def get_previous_business_day(super_set: pd.DatetimeIndex,
sub_set: pd.DatetimeIndex):
diff = sub_set.difference(super_set)
while len(diff) > 0:
new_dates = diff - pd.tseries.offsets.BDay(1)
sub_set = new_dates.union(sub_set.intersection(super_set))
diff = sub_set.difference(super_set)
return sub_set
class SetDisjoint:
def setup(self):
N = 10**5
B = N + 20000
self.datetime_left = DatetimeIndex(range(N))
self.datetime_right = DatetimeIndex(range(N, B))
def time_datetime_difference_disjoint(self):
self.datetime_left.difference(self.datetime_right)
class SetDisjoint:
def setup(self):
N = 10**5
B = N + 20000
self.datetime_left = DatetimeIndex(range(N))
self.datetime_right = DatetimeIndex(range(N, B))
def time_datetime_difference_disjoint(self):
self.datetime_left.difference(self.datetime_right)
def test_datetimeindex_diff(self):
dti1 = DatetimeIndex(freq='Q-JAN',
start=datetime(1997, 12, 31),
periods=100)
dti2 = DatetimeIndex(freq='Q-JAN',
start=datetime(1997, 12, 31),
periods=98)
assert len(dti1.difference(dti2)) == 2
def apply_to_issue_times(
self,
issue_times: pd.DatetimeIndex) -> Iterable[IssueTimesPartition]:
num_partitions = self.num_folds * self.num_repeats
partition_size = len(issue_times) / num_partitions
partitions = []
for i in range(num_partitions):
start = round(i * partition_size)
stop = round((i + 1) * partition_size)
partitions.append(issue_times[start:stop])
for i in range(self.num_folds):
test_set = pd.DatetimeIndex(
np.concatenate(partitions[i::self.num_folds]))
train_set = issue_times.difference(test_set)
yield IssueTimesPartition(train_set, test_set)
def missing_dataset_days(
self, desireddays: pd.DatetimeIndex) -> pd.DatetimeIndex:
"""
Checks if the desired daily timerange is present in the dataset, for the variable + operation of interest. Returns the difference.
"""
with nc.Dataset(self.datapath, mode='r') as ds:
try:
datearray = nc.num2date(
ds[self.operation]['time'][:],
units=ds[self.operation]['time'].units,
calendar=ds[self.operation]['time'].calendar)
presentdays = pd.DatetimeIndex(datearray)
except IndexError: # then the time dimension is completely empty
presentdays = pd.DatetimeIndex([])
#for var in presentset.variables.keys():
# print(presentset[var])
return (desireddays.difference(presentdays))
def test_datetimeindex_diff(self):
dti1 = DatetimeIndex(freq='Q-JAN', start=datetime(1997, 12, 31),
periods=100)
dti2 = DatetimeIndex(freq='Q-JAN', start=datetime(1997, 12, 31),
periods=98)
self.assertEqual(len(dti1.difference(dti2)), 2)
