7 -4
View File
@@ -1,8 +1,11 @@
"""
Datasets representing dates of recently announced buyback authorizations.
"""
from zipline.utils.numpy_utils import datetime64ns_dtype, float64_dtype, \
from zipline.utils.numpy_utils import (
datetime64ns_dtype,
float64_dtype,
categorical_dtype
)
from .dataset import Column, DataSet
@@ -12,7 +15,7 @@ class BuybackAuthorizations(DataSet):
Dataset representing dates of recently announced cash buyback
authorizations.
"""
previous_value = Column(float64_dtype)
previous_amount = Column(float64_dtype)
previous_date = Column(datetime64ns_dtype)
previous_value_type = Column(categorical_dtype, missing_value="<<NONE>>")
previous_buyback_type = Column(categorical_dtype, missing_value="<<NONE>>")
previous_unit = Column(categorical_dtype, missing_value=None)
previous_type = Column(categorical_dtype, missing_value=None)
zipline/pipeline/factors/events.py
+2 -2
View File
@@ -136,11 +136,11 @@ class BusinessDaysSinceBuybackAuth(
):
"""
Factor returning the number of **business days** (not trading days!) since
the most recent cash buyback authorization for each asset.
the most recent buyback authorization for each asset.
See Also
--------
zipline.pipeline.factors.BusinessDaysSinceCashBuybackAuth
zipline.pipeline.factors.BusinessDaysSinceBuybackAuth
"""
inputs = [BuybackAuthorizations.previous_date]
zipline/pipeline/loaders/__init__.py
+1 -1
View File
@@ -1,7 +1,7 @@
from ._13d_filings import _13DFilingsLoader
from .buyback_auth import BuybackAuthorizationsLoader
from .consensus_estimates import ConsensusEstimatesLoader
from .earnings import EarningsCalendarLoader
from .buyback_auth import BuybackAuthorizationsLoader
from .dividends import (
DividendsByAnnouncementDateLoader,
DividendsByExDateLoader,
zipline/pipeline/loaders/blaze/buyback_auth.py
+11 -11
View File
@@ -1,12 +1,12 @@
from .core import (
TS_FIELD_NAME,
SID_FIELD_NAME,
TS_FIELD_NAME,
)
from zipline.pipeline.common import (
BUYBACK_AMOUNT_FIELD_NAME,
BUYBACK_ANNOUNCEMENT_FIELD_NAME,
BUYBACK_TYPE_FIELD_NAME,
VALUE_FIELD_NAME,
VALUE_TYPE_FIELD_NAME,
BUYBACK_UNIT_FIELD_NAME,
)
from zipline.pipeline.data import BuybackAuthorizations
from zipline.pipeline.loaders import BuybackAuthorizationsLoader
@@ -40,15 +40,15 @@ class BlazeBuybackAuthorizationsLoader(BlazeEventsLoader):
{SID_FIELD_NAME}: int64,
{TS_FIELD_NAME}: datetime,
{BUYBACK_ANNOUNCEMENT_FIELD_NAME}: ?datetime,
{VALUE_FIELD_NAME}: ?float64,
{VALUE_TYPE_FIELD_NAME}: ?str,
{BUYBACK_AMOUNT_FIELD_NAME}: ?float64,
{BUYBACK_UNIT_FIELD_NAME}: ?str,
{BUYBACK_TYPE_FIELD_NAME}: ?str,
}}
Where each row of the table is a record including the sid to identify the
company, the timestamp where we learned about the announcement, the
date when the buyback was announced, the buyback value, the value type
(in cash or in shares), and the buyback type.
date when the buyback was announced, the buyback amount, the buyback unit,
and the buyback type.
If the '{TS_FIELD_NAME}' field is not included it is assumed that we
start the backtest with knowledge of all announcements.
@@ -57,8 +57,8 @@ class BlazeBuybackAuthorizationsLoader(BlazeEventsLoader):
TS_FIELD_NAME=TS_FIELD_NAME,
SID_FIELD_NAME=SID_FIELD_NAME,
BUYBACK_ANNOUNCEMENT_FIELD_NAME=BUYBACK_ANNOUNCEMENT_FIELD_NAME,
VALUE_FIELD_NAME=VALUE_FIELD_NAME,
VALUE_TYPE_FIELD_NAME=VALUE_TYPE_FIELD_NAME,
BUYBACK_AMOUNT_FIELD_NAME=BUYBACK_AMOUNT_FIELD_NAME,
BUYBACK_UNIT_FIELD_NAME=BUYBACK_UNIT_FIELD_NAME,
BUYBACK_TYPE_FIELD_NAME=BUYBACK_TYPE_FIELD_NAME
)
@@ -66,8 +66,8 @@ class BlazeBuybackAuthorizationsLoader(BlazeEventsLoader):
TS_FIELD_NAME,
SID_FIELD_NAME,
BUYBACK_ANNOUNCEMENT_FIELD_NAME,
VALUE_FIELD_NAME,
VALUE_TYPE_FIELD_NAME,
BUYBACK_AMOUNT_FIELD_NAME,
BUYBACK_UNIT_FIELD_NAME,
BUYBACK_TYPE_FIELD_NAME
})
zipline/pipeline/loaders/buyback_auth.py
+13 -13
View File
@@ -5,10 +5,10 @@ Reference implementation for buyback auth loaders.
from ..data import BuybackAuthorizations
from .events import EventsLoader
from zipline.pipeline.common import (
BUYBACK_AMOUNT_FIELD_NAME,
BUYBACK_ANNOUNCEMENT_FIELD_NAME,
BUYBACK_TYPE_FIELD_NAME,
VALUE_FIELD_NAME,
VALUE_TYPE_FIELD_NAME
BUYBACK_UNIT_FIELD_NAME
)
from zipline.utils.memoize import lazyval
@@ -19,12 +19,12 @@ class BuybackAuthorizationsLoader(EventsLoader):
:class:`zipline.pipeline.data.BuybackAuthorizations`.
events_by_sid: dict[sid -> pd.DataFrame(knowledge date,
event date, value, value type, buyback type)]
event date, buyback amount, buyback unit, buyback type)]
"""
expected_cols = frozenset([BUYBACK_ANNOUNCEMENT_FIELD_NAME,
VALUE_FIELD_NAME,
VALUE_TYPE_FIELD_NAME,
BUYBACK_AMOUNT_FIELD_NAME,
BUYBACK_UNIT_FIELD_NAME,
BUYBACK_TYPE_FIELD_NAME])
event_date_col = BUYBACK_ANNOUNCEMENT_FIELD_NAME
@@ -42,10 +42,10 @@ class BuybackAuthorizationsLoader(EventsLoader):
)
@lazyval
def previous_value_loader(self):
def previous_amount_loader(self):
return self._previous_event_value_loader(
self.dataset.previous_value,
VALUE_FIELD_NAME
self.dataset.previous_amount,
BUYBACK_AMOUNT_FIELD_NAME
)
@lazyval
@@ -55,15 +55,15 @@ class BuybackAuthorizationsLoader(EventsLoader):
)
@lazyval
def previous_value_type_loader(self):
def previous_unit_loader(self):
return self._previous_event_value_loader(
self.dataset.previous_value_type,
VALUE_TYPE_FIELD_NAME,
self.dataset.previous_unit,
BUYBACK_UNIT_FIELD_NAME,
)
@lazyval
def previous_buyback_type_loader(self):
def previous_type_loader(self):
return self._previous_event_value_loader(
self.dataset.previous_buyback_type,
self.dataset.previous_type,
BUYBACK_TYPE_FIELD_NAME,
)
zipline/pipeline/loaders/utils.py
+8 -4
View File
@@ -5,7 +5,7 @@ import pandas as pd
from six import iteritems
from six.moves import zip
from zipline.utils.numpy_utils import NaTns
from zipline.utils.numpy_utils import categorical_dtype, NaTns
def next_event_frame(events_by_sid,
@@ -116,9 +116,11 @@ def previous_event_frame(events_by_sid,
next_date_frame
"""
sids = list(events_by_sid)
populate_value = None if field_dtype == categorical_dtype else \
missing_value
out = np.full(
(len(date_index), len(sids)),
missing_value,
populate_value,
dtype=field_dtype
)
d_n = date_index[-1].asm8
@@ -140,6 +142,8 @@ def previous_event_frame(events_by_sid,
frame = pd.DataFrame(out, index=date_index, columns=sids)
frame.ffill(inplace=True)
if field_dtype == categorical_dtype:
frame[frame.isnull()] = missing_value
return frame
@@ -280,8 +284,8 @@ def zip_with_floats(dates, flts):
return pd.Series(flts, index=dates, dtype='float')
def zip_with_strs(dates, flts):
return pd.Series(flts, index=dates, dtype='string')
def zip_with_strs(dates, strs):
return pd.Series(strs, index=dates, dtype='object')
def zip_with_dates(index_dates, dts):
zipline/testing/fixtures.py
+20 -8
View File
@@ -887,7 +887,9 @@ class WithPipelineEventDataLoader(with_metaclass(
zip_date_index_with_vals,
vals,
date_intervals,
dates):
dates,
dtype_name,
missing_dtype):
"""
Construct a DataFrame that maps sid to the expected values for the
given dates.
@@ -907,6 +909,11 @@ class WithPipelineEventDataLoader(with_metaclass(
dates: DatetimeIndex
The dates which will serve as the index for each Series for each
sid in the DataFrame.
dtype_name: str
The name of the dtype of the values in `vals`.
missing_dtype: str
The name of the value that should be used as the missing value
for the dtype of `vals` - e.g., 'NaN' for floats.
"""
frame = pd.DataFrame({sid: get_values_for_date_ranges(
zip_date_index_with_vals,
@@ -914,10 +921,10 @@ class WithPipelineEventDataLoader(with_metaclass(
pd.DatetimeIndex(list(zip(*date_intervals[sid]))[0]),
pd.DatetimeIndex(list(zip(*date_intervals[sid]))[1]),
dates
) for sid in self.get_sids()[:-1]})
).astype(dtype_name) for sid in self.get_sids()[:-1]})
frame[self.get_sids()[-1]] = zip_date_index_with_vals(
dates, ['NaN'] * len(dates)
)
dates, [missing_dtype] * len(dates)
).astype(dtype_name)
return frame
@staticmethod
@@ -1232,18 +1239,23 @@ class WithNextAndPreviousEventDataLoader(WithPipelineEventDataLoader):
['NaT']
]
def get_expected_previous_event_dates(self, dates):
def get_expected_previous_event_dates(self, dates, dtype_name,
missing_dtype):
return self.get_sids_to_frames(
zip_with_dates,
self.prev_dates,
self.prev_date_intervals,
dates
dates,
dtype_name,
missing_dtype
)
def get_expected_next_event_dates(self, dates):
def get_expected_next_event_dates(self, dates, dtype_name, missing_dtype):
return self.get_sids_to_frames(
zip_with_dates,
self.next_dates,
self.next_date_intervals,
dates
dates,
dtype_name,
missing_dtype
)