Decrease dependency on elevation / azimuth

[GernotMaier]

• remove tel_shower_x / tel_shower_y - should be duplicated and the same as R_Core
• calculate array footprint from telescope ground coordinates (to avoid Y bias)
• add number of channels / low-gain channels.

Closes #40

[Copilot]

Pull request overview

Reduces reliance on elevation/azimuth-derived coordinates and expands per-telescope feature set by adding channel-count features.

Changes:

• Removed tel_shower_x / tel_shower_y from the feature set and related synthetic-feature computation.
• Added ntubes and nlowgain as telescope features, including clip intervals and log10 transforms.
• Changed array_footprint computation to use telescope ground coordinates (rather than shower-plane coordinates), with special handling for low-multiplicity events.

Reviewed changes

Copilot reviewed 2 out of 2 changed files in this pull request and generated 4 comments.

File	Description
src/eventdisplay_ml/features.py	Updates the declared feature list and clip intervals (adds ntubes/nlowgain, removes tel_shower_*).
src/eventdisplay_ml/data_processing.py	Removes tel_shower_* synthesis, applies log10 to new count features, and rewrites array_footprint to use ground coordinates.

Comments suppressed due to low confidence (2)

src/eventdisplay_ml/data_processing.py:429

• After removing tel_shower_x/y support, make_relative_coord_columns no longer uses the pointing angles, but this call site still computes/passes np.radians(ArrayPointing*). Consider removing the unused parameters from _make_relative_coord_columns and skipping these per-event conversions to keep the API aligned and avoid unnecessary work.

        if var in ("tel_rel_x", "tel_rel_y") and tel_config:
            _logger.info(f"Computing synthetic feature: {var}")
            flat_features.update(
                _make_relative_coord_columns(
                    var,

src/eventdisplay_ml/data_processing.py:898

• _calculate_array_footprint sizes lookup_x/lookup_y from the max telescope id present in tel_list_matrix, but then writes all tel_config telescope IDs into those arrays. If tel_config contains IDs larger than any ID appearing in tel_list_matrix (or tel_list_matrix is all-NaN), this will raise IndexError. Size the lookup arrays using tel_config["max_tel_id"] (or guard the assignments).

    # Pre-map all telescope positions to a dense array aligned with tel_list_matrix IDs
    max_id = int(np.nanmax(tel_list_matrix)) if np.any(~np.isnan(tel_list_matrix)) else 0
    lookup_x = np.zeros(max_id + 1)
    lookup_y = np.zeros(max_id + 1)
    for tid, tx, ty in zip(tel_config["tel_ids"], tel_config["tel_x"], tel_config["tel_y"]):

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