def get_time_region(self, time_region, return_indices=False):
assert isinstance(time_region, dict)
# return the values to use for the temporal region subsetting.
value = self.value_datetime
bounds = self.bounds_datetime
# switch to indicate if bounds or centroid datetimes are to be used.
use_bounds = False if bounds is None else True
# remove any none values in the time_region dictionary. this will save
# time in iteration.
time_region = time_region.copy()
time_region = {k: v for k, v in time_region.iteritems() if v is not None}
assert len(time_region) > 0
# this is the boolean selection array.
select = np.zeros(self.shape[0], dtype=bool)
# for each row, determine if the date criterion are met updating the
# select matrix accordingly.
row_check = np.zeros(len(time_region), dtype=bool)
for idx_row in range(select.shape[0]):
# do the comparison for each time_region element.
if use_bounds:
row = bounds[idx_row, :]
else:
row = value[idx_row]
for ii, (k, v) in enumerate(time_region.iteritems()):
if use_bounds:
to_include = []
for element in v:
kwds = {k: element}
to_include.append(get_is_date_between(row[0], row[1], **kwds))
fill = any(to_include)
else:
part = getattr(row, k)
fill = True if part in v else False
row_check[ii] = fill
if row_check.all():
select[idx_row] = True
if not select.any():
raise EmptySubsetError(origin='temporal')
ret = self[select]
if return_indices:
raw_idx = np.arange(0, self.shape[0])[select]
ret = (ret, raw_idx)
return ret
def test_get_is_date_between(self):
lower = dt(1971,1,1)
upper = dt(2000,2,1)
self.assertFalse(get_is_date_between(lower,upper,month=6))
self.assertFalse(get_is_date_between(lower,upper,month=2))
self.assertTrue(get_is_date_between(lower,upper,month=1))
self.assertFalse(get_is_date_between(lower,upper,year=1968))
self.assertTrue(get_is_date_between(lower,upper,year=1995))
lower = dt(2013, 1, 1, 0, 0)
upper = dt(2013, 1, 2, 0, 0)
self.assertTrue(get_is_date_between(lower,upper,year=2013))
def get_time_region(self, time_region, return_indices=False):
"""
:param dict time_region: A dictionary defining the time region subset.
>>> time_region = {'month': [1, 2, 3], 'year': [2000]}
:param bool return_indices: If ``True``, also return the indices used to subset the variable.
:return: shallow copy of the sliced time variable
:rtype: :class:`~ocgis.TemporalVariable`
"""
assert isinstance(time_region, dict)
# return the values to use for the temporal region subsetting.
value = self.value_datetime
if self.has_bounds:
bounds = self.bounds.value_datetime
else:
bounds = None
# switch to indicate if bounds or centroid datetimes are to be used.
use_bounds = False if bounds is None else True
# remove any none values in the time_region dictionary. this will save
# time in iteration.
time_region = time_region.copy()
time_region = {k: v for k, v in time_region.items() if v is not None}
assert len(time_region) > 0
# this is the boolean selection array.
select = np.zeros(self.shape[0], dtype=bool)
# for each row, determine if the date criterion are met updating the
# select matrix accordingly.
row_check = np.zeros(len(time_region), dtype=bool)
for idx_row in range(select.shape[0]):
# do the comparison for each time_region element.
if use_bounds:
row = bounds[idx_row, :]
else:
row = value[idx_row]
for ii, (k, v) in enumerate(time_region.items()):
if use_bounds:
to_include = []
for element in v:
kwds = {k: element}
to_include.append(get_is_date_between(row[0], row[1], **kwds))
fill = any(to_include)
else:
part = getattr(row, k)
fill = True if part in v else False
row_check[ii] = fill
if row_check.all():
select[idx_row] = True
if not select.any():
raise EmptySubsetError(origin='temporal')
ret = self[select]
if return_indices:
raw_idx = np.arange(0, self.shape[0])[select]
ret = (ret, raw_idx)
return ret
