Skip to content

Commit

Permalink
update test_find_contiguous_t0_periods_nwp
Browse files Browse the repository at this point in the history
  • Loading branch information
@AUdaltsova
AUdaltsova committed Aug 13, 2024
1 parent e5cb0ab commit 1225963
Showing 1 changed file with 25 additions and 16 deletions.
41 changes: 25 additions & 16 deletions tests/select/test_find_contiguous_t0_time_periods.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -62,13 +62,11 @@ def test_find_contiguous_t0_time_periods_nwp():
[
"2023-01-01 05:00",
"2023-01-02 05:00",
"2023-01-02 14:00",
]
),
"end_dt": pd.to_datetime(
[
"2023-01-01 21:00",
"2023-01-02 12:00",
"2023-01-03 06:00",
]
),
Expand All @@ -79,14 +77,12 @@ def test_find_contiguous_t0_time_periods_nwp():
"start_dt": pd.to_datetime(
[
"2023-01-01 05:00",
"2023-01-01 11:00",
"2023-01-02 05:00",
"2023-01-02 14:00",
]
),
"end_dt": pd.to_datetime(
[
"2023-01-01 09:00",
"2023-01-01 18:00",
"2023-01-02 09:00",
"2023-01-03 03:00",
Expand All @@ -100,28 +96,40 @@ def test_find_contiguous_t0_time_periods_nwp():
[
"2023-01-01 05:00",
"2023-01-01 11:00",
"2023-01-01 14:00",
"2023-01-02 05:00",
"2023-01-02 14:00",
"2023-01-02 17:00",
"2023-01-02 20:00",
"2023-01-02 23:00",
]
),
"end_dt": pd.to_datetime(
[
"2023-01-01 06:00",
"2023-01-01 12:00",
"2023-01-01 15:00",
"2023-01-02 06:00",
"2023-01-02 15:00",
"2023-01-02 18:00",
"2023-01-02 21:00",
"2023-01-03 00:00",
]
),
},
),
pd.DataFrame(
{
"start_dt": pd.to_datetime(
[
"2023-01-01 06:00",
"2023-01-01 12:00",
"2023-01-02 06:00",
"2023-01-02 15:00",
]
),
"end_dt": pd.to_datetime(
[
"2023-01-01 09:00",
"2023-01-01 18:00",
"2023-01-02 09:00",
"2023-01-03 03:00",
]
),
},
),
]

# Create 3-hourly init times with a few time stamps missing
Expand All @@ -131,21 +139,22 @@ def test_find_contiguous_t0_time_periods_nwp():
pd.date_range("2023-01-01 03:00", "2023-01-02 21:00", freq=freq)
.delete([1, 4, 5, 6, 7, 9, 10])
)
steps = pd.to_timedelta(range(24), unit="h")

# Choose some history durations and max stalenesses
history_durations_hr = [0, 2, 2, 2]
max_stalenesses_hr = [9, 9, 6, 3]
history_durations_hr = [0, 2, 2, 2, 2]
max_stalenesses_hr = [9, 9, 6, 3, 6]
max_dropouts_hr = [0, 0, 0, 0, 3]

for i in range(len(expected_results)):
history_duration = pd.Timedelta(history_durations_hr[i], "h")
max_staleness = pd.Timedelta(max_stalenesses_hr[i], "h")
max_dropout = pd.Timedelta(max_dropouts_hr[i], "h")

time_periods = find_contiguous_t0_periods_nwp(
datetimes=datetimes,
history_duration=history_duration,
max_staleness=max_staleness,
max_dropout = pd.Timedelta(0),
max_dropout=max_dropout,
)

# Check if results are as expected
Expand Down

0 comments on commit 1225963

Please sign in to comment.