def test_get_rule_month():
result = frequencies._get_rule_month('W')
assert (result == 'DEC')
result = frequencies._get_rule_month(offsets.Week())
assert (result == 'DEC')
result = frequencies._get_rule_month('D')
assert (result == 'DEC')
result = frequencies._get_rule_month(offsets.Day())
assert (result == 'DEC')
result = frequencies._get_rule_month('Q')
assert (result == 'DEC')
result = frequencies._get_rule_month(offsets.QuarterEnd(startingMonth=12))
print(result == 'DEC')
result = frequencies._get_rule_month('Q-JAN')
assert (result == 'JAN')
result = frequencies._get_rule_month(offsets.QuarterEnd(startingMonth=1))
assert (result == 'JAN')
result = frequencies._get_rule_month('A-DEC')
assert (result == 'DEC')
result = frequencies._get_rule_month(offsets.YearEnd())
assert (result == 'DEC')
result = frequencies._get_rule_month('A-MAY')
assert (result == 'MAY')
result = frequencies._get_rule_month(offsets.YearEnd(month=5))
assert (result == 'MAY')
def test_anchored_shortcuts():
result = frequencies.to_offset('W')
expected = frequencies.to_offset('W-SUN')
assert (result == expected)
result1 = frequencies.to_offset('Q')
result2 = frequencies.to_offset('Q-DEC')
expected = offsets.QuarterEnd(startingMonth=12)
assert (result1 == expected)
assert (result2 == expected)
result1 = frequencies.to_offset('Q-MAY')
expected = offsets.QuarterEnd(startingMonth=5)
assert (result1 == expected)
def test_anchored_shortcuts():
result = frequencies.to_offset('W')
expected = frequencies.to_offset('W-SUN')
assert (result == expected)
result1 = frequencies.to_offset('Q')
result2 = frequencies.to_offset('Q-DEC')
expected = offsets.QuarterEnd(startingMonth=12)
assert (result1 == expected)
assert (result2 == expected)
result1 = frequencies.to_offset('Q-MAY')
expected = offsets.QuarterEnd(startingMonth=5)
assert (result1 == expected)
result1 = frequencies.to_offset('SM')
result2 = frequencies.to_offset('SM-15')
expected = offsets.SemiMonthEnd(day_of_month=15)
assert (result1 == expected)
assert (result2 == expected)
result = frequencies.to_offset('SM-1')
expected = offsets.SemiMonthEnd(day_of_month=1)
assert (result == expected)
result = frequencies.to_offset('SM-27')
expected = offsets.SemiMonthEnd(day_of_month=27)
assert (result == expected)
result = frequencies.to_offset('SMS-2')
expected = offsets.SemiMonthBegin(day_of_month=2)
assert (result == expected)
result = frequencies.to_offset('SMS-27')
expected = offsets.SemiMonthBegin(day_of_month=27)
assert (result == expected)
# ensure invalid cases fail as expected
invalid_anchors = [
'SM-0', 'SM-28', 'SM-29', 'SM-FOO', 'BSM', 'SM--1'
'SMS-1', 'SMS-28', 'SMS-30', 'SMS-BAR', 'BSMS', 'SMS--2'
]
for invalid_anchor in invalid_anchors:
try:
frequencies.to_offset(invalid_anchor)
except ValueError:
pass
else:
raise AssertionError(invalid_anchor)
def get_dates_range(self,
scale='auto',
start=None,
end=None,
date_max='2010-01-01'):
'''
Returns a list of dates sampled according to the specified parameters.
:param scale: {'auto', 'maximum', 'daily', 'weekly', 'monthly',
'quarterly', 'yearly'}
Scale specifies the sampling intervals.
'auto' will heuristically choose a scale for quick processing
:param start: First date that will be included.
:param end: Last date that will be included
'''
if scale not in [
'auto', 'maximum', 'daily', 'weekly', 'monthly', 'quarterly',
'yearly'
]:
raise ValueError('Incorrect scale: %s' % scale)
start = Timestamp(start or self._start.min() or date_max)
# FIXME: start != start is true for NaN objects... is NaT the same?
start = Timestamp(date_max) if repr(start) == 'NaT' else start
end = Timestamp(end
or max(Timestamp(self._end.max()), self._start.max()))
# FIXME: end != end ?
end = datetime.utcnow() if repr(end) == 'NaT' else end
start = start if self.check_in_bounds(start) else self._lbound
end = end if self.check_in_bounds(end) else self._rbound
if scale == 'auto':
scale = self._auto_select_scale(start, end)
if scale == 'maximum':
start_dts = list(self._start.dropna().values)
end_dts = list(self._end.dropna().values)
dts = map(Timestamp, set(start_dts + end_dts))
dts = filter(
lambda ts: self.check_in_bounds(ts) and ts >= start and ts <=
end, dts)
return dts
freq = dict(daily='D',
weekly='W',
monthly='M',
quarterly='3M',
yearly='12M')
offset = dict(daily=off.Day(n=0),
weekly=off.Week(),
monthly=off.MonthEnd(),
quarterly=off.QuarterEnd(),
yearly=off.YearEnd())
# for some reason, weekly date range gives one week less:
end_ = end + off.Week() if scale == 'weekly' else end
ret = list(pd.date_range(start + offset[scale], end_,
freq=freq[scale]))
ret = [dt for dt in ret if dt <= end]
ret = [start] + ret if ret and start < ret[0] else ret
ret = ret + [end] if ret and end > ret[-1] else ret
ret = filter(lambda ts: self.check_in_bounds(ts), ret)
return ret
def get_date_ranges(self, start, end, scale='daily', include_bounds=True):
'''
Returns a list of dates sampled according to the specified parameters.
Parameters
----------
start: str
First date that will be included.
end: str
Last date that will be included
scale: {'daily', 'weekly', 'monthly', 'quarterly', 'yearly'}
Scale specifies the sampling intervals.
include_bounds: boolean
Include start and end in the result if they are not included yet.
'''
if scale not in ['daily', 'weekly', 'monthly', 'quarterly', 'yearly']:
raise ValueError('Incorrect scale: %s' % scale)
start = Timestamp(start)
end = Timestamp(end)
freq = dict(weekly='W', monthly='M', quarterly='3M', yearly='12M')
offset = dict(weekly=off.Week(),
monthly=off.MonthEnd(),
quarterly=off.QuarterEnd(),
yearly=off.YearEnd())
if scale == 'daily':
ret = pd.date_range(start, end, freq='D')
else:
ret = pd.date_range(start + offset[scale], end, freq=freq[scale])
ret = list(ret)
if include_bounds:
if start not in ret:
ret = [start] + ret
if end not in ret:
ret = ret + [end]
return ret
def test_anchored_shortcuts(self):
result = frequencies.to_offset('W')
expected = frequencies.to_offset('W-SUN')
assert (result == expected)
result1 = frequencies.to_offset('Q')
result2 = frequencies.to_offset('Q-DEC')
expected = offsets.QuarterEnd(startingMonth=12)
assert (result1 == expected)
assert (result2 == expected)
result1 = frequencies.to_offset('Q-MAY')
expected = offsets.QuarterEnd(startingMonth=5)
assert (result1 == expected)
result1 = frequencies.to_offset('SM')
result2 = frequencies.to_offset('SM-15')
expected = offsets.SemiMonthEnd(day_of_month=15)
assert (result1 == expected)
assert (result2 == expected)
result = frequencies.to_offset('SM-1')
expected = offsets.SemiMonthEnd(day_of_month=1)
assert (result == expected)
result = frequencies.to_offset('SM-27')
expected = offsets.SemiMonthEnd(day_of_month=27)
assert (result == expected)
result = frequencies.to_offset('SMS-2')
expected = offsets.SemiMonthBegin(day_of_month=2)
assert (result == expected)
result = frequencies.to_offset('SMS-27')
expected = offsets.SemiMonthBegin(day_of_month=27)
assert (result == expected)
# ensure invalid cases fail as expected
invalid_anchors = ['SM-0', 'SM-28', 'SM-29',
'SM-FOO', 'BSM', 'SM--1',
'SMS-1', 'SMS-28', 'SMS-30',
'SMS-BAR', 'SMS-BYR' 'BSMS',
'SMS--2']
for invalid_anchor in invalid_anchors:
with tm.assert_raises_regex(ValueError,
'Invalid frequency: '):
frequencies.to_offset(invalid_anchor)
is_superperiod,
)
from pandas._libs.tslibs.parsing import get_rule_month
from pandas.tseries import offsets
@pytest.mark.parametrize(
"obj,expected",
[
("W", "DEC"),
(offsets.Week(), "DEC"),
("D", "DEC"),
(offsets.Day(), "DEC"),
("Q", "DEC"),
(offsets.QuarterEnd(startingMonth=12), "DEC"),
("Q-JAN", "JAN"),
(offsets.QuarterEnd(startingMonth=1), "JAN"),
("A-DEC", "DEC"),
("Y-DEC", "DEC"),
(offsets.YearEnd(), "DEC"),
("A-MAY", "MAY"),
("Y-MAY", "MAY"),
(offsets.YearEnd(month=5), "MAY"),
],
)
def test_get_rule_month(obj, expected):
result = get_rule_month(obj)
assert result == expected
(dict(microseconds=1), offsets.Micro(1)),
(dict(microseconds=0), offsets.Nano(0)),
],
)
def test_to_offset_pd_timedelta(kwargs, expected):
# see gh-9064
td = Timedelta(**kwargs)
result = frequencies.to_offset(td)
assert result == expected
@pytest.mark.parametrize(
"shortcut,expected",
[
("W", offsets.Week(weekday=6)),
("W-SUN", offsets.Week(weekday=6)),
("Q", offsets.QuarterEnd(startingMonth=12)),
("Q-DEC", offsets.QuarterEnd(startingMonth=12)),
("Q-MAY", offsets.QuarterEnd(startingMonth=5)),
("SM", offsets.SemiMonthEnd(day_of_month=15)),
("SM-15", offsets.SemiMonthEnd(day_of_month=15)),
("SM-1", offsets.SemiMonthEnd(day_of_month=1)),
("SM-27", offsets.SemiMonthEnd(day_of_month=27)),
("SMS-2", offsets.SemiMonthBegin(day_of_month=2)),
("SMS-27", offsets.SemiMonthBegin(day_of_month=27)),
],
)
def test_anchored_shortcuts(shortcut, expected):
result = frequencies.to_offset(shortcut)
assert result == expected
import pytest
from pandas._libs.tslibs.parsing import get_rule_month
from pandas.tseries import offsets
@pytest.mark.parametrize(
"obj,expected",
[
("W", "DEC"),
(offsets.Week().freqstr, "DEC"),
("D", "DEC"),
(offsets.Day().freqstr, "DEC"),
("Q", "DEC"),
(offsets.QuarterEnd(startingMonth=12).freqstr, "DEC"),
("Q-JAN", "JAN"),
(offsets.QuarterEnd(startingMonth=1).freqstr, "JAN"),
("A-DEC", "DEC"),
("Y-DEC", "DEC"),
(offsets.YearEnd().freqstr, "DEC"),
("A-MAY", "MAY"),
("Y-MAY", "MAY"),
(offsets.YearEnd(month=5).freqstr, "MAY"),
],
)
def test_get_rule_month(obj, expected):
result = get_rule_month(obj)
assert result == expected
xt = [dav.index[1]] + [dav[str(i)].index[-1] for i in set(dav.index.year)]
yearly = pd.concat(
[np.exp(dao["Close"][dav.index] - dao["Close"][dat.index[-1]]), cumreturn],
axis=1).loc[xt]
yearly = pd.concat([yearly, np.exp(np.log(yearly).diff()) - 1], axis=1)
fig = plt.figure(figsize=(12, 4))
np.exp(dao["Close"][dav.index] - dao["Close"][dat.index[-1]]).plot(
color="#0000ff", alpha=0.5)
plt.title("Decision in " + yv + ", Period: " + str(period), fontsize=11)
plt.ylabel(yv + " Index")
np.exp((dao["Close"][dav.index] - dao["Close"][dat.index[-1]])[1:] *
score[:-1]).plot(color="#ff0000", linewidth=0.4)
cumreturn.plot(color="#008800", linewidth=0.5)
for ti in range(2, len(yearly.index)):
plt.annotate(str(round(100 * yearly.iloc[ti, 2], 1)) + "%",
xy=(yearly.index[ti] - tso.QuarterEnd(1), yearly.iloc[ti, 0]),
xytext=(yearly.index[ti] - tso.QuarterEnd(1),
yearly.iloc[ti - 1, 0]),
size=6,
color='#0000ff',
arrowprops=dict(color='#0000ff', alpha=0.5))
plt.annotate(str(round(100 * yearly.iloc[ti, 3], 1)) + "%",
xy=(yearly.index[ti], yearly.iloc[ti, 1]),
xytext=(yearly.index[ti], yearly.iloc[ti - 1, 1]),
weight=1000,
size=6,
color='#008800',
arrowprops=dict(color='#00cc00', alpha=0.8))
fig.savefig(yv + "_Period_" + str(period) + ".png", format="png")
print(
pd.Series([
