Datasets:
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1c49dd2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 | #!/usr/bin/env python3
"""Inspect downloaded PHM-Vibench metadata and H5 samples locally."""
from __future__ import annotations
import argparse
import sys
from pathlib import Path
from phm_vibench_manifest import DATASET_TO_FILE, FILE_SIZES
REQUIRED_COLUMNS = ["Id", "Name", "File", "Label", "Sample_rate", "Sample_lenth", "Channel"]
def import_pandas():
try:
import pandas as pd
except ImportError as exc:
raise SystemExit("Missing dependency: pandas/openpyxl. Install with `pip install -r requirements.txt`.") from exc
return pd
def import_h5py():
try:
import h5py
except ImportError as exc:
raise SystemExit("Missing dependency: h5py. Install with `pip install -r requirements.txt`.") from exc
return h5py
def load_metadata(root: Path):
path = root / "metadata.xlsx"
if not path.is_file():
raise SystemExit(f"Missing metadata.xlsx under {root}")
pd = import_pandas()
df = pd.read_excel(path)
missing = [column for column in REQUIRED_COLUMNS if column not in df.columns]
if missing:
raise SystemExit("metadata.xlsx missing required columns: " + ", ".join(missing))
return df
def print_dataset_summary(df) -> None:
counts = df["Name"].value_counts().sort_index()
print("datasets:", len(counts))
for dataset, count in counts.items():
file_name = DATASET_TO_FILE.get(dataset, "")
print(f"{dataset:<18} samples={count:<6} file={file_name}")
def normalize_dataset_id(dataset: str) -> str:
lookup = {name.lower(): name for name in DATASET_TO_FILE}
normalized = lookup.get(dataset.lower())
if normalized is None:
raise SystemExit(f"Unknown dataset {dataset}. Use --list-datasets to inspect valid dataset ids.")
return normalized
def choose_smoke_dataset(root: Path) -> str:
present = []
for dataset, h5_name in DATASET_TO_FILE.items():
if (root / h5_name).is_file():
present.append((FILE_SIZES[h5_name], dataset))
if not present:
raise SystemExit(f"No published H5 file found under {root}; download --preset demo or choose --metadata-only")
present.sort()
return present[0][1]
def select_sample(df, dataset: str, sample_index: int, sample_id: str | None):
rows = df[df["Name"].eq(dataset)].reset_index(drop=True)
if rows.empty:
raise SystemExit(f"Dataset {dataset} not found in metadata.xlsx")
if sample_id is not None:
matches = rows[rows["Id"].astype(str).eq(sample_id)]
if matches.empty:
raise SystemExit(f"Sample id {sample_id} not found in dataset {dataset}")
return matches.iloc[0], len(rows)
if sample_index < 0 or sample_index >= len(rows):
raise SystemExit(f"--sample-index must be in [0, {len(rows) - 1}] for {dataset}")
return rows.iloc[sample_index], len(rows)
def inspect_sample(root: Path, dataset: str, sample_index: int, sample_id: str | None, *, metadata_only: bool) -> None:
df = load_metadata(root)
row, dataset_rows = select_sample(df, dataset, sample_index, sample_id)
sample_key = str(int(row["Id"]))
h5_name = DATASET_TO_FILE.get(dataset)
if h5_name is None:
raise SystemExit(f"Dataset {dataset} is not in the published H5 manifest")
print(f"root={root}")
print(f"dataset={dataset} samples={dataset_rows} h5={h5_name}")
print(
"sample "
f"id={sample_key} label={row['Label']} sample_rate={row['Sample_rate']} "
f"sample_lenth={row['Sample_lenth']} channel={row['Channel']}"
)
if metadata_only:
return
h5_path = root / h5_name
if not h5_path.is_file():
raise SystemExit(f"Missing {h5_name} under {root}")
h5py = import_h5py()
with h5py.File(h5_path, "r") as h5:
if sample_key not in h5:
raise SystemExit(f"Sample id {sample_key} not found in {h5_name}")
dataset_obj = h5[sample_key]
print(f"h5 key={sample_key} shape={dataset_obj.shape} dtype={dataset_obj.dtype}")
def parse_args() -> argparse.Namespace:
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--root", type=Path, default=Path("PHM-Vibench"), help="Downloaded dataset root")
parser.add_argument("--dataset", default="RM_007_MFPT", help="Dataset id such as RM_007_MFPT; case-insensitive")
parser.add_argument("--sample-index", type=int, default=0, help="Zero-based sample index within --dataset")
parser.add_argument("--sample-id", help="Explicit sample Id from metadata.xlsx; overrides --sample-index")
parser.add_argument("--metadata-only", action="store_true", help="Inspect metadata without opening the H5 file")
parser.add_argument("--list-datasets", action="store_true", help="List dataset sample counts from metadata.xlsx")
parser.add_argument("--smoke", action="store_true", help="Inspect the smallest published H5 file present under --root")
return parser.parse_args()
def main() -> int:
args = parse_args()
if args.list_datasets:
print_dataset_summary(load_metadata(args.root))
return 0
dataset = choose_smoke_dataset(args.root) if args.smoke else normalize_dataset_id(args.dataset)
inspect_sample(
args.root,
dataset,
args.sample_index,
args.sample_id,
metadata_only=args.metadata_only,
)
return 0
if __name__ == "__main__":
sys.exit(main())
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