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- from datetime import timedelta
- import pint.errors
- import pytest
- import pandas as pd
- import timely_beliefs as tb
- from flexmeasures.utils.unit_utils import (
- convert_units,
- determine_flow_unit,
- determine_stock_unit,
- determine_unit_conversion_multiplier,
- units_are_convertible,
- is_energy_unit,
- is_power_unit,
- ur,
- )
- @pytest.mark.parametrize(
- "from_unit, to_unit, expected_multiplier, expected_values",
- [
- ("%", "‰", 10, None),
- ("m/s", "km/h", 3.6, None),
- ("m³/h", "l/h", 1000, None),
- ("m³", "m³/h", 4, None),
- ("MW", "kW", 1000, None),
- ("%", "kWh", 0.5, None), # i.e. 1% of 50 kWh (the capacity used in the test)
- ("kWh", "%", 2, None), # i.e. 1 kWh = 2% of 50 kWh
- ("kWh", "kW", 4, None),
- ("kW", "kWh", 1 / 4, None),
- ("-W", "W", -1, None),
- ("l/(100km)", "l/km", 0.01, None),
- ("°C", "K", None, [273.15, 283.15, 284.15]),
- # no support for combining an offset unit with a scaling factor, but this is also overly specific
- # ("-°C", "K", None, [273.15, 263.15, 262.15]),
- # ("l/(10°C)", "l/(°C)", 0.1, None),
- ],
- )
- def test_convert_unit(
- from_unit,
- to_unit,
- expected_multiplier,
- expected_values,
- ):
- """Check some common unit conversions.
- Note that for the above expectations:
- - conversion from kWh to kW, and from m³ to m³/h, both depend on the event resolution set below
- - conversion from °C to K depends on the data values set below
- """
- data = pd.Series([0, 10.0, 11.0])
- converted_data: pd.Series = convert_units(
- data=data,
- from_unit=from_unit,
- to_unit=to_unit,
- event_resolution=timedelta(minutes=15),
- capacity="50 kWh",
- )
- if expected_multiplier is not None:
- expected_data = data * expected_multiplier
- else:
- expected_data = pd.Series(expected_values)
- pd.testing.assert_series_equal(converted_data, expected_data)
- @pytest.mark.parametrize(
- "from_unit, to_unit, timezone, input_values, expected_values",
- [
- # datetimes are converted to seconds since UNIX epoch
- (
- "datetime",
- "s",
- None,
- ["1970-01-01", "1970-01-02", "1970-01-03"],
- [0, 60 * 60 * 24, 60 * 60 * 48],
- ),
- # nothing overflows for the next 100 years
- (
- "datetime",
- "s",
- None,
- ["2123-05-02", "2123-05-03", "2123-05-04"],
- [4838659200, 4838659200 + 60 * 60 * 24, 4838659200 + 60 * 60 * 48],
- ),
- # Same as above, but day precedes month in input
- (
- "dayfirst datetime",
- "s",
- None,
- ["02-05-2123", "03-05-2123", "04-05-2123"],
- [4838659200, 4838659200 + 60 * 60 * 24, 4838659200 + 60 * 60 * 48],
- ),
- # Localize timezone-naive datetimes to UTC in case there is no sensor information available
- (
- "datetime",
- "s",
- None,
- ["2023-05-02 00:00:01", "2023-05-02 00:00:02", "2023-05-02 00:00:03"],
- [1682985601, 1682985602, 1682985603],
- ),
- # Localize timezone-naive datetimes to sensor's timezone in case that is available
- (
- "datetime",
- "s",
- "Europe/Amsterdam",
- ["2023-05-02 00:00:01", "2023-05-02 00:00:02", "2023-05-02 00:00:03"],
- [
- 1682985601 - 60 * 60 * 2,
- 1682985602 - 60 * 60 * 2,
- 1682985603 - 60 * 60 * 2,
- ],
- ),
- # Timezone-aware datetimes work don't require localization
- (
- "datetime",
- "s",
- None,
- [
- "2023-05-02 00:00:01 +02:00",
- "2023-05-02 00:00:02 +02:00",
- "2023-05-02 00:00:03 +02:00",
- ],
- [
- 1682985601 - 60 * 60 * 2,
- 1682985602 - 60 * 60 * 2,
- 1682985603 - 60 * 60 * 2,
- ],
- ),
- # Timezone-aware datetimes also means that the sensor timezone is irrelevant
- (
- "datetime",
- "s",
- "Asia/Seoul",
- [
- "2023-05-02 00:00:01 +02:00",
- "2023-05-02 00:00:02 +02:00",
- "2023-05-02 00:00:03 +02:00",
- ],
- [
- 1682985601 - 60 * 60 * 2,
- 1682985602 - 60 * 60 * 2,
- 1682985603 - 60 * 60 * 2,
- ],
- ),
- # Timedeltas can be converted to units of time
- ("timedelta", "s", None, ["1 minute", "1 minute 2 seconds"], [60.0, 62.0]),
- # Convertible timedeltas include absolute days of 24 hours
- ("timedelta", "d", None, ["1 day", "1 day 12 hours"], [1.0, 1.5]),
- # Convertible timedeltas exclude nominal durations like month or year, which cannot be represented as a datetime.timedelta object
- # ("timedelta", "d", None, ["1 month", "1 year"], [30., 365.]), # fails
- ],
- )
- def test_convert_special_unit(
- from_unit,
- to_unit,
- timezone,
- input_values,
- expected_values,
- ):
- """Check some special unit conversions."""
- data = pd.Series(input_values)
- if timezone:
- data.sensor = tb.Sensor("test", timezone=timezone)
- converted_data: pd.Series = convert_units(
- data=data,
- from_unit=from_unit,
- to_unit=to_unit,
- )
- print(converted_data)
- expected_data = pd.Series(expected_values)
- print(expected_data)
- pd.testing.assert_series_equal(converted_data, expected_data)
- @pytest.mark.parametrize(
- "unit, time_unit, expected_unit",
- [
- ("m³", None, "m³/h"),
- ("kWh", None, "kW"),
- ("km", "h", "km/h"),
- ("m", "s", "m/s"),
- ],
- )
- def test_determine_flow_unit(
- unit,
- time_unit,
- expected_unit,
- ):
- if time_unit is None:
- assert determine_flow_unit(unit) == expected_unit
- else:
- assert determine_flow_unit(unit, time_unit) == expected_unit
- @pytest.mark.parametrize(
- "unit, time_unit, expected_unit",
- [
- ("m³/h", None, "m³"),
- ("km³/h", None, "km³"),
- # ("hm³/h", None, "hm³"), # todo: uncomment after switching to decimal unit registry
- ("kW", None, "kWh"),
- ("m/s", "s", "m"),
- ("m/s", "h", "km"),
- ("t/h", None, "t"),
- ],
- )
- def test_determine_stock_unit(
- unit,
- time_unit,
- expected_unit,
- ):
- if time_unit is None:
- assert determine_stock_unit(unit) == expected_unit
- else:
- assert determine_stock_unit(unit, time_unit) == expected_unit
- def test_determine_unit_conversion_multiplier():
- assert determine_unit_conversion_multiplier("kW", "W") == 1000
- assert determine_unit_conversion_multiplier("J/s", "W") == 1
- assert determine_unit_conversion_multiplier("Wh", "W", timedelta(minutes=10)) == 6
- assert determine_unit_conversion_multiplier("kWh", "MJ") == 3.6
- with pytest.raises(pint.errors.OffsetUnitCalculusError):
- # Not a conversion that can be specified as a multiplication
- determine_unit_conversion_multiplier("°C", "K")
- def test_h_denotes_hour_and_not_planck_constant():
- assert ur.Quantity("h").dimensionality == ur.Quantity("hour").dimensionality
- assert (
- ur.Quantity("hbar").dimensionality
- == ur.Quantity("planck_constant").dimensionality
- )
- def test_units_are_convertible():
- assert units_are_convertible("kW", "W") # units just have different prefixes
- assert units_are_convertible(
- "J/s", "W"
- ) # units can be converted using some multiplier
- assert units_are_convertible(
- "Wh", "W"
- ) # units that represent a stock delta can, knowing the duration, be converted to a flow
- assert units_are_convertible("toe", "W") # tonne of oil equivalent
- assert units_are_convertible("°C", "K") # offset unit to absolute unit
- assert not units_are_convertible("°C", "W")
- assert not units_are_convertible("EUR/MWh", "W")
- assert not units_are_convertible("not-a-unit", "W")
- @pytest.mark.parametrize(
- "unit, power_unit",
- [
- ("EUR/MWh", False),
- ("KRW/kWh", False),
- ("kWh", False),
- ("kW", True),
- ("watt", True),
- ("°C", False),
- ("", False),
- ("not-a-unit", False),
- ("#", False),
- ],
- )
- def test_is_power_unit(unit: str, power_unit: bool):
- assert is_power_unit(unit) is power_unit
- @pytest.mark.parametrize(
- "unit, energy_unit",
- [
- ("EUR/MWh", False),
- ("KRW/kWh", False),
- ("kWh", True),
- ("kW", False),
- ("watthour", True),
- ("°C", False),
- ("", False),
- ("not-a-unit", False),
- ],
- )
- def test_is_energy_unit(unit: str, energy_unit: bool):
- assert is_energy_unit(unit) is energy_unit
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