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2bfd19c | 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 | #!/usr/bin/env python3
import argparse
import json
from collections import defaultdict
from pathlib import Path
from typing import Dict, List, Optional, Set, Tuple
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
def parse_int_list(value: Optional[str]) -> Optional[Set[int]]:
if not value:
return None
return {int(item.strip()) for item in value.split(",") if item.strip()}
def load_records(json_path: Path) -> List[dict]:
with json_path.open("r") as f:
payload = json.load(f)
if isinstance(payload, list):
return payload
if isinstance(payload, dict) and isinstance(payload.get("records"), list):
return payload["records"]
raise ValueError(f"Cannot find records in {json_path}")
def group_records(records: List[dict], chunk_ids: Optional[Set[int]], max_chunks: Optional[int]) -> Dict[int, List[dict]]:
grouped = defaultdict(list)
for record in records:
chunk_idx = int(record["chunk_idx"])
if chunk_ids is not None and chunk_idx not in chunk_ids:
continue
grouped[chunk_idx].append(record)
grouped = dict(sorted(grouped.items()))
if max_chunks is not None:
grouped = dict(list(grouped.items())[:max_chunks])
return grouped
def build_plot(
grouped_records: Dict[int, List[dict]],
output_path: Path,
x_field: str,
y_field: str,
title: Optional[str],
reverse_x: bool,
figsize: Tuple[float, float],
dpi: int,
) -> None:
fig, ax = plt.subplots(figsize=figsize)
for chunk_idx, records in grouped_records.items():
points = []
for record in records:
if x_field not in record or y_field not in record:
continue
if record[x_field] is None or record[y_field] is None:
continue
points.append((float(record[x_field]), float(record[y_field])))
if not points:
continue
points.sort(key=lambda item: item[0])
xs, ys = zip(*points)
ax.plot(xs, ys, marker="o", linewidth=1.6, markersize=3, label=f"chunk {chunk_idx}")
ax.set_xlabel(x_field)
ax.set_ylabel(y_field)
ax.set_title(title or f"{y_field} by timestep")
ax.grid(True, alpha=0.3)
if reverse_x:
ax.invert_xaxis()
ax.legend(loc="best", fontsize="small", ncols=2)
fig.tight_layout()
output_path.parent.mkdir(parents=True, exist_ok=True)
fig.savefig(output_path, dpi=dpi)
plt.close(fig)
def parse_arguments():
parser = argparse.ArgumentParser(description="Plot per-chunk residual norm curves from MAGI residual stats JSON.")
parser.add_argument("json_path", type=Path, help="Path to residual stats JSON saved by --residual_stats_path.")
parser.add_argument(
"-o",
"--output",
type=Path,
help="Output image path. Defaults to <json_path stem>_residual_norms.png.",
)
parser.add_argument("--chunks", type=str, help="Comma-separated chunk_idx list to plot, for example: 0,1,2.")
parser.add_argument("--max-chunks", type=int, help="Plot at most this many chunks after filtering.")
parser.add_argument(
"--x-field",
choices=["timestep", "cur_denoise_step", "denoise_idx"],
default="timestep",
help="Record field used for the x axis.",
)
parser.add_argument(
"--y-field",
choices=["residual_norm", "residual_diff_norm"],
default="residual_norm",
help="Record field used for the y axis.",
)
parser.add_argument("--reverse-x", action="store_true", help="Reverse the x axis.")
parser.add_argument("--title", type=str, help="Figure title.")
parser.add_argument("--figsize", type=str, default="10,6", help="Figure size as width,height.")
parser.add_argument("--dpi", type=int, default=160, help="Output image DPI.")
return parser.parse_args()
def main():
args = parse_arguments()
output_path = args.output or args.json_path.with_name(f"{args.json_path.stem}_residual_norms.png")
figsize_parts = [float(part.strip()) for part in args.figsize.split(",")]
if len(figsize_parts) != 2:
raise ValueError("--figsize must be formatted as width,height")
records = load_records(args.json_path)
grouped_records = group_records(records, parse_int_list(args.chunks), args.max_chunks)
if not grouped_records:
raise ValueError("No records matched the requested chunks.")
build_plot(
grouped_records=grouped_records,
output_path=output_path,
x_field=args.x_field,
y_field=args.y_field,
title=args.title,
reverse_x=args.reverse_x,
figsize=(figsize_parts[0], figsize_parts[1]),
dpi=args.dpi,
)
print(f"Saved plot to {output_path}")
if __name__ == "__main__":
main()
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