Datasets:
Formats:
csv
Languages:
English
Size:
1K - 10K
Tags:
mathematics
inverse-problems
observability
noncommutative-algebra
symbolic-computation
calibration-rigidity
File size: 2,046 Bytes
d1c6c9a | 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 | #!/usr/bin/env python3
"""Regenerate lossless CSV viewer projections and synchronize the data catalog."""
from __future__ import annotations
import csv,hashlib,json
from pathlib import Path
ROOT=Path(__file__).resolve().parents[1]
def main():
dest=ROOT/"hub_data";dest.mkdir(exist_ok=True)
for name in ["v3_components_m6","v3_visibility_certificates"]:
records=json.loads((ROOT/"data"/(name+".json")).read_text(encoding="utf-8"))
rows=[]
for r in records:
row={"record_json":json.dumps(r,ensure_ascii=False,separators=(",",":")),"channels":6}
if name=="v3_components_m6":
row.update(component_id=r["type"]+"-"+"-".join(map(str,r["labels_zero_based"])),
kind=r["type"],dimension=r["dimension"],
labels_zero_based_json=json.dumps(r["labels_zero_based"],separators=(",",":")),
equation_count=len(r["linear_equations_ascending_edges"]))
else:
row.update(stratum=r["stratum"],blocks=3,visible=r["visible"],
normalized_response_exact=str(r["normalized_response"]),
motif_json=json.dumps(r["motif"],separators=(",",":")))
rows.append(row)
p=dest/(name+".csv")
with p.open("w",newline="",encoding="utf-8") as f:
w=csv.DictWriter(f,fieldnames=list(rows[0]));w.writeheader();w.writerows(rows)
print(name,len(rows))
cp=ROOT/"data_catalog.json"
catalog=json.loads(cp.read_text(encoding="utf-8"))
for item in catalog["configurations"]:
p=ROOT/item["path"]
with p.open(newline="",encoding="utf-8") as f:
r=csv.DictReader(f);rows=list(r)
item.update(columns=r.fieldnames,rows=len(rows),sha256=hashlib.sha256(p.read_bytes()).hexdigest())
catalog["total_rows"]=sum(x["rows"] for x in catalog["configurations"])
cp.write_text(json.dumps(catalog,indent=2,ensure_ascii=False)+"\n",encoding="utf-8")
return 0
if __name__=="__main__":raise SystemExit(main())
|