preprocessing.exog_providers.EntsoeDayAheadPriceProvider

preprocessing.exog_providers.EntsoeDayAheadPriceProvider(
    data_home=None,
    max_gap=0,
    max_tail_gap=0,
    provider_window=None,
)

ENTSO-E day-ahead spot price (DE/LU) as an exogenous input.

Reads interim/day_ahead_price.csv via spotforecast2_safe.data.fetch_data.load_day_ahead_price. The day-ahead auction price is published on D-1 and is leakage-clean at forecast time; the realised price must never be used.

Parameters

Name	Type	Description	Default
data_home	`DataHome`	Root data directory forwarded to the loader.	`None`
max_gap	int	Maximum contiguous missing-value run healed by `_align_to_index`. See `_align_to_index` for full semantics. Defaults to `0`.	`0`
max_tail_gap	int	Extended healing budget for the trailing-edge NaN run. See `_align_to_index`. Defaults to `0`.	`0`
provider_window	Optional[pd.DatetimeIndex]	Validation index passed to `_align_to_index` as validate_index. See `_align_to_index`. Defaults to `None`.	`None`

Examples

import os
import shutil
import tempfile

import pandas as pd

from spotforecast2_safe.preprocessing.exog_providers import (
    EntsoeDayAheadPriceProvider,
)

tmp = tempfile.mkdtemp()
os.environ["SPOTFORECAST2_DATA"] = tmp
os.makedirs(os.path.join(tmp, "interim"), exist_ok=True)
idx = pd.date_range("2023-06-01", periods=24, freq="h", tz="UTC")
pd.DataFrame(
    {"Day-ahead Price": 95.0}, index=idx
).rename_axis("Time (UTC)").to_csv(
    os.path.join(tmp, "interim", "day_ahead_price.csv")
)

provider = EntsoeDayAheadPriceProvider()
out = provider.build(idx)
print(out.columns.tolist(), out.shape, out.dtypes.iloc[0].name)
assert out.shape == (24, 1)
assert not out.isna().any().any()

shutil.rmtree(tmp)
del os.environ["SPOTFORECAST2_DATA"]

['entsoe_day_ahead_price'] (24, 1) float32

Methods

Name	Description
build	Return the day-ahead price series aligned to index.

build

preprocessing.exog_providers.EntsoeDayAheadPriceProvider.build(index)

Return the day-ahead price series aligned to index.

Parameters

Name	Type	Description	Default
index	pd.DatetimeIndex	Hourly `DatetimeIndex` (tz-aware UTC) for the forecast window.	required

Returns

Name	Type	Description
	pd.DataFrame	pd.DataFrame: Single column `entsoe_day_ahead_price`, `float32`.

Raises

Name	Type	Description
	`ExogProviderError`	If `interim/day_ahead_price.csv` is missing or the `Day-ahead Price` column is absent.

Examples

import os
import shutil
import tempfile

import pandas as pd

from spotforecast2_safe.preprocessing.exog_providers import (
    EntsoeDayAheadPriceProvider,
)

tmp = tempfile.mkdtemp()
os.environ["SPOTFORECAST2_DATA"] = tmp
os.makedirs(os.path.join(tmp, "interim"), exist_ok=True)
idx = pd.date_range("2023-06-01", periods=12, freq="h", tz="UTC")
pd.DataFrame(
    {"Day-ahead Price": 88.5}, index=idx
).rename_axis("Time (UTC)").to_csv(
    os.path.join(tmp, "interim", "day_ahead_price.csv")
)

out = EntsoeDayAheadPriceProvider().build(idx)
print(out.columns.tolist(), out.shape, float(out.iloc[0, 0]))
assert out.shape == (12, 1)

shutil.rmtree(tmp)
del os.environ["SPOTFORECAST2_DATA"]

['entsoe_day_ahead_price'] (12, 1) 88.5