def example_arrow():
l = TimeSeries()
l[arrow.Arrow(2010, 1, 1)] = 0
l[arrow.Arrow(2010, 1, 3, 10)] = 1
l[arrow.Arrow(2010, 1, 5)] = 0
l[arrow.Arrow(2010, 1, 8)] = 1
l[arrow.Arrow(2010, 1, 17)] = 0
l[arrow.Arrow(2010, 1, 19)] = 1
l[arrow.Arrow(2010, 1, 23)] = 0
l[arrow.Arrow(2010, 1, 26)] = 1
l[arrow.Arrow(2010, 1, 28)] = 0
l[arrow.Arrow(2010, 1, 31)] = 1
l[arrow.Arrow(2010, 2, 5)] = 0
for time, value in l:
print(time.naive.isoformat(), 0.1 * value + 1.1)
print('')
start = arrow.Arrow(2010, 1, 1)
end = arrow.Arrow(2010, 2, 5)
unit = {'hours': 25}
for start, end in span_range(start, end, unit):
print(start.naive.isoformat(), l.mean(start, end))
print('')
for start, end in span_range(start, end, unit):
print(start.naive.isoformat(), -0.2)
print(start.naive.isoformat(), 1.2)
def example_mean():
l = TimeSeries()
l[datetime.datetime(2010, 1, 1)] = 0
l[datetime.datetime(2010, 1, 3, 10)] = 1
l[datetime.datetime(2010, 1, 5)] = 0
l[datetime.datetime(2010, 1, 8)] = 1
l[datetime.datetime(2010, 1, 17)] = 0
l[datetime.datetime(2010, 1, 19)] = 1
l[datetime.datetime(2010, 1, 23)] = 0
l[datetime.datetime(2010, 1, 26)] = 1
l[datetime.datetime(2010, 1, 28)] = 0
l[datetime.datetime(2010, 1, 31)] = 1
l[datetime.datetime(2010, 2, 5)] = 0
for time, value in l:
print(time.isoformat(), 0.1 * value + 1.1)
print('')
timestep = {'hours': 25}
start = datetime.datetime(2010, 1, 1)
while start <= datetime.datetime(2010, 2, 5):
end = start + datetime.timedelta(**timestep)
print(start.isoformat(), l.mean(start, end))
start = end
print('')
start = datetime.datetime(2010, 1, 1)
while start <= datetime.datetime(2010, 2, 5):
end = start + datetime.timedelta(**timestep)
print(start.isoformat(), -0.2)
print(start.isoformat(), 1.2)
start = end
def example_arrow():
l = TimeSeries()
l[arrow.Arrow(2010, 1, 1)] = 0
l[arrow.Arrow(2010, 1, 3, 10)] = 1
l[arrow.Arrow(2010, 1, 5)] = 0
l[arrow.Arrow(2010, 1, 8)] = 1
l[arrow.Arrow(2010, 1, 17)] = 0
l[arrow.Arrow(2010, 1, 19)] = 1
l[arrow.Arrow(2010, 1, 23)] = 0
l[arrow.Arrow(2010, 1, 26)] = 1
l[arrow.Arrow(2010, 1, 28)] = 0
l[arrow.Arrow(2010, 1, 31)] = 1
l[arrow.Arrow(2010, 2, 5)] = 0
for time, value in l:
print time.naive.isoformat(), 0.1 * value + 1.1
print ''
start = arrow.Arrow(2010, 1, 1)
end = arrow.Arrow(2010, 2, 5)
unit = {'hours': 25}
for start_time, end_time in span_range(start, end, unit):
print start_time.naive.isoformat(), l.mean(start_time, end_time)
print ''
for start_time, end_time in span_range(start, end, unit):
print start_time.naive.isoformat(), -0.2
print start_time.naive.isoformat(), 1.2
def example_mean():
l = TimeSeries()
l[datetime.datetime(2010, 1, 1)] = 0
l[datetime.datetime(2010, 1, 3, 10)] = 1
l[datetime.datetime(2010, 1, 5)] = 0
l[datetime.datetime(2010, 1, 8)] = 1
l[datetime.datetime(2010, 1, 17)] = 0
l[datetime.datetime(2010, 1, 19)] = 1
l[datetime.datetime(2010, 1, 23)] = 0
l[datetime.datetime(2010, 1, 26)] = 1
l[datetime.datetime(2010, 1, 28)] = 0
l[datetime.datetime(2010, 1, 31)] = 1
l[datetime.datetime(2010, 2, 5)] = 0
for time, value in l:
print time.isoformat(), 0.1 * value + 1.1
print ''
timestep = {'hours': 25}
start_time = datetime.datetime(2010, 1, 1)
while start_time <= datetime.datetime(2010, 2, 5):
end_time = start_time + datetime.timedelta(**timestep)
print start_time.isoformat(), l.mean(start_time, end_time)
start_time = end_time
print ''
start_time = datetime.datetime(2010, 1, 1)
while start_time <= datetime.datetime(2010, 2, 5):
end_time = start_time + datetime.timedelta(**timestep)
print start_time.isoformat(), -0.2
print start_time.isoformat(), 1.2
start_time = end_time
def test_mean():
ts = TimeSeries([[1, 2], [2, 3], [6, 1], [8, 4]], domain=Domain(0, 9))
assert ts.mean() == 22. / 9
ts = TimeSeries([[1, 2], [2, 3], [6, 1], [8, 4]],
domain=Domain([1, 2], [3, 5], [6, 8]))
nose.tools.assert_raises(NotImplementedError, ts.mean)
def test_moving_average():
ts = TimeSeries([[1, 2], [2, 3], [6, 1], [8, 4]], domain=Domain(1, 9))
ts2 = TimeSeries(
[[1, 2], [2, 3], [6, 1], [8, 4]],
domain=Domain(1 - 1, 9 + 1),
)
assert dict(ts.moving_average(
1, 2)) == {i: ts2.mean(i - 1, i + 1)
for i in range(1, 10)}
assert dict(ts.moving_average(0.5, 2)) == {
1 + i / 2.: ts2.mean(1 + i / 2. - 1, 1 + i / 2. + 1)
for i in range(0, 17)
}
ts = TimeSeries([[1, 2], [2, 3], [6, 1], [8, 4]],
domain=Domain([1, 2], [3, 5], [6, 8]))
nose.tools.assert_raises(NotImplementedError, ts.moving_average, 1, 0.5)
