"""Old deterministic-v2 references, into new output paths only."""
import sys
import time
import numpy as np
import pandas as pd
import yaml
from context import ROOT, EXP, check, save, bit_equal
from run_suite import preflight


def main():
    check(full=True)
    assert not (EXP / 'regression/frozen-five.json').exists()
    preflight()
    runtime_path = ROOT / 'models/male-cns-lif/deterministic-runtime-v2'
    pc = yaml.safe_load((runtime_path / 'phase4p.yaml').read_text())
    sys.path.insert(0, str(ROOT / 'models/male-cns-lif'))
    sys.path.insert(0, str(runtime_path))
    import torch
    import phase4p
    assert torch.cuda.mem_get_info()[0] > 2 * 1024**3
    torch.cuda.reset_peak_memory_stats()
    started = time.perf_counter()
    runtime = phase4p.CanonicalRuntime(pc, runtime_path, EXP)
    rows = []
    for spec in pc['reference_trials']:
        preflight()
        reference_dir = ROOT / 'experiments/phase4p-deterministic-runtime/phase4c-v2/reference' / spec['name']
        events = pd.read_parquet(reference_dir / 'spike-events.parquet')
        reference = dict(step=events.step.to_numpy(), neuron_idx=events.neuron_idx.to_numpy(),
            counts=np.load(reference_dir / 'per-neuron-spike-counts.int32.npy'),
            v=np.load(reference_dir / 'final-voltage.float32.npy'), g=np.load(reference_dir / 'final-g.float32.npy'))
        result = runtime.run(np.flatnonzero(runtime.pops[spec['population']]), spec['rate_hz'], spec['seed'], spec['duration_ms'])
        row = dict(trial=spec['name'], exact={key: bool(bit_equal(value, result[key])) for key, value in reference.items()},
            dtype_shape={key: dict(reference_dtype=str(value.dtype), actual_dtype=str(result[key].dtype),
                reference_shape=list(value.shape), actual_shape=list(result[key].shape)) for key, value in reference.items()},
            wall_seconds=result['metrics']['wall_seconds'])
        rows.append(row); print(row, flush=True)
    passed = len(rows) == 5 and all(all(row['exact'].values()) for row in rows)
    save(EXP / 'regression/frozen-five.json', dict(pass_all=passed, trials=rows,
        wall_seconds=time.perf_counter() - started, peak_allocated_vram=int(torch.cuda.max_memory_allocated()),
        scope='Old frozen deterministic-v2 references; not a claim D18 equals old runtime'))
    assert passed


if __name__ == '__main__':
    main()