def _get_predict_end(self, end):
"""
See _get_predict_start for more information. Subclasses do not
need to define anything for this.
"""
out_of_sample = 0 # will be overwritten if needed
if end is None: # use data for ARIMA - endog changes
end = len(self.data.endog) - 1
dates = self.data.dates
if isinstance(end, str):
if dates is None:
raise ValueError("Got a string for end and dates is None")
try:
dtend = self._str_to_date(end)
self.data.predict_end = dtend
# for pandas 0.7.x vs 0.8.x
if hasattr(dates, 'indexMap'): # 0.7.x
end = dates.indexMap[dtend]
else:
end = dates.get_loc(dtend)
except KeyError, err: # end is greater than dates[-1]...probably
if dtend > self.data.dates[-1]:
end = len(self.data.endog) - 1
freq = self.data.freq
out_of_sample = datetools._idx_from_dates(dates[-1], dtend,
freq)
else:
raise err
self._make_predict_dates() # attaches self.data.predict_dates
def _get_predict_end(self, end):
"""
See _get_predict_start for more information. Subclasses do not
need to define anything for this.
"""
out_of_sample = 0 # will be overwritten if needed
if end is None:
end = len(self.endog) - 1
dates = self._data.dates
if isinstance(end, str):
if dates is None:
raise ValueError("Got a string for end and dates is None")
try:
dtend = self._str_to_date(end)
self._data.predict_end = dtend
end = dates.indexMap[dtend]
except ImportError, err: # make sure timeseries isn't the prob
raise ImportError(err)
except KeyError, err: # end is greater than dates[-1]...probably
if dtend > self._data.dates[-1]:
end = len(self.endog) - 1
freq = self._data.freq
out_of_sample = datetools._idx_from_dates(dates[-1], dtend, freq)
else:
raise err
def _get_predict_end(self, end):
"""
See _get_predict_start for more information. Subclasses do not
need to define anything for this.
"""
out_of_sample = 0 # will be overwritten if needed
if end is None:
end = len(self.endog) - 1
dates = self._data.dates
if isinstance(end, str):
if dates is None:
raise ValueError("Got a string for end and dates is None")
try:
dtend = self._str_to_date(end)
self._data.predict_end = dtend
end = dates.indexMap[dtend]
except ImportError as err: # make sure timeseries isn't the prob
raise ImportError(err)
except KeyError as err: # end is greater than dates[-1]...probably
if dtend > self._data.dates[-1]:
end = len(self.endog) - 1
freq = self._data.freq
out_of_sample = datetools._idx_from_dates(dates[-1], dtend,
freq)
else:
raise err
self._make_predict_dates() # attaches self._data.predict_dates
elif isinstance(end, int) and dates is not None:
try:
self._data.predict_end = dates[end]
except IndexError as err:
nobs = len(self.endog) - 1 # as an index
out_of_sample = end - nobs
end = nobs
freq = self._data.freq
self._data.predict_end = datetools._date_from_idx(dates[-1],
out_of_sample, freq)
self._make_predict_dates()
elif isinstance(end, int):
nobs = len(self.endog) - 1 # is an index
if end > nobs:
out_of_sample = end - nobs
end = nobs
return end, out_of_sample
def test_idx_from_date():
d1 = datetime(2008, 12, 31)
idx = 15
npt.assert_equal(_idx_from_dates(d1, datetime(2012, 9, 30), "Q"), idx)
npt.assert_equal(_idx_from_dates(d1, datetime(2023, 12, 31), "A"), idx)
npt.assert_equal(_idx_from_dates(d1, datetime(2009, 1, 21), "B"), idx)
npt.assert_equal(_idx_from_dates(d1, datetime(2009, 1, 15), "D"), idx)
# move d1 and d2 forward to end of week
npt.assert_equal(_idx_from_dates(datetime(2009, 1, 4), datetime(2009, 4, 17), "W"), idx - 1)
npt.assert_equal(_idx_from_dates(d1, datetime(2010, 3, 31), "M"), idx)
def test_idx_from_date():
d1 = datetime(2008, 12, 31)
idx = 15
npt.assert_equal(_idx_from_dates(d1, datetime(2012, 9, 30), 'Q'), idx)
npt.assert_equal(_idx_from_dates(d1, datetime(2023, 12, 31), 'A'), idx)
npt.assert_equal(_idx_from_dates(d1, datetime(2009, 1, 21), 'B'), idx)
npt.assert_equal(_idx_from_dates(d1, datetime(2009, 1, 15), 'D'), idx)
# move d1 and d2 forward to end of week
npt.assert_equal(_idx_from_dates(datetime(2009, 1, 4),
datetime(2009, 4, 17), 'W'), idx-1)
npt.assert_equal(_idx_from_dates(d1, datetime(2010, 3, 31), 'M'), idx)
def test_idx_from_date():
d1 = datetime(2008, 12, 31)
idx = 15
npt.assert_equal(_idx_from_dates(d1, datetime(2012, 9, 30), 'Q'), idx)
npt.assert_equal(_idx_from_dates(d1, datetime(2023, 12, 31), 'A'), idx)
npt.assert_equal(_idx_from_dates(d1, datetime(2009, 1, 21), 'B'), idx)
npt.assert_equal(_idx_from_dates(d1, datetime(2009, 1, 15), 'D'), idx)
# move d1 and d2 forward to end of week
npt.assert_equal(_idx_from_dates(datetime(2009, 1, 4),
datetime(2009, 4, 17), 'W'), idx-1)
npt.assert_equal(_idx_from_dates(d1, datetime(2010, 3, 31), 'M'), idx)
def _get_predict_end(self, end):
"""
See _get_predict_start for more information. Subclasses do not
need to define anything for this.
"""
out_of_sample = 0 # will be overwritten if needed
if end is None: # use data for ARIMA - endog changes
end = len(self.data.endog) - 1
dates = self.data.dates
freq = self.data.freq
if isinstance(end, str):
if dates is None:
raise ValueError("Got a string for end and dates is None")
try:
dtend = self._str_to_date(end)
self.data.predict_end = dtend
end = self._get_dates_loc(dates, dtend)
except KeyError, err: # end is greater than dates[-1]...probably
if dtend > self.data.dates[-1]:
end = len(self.data.endog) - 1
freq = self.data.freq
out_of_sample = datetools._idx_from_dates(dates[-1], dtend,
freq)
else:
if freq is None:
raise ValueError("There is no frequency for these "
"dates and date %s is not in dates "
"index. Try giving a date that is in "
"the dates index or use an integer."
% dtend)
else: #pragma: no cover
raise err # should never get here
self._make_predict_dates() # attaches self.data.predict_dates
def _get_predict_end(self, end):
"""
See _get_predict_start for more information. Subclasses do not
need to define anything for this.
"""
out_of_sample = 0 # will be overwritten if needed
if end is None: # use data for ARIMA - endog changes
end = len(self.data.endog) - 1
dates = self.data.dates
freq = self.data.freq
if isinstance(end, str):
if dates is None:
raise ValueError("Got a string for end and dates is None")
try:
dtend = self._str_to_date(end)
self.data.predict_end = dtend
end = self._get_dates_loc(dates, dtend)
except KeyError, err: # end is greater than dates[-1]...probably
if dtend > self.data.dates[-1]:
end = len(self.data.endog) - 1
freq = self.data.freq
out_of_sample = datetools._idx_from_dates(
dates[-1], dtend, freq)
else:
if freq is None:
raise ValueError("There is no frequency for these "
"dates and date %s is not in dates "
"index. Try giving a date that is in "
"the dates index or use an integer." %
dtend)
else: #pragma: no cover
raise err # should never get here
self._make_predict_dates() # attaches self.data.predict_dates
def _get_predict_end(self, end):
"""
See _get_predict_start for more information. Subclasses do not
need to define anything for this.
"""
out_of_sample = 0 # will be overwritten if needed
if end is None: # use data for ARIMA - endog changes
end = len(self.data.endog) - 1
dates = self.data.dates
freq = self.data.freq
if isinstance(end, str) or (dates is not None
and isinstance(end, type(dates[0]))):
if dates is None:
raise ValueError("Got a string or date for `end` and `dates` is None")
if isinstance(end, str):
dtend = self._str_to_date(end)
else:
dtend = end # end could be a pandas TimeStamp not a datetime
self.data.predict_end = dtend
try:
end = self._get_dates_loc(dates, dtend)
except KeyError as err: # end is greater than dates[-1]...probably
if dtend > self.data.dates[-1]:
end = len(self.data.endog) - 1
freq = self.data.freq
out_of_sample = datetools._idx_from_dates(dates[-1], dtend,
freq)
else:
if freq is None:
raise ValueError("There is no frequency for these "
"dates and date %s is not in dates "
"index. Try giving a date that is in "
"the dates index or use an integer."
% dtend)
else: #pragma: no cover
raise err # should never get here
self._make_predict_dates() # attaches self.data.predict_dates
elif isinstance(end, int) and dates is not None:
try:
self.data.predict_end = dates[end]
except IndexError as err:
nobs = len(self.data.endog) - 1 # as an index
out_of_sample = end - nobs
end = nobs
if freq is not None:
self.data.predict_end = datetools._date_from_idx(dates[-1],
out_of_sample, freq)
elif out_of_sample <= 0: # have no frequency but are in sample
#TODO: what error to catch here to make sure dates is
#on the index?
try:
self.data.predict_end = self._get_dates_loc(dates,
end)
except KeyError:
raise
else:
self.data.predict_end = end + out_of_sample
self.data.predict_start = self._get_dates_loc(dates,
self.data.predict_start)
self._make_predict_dates()
elif isinstance(end, int):
nobs = len(self.data.endog) - 1 # is an index
if end > nobs:
out_of_sample = end - nobs
end = nobs
elif freq is None: # should have a date with freq = None
raise ValueError("When freq is None, you must give an integer "
"index for end.")
else:
raise ValueError("no rule for interpreting end")
return end, out_of_sample
