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Forward fill and Power/Energy processes: use start_dt timezone #264

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Merged
lafrech merged 1 commit into from
Jun 3, 2025
+125 −0
Merged

Forward fill and Power/Energy processes: use start_dt timezone #264

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6 changes: 6 additions & 0 deletions src/bemserver_core/process/energy_power.py
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Original file line number Diff line number Diff line change
Expand Up @@ -58,6 +58,8 @@ def energy2power(
convert_to,
):
"""Convert energy to power"""
timezone = start_dt.tzinfo
end_dt = end_dt.astimezone(timezone)

interval = energy_ts.get_property_value("Interval")
if interval is None:
Expand All @@ -71,6 +73,7 @@ def energy2power(
end_dt,
(energy_ts,),
data_state,
timezone=str(timezone),
)[energy_ts.id]

# Power = Energy / Time
Expand All @@ -93,13 +96,16 @@ def energyindex2power(
convert_to,
):
"""Convert energy index to power"""
timezone = start_dt.tzinfo
end_dt = end_dt.astimezone(timezone)

# Get energy index values
index_s = tsdio.get_timeseries_data(
start_dt,
end_dt,
(index_ts,),
data_state,
timezone=str(timezone),
)[index_ts.id]

# Compute energy as diff, with a 0 min for index rollover or meter change
Expand Down
3 changes: 3 additions & 0 deletions src/bemserver_core/process/forward_fill.py
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Original file line number Diff line number Diff line change
Expand Up @@ -18,6 +18,8 @@ def ffill(
bucket_width_unit,
):
"""Forward fill process"""
timezone = start_dt.tzinfo
end_dt = end_dt.astimezone(timezone)

# Define expected index
start_dt = ceil(start_dt, bucket_width_unit, bucket_width_value)
Expand All @@ -41,6 +43,7 @@ def ffill(
end_dt,
timeseries,
data_state,
timezone=str(timezone),
)

# For each TS, set last value before time interval as first value for interval
Expand Down
88 changes: 88 additions & 0 deletions tests/process/test_energy_power.py
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Original file line number Diff line number Diff line change
@@ -1,6 +1,7 @@
"""Energy <=> Power conversions tests"""

import datetime as dt
from zoneinfo import ZoneInfo

import pytest

Expand Down Expand Up @@ -153,6 +154,35 @@ def test_power2energy_process(self, users, timeseries):
)
assert_series_equal(data_s, expected_data_s)

# Check result is in start_dt timezone
data_s = power2energy(
start_dt.astimezone(ZoneInfo("Europe/Paris")),
h4_dt,
ts_0,
ds_1,
1800,
"Wh",
)
timestamps = sum(
[
[
dt.datetime(
2020, 1, 1, hour, 0, tzinfo=dt.timezone.utc
).astimezone(ZoneInfo("Europe/Paris")),
dt.datetime(
2020, 1, 1, hour, 30, tzinfo=dt.timezone.utc
).astimezone(ZoneInfo("Europe/Paris")),
]
for hour in (0, 1, 2, 3)
],
[],
)
expected_data_s = pd.Series(
[0.0, 0.0, 0.5, 0.5, 0.0, 0.0, 0.5, 0.5],
index=pd.DatetimeIndex(timestamps, name="timestamp", freq="1800s"),
)
assert_series_equal(data_s, expected_data_s)

with pytest.raises(BEMServerCoreUndefinedUnitError):
data_s = power2energy(start_dt, h4_dt, ts_0, ds_1, 3600, "dummy")

Expand Down Expand Up @@ -283,6 +313,22 @@ def test_energy2power_process(self, users, timeseries):
):
data_s = energy2power(start_dt, end_dt, ts_4, ds_1, "W")

# Check result is in start_dt timezone
data_s = energy2power(
start_dt.astimezone(ZoneInfo("Europe/Paris")), h4_dt, ts_0, ds_1, "W"
)
timestamps = [
dt.datetime(2020, 1, 1, hour, 0, tzinfo=dt.timezone.utc).astimezone(
ZoneInfo("Europe/Paris")
)
for hour in (0, 1, 2, 3)
]
expected_data_s = pd.Series(
[0.0, 1.0, 0.0, 1.0],
index=pd.DatetimeIndex(timestamps, name="timestamp"),
)
assert_series_equal(data_s, expected_data_s)

with pytest.raises(BEMServerCoreUndefinedUnitError):
data_s = energy2power(start_dt, end_dt, ts_0, ds_1, "dummy")

Expand Down Expand Up @@ -410,6 +456,27 @@ def test_energyindex2power_process(self, users, timeseries):
)
assert_series_equal(data_s, expected_data_s)

# Check result is in start_dt timezone
data_s = energyindex2power(
start_dt.astimezone(ZoneInfo("Europe/Paris")),
h6_dt,
ts_0,
ds_1,
3600,
"W",
)
timestamps = [
dt.datetime(2020, 1, 1, hour, 0, tzinfo=dt.timezone.utc).astimezone(
ZoneInfo("Europe/Paris")
)
for hour in (0, 1, 2, 3, 4, 5)
]
expected_data_s = pd.Series(
[1.0, 3.0, 5.0, 7.0, 9.0, np.nan],
index=pd.DatetimeIndex(timestamps, name="timestamp", freq="h"),
)
assert_series_equal(data_s, expected_data_s)

with pytest.raises(BEMServerCoreUndefinedUnitError):
data_s = energyindex2power(start_dt, end_dt, ts_0, ds_1, 3600, "dummy")

Expand Down Expand Up @@ -537,6 +604,27 @@ def test_energyindex2energy_process(self, users, timeseries):
)
assert_series_equal(data_s, expected_data_s)

# Check result is in start_dt timezone
data_s = energyindex2energy(
start_dt.astimezone(ZoneInfo("Europe/Paris")),
h6_dt,
ts_0,
ds_1,
3600,
"Wh",
)
timestamps = [
dt.datetime(2020, 1, 1, hour, 0, tzinfo=dt.timezone.utc).astimezone(
ZoneInfo("Europe/Paris")
)
for hour in (0, 1, 2, 3, 4, 5)
]
expected_data_s = pd.Series(
[1.0, 3.0, 5.0, 7.0, 9.0, np.nan],
index=pd.DatetimeIndex(timestamps, name="timestamp", freq="h"),
)
assert_series_equal(data_s, expected_data_s)

with pytest.raises(BEMServerCoreUndefinedUnitError):
data_s = energyindex2energy(start_dt, end_dt, ts_0, ds_1, 3600, "dummy")

Expand Down
28 changes: 28 additions & 0 deletions tests/process/test_forward_fill.py
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Original file line number Diff line number Diff line change
@@ -1,6 +1,7 @@
"""Forward fill tests"""

import datetime as dt
from zoneinfo import ZoneInfo

import pytest

Expand Down Expand Up @@ -113,3 +114,30 @@ def test_ffill_process(self, users, timeseries):
)
expected_data_df.columns = [ts_3.id, ts_2.id, ts_2.id, ts_0.id]
assert_frame_equal(data_df, expected_data_df)

# Check result is in start_dt timezone
ts_l = (ts_0, ts_1, ts_2, ts_3)

data_df = ffill(
h4_dt.astimezone(ZoneInfo("Europe/Paris")),
end_dt,
ts_l,
ds_1,
2,
"hour",
)

timestamps = [
dt.datetime(2020, 1, 1, hour, 0, tzinfo=ZoneInfo("Europe/Paris"))
for hour in (6, 7, 8, 10, 12)
]
expected_data_df = pd.DataFrame(
{
ts_0.id: [1.0, np.nan, 1.0, 1.0, 1.0],
ts_1.id: [0.0, 6.0, 6.0, 9.0, 9.0],
ts_2.id: [np.nan, 42.0, 42.0, 42.0, 42.0],
ts_3.id: [np.nan, np.nan, np.nan, np.nan, np.nan],
},
index=pd.DatetimeIndex(timestamps, name="timestamp"),
)
assert_frame_equal(data_df, expected_data_df)
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