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Use last element as end time #58

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merged 2 commits into from
Nov 1, 2024
Merged

Use last element as end time #58

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ca4f826
Use last element as end time
magnusuMET Nov 1, 2024
d14a17f
Fix type comparison error
magnusuMET Nov 1, 2024
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2 changes: 1 addition & 1 deletion src/pyaro/timeseries/Filter.py
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Original file line number Diff line number Diff line change
Expand Up @@ -614,7 +614,7 @@ def envelope(self) -> tuple[datetime, datetime]:
end = datetime.min
for s, e in self._start_include + self._startend_include + self._end_include:
start = min(start, s)
end = max(end, s)
end = max(end, e)
Comment on lines 613 to +616
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@avaldebe avaldebe Nov 1, 2024 •
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Is this the cleanest way to set the start/end
Also, why is does start depends on self._end_include and end depends on self._start_include?

maybe itertools.chain can improve the readability

from itertools import chain
[...]
        if self._start_include or self._startend_include:
            start = min(s for s, e in chain(self._start_include, self._startend_include))
        else:
            start = datetime.max

        if self._end_include or self._startend_include:
            end = max(e for s, e in chain(self._end_include, self._startend_include))
        else:
            end = datetime.min

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I don't think the chain-version is very readable here.

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I don't think the chain-version is very readable here.

Yes, at the cost of creating new lists this could be written on a simpler way

        if self._start_include or self._startend_include:
            start = min(s for s, e in self._start_include + self._startend_include)
        else:
            start = datetime.max

        if self._end_include or self._startend_include:
            end = max(e for s, e in self._end_include + self._startend_include)
        else:
            end = datetime.min

In any case, my question still stands

Also, why is does start depends on self._end_include and end depends on self._start_include?

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The tuple values of (start, end) are the time-ranges of the filter, while start_include/end_include refer to measurements starttime/endtime.

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Thanks, very well that you also included a test.

if end < start:
raise TimeBoundsException(
f"TimeBoundsEnvelope end < start: {end} < {start}"
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11 changes: 11 additions & 0 deletions tests/test_timefilter.py
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Original file line number Diff line number Diff line change
@@ -0,0 +1,11 @@
from datetime import datetime

from pyaro.timeseries.Filter import TimeBoundsFilter


def test_timemax():
bounds = TimeBoundsFilter(start_include=[("2023-01-01 00:00:00", "2024-01-01 00:00:00")])

envelope = bounds.envelope()
assert envelope[0] == datetime.fromisoformat("2023-01-01 00:00:00")
assert envelope[1] == datetime.fromisoformat("2024-01-01 00:00:00")