occC/code/pass_b1.py

"""Pass B1: molecular-orbital coefficients from the gbw files into the p2 store.

For every p2 shard the worker reads each calculation's gbw (staged by Globus at
<gbw_root>/<dataset>/<calc_id>.gbw.zstd0), takes the FULL coefficient matrix of both spin
channels, checks that the gbw and the Pass A text describe the same calculation, and appends the
result to the shard group. Zarr lets arrays be added to an existing group, so p2 keeps its layout
and row order; every new array is row-aligned with the shard's existing calculations.

Added arrays:

    cmo_a, cmo_a_offsets        MO coefficients, MO-major: calculation i is
                                cmo_a[o[i]:o[i+1]].reshape(nbas, nbas) = C^T, i.e. row k is MO k
                                over the AOs (ORCA AO order). Occupied orbitals are the first
                                nocc rows, so C_occ is a contiguous prefix. float32 by default.
    cmo_b, cmo_b_offsets        the same for the beta channel (empty for RHF)
    gbw_eps_a/b (+_offsets)     fp64 orbital energies of all nbas orbitals from the gbw
    gbw_occ_a/b (+_offsets)     fp64 occupations of all nbas orbitals from the gbw
    mo_i                        int columns: nocc_a, nocc_b, gbw_nbas, gbw_nop
    mo_f8                       diagnostics: occ_sum_a/b; eps_err_a/b = max |gbw - printed| over
                                the printed orbital energies; fc_offdiag_a/b = largest
                                off-diagonal of C_occ^T F C_occ (Eh); fc_diag_err_a/b =
                                max |diag(C_occ^T F C_occ) - eps_occ| (Eh); fc_bound_a/b = what
                                the 5e-7 Eh print rounding of F can do to that block
    mo_flags                    gbw_found, nbas_match, nspin_match, nelec_match, spin_match,
                                eps_checked, eps_match, occ_contiguous, fock_checked, fock_match,
                                mo_ok

mo_ok is the conjunction of every check that could be run. fock_match is only meaningful when
fock_checked is set (a Fock matrix was printed and nbas agreed); it asks that the printed Fock
matrix be diagonal in the gbw's occupied orbitals to 1e-2 Eh. A mismatched pair is off by
0.1 to 1 Eh, so the flag is a pairing test, not a convergence test. Typical values are ~1e-6 Eh,
but in near-linearly-dependent bases (smallest overlap eigenvalue ~1e-6, not removed by ORCA)
the 5e-7 Eh print rounding of F is amplified by the large MO coefficients into ~1e-3 Eh on the
occupied block even though F_print agrees with C^-T diag(e) C^-1 to 1e-5 in the AO basis. The
fc_bound columns give that rounding amplification per calculation (5e-7 x max_i ||C_i||_1^2);
compare fc_diag_err against it before reading a large value as an inconsistency.

Usage:
    python pass_b1.py --store $PSCRATCH/omol_100k --gbw-root $PSCRATCH/gbw_100k --workers 48
"""
from __future__ import annotations
import argparse, glob, json, os, sys, time, traceback
import multiprocessing as mp
import numpy as np
import zarr

# One thread per worker process: zarr's default pool (os.cpu_count() threads) times 64 to 96
# forked workers thrashed a 128-core node, cutting throughput several-fold.
zarr.config.set({"threading.max_workers": 1, "async.concurrency": 2})
try:
    import numcodecs.blosc
    numcodecs.blosc.set_nthreads(1)
    numcodecs.blosc.use_threads = False
except Exception:
    pass

sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
from gbw_reader import read_gbw
from omol_store import put_array, inflate_fock

MO_I = ("nocc_a", "nocc_b", "gbw_nbas", "gbw_nop")
MO_F8 = ("occ_sum_a", "occ_sum_b", "eps_err_a", "eps_err_b",
         "fc_offdiag_a", "fc_offdiag_b", "fc_diag_err_a", "fc_diag_err_b",
         "fc_bound_a", "fc_bound_b")
MO_FLAGS = ("gbw_found", "nbas_match", "nspin_match", "nelec_match", "spin_match",
            "eps_checked", "eps_match", "occ_contiguous", "fock_checked", "fock_match", "mo_ok")
INFORMATIONAL = ("eps_checked", "fock_checked", "mo_ok")
EPS_TOL = 5e-6      # printed to 6 decimals; rounding alone gives 5e-7
FOCK_TOL = 1e-2     # Eh; see the docstring on why the occupied block can be off by ~1e-3
CMO_CHUNK = 1 << 22
OLD_ARRAYS = ("cocc_a", "cocc_a_offsets", "cocc_b", "cocc_b_offsets", "cocc_occ_a",
              "cocc_occ_a_offsets", "cocc_occ_b", "cocc_occ_b_offsets", "cocc_i", "cocc_f8",
              "cocc_flags")


def p2_shards(store):
    out = []
    for depth in ("*", "*/*/*"):
        out += glob.glob(os.path.join(store, "p2", depth, "*.zarr"))
    return sorted(set(out))


def fock_check(F, C, eps):
    """Largest off-diagonal of C^T F C and largest |diag - eps|, in Eh."""
    M = C.T @ (F @ C)
    d = np.diag(M).copy()
    np.fill_diagonal(M, 0.0)
    return float(np.abs(M).max()) if M.size else 0.0, float(np.abs(d - eps).max()) if d.size else 0.0


def process_shard(args):
    sp, gbw_root, force, dtype = args
    t0 = time.time()
    try:
        g = zarr.open_group(sp, mode="r+")
        if g.attrs.get("has_mo") and g.attrs.get("mo_dtype") == dtype and not force:
            return sp, "skip", {}, [], 0.0, ""
        n = int(g.attrs["n_calc"])
        ids = g.attrs["calc_id"]
        ds = g.attrs["dataset"]
        si = np.asarray(g["scalar_i"])
        ic = {k: j for j, k in enumerate(g.attrs["scalar_i_cols"])}
        fl = np.asarray(g["flags"]).astype(bool)
        fc = {k: j for j, k in enumerate(g.attrs["flag_cols"])}
        eps = {s: np.asarray(g[f"eps_{s}"]) for s in "ab"}
        eoff = {s: np.asarray(g[f"eps_{s}_offsets"]) for s in "ab"}
        foff = {s: np.asarray(g[f"fock_{s}_offsets"]) for s in "ab"}
        nbas_all = si[:, ic["nbas"]].astype("i8")
        nsp_all = np.where(fl[:, fc["is_uhf"]], 2, 1)

        # Preallocate the coefficient buffers from the text's nbas (verified against the gbw
        # below; a mismatch leaves that calculation's slot empty and flagged).
        cap = {s: np.zeros(n + 1, dtype="i8") for s in "ab"}
        cap["a"][1:] = np.cumsum(nbas_all ** 2)
        cap["b"][1:] = np.cumsum(np.where(nsp_all == 2, nbas_all ** 2, 0))
        buf = {s: np.zeros(int(cap[s][-1]), dtype=dtype) for s in "ab"}
        filled = {s: np.zeros(n, dtype=bool) for s in "ab"}
        geps = {s: [] for s in "ab"}
        gocc = {s: [] for s in "ab"}
        mi = np.zeros((n, len(MO_I)), dtype="i8")
        mf = np.full((n, len(MO_F8)), np.nan)
        mfl = np.zeros((n, len(MO_FLAGS)), dtype="i1")
        failures = []

        for i in range(n):
            nbas = int(nbas_all[i])
            nelec = int(si[i, ic["nelec"]])
            mult = int(si[i, ic["mult"]])
            is_uhf = bool(fl[i, fc["is_uhf"]])
            has_fock = bool(fl[i, fc["has_fock"]])
            flags = dict.fromkeys(MO_FLAGS, False)
            path = os.path.join(gbw_root, ds, ids[i] + ".gbw.zstd0")
            gb = None
            if os.path.exists(path):
                try:
                    gb = read_gbw(path)
                    flags["gbw_found"] = True
                except Exception as e:
                    failures.append((ids[i], f"gbw read error: {type(e).__name__}: {str(e)[:120]}"))
            else:
                failures.append((ids[i], "gbw missing"))
            if gb is None:
                for s in "ab":
                    geps[s].append(np.zeros(0)); gocc[s].append(np.zeros(0))
                mfl[i] = [flags[k] for k in MO_FLAGS]
                continue

            dim, nop = gb["nbas"], gb["nop"]
            mi[i, MO_I.index("gbw_nbas")] = dim
            mi[i, MO_I.index("gbw_nop")] = nop
            flags["nbas_match"] = dim == nbas
            flags["nspin_match"] = nop == (2 if is_uhf else 1)
            occ_sum = {}
            contiguous = True
            eps_ok = True
            eps_checked = False
            fock_checked = fock_ok = True
            for k, s in enumerate("ab"):
                if k >= nop:
                    geps[s].append(np.zeros(0)); gocc[s].append(np.zeros(0))
                    occ_sum[s] = 0.0
                    continue
                op = gb["ops"][k]
                occ_v, en_v, C = op["occ"], op["energies"], op["C"]
                mask = occ_v > 0
                nocc = int(mask.sum())
                idx = np.flatnonzero(mask)
                if nocc and (idx[-1] != nocc - 1):
                    contiguous = False
                if dim == nbas and (s == "a" or is_uhf):
                    # MO-major (C^T) so the occupied block is a contiguous prefix
                    buf[s][cap[s][i]:cap[s][i + 1]] = C.T.ravel().astype(dtype, copy=False)
                    filled[s][i] = True
                geps[s].append(en_v.copy())
                gocc[s].append(occ_v.copy())
                mi[i, MO_I.index(f"nocc_{s}")] = nocc
                occ_sum[s] = float(occ_v.sum())
                mf[i, MO_F8.index(f"occ_sum_{s}")] = occ_sum[s]
                # printed orbital energies (6 decimals) against the gbw. A reduced print level
                # (the no-Fock metal_organics inputs) lists only the first few hundred orbitals,
                # so compare over the printed prefix; energies of removed orbitals print as 0.
                e_txt = eps[s][eoff[s][i]:eoff[s][i + 1]]
                if 0 < len(e_txt) <= dim:
                    eps_checked = True
                    m = e_txt != 0.0
                    err = float(np.abs(en_v[:len(e_txt)][m] - e_txt[m]).max()) if m.any() else 0.0
                    mf[i, MO_F8.index(f"eps_err_{s}")] = err
                    if err > EPS_TOL:
                        eps_ok = False
                elif len(e_txt) > dim:
                    eps_checked = True
                    eps_ok = False
                # printed Fock diagonal in the gbw occupied orbitals
                if has_fock and dim == nbas and nocc:
                    f0, f1 = int(foff[s][i]), int(foff[s][i + 1])
                    if f1 > f0:
                        Co = np.ascontiguousarray(C[:, mask])
                        F = inflate_fock(np.asarray(g[f"fock_{s}"][f0:f1]), nbas)
                        od, de = fock_check(F, Co, en_v[mask])
                        mf[i, MO_F8.index(f"fc_offdiag_{s}")] = od
                        mf[i, MO_F8.index(f"fc_diag_err_{s}")] = de
                        mf[i, MO_F8.index(f"fc_bound_{s}")] = 5e-7 * float(
                            (np.abs(Co).sum(axis=0) ** 2).max())
                        if od > FOCK_TOL or de > FOCK_TOL:
                            fock_ok = False
                        del F, Co
                    else:
                        fock_checked = False
                else:
                    fock_checked = False
            tot = occ_sum["a"] + occ_sum["b"]
            flags["nelec_match"] = abs(tot - nelec) < 1e-6
            if nop == 2:
                flags["spin_match"] = abs((occ_sum["a"] - occ_sum["b"]) - (mult - 1)) < 1e-6
            else:
                flags["spin_match"] = mult == 1 and abs(occ_sum["a"] - nelec) < 1e-6
            flags["eps_checked"] = eps_checked
            flags["eps_match"] = eps_ok
            flags["occ_contiguous"] = contiguous
            flags["fock_checked"] = fock_checked
            flags["fock_match"] = fock_ok
            flags["mo_ok"] = all(flags[k] for k in MO_FLAGS if k not in INFORMATIONAL)
            mfl[i] = [flags[k] for k in MO_FLAGS]
            if not flags["mo_ok"]:
                bad = [k for k in MO_FLAGS if k not in INFORMATIONAL and not flags[k]]
                failures.append((ids[i], "failed: " + ",".join(bad)))

        def ragged(parts, dt):
            offs = np.zeros(len(parts) + 1, dtype="i8")
            offs[1:] = np.cumsum([len(p) for p in parts])
            flat = np.concatenate(parts).astype(dt) if parts else np.zeros(0, dt)
            return flat, offs

        for name in OLD_ARRAYS:
            if name in g:
                del g[name]
        for s in "ab":
            # offsets follow the filled slots; an unfilled slot (gbw missing or nbas mismatch)
            # gets a zero-length block so the array stays dense
            lens = np.where(filled[s], np.diff(cap[s]), 0)
            offs = np.zeros(n + 1, dtype="i8")
            offs[1:] = np.cumsum(lens)
            if filled[s].all():
                flat = buf[s]
            else:
                flat = np.concatenate([buf[s][cap[s][i]:cap[s][i + 1]] for i in range(n) if filled[s][i]]
                                      ) if filled[s].any() else np.zeros(0, dtype)
            put_array(g, f"cmo_{s}", flat, codec=None,
                      chunks=(max(1, min(len(flat), CMO_CHUNK)),), overwrite=True)
            put_array(g, f"cmo_{s}_offsets", offs, overwrite=True)
            flat, offs = ragged(geps[s], "f8")
            put_array(g, f"gbw_eps_{s}", flat, overwrite=True)
            put_array(g, f"gbw_eps_{s}_offsets", offs, overwrite=True)
            flat, offs = ragged(gocc[s], "f8")
            put_array(g, f"gbw_occ_{s}", flat, overwrite=True)
            put_array(g, f"gbw_occ_{s}_offsets", offs, overwrite=True)
        put_array(g, "mo_i", mi, overwrite=True)
        put_array(g, "mo_f8", mf, overwrite=True)
        put_array(g, "mo_flags", mfl, overwrite=True)
        for k in ("has_cocc", "cocc_schema", "cocc_i_cols", "cocc_f8_cols", "cocc_flag_cols",
                  "cocc_layout", "cocc_gbw_root"):
            g.attrs.pop(k, None)
        g.attrs.update({
            "has_mo": True,
            "mo_schema": "omol_elec/pass_b1/2",
            "mo_dtype": dtype,
            "mo_i_cols": list(MO_I),
            "mo_f8_cols": list(MO_F8),
            "mo_flag_cols": list(MO_FLAGS),
            "mo_layout": "cmo_x[o[i]:o[i+1]].reshape(nbas, nbas) = C^T (row k = MO k over AOs, "
                         "ORCA AO order); occupied MOs are the first nocc_x rows",
            "mo_gbw_root": gbw_root,
        })
        stats = {
            "n": n,
            "found": int(mfl[:, MO_FLAGS.index("gbw_found")].sum()),
            "ok": int(mfl[:, MO_FLAGS.index("mo_ok")].sum()),
            "fock_checked": int(mfl[:, MO_FLAGS.index("fock_checked")].sum()),
            "bytes_cmo": int(sum(int(g[f"cmo_{s}"].shape[0]) for s in "ab") * np.dtype(dtype).itemsize),
            "eps_err_max": float(np.nanmax(mf[:, [2, 3]])) if np.isfinite(mf[:, [2, 3]]).any() else float("nan"),
            "fc_offdiag_max": float(np.nanmax(mf[:, [4, 5]])) if np.isfinite(mf[:, [4, 5]]).any() else float("nan"),
            "fc_offdiag_p50": float(np.nanmedian(mf[:, [4, 5]])) if np.isfinite(mf[:, [4, 5]]).any() else float("nan"),
        }
        for k in MO_FLAGS:
            stats["fail_" + k] = int(n - mfl[:, MO_FLAGS.index(k)].sum())
        return sp, "ok", stats, failures, time.time() - t0, ""
    except Exception:
        return sp, "fail", {}, [], time.time() - t0, traceback.format_exc(limit=4)


def main():
    ap = argparse.ArgumentParser()
    ap.add_argument("--store", required=True)
    ap.add_argument("--gbw-root", required=True)
    ap.add_argument("--workers", type=int, default=48)
    ap.add_argument("--dtype", default="f4", choices=("f4", "f8"))
    ap.add_argument("--limit", type=int, default=0)
    ap.add_argument("--force", action="store_true", help="recompute shards that already have MOs")
    args = ap.parse_args()
    shards = p2_shards(args.store)
    if args.limit:
        shards = shards[:args.limit]
    print(f"pass B1 (full C, {args.dtype}): {len(shards)} p2 shards in {args.store}, "
          f"gbw from {args.gbw_root}", flush=True)
    jobs = [(s, args.gbw_root, args.force, args.dtype) for s in shards]
    t0 = time.time()
    tot = {}
    all_fail, shard_fail = [], []
    n_skip = 0
    eps_max = fc_max = 0.0
    fc_p50 = []
    with mp.Pool(min(args.workers, len(jobs))) as pool:
        for k, (sp, status, st, failures, dt, err) in enumerate(pool.imap_unordered(process_shard, jobs), 1):
            if status == "ok":
                for key, v in st.items():
                    if key.startswith(("n", "found", "ok", "fock_checked", "bytes", "fail_")):
                        tot[key] = tot.get(key, 0) + v
                if st["eps_err_max"] == st["eps_err_max"]:
                    eps_max = max(eps_max, st["eps_err_max"])
                if st["fc_offdiag_max"] == st["fc_offdiag_max"]:
                    fc_max = max(fc_max, st["fc_offdiag_max"])
                if st["fc_offdiag_p50"] == st["fc_offdiag_p50"]:
                    fc_p50.append(st["fc_offdiag_p50"])
                all_fail.extend((sp, cid, why) for cid, why in failures)
            elif status == "skip":
                n_skip += 1
            else:
                shard_fail.append((sp, err))
                print(f"SHARD FAIL {sp}\n{err}", flush=True)
            if k % 50 == 0 or k == len(jobs):
                el = time.time() - t0
                print(f"  {k}/{len(jobs)}  calcs {tot.get('n',0):,} found {tot.get('found',0):,} "
                      f"ok {tot.get('ok',0):,}  {tot.get('bytes_cmo',0)/1e9:.0f} GB  {el/60:.1f} min  "
                      f"eta {el/k*(len(jobs)-k)/60:.1f} min", flush=True)
    dt = time.time() - t0
    print(f"\nB1 done in {dt/60:.1f} min: shards ok {len(jobs)-n_skip-len(shard_fail)}, "
          f"skipped {n_skip}, failed {len(shard_fail)}")
    print(f"calculations {tot.get('n',0):,}: gbw found {tot.get('found',0):,}, "
          f"mo_ok {tot.get('ok',0):,}, fock checked {tot.get('fock_checked',0):,}")
    for k in MO_FLAGS:
        print(f"  not {k:15s}: {tot.get('fail_'+k, 0):,}")
    print(f"C bytes {tot.get('bytes_cmo',0)/1e12:.3f} TB  "
          f"({tot.get('bytes_cmo',0)/max(tot.get('n',1),1)/1e6:.2f} MB/calc, {args.dtype})")
    print(f"max eps error (gbw vs printed) {eps_max:.2e} Eh; "
          f"C_occ^T F C_occ off-diagonal: median-of-shard-medians "
          f"{np.median(fc_p50) if fc_p50 else float('nan'):.2e}, max {fc_max:.2e} Eh")
    out = os.path.join(args.store, "b1_failures.tsv")
    with open(out, "w") as fh:
        fh.write("shard\tcalc_id\treason\n")
        for sp, cid, why in all_fail:
            fh.write(f"{os.path.relpath(sp, args.store)}\t{cid}\t{why}\n")
    print(f"{len(all_fail)} per-calculation problems written to {out}")
    with open(os.path.join(args.store, "b1_summary.json"), "w") as fh:
        json.dump({"totals": tot, "dtype": args.dtype, "eps_err_max": eps_max,
                   "fc_offdiag_max": fc_max, "wall_s": dt,
                   "shard_failures": [s for s, _ in shard_fail]}, fh, indent=1)


if __name__ == "__main__":
    mp.set_start_method("fork", force=True)
    main()