`Table(ak.Array)` doesn't preserve `WaveformTable`s

[Yuan-Ru-Lin]

import numpy as np
from lgdo import Table, WaveformTable, Array

tbl = Table({
    "energy": Array([100, 200, 300]),
    "wf": WaveformTable(
        t0=np.array([0.0, 1.0, 2.0]),
        dt=np.array([0.01, 0.01, 0.01]),
        values=np.array([[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]]),
    )
})

# Flatten for columnar storage
flat = tbl.flatten()
ak_arr = flat.view_as("ak")

# Reconstruct
tbl_back = Table(ak_arr)

assert "wf" not in tbl_back.keys()  # Lost! Only has wf__t0, wf__dt, wf__values

Note that a WaveformTable isn't reconstructed from the flattened arrays wf__{t0,dt,values}.

This issue is blocked by #208 because values needs to be reconstructed as an AOESA. After #208 is closed, this issue can be resolved by processing col_dict one more time here.

        if isinstance(col_dict, ak.Array):
            col_dict = _ak_to_lgdo_or_col_dict(col_dict)
+           col_dict = _reconstruct_waveform_tables(col_dict)

where _reconstruct_waveform_tables is defined as

def _reconstruct_waveform_tables(col_dict: dict) -> dict:
    """Detect {prefix}__t0, {prefix}__dt, {prefix}__values patterns and reconstruct WaveformTables."""
    # Find all prefixes that have the waveform pattern
    wf_prefixes = set()
    for key in col_dict:
        if key.endswith("__values"):
            prefix = key[:-8]  # remove "__values"
            if f"{prefix}__t0" in col_dict and f"{prefix}__dt" in col_dict:
                wf_prefixes.add(prefix)

    if not wf_prefixes:
        return col_dict

    # Reconstruct WaveformTables
    result = {}
    used_keys = set()
    for prefix in wf_prefixes:
        t0_key = f"{prefix}__t0"
        dt_key = f"{prefix}__dt"
        values_key = f"{prefix}__values"
        result[prefix] = lgdo.WaveformTable(
            t0=col_dict[t0_key],
            dt=col_dict[dt_key],
            values=col_dict[values_key],
        )
        used_keys.update([t0_key, dt_key, values_key])

    # Keep other columns unchanged
    for key, value in col_dict.items():
        if key not in used_keys:
            result[key] = value

    return result