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Jungfraujoch/docs
leonarski_fandClaude Opus 5 4e4de57aae Rugnux: two diagnostic outputs a person can check the run by eye with
Written on every rotation run, next to the reflections, with no flag to
switch them on:

<prefix>_detector.jpg - the mean projection the beam-stop pre-scan built,
which is the very image the shadow detection tested, coloured with the
viewer's own default map from common/ColorScale.h: white-to-indigo for the
counts, grey for the module and chip gaps, coral for the detected shadow,
magenta for the rest of the pixel mask. A shadow claimed where the
background is unbroken, or a dark patch left uncoloured, is then visible at
a glance instead of being a pixel count in the log. The projection is the
one the pre-scan already holds, so no frame is read twice; the picture is
rendered there and held as JPEG bytes until the canonical pass writes it,
because on a two-pass run the pre-scan belongs to the superseded pass.

<prefix>_plot.txt - one row per processed image, whitespace-separated with
a single '#' legend line over its own columns, so gnuplot plots it as it
stands: image, spindle angle, background, resolution, spot count, scale,
sigma_M, CC to merge, and whether the image's observations reached the
merged data. A quantity nothing measured is written nan, so the columns
never shift and no row is ever left out.

sigma_M is emitted as the pipeline produces it - a per-image Gaussian
rocking width, smoothed in frame order and filled with the run median where
a frame could not be fitted - and the documentation says so rather than
presenting it as a crystal property.

<prefix>_image.dat stays: the in-tree comparison scripts read it and it
carries the smoothing wedge, which the new file does not. The docs name
_plot.txt as the one to script against.

Measured on a 1800-image rotation sweep: 29.6/30.4 s before against
29.8/30.5 s after, and the merged reflections are byte-identical.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_013nW6FNRP1bBJJ8pfHiByAT
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