Files
sras-viewer/tools/make_test_sras.py
T
Thomas Ales [M S E] 6976cbf767 Add batch export of DC/RF/Velocity map images
Add Export -> Batch Export Images..., which renders and saves one PNG
per angle for whichever of CH1 (RF), CH3 (DC-A), CH4 (DC-B), and
Velocity the user selects, for the currently open file. Each channel
gets its own fixed min/max colorbar range, entered once in the dialog
and held constant across every exported angle, so the resulting images
are directly comparable to each other instead of each auto-scaling to
its own data (today's live-view default).

BatchExportDialog (sras_viewer.py) collects the output folder, file
prefix, and per-channel checkbox + range, seeded from whatever's
already cached (session DC/FFT caches, or the file's own v7 cache
blocks) so opening the dialog never triggers a fresh compute. Export
runs on a background thread via a new BatchExportWorker
(sras_workers.py), which computes each angle's channel image with the
existing dc_image_mv/compute_rf_image helpers (reusing one FFT per
angle for both RF and Velocity) and renders it with a headless
matplotlib Agg canvas.

Also includes several small correctness/robustness fixes that were
already staged in the working tree: an int16-vs-float32 accumulator
mismatch in sras_average.py's row averaging, a DC4-mask cache reuse and
atomic sidecar write in sras_compute.py, a dc3/dc4 pairing guard in
sras_format.py's v7 cache writer, and matching updates to the
tools/ test fixtures.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
2026-08-10 18:30:00 -05:00

193 lines
7.0 KiB
Python

#!/usr/bin/env python3
"""Generate small synthetic .sras files for testing.
Writes v6 files (per-angle geometry, ragged waveform blocks) matching
scan_format.md, with deterministic pseudo-random waveform content so a test
can compute expected DC/FFT images independently of the reader under test.
Usage:
python tools/make_test_sras.py out.sras [--angles 3] [--seed 0]
"""
import argparse
import struct
import sys
from pathlib import Path
import numpy as np
sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
# Packed straight from sras_format.py's own constants (not a hand-copy) so
# this generator can never silently drift from what the real parser expects.
from sras_format import GEO_FMT_V6, HDR_FMT as HDR_FMT_LEGACY, HDR_FMT_V6 # noqa: E402
# Per-angle (n_rows, n_frames) — deliberately different per angle so ragged
# geometry handling is actually exercised.
_GEOMETRY = [(5, 7), (4, 11), (6, 9), (3, 13), (7, 6)]
_SAMPLE_RATE_HZ = 6.25e9
_VELOCITY_MM_S = 20.0
_LASER_FREQ_HZ = 1000.0
_ROW_SPACING_MM = 0.05
def _preamble(ymult_v: float, yoff_adc: float, yzero_v: float) -> bytes:
"""A Tektronix WFMOutpre string in verbose (keyword) form — the reader
pulls YMULT/YOFF/YZERO out of it by name, so the keywords must be
present literally. YMULT/YZERO are in volts, as the scope reports them."""
return (
":WFMOUTPRE:BYT_NR 1;BIT_NR 8;ENCDG BIN;BN_FMT RI;BYT_OR MSB;"
'WFID "Ch1, DC coupling";NR_PT 2500;PT_FMT Y;'
"XINCR 1.6000E-10;XZERO 0.0E0;XUNIT \"s\";"
f"YMULT {ymult_v:.6E};YOFF {yoff_adc:.6E};YZERO {yzero_v:.6E};"
'YUNIT "V"'
).encode("utf-8")
def build(n_angles: int, seed: int, samples_per_frame: int,
geometry: list[tuple[int, int]] | None = None) -> tuple[bytes, dict]:
rng = np.random.default_rng(seed)
src_geom = geometry or _GEOMETRY
geom = [src_geom[a % len(src_geom)] for a in range(n_angles)]
n_ch = 3
bps = 1
angles_deg = np.linspace(0.0, 60.0, n_angles, dtype=np.float32)
# Distinct calibration per channel so a swapped-channel bug is visible.
cal = [
(1.5625e-3, -87.04, 0.0),
(2.0000e-3, -60.00, 1.0e-3),
(2.5000e-3, -40.00, -2.0e-3),
]
out = bytearray()
out += struct.pack(
HDR_FMT_V6, b"SRAS", 6, n_angles,
0.0, 0.0, 1.0, 1.0, _ROW_SPACING_MM,
_VELOCITY_MM_S, _LASER_FREQ_HZ,
samples_per_frame, _SAMPLE_RATE_HZ, bps, n_ch,
)
out += angles_deg.astype(">f4").tobytes()
x_starts = []
for a, (n_rows, n_frames) in enumerate(geom):
x_start = -0.5 + 0.1 * a
x_starts.append(x_start)
out += struct.pack(GEO_FMT_V6, x_start, 1.0, n_frames, n_rows)
y_positions = []
for a, (n_rows, _) in enumerate(geom):
y = (0.2 * a + np.arange(n_rows) * _ROW_SPACING_MM).astype(np.float32)
y_positions.append(y)
out += y.astype(">f4").tobytes()
for ymult_v, yoff, yzero_v in cal:
p = _preamble(ymult_v, yoff, yzero_v)
out += struct.pack(">H", len(p)) + p
background = rng.integers(-8, 9, size=samples_per_frame, dtype=np.int8)
out += struct.pack(">I", samples_per_frame) + background.tobytes()
# Waveform data. CH1 gets a sinusoid at a per-pixel frequency so the FFT
# peak is predictable; CH3/CH4 get per-pixel DC levels so the mean is too.
t = np.arange(samples_per_frame)
waveforms = []
for a, (n_rows, n_frames) in enumerate(geom):
block = np.empty((n_rows, n_ch, n_frames, samples_per_frame), dtype=np.int8)
for r in range(n_rows):
for f in range(n_frames):
bin_idx = 3 + ((a + r + f) % 17)
phase = 2 * np.pi * bin_idx * t / samples_per_frame
block[r, 0, f] = np.clip(
np.round(60 * np.sin(phase)), -128, 127).astype(np.int8)
block[r, 1, f] = np.int8((a * 7 + r * 3 + f) % 100 - 50)
block[r, 2, f] = np.int8((a * 5 + r * 11 + f * 2) % 120 - 60)
waveforms.append(block)
out += block.tobytes()
meta = {
"n_angles": n_angles,
"geometry": geom,
"angles_deg": angles_deg,
"x_starts": x_starts,
"y_positions": y_positions,
"cal": cal,
"background": background,
"waveforms": waveforms,
"samples_per_frame": samples_per_frame,
"sample_rate_hz": _SAMPLE_RATE_HZ,
}
return bytes(out), meta
def write(path: Path, n_angles: int = 3, seed: int = 0,
samples_per_frame: int = 64,
geometry: list[tuple[int, int]] | None = None) -> dict:
payload, meta = build(n_angles, seed, samples_per_frame, geometry)
path.write_bytes(payload)
return meta
def write_legacy(path: Path, version: int = 4, n_angles: int = 2,
n_rows: int = 4, n_frames: int = 10,
samples_per_frame: int = 32, seed: int = 0) -> dict:
"""Write a v2/v3/v4 file: uniform geometry, one flat waveform block.
Used to exercise sras_average.py, which only handles the legacy formats.
"""
rng = np.random.default_rng(seed)
n_ch, bps = 3, 1
out = bytearray()
out += struct.pack(
HDR_FMT_LEGACY, b"SRAS", version, n_angles, n_rows,
-0.5, 1.0, _VELOCITY_MM_S, _LASER_FREQ_HZ,
n_frames, samples_per_frame, _SAMPLE_RATE_HZ, bps, n_ch,
)
angles = np.linspace(0.0, 45.0, n_angles, dtype=np.float32)
out += angles.astype(">f4").tobytes()
y = (np.arange(n_rows) * _ROW_SPACING_MM).astype(np.float32)
out += y.astype(">f4").tobytes()
if version >= 3:
for ymult_v, yoff, yzero_v in ((1.5625e-3, -87.04, 0.0),
(2.0e-3, -60.0, 1.0e-3),
(2.5e-3, -40.0, -2.0e-3))[:n_ch]:
p = _preamble(ymult_v, yoff, yzero_v)
out += struct.pack(">H", len(p)) + p
background = rng.integers(-8, 9, size=samples_per_frame, dtype=np.int8)
if version >= 4:
out += struct.pack(">I", samples_per_frame) + background.tobytes()
data = rng.integers(-100, 101,
size=(n_angles, n_rows, n_ch, n_frames, samples_per_frame),
dtype=np.int8)
out += data.tobytes()
path.write_bytes(bytes(out))
return {"version": version, "n_angles": n_angles, "n_rows": n_rows,
"n_frames": n_frames, "samples_per_frame": samples_per_frame,
"n_channels": n_ch, "data": data, "angles_deg": angles,
"y_positions": y, "background": background}
def main():
p = argparse.ArgumentParser(description=__doc__)
p.add_argument("output")
p.add_argument("--angles", type=int, default=3)
p.add_argument("--seed", type=int, default=0)
p.add_argument("--spf", type=int, default=64, help="samples per frame")
args = p.parse_args()
out = Path(args.output)
meta = write(out, args.angles, args.seed, args.spf)
print(f"Wrote {out} ({out.stat().st_size:,} bytes)")
print(f" angles : {meta['n_angles']}")
print(f" geometry : {meta['geometry']}")
print(f" spf : {meta['samples_per_frame']}")
if __name__ == "__main__":
main()