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fix: set required columns to be all curve columns
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Required columns are necessary for all curve plot types. The required
columns for any curve plot are wind_speed, power, pitch and rpm
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@samuelwnaylor
samuelwnaylor committed Dec 3, 2024
1 parent 173f074 commit e6eefe7
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Showing 3 changed files with 134 additions and 94 deletions.
5 changes: 3 additions & 2 deletions examples/smarteole_example.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -62,7 +62,8 @@
"import logging\n",
"import re\n",
"\n",
"from IPython.display import Markdown, display\n",
"from IPython.display import Markdown\n",
"from IPython.display import display as ipy_display\n",
"\n",
"logging.basicConfig(format=\"%(message)s\", level=logging.INFO)\n",
"\n",
Expand All @@ -72,7 +73,7 @@
" message = self.format(record)\n",
" # Replace newline characters with <br> tags\n",
" message = re.sub(r\"\\n\", \"<br>\", message)\n",
" display(Markdown(message))\n",
" ipy_display(Markdown(message))\n",
"\n",
"\n",
"logger = logging.getLogger()\n",
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184 changes: 102 additions & 82 deletions tests/test_ops_curve_shift.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,103 +10,120 @@
CurveShiftInput,
CurveShiftOutput,
CurveTypes,
OpsCurveRequiredColumns,
calculate_curve_shift,
check_for_ops_curve_shift,
)


@pytest.fixture
def fake_power_curve_df() -> pd.DataFrame:
return pd.DataFrame(
{
"wind_speed": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14],
"power": [0, 0, np.nan, 1, 3, 6, 10, 15, 22, 30, 36, 39, 40, 40, 40],
}
).set_index("power")
def fake_required_columns() -> OpsCurveRequiredColumns:
return OpsCurveRequiredColumns(wind_speed="wind_speed", power="power", rpm="gen_rpm", pitch="pitch")


@pytest.fixture
def fake_gen_rpm_curve_df() -> pd.DataFrame:
def fake_curve_df(fake_required_columns: OpsCurveRequiredColumns) -> pd.DataFrame:
return pd.DataFrame(
{
"wind_speed": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14],
"gen_rpm": [900, 900, 850, 875, 900, 1000, 1100, 1200, 1350, 1500, 1600, 1600, 1600, 1600, 1600],
}
).set_index("gen_rpm")


@pytest.fixture
def fake_pitch_curve_df() -> pd.DataFrame:
return pd.DataFrame(
{
"wind_speed": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14],
"pitch": [4, 4, 4, 3, 2, 1, 1, 1, 2, 5, 8, 11, 13, 14, 15],
fake_required_columns.wind_speed: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14],
fake_required_columns.power: [0, 0, np.nan, 1, 3, 6, 10, 15, 22, 30, 36, 39, 40, 40, 40],
fake_required_columns.rpm: [
900,
900,
850,
875,
900,
1000,
1100,
1200,
1350,
1500,
1600,
1600,
1600,
1600,
1600,
],
fake_required_columns.pitch: [4, 4, 4, 3, 2, 1, 1, 1, 2, 5, 8, 11, 13, 14, 15],
}
).set_index("pitch")
)


class TestCurveShiftInput:
@staticmethod
def test_acceptable_inputs(fake_power_curve_df: pd.DataFrame) -> None:
def test_acceptable_inputs(fake_curve_df: pd.DataFrame, fake_required_columns: OpsCurveRequiredColumns) -> None:
_input = CurveShiftInput(
turbine_name="anything",
pre_df=fake_power_curve_df.reset_index(),
post_df=fake_power_curve_df.reset_index(),
pre_df=fake_curve_df,
post_df=fake_curve_df,
curve_config=CurveConfig(
name=CurveTypes.POWER_CURVE.value,
x_col="wind_speed",
y_col="power",
x_col=fake_required_columns.wind_speed,
y_col=fake_required_columns.power,
x_bin_width=1,
warning_threshold=0.01,
),
ops_curve_required_columns=fake_required_columns,
)

@pytest.mark.parametrize("column_name", ["wind_speed", "power"])
def test_missing_column_in_pre_df(self, column_name: str, fake_power_curve_df: pd.DataFrame) -> None:
with pytest.raises(IndexError, match="Column name missing in dataframe"):
def test_missing_column_in_pre_df(
self, column_name: str, fake_curve_df: pd.DataFrame, fake_required_columns: OpsCurveRequiredColumns
) -> None:
with pytest.raises(IndexError, match=f"'{column_name}' column name missing in pre-dataframe"):
CurveShiftInput(
turbine_name="anything",
pre_df=fake_power_curve_df.reset_index().drop(columns=column_name),
post_df=(fake_power_curve_df + 2).reset_index(),
pre_df=fake_curve_df.drop(columns=column_name),
post_df=(fake_curve_df + 2),
curve_config=CurveConfig(
name=CurveTypes.POWER_CURVE.value,
x_col="wind_speed",
y_col="power",
x_col=fake_required_columns.wind_speed,
y_col=fake_required_columns.power,
x_bin_width=1,
warning_threshold=0.01,
),
ops_curve_required_columns=fake_required_columns,
)

@pytest.mark.parametrize("column_name", ["wind_speed", "power"])
def test_missing_column_in_post_df(self, column_name: str, fake_power_curve_df: pd.DataFrame) -> None:
with pytest.raises(IndexError, match="Column name missing in dataframe"):
def test_missing_column_in_post_df(
self, column_name: str, fake_curve_df: pd.DataFrame, fake_required_columns: OpsCurveRequiredColumns
) -> None:
with pytest.raises(IndexError, match=f"'{column_name}' column name missing in post-dataframe"):
CurveShiftInput(
turbine_name="anything",
pre_df=fake_power_curve_df.reset_index(),
post_df=(fake_power_curve_df + 2).reset_index().drop(columns=column_name),
pre_df=fake_curve_df,
post_df=(fake_curve_df + 2).drop(columns=column_name),
curve_config=CurveConfig(
name=CurveTypes.POWER_CURVE.value,
x_col="wind_speed",
y_col="power",
x_col=fake_required_columns.wind_speed,
y_col=fake_required_columns.power,
x_bin_width=1,
warning_threshold=0.01,
),
ops_curve_required_columns=fake_required_columns,
)


@pytest.mark.parametrize(
("shift_amount", "expected"),
[
pytest.param(2.0, -0.21557719054241997, id="shift DOES exceed threshold"),
pytest.param(0.05, -0.006954837573730166, id="shift DOES NOT exceed threshold"),
pytest.param(0.0, 0.0, id="zero"),
pytest.param(2.0, -0.1376912378303199, id="shift DOES exceed threshold"),
pytest.param(0.05, -0.004489831851395176, id="shift DOES NOT exceed threshold"),
],
)
def test_calculate_power_curve_shift(shift_amount: float, expected: float, fake_power_curve_df: pd.DataFrame) -> None:
def test_calculate_power_curve_shift(
shift_amount: float, expected: float, fake_curve_df: pd.DataFrame, fake_required_columns: OpsCurveRequiredColumns
) -> None:
curve_shift_input = CurveShiftInput(
turbine_name="anything",
pre_df=fake_power_curve_df.reset_index(),
post_df=(fake_power_curve_df + shift_amount).reset_index(),
curve_config=CurveConfig(name=CurveTypes.POWER_CURVE, x_col="wind_speed", y_col="power"),
pre_df=fake_curve_df,
post_df=(fake_curve_df + shift_amount),
curve_config=CurveConfig(
name=CurveTypes.POWER_CURVE, x_col=fake_required_columns.wind_speed, y_col=fake_required_columns.power
),
ops_curve_required_columns=fake_required_columns,
)
# check that CurveShiftInput pydantic model has removed NaNs
assert not curve_shift_input.pre_df.isna().to_numpy().any()
Expand All @@ -119,21 +136,26 @@ def test_calculate_power_curve_shift(shift_amount: float, expected: float, fake_
@pytest.mark.parametrize(
("shift_amount", "expected"),
[
pytest.param(0.2, -0.00712694877505593, id="shift DOES exceed threshold"),
pytest.param(0.1, -0.0033534540576795058, id="shift DOES NOT exceed threshold"),
pytest.param(0.2, -0.00865091569970633, id="shift DOES exceed threshold"),
pytest.param(0.1, -0.004926790475744736, id="shift DOES NOT exceed threshold"),
],
)
def test_calculate_rpm_curve_shift(
shift_amount: float, expected: float, fake_gen_rpm_curve_df: pd.DataFrame, caplog: pytest.LogCaptureFixture
shift_amount: float,
expected: float,
fake_curve_df: pd.DataFrame,
fake_required_columns: OpsCurveRequiredColumns,
caplog: pytest.LogCaptureFixture,
) -> None:
with caplog.at_level(logging.WARNING):
actual = calculate_curve_shift(
curve_shift_input=CurveShiftInput(
turbine_name="anything",
pre_df=fake_gen_rpm_curve_df.reset_index(),
post_df=(fake_gen_rpm_curve_df + shift_amount).reset_index(),
pre_df=fake_curve_df,
post_df=(fake_curve_df + shift_amount),
curve_config=CurveConfig(name=CurveTypes.RPM, x_col="wind_speed", y_col="gen_rpm"),
)
ops_curve_required_columns=fake_required_columns,
),
)

np.testing.assert_almost_equal(actual=actual.value, desired=expected)
Expand All @@ -142,17 +164,23 @@ def test_calculate_rpm_curve_shift(
@pytest.mark.parametrize(
("shift_amount", "expected"),
[
pytest.param(0.14, -0.1026666666666678, id="shift DOES exceed threshold"),
pytest.param(0.13, -0.09533333333333438, id="shift DOES NOT exceed threshold"),
pytest.param(0.0, 0.0, id="zero"),
pytest.param(0.6, 0.10714285714285765, id="shift DOES exceed threshold"),
pytest.param(0.5, 0.08928571428571441, id="shift DOES NOT exceed threshold"),
],
)
def test_calculate_pitch_curve_shift(shift_amount: float, expected: float, fake_pitch_curve_df: pd.DataFrame) -> None:
def test_calculate_pitch_curve_shift(
shift_amount: float, expected: float, fake_curve_df: pd.DataFrame, fake_required_columns: OpsCurveRequiredColumns
) -> None:
actual = calculate_curve_shift(
curve_shift_input=CurveShiftInput(
turbine_name="anything",
pre_df=fake_pitch_curve_df.reset_index(),
post_df=(fake_pitch_curve_df + shift_amount).reset_index(),
curve_config=CurveConfig(name=CurveTypes.PITCH, x_col="wind_speed", y_col="pitch"),
pre_df=fake_curve_df,
post_df=(fake_curve_df + shift_amount),
curve_config=CurveConfig(
name=CurveTypes.PITCH, x_col=fake_required_columns.wind_speed, y_col=fake_required_columns.pitch
),
ops_curve_required_columns=fake_required_columns,
)
)

Expand All @@ -162,19 +190,23 @@ def test_calculate_pitch_curve_shift(shift_amount: float, expected: float, fake_
@pytest.mark.parametrize(
("shift_amount", "expected"),
[
pytest.param(2.0, 0.21296296296296302, id="shift DOES exceed threshold"),
pytest.param(0.05, -0.03981481481481486, id="shift DOES NOT exceed threshold"),
pytest.param(2.0, 0.13811720414537776, id="shift DOES exceed threshold"),
pytest.param(0.0, -0.04629629629629639, id="shift DOES NOT exceed threshold"),
],
)
def test_calculate_wind_speed_curve_shift(
shift_amount: float, expected: float, fake_power_curve_df: pd.DataFrame
shift_amount: float, expected: float, fake_curve_df: pd.DataFrame, fake_required_columns: OpsCurveRequiredColumns
) -> None:
_df = fake_curve_df.copy()
actual = calculate_curve_shift(
curve_shift_input=CurveShiftInput(
turbine_name="anything",
pre_df=fake_power_curve_df.reset_index(),
post_df=(fake_power_curve_df + shift_amount).reset_index(),
curve_config=CurveConfig(name=CurveTypes.WIND_SPEED, x_col="power", y_col="wind_speed"),
pre_df=_df,
post_df=(_df + shift_amount),
curve_config=CurveConfig(
name=CurveTypes.WIND_SPEED, x_col=fake_required_columns.power, y_col=fake_required_columns.wind_speed
),
ops_curve_required_columns=fake_required_columns,
)
)

Expand All @@ -199,18 +231,9 @@ def test_missing_required_column(
self,
pre_df_or_post_df: str,
missing_column: str,
fake_power_curve_df: pd.DataFrame,
fake_gen_rpm_curve_df: pd.DataFrame,
fake_pitch_curve_df: pd.DataFrame,
fake_curve_df: pd.DataFrame,
) -> None:
_df = pd.concat(
[
fake_power_curve_df.reset_index().set_index("wind_speed"),
fake_gen_rpm_curve_df.reset_index().set_index("wind_speed"),
fake_pitch_curve_df.reset_index().set_index("wind_speed"),
],
axis=1,
).reset_index()
_df = fake_curve_df.copy()

pre_df = _df.drop(columns=missing_column) if pre_df_or_post_df == "pre" else _df
post_df = _df.drop(columns=missing_column) if pre_df_or_post_df == "post" else _df
Expand Down Expand Up @@ -238,16 +261,9 @@ def test_missing_required_column(
assert actual == expected

def test_calls_funcs_as_intended(
self, fake_power_curve_df: pd.DataFrame, fake_gen_rpm_curve_df: pd.DataFrame, fake_pitch_curve_df: pd.DataFrame
self, fake_curve_df: pd.DataFrame, fake_required_columns: OpsCurveRequiredColumns
) -> None:
_df = pd.concat(
[
fake_power_curve_df.reset_index().set_index("wind_speed"),
fake_gen_rpm_curve_df.reset_index().set_index("wind_speed"),
fake_pitch_curve_df.reset_index().set_index("wind_speed"),
],
axis=1,
).reset_index()
_df = fake_curve_df.copy()

wtg_name = "anything"

Expand Down Expand Up @@ -279,24 +295,28 @@ def test_calls_funcs_as_intended(
turbine_name=wtg_name,
pre_df=_df,
post_df=_df,
ops_curve_required_columns=fake_required_columns,
curve_config=CurveConfig(name=CurveTypes.POWER_CURVE, x_col="wind_speed", y_col="power"),
)
curve_input_rpm = CurveShiftInput(
turbine_name=wtg_name,
pre_df=_df,
post_df=_df,
ops_curve_required_columns=fake_required_columns,
curve_config=CurveConfig(name=CurveTypes.RPM, x_col="power", y_col="gen_rpm"),
)
curve_input_pitch = CurveShiftInput(
turbine_name=wtg_name,
pre_df=_df,
post_df=_df,
ops_curve_required_columns=fake_required_columns,
curve_config=CurveConfig(name=CurveTypes.PITCH, x_col="wind_speed", y_col="pitch"),
)
curve_input_wind_speed = CurveShiftInput(
turbine_name=wtg_name,
pre_df=_df,
post_df=_df,
ops_curve_required_columns=fake_required_columns,
curve_config=CurveConfig(name=CurveTypes.WIND_SPEED, x_col="power", y_col="wind_speed"),
)
_call_inputs_list = [curve_input_power, curve_input_rpm, curve_input_pitch, curve_input_wind_speed]
Expand Down
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