| """Minimal loader for the solve-anywhere linear-system dataset (numpy + scipy only). |
| |
| from load import catalog, runs, systems, load |
| |
| for run in runs(problem="ex16p", max_n=1e6): # filter the catalog |
| for rec in systems(run, "heat"): # index records of one stream |
| A, b, x = load(run, "heat", rec["sys"]) # scipy CSR, numpy arrays (x may be None) |
| |
| Command line: |
| python load.py summary of the catalog |
| python load.py <run> <stream> <i> print one system's metadata and shapes |
| python load.py --mtx <run> <stream> <i> <out_prefix> write <out_prefix>.mtx / _b.mtx (Matrix Market) |
| """ |
| import json |
| import os |
| import sys |
|
|
| import numpy as np |
| import scipy.io |
| import scipy.sparse as sp |
|
|
| ROOT = os.path.dirname(os.path.abspath(__file__)) |
|
|
|
|
| def catalog(): |
| """Latest catalog entry per run (a re-run replaces an earlier entry).""" |
| latest = {} |
| with open(os.path.join(ROOT, "catalog.jsonl")) as f: |
| for line in f: |
| c = json.loads(line) |
| latest[c["path"]] = c |
| return list(latest.values()) |
|
|
|
|
| def runs(source=None, problem=None, min_n=0, max_n=float("inf"), ok_only=True): |
| """Run directories (absolute) matching the filters.""" |
| out = [] |
| for c in catalog(): |
| if source and c["source"] != source or problem and c["problem"] != problem: |
| continue |
| if ok_only and c["exit"] != 0: |
| continue |
| ns = [n for s in c["streams"].values() for n in s["n"]] |
| if ns and min_n <= max(ns) <= max_n: |
| out.append(os.path.join(ROOT, c["path"])) |
| return out |
|
|
|
|
| def meta(run): |
| with open(os.path.join(run, "meta.json")) as f: |
| return json.load(f) |
|
|
|
|
| def systems(run, stream): |
| """Per-system metadata (one dict per saved system, in order).""" |
| with open(os.path.join(run, stream, "index.jsonl")) as f: |
| return [json.loads(line) for line in f] |
|
|
|
|
| def load(run, stream, i, with_extra=False): |
| """(A, b, x) of system i; x is None if not saved. with_extra=True also returns |
| a dict of the other saved vectors (x0, contact_dofs, block_id, ...).""" |
| rec = systems(run, stream)[i] |
| A = sp.load_npz(os.path.join(run, stream, f"A_{rec['A']:04d}.npz")) |
| v = np.load(os.path.join(run, stream, f"sys_{i:05d}.npz")) |
| x = v["x"] if "x" in v.files else None |
| if with_extra: |
| return A, v["b"], x, {k: v[k] for k in v.files if k not in ("b", "x")} |
| return A, v["b"], x |
|
|
|
|
| def to_matrix_market(run, stream, i, prefix): |
| A, b, x = load(run, stream, i) |
| scipy.io.mmwrite(prefix + ".mtx", A, precision=17) |
| scipy.io.mmwrite(prefix + "_b.mtx", b.reshape(-1, 1), precision=17) |
| if x is not None: |
| scipy.io.mmwrite(prefix + "_x.mtx", x.reshape(-1, 1), precision=17) |
|
|
|
|
| if __name__ == "__main__": |
| if len(sys.argv) >= 6 and sys.argv[1] == "--mtx": |
| to_matrix_market(os.path.abspath(sys.argv[2]), sys.argv[3], int(sys.argv[4]), sys.argv[5]) |
| elif len(sys.argv) == 4: |
| run, stream, i = os.path.abspath(sys.argv[1]), sys.argv[2], int(sys.argv[3]) |
| A, b, x, extra = load(run, stream, i, with_extra=True) |
| print(json.dumps(systems(run, stream)[i], indent=2)) |
| print("A", A.shape, A.nnz, "| b", b.shape, "| x", None if x is None else x.shape, "| extra", list(extra)) |
| else: |
| by = {} |
| for c in catalog(): |
| k = (c["source"], c["problem"]) |
| nsys = sum(s["systems"] for s in c["streams"].values()) |
| nmax = max([n for s in c["streams"].values() for n in s["n"]] or [0]) |
| r, s_, b_, m, f = by.get(k, (0, 0, 0, 0, 0)) |
| by[k] = (r + 1, s_ + nsys, b_ + c["bytes"], max(m, nmax), f + (c["exit"] != 0)) |
| print(f"{'source':8s} {'problem':18s} {'runs':>5s} {'failed':>6s} {'systems':>8s} {'GB':>7s} {'largest n':>10s}") |
| for (src, prob), (r, s_, b_, m, f) in sorted(by.items()): |
| print(f"{src:8s} {prob:18s} {r:5d} {f:6d} {s_:8d} {b_ / 1e9:7.2f} {m:10d}") |
|
|
