add datetime features

[peterdudfield]

Pull Request

Description

Add datetime features to site

#77

How Has This Been Tested?

CI tests + new tests

• Yes

Checklist:

• My code follows OCF's coding style guidelines
• I have performed a self-review of my own code
• I have made corresponding changes to the documentation
• I have added tests that prove my fix is effective or that my feature works
• I have checked my code and corrected any misspellings

[peterdudfield]

Ive put this back as a draft, im we perhaps can do this on the file when loading the data

[felix-e-h-p]

Couple of updates I feel might be worthwhile

[felix-e-h-p]

Potentially update main function to include input validation - also to simplify the dict construction via literal. Feel this improves maintenance ease a little overall. As example:

def make_datetime_numpy_batch(datetimes: pd.DatetimeIndex, key_prefix: str = "wind") -> dict:
    """
    Make a dict of datetime features using sin/cos transformations
    """
    if datetimes.empty:
        raise ValueError("Input datetimes is empty")

    # Obtain scaled radians for date and time
    date_in_pi, time_in_pi = _get_date_time_in_pi(datetimes)

    # Create dict
    return {
        f"{key_prefix}_date_sin": np.sin(date_in_pi),
        f"{key_prefix}_date_cos": np.cos(date_in_pi),
        f"{key_prefix}_time_sin": np.sin(time_in_pi),
        f"{key_prefix}_time_cos": np.cos(time_in_pi),
    }

[felix-e-h-p]

Testing wise - perhaps update to additionaly verify if a custom prefix is sufficiently applied to all dict keys that the function generates and a further basic check if an empty input corresponds to error raising as implemented in main. As example:

def test_make_datetime_numpy_batch_custom_key_prefix():
    # Test function correctly applies custom prefix to dict keys
    datetimes = pd.to_datetime(["2024-06-20 12:00", "2024-06-20 12:30", "2024-06-20 13:00"])
    key_prefix = "solar"

    datetime_features = make_datetime_numpy_batch(datetimes, key_prefix=key_prefix)

    # Assert dict contains expected quantity of keys and verify starting with custom prefix
    assert len(datetime_features) == 4
    assert all(key.startswith(key_prefix) for key in datetime_features.keys())


def test_make_datetime_numpy_batch_empty_input():
    # Verification that function raises error for empty input
    datetimes = pd.DatetimeIndex([])
    
    with pytest.raises(ValueError, match="Input datetimes is empty"):
        make_datetime_numpy_batch(datetimes)