Make both batch image exports reproduce the view on screen

Two strands, committed together because they touch the same four files and answer the same question: an exported PNG must be the image the user was looking at when they triggered the export. Dropped view settings (bug fix): - BatchExportWorker forwarded the DC threshold, bg-sub, pad and row- averaging to compute_rf_image but never min_freq_mhz, so every RF and Velocity map was exported with no min peak frequency floor. The pixels the floor exists to reject came back at their pre-floor peaks. - That also decided *which source* the image came from: requesting floor 0 makes a stored v7 cache look like a match (cache_mismatch_reasons only rejects a higher stored floor), so a batch-computed file exported the cached peak-frequency block verbatim - numbers from an earlier Batch Compute run, while the screen showed that same cache re-masked against the live floor. The symptom was a newly loaded file exporting a stale-looking velocity map, since the floor is a display control that survives a load while the window's own FFT cache does not. - export_view_image had the same class of defect with a different parameter: it dropped row_avg_n, so a file whose stored cache is row- averaged displayed from the store but exported as a full raw recompute - a different, and much slower, image. It now reads sras.precomputed_row_avg_n per file, mirroring _stored_fft_image and _start_compute, and derived per file for the same reason n_fft is. Export at the live canvas size: - Both exporters now take the canvas's current figure size instead of a hard-coded 7x5. draw_view_image uses aspect="auto", so the figure box is what sets the map's proportions - a view sized wide on screen was being squeezed into a different shape on disk. Read at trigger time, in inches, so a resize mid-batch cannot change images later in the same run and a HiDPI display exports like a standard one. - sanitize_figsize clamps a degenerate size (collapsed splitter pane, minimized window): a wrong-looking aspect ratio must never be the reason a batch loses an image. Tests: BatchExportWorker had no coverage at all. Four new tests cover the floor being applied, a stored cache never being served unfloored, the menu-to-worker wiring, and the row-averaged cache case; each was verified to fail against the unfixed code. 166 passed. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Merge the Documents/sras-viewer working copy into this repo
2026-08-12 12:16:45 -05:00 · 2026-08-12 10:36:25 -05:00 · 2026-08-12 10:17:43 -05:00 · 2026-08-12 10:17:16 -05:00 · 2026-08-10 19:01:21 -05:00 · 2026-08-10 18:58:56 -05:00
35 changed files with 14979 additions and 4596 deletions
@@ -1,2 +1,9 @@
 __pycache__/
 .venv/
 .DS_Store
 .pytest_cache/
 *.png
 *.sras
 baseline*.txt
 after*.txt
 sras_viewer.egg-info/
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            <h1 id="sras-file-format-specification">SRAS File Format Specification</h1>
 <p><strong>Format family:</strong> <code>.sras</code><br>
 <strong>Byte order:</strong> Big-endian (network byte order) throughout, unless noted.<br>
 <strong>Version history:</strong> v2 (baseline), v3 (scope calibration), v4 (background waveform), v5 (precomputed images + guaranteed frame count).</p>
 <hr>
 <h2 id="table-of-contents">Table of Contents</h2>
 <ol>
 <li><a href="#overview">Overview</a></li>
 <li><a href="#type-notation">Type notation</a></li>
 <li><a href="#version-history">Version history</a></li>
 <li><a href="#file-structure">File structure</a>
 <ul>
 <li><a href="#1-fixed-header-43-bytes-all-versions">Fixed header (all versions)</a></li>
 <li><a href="#2-angle-table-all-versions">Angle table (all versions)</a></li>
 <li><a href="#3-row-position-table-all-versions">Row position table (all versions)</a></li>
 <li><a href="#4-channel-preambles-v3">Channel preambles (v3+)</a></li>
 <li><a href="#5-background-waveform-v4">Background waveform (v4+)</a></li>
 <li><a href="#6-waveform-data-all-versions">Waveform data (all versions)</a></li>
 <li><a href="#7-prec-section-v5">PREC section (v5)</a></li>
 </ul>
 </li>
 <li><a href="#derived-quantities">Derived quantities</a></li>
 <li><a href="#adc-calibration">ADC calibration</a></li>
 <li><a href="#waveform-data-layout-detail">Waveform data layout detail</a></li>
 <li><a href="#size-reference">Size reference</a></li>
 <li><a href="#compatibility-notes">Compatibility notes</a></li>
 </ol>
 <hr>
 <h2 id="overview">Overview</h2>
 <p>An SRAS file stores the raw RF waveforms captured during a Surface-acoustic-wave Resonance And Spectroscopy (SRAS) scan, along with the scan geometry and scope calibration metadata needed to interpret them.</p>
 <p>A scan consists of one or more <strong>angles</strong> (rotation positions of the sample), each containing a 2-D raster of <strong>rows</strong> × <strong>frames</strong>. At every pixel, <code>n_channels</code> waveforms of <code>samples_per_frame</code> ADC counts are stored. Channel order is fixed:</p>
 <table>
 <thead>
 <tr>
 <th>Index</th>
 <th>Hardware channel</th>
 <th>Signal</th>
 </tr>
 </thead>
 <tbody>
 <tr>
 <td>0</td>
 <td>CH1</td>
 <td>RF acoustic packet (AC-coupled)</td>
 </tr>
 <tr>
 <td>1</td>
 <td>CH3</td>
 <td>Bias A — DC mean used for masking</td>
 </tr>
 <tr>
 <td>2</td>
 <td>CH4</td>
 <td>Bias B — DC mean used for masking</td>
 </tr>
 </tbody>
 </table>
 <hr>
 <h2 id="type-notation">Type notation</h2>
 <table>
 <thead>
 <tr>
 <th>Symbol</th>
 <th>C type</th>
 <th>Size</th>
 <th>Notes</th>
 </tr>
 </thead>
 <tbody>
 <tr>
 <td><code>u8</code></td>
 <td><code>uint8_t</code></td>
 <td>1 byte</td>
 <td>unsigned</td>
 </tr>
 <tr>
 <td><code>u16</code></td>
 <td><code>uint16_t</code></td>
 <td>2 bytes</td>
 <td>big-endian</td>
 </tr>
 <tr>
 <td><code>u32</code></td>
 <td><code>uint32_t</code></td>
 <td>4 bytes</td>
 <td>big-endian</td>
 </tr>
 <tr>
 <td><code>i8</code></td>
 <td><code>int8_t</code></td>
 <td>1 byte</td>
 <td>signed, used for ADC samples when <code>bytes_per_sample == 1</code></td>
 </tr>
 <tr>
 <td><code>i16</code></td>
 <td><code>int16_t</code></td>
 <td>2 bytes</td>
 <td>big-endian signed, used when <code>bytes_per_sample == 2</code></td>
 </tr>
 <tr>
 <td><code>f32</code></td>
 <td><code>float</code></td>
 <td>4 bytes</td>
 <td>big-endian IEEE 754 single</td>
 </tr>
 <tr>
 <td><code>f64</code></td>
 <td><code>double</code></td>
 <td>8 bytes</td>
 <td>big-endian IEEE 754 double</td>
 </tr>
 <tr>
 <td><code>char[N]</code></td>
 <td>—</td>
 <td>N bytes</td>
 <td>raw bytes, no null terminator unless noted</td>
 </tr>
 <tr>
 <td><code>utf8[N]</code></td>
 <td>—</td>
 <td>N bytes</td>
 <td>UTF-8 string, length-prefixed (see preamble section)</td>
 </tr>
 </tbody>
 </table>
 <hr>
 <h2 id="version-history">Version history</h2>
 <table>
 <thead>
 <tr>
 <th>Version</th>
 <th>Added</th>
 </tr>
 </thead>
 <tbody>
 <tr>
 <td>2</td>
 <td>Baseline: fixed header, angle table, row table, raw waveform data. No scope calibration (fallback constants used by readers).</td>
 </tr>
 <tr>
 <td>3</td>
 <td>Per-channel Tektronix WFMOutpre preamble strings carrying YMULT / YOFF / YZERO calibration.</td>
 </tr>
 <tr>
 <td>4</td>
 <td>Background waveform section: one CH1 reference shot subtracted from each CH1 frame before FFT.</td>
 </tr>
 <tr>
 <td>5</td>
 <td><strong>(this document)</strong> Version byte incremented to 5. <code>n_frames_hdr</code> is now the <em>actual</em> acquired frame count (authoritative). PREC section appended after waveform data with precomputed FFT-peak and DC images for instant re-display.</td>
 </tr>
 </tbody>
 </table>
 <blockquote>
 <p><strong>v2 note:</strong> Version 1 is not defined; version 2 is the lowest observed in the field.</p>
 </blockquote>
 <hr>
 <h2 id="file-structure">File structure</h2>
 <pre><code>┌─────────────────────────────────────────────┐
 │  1. Fixed header                  (43 bytes) │  all versions
 ├─────────────────────────────────────────────┤
 │  2. Angle table          (n_angles × 4 bytes)│  all versions
 ├─────────────────────────────────────────────┤
 │  3. Row position table     (n_rows × 4 bytes)│  all versions
 ├─────────────────────────────────────────────┤
 │  4. Channel preambles           (variable)   │  v3+
 ├─────────────────────────────────────────────┤
 │  5. Background waveform         (variable)   │  v4+
 ├─────────────────────────────────────────────┤
 │  6. Waveform data               (variable)   │  all versions
 ├─────────────────────────────────────────────┤
 │  7. PREC section                (variable)   │  v5 only
 └─────────────────────────────────────────────┘
 </code></pre>
 <hr>
 <h3 id="1-fixed-header-43-bytes-all-versions">1. Fixed header (43 bytes, all versions)</h3>
 <table>
 <thead>
 <tr>
 <th>Offset</th>
 <th>Size</th>
 <th>Type</th>
 <th>Field</th>
 <th>Description</th>
 </tr>
 </thead>
 <tbody>
 <tr>
 <td>0</td>
 <td>4</td>
 <td><code>char[4]</code></td>
 <td><code>magic</code></td>
 <td><code>SRAS</code> (ASCII, no null terminator). Reject file if this does not match.</td>
 </tr>
 <tr>
 <td>4</td>
 <td>1</td>
 <td><code>u8</code></td>
 <td><code>version</code></td>
 <td>Format version. This document describes version <strong>5</strong>.</td>
 </tr>
 <tr>
 <td>5</td>
 <td>2</td>
 <td><code>u16</code></td>
 <td><code>n_angles</code></td>
 <td>Number of scan angles (rotation positions). ≥ 1.</td>
 </tr>
 <tr>
 <td>7</td>
 <td>2</td>
 <td><code>u16</code></td>
 <td><code>n_rows</code></td>
 <td>Number of scan rows (Y positions). ≥ 1.</td>
 </tr>
 <tr>
 <td>9</td>
 <td>4</td>
 <td><code>f32</code></td>
 <td><code>x_start_mm</code></td>
 <td>X position of the first frame in the first row, in millimetres.</td>
 </tr>
 <tr>
 <td>13</td>
 <td>4</td>
 <td><code>f32</code></td>
 <td><code>x_delta_mm</code></td>
 <td>Pre-computed pixel pitch in mm (<code>velocity_mm_s / laser_freq_hz</code>). Provided for convenience; readers should prefer the derived value.</td>
 </tr>
 <tr>
 <td>17</td>
 <td>4</td>
 <td><code>f32</code></td>
 <td><code>velocity_mm_s</code></td>
 <td>Scanner stage velocity, mm s⁻¹. Used together with <code>laser_freq_hz</code> to compute pixel pitch.</td>
 </tr>
 <tr>
 <td>21</td>
 <td>4</td>
 <td><code>f32</code></td>
 <td><code>laser_freq_hz</code></td>
 <td>Laser repetition rate, Hz.</td>
 </tr>
 <tr>
 <td>25</td>
 <td>4</td>
 <td><code>u32</code></td>
 <td><code>n_frames_hdr</code></td>
 <td><strong>v2–v4:</strong> the <em>configured</em> frame count written before acquisition; may exceed actual frames acquired (use file-size arithmetic to obtain the true count). <strong>v5:</strong> the <em>actual</em> acquired frame count — authoritative; readers must not re-derive it from file size.</td>
 </tr>
 <tr>
 <td>29</td>
 <td>4</td>
 <td><code>u32</code></td>
 <td><code>samples_per_frame</code></td>
 <td>ADC samples per waveform (<code>spf</code>).</td>
 </tr>
 <tr>
 <td>33</td>
 <td>8</td>
 <td><code>f64</code></td>
 <td><code>sample_rate_hz</code></td>
 <td>Oscilloscope sample rate, Hz (e.g. 5 × 10⁹ for 5 GS/s).</td>
 </tr>
 <tr>
 <td>41</td>
 <td>1</td>
 <td><code>u8</code></td>
 <td><code>bytes_per_sample</code></td>
 <td>ADC word size: <code>1</code> → <code>i8</code>, <code>2</code> → <code>i16</code> (big-endian).</td>
 </tr>
 <tr>
 <td>42</td>
 <td>1</td>
 <td><code>u8</code></td>
 <td><code>n_channels</code></td>
 <td>Number of channels per frame. Currently always <code>3</code>.</td>
 </tr>
 </tbody>
 </table>
 <hr>
 <h3 id="2-angle-table-all-versions">2. Angle table (all versions)</h3>
 <p>Immediately follows the fixed header.</p>
 <pre><code>n_angles × f32   — scan angle in degrees
 </code></pre>
 <p>Each entry is a big-endian <code>f32</code> giving the sample rotation angle in degrees at which that angle index was acquired.</p>
 <hr>
 <h3 id="3-row-position-table-all-versions">3. Row position table (all versions)</h3>
 <p>Immediately follows the angle table.</p>
 <pre><code>n_rows × f32   — Y position of each row, in millimetres
 </code></pre>
 <hr>
 <h3 id="4-channel-preambles-v3">4. Channel preambles (v3+)</h3>
 <p>One entry per channel, in channel-index order (CH1 first).</p>
 <pre><code>for each channel:
    u16          preamble_length   — byte count of the UTF-8 string that follows
    utf8[N]      preamble          — Tektronix WFMOutpre string
 </code></pre>
 <p>The preamble is the oscilloscope's <code>WFMOutpre</code> response string. Readers extract the following keys (case-insensitive, space-separated value):</p>
 <table>
 <thead>
 <tr>
 <th>Key</th>
 <th>Stored unit</th>
 <th>Conversion to mV</th>
 </tr>
 </thead>
 <tbody>
 <tr>
 <td><code>YMULT</code></td>
 <td>V count⁻¹</td>
 <td>multiply by 1000</td>
 </tr>
 <tr>
 <td><code>YOFF</code></td>
 <td>ADC counts</td>
 <td>used directly</td>
 </tr>
 <tr>
 <td><code>YZERO</code></td>
 <td>V</td>
 <td>multiply by 1000</td>
 </tr>
 </tbody>
 </table>
 <p><strong>v2 fallback:</strong> when preambles are absent, readers use:</p>
 <ul>
 <li><code>YMULT</code> = 1.5625 mV count⁻¹ (50 mV/div, 8 div, 8-bit ADC)</li>
 <li><code>YOFF</code>  = −87.04 ADC counts (scope position = −2.72 div)</li>
 <li><code>YZERO</code> = 0 mV</li>
 </ul>
 <hr>
 <h3 id="5-background-waveform-v4">5. Background waveform (v4+)</h3>
 <pre><code>u32          n_bg_samples   — number of i8 ADC samples that follow
 i8[n_bg]     background     — one representative CH1 background shot
 </code></pre>
 <p>The background waveform has the same <code>samples_per_frame</code> length as a normal CH1 waveform. It is subtracted from each CH1 waveform before FFT processing when background subtraction is enabled. When <code>n_bg_samples == 0</code> the section is present but empty.</p>
 <hr>
 <h3 id="6-waveform-data-all-versions">6. Waveform data (all versions)</h3>
 <p>Begins immediately after the fixed header (v2), preambles (v3), or background waveform (v4+). The waveform data is a flat, contiguous array with the following logical shape, stored in row-major (C) order:</p>
 <pre><code>waveform_data[n_angles][n_rows][n_channels][n_frames][samples_per_frame]
 </code></pre>
 <p>Each element is a signed ADC count of size <code>bytes_per_sample</code>:</p>
 <ul>
 <li><code>bytes_per_sample == 1</code> → <code>i8</code></li>
 <li><code>bytes_per_sample == 2</code> → <code>i16</code> big-endian</li>
 </ul>
 <p><strong>Total byte count:</strong></p>
 <pre><code>waveform_bytes = n_angles × n_rows × n_channels × n_frames × samples_per_frame × bytes_per_sample
 </code></pre>
 <h4 id="index-semantics">Index semantics</h4>
 <table>
 <thead>
 <tr>
 <th>Dimension</th>
 <th>Range</th>
 <th>Meaning</th>
 </tr>
 </thead>
 <tbody>
 <tr>
 <td><code>[a]</code></td>
 <td>0 … n_angles−1</td>
 <td>Scan angle (rotation position)</td>
 </tr>
 <tr>
 <td><code>[r]</code></td>
 <td>0 … n_rows−1</td>
 <td>Row (Y position); row 0 is the first acquired</td>
 </tr>
 <tr>
 <td><code>[c]</code></td>
 <td>0 … n_channels−1</td>
 <td>Channel (0=CH1 RF, 1=CH3 Bias A, 2=CH4 Bias B)</td>
 </tr>
 <tr>
 <td><code>[f]</code></td>
 <td>0 … n_frames−1</td>
 <td>Frame (X position) within the row</td>
 </tr>
 <tr>
 <td><code>[s]</code></td>
 <td>0 … spf−1</td>
 <td>Sample index within the waveform</td>
 </tr>
 </tbody>
 </table>
 <h4 id="frame-count-determination">Frame-count determination</h4>
 <ul>
 <li><strong>v5:</strong> use <code>n_frames_hdr</code> directly; do not use file-size arithmetic.</li>
 <li><strong>v2–v4:</strong> <code>n_frames = floor((file_bytes_after_header_sections) / (bytes_per_sample × n_angles × n_rows × n_channels × samples_per_frame))</code>. Any remainder bytes are a partial trailing row and are discarded.</li>
 </ul>
 <hr>
 <h3 id="7-prec-section-v5">7. PREC section (v5)</h3>
 <p>The PREC section is appended immediately after the waveform data and is present if and only if <code>version == 5</code> and the file size exceeds <code>waveform_end_offset</code>.</p>
 <pre><code>waveform_end_offset = data_offset + waveform_bytes
 </code></pre>
 <p>where <code>data_offset</code> is the file offset of the first waveform byte (the byte immediately after the background waveform, or after the angle/row tables for v2 files).</p>
 <h4 id="prec-header-8-bytes">PREC header (8 bytes)</h4>
 <table>
 <thead>
 <tr>
 <th>Offset (relative)</th>
 <th>Size</th>
 <th>Type</th>
 <th>Field</th>
 <th>Description</th>
 </tr>
 </thead>
 <tbody>
 <tr>
 <td>0</td>
 <td>4</td>
 <td><code>char[4]</code></td>
 <td><code>prec_magic</code></td>
 <td><code>PREC</code> (ASCII). Absent or wrong magic → ignore section.</td>
 </tr>
 <tr>
 <td>4</td>
 <td>1</td>
 <td><code>u8</code></td>
 <td><code>prec_version</code></td>
 <td>PREC format version. Currently <code>1</code>.</td>
 </tr>
 <tr>
 <td>5</td>
 <td>1</td>
 <td><code>u8</code></td>
 <td><code>flags</code></td>
 <td>Bitmask (see below).</td>
 </tr>
 <tr>
 <td>6</td>
 <td>2</td>
 <td><code>u16</code></td>
 <td><code>n_stored</code></td>
 <td>Number of angle entries that follow. 0 ≤ <code>n_stored</code> ≤ <code>n_angles</code>.</td>
 </tr>
 </tbody>
 </table>
 <h5 id="flags-byte">Flags byte</h5>
 <table>
 <thead>
 <tr>
 <th>Bit</th>
 <th>Mask</th>
 <th>Meaning when set</th>
 </tr>
 </thead>
 <tbody>
 <tr>
 <td>0</td>
 <td><code>0x01</code></td>
 <td><code>bg_sub_applied</code> — background waveform was subtracted from CH1 before the FFT when these images were computed.</td>
 </tr>
 <tr>
 <td>1–7</td>
 <td>—</td>
 <td>Reserved, must be zero on write; readers must ignore.</td>
 </tr>
 </tbody>
 </table>
 <h4 id="prec-angle-entries">PREC angle entries</h4>
 <p>Repeated <code>n_stored</code> times, in arbitrary angle-index order:</p>
 <pre><code>for each stored angle:
    u16                   angle_idx      — index into the angle table (0-based)
    f32[n_rows×n_frames]  peak_freq_mhz  — CH1 FFT peak frequency, MHz, row-major
    f32[n_rows×n_frames]  dc4_mv         — CH4 waveform mean, mV, row-major
    f32[n_rows×n_frames]  dc3_mv         — CH3 waveform mean, mV, row-major
 </code></pre>
 <p>All image arrays are <code>f32</code> big-endian, stored in row-major order: element <code>[r][f]</code> is at offset <code>(r × n_frames + f) × 4</code> bytes within the array.</p>
 <p><strong><code>peak_freq_mhz</code></strong> is computed without any DC-threshold masking (i.e. the FFT is run on every pixel unconditionally). Readers apply the <code>dc4_mv</code> threshold at display time:</p>
 <pre><code>pixel is valid  ⟺  dc4_mv[r][f]  ≥  threshold_mv
 display_value   =   peak_freq_mhz[r][f]  if valid, else 0
 </code></pre>
 <p><strong><code>dc4_mv</code> / <code>dc3_mv</code></strong> are the mean of all ADC samples in the respective channel waveform, converted to millivolts using the channel calibration:</p>
 <pre><code>dc_mv = (adc_mean − YOFF) × YMULT + YZERO
 </code></pre>
 <h4 id="when-readers-must-bypass-the-prec-fast-path">When readers must bypass the PREC fast path</h4>
 <p>Readers must fall back to real-time FFT computation (ignoring stored <code>peak_freq_mhz</code>) when any of the following are true:</p>
 <ul>
 <li>Time-domain gating is active (zeroing samples outside a time window changes peak frequency).</li>
 <li>Zero-padding (<code>n_fft ≠ samples_per_frame</code>) is requested (changes bin spacing).</li>
 <li>The reader's background-subtraction setting does not match <code>flags.bg_sub_applied</code>.</li>
 </ul>
 <hr>
 <h2 id="derived-quantities">Derived quantities</h2>
 <pre><code>pixel_pitch_mm  = velocity_mm_s / laser_freq_hz
 x_axis_mm[f]    = x_start_mm + f × pixel_pitch_mm          (f = 0 … n_frames−1)
 time_axis_ns[s] = s / sample_rate_hz × 1e9                 (s = 0 … spf−1)
 freq_axis_mhz[k] = k × sample_rate_hz / (n_fft × 1e6)      (k = 0 … n_fft/2)
                   where n_fft = samples_per_frame unless zero-padding is active
 velocity_ms[r][f] = peak_freq_mhz[r][f] × grating_um       (grating_um user-supplied)
 </code></pre>
 <hr>
 <h2 id="adc-calibration">ADC calibration</h2>
 <p>Convert raw ADC counts to millivolts:</p>
 <pre><code>voltage_mv = (adc_count − YOFF) × YMULT_mv + YZERO_mv
 </code></pre>
 <p>Invert (mV → ADC count):</p>
 <pre><code>adc_count = (voltage_mv − YZERO_mv) / YMULT_mv + YOFF
 </code></pre>
 <p>where <code>YMULT_mv</code> is YMULT in mV count⁻¹ (= scope YMULT in V count⁻¹ × 1000).</p>
 <hr>
 <h2 id="waveform-data-layout-detail">Waveform data layout detail</h2>
 <p>For a scan with <code>n_angles=2</code>, <code>n_rows=3</code>, <code>n_channels=3</code>, <code>n_frames=4</code>, <code>spf=5</code> the layout is:</p>
 <pre><code>angle 0
  row 0
    CH1: [s0 s1 s2 s3 s4] [s0 s1 s2 s3 s4] [s0 s1 s2 s3 s4] [s0 s1 s2 s3 s4]
          frame 0           frame 1           frame 2           frame 3
    CH3: …(same layout)…
    CH4: …(same layout)…
  row 1
    …
  row 2
    …
 angle 1
  …
 </code></pre>
 <p>The flat byte offset of sample <code>s</code> of frame <code>f</code>, channel <code>c</code>, row <code>r</code>, angle <code>a</code> is:</p>
 <pre><code>offset = data_offset
       + (a × n_rows × n_channels × n_frames × spf
         + r × n_channels × n_frames × spf
         + c × n_frames × spf
         + f × spf
         + s)
       × bytes_per_sample
 </code></pre>
 <hr>
 <h2 id="size-reference">Size reference</h2>
 <p>Approximate sizes for representative scans (<code>bytes_per_sample = 1</code>, <code>n_channels = 3</code>).</p>
 <table>
 <thead>
 <tr>
 <th>n_angles</th>
 <th>n_rows</th>
 <th>n_frames</th>
 <th>spf</th>
 <th>Waveform data</th>
 <th>PREC section</th>
 </tr>
 </thead>
 <tbody>
 <tr>
 <td>1</td>
 <td>500</td>
 <td>500</td>
 <td>400</td>
 <td>300 MB</td>
 <td>12 MB</td>
 </tr>
 <tr>
 <td>4</td>
 <td>500</td>
 <td>500</td>
 <td>400</td>
 <td>1.2 GB</td>
 <td>48 MB</td>
 </tr>
 <tr>
 <td>1</td>
 <td>2000</td>
 <td>2000</td>
 <td>400</td>
 <td>4.8 GB</td>
 <td>48 MB</td>
 </tr>
 <tr>
 <td>4</td>
 <td>2000</td>
 <td>2000</td>
 <td>400</td>
 <td>19.2 GB</td>
 <td>192 MB</td>
 </tr>
 <tr>
 <td>8</td>
 <td>2000</td>
 <td>2000</td>
 <td>400</td>
 <td>38.4 GB</td>
 <td>384 MB</td>
 </tr>
 <tr>
 <td>16</td>
 <td>2000</td>
 <td>2000</td>
 <td>400</td>
 <td>76.8 GB</td>
 <td>768 MB</td>
 </tr>
 </tbody>
 </table>
 <p><strong>PREC section size formula:</strong></p>
 <pre><code>prec_bytes = 8  +  n_stored × (2 + 3 × n_rows × n_frames × 4)
 </code></pre>
 <hr>
 <h2 id="compatibility-notes">Compatibility notes</h2>
 <h3 id="reading-v5-files-with-a-v4-reader">Reading v5 files with a v4 reader</h3>
 <p>A v4 reader that only accepts versions <code>{2, 3, 4}</code> will reject a v5 file with an &quot;unsupported version&quot; error. This is intentional: a v4 reader would derive <code>n_frames</code> from the file size, incorrectly including the PREC bytes in the sample count, producing a silently wrong reshape.</p>
 <h3 id="producing-v5-files">Producing v5 files</h3>
 <p>v5 files are produced by the SRAS viewer's <strong>&quot;Pre-process and Save as v5&quot;</strong> action. The procedure is:</p>
 <ol>
 <li>Copy the source file (any version) verbatim.</li>
 <li>Set <code>version = 5</code> at byte offset 4.</li>
 <li>Set <code>n_frames_hdr</code> at byte offset 25 to the actual acquired frame count.</li>
 <li>Truncate the copy to <code>data_offset + waveform_bytes</code> (removes any pre-existing stale PREC tail).</li>
 <li>Compute <code>peak_freq_mhz</code>, <code>dc4_mv</code>, and <code>dc3_mv</code> for every angle using chunked FFT.</li>
 <li>Append the PREC section.</li>
 </ol>
 <h3 id="partially-written-prec-sections">Partially-written PREC sections</h3>
 <p>If <code>n_stored &lt; n_angles</code> (e.g. pre-processing was interrupted), the file is still valid. Readers use stored images for the angles present in the PREC section and fall back to real-time FFT for the remainder. Readers must check <code>angle_idx</code> bounds on each entry and stop parsing on an out-of-range value.</p>
        </body>
        </html>
@@ -1,379 +0,0 @@
 # SRAS File Format Specification
 **Format family:** `.sras`  
 **Byte order:** Big-endian (network byte order) throughout, unless noted.  
 **Version history:** v2 (baseline), v3 (scope calibration), v4 (background waveform), v5 (precomputed images + guaranteed frame count).
 ---
 ## Table of Contents
 1. [Overview](#overview)
 2. [Type notation](#type-notation)
 3. [Version history](#version-history)
 4. [File structure](#file-structure)
   - [Fixed header (all versions)](#1-fixed-header-43-bytes-all-versions)
   - [Angle table (all versions)](#2-angle-table-all-versions)
   - [Row position table (all versions)](#3-row-position-table-all-versions)
   - [Channel preambles (v3+)](#4-channel-preambles-v3)
   - [Background waveform (v4+)](#5-background-waveform-v4)
   - [Waveform data (all versions)](#6-waveform-data-all-versions)
   - [PREC section (v5)](#7-prec-section-v5)
 5. [Derived quantities](#derived-quantities)
 6. [ADC calibration](#adc-calibration)
 7. [Waveform data layout detail](#waveform-data-layout-detail)
 8. [Size reference](#size-reference)
 9. [Compatibility notes](#compatibility-notes)
 ---
 ## Overview
 An SRAS file stores the raw RF waveforms captured during a Surface-acoustic-wave Resonance And Spectroscopy (SRAS) scan, along with the scan geometry and scope calibration metadata needed to interpret them.
 A scan consists of one or more **angles** (rotation positions of the sample), each containing a 2-D raster of **rows** × **frames**. At every pixel, `n_channels` waveforms of `samples_per_frame` ADC counts are stored. Channel order is fixed:
 | Index | Hardware channel | Signal |
 |-------|-----------------|--------|
 | 0     | CH1             | RF acoustic packet (AC-coupled) |
 | 1     | CH3             | Bias A — DC mean used for masking |
 | 2     | CH4             | Bias B — DC mean used for masking |
 ---
 ## Type notation
 | Symbol | C type | Size | Notes |
 |--------|--------|------|-------|
 | `u8`   | `uint8_t`  | 1 byte | unsigned |
 | `u16`  | `uint16_t` | 2 bytes | big-endian |
 | `u32`  | `uint32_t` | 4 bytes | big-endian |
 | `i8`   | `int8_t`   | 1 byte | signed, used for ADC samples when `bytes_per_sample == 1` |
 | `i16`  | `int16_t`  | 2 bytes | big-endian signed, used when `bytes_per_sample == 2` |
 | `f32`  | `float`    | 4 bytes | big-endian IEEE 754 single |
 | `f64`  | `double`   | 8 bytes | big-endian IEEE 754 double |
 | `char[N]` | —      | N bytes | raw bytes, no null terminator unless noted |
 | `utf8[N]` | —      | N bytes | UTF-8 string, length-prefixed (see preamble section) |
 ---
 ## Version history
 | Version | Added |
 |---------|-------|
 | 2 | Baseline: fixed header, angle table, row table, raw waveform data. No scope calibration (fallback constants used by readers). |
 | 3 | Per-channel Tektronix WFMOutpre preamble strings carrying YMULT / YOFF / YZERO calibration. |
 | 4 | Background waveform section: one CH1 reference shot subtracted from each CH1 frame before FFT. |
 | 5 | **(this document)** Version byte incremented to 5. `n_frames_hdr` is now the *actual* acquired frame count (authoritative). PREC section appended after waveform data with precomputed FFT-peak and DC images for instant re-display. |
 > **v2 note:** Version 1 is not defined; version 2 is the lowest observed in the field.
 ---
 ## File structure
 ```
 ┌─────────────────────────────────────────────┐
 │  1. Fixed header                  (43 bytes) │  all versions
 ├─────────────────────────────────────────────┤
 │  2. Angle table          (n_angles × 4 bytes)│  all versions
 ├─────────────────────────────────────────────┤
 │  3. Row position table     (n_rows × 4 bytes)│  all versions
 ├─────────────────────────────────────────────┤
 │  4. Channel preambles           (variable)   │  v3+
 ├─────────────────────────────────────────────┤
 │  5. Background waveform         (variable)   │  v4+
 ├─────────────────────────────────────────────┤
 │  6. Waveform data               (variable)   │  all versions
 ├─────────────────────────────────────────────┤
 │  7. PREC section                (variable)   │  v5 only
 └─────────────────────────────────────────────┘
 ```
 ---
 ### 1. Fixed header (43 bytes, all versions)
 | Offset | Size | Type | Field | Description |
 |--------|------|------|-------|-------------|
 | 0 | 4 | `char[4]` | `magic` | `SRAS` (ASCII, no null terminator). Reject file if this does not match. |
 | 4 | 1 | `u8` | `version` | Format version. This document describes version **5**. |
 | 5 | 2 | `u16` | `n_angles` | Number of scan angles (rotation positions). ≥ 1. |
 | 7 | 2 | `u16` | `n_rows` | Number of scan rows (Y positions). ≥ 1. |
 | 9 | 4 | `f32` | `x_start_mm` | X position of the first frame in the first row, in millimetres. |
 | 13 | 4 | `f32` | `x_delta_mm` | Pre-computed pixel pitch in mm (`velocity_mm_s / laser_freq_hz`). Provided for convenience; readers should prefer the derived value. |
 | 17 | 4 | `f32` | `velocity_mm_s` | Scanner stage velocity, mm s⁻¹. Used together with `laser_freq_hz` to compute pixel pitch. |
 | 21 | 4 | `f32` | `laser_freq_hz` | Laser repetition rate, Hz. |
 | 25 | 4 | `u32` | `n_frames_hdr` | **v2–v4:** the *configured* frame count written before acquisition; may exceed actual frames acquired (use file-size arithmetic to obtain the true count). **v5:** the *actual* acquired frame count — authoritative; readers must not re-derive it from file size. |
 | 29 | 4 | `u32` | `samples_per_frame` | ADC samples per waveform (`spf`). |
 | 33 | 8 | `f64` | `sample_rate_hz` | Oscilloscope sample rate, Hz (e.g. 5 × 10⁹ for 5 GS/s). |
 | 41 | 1 | `u8` | `bytes_per_sample` | ADC word size: `1` → `i8`, `2` → `i16` (big-endian). |
 | 42 | 1 | `u8` | `n_channels` | Number of channels per frame. Currently always `3`. |
 ---
 ### 2. Angle table (all versions)
 Immediately follows the fixed header.
 ```
 n_angles × f32   — scan angle in degrees
 ```
 Each entry is a big-endian `f32` giving the sample rotation angle in degrees at which that angle index was acquired.
 ---
 ### 3. Row position table (all versions)
 Immediately follows the angle table.
 ```
 n_rows × f32   — Y position of each row, in millimetres
 ```
 ---
 ### 4. Channel preambles (v3+)
 One entry per channel, in channel-index order (CH1 first).
 ```
 for each channel:
    u16          preamble_length   — byte count of the UTF-8 string that follows
    utf8[N]      preamble          — Tektronix WFMOutpre string
 ```
 The preamble is the oscilloscope's `WFMOutpre` response string. Readers extract the following keys (case-insensitive, space-separated value):
 | Key | Stored unit | Conversion to mV |
 |-----|-------------|-----------------|
 | `YMULT` | V count⁻¹ | multiply by 1000 |
 | `YOFF` | ADC counts | used directly |
 | `YZERO` | V | multiply by 1000 |
 **v2 fallback:** when preambles are absent, readers use:
 - `YMULT` = 1.5625 mV count⁻¹ (50 mV/div, 8 div, 8-bit ADC)
 - `YOFF`  = −87.04 ADC counts (scope position = −2.72 div)
 - `YZERO` = 0 mV
 ---
 ### 5. Background waveform (v4+)
 ```
 u32          n_bg_samples   — number of i8 ADC samples that follow
 i8[n_bg]     background     — one representative CH1 background shot
 ```
 The background waveform has the same `samples_per_frame` length as a normal CH1 waveform. It is subtracted from each CH1 waveform before FFT processing when background subtraction is enabled. When `n_bg_samples == 0` the section is present but empty.
 ---
 ### 6. Waveform data (all versions)
 Begins immediately after the fixed header (v2), preambles (v3), or background waveform (v4+). The waveform data is a flat, contiguous array with the following logical shape, stored in row-major (C) order:
 ```
 waveform_data[n_angles][n_rows][n_channels][n_frames][samples_per_frame]
 ```
 Each element is a signed ADC count of size `bytes_per_sample`:
 - `bytes_per_sample == 1` → `i8`
 - `bytes_per_sample == 2` → `i16` big-endian
 **Total byte count:**
 ```
 waveform_bytes = n_angles × n_rows × n_channels × n_frames × samples_per_frame × bytes_per_sample
 ```
 #### Index semantics
 | Dimension | Range | Meaning |
 |-----------|-------|---------|
 | `[a]` | 0 … n_angles−1 | Scan angle (rotation position) |
 | `[r]` | 0 … n_rows−1 | Row (Y position); row 0 is the first acquired |
 | `[c]` | 0 … n_channels−1 | Channel (0=CH1 RF, 1=CH3 Bias A, 2=CH4 Bias B) |
 | `[f]` | 0 … n_frames−1 | Frame (X position) within the row |
 | `[s]` | 0 … spf−1 | Sample index within the waveform |
 #### Frame-count determination
 - **v5:** use `n_frames_hdr` directly; do not use file-size arithmetic.
 - **v2–v4:** `n_frames = floor((file_bytes_after_header_sections) / (bytes_per_sample × n_angles × n_rows × n_channels × samples_per_frame))`. Any remainder bytes are a partial trailing row and are discarded.
 ---
 ### 7. PREC section (v5)
 The PREC section is appended immediately after the waveform data and is present if and only if `version == 5` and the file size exceeds `waveform_end_offset`.
 ```
 waveform_end_offset = data_offset + waveform_bytes
 ```
 where `data_offset` is the file offset of the first waveform byte (the byte immediately after the background waveform, or after the angle/row tables for v2 files).
 #### PREC header (8 bytes)
 | Offset (relative) | Size | Type | Field | Description |
 |-------------------|------|------|-------|-------------|
 | 0 | 4 | `char[4]` | `prec_magic` | `PREC` (ASCII). Absent or wrong magic → ignore section. |
 | 4 | 1 | `u8` | `prec_version` | PREC format version. Currently `1`. |
 | 5 | 1 | `u8` | `flags` | Bitmask (see below). |
 | 6 | 2 | `u16` | `n_stored` | Number of angle entries that follow. 0 ≤ `n_stored` ≤ `n_angles`. |
 ##### Flags byte
 | Bit | Mask | Meaning when set |
 |-----|------|-----------------|
 | 0 | `0x01` | `bg_sub_applied` — background waveform was subtracted from CH1 before the FFT when these images were computed. |
 | 1–7 | — | Reserved, must be zero on write; readers must ignore. |
 #### PREC angle entries
 Repeated `n_stored` times, in arbitrary angle-index order:
 ```
 for each stored angle:
    u16                   angle_idx      — index into the angle table (0-based)
    f32[n_rows×n_frames]  peak_freq_mhz  — CH1 FFT peak frequency, MHz, row-major
    f32[n_rows×n_frames]  dc4_mv         — CH4 waveform mean, mV, row-major
    f32[n_rows×n_frames]  dc3_mv         — CH3 waveform mean, mV, row-major
 ```
 All image arrays are `f32` big-endian, stored in row-major order: element `[r][f]` is at offset `(r × n_frames + f) × 4` bytes within the array.
 **`peak_freq_mhz`** is computed without any DC-threshold masking (i.e. the FFT is run on every pixel unconditionally). Readers apply the `dc4_mv` threshold at display time:
 ```
 pixel is valid  ⟺  dc4_mv[r][f]  ≥  threshold_mv
 display_value   =   peak_freq_mhz[r][f]  if valid, else 0
 ```
 **`dc4_mv` / `dc3_mv`** are the mean of all ADC samples in the respective channel waveform, converted to millivolts using the channel calibration:
 ```
 dc_mv = (adc_mean − YOFF) × YMULT + YZERO
 ```
 #### When readers must bypass the PREC fast path
 Readers must fall back to real-time FFT computation (ignoring stored `peak_freq_mhz`) when any of the following are true:
 - Time-domain gating is active (zeroing samples outside a time window changes peak frequency).
 - Zero-padding (`n_fft ≠ samples_per_frame`) is requested (changes bin spacing).
 - The reader's background-subtraction setting does not match `flags.bg_sub_applied`.
 ---
 ## Derived quantities
 ```
 pixel_pitch_mm  = velocity_mm_s / laser_freq_hz
 x_axis_mm[f]    = x_start_mm + f × pixel_pitch_mm          (f = 0 … n_frames−1)
 time_axis_ns[s] = s / sample_rate_hz × 1e9                 (s = 0 … spf−1)
 freq_axis_mhz[k] = k × sample_rate_hz / (n_fft × 1e6)      (k = 0 … n_fft/2)
                   where n_fft = samples_per_frame unless zero-padding is active
 velocity_ms[r][f] = peak_freq_mhz[r][f] × grating_um       (grating_um user-supplied)
 ```
 ---
 ## ADC calibration
 Convert raw ADC counts to millivolts:
 ```
 voltage_mv = (adc_count − YOFF) × YMULT_mv + YZERO_mv
 ```
 Invert (mV → ADC count):
 ```
 adc_count = (voltage_mv − YZERO_mv) / YMULT_mv + YOFF
 ```
 where `YMULT_mv` is YMULT in mV count⁻¹ (= scope YMULT in V count⁻¹ × 1000).
 ---
 ## Waveform data layout detail
 For a scan with `n_angles=2`, `n_rows=3`, `n_channels=3`, `n_frames=4`, `spf=5` the layout is:
 ```
 angle 0
  row 0
    CH1: [s0 s1 s2 s3 s4] [s0 s1 s2 s3 s4] [s0 s1 s2 s3 s4] [s0 s1 s2 s3 s4]
          frame 0           frame 1           frame 2           frame 3
    CH3: …(same layout)…
    CH4: …(same layout)…
  row 1
    …
  row 2
    …
 angle 1
  …
 ```
 The flat byte offset of sample `s` of frame `f`, channel `c`, row `r`, angle `a` is:
 ```
 offset = data_offset
       + (a × n_rows × n_channels × n_frames × spf
         + r × n_channels × n_frames × spf
         + c × n_frames × spf
         + f × spf
         + s)
       × bytes_per_sample
 ```
 ---
 ## Size reference
 Approximate sizes for representative scans (`bytes_per_sample = 1`, `n_channels = 3`).
 | n_angles | n_rows | n_frames | spf | Waveform data | PREC section |
 |----------|--------|----------|-----|---------------|-------------|
 | 1 | 500 | 500 | 400 | 300 MB | 12 MB |
 | 4 | 500 | 500 | 400 | 1.2 GB | 48 MB |
 | 1 | 2000 | 2000 | 400 | 4.8 GB | 48 MB |
 | 4 | 2000 | 2000 | 400 | 19.2 GB | 192 MB |
 | 8 | 2000 | 2000 | 400 | 38.4 GB | 384 MB |
 | 16 | 2000 | 2000 | 400 | 76.8 GB | 768 MB |
 **PREC section size formula:**
 ```
 prec_bytes = 8  +  n_stored × (2 + 3 × n_rows × n_frames × 4)
 ```
 ---
 ## Compatibility notes
 ### Reading v5 files with a v4 reader
 A v4 reader that only accepts versions `{2, 3, 4}` will reject a v5 file with an "unsupported version" error. This is intentional: a v4 reader would derive `n_frames` from the file size, incorrectly including the PREC bytes in the sample count, producing a silently wrong reshape.
 ### Producing v5 files
 v5 files are produced by the SRAS viewer's **"Pre-process and Save as v5"** action. The procedure is:
 1. Copy the source file (any version) verbatim.
 2. Set `version = 5` at byte offset 4.
 3. Set `n_frames_hdr` at byte offset 25 to the actual acquired frame count.
 4. Truncate the copy to `data_offset + waveform_bytes` (removes any pre-existing stale PREC tail).
 5. Compute `peak_freq_mhz`, `dc4_mv`, and `dc3_mv` for every angle using chunked FFT.
 6. Append the PREC section.
 ### Partially-written PREC sections
 If `n_stored < n_angles` (e.g. pre-processing was interrupted), the file is still valid. Readers use stored images for the angles present in the PREC section and fall back to real-time FFT for the remainder. Readers must check `angle_idx` bounds on each entry and stop parsing on an out-of-range value.
@@ -0,0 +1,427 @@
 # sras-viewer design notes
 Rationale that outgrew code comments. Each section is referenced by a short
 pointer comment at the relevant definition, so the code stays scannable and
 the reasoning stays findable.
 ## Memory budget and row chunking (`sras_compute.py`)
 DC images are computed over row chunks so the float32 working buffers for one
 chunk stay under a memory budget. A fixed row count (the original design)
 works fine for small legacy scans but is catastrophic for a v6 scan with a
 large per-angle frame/sample count — e.g. a 7500-frame × 2500-sample angle
 needs ~2.4 GB for a single 32-row chunk.
 With chunks running concurrently the budget has to cover *all* live chunks at
 once. On a large scan `chunk_rows` is already clamped to its floor of one row
 (one row alone is ~75 MB of float32 at 7507×2500), so shrinking the per-chunk
 size cannot buy more concurrency — the worker count must be derived from the
 budget instead: `_plan_chunks` picks the worker count *first* and sizes the
 chunk to it. Sizing the chunk first is the trap: a single chunk would always
 consume the whole budget and leave room for exactly one worker, precisely on
 the large scans that need concurrency most.
 The 1024 MB default (`SRAS_MEM_BUDGET_MB`) is the measured knee on a 16-core
 machine against a 7507-frame × 2500-sample angle: 512 MB left ~20% of the
 speedup on the table, and 1536+ MB cost ~0.4 GB more resident memory for no
 further gain.
 A caller that itself runs several computations concurrently (angle-level
 parallelism, `plan_angle_level`) must pass *both* `max_workers=1` and its
 share of the budget. Capping the workers alone is not enough: the chunk would
 still be sized against the whole budget, and N concurrent callers would each
 allocate all of it.
 ## FFT peak search: block-parallel direct transform (`sras_compute.py`)
 The displayed RF value per pixel is the argmax of the zero-padded power
 spectrum of that pixel's CH1 waveform. This used to run through `_peak_bins_zoom`,
 a coarse-rfft-plus-local-fine-DFT refinement that avoided ever materialising
 a padded spectrum — at the pad factor of 40 needed for mapping resolution, a
 full padded spectrum is ~9 GB per scan row, which used to collapse the old
 row-chunk planner to one worker and make synthesis single-threaded. That
 refinement was removed once pyFFTW became the sole, mandatory FFT backend
 (SciPy dropped as a compute backend entirely): `_peak_bins` now always runs
 the real full transform, and the memory problem zoom dodged is instead
 solved by bounding *per-block* spectrum memory rather than avoiding full
 spectra altogether.
 `_peak_bins` runs the full transform (`_block_rfft`, a cached pyFFTW
 `builders.rfft` plan, FFTW_MEASURE, wisdom persisted under
 `~/.cache/sras-viewer/`) and argmaxes the power spectrum, in blocks fanned
 out task-parallel over a persistent thread pool (`_fft_pool()`) — each pool
 thread runs one single-threaded transform at a time, so aggregate
 parallelism equals the pool's worker count. This block-streaming structure
 is not just about parallelism: it is also what keeps memory bounded, by
 never materialising more than one block's worth of full padded spectrum at
 a time, regardless of how many waveforms a chunk holds.
 The block size is the part that has to adapt to pad factor.
 `_fft_block_for(spf, n_len)` derives waveforms-per-task from a fixed
 per-thread byte budget (`_FFT_PLAN_BYTES_BUDGET`, `SRAS_FFT_PLAN_BUDGET_MB`,
 default 16 MB) rather than a fixed constant, because a cached pyFFTW plan's
 input+output buffers are *permanent* per-thread memory (the plan cache is
 never evicted) — with a fixed 512-waveform block, pad 40 at a 2500-sample
 frame costs ~210 MB per pool thread (~3.3 GB total across 16 threads);
 `_fft_block_for` bounds that to ~16 MB per thread (~260 MB across 16
 threads) at the same pad factor, while still reproducing the old tuned 512
 exactly at natural resolution (pad 1), where it cost nothing to begin with.
 `_FFT_BLOCK_MAX` (512) and `_FFT_BLOCK_MIN` (32) cap and floor the result:
 the ceiling is the measured knee on a 16-core machine at natural resolution
 (smaller blocks serialise on GIL-held numpy dispatch, larger ones lose cache
 residency and task granularity); the floor keeps task granularity from
 collapsing at extreme pad factors, at the cost of exceeding the byte budget
 there.
 The outer row-chunk sizing (`_plan_fft_rows`) needed no companion change.
 It only ever budgets the raw float32 waveform *read* buffer, which this
 change doesn't touch — spectrum memory is bounded independently by
 `_fft_block_for`, and since the pool only ever runs as many blocks
 concurrently as it has workers, peak transient spectrum memory during a
 chunk's FFT phase is `_MAX_WORKERS * block * bytes_per_wf`, the same bound
 whether the chunk holds 10 rows or 10,000. Queuing more rows into one chunk
 to keep the read-row pool busy therefore can't blow up spectrum memory.
 `tools/check_equivalence.py`'s golden-hash harness remains the end-to-end
 regression baseline for this path, unaffected by this change.
 ## Row-averaged FFT: same-row, distance-weighted SNR cleanup (`sras_compute.py`)
 `compute_rf_image`'s `row_avg_n` parameter averages each pixel's CH1
 waveform with its up-to-n same-row neighbors before the FFT peak search, to
 improve SNR on noisy scans. Never crosses rows: pixel pitch is strongly
 anisotropic and varies by scan (5 µm × 50 µm on a typical scan, but as
 stretched as 5 µm × 1 mm on others), so a physically meaningful "neighbor"
 set can't be a fixed-shape 2-D window — but the X pitch *within one row* is
 a single file-wide constant (`SrasFile.pixel_x_mm`), so restricting to the
 row axis sidesteps the anisotropy question entirely rather than solving it
 with an elliptical or physically-scaled 2-D kernel.
 `_row_average_weights` is a Gaussian in pixel-index distance, not physical
 mm distance — deliberately: within one row those are the same function up
 to a fixed scale factor (`pixel_x_mm` is constant along a row), so the
 kernel itself needs no pitch at all. `pixel_x_mm` is used for real exactly
 once, in the GUI's options dialog, to show the window's physical width —
 not in the kernel math, where it would only ever cancel out.
 `_row_average_waveforms` is a masked/renormalized convolution (two
 `correlate1d` calls, numerator and denominator, divided) rather than a
 single fixed-normalized convolution, because a masked neighbor must
 contribute *zero weight*, not a zero-amplitude sample at full weight — the
 latter would bias every average near a masked run or a row's own edge
 toward zero. The same two-correlation trick handles row-edge truncation for
 free: `mode="constant", cval=0.0` zero-pads both the numerator and the
 denominator beyond a row's own ends, so the output renormalizes by whatever
 weight sum actually landed inside the row, no separate edge case.
 Background subtraction stays exactly where it already was (subtracted once
 from the fully-assembled `waves` buffer) rather than being threaded into the
 per-neighbor gather. This is exact, not an approximation: because
 `_row_average_waveforms`'s denominator is always the *actual* sum of
 included, valid weights (never a fixed total), `Σwᵢ·(rawᵢ−bg) / Σwᵢ`
 distributes to `avg − bg·(Σwᵢ/Σwᵢ) = avg − bg` regardless of which or how
 many neighbors were included — subtracting background from the averaged
 waveform is identical to subtracting it from every neighbor first, for any
 window, at any row edge, with any number of masked-out neighbors.
 No cross-row halo is needed: `compute_rf_image`'s chunk loop already splits
 on rows only, and `read_row` already reads one row's complete
 `(n_frames, spf)` slice at a time — averaging happens entirely inside that
 one row's own frame axis, so a chunk boundary (which falls between rows)
 can never truncate a window. Only a row's own start/end can, and that's the
 same edge case the masked convolution already handles.
 The averaging step doubles the live per-row scratch memory (a full-width
 `(n_frames, spf)` buffer on top of the existing compacted `waves` buffer),
 so `compute_rf_image` halves its byte budget when `row_avg_n > 0` before
 `_plan_fft_rows` runs — see "Memory budget and row chunking" above. On the
 largest real scans `_plan_chunks` is already
 clamped to its floor of one row regardless, so this costs no concurrency
 where it matters most; it mainly protects moderate-sized scans from an
 unexpected regression.
 Persistence: `cached_rf_image` (the extracted fast-path check) requires
 `sras.precomputed_row_avg_n == row_avg_n` exactly, so a raw request can
 never be silently served a row-averaged cache or vice versa, and a request
 at one window size can never be served a cache at another — see
 `scan_format.md`'s Cache Tail / CACH tail version history sections for the
 on-disk `row_avg_n` field this depends on.
 ## Serving a stored cache: provenance, not just presence
 A stored `peak_freq_mhz` image is only interchangeable with a live compute
 for the *exact* settings it was computed under. Three of them are baked
 irreversibly into the numbers — background subtraction, row-averaging window,
 and zero-padding — so all three are recorded in the `SFFT` block and checked
 by `cached_rf_image` before it hands the image back. Getting this wrong is
 not a slow display, it is a *wrong* display, which is why the check is a
 single predicate in one place rather than spread across callers.
 The min peak frequency floor is the fourth recorded setting, and it sits
 between the DC threshold (fully re-applicable at display time) and the
 baked-in three: it is *tighten-only* re-applicable. A floor at or above the
 stored one is served by masking stored pixels below it to the 0.0 "no valid
 peak" sentinel — invalidated, not re-resolved; only a real recompute can
 find their true above-floor peak. A floor *below* the stored one is a
 genuine mismatch: the stored search never looked at those bins. Because a
 served-then-masked image is a lossy stand-in for a real floored compute,
 `cache_file` passes `use_stored=False` so a batch recompute always runs the
 real FFT — otherwise re-batching a cached file would silently bake the
 masked copy of its own old image back into the store.
 Padding is the subtlest of the three, because a padded FFT looks like it
 should be a refinement of the unpadded one. It isn't: zero-padding
 interpolates between the natural bins, so it resolves a different peak
 frequency for the same waveform. `precomputed_pad_factor` exists so a padded
 view can be served from a cache computed at *its* pad while still refusing
 one computed at any other, including pad 1. Before it existed the store was
 pad 1 by definition and any `n_fft` was rejected outright — correct, but it
 meant a user working at a pad factor got nothing at all from batch-computing
 a file, which is most of the point of the feature. `pad_factor_for` maps an
 `n_fft` request onto the integer factor a store could have recorded, and
 returns 0 for a request that is not a whole multiple of `samples_per_frame`
 — unmatchable by construction, since only integer factors are representable.
 The batch actions therefore have to cache at the *viewer's* current pad
 factor, not a fixed one: a cache stored at a pad nobody is viewing at is
 dead weight. When the two do diverge (the user changes the pad after
 batching), `_cache_mismatch_notes` says so in the scan info panel, because
 the symptom otherwise is just "the file I pre-computed got slow again" with
 no visible cause.
 That divergence note is informational only, not a warning of an impending
 recompute. The *display* path (`_stored_fft_image`) never asks
 `cached_rf_image` whether a stored image matches the window's live
 bg-sub/pad/row-averaging controls — it asks whether the image matches its
 *own* recorded settings (`sras.precomputed_bg_sub`/`precomputed_pad_factor`/
 `precomputed_row_avg_n`), which is always true whenever a stored image
 exists. Two settings are taken live instead: the DC threshold and the min
 peak frequency floor, both cheaply re-appliable as masks on serve. So for
 bg-sub/pad/row-avg, presence alone decides whether a stored image is shown;
 the floor is the one case where a live control can gate it — a live floor
 *below* the stored one can't be answered by masking, so `cached_rf_image`
 declines and the caller falls through to a real compute. They still matter for two things: a genuinely never-computed
 angle's first live compute, and an explicit batch recompute — both of which
 read the live controls and produce new stored data, at which point it's the
 new data's *own* settings that get self-matched from then on. This is what
 keeps a view switch (angle, channel, or flipping bg-sub/pad) from ever
 discarding precomputed data — only an explicit batch recompute does, and it
 already reloads the file afterward so the new data displays immediately.
 Row-averaging has no live control to diverge from in the first place (it's
 only ever set inside the batch dialog), so it never appears in the
 divergence note — the "Cached images" line's own `row-averaged n=…` phrase
 already covers it.
 ### Two caches, in cost order
 `_refresh_display` consults this window's in-session `_fft_cache`/`_dc_cache`
 dicts first, then the open file's stored v5/v7 blocks, and only then
 dispatches a `ComputeWorker`. The second tier is what makes a batch-computed
 file worth having; without it every angle change queued a worker and a
 progress popup for an image already sitting on disk — precisely the cost the
 batch was run to avoid. (The stored image *was* reachable before, but only
 from inside `ComputeWorker`, i.e. after paying for the thread and the popup.)
 The file tier asks with `allow_dc_recompute=False`. If applying the DC4 mask
 would mean reading a whole CH4 channel, it declines rather than blocking the
 GUI thread, and the fall-through worker reaches the same stored image via
 `compute_rf_image` and pays for the mask off-thread. So the GUI thread never
 does I/O, and the slow path is still a fast path.
 ## Angle alignment coordinate frames (`sras_compute.py`)
 Alignment puts every angle's images onto one shared, zero-padded pixel grid
 using a rigid transform only — rotation + translation, never scale.
 Angle 0 (the reference) is the sole coordinate authority: it is the only
 angle whose stage XY (`x_start_mm` / `y_positions_mm`) is ever read, and the
 shared canvas is literally an extension of angle 0's own pixel grid, so the
 aligned view carries angle 0's real X/Y axes. Every *other* angle is placed
 purely by content — its rotation and translation come from cross-correlating
 its CH4 image against angle 0's (`register_angle_to_reference`) — and its own
 stage XY is deliberately never consulted. That is not an oversight: the
 rotation stage moves the sample relative to the scan window, so where a
 window sat in stage coordinates says nothing about where the sample is, and
 an earlier design that pivoted each angle on a signal-weighted centroid of
 its own window put every angle on a ~20 mm circle around the optical center
 instead of stacking them into one shape.
 Only two coordinate frames exist:
 * **local mm** — one angle's own physical frame: origin at the *center of its
  own pixel array*, x along +column, y along +row, scaled by that angle's own
  pitches. Carries no stage position whatsoever.
 * **ref mm** — the reference angle's local mm. A registration result
  `(rotation_deg, shift_mm)` is exactly the rigid map from an angle's local
  mm to ref mm: `q = R(rotation_deg) @ l + shift_mm`. Stage coordinates
  re-enter once, at the very end, when the canvas origin is converted to
  angle 0's stage mm (`AlignmentResult.canvas_origin_mm`).
 Rotation is done in mm, never on raw pixel indices: the x pitch
 (`SrasFile.pixel_x_mm`, 5 µm on a real scan) and the y/row pitch (50 µm)
 differ by 10×, so rotating the raw index grid would shear the image — an
 unwanted anisotropic scale. Registration runs on a resampled *isotropic* grid
 for the same reason, and every affine maps shared-grid index → mm → undo
 rotation/shift → that angle's own local mm → that angle's own raw index,
 matching the output→input convention `scipy.ndimage.affine_transform` wants.
 ### Cropping the canvas is index translation, not a second transform
 `crop_alignment_result` restricts an `AlignmentResult` to a rectangular window
 of its canvas by folding the crop into each angle's existing affine rather than
 composing a new one. From `_affine_out_to_src`, `matrix = D @ Rinv @ A_out`
 depends only on the pitches and the rotation, and `A_out @ [row0, col0]` is
 exactly the mm displacement of the new origin, so
 ```
 matrix @ [r', c'] + (offset + matrix @ [row0, col0])
    == matrix @ [r' + row0, c' + col0] + offset
 ```
 identically. `matrix` is untouched and `offset` — which already absorbs the
 origin — absorbs the crop too.
 Two things follow, and both are relied on. `apply_alignment`, `reproject_mask`
 and the aligned exporter all work on a cropped result with no special-casing:
 resampling a cropped result is *exactly* a slice of resampling the full one
 (`tests/test_align_export.py::test_crop_is_a_window_of_the_full_canvas` asserts
 bit equality). And because the crop offset is a whole number of canvas pixels,
 `canvas_for_params`' snap invariant — the reference angle lands on integer
 canvas pixels — survives the crop, which is what keeps the reference exportable
 as a verbatim block.
 ## Aligned export (`sras_align_export.py`)
 `write_aligned_sras` bakes an alignment into a new v6 file: every angle
 resampled onto the cropped shared canvas, so all of them end up with identical
 geometry and the file opens already aligned. It is the only place in the
 codebase that *resamples* waveform data — `sras_edit_scans` and `sras_average`
 copy waveform bytes verbatim — which is why it is its own top-level module
 rather than part of `sras_format` (scoped to the versioned binary spec, per the
 sidecar section's own rule) or `sras_compute` (imported by every
 multiprocessing child).
 **Nearest neighbour, never interpolation.** Each output pixel gets exactly one
 source pixel's three waveforms, verbatim. Averaging two neighbouring CH1
 packets would synthesise a waveform the instrument never measured, whose FFT
 peak is the peak of neither — meaningless for a technique whose entire output is
 that peak frequency. The cost is that some source pixels are duplicated and
 others dropped, which is the same trade `apply_alignment`'s `order=0` already
 makes for the display.
 **The rounding rule is `floor(x + 0.5)`, not `np.rint`.** `scipy.ndimage`'s
 `order=0` rounds halves away from zero while `np.rint` rounds them to even. The
 canvas is snapped to the reference's own pixel grid, so an angle whose row pitch
 differs from the reference's lands on exact half-integers across whole rows —
 this is the common case, not a corner case. Getting it wrong shifts those rows
 by one source pixel relative to what the Aligned View drew.
 **Out-of-bounds is tested on the fractional coordinate, not the rounded index.**
 `scipy`'s `mode="constant"` writes `cval` wherever the coordinate leaves the
 range of sample *centres*, `[0, n-1]` — a coordinate of −0.4 rounds to a
 perfectly valid index 0 and is still padding. Testing the rounded index instead
 puts a one-pixel rim of real data everywhere the preview shows padding.
 **...but with a tolerance (`_EDGE_TOL`).** The affine is built from a chain of
 mm-space multiplications, so an exactly-integer transform comes out a few times
 1e-13 off: the reference angle's offset is `-20 - 7e-15`, not `-20`. A bare
 `>= 0.0` therefore rejects that angle's entire first row, and `<= n-1` its last
 column — for the *reference* angle, whose whole job is to pass through as an
 exact integer crop. The tolerance is ~7 orders of magnitude above that noise and
 ~7 below the half-pixel scale at which a rounding decision means anything, so it
 can only ever change pixels whose scipy answer was itself decided by noise.
 **Padding is the per-channel ADC code nearest 0 mV, not 0.** Zero ADC decodes to
 `(0 - yoff) * ymult + yzero`, which on real calibration is around +100 mV —
 above any sensible CH4 mask threshold, so a zero fill would paint a solid
 rectangle of "valid" pixels around the sample and corrupt every DC image and ROI
 statistic downstream.
 **Source rows are served from sliding in-RAM bands** (`_SourceReader`). A
 rotated angle maps one output row to a *diagonal* across the source array, so
 the pixels of a single output row come from hundreds of different source rows —
 ~1.4 MB each on a full-size scan. Indexing a memmap pixel-by-pixel in output
 order re-faults nearly the whole angle per output row: terabytes of paging for a
 gigabyte of data. Reading a contiguous band per output chunk, with the band
 advancing monotonically, costs roughly 2× the source size in total reads.
 **Writes go to `.part` and are `os.replace`d into position.** Not politeness: a
 truncated .sras is not detectably broken, because `_parse_v6` drops incomplete
 trailing angle blocks and opens what is left as an aborted scan. A half-written
 export left in place would silently look like a real file with fewer angles.
 **The Angle Table is carried over unchanged.** Alignment removes the *spatial*
 rotation of the sample; it does not change which acoustic propagation direction
 each angle measured, and that direction is the scientific content of a
 multi-angle scan. Zeroing the table would make the export self-consistent for
 re-registration and useless for anisotropy work. The consequence is that
 re-registering an export needs `seed_deg=0.0` to put 0° inside the coarse sweep,
 since `nominal_delta_deg` is still non-zero — which is exactly what the seed
 parameter exists for.
 ## Alignment wizard (`sras_viewer/align_wizard.py`)
 A `QWizard` rather than another dialog because the three steps are genuinely
 sequential and the last one is destructive: correlate, choose a crop, write a
 file. It replaces both former Fusion actions, so it also absorbs the old
 `ManualAlignmentDialog`'s by-eye nudge editor — otherwise a scan the search
 cannot fit would have no fallback at all.
 Shared state lives on the wizard object, not in `registerField`: the pages pass
 numpy arrays, `ManualAngleParams` and an `AlignmentResult` between them, none of
 which are scalar widget properties.
 `IndependentPages` is deliberately left **off**. With it set Qt never calls
 `cleanupPage`, and `cleanupPage` is how the ROI page discards a crop when the
 user goes back to re-correlate — a crop is indexed in canvas pixels, and a new
 rotation means a different canvas, so stale indices would silently be
 reinterpreted against the wrong grid. `geometry_generation` is the belt-and-
 braces check for the same hazard.
 The mask-stack preview shares the **final** canvas's origin and uses a pitch
 that is an integer multiple of it, unlike the old manual dialog's padded,
 unsnapped preview canvas. That is what lets the crop page convert a rectangle
 drawn in millimetres into an exact integer window of the real canvas, with no
 second coordinate frame to reconcile.
 "Fit to full overlap" uses `largest_rect_at_least`, a largest-rectangle sweep,
 not a bounding box of the fully-covered pixels. The full-overlap region of
 several rotated scans is roughly a disc, and its bounding box has corners no
 angle covers — offering that as the crop would hand the user the padding they
 were trying to avoid.
 Every background launch follows the two rules `_run_worker`'s docstring
 establishes: disable the trigger *before* the call (so a re-entrant click cannot
 start a second thread over the first), and never ignore the returned bool.
 Progress is an inline `QProgressBar` on the page rather than a `QProgressDialog`
 — a window-modal popup over a wizard both looks wrong and reintroduces the
 event-loop pumping hazard that ordering exists to avoid. `reject()` refuses to
 close while a job is in flight, since the running worker's signals are connected
 to bound methods of the pages Qt would be deleting.
 ## Manual-alignment sidecar (`sras_compute.py`)
 `<name>.sras.align.json` lives next to the scan file. The code lives in
 `sras_compute`, not `sras_format`: `sras_format` is scoped to the versioned
 binary .sras spec itself (see `scan_format.md`), while a manual alignment is
 a viewer-computed *derived* artifact, analogous in kind to `AlignmentResult`
 — so it belongs with the alignment math it serialises. json + pathlib are
 stdlib, so this adds no dependency to a module whose load-bearing constraint
 is staying free of Qt/matplotlib for cheap multiprocessing-child imports.
 ### Schema history
 The stored `rotation_deg`/`shift_mm` are meaningless without the frame they
 were measured in, so `_SIDECAR_SCHEMA_VERSION` is bumped whenever that frame
 changes. Each bump makes older files describe a different (and, for the bugs
 each bump fixed, actively wrong) transform than the same numbers would today;
 loading one unchanged would silently reproduce the very "scans show up
 everywhere" symptom the bump fixed — so older sidecars are treated as absent
 rather than migrated.
 * **1 → 2** — pivot moved from the scan-window bbox center to a
  content-derived centroid, and the rotation sign convention was corrected.
 * **2 → 3** — the content centroid was abandoned entirely: rotation is now
  about each angle's own array center, mapped onto the reference's array
  center, with `shift_mm` in the reference's local mm frame. No angle but the
  reference contributes stage coordinates any more.
@@ -0,0 +1,40 @@
 [build-system]
 requires = ["setuptools>=68"]
 build-backend = "setuptools.build_meta"
 [project]
 name = "sras-viewer"
 version = "0.1.0"
 description = "Viewer and processing tools for SRAS .sras scan files"
 requires-python = ">=3.12"
 dependencies = [
    "PyQt6==6.10.2",
    "numpy==2.4.1",
    "matplotlib==3.10.8",
    "scipy==1.18.0",
    # Angle alignment only: masked FFT phase correlation (skimage.registration).
    "scikit-image==0.26.0",
    # Mandatory rfft backend for the peak search (no SciPy fallback).
    "pyFFTW==0.15.1",
 ]
 [project.optional-dependencies]
 dev = ["pytest"]
 [project.scripts]
 sras-viewer = "sras_viewer.main_window:main"
 [tool.setuptools]
 py-modules = [
    "sras_format",
    "sras_compute",
    "sras_render",
    "sras_workers",
    "sras_align_export",
    "sras_average",
    "sras_edit_scans",
 ]
 packages = ["sras_viewer"]
 [tool.pytest.ini_options]
 testpaths = ["tests"]
@@ -173,6 +173,41 @@ sum over angles a of: n_rows[a] × 3 × n_frames[a] × samples_per_frame × byte
 > Table and check `file_size` against the running total before reshaping —
 > a fixed `(n_angles, n_rows, ...)` reshape (as in pre-v6 readers) will not
 > work since row/frame counts are no longer uniform across angles.
 >
 > A consequence worth stating explicitly: because a short file opens
 > *successfully* as a scan with fewer angles, a truncated file is not
 > detectably broken. Anything that writes a .sras must therefore stage to a
 > temporary name and rename on success — the viewer's aligned export writes
 > `<name>.part` and `os.replace`s it — or an interrupted write leaves behind
 > something that loads without complaint and silently has the wrong angle count.
 ---
 ## Files written by the viewer's Alignment Wizard
 The acquisition app is not the only producer of this format. The viewer's
 `Fusion → Alignment Wizard…` writes a **v6** file holding the aligned, cropped
 stack, with these properties:
 * Every angle shares one grid — the cropped alignment canvas — so the
  Per-Angle Geometry Table is `n_angles` identical records and the ragged Row
  Table is `n_angles` identical spans. The raggedness v6 exists for is still
  *expressible*, just unused, so any v6 reader works unchanged.
 * `x_delta` is the reference angle's own pitch, which is exactly
  `velocity_mm_s / laser_freq_hz`, so the derived X axis stays consistent with
  the header.
 * The `*_nominal` header fields describe the crop. Uniquely for these files they
  coincide with the actual per-angle geometry, since after alignment every angle
  really does scan the same box.
 * The **Angle Table is unchanged**. Alignment removes the sample's spatial
  rotation, not the acoustic propagation direction each angle measured — that
  direction is the point of a multi-angle scan, so it is preserved.
 * Output pixels with no corresponding source pixel (the canvas corners a rotated
  scan cannot reach) hold the per-channel ADC code nearest **0 mV**, not zero.
  Zero ADC decodes to roughly +100 mV on real calibration and would read as
  signal.
 * No Cache Tail is written: any cached DC/FFT is indexed by the source's grid
  and would be meaningless on the new one.
 ---
@@ -220,7 +255,7 @@ actions.
 | Offset | Size | Type | Field | Description |
 |--------|------|------|-------|-------------|
 | 0 | 4 | `char[4]` | `cach_magic` | `CACH` (ASCII). Missing/wrong magic → treat file as having no cache. |
-| 4 | 1 | `u8` | `cach_version` | Cache format version. Currently `1`. Readers must treat the file as uncached if this is not a version they understand (unlike v5's `PREC` section, which read but never validated its version byte). |
+| 4 | 1 | `u8` | `cach_version` | Cache format version. Currently `4`; readers also accept `1`–`3` (each older tail simply lacks the fields added since — see the `SFFT` block below and [CACH tail version history](#cach-tail-version-history)). Any other value → treat the file as uncached (unlike v5's `PREC` section, which read but never validated its version byte). |
 | 5 | 1 | `u8` | `block_flags` | Bit 0 = DC block (`SDCB`) follows. Bit 1 = FFT block (`SFFT`) follows, immediately after the DC block if both are present. Bits 2–7 reserved, must be zero on write. |
 ### DC block `SDCB` (present iff `block_flags & 0x01`)
@@ -249,13 +284,33 @@ value, same as v5's `PREC` section.
 ### FFT block `SFFT` (present iff `block_flags & 0x02`)
-7-byte block header, format `">4sBH"`:
+Block header layout depends on `cach_version`:
 Each `cach_version` appended one trailing field, so the header grows but
 never shifts an existing offset:
 - **`cach_version` 1**: 7 bytes, format `">4sBH"` — magic, flags, n_stored.
 - **`cach_version` 2**: 8 bytes, format `">4sBHB"` — + `row_avg_n`.
 - **`cach_version` 3**: 10 bytes, format `">4sBHBH"` — + `pad_factor`.
 - **`cach_version` 4**: 14 bytes, format `">4sBHBHI"` — + `min_freq_khz`.
  Always written by current code.
 An older tail is read with its absent fields taken as the only value such a
 tail can describe: `row_avg_n = 0` for a `cach_version` 1 tail, which
 predates row-averaged FFT caching, `pad_factor = 1` for `cach_version`
 1 or 2, which predate padded caching and are therefore natural-resolution,
 and `min_freq_khz = 0` (no floor) for `cach_version` 1–3, which predate the
 min peak frequency floor and therefore searched every bin above DC.
 Files cached before any of these changes keep working with no recompute.
 | Offset (rel) | Size | Type | Field | Description |
 |--------------|------|------|-------|-------------|
 | 0 | 4 | `char[4]` | `magic` | `SFFT` |
-| 4 | 1 | `u8` | `flags` | Bit 0 = `bg_sub_applied` — background waveform was subtracted from CH1 before the FFT when these images were computed. Bits 1–7 reserved. |
+| 4 | 1 | `u8` | `flags` | Bit 0 = `bg_sub_applied` — background waveform was subtracted from CH1 before the FFT when these images were computed. Bit 1 = `row_averaged` — `peak_freq_mhz` came from same-row, distance-weighted averaged CH1 waveforms rather than raw per-pixel ones; `row_avg_n` (below) is the neighbor half-width used. Bits 2–7 reserved. |
 | 5 | 2 | `u16` | `n_stored` | Number of angle entries that follow |
 | 7 | 1 | `u8` | `row_avg_n` | *`cach_version` ≥ 2 only.* Same-row neighbor half-width, in pixels, that `peak_freq_mhz` was averaged over before its FFT; `0` = raw (unaveraged). Meaningful only when `flags` bit 1 is set — a `cach_version` 1 tail has no such byte and is always `row_avg_n = 0`. |
 | 8 | 2 | `u16` | `pad_factor` | *`cach_version` ≥ 3 only.* Zero-padding factor the stored `peak_freq_mhz` was resolved at: `n_fft = pad_factor × samples_per_frame`, so `1` = natural resolution. Never `0`; a `cach_version` 1 or 2 tail has no such field and is always `pad_factor = 1`. |
 | 10 | 4 | `u32` | `min_freq_khz` | *`cach_version` ≥ 4 only.* Min peak frequency floor the stored peak search excluded bins below, fixed-point in units of 0.001 MHz (kHz); `0` = no floor. Fixed-point rather than `f32` so a value that round-trips through the file compares exactly against the same value re-requested by a reader (the viewer's floor control has 0.001 MHz granularity). A `cach_version` 1–3 tail has no such field and is always `min_freq_khz = 0`. |
 followed by `n_stored` entries, each:
@@ -264,9 +319,10 @@ u16                          angle_idx      — index into the angle table (0-ba
 f32[n_rows[angle_idx] × n_frames[angle_idx]]  peak_freq_mhz  — CH1 FFT peak frequency, MHz, row-major
 ```
-**`peak_freq_mhz`** is computed without any DC-threshold masking (i.e. the
+**`peak_freq_mhz`** for a raw store (`row_avg_n == 0`) is computed without
-FFT is run on every pixel unconditionally, same as v5's `PREC` convention).
+any DC-threshold masking (i.e. the FFT is run on every pixel
-Readers apply the DC4 threshold at display time:
+unconditionally, same as v5's `PREC` convention). Readers apply the DC4
 threshold at display time:
 ```
 pixel is valid  ⟺  dc4_mv[r][f]  ≥  threshold_mv
@@ -276,10 +332,40 @@ display_value   =   peak_freq_mhz[r][f]  if valid, else 0
 using the DC4 image from the DC block if that angle is also cached there,
 else computed on demand.
 For a row-averaged store (`row_avg_n > 0`), the DC4 threshold is applied
 *during* the store — a pixel below threshold is left at `0` and never
 contributes to any neighbor's average — since neighbor validity can't be
 deferred to display time the way plain masking can. The threshold value
 itself is not recorded, only that averaging happened and at what window
 size. Readers still apply their own live DC4 threshold at display time
 exactly as for a raw store, using whatever mask they currently have.
 Readers must fall back to real-time FFT computation (ignoring stored
-`peak_freq_mhz`) under the same conditions as v5's PREC fast path: time-domain
+`peak_freq_mhz`) whenever the store's recorded provenance doesn't match what
-gating is active, zero-padding (`n_fft ≠ samples_per_frame`) is requested, or
+the reader is asking for: time-domain gating is active, the reader's
-the reader's background-subtraction setting doesn't match `flags.bg_sub_applied`.
+requested `n_fft` doesn't equal `pad_factor × samples_per_frame`, the
 reader's background-subtraction setting doesn't match
 `flags.bg_sub_applied`, the reader's requested `row_avg_n` doesn't match
 the stored value exactly, or the reader's requested min peak frequency
 floor is *below* the stored `min_freq_khz`. A raw request must never be
 served a row-averaged store, or vice versa; a request at one row-averaging
 window size must never be served a store at another; and a request at one
 padding must never be served a store at another, since a padded FFT
 interpolates between the natural bins and so resolves genuinely different
 peak frequencies. An `n_fft` that is not a whole multiple of
 `samples_per_frame` can never match any store, because only an integer
 `pad_factor` is representable.
 The min peak frequency floor is the one asymmetric provenance field. A
 request at a floor *below* the stored one cannot be served: the stored
 search never looked at bins below its floor, so the stored numbers cannot
 say what a lower-floored search would have found. A request at a floor at
 or *above* the stored one **is** servable — the difference is re-applied at
 display time by masking every pixel whose stored `peak_freq_mhz` is below
 the requested floor to `0` (the same sentinel as the DC threshold mask;
 a genuine peak can never be `0`, since bin 0 is always excluded from the
 search). Such masked pixels are *invalid*, not re-resolved — only a real
 recompute can recover the strongest peak above the floor for them.
 ### In-place write ordering
@@ -294,6 +380,24 @@ interrupted write leaves harmless trailing bytes rather than a corrupt file,
 and the next successful write overwrites them via the same deterministic
 `cache_offset`.
 ### CACH tail version history
 Distinct from the outer `.sras` file `version` byte (top of this document),
 which has stayed `7` since the Cache Tail was introduced — this is the inner
 `cach_version` byte inside the `CACH` header itself.
 | cach_version | Change |
 |--------------|--------|
 | 1 | Initial Cache Tail: `SDCB` (DC) and `SFFT` (FFT, 7-byte header) blocks. |
 | 2 | `SFFT` header grows one byte, `row_avg_n` — the same-row neighbor half-width the stored `peak_freq_mhz` was averaged over before its FFT, `0` = raw. Readers still accept a `cach_version` 1 tail, treated as `row_avg_n = 0` for every angle it stores, so files cached before this change keep working without a recompute. |
 | 3 | `SFFT` header grows a `u16` `pad_factor` — the zero-padding factor the stored `peak_freq_mhz` was resolved at, `1` = natural resolution. Before this, a padded view could never use a stored cache at all (the store was pad 1 by definition and readers rejected any `n_fft ≠ samples_per_frame`), so a user working at a pad factor got no benefit from batch-computing a file. Recording the factor lets such a view be served, while still refusing a store resolved at a *different* pad. Readers accept `cach_version` 1 and 2 tails as `pad_factor = 1`. |
 | 4 | `SFFT` header grows a `u32` `min_freq_khz` — the min peak frequency floor the stored peak search excluded bins below, in 0.001 MHz units, `0` = no floor. The floor exists because a pixel that passes the DC-bias threshold but carries only weak real signal can otherwise resolve to the un-subtracted background's DC-leakage skirt — an implausibly-near-zero frequency (and so an implausibly slow velocity) for a pixel that has a genuine peak higher up. Recording the floor is what makes it enforceable against a store: without it, a stored image silently bypassed the floor entirely. Unlike the other provenance fields it is asymmetric — a *higher* requested floor is servable by masking stored pixels below it, only a *lower* one forces a recompute (see above). Readers accept `cach_version` 1–3 tails as `min_freq_khz = 0`. |
 A reader that does not know a `cach_version` must treat the file as
 uncached — not attempt a partial parse — and the file still reads as an
 ordinary v7 (byte-identical to v6) scan, so a forward-dated tail costs a
 recompute and never correctness.
 ---
 ## Acquisition Settings (fixed by sc3_aui_app.py)
@@ -0,0 +1,456 @@
 #!/usr/bin/env python3
 """Write an aligned, cropped .sras file from an AlignmentResult.
 The alignment machinery in sras_compute never modifies a scan: it produces an
 AlignmentResult, and every consumer resamples on the fly (apply_alignment for
 the display, reproject_mask for the overlay). That is right for a viewer, but it
 means the aligned stack cannot leave the process — no other tool can read it,
 and re-opening the scan re-does the registration.
 This module bakes an alignment into a new file. Each angle is resampled onto the
 shared canvas that AlignmentResult already defines, cropped to the caller's
 window, so every output angle ends up with *identical* geometry: same rows, same
 frames, same X/Y coordinates. Rotation and translation are gone, absorbed into
 where each waveform sits. The result is an ordinary v6 file that opens already
 aligned, and registering it against itself returns identity.
 Two deliberate choices, both about not inventing data:
  * The resample is a nearest-neighbour **gather** of whole waveforms, never an
    interpolation. Averaging two neighbouring pixels' CH1 packets would produce
    a waveform the instrument never measured, whose FFT peak is not the peak of
    either — meaningless for a technique whose entire output is that peak
    frequency. So each output pixel gets exactly one source pixel's three
    waveforms, verbatim, and the cost is that some source pixels are duplicated
    and others dropped. This matches apply_alignment's order=0 for the same
    reason.
  * Output pixels with no source pixel (the canvas corners a rotated scan cannot
    reach, and anything outside the crop's coverage) are filled with the ADC
    code for 0 mV, not with zero. See _fill_row.
 Depends only on numpy/sras_format/sras_compute — no Qt — so it is directly
 unit-testable and importable from a worker thread.
 """
 import os
 import struct
 from dataclasses import dataclass, field
 from pathlib import Path
 import numpy as np
 import sras_compute as compute
 from sras_compute import AlignmentResult
 from sras_format import GEO_FMT_V6, HDR_FMT_V6, SrasFile, mv_to_adc
 # GEO_FMT_V6 stores n_rows as ">H" and n_frames as ">I". A canvas that overflows
 # either is not representable, and silently truncating would write a file whose
 # geometry table disagrees with its waveform block.
 _MAX_ROWS = 0xFFFF
 _MAX_FRAMES = 0xFFFFFFFF
 # Slack, in source pixels, on the in-bounds test at the very edge of a source
 # array. Absorbs the ~1e-13 of float noise an exactly-integer affine picks up
 # from being built in mm space; see _in_bounds.
 _EDGE_TOL = 1e-6
 # Output rows per write() call. One row is n_channels * n_cols * spf bytes —
 # ~1.5 MB on a full-size scan — so a handful of rows keeps the peak buffer in
 # the low tens of MB no matter how large the scan is.
 _ROW_CHUNK = 8
@dataclass
 class ExportPlan:
    """What write_aligned_sras would produce, without producing it.
    Derived from the affine transforms alone — no waveform bytes are read — so
    the wizard can call it on every ROI edit to keep a live size estimate and
    per-angle coverage readout in front of the user *before* they commit to a
    multi-gigabyte write.
    """
    n_rows: int
    n_frames: int
    n_angles: int
    bytes_per_angle: int
    total_bytes: int
    valid_px: dict[int, int]              # output pixels with a source pixel
    warnings: list[str] = field(default_factory=list)
    def coverage_frac(self, angle_idx: int) -> float:
        px = self.n_rows * self.n_frames
        return (self.valid_px.get(angle_idx, 0) / px) if px else 0.0
    def empty_angles(self) -> list[int]:
        """Angles that would be written as pure padding — no output pixel of
        theirs has a source pixel."""
        return [a for a in range(self.n_angles) if not self.valid_px.get(a, 0)]
 def _src_coords(t, rows, n_cols: int) -> tuple[np.ndarray, np.ndarray]:
    """Fractional source (row, col) coordinates for whole output rows.
    *rows* is an array of output row indices; both results are shaped
    (len(rows), n_cols).
    """
    cols = np.arange(n_cols, dtype=np.float64)
    r = np.asarray(rows, dtype=np.float64)[:, None]
    sr = t.matrix[0, 0] * r + t.matrix[0, 1] * cols + t.offset[0]
    sc = t.matrix[1, 0] * r + t.matrix[1, 1] * cols + t.offset[1]
    return sr, sc
 def _round_idx(coord: np.ndarray) -> np.ndarray:
    """Nearest source index, rounding halves away from zero.
    floor(x + 0.5), not np.rint: scipy.ndimage's order=0 rounds halves away
    from zero while np.rint rounds them to even, and these have to be the same
    source pixels the apply_alignment(order=0) preview drew. Exact halves are
    not a corner case here — the canvas is snapped to the reference angle's own
    pixel grid (see canvas_for_params), so an unrotated angle lands on
    half-integers wherever its row pitch differs from the reference's.
    """
    return np.floor(coord + 0.5).astype(np.int64)
 def _in_bounds(sr: np.ndarray, sc: np.ndarray,
               n_rows: int, n_frames: int) -> np.ndarray:
    """Which output pixels have a source pixel, by scipy's mode="constant" rule
    plus a tolerance at the edge.
    Tested on the *fractional* coordinate against the range of sample centres,
    [0, n-1] inclusive — deliberately not on the rounded index. The two differ
    around the whole rim: a coordinate of -0.4 rounds to a perfectly valid index
    0, but scipy calls it out of bounds and writes cval there, so testing the
    rounded index would put a one-pixel rim of real data everywhere the Aligned
    View shows padding.
    _EDGE_TOL is why this is not literally scipy's test. The affine is built
    from a chain of mm-space multiplications, so an exactly-integer transform
    comes out a few times 1e-13 off (the reference angle's offset lands on
    -20 - 7e-15 rather than -20). Bare >= 0.0 then rejects that angle's entire
    first row, and <= n-1 its last column — for the *reference* angle, whose
    whole role is to pass through as an exact integer crop. The tolerance is
    seven orders of magnitude above that noise and seven below the half-pixel
    scale at which a rounding decision is ever meaningful, so it can only ever
    change pixels whose scipy answer was itself decided by rounding noise.
    """
    return ((sr >= -_EDGE_TOL) & (sr <= n_rows - 1 + _EDGE_TOL)
            & (sc >= -_EDGE_TOL) & (sc <= n_frames - 1 + _EDGE_TOL))
 # Output rows evaluated per numpy call when counting coverage. Counting row by
 # row costs one small matmul per row (hundreds of milliseconds per angle on a
 # full-size scan, on every ROI edit); counting the whole canvas at once needs
 # hundreds of MB of index arrays. Blocking gets both: ~10 numpy calls per angle
 # against ~30 MB of live index arrays.
 _COUNT_BLOCK = 128
 def _count_in_bounds(t, n_rows: int, n_cols: int,
                     src_rows: int, src_frames: int) -> int:
    """How many of the n_rows x n_cols output pixels have a source pixel."""
    total = 0
    for start in range(0, n_rows, _COUNT_BLOCK):
        rows = np.arange(start, min(start + _COUNT_BLOCK, n_rows))
        sr, sc = _src_coords(t, rows, n_cols)
        total += int(np.count_nonzero(_in_bounds(sr, sc, src_rows, src_frames)))
    return total
 def plan_export(sras: SrasFile, result: AlignmentResult) -> ExportPlan:
    """Geometry, size and per-angle coverage of the file *result* would export.
    Coverage is counted from the actual per-pixel index arrays rather than
    approximated by the footprint parallelogram's area, because the two differ
    exactly where it matters — a crop that clips one angle's scan window — and
    this number is what tells the user an angle will come out mostly empty. No
    waveform bytes are read, so it stays fast enough to call on every ROI edit.
    """
    n_rows, n_cols = result.canvas_shape
    n_angles = sras.n_angles
    warnings: list[str] = []
    valid_px: dict[int, int] = {}
    for a in range(n_angles):
        t = result.per_angle.get(a)
        if t is None:
            valid_px[a] = 0
            warnings.append(f"Angle {a} has no transform and will be all padding.")
            continue
        src_rows, src_frames = sras.image_shape(a)
        valid_px[a] = _count_in_bounds(t, n_rows, n_cols, src_rows, src_frames)
    bytes_per_angle = (n_rows * sras.n_channels * n_cols
                       * sras.samples_per_frame * sras.bytes_per_sample)
    # Built before the remaining warnings so they can be phrased with the
    # plan's own coverage_frac rather than a second copy of the same division.
    plan = ExportPlan(n_rows=n_rows, n_frames=n_cols, n_angles=n_angles,
                      bytes_per_angle=bytes_per_angle,
                      total_bytes=bytes_per_angle * n_angles,
                      valid_px=valid_px, warnings=warnings)
    if n_rows > _MAX_ROWS:
        warnings.append(
            f"Crop is {n_rows} rows; the .sras geometry table caps rows at "
            f"{_MAX_ROWS}. Narrow the ROI in Y.")
    if n_cols > _MAX_FRAMES:
        warnings.append(f"Crop is {n_cols} frames; the cap is {_MAX_FRAMES}.")
    for a in range(n_angles):
        frac = plan.coverage_frac(a)
        if frac == 0.0:
            warnings.append(
                f"Angle {a} has no data inside this crop — it will be written "
                f"as all padding.")
        elif frac < 0.10:
            warnings.append(
                f"Angle {a} covers only {frac * 100:.1f}% of the crop.")
    if sras.background is None:
        warnings.append(
            "Input has no background waveform (pre-v4 scan); a zero background "
            "is written, which makes background subtraction a no-op.")
    if sras.version != 6:
        warnings.append(f"Input is v{sras.version}; the export is written as v6.")
    if sras.scan_aborted:
        warnings.append(
            f"Input scan was aborted: only its {n_angles} complete angle(s) "
            f"are exported.")
    return plan
 def _fill_row(sras: SrasFile, n_cols: int, dtype) -> np.ndarray:
    """One output row of pure padding, shape (n_channels, n_cols, spf).
    Filled per channel with the ADC code for 0 mV, not with 0. Zero ADC decodes
    to (0 - yoff) * ymult + yzero, which for a real scope preamble is a long way
    from 0 mV — often far enough to sit above the CH4 mask threshold, which
    would paint a solid rectangle of "valid" pixels around the sample and make
    every DC image and every ROI statistic wrong. Rounding to the integer code
    lands within half an ADC step of 0 mV, which is as close as the format can
    represent.
    """
    info = np.iinfo(dtype)
    codes = [int(np.clip(round(mv_to_adc(0.0, *sras.cal(ch))), info.min, info.max))
             for ch in range(sras.n_channels)]
    row = np.empty((sras.n_channels, n_cols, sras.samples_per_frame), dtype=dtype)
    for ch, code in enumerate(codes):
        row[ch] = code
    return row
 class _SourceReader:
    """Gives the gather source rows without ever reading one twice.
    This is the difference between a usable export and an unusable one, and it
    is entirely about read amplification. A rotated angle maps one output row to
    a *diagonal* line across the source array, so the pixels of a single output
    row come from hundreds of different source rows — on a full-size scan, a
    ~1.4 MB source row each. Indexing a memmap pixel by pixel in output order
    therefore re-faults nearly the whole angle for every output row: terabytes
    of paging for a gigabyte of data.
    So rows are served from a contiguous *band* held in RAM. The band for a
    chunk of output rows is read in one sequential slice, and because output
    rows advance monotonically through the source, consecutive chunks' bands
    barely overlap: each source row is read about once, and the whole job costs
    roughly 2x the source size in reads rather than a thousand times it.
    Small angles skip the machinery — if the whole block fits the budget it is
    materialized once and every band is a view of it.
    One honest caveat: a chunk whose diagonal spans more source rows than the
    budget allows still gets the band it asked for, so the budget can be
    overshot. The overshoot is bounded by the span of _ROW_CHUNK output rows,
    and in the worst case (an extreme rotation on a huge scan) that is the whole
    angle — i.e. no worse than the in-RAM path above. Accepted deliberately:
    correctness of the gather is not negotiable, and the alternative is the
    memmap thrashing this class exists to avoid.
    """
    def __init__(self, sras: SrasFile, angle_idx: int, budget: int):
        self._src = sras.data[angle_idx]
        self._n_rows = self._src.shape[0]
        self._row_bytes = max(1, self._src[0].nbytes)
        self._whole = np.asarray(self._src) if self._src.nbytes <= budget else None
        # Leave room for the output buffer and the index arrays alongside.
        self._max_band = max(1, int(budget * 0.5) // self._row_bytes)
        self._band = None
        self._lo = self._hi = 0
    def band(self, lo: int, hi: int) -> tuple[np.ndarray, int]:
        """Rows [lo, hi) as an in-RAM array, plus the index its row 0 holds."""
        lo = max(0, min(lo, self._n_rows))
        hi = max(lo + 1, min(hi, self._n_rows))
        if self._whole is not None:
            return self._whole, 0
        if self._band is None or lo < self._lo or hi > self._hi:
            # Read a little more than asked so a chunk whose band creeps
            # forward by a few rows does not re-read the whole span.
            span = min(self._max_band, max(hi - lo, self._max_band // 2))
            self._lo = lo
            self._hi = min(self._n_rows, lo + span)
            if self._hi < hi:                     # band cannot cover the ask
                self._hi = hi
            self._band = np.asarray(self._src[self._lo:self._hi])
        return self._band, self._lo
    def close(self):
        self._whole = None
        self._band = None
 def write_aligned_sras(sras: SrasFile, result: AlignmentResult, out_path,
                       *, progress_cb=None, should_stop=None,
                       budget: int | None = None) -> Path:
    """Write *sras*, aligned per *result* and cropped to its canvas, to a new
    v6 .sras file. Returns the path written.
    *result* is used exactly as given: crop the canvas first with
    compute.crop_alignment_result, whose offset shift makes the cropped result
    resample precisely the window the user selected.
    No cache tail is written. Any DC/FFT the input had cached is indexed by the
    input's grid and is meaningless on the new one, so — like sras_edit_scans —
    the export drops it and lets the viewer recompute.
    Writes to a sibling ".part" file and os.replace()s it into position on
    success, unlinking it on error or cancellation: a half-written .sras is not
    detectably broken (the v6 parser treats a short file as an aborted scan and
    opens it happily), so it must never be left where the user might load it.
    *should_stop* is polled once per output row chunk; returning True aborts and
    raises nothing — the partial file is removed and the returned path will not
    exist, so callers must check.
    """
    out_path = Path(out_path)
    n_rows, n_cols = result.canvas_shape
    n_ch, spf = sras.n_channels, sras.samples_per_frame
    n_angles = sras.n_angles
    if n_rows <= 0 or n_cols <= 0:
        raise ValueError(f"empty canvas: {n_rows} x {n_cols}")
    if n_rows > _MAX_ROWS:
        raise ValueError(
            f"{n_rows} rows exceeds the .sras per-angle geometry limit of "
            f"{_MAX_ROWS}; crop further in Y")
    if n_cols > _MAX_FRAMES:
        raise ValueError(f"{n_cols} frames exceeds the limit of {_MAX_FRAMES}")
    missing = [a for a in range(n_angles) if a not in result.per_angle]
    if missing:
        raise ValueError(f"alignment result has no transform for angle(s) {missing}")
    # The source's waveform blocks are live read-only memmaps into sras.path,
    # so writing over it would corrupt the very reads the gather is making.
    if out_path.exists() and out_path.samefile(sras.path):
        raise ValueError(
            "refusing to export onto the source scan; choose another filename")
    dtype = np.dtype(np.int8 if sras.bytes_per_sample == 1 else ">i2")
    x0_mm, y0_mm = result.canvas_origin_mm
    y_rows = (y0_mm + np.arange(n_rows) * result.canvas_dy_mm).astype(">f4")
    # Reference-only header fields. v6/v7 inputs have real ones to carry over;
    # for a legacy input describe the canvas we are actually writing.
    if sras.x_start_nominal_mm is not None:
        nominal = (sras.x_start_nominal_mm, sras.y_start_nominal_mm,
                   sras.x_delta_nominal_mm, sras.y_delta_nominal_mm,
                   sras.row_spacing_mm)
    else:
        nominal = (x0_mm, y0_mm,
                   n_cols * sras.pixel_x_mm, n_rows * result.canvas_dy_mm,
                   result.canvas_dy_mm)
    header = struct.pack(
        HDR_FMT_V6, b"SRAS", 6, n_angles,
        float(nominal[0]), float(nominal[1]), float(nominal[2]),
        float(nominal[3]), float(nominal[4]),
        sras.velocity_mm_s, sras.laser_freq_hz, spf, sras.sample_rate_hz,
        sras.bytes_per_sample, n_ch)
    # Every angle now shares one grid, so the ragged v6 tables collapse to
    # n_angles copies of the same record. x_delta is the reference angle's own
    # pitch (the canvas is its grid extended), which is velocity/laser_freq
    # exactly, so x_axis_mm() stays self-consistent on re-read.
    geo = struct.pack(GEO_FMT_V6, float(x0_mm), float(sras.pixel_x_mm),
                      int(n_cols), int(n_rows)) * n_angles
    budget = compute.memory_budget_bytes() if budget is None else max(1, budget)
    total_chunks = max(1, n_angles * ((n_rows + _ROW_CHUNK - 1) // _ROW_CHUNK))
    done_chunks = 0
    cancelled = False
    part_path = out_path.with_name(out_path.name + ".part")
    try:
        with open(part_path, "wb") as fout:
            fout.write(header)
            fout.write(sras.angles_deg.astype(">f4").tobytes())
            fout.write(geo)
            fout.write(y_rows.tobytes() * n_angles)
            fout.write(sras.encoded_preambles())
            fout.write(sras.encoded_background())
            pad = _fill_row(sras, n_cols, dtype)
            for a in range(n_angles):
                t = result.per_angle[a]
                reader = _SourceReader(sras, a, budget)
                src_rows, src_frames = sras.image_shape(a)
                try:
                    for chunk_start in range(0, n_rows, _ROW_CHUNK):
                        if should_stop is not None and should_stop():
                            cancelled = True
                            break
                        chunk = np.arange(chunk_start,
                                          min(chunk_start + _ROW_CHUNK, n_rows))
                        sr, sc = _src_coords(t, chunk, n_cols)
                        ok = _in_bounds(sr, sc, src_rows, src_frames)
                        # Clip rather than trust: _EDGE_TOL admits coordinates a
                        # hair outside the array, and an index off the end here
                        # would silently read the wrong row of the band.
                        idx_r = np.clip(_round_idx(sr), 0, src_rows - 1)
                        idx_c = np.clip(_round_idx(sc), 0, src_frames - 1)
                        # One band read covers the whole chunk: every source row
                        # any of these output rows touches, in one sequential
                        # slice. See _SourceReader.
                        if ok.any():
                            band, base = reader.band(int(idx_r[ok].min()),
                                                     int(idx_r[ok].max()) + 1)
                        else:
                            band, base = None, 0
                        for i in range(len(chunk)):
                            out = pad.copy()
                            keep = ok[i]
                            if keep.any():
                                # The two advanced indices are separated by a
                                # slice, so numpy puts the gathered axis first:
                                # (n_sel, n_ch, spf). Move it behind channels.
                                out[:, keep, :] = band[
                                    idx_r[i][keep] - base, :, idx_c[i][keep], :
                                ].transpose(1, 0, 2)
                            # out is C-contiguous, so the buffer protocol
                            # writes it straight out — .tobytes() would
                            # copy a full row per row written.
                            fout.write(out)
                        done_chunks += 1
                        if progress_cb is not None:
                            progress_cb(int(done_chunks / total_chunks * 100))
                finally:
                    reader.close()
                if cancelled:
                    break
            if not cancelled:
                fout.flush()
                os.fsync(fout.fileno())
        if cancelled:
            part_path.unlink(missing_ok=True)
            return out_path
        os.replace(part_path, out_path)
    except BaseException:
        part_path.unlink(missing_ok=True)
        raise
    if progress_cb is not None:
        progress_cb(100)
    return out_path
@@ -3,7 +3,23 @@
 sras_average.py — Waveform-averaging utility for .sras files.
 Reduces memory footprint by coherently averaging every N consecutive frames
-along the acquisition axis, writing a new .sras file with n_frames / N frames.
+along the acquisition axis, writing a new v6 .sras file with (about)
 n_frames / N frames per angle.
 Handles v6/v7 only (per-angle ragged geometry). A v7 input's cache tail is
 dropped — it's indexed by frame, which this changes — so the output is always
 written as v6; the viewer recomputes DC/FFT on next open. Reads via memmap and
 writes in row-chunks sized to a memory budget (default 1024 MB, override with
 the SRAS_MEM_BUDGET_MB env var), so peak RAM stays bounded regardless of file
 size — this is what makes the tool usable on multi-hundred-GB scans.
 Averaging every N frames also coarsens the physical X spacing between output
 frames (each frame is a distinct stage position — see scan_format.md's
 Spatial Mapping section: x_k = x_start + k * velocity_mm_s / laser_freq_hz) —
 so the output header's laser_freq_hz is divided by N to keep x_axis_mm()
 correct on the averaged file. This means the GUI's "Laser freq" info label
 will show that adjusted value rather than the scope's real setting for an
 averaged file; v6/v7 has no separate field for effective pixel pitch.
 Usage:
    python sras_average.py input.sras output.sras --n 10
@@ -13,25 +29,38 @@ Options:
    --n INT              Number of frames to average into one (required).
    --discard-remainder  Drop trailing frames that don't fill a complete group.
                         Default: include a partial average for the last group.
 Environment:
    SRAS_MEM_BUDGET_MB   Ceiling on one row-chunk's working memory, in MB
                         (default 1024). Lower it on a memory-constrained
                         machine; the tool just takes more, smaller chunks.
 """
 import sys
 import struct
 import argparse
-import numpy as np
+import os
 import shutil
 import struct
 import sys
 from pathlib import Path
-# ---------------------------------------------------------------------------
+import numpy as np
 # Header format — must match sras_viewer.py exactly
 # ---------------------------------------------------------------------------
-HDR_FMT  = ">4sBHHffffIIdBB"
+from sras_format import GEO_FMT_V6, HDR_FMT_V6, SrasFile
-HDR_SIZE = struct.calcsize(HDR_FMT)   # 43 bytes
+
 _SUPPORTED = (6, 7)
 _DEFAULT_BUDGET_MB = 1024
 # Throttle per-chunk progress printing to roughly this many lines per angle,
 # so a huge angle (thousands of chunks) doesn't flood stdout while a small
 # one still gets to print every chunk.
 _MAX_PROGRESS_LINES = 40
 def parse_args():
    p = argparse.ArgumentParser(
-        description="Average every N waveforms in a .sras file and write a new file."
+        description="Average every N waveforms in a .sras file and write a new file.",
        formatter_class=argparse.RawDescriptionHelpFormatter,
        epilog=__doc__,
    )
    p.add_argument("input", help="Input .sras file")
    p.add_argument("output", help="Output .sras file")
@@ -42,143 +71,142 @@ def parse_args():
    return p.parse_args()
-def read_sras(path: Path):
+def _memory_budget_bytes() -> int:
-    """Read all sections of a .sras file and return them as a dict."""
+    return int(os.environ.get("SRAS_MEM_BUDGET_MB", _DEFAULT_BUDGET_MB)) * 1024 * 1024
    with open(path, "rb") as f:
        header_bytes = f.read(HDR_SIZE)
        fields = struct.unpack(HDR_FMT, header_bytes)
    (magic, ver, n_angles, n_rows, x_start, x_delta, vel, freq,
     n_frames_hdr, spf, sr, bps, n_ch) = fields
    if magic != b"SRAS":
        raise ValueError(f"Not a .sras file (bad magic: {magic!r})")
    if ver not in (2, 3, 4):
        raise ValueError(f"Unsupported .sras version: {ver}")
    with open(path, "rb") as f:
        f.seek(HDR_SIZE)
        angles = f.read(n_angles * 4)   # big-endian float32 array, raw bytes
        y_pos  = f.read(n_rows * 4)     # big-endian float32 array, raw bytes
        preambles = []          # list of raw bytes (length-prefixed strings)
        if ver >= 3:
            for _ in range(n_ch):
                (length,) = struct.unpack(">H", f.read(2))
                preambles.append(f.read(length))
        background = b""        # raw bytes for the v4 background block
        if ver >= 4:
            (n_bg,) = struct.unpack(">I", f.read(4))
            background = f.read(n_bg)
        raw = f.read()          # all waveform data
    # -----------------------------------------------------------------------
    # Determine actual frame count from file size (the header value can be
    # wrong — the viewer does the same correction)
    # -----------------------------------------------------------------------
    total_samples = len(raw) // bps
    samples_per_pixel = n_ch * spf         # samples in one (angle, row, frame) cell
    samples_per_full  = n_angles * n_rows * samples_per_pixel
    actual_n_frames = total_samples // (n_angles * n_rows * samples_per_pixel)
    good_bytes      = actual_n_frames * samples_per_full * bps
    # Decode waveform data
    dtype = np.int8 if bps == 1 else ">i2"
    data  = np.frombuffer(raw[:good_bytes], dtype=dtype)
    data  = data.reshape(n_angles, n_rows, n_ch, actual_n_frames, spf)
    # Work in int16 (safe intermediate for both int8 and int16 inputs)
    data  = data.astype(np.int16)
    return {
        "ver": ver, "n_angles": n_angles, "n_rows": n_rows,
        "x_start": x_start, "x_delta": x_delta, "vel": vel, "freq": freq,
        "n_frames_hdr": n_frames_hdr, "spf": spf, "sr": sr,
        "bps": bps, "n_ch": n_ch,
        "angles_raw": angles, "y_pos_raw": y_pos,
        "preambles": preambles, "background": background,
        "data": data,       # shape: (n_angles, n_rows, n_ch, n_frames, spf), int16
    }
-def average_frames(data: np.ndarray, n: int, discard_remainder: bool) -> np.ndarray:
+def _plan_angle(n_frames_in: int, n: int, discard_remainder: bool) -> tuple[int, int, int]:
-    """Average every N frames along axis 3.
+    """(n_full, remainder, n_frames_out) for averaging one angle's frames."""
    n_full = n_frames_in // n
    remainder = n_frames_in % n
    n_out = n_full + (1 if remainder and not discard_remainder else 0)
    return n_full, remainder, n_out
-    data shape: (n_angles, n_rows, n_ch, n_frames, spf)
+
-    Returns array of shape (n_angles, n_rows, n_ch, n_out, spf).
+def _chunk_rows(n_rows: int, n_channels: int, n_frames_in: int,
                samples_per_frame: int, budget: int) -> int:
    """How many rows to hold in RAM at once so one chunk's working buffers
    (source block, mean's float64 accumulator, output block) fit the budget.
    The 4 bytes/sample below is a deliberate middle estimate, not a sum of
    the three buffers: the int16 source and int16 output are 2 each, and
    only mean()'s float64 result is 8, over the reduced frame axis rather
    than the full block. Raise SRAS_MEM_BUDGET_MB if a machine still runs
    tight at a large --n."""
    bytes_per_row = max(1, n_channels * n_frames_in * samples_per_frame * 4)
    return max(1, min(n_rows, budget // bytes_per_row))
 def _average_block(block: np.ndarray, n: int, discard_remainder: bool,
                   bps: int) -> np.ndarray:
    """Average every N frames of a (rows, n_ch, n_frames, spf) block along
    the frame axis, returning the result already encoded in the on-disk
    dtype: int8 (clipped) if bps == 1, else big-endian int16.
    Cast to native int16 (not float32) before calling .mean(): numpy's mean()
    uses a float64 accumulator by default for integer input, matching the
    original implementation exactly (which kept the whole file as int16 and
    called .mean() directly). A float32 cast here would use a float32
    accumulator instead — for large group sizes that can round the sum
    differently than float64 and, after the int16 cast below, occasionally
    land on a value 1 ADC count away from the original tool's output.
    """
-    n_frames = data.shape[3]
+    n_frames = block.shape[2]
    n_full = n_frames // n
    remainder = n_frames % n
-    # Average full groups using reshape-trick (no Python loop)
+    parts = []
-    if n_full > 0:
+    if n_full:
-        full = data[:, :, :, :n_full * n, :]           # trim to full groups
+        full = block[:, :, :n_full * n, :].astype(np.int16)
-        full = full.reshape(data.shape[0], data.shape[1], data.shape[2],
+        full = full.reshape(block.shape[0], block.shape[1], n_full, n, block.shape[3])
-                            n_full, n, data.shape[4])   # (..., n_out, n, spf)
+        parts.append(full.mean(axis=3).astype(np.int16))
-        averaged = full.mean(axis=4).astype(np.int16)   # (..., n_out, spf)
+    if remainder and not discard_remainder:
        tail = block[:, :, n_full * n:, :].astype(np.int16)
        parts.append(tail.mean(axis=2, keepdims=True).astype(np.int16))
    if not parts:
        averaged = np.empty((*block.shape[:2], 0, block.shape[3]), dtype=np.int16)
    else:
-        averaged = np.empty((*data.shape[:3], 0, data.shape[4]), dtype=np.int16)
+        averaged = parts[0] if len(parts) == 1 else np.concatenate(parts, axis=2)
-    if remainder > 0 and not discard_remainder:
+    if bps == 1:
-        tail = data[:, :, :, n_full * n:, :]           # shape (..., remainder, spf)
+        return np.clip(averaged, -128, 127).astype(np.int8)
-        tail_avg = tail.mean(axis=3, keepdims=True).astype(np.int16)
+    return averaged.astype(">i2")
        averaged = np.concatenate([averaged, tail_avg], axis=3)
    return averaged
-def write_sras(path: Path, src: dict, data_out: np.ndarray):
+def write_v6_averaged(sras: SrasFile, out_path: Path, n: int,
-    """Write a new .sras file with the averaged waveform data."""
+                      discard_remainder: bool, budget: int | None = None) -> list[int]:
-    ver    = src["ver"]
+    """Write *sras* averaged every N frames to a new v6 .sras file, streaming
-    bps    = src["bps"]
+    row-chunks per angle so peak RAM never holds more than one chunk (bounded
-    n_out  = data_out.shape[3]
+    by *budget* bytes, default from SRAS_MEM_BUDGET_MB).
    Stages to a sibling '.part' file and os.replace()s it into position on
    success, per scan_format.md's requirement that any .sras writer must
    never leave a half-written file visible under its final name (a short
    v6 file opens successfully with the wrong angle/frame count rather than
    failing loudly).
    Returns the per-angle output frame counts.
    """
    budget = _memory_budget_bytes() if budget is None else max(1, budget)
    n_ch = sras.n_channels
    spf = sras.samples_per_frame
    bps = sras.bytes_per_sample
    plans = [_plan_angle(int(sras.n_frames[a]), n, discard_remainder)
             for a in range(sras.n_angles)]
    n_out_per_angle = [p[2] for p in plans]
    # Pack header — update only n_frames_hdr; everything else stays the same
    header = struct.pack(
-        HDR_FMT,
+        HDR_FMT_V6, b"SRAS", 6, sras.n_angles,
-        b"SRAS",
+        sras.x_start_nominal_mm, sras.y_start_nominal_mm,
-        ver,
+        sras.x_delta_nominal_mm, sras.y_delta_nominal_mm,
-        src["n_angles"],
+        sras.row_spacing_mm, sras.velocity_mm_s, sras.laser_freq_hz / n,
-        src["n_rows"],
+        spf, sras.sample_rate_hz, bps, n_ch,
        src["x_start"],
        src["x_delta"],
        src["vel"],
        src["freq"],
        n_out,              # updated frame count
        src["spf"],
        src["sr"],
        bps,
        src["n_ch"],
    )
-    # Encode waveform data back to original dtype
+    geo = bytearray()
-    if bps == 1:
+    for a in range(sras.n_angles):
-        raw_out = np.clip(data_out, -128, 127).astype(np.int8).tobytes()
+        geo += struct.pack(GEO_FMT_V6, float(sras.x_start_mm[a]),
-    else:
+                           float(sras.x_delta_mm_per_angle[a]),
-        # big-endian int16
+                           int(n_out_per_angle[a]), int(sras.n_rows[a]))
        raw_out = data_out.astype(">i2").tobytes()
-    with open(path, "wb") as f:
+    part_path = out_path.with_name(out_path.name + ".part")
    try:
        with open(part_path, "wb") as f:
            f.write(header)
-        f.write(src["angles_raw"])
+            f.write(sras.angles_deg.astype(">f4").tobytes())
-        f.write(src["y_pos_raw"])
+            f.write(bytes(geo))
            for a in range(sras.n_angles):
                f.write(sras.y_pos_per_angle[a].astype(">f4").tobytes())
            f.write(sras.encoded_preambles())
            f.write(sras.encoded_background())
-        if ver >= 3:
+            for a in range(sras.n_angles):
-            for preamble_bytes in src["preambles"]:
+                n_rows = int(sras.n_rows[a])
-                f.write(struct.pack(">H", len(preamble_bytes)))
+                n_frames_in = int(sras.n_frames[a])
-                f.write(preamble_bytes)
+                chunk_rows = _chunk_rows(n_rows, n_ch, n_frames_in, spf, budget)
                total_chunks = max(1, -(-n_rows // chunk_rows))
                print_every = max(1, total_chunks // _MAX_PROGRESS_LINES)
-        if ver >= 4:
+                data = sras.data[a]
-            bg = src["background"]
+                for i, r0 in enumerate(range(0, n_rows, chunk_rows)):
-            f.write(struct.pack(">I", len(bg)))
+                    r1 = min(r0 + chunk_rows, n_rows)
-            f.write(bg)
+                    block = np.asarray(data[r0:r1])
                    out_block = _average_block(block, n, discard_remainder, bps)
                    f.write(out_block.tobytes())
                    if total_chunks > 1 and (i % print_every == 0 or r1 == n_rows):
                        print(f"  angle {a + 1}/{sras.n_angles}: "
                              f"{r1}/{n_rows} rows", flush=True)
-        f.write(raw_out)
+            f.flush()
            os.fsync(f.fileno())
        os.replace(part_path, out_path)
    except BaseException:
        part_path.unlink(missing_ok=True)
        raise
    return n_out_per_angle
 def main():
@@ -194,56 +222,53 @@ def main():
    if not in_path.exists():
        print(f"Error: input file not found: {in_path}", file=sys.stderr)
        sys.exit(1)
    if out_path.resolve() == in_path.resolve():
        print("Error: output path must differ from input path.", file=sys.stderr)
        sys.exit(1)
    print(f"Reading {in_path} ...", flush=True)
-    src = read_sras(in_path)
+    sras = SrasFile(str(in_path))
    if sras.version not in _SUPPORTED:
        print(f"Error: unsupported .sras version: {sras.version} "
              f"(this tool handles v{'/v'.join(map(str, _SUPPORTED))} only)",
              file=sys.stderr)
        sys.exit(1)
-    n_frames_in = src["data"].shape[3]
+    aborted_note = " (scan aborted; trailing angle(s) already excluded)" if sras.scan_aborted else ""
-    print(f"  Version        : v{src['ver']}")
+    print(f"  Version      : v{sras.version}")
-    print(f"  Angles         : {src['n_angles']}")
+    print(f"  Angles       : {sras.n_angles}{aborted_note}")
-    print(f"  Rows           : {src['n_rows']}")
+    print(f"  Channels     : {sras.n_channels}")
-    print(f"  Frames (actual): {n_frames_in}")
+    print(f"  Samples/frame: {sras.samples_per_frame}")
-    print(f"  Channels       : {src['n_ch']}")
+    print(f"  Bytes/sample : {sras.bytes_per_sample}")
    print(f"  Samples/frame  : {src['spf']}")
    print(f"  Bytes/sample   : {src['bps']}")
    if args.n == 1:
        print("--n 1: no averaging needed; copying file as-is.")
        import shutil
        shutil.copy2(in_path, out_path)
        print(f"Wrote {out_path}")
        return
    print(f"\n{'idx':>4}  {'angle_deg':>10}  {'rows':>6}  {'frames_in':>10}  {'frames_out':>11}")
    for a in range(sras.n_angles):
        n_frames_in = int(sras.n_frames[a])
        n_full, remainder, n_out = _plan_angle(n_frames_in, args.n, args.discard_remainder)
        print(f"{a:>4}  {sras.angles_deg[a]:>10.4f}  {int(sras.n_rows[a]):>6}  "
              f"{n_frames_in:>10}  {n_out:>11}")
        if args.n > n_frames_in:
-        print(f"Warning: --n ({args.n}) exceeds available frames ({n_frames_in}). "
+            print(f"      Warning: --n ({args.n}) exceeds angle {a}'s frames "
-              "The entire dataset will be averaged into a single frame.")
+                  f"({n_frames_in}); it collapses to a single frame.")
-    print(f"\nAveraging every {args.n} frames ...", flush=True)
+    if sras.version == 7:
-    data_out = average_frames(src["data"], args.n, args.discard_remainder)
+        print("\nNote: input has a v7 cache tail; it is indexed by frame count "
-    n_frames_out = data_out.shape[3]
+              "and will be dropped. The viewer will recompute DC/FFT on next open.")
-    n_full    = n_frames_in // args.n
+    print(f"\nAveraging every {args.n} frames and writing {out_path} ...", flush=True)
-    remainder = n_frames_in  % args.n
+    n_out_per_angle = write_v6_averaged(sras, out_path, args.n, args.discard_remainder)
    if remainder and not args.discard_remainder:
        status = f"({n_full} full groups + 1 partial group of {remainder})"
    elif remainder and args.discard_remainder:
        status = f"({n_full} full groups, {remainder} trailing frames discarded)"
    else:
        status = f"({n_full} full groups)"
    print(f"  {n_frames_in} frames -> {n_frames_out} frames {status}")
    print(f"\nWriting {out_path} ...", flush=True)
    write_sras(out_path, src, data_out)
    in_mb = in_path.stat().st_size / 1024**2
    out_mb = out_path.stat().st_size / 1024**2
    print(f"\n  Frames out: {n_out_per_angle}")
    print(f"  Input size : {in_mb:.1f} MB")
-    print(f"  Output size: {out_mb:.1f} MB  ({out_mb/in_mb*100:.1f}% of input)")
+    print(f"  Output size: {out_mb:.1f} MB  ({out_mb / in_mb * 100:.1f}% of input)")
    print("Done.")
@@ -0,0 +1,224 @@
 #!/usr/bin/env python3
 """
 sras_edit_scans.py — Remove one or more angle scans from a .sras file.
 A .sras file holds one or more "angles" (rotation positions); the viewer
 cross-correlates each non-reference angle against the reference to align
 them. If one angle's acquisition went wrong (stage glitch, bad trigger,
 laser dropout, ...) it throws off that alignment for the whole file. This
 tool drops the bad angle(s) and renumbers the rest, writing a new .sras file
 with everything else — waveform samples, calibration preambles, background
 waveform, row/geometry tables — carried over byte-for-byte.
 Handles v2-v7. Any precomputed FFT/DC cache (v5 PREC tail, v7 CACH tail) is
 dropped on write, since it's indexed by angle and would be stale/misaligned
 after renumbering; the viewer just recomputes it next time the file opens.
 This tool only ever *drops* angles — every kept angle's waveform bytes and
 geometry are carried across verbatim. To write a file whose angles have been
 resampled onto one shared aligned grid and cropped, use the viewer's
 Fusion -> Alignment Wizard (sras_align_export.py) instead.
 Usage:
    python sras_edit_scans.py input.sras --list
    python sras_edit_scans.py input.sras output.sras --drop 2,5
    python sras_edit_scans.py input.sras output.sras --keep 0,1,3,4,6
 """
 import argparse
 import struct
 import sys
 from pathlib import Path
 from sras_format import GEO_FMT_V6, HDR_FMT, HDR_FMT_V6, HDR_SIZE, SrasFile
 _LEGACY_VERSIONS = (2, 3, 4, 5)
 _V6_VERSIONS = (6, 7)
 def _die(msg: str):
    print(f"Error: {msg}", file=sys.stderr)
    sys.exit(1)
 def parse_args():
    p = argparse.ArgumentParser(
        description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter)
    p.add_argument("input", help="Input .sras file")
    p.add_argument("output", nargs="?", help="Output .sras file (omit with --list)")
    p.add_argument("--list", action="store_true",
                   help="Print each angle's index/degrees/geometry and exit")
    g = p.add_mutually_exclusive_group()
    g.add_argument("--drop", metavar="I,J,...",
                   help="Comma-separated angle indices to remove")
    g.add_argument("--keep", metavar="I,J,...",
                   help="Comma-separated angle indices to keep (all others dropped)")
    return p.parse_args()
 def _parse_index_list(s: str, n_angles: int) -> set[int]:
    out = set()
    for piece in s.split(","):
        piece = piece.strip()
        if not piece:
            continue
        i = int(piece)
        if not (0 <= i < n_angles):
            raise ValueError(f"angle index {i} out of range [0, {n_angles - 1}]")
        out.add(i)
    return out
 def print_listing(sras: SrasFile):
    print(f"\n{'idx':>4}  {'angle_deg':>10}  {'x_start_mm':>11}  {'rows':>6}  {'frames':>7}")
    for a in range(sras.n_angles):
        print(f"{a:>4}  {sras.angles_deg[a]:>10.4f}  {sras.x_start_mm[a]:>11.4f}  "
              f"{int(sras.n_rows[a]):>6}  {int(sras.n_frames[a]):>7}")
 def _copy_range(fin, fout, offset: int, nbytes: int, chunk: int = 64 * 1024 * 1024):
    """Stream *nbytes* raw bytes from *fin* at *offset* into *fout*, without
    ever holding more than one chunk in memory (waveform blocks can be
    hundreds of MB to low GB each)."""
    fin.seek(offset)
    remaining = nbytes
    while remaining:
        buf = fin.read(min(chunk, remaining))
        if not buf:
            raise IOError("unexpected EOF while copying waveform data")
        fout.write(buf)
        remaining -= len(buf)
 # ---------------------------------------------------------------------------
 # Legacy (v2-v5): uniform geometry across angles, one flat waveform block
 # ---------------------------------------------------------------------------
 def _write_legacy(sras: SrasFile, keep: list[int], out_path: Path):
    n_rows = int(sras.n_rows[0])
    n_frames = int(sras.n_frames[0])       # uniform across angles for v2-v5
    n_ch = sras.n_channels
    spf = sras.samples_per_frame
    bps = sras.bytes_per_sample
    header = struct.pack(
        HDR_FMT, b"SRAS", sras.version, len(keep), n_rows,
        float(sras.x_start_mm[0]), float(sras.x_delta_mm),
        sras.velocity_mm_s, sras.laser_freq_hz,
        n_frames, spf, sras.sample_rate_hz, bps, n_ch,
    )
    # Row table + preambles + background sit right after the angle table and
    # don't vary per angle — copy that whole span through unmodified.
    angle_table_size = sras.n_angles * 4
    with open(sras.path, "rb") as f:
        f.seek(HDR_SIZE + angle_table_size)
        shared_mid = f.read(sras.data_offset - (HDR_SIZE + angle_table_size))
    angle_bytes = n_rows * n_ch * n_frames * spf * bps
    with open(sras.path, "rb") as fin, open(out_path, "wb") as fout:
        fout.write(header)
        fout.write(sras.angles_deg[keep].astype(">f4").tobytes())
        fout.write(shared_mid)
        for a in keep:
            _copy_range(fin, fout, sras.data_offset + a * angle_bytes, angle_bytes)
 # ---------------------------------------------------------------------------
 # v6/v7: per-angle geometry, ragged waveform blocks
 # ---------------------------------------------------------------------------
 def _write_v6(sras: SrasFile, keep: list[int], out_path: Path):
    header = struct.pack(
        HDR_FMT_V6, b"SRAS", sras.version, len(keep),
        sras.x_start_nominal_mm, sras.y_start_nominal_mm,
        sras.x_delta_nominal_mm, sras.y_delta_nominal_mm,
        sras.row_spacing_mm, sras.velocity_mm_s, sras.laser_freq_hz,
        sras.samples_per_frame, sras.sample_rate_hz,
        sras.bytes_per_sample, sras.n_channels,
    )
    blocks = {a: (offset, nbytes) for a, offset, nbytes in sras.iter_angle_blocks()}
    with open(sras.path, "rb") as fin, open(out_path, "wb") as fout:
        fout.write(header)
        fout.write(sras.angles_deg[keep].astype(">f4").tobytes())
        for i in keep:
            fout.write(struct.pack(
                GEO_FMT_V6, float(sras.x_start_mm[i]),
                float(sras.x_delta_mm_per_angle[i]),
                int(sras.n_frames[i]), int(sras.n_rows[i])))
        for i in keep:
            fout.write(sras.y_pos_per_angle[i].astype(">f4").tobytes())
        fout.write(sras.preambles_raw)
        fout.write(sras.background_raw)
        for i in keep:
            offset, nbytes = blocks[i]
            _copy_range(fin, fout, offset, nbytes)
 def main():
    args = parse_args()
    in_path = Path(args.input)
    if not in_path.exists():
        _die(f"input file not found: {in_path}")
    print(f"Reading {in_path} ...", flush=True)
    try:
        sras = SrasFile(str(in_path))
    except ValueError as e:
        _die(str(e))
    if sras.version not in (*_LEGACY_VERSIONS, *_V6_VERSIONS):
        _die(f"unsupported .sras version: {sras.version}")
    aborted_note = " (scan aborted; trailing angle(s) already excluded)" if sras.scan_aborted else ""
    print(f"  Version : v{sras.version}", flush=True)
    print(f"  Angles  : {sras.n_angles}{aborted_note}", flush=True)
    if args.list:
        print_listing(sras)
        return
    if not args.output:
        _die("output path required unless --list is given.")
    if not (args.drop or args.keep):
        _die("specify --drop or --keep (see --list for indices).")
    out_path = Path(args.output)
    if out_path.resolve() == in_path.resolve():
        _die("output path must differ from input path.")
    try:
        if args.drop:
            drop = _parse_index_list(args.drop, sras.n_angles)
            keep = [a for a in range(sras.n_angles) if a not in drop]
        else:
            keep = sorted(_parse_index_list(args.keep, sras.n_angles))
    except ValueError as e:
        _die(str(e))
    if not keep:
        _die("at least one angle must remain.")
    dropped = [a for a in range(sras.n_angles) if a not in keep]
    print(f"\nDropping angle(s): {dropped}")
    print(f"Keeping angle(s) : {keep}  ({len(keep)} of {sras.n_angles})")
    print(f"\nWriting {out_path} ...", flush=True)
    if sras.version in _LEGACY_VERSIONS:
        _write_legacy(sras, keep, out_path)
    else:
        _write_v6(sras, keep, out_path)
    in_mb = in_path.stat().st_size / 1024**2
    out_mb = out_path.stat().st_size / 1024**2
    print(f"  Input size : {in_mb:.1f} MB")
    print(f"  Output size: {out_mb:.1f} MB")
    print("Done.")
    print("Note: any precomputed FFT/DC cache was dropped (it's indexed by "
          "angle); the viewer will recompute it next time this file opens.")
 if __name__ == "__main__":
    main()
@@ -0,0 +1,866 @@
 #!/usr/bin/env python3
 """SRAS binary scan file format — parsing and writing.
 Reads v2–v7 .sras files. Depends only on numpy + struct, so compute workers
 (including multiprocessing children) can import it without pulling in Qt or
 matplotlib. See scan_format.md for the full v6/v7 spec.
 Channel semantics (fixed by sc3_aui_app.py acquisition settings):
  CH1 — RF Acoustic Packet (AC-coupled, 100 mV/div): FFT → peak frequency
  CH3 — Bias A (DC-coupled, 50 mV/div): waveform mean
  CH4 — Bias B (DC-coupled, 50 mV/div): waveform mean
 Frame-count correction: the scanner writes the *configured* frame count in the
 header before acquisition, but the scope may acquire fewer frames.  The actual
 count is computed from the file size and used for the reshape so channels are
 correctly aligned.
 Scan geometry: v6/v7 files scan a different bounding box per angle (x_start,
 x_delta, n_frames, n_rows all vary by angle), so geometry is exposed per-angle
 via SrasFile.n_rows / n_frames / x_start_mm arrays and the x_axis_mm() /
 y_positions_mm() methods. v2–v5 files have uniform geometry across angles, so
 those arrays simply repeat the same value n_angles times.
 v7 files are v6 files with an optional trailing cache section holding
 precomputed per-angle DC and/or FFT images, so display never has to recompute
 them after the "Convert" menu's batch actions have stored them once.
 """
 import os
 import re
 import struct
 from pathlib import Path
 import numpy as np
 # ---------------------------------------------------------------------------
 # Format constants
 # ---------------------------------------------------------------------------
 # v2–v5: fixed header, uniform geometry across angles (43 bytes)
 HDR_FMT = ">4sBHHffffIIdBB"
 HDR_SIZE = struct.calcsize(HDR_FMT)
 # v6/v7: fixed header, per-angle geometry in a separate table (49 bytes)
 HDR_FMT_V6 = ">4sBHfffffffIdBB"
 HDR_SIZE_V6 = struct.calcsize(HDR_FMT_V6)
 # v6/v7: per-angle geometry record (x_start, x_delta, n_frames, n_rows)
 GEO_FMT_V6 = ">ffIH"
 GEO_SIZE_V6 = struct.calcsize(GEO_FMT_V6)
 # v5 precomputed-image tail
 PREC_MAGIC = b"PREC"
 PREC_FLAG_BG_SUB = 0x01
 # v7 cache tail. v7 is byte-identical to v6 (the version byte is the only
 # header difference) plus this optional trailing section. Sub-block sizes are
 # per-angle (n_rows[a] * n_frames[a]), taken from the Per-Angle Geometry Table
 # already parsed for v6 — no new geometry fields are needed.
 CACH_MAGIC = b"CACH"
 CACH_HDR_FMT = ">4sBB"                        # magic, cach_version, block_flags
 CACH_HDR_SIZE = struct.calcsize(CACH_HDR_FMT)
 CACH_VERSION = 4                              # written on every fresh write
 CACH_VERSIONS_READABLE = (1, 2, 3, 4)         # accepted on read — see
                                               # _read_sfft_block. Each bump only
                                               # appended a field, and every older
                                               # tail has a well-defined reading:
                                               # v1 predates row-averaged FFT
                                               # caching (row_avg_n=0), v1/v2
                                               # predate padded caching, so both
                                               # are natural-resolution (pad 1),
                                               # and v1-v3 predate the min peak
                                               # frequency floor (min_freq 0 =
                                               # no floor).
 CACH_FLAG_DC = 0x01
 CACH_FLAG_FFT = 0x02
 SDCB_MAGIC = b"SDCB"
 SDCB_HDR_FMT = ">4sBH"                        # magic, reserved, n_stored
 SDCB_HDR_SIZE = struct.calcsize(SDCB_HDR_FMT)
 SFFT_MAGIC = b"SFFT"
 SFFT_HDR_FMT_V1 = ">4sBH"                     # magic, flags, n_stored (cach_version 1)
 SFFT_HDR_FMT_V2 = ">4sBHB"                    # + row_avg_n              (cach_version 2)
 SFFT_HDR_FMT_V3 = ">4sBHBH"                   # + pad_factor             (cach_version 3)
 SFFT_HDR_FMT = ">4sBHBHI"                     # + min_freq_khz           (cach_version 4)
 SFFT_HDR_SIZE_V1 = struct.calcsize(SFFT_HDR_FMT_V1)
 SFFT_HDR_SIZE_V2 = struct.calcsize(SFFT_HDR_FMT_V2)
 SFFT_HDR_SIZE_V3 = struct.calcsize(SFFT_HDR_FMT_V3)
 SFFT_HDR_SIZE = struct.calcsize(SFFT_HDR_FMT)
 MAX_PAD_FACTOR = 0xFFFF                       # the H field above
 # min_freq_khz is fixed-point (u32, units of 0.001 MHz), not a float32:
 # the viewer's floor spinbox has 0.001 MHz granularity, and
 # round(mhz * 1000) / 1000.0 reproduces the exact float64 the user typed,
 # so the accept rule in sras_compute.cache_mismatch_reasons can compare
 # with plain integer ordering. A ">f" float32 of e.g. 20.1 would read back
 # as 20.10000038… > 20.1 and report a spurious mismatch forever.
 MAX_MIN_FREQ_KHZ = 0xFFFFFFFF                 # the I field above; 0 = no floor
 SFFT_FLAG_BG_SUB = 0x01
 SFFT_FLAG_ROW_AVG = 0x02                      # peak_freq_mhz came from same-row,
                                               # distance-weighted averaged CH1
                                               # waveforms, not raw per-pixel ones;
                                               # row_avg_n is the neighbor half-width
                                               # (pixels) used. Bits 2-7 reserved.
 # Fixed channel indices into the .sras data array (CH1=RF, CH3/CH4=Bias DC)
 CH1_IDX, CH3_IDX, CH4_IDX = 0, 1, 2
 CH_NAMES = ["CH1", "CH3", "CH4", "VEL"]
 # Fallback scope calibration used only when reading v2 files without embedded
 # preambles.  v3+ files carry the WFMOutpre string so these are not used.
 #   50 mV/div, 8 div full-scale, int8 ADC, position = -2.72 div
 #   ymult  = 50 mV × 8 / 256  = 1.5625 mV/count
 #   yoff   = position × (256/8) = -2.72 × 32 = -87.04  (ADC count for 0 V)
 _FALLBACK_YMULT_MV = 1.5625   # mV per ADC count
 _FALLBACK_YOFF_ADC = -87.04   # ADC count that represents 0 V
 # ---------------------------------------------------------------------------
 # Calibration
 # ---------------------------------------------------------------------------
 def _parse_preamble(preamble: str) -> dict[str, float]:
    """Extract YMULT, YOFF, YZERO from a Tektronix WFMOutpre string.
    Returns a dict with float values for whichever keys are present.
    YMULT is left in V/count as the scope reports it.
    """
    result = {}
    for key in ("YMULT", "YOFF", "YZERO"):
        m = re.search(rf'\b{key}\s+([-+]?\d*\.?\d+(?:[Ee][+-]?\d+)?)', preamble)
        if m:
            result[key] = float(m.group(1))
    return result
 def mv_to_adc(mv: float, ymult_mv: float = _FALLBACK_YMULT_MV,
              yoff_adc: float = _FALLBACK_YOFF_ADC,
              yzero_mv: float = 0.0) -> float:
    return (mv - yzero_mv) / ymult_mv + yoff_adc
 def adc_to_mv(adc, ymult_mv: float = _FALLBACK_YMULT_MV,
              yoff_adc: float = _FALLBACK_YOFF_ADC,
              yzero_mv: float = 0.0):
    return (adc - yoff_adc) * ymult_mv + yzero_mv
 def _axes_extent(x_axis, y_axis, dx: float, dy: float) -> list[float]:
    """Matplotlib imshow extent with half-pixel margins, Y flipped so row 0
    renders at the top."""
    return [x_axis[0] - dx / 2, x_axis[-1] + dx / 2,
            y_axis[-1] + dy / 2, y_axis[0] - dy / 2]
 # ---------------------------------------------------------------------------
 # Binary read helpers
 # ---------------------------------------------------------------------------
 def _read_struct(f, fmt: str) -> tuple:
    return struct.unpack(fmt, f.read(struct.calcsize(fmt)))
 def _read_preambles(f, n_ch: int) -> list[str]:
    """n_ch length-prefixed UTF-8 WFMOutpre strings."""
    out = []
    for _ in range(n_ch):
        (length,) = _read_struct(f, ">H")
        out.append(f.read(length).decode("utf-8"))
    return out
 def _read_background(f) -> np.ndarray:
    """uint32 sample count followed by that many int8 samples."""
    (n_bg,) = _read_struct(f, ">I")
    return np.frombuffer(f.read(n_bg), dtype=np.int8).astype(np.float32)
 def _read_f32_image(f, shape: tuple[int, int]) -> np.ndarray:
    """One big-endian float32 image, converted to native float32.
    The conversion matters: np.frombuffer hands back a read-only big-endian
    view, and these arrays flow straight into the display caches and every
    downstream arithmetic op.
    """
    n_bytes = shape[0] * shape[1] * 4
    return np.frombuffer(f.read(n_bytes), dtype=">f4").reshape(shape).astype(np.float32)
 # ---------------------------------------------------------------------------
 # File parser
 # ---------------------------------------------------------------------------
 class SrasFile:
    """Parsed in-memory representation of a v2–v7 .sras file.
    Scan geometry (rows, frames, x_start) is exposed per-angle via the
    ``n_rows`` / ``n_frames`` / ``x_start_mm`` arrays and the ``x_axis_mm()``
    / ``y_positions_mm()`` methods, since v6/v7 files scan a different
    bounding box per angle. v2–v5 files have uniform geometry, so these
    arrays just repeat the same value ``n_angles`` times. Waveform data is
    likewise exposed as ``data[angle_idx]``, an array of shape
    ``(n_rows[a], n_channels, n_frames[a], samples_per_frame)``.
    Precomputed images (v5's PREC tail or v7's CACH tail) are exposed as
    ``precomputed_dc3_mv`` / ``precomputed_dc4_mv`` / ``precomputed_freq_mhz``,
    always as ragged per-angle lists (``list[np.ndarray | None]``, one entry
    per angle, ``None`` where that angle was never stored) regardless of
    source version. The scalars ``precomputed_bg_sub`` /
    ``precomputed_row_avg_n`` / ``precomputed_pad_factor`` /
    ``precomputed_min_freq_mhz`` record the settings the stored FFT images
    were computed under, so a reader can tell whether they answer the
    question it is actually asking.
    """
    def __init__(self, path: str):
        self.path = Path(path)
        self._parse()
    def _parse(self):
        with open(self.path, "rb") as f:
            magic = f.read(4)
            if magic != b"SRAS":
                raise ValueError(f"Bad magic bytes: {magic!r}")
            (version,) = struct.unpack(">B", f.read(1))
        self.version = version
        if version in (2, 3, 4, 5):
            self._parse_legacy()
        elif version in (6, 7):
            self._parse_v6()
        else:
            raise ValueError(f"Unsupported version: {version}")
    # ------------------------------------------------------------------
    # Calibration
    # ------------------------------------------------------------------
    def _set_calibration(self, preambles: list[str] | None, n_ch: int):
        """Populate the per-channel ymult/yoff/yzero lists from preamble
        strings, falling back to the hardcoded scope constants for v2 files
        that carry no preambles."""
        if preambles is None:
            self.preambles = None
            self.ch_ymult_mv = [_FALLBACK_YMULT_MV] * n_ch
            self.ch_yoff_adc = [_FALLBACK_YOFF_ADC] * n_ch
            self.ch_yzero_mv = [0.0] * n_ch
            return
        self.preambles = preambles
        self.ch_ymult_mv, self.ch_yoff_adc, self.ch_yzero_mv = [], [], []
        for p in preambles:
            cal = _parse_preamble(p)
            # The scope reports YMULT and YZERO in volts; store both as mV.
            self.ch_ymult_mv.append(cal.get("YMULT", _FALLBACK_YMULT_MV / 1000) * 1000)
            self.ch_yoff_adc.append(cal.get("YOFF", _FALLBACK_YOFF_ADC))
            self.ch_yzero_mv.append(cal.get("YZERO", 0.0) * 1000)
    def cal(self, ch_idx: int) -> tuple[float, float, float]:
        """(ymult_mv, yoff_adc, yzero_mv) for one channel — splat straight
        into adc_to_mv / mv_to_adc."""
        return (self.ch_ymult_mv[ch_idx], self.ch_yoff_adc[ch_idx],
                self.ch_yzero_mv[ch_idx])
    def _init_precomputed(self, n_angles: int):
        self.precomputed_freq_mhz: list[np.ndarray | None] = [None] * n_angles
        self.precomputed_dc4_mv: list[np.ndarray | None] = [None] * n_angles
        self.precomputed_dc3_mv: list[np.ndarray | None] = [None] * n_angles
        self.precomputed_bg_sub: bool = False
        self.precomputed_row_avg_n: int = 0
        # Zero-padding factor the stored peak_freq_mhz images were resolved
        # at: 1 = natural resolution (n_fft == samples_per_frame). A padded
        # FFT resolves peaks a padded view would, and only such a view can
        # be served from it — see sras_compute.cached_rf_image.
        self.precomputed_pad_factor: int = 1
        # Min peak frequency floor (MHz) the stored peak search excluded
        # bins below; 0.0 = no floor. Unlike bg-sub/pad/row-avg it is
        # tighten-only re-applicable: a *higher* floor can be re-imposed on
        # a stored image by masking pixels below it, but bins below the
        # stored floor were never searched, so a lower floor needs a real
        # recompute — see sras_compute.cache_mismatch_reasons.
        self.precomputed_min_freq_mhz: float = 0.0
    def encoded_preambles(self) -> bytes:
        """This file's Preamble Blocks section, as bytes a writer can emit.
        v6/v7 files kept the on-disk span verbatim, which is both cheaper and
        lossless; legacy files did not keep it, and a v2 file has no preambles
        at all, so those are re-encoded from the parsed strings (empty ones for
        v2). Empty is not a silent downgrade: _parse_preamble("") returns {} and
        _set_calibration falls back to the hardcoded scope constants, which is
        exactly the calibration a v2 file already gets, so mV values round-trip
        unchanged.
        Lives here rather than at each writer so the version fan-out sits next
        to the parser that creates it, and no writer has to probe the object
        to find out which shape it got.
        """
        raw = getattr(self, "preambles_raw", None)
        if raw is not None:
            return raw
        out = bytearray()
        for s in self.preambles or [""] * self.n_channels:
            encoded = s.encode("utf-8")
            out += struct.pack(">H", len(encoded)) + encoded
        return bytes(out)
    def encoded_background(self) -> bytes:
        """This file's Background Block, as bytes a writer can emit.
        When there is none (v2/v3), this is samples_per_frame zeros rather than
        a zero-length block. Every consumer guards on `background is not None`
        and then subtracts it from a (spf,)-shaped row, so a length-0 array
        would broadcast-fail at the first background-subtracted FFT; zeros make
        the subtraction a correct no-op instead.
        """
        raw = getattr(self, "background_raw", None)
        if raw is not None:
            return raw
        if self.background is None:
            samples = np.zeros(self.samples_per_frame, dtype=np.int8)
        else:
            samples = np.rint(self.background).astype(np.int8)
        return struct.pack(">I", samples.size) + samples.tobytes()
    def cached_dc_mv(self, angle_idx: int, ch_idx: int) -> np.ndarray | None:
        """A stored DC image (already in mV) for (angle, channel), or None."""
        store = self.precomputed_dc3_mv if ch_idx == CH3_IDX else self.precomputed_dc4_mv
        return store[angle_idx] if angle_idx < len(store) else None
    def image_shape(self, angle_idx: int) -> tuple[int, int]:
        return int(self.n_rows[angle_idx]), int(self.n_frames[angle_idx])
    # ------------------------------------------------------------------
    # v2–v5 parsing (uniform geometry, flat waveform block)
    # ------------------------------------------------------------------
    def _parse_legacy(self):
        with open(self.path, "rb") as f:
            (magic, ver, n_angles, n_rows, x_start, x_delta, vel, freq,
             n_frames_hdr, spf, sr, bps, n_ch) = _read_struct(f, HDR_FMT)
            self.n_angles = n_angles
            self.velocity_mm_s = float(vel)
            self.laser_freq_hz = float(freq)
            self.n_frames_header = n_frames_hdr   # configured count (may be wrong)
            self.samples_per_frame = spf
            self.sample_rate_hz = float(sr)
            self.bytes_per_sample = bps
            self.n_channels = n_ch
            self._init_precomputed(n_angles)
            self.scan_aborted = False
            self.n_angles_declared = n_angles
            # Pre-v6 files carry no nominal ROI. Defined as None rather than
            # left absent so the object's shape does not depend on its version
            # and writers can ask instead of probing with hasattr.
            self.x_start_nominal_mm = None
            self.y_start_nominal_mm = None
            self.x_delta_nominal_mm = None
            self.y_delta_nominal_mm = None
            self.row_spacing_mm = None
            angles = np.frombuffer(f.read(n_angles * 4), dtype=">f4").astype(np.float32)
            y_pos = np.frombuffer(f.read(n_rows * 4), dtype=">f4").astype(np.float32)
            self._set_calibration(_read_preambles(f, n_ch) if ver >= 3 else None, n_ch)
            self.background = _read_background(f) if ver >= 4 else None
            # Record where raw waveform data begins; np.memmap maps from here.
            data_offset = f.tell()
        # ---- Determine actual frame count from file size ---------------
        # For v4 and earlier the header n_frames may be the *configured*
        # count before acquisition; the actual count is derived from the
        # bytes on disk.  For v5 files a PREC tail follows the waveform
        # data, so we must not include those extra bytes in the frame count.
        file_size = self.path.stat().st_size
        samples_per_row_per_ch = n_ch * spf
        available_bytes = file_size - data_offset
        if ver == 5:
            actual_n_frames = n_frames_hdr
            remainder = 0
        else:
            total_samples = available_bytes // bps
            per_frame = n_angles * n_rows * samples_per_row_per_ch
            actual_n_frames = total_samples // per_frame
            remainder = total_samples % per_frame
        self.frame_count_mismatch = (actual_n_frames != n_frames_hdr)
        self.n_frames_remainder = remainder
        # ---- Memory-map the waveform data (zero RAM cost) --------------
        # Instead of f.read() → astype() (which peaks at 2× file size),
        # memmap lets the OS page only the bytes that are actually touched.
        data5d = np.memmap(
            str(self.path),
            dtype=np.int8 if bps == 1 else ">i2",
            mode="r",
            offset=data_offset,
            shape=(n_angles, n_rows, n_ch, actual_n_frames, spf),
        )
        # Expose as a list of per-angle views so downstream code shares one
        # indexing convention with v6: sras.data[a][row, ch, frame, sample]
        self.data = [data5d[a] for a in range(n_angles)]
        # Uniform per-angle geometry, repeated so callers don't need to
        # special-case legacy vs. v6 files.
        self.n_rows = np.full(n_angles, n_rows, dtype=np.int64)
        self.n_frames = np.full(n_angles, actual_n_frames, dtype=np.int64)
        self.x_start_mm = np.full(n_angles, float(x_start), dtype=np.float64)
        self.x_delta_mm = float(x_delta)   # reference only; kept for re-encode
        self._y_pos_per_angle = [y_pos] * n_angles
        self.angles_deg = angles
        self._data_offset = data_offset
        if ver >= 5:
            waveform_bytes = actual_n_frames * n_angles * n_rows * n_ch * spf * bps
            prec_offset = data_offset + waveform_bytes
            if file_size > prec_offset:
                self._parse_prec_section(prec_offset)
    def _parse_prec_section(self, offset: int):
        """Parse the v5 PREC tail that holds precomputed images.
        Stored per-angle as (freq, dc4, dc3), each a full-image float32
        block prefixed by its uint16 angle index.
        """
        with open(self.path, "rb") as f:
            f.seek(offset)
            header_raw = f.read(6)      # magic(4) + fmt_ver(1) + flags(1)
            if len(header_raw) < 6 or header_raw[:4] != PREC_MAGIC:
                return
            self.precomputed_bg_sub = bool(header_raw[5] & PREC_FLAG_BG_SUB)
            (n_stored,) = _read_struct(f, ">H")
            for _ in range(n_stored):
                (aidx,) = _read_struct(f, ">H")
                if aidx >= self.n_angles:
                    break
                shape = self.image_shape(aidx)
                self.precomputed_freq_mhz[aidx] = _read_f32_image(f, shape)
                self.precomputed_dc4_mv[aidx] = _read_f32_image(f, shape)
                self.precomputed_dc3_mv[aidx] = _read_f32_image(f, shape)
    # ------------------------------------------------------------------
    # v6/v7 parsing (per-angle geometry, ragged waveform blocks)
    # ------------------------------------------------------------------
    def _parse_v6(self):
        with open(self.path, "rb") as f:
            (magic, ver, n_angles, x_start_nom, y_start_nom, x_delta_nom,
             y_delta_nom, row_spacing, vel, freq, spf, sr, bps,
             n_ch) = _read_struct(f, HDR_FMT_V6)
            n_angles_declared = n_angles
            self.velocity_mm_s = float(vel)
            self.laser_freq_hz = float(freq)
            self.samples_per_frame = spf
            self.sample_rate_hz = float(sr)
            self.bytes_per_sample = bps
            self.n_channels = n_ch
            # Reference-only fields: the ROI as entered before per-angle
            # bounding-box expansion. Actual per-angle geometry used for
            # rendering comes from the Per-Angle Geometry Table below.
            self.x_start_nominal_mm = float(x_start_nom)
            self.y_start_nominal_mm = float(y_start_nom)
            self.x_delta_nominal_mm = float(x_delta_nom)
            self.y_delta_nominal_mm = float(y_delta_nom)
            self.row_spacing_mm = float(row_spacing)
            self.n_frames_header = None
            self.frame_count_mismatch = False
            self.n_frames_remainder = 0
            angles = np.frombuffer(f.read(n_angles * 4), dtype=">f4").astype(np.float32)
            x_start = np.empty(n_angles, dtype=np.float64)
            x_delta = np.empty(n_angles, dtype=np.float64)
            n_frames = np.empty(n_angles, dtype=np.int64)
            n_rows = np.empty(n_angles, dtype=np.int64)
            for a in range(n_angles):
                xs, xd, nf, nr = _read_struct(f, GEO_FMT_V6)
                x_start[a], x_delta[a], n_frames[a], n_rows[a] = xs, xd, nf, nr
            y_pos_per_angle = [
                np.frombuffer(f.read(int(n_rows[a]) * 4), dtype=">f4").astype(np.float32)
                for a in range(n_angles)
            ]
            # Verbatim on-disk spans of the preamble and background sections,
            # kept so file-rewriting tools (sras_edit_scans) can carry them
            # over byte-for-byte without re-parsing.
            span_start = f.tell()
            self._set_calibration(_read_preambles(f, n_ch), n_ch)
            span_end = f.tell()
            f.seek(span_start)
            self.preambles_raw = f.read(span_end - span_start)
            span_start = span_end
            self.background = _read_background(f)
            span_end = f.tell()
            f.seek(span_start)
            self.background_raw = f.read(span_end - span_start)
            data_offset = span_end
        self._data_offset = data_offset
        # ---- Memory-map each angle's ragged waveform block -------------
        # v6 gives each angle its own row/frame count, so waveform data is
        # no longer one uniform (n_angles, n_rows, ...) block — each angle's
        # block sits at a different offset with its own shape. An aborted
        # scan truncates the file mid-angle; per the format spec we keep
        # whatever complete angles are present rather than refusing to open
        # the file.
        file_size = self.path.stat().st_size
        waveform_dtype = np.int8 if bps == 1 else ">i2"
        data = []
        offset = data_offset
        for a in range(n_angles):
            nr, nf = int(n_rows[a]), int(n_frames[a])
            nbytes = nr * n_ch * nf * spf * bps
            if offset + nbytes > file_size:
                break
            data.append(np.memmap(
                str(self.path), dtype=waveform_dtype, mode="r",
                offset=offset, shape=(nr, n_ch, nf, spf),
            ))
            offset += nbytes
        n_complete = len(data)
        if n_complete == 0:
            raise ValueError(
                "v6 file has no complete angle blocks — scan was aborted "
                "before the first angle finished.")
        self.data = data
        self.n_angles = n_complete
        self.n_angles_declared = n_angles_declared
        self.scan_aborted = n_complete < n_angles_declared
        self.angles_deg = angles[:n_complete]
        self.x_start_mm = x_start[:n_complete]
        self.x_delta_mm_per_angle = x_delta[:n_complete]
        self.n_frames = n_frames[:n_complete]
        self.n_rows = n_rows[:n_complete]
        self._y_pos_per_angle = y_pos_per_angle[:n_complete]
        self._init_precomputed(n_complete)
        if self.version == 7 and offset < file_size:
            self._parse_cach_section(offset)
    # ------------------------------------------------------------------
    # Byte-layout accessors (public: used by file-rewriting tools)
    # ------------------------------------------------------------------
    @property
    def data_offset(self) -> int:
        """File offset where the waveform data begins (headers end)."""
        return self._data_offset
    @property
    def y_pos_per_angle(self) -> list[np.ndarray]:
        """Per-angle Y row positions (mm). The list and its arrays are the
        live parsed state — tools that reproject may replace entries."""
        return self._y_pos_per_angle
    @y_pos_per_angle.setter
    def y_pos_per_angle(self, value: list[np.ndarray]):
        self._y_pos_per_angle = value
    def iter_angle_blocks(self):
        """Yields (angle_idx, byte_offset, byte_count) for each complete
        angle's waveform block. Works for every version: legacy files have
        uniform per-angle geometry, so the same walk applies."""
        offset = self._data_offset
        for a in range(self.n_angles):
            nbytes = (int(self.n_rows[a]) * self.n_channels
                      * int(self.n_frames[a]) * self.samples_per_frame
                      * self.bytes_per_sample)
            yield a, offset, nbytes
            offset += nbytes
    # ------------------------------------------------------------------
    # v7 cache tail (CACH section: precomputed DC / FFT images)
    # ------------------------------------------------------------------
    def _cache_tail_offset(self) -> int:
        """Deterministic file offset where the CACH tail starts (or would
        start), derived purely from the header + Per-Angle Geometry Table —
        independent of whether a cache tail is actually present. Used by
        both the parser and the in-place writer."""
        end = self._data_offset
        for _, offset, nbytes in self.iter_angle_blocks():
            end = offset + nbytes
        return end
    def _read_cache_block(self, f, hdr_fmt: str, magic: bytes,
                          stores: list[list]) -> int | None:
        """Read one CACH sub-block header, then its per-angle image entries
        into *stores* (one list per image the block stores per angle).
        Returns the header's flags byte, or None if the block is malformed.
        """
        raw = f.read(struct.calcsize(hdr_fmt))
        if len(raw) < struct.calcsize(hdr_fmt):
            return None
        block_magic, flags, n_stored = struct.unpack(hdr_fmt, raw)
        if block_magic != magic:
            return None
        for _ in range(n_stored):
            (angle_idx,) = _read_struct(f, ">H")
            if angle_idx >= self.n_angles:
                break
            shape = self.image_shape(angle_idx)
            for store in stores:
                store[angle_idx] = _read_f32_image(f, shape)
        return flags
    def _read_sfft_block(self, f, cach_version: int) -> tuple[int, int, int, float] | None:
        """Read the SFFT block header — its layout depends on cach_version,
        since each bump appended a trailing field (v2 row_avg_n, v3
        pad_factor, v4 min_freq_khz) — then n_stored per-angle
        peak_freq_mhz entries (unchanged across versions).
        Returns (flags, row_avg_n, pad_factor, min_freq_mhz), or None if
        the block is malformed. The absent fields of an older tail take the
        value that describes what such a tail can only have been:
        row_avg_n=0 for v1, which predates row-averaged FFT caching;
        pad_factor=1 for v1/v2, which predate padded caching and so are
        natural-resolution; and min_freq_mhz=0.0 for v1-v3, which predate
        the min peak frequency floor and so searched every bin above DC.
        """
        hdr_fmt = {1: SFFT_HDR_FMT_V1, 2: SFFT_HDR_FMT_V2,
                   3: SFFT_HDR_FMT_V3}.get(cach_version, SFFT_HDR_FMT)
        raw = f.read(struct.calcsize(hdr_fmt))
        if len(raw) < struct.calcsize(hdr_fmt):
            return None
        row_avg_n, pad_factor, min_freq_khz = 0, 1, 0
        if cach_version == 1:
            magic, flags, n_stored = struct.unpack(hdr_fmt, raw)
        elif cach_version == 2:
            magic, flags, n_stored, row_avg_n = struct.unpack(hdr_fmt, raw)
        elif cach_version == 3:
            magic, flags, n_stored, row_avg_n, pad_factor = struct.unpack(hdr_fmt, raw)
        else:
            (magic, flags, n_stored, row_avg_n, pad_factor,
             min_freq_khz) = struct.unpack(hdr_fmt, raw)
        if magic != SFFT_MAGIC:
            return None
        for _ in range(n_stored):
            (angle_idx,) = _read_struct(f, ">H")
            if angle_idx >= self.n_angles:
                break
            self.precomputed_freq_mhz[angle_idx] = _read_f32_image(
                f, self.image_shape(angle_idx))
        return flags, row_avg_n, pad_factor, min_freq_khz / 1000.0
    def _parse_cach_section(self, offset: int):
        """Parse the v7 CACH tail that holds precomputed DC/FFT images."""
        with open(self.path, "rb") as f:
            f.seek(offset)
            header_raw = f.read(CACH_HDR_SIZE)
            if len(header_raw) < CACH_HDR_SIZE:
                return
            magic, cach_version, block_flags = struct.unpack(CACH_HDR_FMT, header_raw)
            if magic != CACH_MAGIC or cach_version not in CACH_VERSIONS_READABLE:
                return
            if block_flags & CACH_FLAG_DC:
                if self._read_cache_block(
                        f, SDCB_HDR_FMT, SDCB_MAGIC,
                        [self.precomputed_dc3_mv, self.precomputed_dc4_mv]) is None:
                    return
            if block_flags & CACH_FLAG_FFT:
                result = self._read_sfft_block(f, cach_version)
                if result is None:
                    return
                flags, row_avg_n, pad_factor, min_freq_mhz = result
                self.precomputed_bg_sub = bool(flags & SFFT_FLAG_BG_SUB)
                self.precomputed_row_avg_n = row_avg_n if (flags & SFFT_FLAG_ROW_AVG) else 0
                self.precomputed_pad_factor = max(1, pad_factor)
                # No flag bit gates the floor: 0 (= no floor) is already the
                # value every pre-v4 tail reads as.
                self.precomputed_min_freq_mhz = min_freq_mhz
    def write_v7_cache(self, *,
                       new_dc3_mv: list[np.ndarray | None] | None = None,
                       new_dc4_mv: list[np.ndarray | None] | None = None,
                       new_freq_mhz: list[np.ndarray | None] | None = None,
                       new_bg_sub: bool | None = None,
                       new_row_avg_n: int | None = None,
                       new_pad_factor: int | None = None,
                       new_min_freq_mhz: float | None = None):
        """Store computed DC and/or FFT images into this file's CACH tail,
        in place, converting a v6 source to v7 (or updating an existing v7
        file). Only the block(s) passed in are recomputed; whichever block
        isn't passed is carried forward unchanged from whatever this
        ``SrasFile`` already has in memory (from parsing, or a prior write
        in this same session) — its bytes are never re-read from disk.
        *new_row_avg_n* is the same-row neighbor half-width (pixels) the
        passed *new_freq_mhz* was averaged over before its FFT, 0 for a raw
        (unaveraged) compute — carried forward like *new_bg_sub* when None.
        It describes the whole stored FFT block, not per-angle, mirroring
        how bg-sub has never been tracked per-angle either.
        *new_pad_factor* is the zero-padding factor the passed *new_freq_mhz*
        was resolved at (1 = natural resolution), carried forward the same
        way. Like row_avg_n it is provenance, not a hint: a view at a
        different pad resolves different peaks, so recording it is what lets
        a reader refuse the cache instead of showing the wrong numbers.
        *new_min_freq_mhz* is the min peak frequency floor the passed
        *new_freq_mhz*'s peak search excluded bins below (0.0 = no floor),
        carried forward the same way. It is stored fixed-point (whole kHz),
        so the value is quantized to 0.001 MHz on write and
        ``precomputed_min_freq_mhz`` is updated to the quantized value —
        what a reload would see, never a float the header can't represent.
        The waveform data itself is never touched: the cache tail always
        starts at ``_cache_tail_offset()``, a fixed offset derived from the
        header and geometry table alone.
        """
        if self.version not in (6, 7):
            raise ValueError(
                f"write_v7_cache only supports v6/v7 source files, got v{self.version}")
        final_dc3 = new_dc3_mv if new_dc3_mv is not None else self.precomputed_dc3_mv
        final_dc4 = new_dc4_mv if new_dc4_mv is not None else self.precomputed_dc4_mv
        final_freq = new_freq_mhz if new_freq_mhz is not None else self.precomputed_freq_mhz
        final_bg_sub = new_bg_sub if new_bg_sub is not None else self.precomputed_bg_sub
        final_row_avg_n = (new_row_avg_n if new_row_avg_n is not None
                           else self.precomputed_row_avg_n)
        final_pad_factor = (new_pad_factor if new_pad_factor is not None
                            else self.precomputed_pad_factor)
        final_min_freq_mhz = (new_min_freq_mhz if new_min_freq_mhz is not None
                              else self.precomputed_min_freq_mhz)
        if not (0 <= final_row_avg_n <= 255):
            raise ValueError(f"row_avg_n must fit in a byte (0-255), got {final_row_avg_n}")
        if not (1 <= final_pad_factor <= MAX_PAD_FACTOR):
            raise ValueError(
                f"pad_factor must be 1-{MAX_PAD_FACTOR}, got {final_pad_factor}")
        if not (np.isfinite(final_min_freq_mhz) and final_min_freq_mhz >= 0):
            raise ValueError(
                f"min_freq_mhz must be a finite value >= 0, got {final_min_freq_mhz}")
        final_min_freq_khz = int(round(final_min_freq_mhz * 1000))
        if final_min_freq_khz > MAX_MIN_FREQ_KHZ:
            raise ValueError(
                f"min_freq_mhz too large for the u32 kHz header field: "
                f"{final_min_freq_mhz}")
        # dc3/dc4 are always populated together by every current caller, but
        # guard the per-angle pairing explicitly rather than assume it: an
        # angle present in only one of the two arrays would otherwise crash
        # below on final_dc4[a].astype(...) (or silently store the wrong
        # dc3/dc4 pairing for that angle).
        dc_entries = [a for a in range(self.n_angles)
                     if final_dc3[a] is not None and final_dc4[a] is not None]
        fft_entries = [a for a in range(self.n_angles) if final_freq[a] is not None]
        block_flags = ((CACH_FLAG_DC if dc_entries else 0)
                       | (CACH_FLAG_FFT if fft_entries else 0))
        payload = bytearray()
        payload += struct.pack(CACH_HDR_FMT, CACH_MAGIC, CACH_VERSION, block_flags)
        if dc_entries:
            payload += struct.pack(SDCB_HDR_FMT, SDCB_MAGIC, 0, len(dc_entries))
            for a in dc_entries:
                payload += struct.pack(">H", a)
                payload += final_dc3[a].astype(">f4").tobytes()
                payload += final_dc4[a].astype(">f4").tobytes()
        if fft_entries:
            fft_flags = SFFT_FLAG_BG_SUB if final_bg_sub else 0
            fft_flags |= SFFT_FLAG_ROW_AVG if final_row_avg_n else 0
            payload += struct.pack(SFFT_HDR_FMT, SFFT_MAGIC, fft_flags,
                                   len(fft_entries), final_row_avg_n,
                                   final_pad_factor, final_min_freq_khz)
            for a in fft_entries:
                payload += struct.pack(">H", a)
                payload += final_freq[a].astype(">f4").tobytes()
        with open(self.path, "r+b") as f:
            f.seek(self._cache_tail_offset())
            f.write(payload)
            f.truncate()
            f.flush()
            os.fsync(f.fileno())
            # Version-byte flip last: when converting a v6 source (self.version
            # was 6 on entry), if the process dies before this point the file
            # is still readable as plain v6 (v6 parsing only bounds-checks
            # per-angle offset+nbytes <= file_size, it never asserts exactly
            # how many bytes follow the last angle) — so an interrupted write
            # can never corrupt the file, only leave harmless trailing bytes
            # that the next successful write overwrites via this same
            # deterministic cache offset.
            #
            # That guarantee does NOT extend to updating an already-v7 file:
            # the version byte here is already 7 before this call, so a crash
            # during the payload write above (before flush/fsync/truncate)
            # can leave a cache tail that mixes a prefix of the new payload
            # with a stale suffix of the old one, and this method has no
            # protection against that case (no atomic rename — the tail is
            # rewritten in place to avoid copying the, potentially huge,
            # waveform data that precedes it).
            f.seek(4)
            f.write(struct.pack("B", 7))
            f.flush()
            os.fsync(f.fileno())
        self.version = 7
        self.precomputed_dc3_mv = final_dc3
        self.precomputed_dc4_mv = final_dc4
        self.precomputed_freq_mhz = final_freq
        self.precomputed_bg_sub = final_bg_sub
        self.precomputed_row_avg_n = final_row_avg_n
        self.precomputed_pad_factor = final_pad_factor
        self.precomputed_min_freq_mhz = final_min_freq_khz / 1000.0
    # ------------------------------------------------------------------
    # Axes helpers
    # ------------------------------------------------------------------
    @property
    def pixel_x_mm(self) -> float:
        return self.velocity_mm_s / self.laser_freq_hz
    def x_axis_mm(self, angle_idx: int) -> np.ndarray:
        n = int(self.n_frames[angle_idx])
        return self.x_start_mm[angle_idx] + np.arange(n) * self.pixel_x_mm
    def y_positions_mm(self, angle_idx: int) -> np.ndarray:
        return self._y_pos_per_angle[angle_idx]
    def angles_share_raw_grid(self) -> bool:
        """True iff every angle's raw (x, y) pixel grid is literally the same
        array as angle 0's -- the case for a .sras file the viewer's own
        Alignment Wizard exported (see scan_format.md, "Files written by the
        viewer's Alignment Wizard"): the writer packs one Per-Angle Geometry
        record and one Row Table span and repeats those same bytes for every
        angle, so re-parsed arrays are bit-identical copies rather than
        independently re-derived numbers -- a bare np.array_equal is the
        correct test here, no tolerance needed.
        """
        if self.n_angles <= 1:
            return True
        x0 = self.x_axis_mm(0)
        y0 = self.y_positions_mm(0)
        return all(np.array_equal(self.x_axis_mm(a), x0)
                   and np.array_equal(self.y_positions_mm(a), y0)
                   for a in range(1, self.n_angles))
    def time_axis_ns(self) -> np.ndarray:
        return np.arange(self.samples_per_frame) / self.sample_rate_hz * 1e9
    def freq_axis_mhz(self, n_fft: int | None = None) -> np.ndarray:
        n = n_fft if n_fft is not None else self.samples_per_frame
        return np.fft.rfftfreq(n, d=1.0 / self.sample_rate_hz) / 1e6
@@ -0,0 +1,204 @@
 """Pure-matplotlib rendering of a displayed SRAS image: imshow + colorbar +
 axis/title labeling, shared by the interactive Qt canvas
 (sras_viewer.canvases.ImageCanvas, which supplies its own already-Qt-backed
 Figure/Axes) and the headless batch image-export worker (which builds a
 throwaway Agg Figure per file and never touches Qt) -- so an exported PNG
 can never quietly start looking different from what the GUI actually shows.
 Deliberately no PyQt6 import anywhere in this module: BatchExportImagesWorker
 (sras_workers.py) may run export_view_image inside a spawned
 ProcessPoolExecutor subprocess, exactly like sras_compute.cache_file, and
 importing anything under the sras_viewer package would run its __init__.py
 and pull in the whole Qt widget tree for no reason.
 """
 from pathlib import Path
 import matplotlib as mpl
 import numpy as np
 from matplotlib.backends.backend_agg import FigureCanvasAgg
 from matplotlib.figure import Figure
 from sras_compute import compute_rf_image, dc_image_mv
 from sras_format import CH4_IDX, CH_NAMES, SrasFile, _axes_extent
 # Figure size (inches) to fall back on when a caller has no live view to
 # match: the size ImageCanvas is constructed at, so a headless render with
 # no canvas behind it still looks like the viewer's starting layout.
 DEFAULT_FIGSIZE = (7.0, 5.0)
 # The canvas size travels from the GUI as-is, so it can be degenerate (a
 # collapsed splitter pane, a window minimized mid-batch) or, on a very wide
 # multi-monitor window, big enough that width * dpi approaches matplotlib's
 # 2**16 pixel limit. Clamp rather than fail: an export's aspect ratio is a
 # presentation detail and must never be the reason a batch loses an image.
 _MIN_FIG_IN = 1.0
 _MAX_FIG_IN = 100.0
 def sanitize_figsize(figsize) -> tuple[float, float]:
    """(width, height) in inches, clamped to something renderable.
    *figsize* is None (use DEFAULT_FIGSIZE) or any 2-sequence of numbers --
    including the float64 pair Figure.get_size_inches returns, which is how
    the GUI hands over the live canvas's current size.
    """
    try:
        w, h = float(figsize[0]), float(figsize[1])
    except (TypeError, ValueError, IndexError, KeyError):
        return DEFAULT_FIGSIZE
    if not (np.isfinite(w) and np.isfinite(h)):
        return DEFAULT_FIGSIZE
    return (min(max(w, _MIN_FIG_IN), _MAX_FIG_IN),
            min(max(h, _MIN_FIG_IN), _MAX_FIG_IN))
 def draw_view_image(ax, fig, img: np.ndarray, extent: list[float], cmap,
                    vmin: float, vmax: float, xlabel: str, ylabel: str,
                    title: str, colorbar_label: str = "", cb_ticks=None,
                    norm=None, bad_color=None):
    """imshow + colorbar + labels onto an already-created (ax, fig) pair.
    *cmap* may be a name or a Colormap instance. *norm* (which overrides
    vmin/vmax) and *cb_ticks* let a caller draw a discrete integer image
    with whole-number colorbar bands instead of a continuous shade.
    *bad_color*, if given, is the fill for NaN pixels -- a copy of *cmap* is
    made so a shared, registered instance is never mutated.
    Shared by ImageCanvas.show_image (Qt-backed ax/fig) and
    export_view_image (headless Agg ax/fig) so the two can never drift into
    showing different things for the same settings.
    """
    if bad_color is not None:
        cmap = (cmap if hasattr(cmap, "with_extremes")
               else mpl.colormaps[cmap]).with_extremes(bad=bad_color)
    kw = ({"norm": norm} if norm is not None
          else {"vmin": vmin, "vmax": vmax})
    im = ax.imshow(
        img, aspect="auto", origin="upper",
        extent=extent, cmap=cmap, interpolation="nearest", **kw,
    )
    cb = fig.colorbar(im, ax=ax, fraction=0.046, pad=0.04, ticks=cb_ticks)
    if colorbar_label:
        cb.set_label(colorbar_label)
    ax.set_xlabel(xlabel)
    ax.set_ylabel(ylabel)
    ax.set_title(title)
    return im
 def export_view_image(path: str, *, out_dir: str, angle_idx: int, ch_idx: int,
                      is_fft_mode: bool, is_velocity: bool,
                      dc_threshold_mv: float, apply_bg_sub: bool,
                      pad_factor: int, min_freq_mhz: float, grating_um: float,
                      cmap: str, auto_scale: bool, vmin: float, vmax: float,
                      highlight_masked: bool, mode_str: str,
                      colorbar_label: str, mask_color: str = "magenta",
                      max_workers: int | None = None,
                      figsize: tuple[float, float] | None = None,
                      dpi: int = 150) -> tuple[str, str]:
    """One file's contribution to Batch Export View as Images: renders
    (angle_idx, ch_idx) at the given display settings to a PNG under
    *out_dir*, via draw_view_image -- so a batch export is a folder of what
    ImageCanvas.show_image would have put on screen for these settings, not
    a raw data dump.
    Module-level and picklable, like sras_compute.cache_file, so it can run
    in a ProcessPoolExecutor -- see BatchExportImagesWorker. Unlike
    cache_file this never writes to *path*: export is a read of the file's
    own data, not a cache conversion, so any version SrasFile can open
    works, with no v6/v7 precondition.
    *figsize* is the on-screen ImageCanvas's current size in inches, so the
    PNG carries the aspect ratio the view was actually being read at. It
    matters more here than it would for a plot with fixed data aspect:
    draw_view_image uses aspect="auto", so the image stretches to whatever
    box it is given -- rendering a view the user has sized wide into a
    hard-coded 7x5 squeezes the map into a different shape than the one
    they judged it by. Passing the full size, not just the ratio, also
    keeps titles, tick labels and the colorbar in the same proportion to
    the map as on screen; *dpi* alone then sets the output resolution.
    *pad_factor* (not n_fft) travels across files deliberately: n_fft
    depends on samples_per_frame, which can differ between files in the
    same batch, so n_fft is derived per file, here, from *this* file's own
    value -- the same reason sras_compute.cache_file does the same thing.
    row_avg_n is per file for the same reason and so is not a parameter at
    all: it comes from *this* file's stored cache, mirroring
    SrasViewerWindow._stored_fft_image and _start_compute, which both ask at
    the window size the store was written at. Leaving it at compute_rf_image's
    "raw per-pixel" default would make a row-averaged cache a mismatch, so a
    file the viewer displays from its store would export as a full raw
    recompute instead -- a different (and much slower) image than the one the
    batch was triggered to reproduce.
    Returns (error, out_name). error is "" on success. out_name is the
    filename this call targeted -- set as soon as it's known, even on most
    failures -- so the caller can flag same-stem collisions across the
    batch without any cross-process bookkeeping.
    """
    out_name = ""
    try:
        sras = SrasFile(path)
        if angle_idx >= sras.n_angles:
            return (f"angle {angle_idx} out of range "
                    f"(file has {sras.n_angles} angle(s))", out_name)
        out_name = f"{Path(path).stem}_angle{angle_idx}_{CH_NAMES[ch_idx]}.png"
        if is_fft_mode:
            n_fft = (sras.samples_per_frame * pad_factor
                     if pad_factor > 1 else None)
            freq = compute_rf_image(
                sras, angle_idx, dc_threshold_mv=dc_threshold_mv,
                apply_bg_sub=apply_bg_sub, n_fft=n_fft,
                row_avg_n=sras.precomputed_row_avg_n,
                min_freq_mhz=min_freq_mhz, max_workers=max_workers)
            img = freq * grating_um if is_velocity else freq
        else:
            img = dc_image_mv(sras, angle_idx, ch_idx, max_workers=max_workers)
        display_img, bad_color = img, None
        if highlight_masked and is_fft_mode:
            # Mirrors the viewer's _redraw_image rule: DC-masked pixels and
            # value-0 pixels (the "no valid peak" sentinel — DC-masked,
            # below the min-freq floor, or empty spectrum; the grating
            # multiply above preserves zeros, so this holds for Velocity
            # too) both render in the highlight color.
            dc4 = dc_image_mv(sras, angle_idx, CH4_IDX, max_workers=max_workers)
            valid = dc4 >= dc_threshold_mv
            if valid.shape == display_img.shape:
                valid &= display_img != 0.0
                display_img = display_img.astype(np.float32, copy=True)
                display_img[~valid] = np.nan
                bad_color = mask_color
        if auto_scale:
            v0, v1 = float(np.nanmin(display_img)), float(np.nanmax(display_img))
            if not np.isfinite(v0):
                v0, v1 = 0.0, 0.0   # every pixel masked out
        else:
            v0, v1 = vmin, vmax
        x_axis = sras.x_axis_mm(angle_idx)
        y_axis = sras.y_positions_mm(angle_idx)
        dx = x_axis[1] - x_axis[0] if len(x_axis) > 1 else sras.pixel_x_mm
        dy = float(y_axis[1] - y_axis[0]) if len(y_axis) > 1 else 1.0
        extent = _axes_extent(x_axis, y_axis, dx, dy)
        title = (f"{CH_NAMES[ch_idx]}  |  {mode_str}  |  "
                f"{sras.angles_deg[angle_idx]:.1f}°")
        fig = Figure(figsize=sanitize_figsize(figsize), tight_layout=True)
        FigureCanvasAgg(fig)   # Agg-only: never registered with pyplot
        ax = fig.add_subplot(111)
        draw_view_image(ax, fig, display_img, extent, cmap, v0, v1,
                        "X (mm)", "Y (mm)", title, colorbar_label,
                        bad_color=bad_color)
        fig.savefig(str(Path(out_dir) / out_name), dpi=dpi)
        return ("", out_name)
    except Exception as exc:
        return (str(exc), out_name)
@@ -0,0 +1,29 @@
 """
 SRAS Scan File Viewer
 PyQt6 application for visualizing channel data from .sras binary scan files.
 Channel semantics (fixed by sc3_aui_app.py acquisition settings):
  CH1 — RF Acoustic Packet (AC-coupled, 100 mV/div): FFT → peak frequency
  CH3 — Bias A (DC-coupled, 50 mV/div): waveform mean
  CH4 — Bias B (DC-coupled, 50 mV/div): waveform mean
 RF images are masked: pixels where CH4_dc < dc_threshold show 0.
 File parsing lives in sras_format, image/alignment math in sras_compute, and
 background workers in sras_workers — none of which import Qt or matplotlib,
 so multiprocessing children can load them cheaply.
 """
 import faulthandler
 faulthandler.enable()   # print a native stack trace on SIGSEGV/SIGABRT/etc.
 from .align_wizard import AlignmentWizard                            # noqa: E402,F401
 from .canvases import (                                               # noqa: E402,F401
    AlignOverlayCanvas, ImageCanvas, RoiQuad, WaveformCanvas,
 )
 from .common import CH_LABELS, CMAPS, VELOCITY_MODE_IDX              # noqa: E402,F401
 from .dialogs import (                                                # noqa: E402,F401
    FftOptionsDialog, FusedRoiExportDialog, RowAverageFftOptionsDialog,
 )
 from .main_window import SrasViewerWindow, main                      # noqa: E402,F401
@@ -0,0 +1,4 @@
 from .main_window import main
 if __name__ == "__main__":
    main()
@@ -0,0 +1,647 @@
 """Matplotlib canvases and the ROI primitive."""
 import matplotlib as mpl
 import numpy as np
 from matplotlib.backends.backend_qtagg import FigureCanvasQTAgg
 from matplotlib.colors import BoundaryNorm, ListedColormap
 from matplotlib.figure import Figure
 from matplotlib.patches import Polygon
 from matplotlib.path import Path as MplPath
 from PyQt6.QtCore import Qt, pyqtSignal
 from PyQt6.QtGui import QKeyEvent
 from PyQt6.QtWidgets import QSizePolicy
 from sras_format import CH1_IDX, CH3_IDX, CH4_IDX, CH_NAMES, SrasFile, adc_to_mv
 from sras_render import draw_view_image
 def count_colormap(n_angles: int):
    """(cmap, norm, ticks) for an integer "how many angles cover this pixel"
    image, 0..n_angles.
    Discrete, not continuous: the judgement the wizard's stack view exists for
    is "is this a plateau at N, or a fan of partial overlaps", so a region
    covered by one angle too few has to read as its own band rather than a
    slightly darker shade. Count 0 is fully transparent so uncovered canvas
    cannot be mistaken for a low count.
    Shared by both wizard pages that draw this image — they use different canvas
    classes, and the same number must not change colour between them.
    """
    n = max(1, int(n_angles))
    base = mpl.colormaps["viridis"].resampled(n)
    colors = [(0.0, 0.0, 0.0, 0.0)] + [base(i) for i in range(n)]
    return (ListedColormap(colors),
            BoundaryNorm(np.arange(-0.5, n + 1), len(colors)),
            np.arange(0, n + 1))
 # ---------------------------------------------------------------------------
 # ROI (free quadrilateral in data coordinates)
 # ---------------------------------------------------------------------------
 class RoiQuad:
    """Free quadrilateral defined in data coordinates (mm).
    Stored as 4 corner points (shape (4, 2)) in CCW order: BL, BR, TR, TL.
    Each corner can be positioned independently, allowing skewed /
    non-orthogonal regions of interest.  Because it lives in scan/data
    coords it persists unchanged when the displayed channel/mode switches.
    """
    def __init__(self, pts: np.ndarray):
        """pts : array-like, shape (4, 2)."""
        self._pts = np.asarray(pts, dtype=np.float64).reshape(4, 2).copy()
    @classmethod
    def from_bbox(cls, x0: float, y0: float, x1: float, y1: float) -> "RoiQuad":
        """Create an axis-aligned rectangle from two opposite corners."""
        lx, rx = min(x0, x1), max(x0, x1)
        by, ty = min(y0, y1), max(y0, y1)
        return cls(np.array([[lx, by], [rx, by], [rx, ty], [lx, ty]]))
    def copy(self) -> "RoiQuad":
        return RoiQuad(self._pts.copy())
    def corners(self) -> np.ndarray:
        """World-coord corners, shape (4, 2), CCW: BL, BR, TR, TL."""
        return self._pts.copy()
    def centroid(self) -> np.ndarray:
        return self._pts.mean(axis=0)
    def bbox_size(self) -> np.ndarray:
        """Width and height of the axis-aligned bounding box, shape (2,)."""
        return self._pts.max(axis=0) - self._pts.min(axis=0)
    def contains(self, x: float, y: float) -> bool:
        return bool(MplPath(self._pts).contains_point((x, y)))
    def mask_for_grid(self, x_axis: np.ndarray,
                      y_axis: np.ndarray) -> np.ndarray:
        """Boolean mask (n_rows, n_frames) of pixels whose centres lie
        inside the quadrilateral.
        Only the quad's axis-aligned bounding box is tested — meshgrid and
        contains_points over the *whole* grid would be tens of millions of
        point-in-polygon tests (and hundreds of MB of float64 temporaries)
        on a large scan, on every ROI edit.
        """
        x = np.asarray(x_axis, dtype=np.float64)
        y = np.asarray(y_axis, dtype=np.float64)
        mask = np.zeros((y.size, x.size), dtype=bool)
        (x0, y0), (x1, y1) = self._pts.min(axis=0), self._pts.max(axis=0)
        cols = np.nonzero((x >= x0) & (x <= x1))[0]
        rows = np.nonzero((y >= y0) & (y <= y1))[0]
        if cols.size == 0 or rows.size == 0:
            return mask
        c0, c1 = int(cols[0]), int(cols[-1]) + 1
        r0, r1 = int(rows[0]), int(rows[-1]) + 1
        X, Y = np.meshgrid(x[c0:c1], y[r0:r1])
        inside = MplPath(self._pts).contains_points(
            np.column_stack([X.ravel(), Y.ravel()]))
        mask[r0:r1, c0:c1] = inside.reshape(X.shape)
        return mask
 # ---------------------------------------------------------------------------
 # Matplotlib canvases
 # ---------------------------------------------------------------------------
 class ImageCanvas(FigureCanvasQTAgg):
    pixel_clicked = pyqtSignal(int, int)    # row_idx, frame_idx
    roi_changed = pyqtSignal()              # ROI created / edited / cleared
    draw_mode_changed = pyqtSignal(bool)    # "draw new ROI" arm toggled
    # Interaction state values
    _IDLE = "idle"
    _DRAW_NEW = "draw_new"
    _MOVE = "move"
    _DRAG_CORNER = "drag_corner"
    # Hit tolerance (display pixels) for handles.
    _HANDLE_PX = 12
    _CLICK_THRESH_PX = 4   # releases within this of press count as a click
    def __init__(self, parent=None, *, rect_only: bool = False):
        """*rect_only* constrains the ROI to an axis-aligned rectangle.
        Used by the alignment wizard's crop page, where a free quadrilateral
        would be actively misleading: v6 geometry can only express an
        axis-aligned rectangle, so anything else the user drew would have to be
        squared off behind their back. Default off, so the main window's
        free-quad ROI is unaffected.
        """
        fig = Figure(figsize=(7, 5), tight_layout=True)
        self.ax = fig.add_subplot(111)
        super().__init__(fig)
        self.setParent(parent)
        self.setSizePolicy(QSizePolicy.Policy.Expanding, QSizePolicy.Policy.Expanding)
        self._extent = None
        self._img_shape = None
        self._rect_only = rect_only
        # ROI state
        self._roi: RoiQuad | None = None
        self._roi_artists: list = []
        self._state = self._IDLE
        self._draw_mode = False
        # Per-interaction snapshots / anchors
        self._press_xy: tuple[float, float] | None = None
        self._press_pixel: tuple[float, float] | None = None
        self._press_button = None
        self._snapshot: RoiQuad | None = None
        self._drag_corner_idx: int = -1
        self._move_anchor = None                 # press-point in world coords
        self._draw_previous: RoiQuad | None = None
        self.mpl_connect("button_press_event", self._on_press)
        self.mpl_connect("motion_notify_event", self._on_motion)
        self.mpl_connect("button_release_event", self._on_release)
    # ------------------------------------------------------------------
    # Public API
    # ------------------------------------------------------------------
    def show_image(self, img: np.ndarray, extent: list[float], cmap,
                   vmin: float, vmax: float, xlabel: str, ylabel: str, title: str,
                   colorbar_label: str = "", cb_ticks=None, norm=None,
                   bad_color=None):
        """*cmap* may be a name or a Colormap instance. *norm* (which overrides
        vmin/vmax) and *cb_ticks* let a caller draw a discrete integer image —
        the wizard's overlap-count view — with whole-number colorbar bands
        instead of a continuous shade. *bad_color*, if given, is the fill for
        NaN pixels — a copy of *cmap* is made so the shared, registered
        instance is never mutated."""
        self.figure.clf()
        self.ax = self.figure.add_subplot(111)
        # Patches and lines are destroyed by figure.clf(); drop stale refs.
        self._roi_artists = []
        self._extent = extent
        self._img_shape = img.shape
        # Shared with the headless batch image-export worker (sras_render.py)
        # so an exported PNG can never quietly drift from what this canvas
        # shows on screen for the same settings.
        draw_view_image(self.ax, self.figure, img, extent, cmap, vmin, vmax,
                        xlabel, ylabel, title, colorbar_label, cb_ticks, norm,
                        bad_color)
        # Re-draw the ROI (if any) on top of the fresh image so it persists
        # unchanged across mode / angle / channel switches.
        self._draw_roi()
        self.draw()
    def get_roi(self) -> RoiQuad | None:
        return self._roi
    def set_roi(self, roi: RoiQuad | None):
        self._roi = roi.copy() if roi is not None else None
        self._draw_roi()
        self.draw_idle()
        self.roi_changed.emit()
    def clear_roi(self):
        self._roi = None
        self._remove_roi_artists()
        self.draw_idle()
        self.roi_changed.emit()
    def start_drawing(self):
        """Arm the next click+drag on the image to create a new ROI,
        replacing any existing one."""
        self._draw_mode = True
        self.setCursor(Qt.CursorShape.CrossCursor)
        self.draw_mode_changed.emit(True)
    def cancel_drawing(self):
        if self._draw_mode:
            self._draw_mode = False
            self.setCursor(Qt.CursorShape.ArrowCursor)
            self.draw_mode_changed.emit(False)
    # ------------------------------------------------------------------
    # Rendering
    # ------------------------------------------------------------------
    def _remove_roi_artists(self):
        for a in self._roi_artists:
            try:
                a.remove()
            except (ValueError, AttributeError, NotImplementedError):
                pass
        self._roi_artists = []
    def _draw_roi(self):
        self._remove_roi_artists()
        if self._roi is None or self.ax is None:
            return
        corners = self._roi.corners()
        # Filled quad, then a sharp unfilled edge for visibility over bright
        # images, then draggable corner handles.
        for kwargs in (
            dict(fill=True, facecolor="#ffd93a", edgecolor="#e53935",
                 alpha=0.22, linewidth=2.0, zorder=10),
            dict(fill=False, edgecolor="#e53935", linewidth=1.8, zorder=11),
        ):
            patch = Polygon(corners, closed=True, **kwargs)
            self.ax.add_patch(patch)
            self._roi_artists.append(patch)
        self._roi_artists.append(self.ax.scatter(
            corners[:, 0], corners[:, 1], s=60, c="white",
            edgecolors="#e53935", linewidths=1.6, zorder=13))
    # ------------------------------------------------------------------
    # Hit testing (display pixels for handles, data coords for "inside")
    # ------------------------------------------------------------------
    def _hit_test(self, event) -> tuple[str, int | None] | None:
        if self._roi is None or self.ax is None:
            return None
        if event.x is None or event.y is None:
            return None
        corners_disp = self.ax.transData.transform(self._roi.corners())
        click = np.array([event.x, event.y])
        for i in range(4):
            if np.hypot(*(corners_disp[i] - click)) <= self._HANDLE_PX:
                return ("corner", i)
        if event.xdata is not None and event.ydata is not None:
            if self._roi.contains(event.xdata, event.ydata):
                return ("inside", None)
        return None
    # ------------------------------------------------------------------
    # Mouse event handlers
    # ------------------------------------------------------------------
    def _on_press(self, event):
        if event.inaxes is not self.ax or self._extent is None:
            return
        if event.button != 1:   # only left mouse button
            return
        # If the matplotlib toolbar is in pan / zoom mode, let it handle
        # the interaction instead of starting a ROI manipulation.
        tb = getattr(self, "toolbar", None)
        if tb is not None and getattr(tb, "mode", ""):
            return
        self._press_xy = (event.xdata, event.ydata)
        self._press_pixel = (event.x, event.y)
        self._press_button = event.button
        if self._draw_mode:
            self._draw_previous = self._roi.copy() if self._roi else None
            self._roi = RoiQuad.from_bbox(event.xdata, event.ydata,
                                          event.xdata, event.ydata)
            self._state = self._DRAW_NEW
            self._draw_roi()
            self.draw_idle()
            return
        hit = self._hit_test(event)
        if hit is None:
            self._state = self._IDLE
            return
        kind, idx = hit
        self._snapshot = self._roi.copy()
        if kind == "corner":
            self._state = self._DRAG_CORNER
            self._drag_corner_idx = idx
        else:
            self._state = self._MOVE
            self._move_anchor = (event.xdata, event.ydata)
    def _on_motion(self, event):
        if self._state == self._IDLE:
            return
        if event.xdata is None or event.ydata is None:
            return
        if event.inaxes is not self.ax:
            return
        if self._state == self._DRAW_NEW:
            x0, y0 = self._press_xy
            self._roi = RoiQuad.from_bbox(x0, y0, event.xdata, event.ydata)
        elif self._state == self._MOVE:
            delta = np.array([event.xdata - self._move_anchor[0],
                              event.ydata - self._move_anchor[1]])
            self._roi._pts = self._snapshot.corners() + delta
        elif self._state == self._DRAG_CORNER:
            self._roi._pts[self._drag_corner_idx] = [event.xdata, event.ydata]
            if self._rect_only:
                self._rectify_corner(self._drag_corner_idx)
        self._draw_roi()
        self.draw_idle()
    def _rectify_corner(self, idx: int):
        """Re-square the quad after a corner drag, anchored on the *opposite*
        corner.
        Anchoring on the diagonal opposite (idx ^ 2, since corners run
        BL, BR, TR, TL) rather than taking the bbox of all four points is what
        lets the rectangle shrink: a bbox over the three stale corners plus the
        new one is the union of the old rectangle and the new point, so dragging
        inward would never make it smaller.
        """
        pts = self._roi.corners()
        ax_, ay = pts[idx ^ 2]
        bx, by = pts[idx]
        self._roi._pts = RoiQuad.from_bbox(min(ax_, bx), min(ay, by),
                                           max(ax_, bx), max(ay, by)).corners()
    def _on_release(self, event):
        if event.button != 1 and self._press_button != 1:
            return
        prev_state = self._state
        self._state = self._IDLE
        try:
            if prev_state == self._DRAW_NEW:
                self._finish_draw()
            elif prev_state in (self._MOVE, self._DRAG_CORNER):
                self._draw_roi()
                self.draw_idle()
                self.roi_changed.emit()
            else:
                self._maybe_emit_pixel_click(event)
        finally:
            self._press_xy = self._press_pixel = None
            self._press_button = None
    def _finish_draw(self):
        """Commit (or reject) a freshly-dragged quad."""
        if self._extent is not None:
            x0, x1, y_bot, y_top = self._extent
            min_w = abs(x1 - x0) * 0.01     # minimum: 1% of each axis range
            min_h = abs(y_bot - y_top) * 0.01
        else:
            min_w = min_h = 1e-6
        if self._roi is None:
            too_small = True
        else:
            bbox = self._roi.bbox_size()
            too_small = bbox[0] < min_w or bbox[1] < min_h
        if too_small:
            self._roi = self._draw_previous
        self._draw_previous = None
        self.cancel_drawing()
        self._draw_roi()
        self.draw_idle()
        self.roi_changed.emit()
    def _maybe_emit_pixel_click(self, event):
        """A release close enough to its press counts as a pixel click."""
        if (self._press_pixel is None or event.x is None or event.y is None
                or self._extent is None or event.inaxes is not self.ax
                or event.xdata is None):
            return
        dx_px = event.x - self._press_pixel[0]
        dy_px = event.y - self._press_pixel[1]
        if dx_px * dx_px + dy_px * dy_px > self._CLICK_THRESH_PX ** 2:
            return
        x0, x1, y_bot, y_top = self._extent
        n_rows, n_frames = self._img_shape
        col = int((event.xdata - x0) / (x1 - x0) * n_frames)
        row = int((event.ydata - y_top) / (y_bot - y_top) * n_rows)
        self.pixel_clicked.emit(max(0, min(row, n_rows - 1)),
                                max(0, min(col, n_frames - 1)))
 class WaveformCanvas(FigureCanvasQTAgg):
    def __init__(self, parent=None):
        fig = Figure(figsize=(8, 3), tight_layout=True)
        self.ax_wave = fig.add_subplot(121)
        self.ax_right = fig.add_subplot(122)
        super().__init__(fig)
        self.setParent(parent)
        self.setSizePolicy(QSizePolicy.Policy.Expanding, QSizePolicy.Policy.Expanding)
    def show_rf_waveform(self, sras: SrasFile, angle_idx: int,
                         row_idx: int, frame_idx: int,
                         apply_bg_sub: bool = True,
                         min_freq_mhz: float = 0.0):
        """CH1 RF: time-domain + FFT spectrum.
        If apply_bg_sub is True and sras.background is not None, the background
        waveform is overlaid on the time-domain plot and the FFT is computed
        on the subtracted signal.  The unsubtracted FFT is also shown faintly
        for comparison.
        *min_freq_mhz* > 0 restricts the labeled peak to bins at or above
        it — the same floor the image's peak search uses, so the label
        explains the map pixel instead of contradicting it — and shades the
        excluded band on the spectrum. The spectrum curves themselves stay
        complete (they are the evidence for choosing the floor). The peak
        can still legitimately differ from a padded or row-averaged map:
        this panel is always a single waveform at natural resolution.
        """
        data = sras.data[angle_idx]
        waveform = data[row_idx, CH1_IDX, frame_idx, :].astype(np.float32)
        t_ns = sras.time_axis_ns()
        f_mhz = sras.freq_axis_mhz()
        dc3_val = data[row_idx, CH3_IDX, frame_idx, :].astype(np.float32).mean()
        dc4_val = data[row_idx, CH4_IDX, frame_idx, :].astype(np.float32).mean()
        bg = sras.background if (apply_bg_sub and sras.background is not None) else None
        waveform_plot = waveform - bg if bg is not None else waveform
        self.ax_wave.cla()
        self.ax_right.cla()
        if bg is not None:
            self.ax_wave.plot(t_ns, waveform, linewidth=0.5, color="#aaaaaa",
                              label="raw", zorder=1)
            self.ax_wave.plot(t_ns, bg, linewidth=0.5, color="#e07030",
                              linestyle="--", label="background", zorder=2)
            self.ax_wave.plot(t_ns, waveform_plot, linewidth=0.7, color="#4488cc",
                              label="subtracted", zorder=3)
            self.ax_wave.legend(fontsize=7, loc="upper right")
        else:
            self.ax_wave.plot(t_ns, waveform, linewidth=0.7, color="#4488cc")
        self.ax_wave.set_xlabel("Time (ns)")
        self.ax_wave.set_ylabel("ADC counts")
        bg_tag = "  [bg sub]" if bg is not None else ""
        dc3_mv = adc_to_mv(dc3_val, *sras.cal(CH3_IDX))
        dc4_mv = adc_to_mv(dc4_val, *sras.cal(CH4_IDX))
        self.ax_wave.set_title(
            f"CH1 RF  row={row_idx}  frame={frame_idx}{bg_tag}\n"
            f"CH3={dc3_val:.1f}  CH4={dc4_val:.1f}  "
            f"({dc3_mv:.2f} / {dc4_mv:.2f} mV)",
            fontsize=8,
        )
        # FFT of the (possibly subtracted) waveform
        power_sub = np.abs(np.fft.rfft(waveform_plot)) ** 2
        power_sub[0] = 0.0
        # First bin at or above the floor, exactly as the image peak search
        # picks it (bin 0 always excluded). If the floor excludes every bin,
        # fall back to the unrestricted peak rather than indexing past the
        # end — the label is informational, not a mask.
        lo = max(1, int(np.searchsorted(f_mhz, min_freq_mhz)))
        if lo < len(power_sub):
            peak_mhz = f_mhz[lo + int(np.argmax(power_sub[lo:]))]
        else:
            peak_mhz = f_mhz[int(np.argmax(power_sub))]
        if min_freq_mhz > 0.0:
            self.ax_right.axvspan(0, min_freq_mhz, color="#888888",
                                  alpha=0.15, zorder=0,
                                  label=f"< {min_freq_mhz:g} MHz excluded")
        if bg is not None:
            # Also show the unsubtracted FFT for reference
            power_raw = np.abs(np.fft.rfft(waveform)) ** 2
            power_raw[0] = 0.0
            self.ax_right.plot(f_mhz, power_raw, linewidth=0.5, color="#aaaaaa",
                               label="raw FFT", zorder=1)
        self.ax_right.plot(f_mhz, power_sub, linewidth=0.7, color="#4488cc",
                           label="subtracted FFT" if bg is not None else None, zorder=2)
        self.ax_right.axvline(peak_mhz, color="tomato", linestyle="--",
                              linewidth=1.2, label=f"peak = {peak_mhz:.1f} MHz")
        self.ax_right.set_xlabel("Frequency (MHz)")
        self.ax_right.set_ylabel("Power (arb.)")
        self.ax_right.set_title("FFT Power Spectrum")
        self.ax_right.set_xlim(0, 500)
        self.ax_right.legend(fontsize=8)
        self.draw()
    def show_dc_waveform(self, sras: SrasFile, angle_idx: int, ch_idx: int,
                         row_idx: int, frame_idx: int):
        """CH3 or CH4 DC: time-domain + mean annotation."""
        waveform = sras.data[angle_idx][row_idx, ch_idx, frame_idx, :].astype(np.float32)
        mean_val = float(waveform.mean())
        mean_mv = adc_to_mv(mean_val, *sras.cal(ch_idx))
        self.ax_wave.cla()
        self.ax_right.cla()
        self.ax_wave.plot(sras.time_axis_ns(), waveform, linewidth=0.7, color="#4488cc")
        self.ax_wave.axhline(mean_val, color="tomato", linestyle="--",
                             linewidth=1.2, label=f"mean = {mean_val:.2f} ADC")
        self.ax_wave.set_xlabel("Time (ns)")
        self.ax_wave.set_ylabel("ADC counts")
        self.ax_wave.set_title(
            f"{CH_NAMES[ch_idx]} DC  row={row_idx}  frame={frame_idx}")
        self.ax_wave.legend(fontsize=8)
        self.ax_right.text(
            0.5, 0.5,
            f"DC mode\n\nmean = {mean_val:.3f} ADC\n     = {mean_mv:.3f} mV",
            ha="center", va="center",
            transform=self.ax_right.transAxes, fontsize=11,
        )
        self.ax_right.set_axis_off()
        self.draw()
 class AlignOverlayCanvas(FigureCanvasQTAgg):
    """Renders the alignment wizard's multi-angle mask views and turns keyboard
    input into translate/rotate nudge requests for whichever angle is active.
    Two views of the same reprojected masks, because they answer different
    questions. show_counts colours each pixel by *how many* angles cover it,
    which is the at-a-glance verdict on a correlation run: a good alignment is
    one saturated plateau, a bad one is a fringe of low-count halos.
    show_overlay gives each angle its own colour, which is what you need while
    nudging a specific angle by hand.
    A pure input+render widget — it holds no alignment state and never
    touches SrasFile itself; the wizard page owns all of that and decides,
    from these signals, whether a cheap single-layer refresh or a
    full preview-canvas rebuild is needed.
    FigureCanvasQTAgg is a real QWidget, so keyPressEvent works like on any
    other widget, but Qt only ever delivers key events to whichever widget
    currently has focus — StrongFocus, plus grabbing focus on click and once
    right after the dialog is shown, are both required or arrow keys
    silently do nothing.
    Rotate keys are letters (Q/E), not punctuation (comma/period or
    brackets): Shift+letter still reports the same Qt.Key on every platform,
    whereas Shift+comma/bracket can report a different virtual key
    (Key_Less / Key_BraceLeft) depending on platform and keyboard layout —
    which would silently break the "Shift = coarse step" modifier for
    rotation specifically. Arrow keys have no such hazard.
    """
    nudge_translate = pyqtSignal(int, int, bool)   # dir_x, dir_y in {-1,0,1}; coarse
    nudge_rotate = pyqtSignal(int, bool)           # dir in {-1,1} (CCW/CW); coarse
    _TRANSLATE_KEYS = {
        Qt.Key.Key_Left:  (-1, 0),
        Qt.Key.Key_Right: (1, 0),
        Qt.Key.Key_Up:    (0, -1),
        Qt.Key.Key_Down:  (0, 1),
    }
    _ROTATE_KEYS = {Qt.Key.Key_Q: 1, Qt.Key.Key_E: -1}   # CCW, CW
    def __init__(self, parent=None):
        fig = Figure(figsize=(6, 6), tight_layout=True)
        self.ax = fig.add_subplot(111)
        super().__init__(fig)
        self.setParent(parent)
        self.setFocusPolicy(Qt.FocusPolicy.StrongFocus)
        self.setSizePolicy(QSizePolicy.Policy.Expanding, QSizePolicy.Policy.Expanding)
        self.mpl_connect("button_press_event", lambda _e: self.setFocus())
    def show_overlay(self, rgba: np.ndarray, extent: list[float], title: str):
        self.figure.clf()
        self.ax = self.figure.add_subplot(111)
        self.ax.imshow(rgba, extent=extent, origin="upper", aspect="auto")
        self._finish(title)
    def show_counts(self, counts: np.ndarray, n_angles: int,
                    extent: list[float], title: str):
        """The mask stack coloured by how many angles cover each pixel.
        A discrete colormap with integer-ticked colorbar rather than a
        continuous one: the judgement being made is "is this a plateau at N, or
        a fan of partial overlaps", and a region covered by one angle too few
        has to read as its own band rather than a slightly darker shade.
        Uncovered pixels are transparent so they cannot be mistaken for a low
        count.
        """
        self.figure.clf()
        self.ax = self.figure.add_subplot(111)
        cmap, norm, ticks = count_colormap(n_angles)
        im = self.ax.imshow(
            np.asarray(counts), extent=extent, origin="upper", aspect="auto",
            interpolation="nearest", cmap=cmap, norm=norm)
        cb = self.figure.colorbar(im, ax=self.ax, fraction=0.046, pad=0.04,
                                  ticks=ticks)
        cb.set_label("angles overlapping")
        self._finish(title)
    def _finish(self, title: str):
        self.ax.set_xlabel("X (mm)")
        self.ax.set_ylabel("Y (mm)")
        self.ax.set_title(title)
        self.draw_idle()   # coalesces rapid redraws — matters for key-repeat.
    def keyPressEvent(self, event: QKeyEvent):
        key = event.key()
        coarse = bool(event.modifiers() & Qt.KeyboardModifier.ShiftModifier)
        if key in self._TRANSLATE_KEYS:
            dx, dy = self._TRANSLATE_KEYS[key]
            self.nudge_translate.emit(dx, dy, coarse)
            event.accept()
        elif key in self._ROTATE_KEYS:
            self.nudge_rotate.emit(self._ROTATE_KEYS[key], coarse)
            event.accept()
        else:
            super().keyPressEvent(event)
@@ -0,0 +1,176 @@
 """Shared constants and small layout helpers for the viewer widgets."""
 from PyQt6.QtCore import Qt
 from PyQt6.QtWidgets import (
    QComboBox, QDoubleSpinBox, QFormLayout, QFrame, QGroupBox, QLabel,
    QScrollArea, QSizePolicy, QVBoxLayout, QWidget,
 )
 from sras_format import CH1_IDX, CH3_IDX, CH4_IDX, _axes_extent  # noqa: F401 (re-exported)
 # ---------------------------------------------------------------------------
 # Display constants
 # ---------------------------------------------------------------------------
 CH_LABELS = [
    "CH1 — RF (FFT peak freq)",
    "CH3 — Bias A (DC mean)",
    "CH4 — Bias B (DC mean)",
    "CH1 — Velocity (SRAS)",
 ]
 # Combo index for the derived velocity mode (uses CH1_IDX data)
 VELOCITY_MODE_IDX = 3
 # All modes that operate on CH1 waveforms
 CH1_DERIVED_MODES = (CH1_IDX, VELOCITY_MODE_IDX)
 CMAPS = ["gray", "viridis", "plasma", "inferno", "hot", "jet", "RdBu_r", "seismic"]
 # Fill color for masked (below-DC-threshold) pixels when "Highlight masked
 # pixels" is on, chosen to stand out against every colormap in CMAPS above.
 _MASKED_HIGHLIGHT_COLOR = "magenta"
 # (mode_str, status-bar unit, colorbar label) per channel index
 _CHANNEL_DISPLAY = {
    CH1_IDX: ("RF", "Peak frequency (MHz)", "MHz"),
    CH3_IDX: ("DC", "DC mean (mV)", "mV"),
    CH4_IDX: ("DC", "DC mean (mV)", "mV"),
    VELOCITY_MODE_IDX: ("Velocity", "Velocity (m/s)", "m/s"),
 }
 _CSS_HINT = "font-size: 11px; color: #aaa;"
 _CSS_INFO = "font-size: 11px;"
 _CSS_MUTED = "color: #888; font-size: 11px;"
 _CSS_WARN = "color: #e07000; font-size: 11px;"
 _CSS_BUSY = "color: #4a90d9; font-size: 11px;"
 # Side-panel column widths (the scroll areas that hold the controls).
 _LEFT_PANEL_W = 288
 _RIGHT_PANEL_W = 272
 # Minimum width for a spin box so its value + suffix are never clipped.
 _SPIN_MIN_W = 96
 # ---------------------------------------------------------------------------
 # Small layout helpers
 # ---------------------------------------------------------------------------
 class Jobs:
    """Keys for SrasViewerWindow's background-job registry (_run_worker /
    _job_running) and its progress dialogs — one place instead of string
    literals scattered across window and dialogs."""
    LOAD = "load"
    COMPUTE = "compute"
    DC_PRECOMPUTE = "dc_precompute"
    BATCH = "batch"
    EXPORT = "export"
    # The alignment wizard's three background steps: fetching each angle's CH4
    # image for the mask stack, registering the angles, and writing the aligned
    # export. Separate keys because a retry of one must not be blocked by
    # another having run, and _run_worker's busy check is per key.
    ALIGN_MASKS = "align_masks"
    ALIGN_CORRELATE = "align_correlate"
    ALIGN_EXPORT = "align_export"
 def _make_dspin(lo: float, hi: float, decimals: int, *, suffix: str = "",
                value: float | None = None, step: float | None = None) -> QDoubleSpinBox:
    """A QDoubleSpinBox with the panel-standard construction."""
    spin = QDoubleSpinBox()
    spin.setRange(lo, hi)
    spin.setDecimals(decimals)
    if suffix:
        spin.setSuffix(suffix)
    if step is not None:
        spin.setSingleStep(step)
    if value is not None:
        spin.setValue(value)
    spin.setMinimumWidth(_SPIN_MIN_W)
    return spin
 def _combo(items=(), *, min_chars: int = 10) -> QComboBox:
    """A combo box whose size hint does not depend on its longest entry.
    By default a QComboBox asks for enough width to show its widest item. These
    hold descriptive phrases, and the side panels are fixed-width — in a scroll
    area with the horizontal scrollbar off (`_scroll_panel`) an unconstrained
    hint pushes the inner widget past the panel and everything on the right,
    including the hint text, is silently clipped instead of scrolling.
    *items* is a sequence of (label, data) pairs, or of plain labels.
    """
    combo = QComboBox()
    combo.setSizeAdjustPolicy(
        QComboBox.SizeAdjustPolicy.AdjustToMinimumContentsLengthWithIcon)
    combo.setMinimumContentsLength(min_chars)
    for item in items:
        if isinstance(item, tuple):
            combo.addItem(item[0], item[1])
        else:
            combo.addItem(item)
    return combo
 def _wrap_label(text: str = "", css: str | None = None) -> QLabel:
    """A word-wrapped QLabel that reports its *wrapped* height to the layout.
    A plain word-wrapped QLabel advertises a single-line minimum height, so in a
    fixed-width column the layout happily shrinks it and the extra lines get
    clipped.  Enabling height-for-width makes the box layout ask for the real
    height at the column's width instead.
    """
    lbl = QLabel(text)
    lbl.setWordWrap(True)
    sp = lbl.sizePolicy()
    sp.setVerticalPolicy(QSizePolicy.Policy.Minimum)
    sp.setHeightForWidth(True)
    lbl.setSizePolicy(sp)
    if css:
        lbl.setStyleSheet(css)
    return lbl
 def _group(title: str) -> tuple[QGroupBox, QVBoxLayout]:
    """A group box with consistent, non-cramped internal margins."""
    grp = QGroupBox(title)
    lay = QVBoxLayout(grp)
    lay.setContentsMargins(10, 8, 10, 10)
    lay.setSpacing(6)
    return grp, lay
 def _form() -> QFormLayout:
    """A label/field form layout for a narrow side panel."""
    form = QFormLayout()
    form.setContentsMargins(0, 0, 0, 0)
    form.setHorizontalSpacing(8)
    form.setVerticalSpacing(6)
    form.setLabelAlignment(Qt.AlignmentFlag.AlignRight
                           | Qt.AlignmentFlag.AlignVCenter)
    form.setFormAlignment(Qt.AlignmentFlag.AlignLeft | Qt.AlignmentFlag.AlignTop)
    form.setFieldGrowthPolicy(
        QFormLayout.FieldGrowthPolicy.AllNonFixedFieldsGrow)
    form.setRowWrapPolicy(QFormLayout.RowWrapPolicy.DontWrapRows)
    return form
 def _scroll_panel(inner: QWidget, width: int) -> QScrollArea:
    """Put a side panel in a fixed-width scroll area.
    Without this the panels are sized by the window: a short window squeezes the
    controls past their minimum heights, which is what makes text overlap the
    widget below it.  Scrolling keeps every control at its natural size.
    """
    area = QScrollArea()
    area.setWidget(inner)
    area.setWidgetResizable(True)
    area.setFrameShape(QFrame.Shape.NoFrame)
    area.setHorizontalScrollBarPolicy(Qt.ScrollBarPolicy.ScrollBarAlwaysOff)
    area.setVerticalScrollBarPolicy(Qt.ScrollBarPolicy.ScrollBarAsNeeded)
    area.setFixedWidth(width)
    area.viewport().setAutoFillBackground(False)
    inner.setAutoFillBackground(False)
    return area
@@ -0,0 +1,523 @@
 """FFT option dialogs.
 Angle alignment used to live here too, as ManualAlignmentDialog; it is now the
 alignment wizard's first page (see align_wizard.py), which needed the same
 mask-overlay editor plus the crop and export steps.
 """
 from pathlib import Path
 from PyQt6.QtWidgets import (
    QButtonGroup, QCheckBox, QDialog, QDialogButtonBox, QDoubleSpinBox,
    QFileDialog, QGridLayout, QGroupBox, QHBoxLayout, QLabel, QLineEdit,
    QMessageBox, QPushButton, QRadioButton, QScrollArea, QSpinBox,
    QVBoxLayout, QWidget,
 )
 from sras_format import CH1_IDX, CH3_IDX, CH4_IDX, CH_NAMES
 from sras_workers import ExportChannel
 from .common import (
    CH_LABELS, VELOCITY_MODE_IDX, _CHANNEL_DISPLAY, _CSS_HINT, _CSS_WARN,
    _SPIN_MIN_W, _form, _group, _make_dspin, _wrap_label,
 )
 # ---------------------------------------------------------------------------
 # FFT Options dialog
 # ---------------------------------------------------------------------------
 class FftOptionsDialog(QDialog):
    """Configure FFT zero-padding.
    Changes take effect only when the user clicks Apply.  Cancel discards
    all pending edits.  The live 'frequency resolution' label updates as
    the user adjusts the pad factor so they can see the trade-off before
    committing.
    """
    def __init__(self, parent=None, *,
                 current_pad_factor: int,
                 samples_per_frame: int | None,
                 sample_rate_hz: float | None,
                 grating_um: float):
        super().__init__(parent)
        self.setWindowTitle("FFT Options")
        self.setModal(True)
        self.setMinimumWidth(380)
        self._samples_per_frame = samples_per_frame
        self._sample_rate_hz = sample_rate_hz
        self._grating_um = grating_um
        layout = QVBoxLayout(self)
        # ---- Zero-padding ----------------------------------------------
        grp_zp = QGroupBox("Zero-Padding")
        zl = QVBoxLayout(grp_zp)
        pad_row = QHBoxLayout()
        pad_row.addWidget(QLabel("Pad factor:"))
        self._spin_pad = QSpinBox()
        self._spin_pad.setRange(1, 256)
        self._spin_pad.setValue(max(1, current_pad_factor))
        self._spin_pad.setToolTip(
            "Multiply the waveform length by this factor via zero-padding\n"
            "before computing the FFT.\n"
            "1 = no padding (natural length).\n"
            "Powers of 2 (2, 4, 8 …) give the best performance."
        )
        self._spin_pad.valueChanged.connect(self._update_info)
        pad_row.addWidget(self._spin_pad)
        zl.addLayout(pad_row)
        self._lbl_nfft = QLabel()
        self._lbl_freq_res = QLabel()
        self._lbl_vel_res = QLabel()
        for lbl in (self._lbl_nfft, self._lbl_freq_res, self._lbl_vel_res):
            lbl.setStyleSheet(_CSS_HINT)
            zl.addWidget(lbl)
        layout.addWidget(grp_zp)
        # ---- Buttons ---------------------------------------------------
        buttons = QDialogButtonBox()
        buttons.addButton("Apply", QDialogButtonBox.ButtonRole.AcceptRole
                          ).clicked.connect(self.accept)
        buttons.addButton("Cancel", QDialogButtonBox.ButtonRole.RejectRole
                          ).clicked.connect(self.reject)
        layout.addWidget(buttons)
        self._update_info()
    def _update_info(self):
        spf = self._samples_per_frame
        sr = self._sample_rate_hz
        pad = self._spin_pad.value()
        if spf is None or sr is None:
            self._lbl_nfft.setText("Load a file to preview FFT parameters.")
            self._lbl_freq_res.setText("")
            self._lbl_vel_res.setText("")
            return
        n_fft = spf * pad
        freq_res_hz = sr / n_fft
        freq_res_mhz = freq_res_hz / 1e6
        # v (m/s) = freq (MHz) × grating (µm)
        vel_res_ms = freq_res_mhz * self._grating_um
        self._lbl_nfft.setText(f"FFT points: {spf} × {pad} = {n_fft:,}")
        self._lbl_freq_res.setText(
            f"Frequency bin: {freq_res_mhz:.4f} MHz  ({freq_res_hz / 1e3:.2f} kHz)")
        self._lbl_vel_res.setText(
            f"Velocity bin: {vel_res_ms:.3f} m/s  "
            f"(at grating = {self._grating_um:.2f} µm)")
    def get_pad_factor(self) -> int:
        return max(1, self._spin_pad.value())
 # ---------------------------------------------------------------------------
 # Row-Averaged FFT Options dialog
 # ---------------------------------------------------------------------------
 class RowAverageFftOptionsDialog(QDialog):
    """Configure the same-row, distance-weighted neighbor averaging applied
    to each pixel's CH1 waveform before 'Batch Compute Row-Averaged FFT and
    Store' re-runs the FFT peak search — a same-row SNR cleanup pass, never
    mixing across rows/Y (see sras_compute._row_average_waveforms).
    Unlike the plain FFT batch action (which stores unmasked and defers
    masking to display time), the DC threshold here is required up front:
    it decides which same-row neighbors are eligible to contribute to a
    pixel's average, so it can't be deferred.
    Changes take effect only when the user clicks Apply. Cancel discards
    all pending edits.
    """
    def __init__(self, parent=None, *,
                 current_n: int,
                 current_threshold_mv: float,
                 pixel_x_mm: float | None):
        super().__init__(parent)
        self.setWindowTitle("Row-Averaged FFT Options")
        self.setModal(True)
        self.setMinimumWidth(380)
        self._pixel_x_mm = pixel_x_mm
        layout = QVBoxLayout(self)
        # ---- Neighbor window ---------------------------------------------
        grp_window = QGroupBox("Same-Row Neighbor Window")
        wl = QVBoxLayout(grp_window)
        n_row = QHBoxLayout()
        n_row.addWidget(QLabel("Neighbor half-width (n):"))
        self._spin_n = QSpinBox()
        self._spin_n.setRange(1, 50)
        self._spin_n.setValue(max(1, current_n))
        self._spin_n.setToolTip(
            "Each pixel's CH1 waveform is averaged with up to n same-row\n"
            "neighbors on each side, distance-weighted (Gaussian) and\n"
            "counting only neighbors that already pass the DC threshold\n"
            "below. Never mixes across rows/Y.")
        self._spin_n.valueChanged.connect(self._update_info)
        n_row.addWidget(self._spin_n)
        wl.addLayout(n_row)
        self._lbl_width = QLabel()
        self._lbl_width.setStyleSheet(_CSS_HINT)
        wl.addWidget(self._lbl_width)
        layout.addWidget(grp_window)
        # ---- DC threshold ------------------------------------------------
        grp_thr = QGroupBox("Neighbor Validity")
        tl = QVBoxLayout(grp_thr)
        thr_row = QHBoxLayout()
        thr_row.addWidget(QLabel("DC threshold:"))
        self._spin_threshold = _make_dspin(-500.0, 500.0, 3, suffix=" mV",
                                           value=current_threshold_mv, step=0.025)
        self._spin_threshold.setToolTip(
            "A same-row neighbor only contributes to a pixel's average if\n"
            "its own CH4 signal is at or above this threshold -- the same\n"
            "test used for RF mask display. A pixel below threshold stays\n"
            "masked, exactly as today; it is never rescued by its neighbors.")
        thr_row.addWidget(self._spin_threshold)
        tl.addLayout(thr_row)
        layout.addWidget(grp_thr)
        # ---- Buttons -----------------------------------------------------
        buttons = QDialogButtonBox()
        buttons.addButton("Apply", QDialogButtonBox.ButtonRole.AcceptRole
                          ).clicked.connect(self.accept)
        buttons.addButton("Cancel", QDialogButtonBox.ButtonRole.RejectRole
                          ).clicked.connect(self.reject)
        layout.addWidget(buttons)
        self._update_info()
    def _update_info(self):
        n = self._spin_n.value()
        if self._pixel_x_mm is None:
            self._lbl_width.setText("Load a file to preview the window's physical width.")
            return
        width_um = 2 * n * self._pixel_x_mm * 1e3
        self._lbl_width.setText(
            f"Window: ±{n} px = {width_um:.2f} µm full width "
            f"(pixel pitch {self._pixel_x_mm * 1e3:.3g} µm)")
    def get_half_width(self) -> int:
        return self._spin_n.value()
    def get_threshold_mv(self) -> float:
        return self._spin_threshold.value()
 # ---------------------------------------------------------------------------
 # Batch export dialog (Export -> Batch Export Images...)
 # ---------------------------------------------------------------------------
 class BatchExportDialog(QDialog):
    """Configure a batch PNG export of DC/RF/Velocity maps across every angle
    of the currently open file.
    Each channel's colorbar range is entered here and held fixed for every
    exported angle (rather than auto-scaled per image, today's live-view
    default) so the exported images are directly comparable to each other.
    """
    # (ch_idx, is_velocity, label, colorbar unit, filename tag)
    _ROWS = [
        (CH1_IDX, False, CH_LABELS[CH1_IDX], _CHANNEL_DISPLAY[CH1_IDX][2],
         CH_NAMES[CH1_IDX]),
        (CH3_IDX, False, CH_LABELS[CH3_IDX], _CHANNEL_DISPLAY[CH3_IDX][2],
         CH_NAMES[CH3_IDX]),
        (CH4_IDX, False, CH_LABELS[CH4_IDX], _CHANNEL_DISPLAY[CH4_IDX][2],
         CH_NAMES[CH4_IDX]),
        (CH1_IDX, True, CH_LABELS[VELOCITY_MODE_IDX],
         _CHANNEL_DISPLAY[VELOCITY_MODE_IDX][2], CH_NAMES[VELOCITY_MODE_IDX]),
    ]
    # DC is cheap and precomputed on load; CH1/Velocity need a per-pixel FFT
    # that can take minutes, so don't default to exporting them (same
    # rationale as SrasViewerWindow._on_load_done's channel default).
    _DEFAULT_CHECKED = {CH3_IDX, CH4_IDX}
    def __init__(self, parent, *, default_dir: str, default_prefix: str,
                 default_ranges: dict[tuple[int, bool], tuple[float, float]]):
        super().__init__(parent)
        self.setWindowTitle("Batch Export Images")
        self.setModal(True)
        self.setMinimumWidth(460)
        layout = QVBoxLayout(self)
        # ---- Output ------------------------------------------------------
        grp_out, ol = _group("Output")
        dir_row = QHBoxLayout()
        self._edit_dir = QLineEdit(default_dir)
        btn_browse = QPushButton("Browse…")
        btn_browse.clicked.connect(self._on_browse)
        dir_row.addWidget(self._edit_dir)
        dir_row.addWidget(btn_browse)
        out_form = _form()
        out_form.addRow("Folder:", dir_row)
        self._edit_prefix = QLineEdit(default_prefix)
        out_form.addRow("File prefix:", self._edit_prefix)
        ol.addLayout(out_form)
        layout.addWidget(grp_out)
        # ---- Channels ------------------------------------------------------
        grp_ch, cl = _group("Channels  (fixed range, applied to every angle)")
        grid = QGridLayout()
        grid.setHorizontalSpacing(8)
        grid.setVerticalSpacing(6)
        grid.addWidget(_wrap_label("min:", _CSS_HINT), 0, 1)
        grid.addWidget(_wrap_label("max:", _CSS_HINT), 0, 2)
        self._rows: list[tuple[QCheckBox, QDoubleSpinBox, QDoubleSpinBox]] = []
        for i, (ch_idx, is_velocity, label, unit, _tag) in enumerate(self._ROWS, 1):
            chk = QCheckBox(label + (f"  [{unit}]" if unit else ""))
            chk.setChecked(not is_velocity and ch_idx in self._DEFAULT_CHECKED)
            vmin, vmax = default_ranges.get((ch_idx, is_velocity), (0.0, 1.0))
            spin_min, spin_max = QDoubleSpinBox(), QDoubleSpinBox()
            for spin, val in ((spin_min, vmin), (spin_max, vmax)):
                spin.setRange(-1e9, 1e9)
                spin.setDecimals(4)
                spin.setMinimumWidth(_SPIN_MIN_W)
                spin.setValue(val)
            grid.addWidget(chk, i, 0)
            grid.addWidget(spin_min, i, 1)
            grid.addWidget(spin_max, i, 2)
            self._rows.append((chk, spin_min, spin_max))
        cl.addLayout(grid)
        layout.addWidget(grp_ch)
        # ---- Buttons --------------------------------------------------
        buttons = QDialogButtonBox()
        buttons.addButton("Export", QDialogButtonBox.ButtonRole.AcceptRole
                          ).clicked.connect(self.accept)
        buttons.addButton("Cancel", QDialogButtonBox.ButtonRole.RejectRole
                          ).clicked.connect(self.reject)
        layout.addWidget(buttons)
    def _on_browse(self):
        d = QFileDialog.getExistingDirectory(
            self, "Select Output Folder", self._edit_dir.text())
        if d:
            self._edit_dir.setText(d)
    def accept(self):
        """Validate before closing — Cancel bypasses this entirely."""
        if not self.get_prefix():
            QMessageBox.warning(self, "Batch Export", "Enter a file prefix.")
            return
        if not self.get_output_dir():
            QMessageBox.warning(self, "Batch Export", "Choose an output folder.")
            return
        selected = self.get_selected_channels()
        if not selected:
            QMessageBox.warning(
                self, "Batch Export", "Select at least one channel to export.")
            return
        for ch in selected:
            if not ch.vmin < ch.vmax:
                QMessageBox.warning(
                    self, "Batch Export", f"{ch.label}: min must be less than max.")
                return
        super().accept()
    def get_output_dir(self) -> str:
        return self._edit_dir.text().strip()
    def get_prefix(self) -> str:
        return self._edit_prefix.text().strip()
    def get_selected_channels(self) -> list[ExportChannel]:
        result = []
        for (chk, spin_min, spin_max), (ch_idx, is_velocity, label, unit, tag) in zip(
                self._rows, self._ROWS):
            if chk.isChecked():
                result.append(ExportChannel(
                    ch_idx=ch_idx, is_velocity=is_velocity,
                    vmin=spin_min.value(), vmax=spin_max.value(),
                    label=label, unit=unit, tag=tag))
        return result
 # ---------------------------------------------------------------------------
 # Export Fused ROI dialog
 # ---------------------------------------------------------------------------
 class FusedRoiExportDialog(QDialog):
    """Choose a value type and which angles to fuse for Export Fused ROI.
    Every angle in the file is listed (a live AlignmentResult's per_angle
    always covers every angle, and the raw-shared-grid path needs no per-
    angle transform at all). Each checkbox is disabled — and auto-unchecked
    — whenever *availability_fn(angle_idx, ch_idx)* is False for the
    currently selected value type; switching the value-type radio
    re-evaluates every checkbox live, since availability is per (angle,
    value type) rather than just per angle — e.g. DC may be ready
    everywhere while FFT is ready nowhere.
    """
    _VALUE_MODES = (CH1_IDX, CH3_IDX, CH4_IDX, VELOCITY_MODE_IDX)
    def __init__(self, parent=None, *,
                 angles: list[tuple[int, float]],
                 availability_fn,
                 default_ch_idx: int,
                 out_dir: str,
                 stem: str,
                 grid_note: str):
        super().__init__(parent)
        self.setWindowTitle("Export Fused ROI")
        self.setModal(True)
        self.setMinimumWidth(420)
        self._availability_fn = availability_fn
        self._out_dir = out_dir
        self._stem = stem
        self._path_user_chosen = False
        layout = QVBoxLayout(self)
        layout.addWidget(_wrap_label(grid_note, _CSS_HINT))
        # ---- Value type --------------------------------------------------
        grp_val, vl = _group("Value to Export")
        self._val_group = QButtonGroup(self)
        self._val_buttons: dict[int, QRadioButton] = {}
        for ch_idx, label in zip(self._VALUE_MODES, CH_LABELS):
            rb = QRadioButton(label)
            self._val_group.addButton(rb, id=ch_idx)
            self._val_buttons[ch_idx] = rb
            vl.addWidget(rb)
        self._val_buttons[default_ch_idx].setChecked(True)
        self._val_group.idClicked.connect(self._on_value_type_changed)
        layout.addWidget(grp_val)
        # ---- Angles --------------------------------------------------
        grp_ang, al = _group("Angles to Include")
        sel_row = QHBoxLayout()
        btn_all = QPushButton("Select All Available")
        btn_none = QPushButton("Select None")
        btn_all.clicked.connect(self._on_select_all_available)
        btn_none.clicked.connect(self._on_select_none)
        sel_row.addWidget(btn_all)
        sel_row.addWidget(btn_none)
        al.addLayout(sel_row)
        scroll_inner = QWidget()
        scroll_layout = QVBoxLayout(scroll_inner)
        self._angle_checks: dict[int, QCheckBox] = {}
        for angle_idx, angle_deg in angles:
            cb = QCheckBox(f"{angle_deg:.1f}°  (angle {angle_idx})")
            self._angle_checks[angle_idx] = cb
            cb.toggled.connect(self._update_accept_enabled)
            scroll_layout.addWidget(cb)
        scroll = QScrollArea()
        scroll.setWidget(scroll_inner)
        scroll.setWidgetResizable(True)
        scroll.setMaximumHeight(220)
        al.addWidget(scroll)
        self._lbl_none_available = _wrap_label("", _CSS_WARN)
        al.addWidget(self._lbl_none_available)
        layout.addWidget(grp_ang)
        # ---- Output path --------------------------------------------------
        grp_out, ol = _group("Output File")
        path_row = QHBoxLayout()
        self._edit_path = QLineEdit()
        self._edit_path.setReadOnly(True)
        path_row.addWidget(self._edit_path, 1)
        btn_browse = QPushButton("Browse…")
        btn_browse.clicked.connect(self._on_browse)
        path_row.addWidget(btn_browse)
        ol.addLayout(path_row)
        layout.addWidget(grp_out)
        # ---- Buttons -----------------------------------------------------
        buttons = QDialogButtonBox()
        self._btn_export = buttons.addButton(
            "Export", QDialogButtonBox.ButtonRole.AcceptRole)
        self._btn_export.clicked.connect(self.accept)
        buttons.addButton("Cancel", QDialogButtonBox.ButtonRole.RejectRole
                          ).clicked.connect(self.reject)
        layout.addWidget(buttons)
        self._refresh_default_path()
        self._apply_availability()
    # ---- internals -----------------------------------------------------
    def _current_ch_idx(self) -> int:
        return self._val_group.checkedId()
    def _apply_availability(self):
        ch_idx = self._current_ch_idx()
        n_ok = 0
        for angle_idx, cb in self._angle_checks.items():
            ok = self._availability_fn(angle_idx, ch_idx)
            cb.setEnabled(ok)
            if ok:
                n_ok += 1
                cb.setToolTip("")
            else:
                cb.setChecked(False)
                cb.setToolTip(
                    f"No cached/stored {CH_LABELS[ch_idx]} data for this "
                    "angle yet — view it in the main window (or run "
                    "Batch Compute) first.")
        self._lbl_none_available.setText(
            "" if n_ok else "No angle has this value type ready yet.")
        self._update_accept_enabled()
    def _on_value_type_changed(self, _id: int):
        self._apply_availability()
        if not self._path_user_chosen:
            self._refresh_default_path()
    def _on_select_all_available(self):
        for cb in self._angle_checks.values():
            if cb.isEnabled():
                cb.setChecked(True)
    def _on_select_none(self):
        for cb in self._angle_checks.values():
            cb.setChecked(False)
    def _refresh_default_path(self):
        ch_idx = self._current_ch_idx()
        name = f"{self._stem}_fused_roi_{CH_NAMES[ch_idx]}.csv"
        self._edit_path.setText(str(Path(self._out_dir) / name))
        self._update_accept_enabled()
    def _on_browse(self):
        path, _ = QFileDialog.getSaveFileName(
            self, "Export Fused ROI as CSV", self._edit_path.text(),
            "CSV files (*.csv);;All files (*)")
        if path:
            self._edit_path.setText(path)
            self._path_user_chosen = True
            self._update_accept_enabled()
    def _update_accept_enabled(self):
        any_checked = any(cb.isChecked() for cb in self._angle_checks.values())
        self._btn_export.setEnabled(any_checked and bool(self._edit_path.text()))
    # ---- getters ---------------------------------------------------------
    def get_ch_idx(self) -> int:
        return self._current_ch_idx()
    def get_selected_angles(self) -> list[int]:
        return sorted(a for a, cb in self._angle_checks.items() if cb.isChecked())
    def get_output_path(self) -> str:
        return self._edit_path.text()
@@ -1,3 +0,0 @@
 PyQt6==6.10.2
 numpy==2.4.1
 matplotlib==3.10.8
@@ -0,0 +1,703 @@
 #!/usr/bin/env python3
 """Background workers for the SRAS viewer.
 Every worker is a plain QObject moved onto its own QThread by
 SrasViewerWindow._run_worker, exposing signals only. Workers must never touch
 GUI-thread-owned state (the display caches in particular) — they take
 everything they need through their constructor and hand results back by signal.
 """
 import os
 from concurrent.futures import ProcessPoolExecutor, ThreadPoolExecutor, as_completed
 from concurrent.futures.process import BrokenProcessPool
 from dataclasses import dataclass
 from pathlib import Path
 import numpy as np
 from matplotlib.backends.backend_agg import FigureCanvasAgg
 from matplotlib.figure import Figure
 from PyQt6.QtCore import QObject, pyqtSignal
 import sras_compute as compute
 from sras_align_export import write_aligned_sras
 from sras_compute import cache_file, compute_rf_image, dc_image_mv
 from sras_format import CH1_IDX, CH3_IDX, CH4_IDX, SrasFile
 from sras_render import export_view_image, sanitize_figsize
 # Concurrency caps. Batch conversion runs one process per file, and each of
 # those processes threads internally, so the two must be divided rather than
 # both set to the core count. Files also commonly sit on one external drive,
 # where a dozen concurrent readers is slower than a few — hence the low
 # default, overridable from the environment.
 _BATCH_MAX_PROCS = int(os.environ.get("SRAS_BATCH_PROCS", 0)) or min(
    4, os.cpu_count() or 2)
 # Spawning a pool costs roughly a second of interpreter startup (each child
 # re-imports the entry module). That is noise against a multi-GB scan but
 # dominates a batch of small files, where it would make the job *slower* —
 # so below this total size the batch just runs in the worker thread.
 _BATCH_POOL_MIN_BYTES = int(os.environ.get("SRAS_BATCH_POOL_MIN_MB", 512)) * 1024 * 1024
 class CancellableWorker(QObject):
    """A worker whose compute polls stop() between row chunks.
    Without this a shutdown has to wait out whatever is in flight, and on a
    large scan a single angle is ~40 s — far too long to block closing the
    window. Chunk-level polling bounds the wait to one chunk instead.
    """
    def __init__(self):
        super().__init__()
        self._stop = False
    def stop(self):
        self._stop = True
    def _stopped(self) -> bool:
        return self._stop
 class _PooledWorker(CancellableWorker):
    """Fans a per-item computation across a thread pool, emitting each result
    from this worker's own thread as it lands (never from a pool thread).
    Subclasses provide _plan() -> n_workers (stashing whatever per-run
    context they need), _items(), _one(item) -> result, and _emit(result).
    On stop(): queued items are dropped, in-flight ones are not waited for —
    that is what keeps closing the window responsive on a large scan.
    """
    finished = pyqtSignal()
    error = pyqtSignal(str)
    def run(self):
        try:
            pool = ThreadPoolExecutor(max_workers=max(1, self._plan()))
            try:
                futures = [pool.submit(self._one, it) for it in self._items()]
                for fut in as_completed(futures):
                    if self._stop:
                        break
                    self._emit(fut.result())
            finally:
                pool.shutdown(wait=not self._stop, cancel_futures=True)
            self.finished.emit()
        except Exception as exc:
            self.error.emit(str(exc))
 class LoadWorker(QObject):
    finished = pyqtSignal(object)   # SrasFile | None
    error = pyqtSignal(str)
    def __init__(self, path: str):
        super().__init__()
        self._path = path
    def run(self):
        try:
            self.finished.emit(SrasFile(self._path))
        except Exception as exc:
            self.error.emit(str(exc))
            self.finished.emit(None)
 class ComputeWorker(CancellableWorker):
    """Computes one displayable image for (angle, channel).
    For CH1/Velocity (FFT-derived) channels, the FFT is only run for pixels
    whose DC4 (Bias B) mean is at or above dc_threshold_mv — masked pixels are
    left at 0 MHz without ever being FFT'd, since that's the expensive part of
    a scan. If the DC4 image for this angle is already known, pass it in as
    *dc4_mv* to skip re-reading the CH4 channel from disk entirely.
    Emits a plain ``np.ndarray`` already in display units.
    """
    finished = pyqtSignal(object)
    error = pyqtSignal(str)
    def __init__(self, sras: SrasFile, angle_idx: int, ch_idx: int,
                 apply_bg_sub: bool = True, n_fft: int | None = None,
                 dc_threshold_mv: float = 0.0,
                 dc4_mv: np.ndarray | None = None,
                 is_fft_mode: bool = False,
                 row_avg_n: int = 0,
                 min_freq_mhz: float = 0.0):
        super().__init__()
        self._sras = sras
        self._angle = angle_idx
        self._ch = ch_idx
        self._apply_bg_sub = apply_bg_sub
        self._n_fft = n_fft
        self._dc_threshold = dc_threshold_mv
        self._dc4_mv = dc4_mv
        self._is_fft_mode = is_fft_mode
        self._row_avg_n = row_avg_n
        self._min_freq_mhz = min_freq_mhz
    def run(self):
        try:
            if self._is_fft_mode:
                img = compute_rf_image(
                    self._sras, self._angle, dc_threshold_mv=self._dc_threshold,
                    apply_bg_sub=self._apply_bg_sub, n_fft=self._n_fft,
                    dc4_mv=self._dc4_mv, should_stop=self._stopped,
                    row_avg_n=self._row_avg_n,
                    min_freq_mhz=self._min_freq_mhz)
            else:
                img = dc_image_mv(self._sras, self._angle, self._ch,
                                  should_stop=self._stopped)
            # On cancellation the image is only partly filled, so hand back
            # None rather than something that would be cached as real. The
            # signal still fires either way — it is what quits the thread.
            self.finished.emit(None if self._stop else img)
        except Exception as exc:
            self.error.emit(str(exc))
 class DcPrecomputeWorker(_PooledWorker):
    """Computes CH3/CH4 DC images for every angle in the background.
    DC images are cheap (a per-waveform mean, no FFT) compared to the
    CH1/Velocity FFT, so precomputing them for the whole file right after load
    makes switching angles instant while on a DC channel, and also means the
    FFT masking step (which needs a DC4 image) rarely has to wait on anything.
    """
    angle_done = pyqtSignal(int, np.ndarray, np.ndarray)   # angle_idx, dc3_mv, dc4_mv
    def __init__(self, sras: SrasFile):
        super().__init__()
        self._sras = sras
        self._angle_budget = 0
    def _plan(self) -> int:
        n_workers, self._angle_budget = compute.plan_angle_level(self._sras)
        return n_workers
    def _items(self):
        return range(self._sras.n_angles)
    def _one(self, a: int) -> tuple[int, np.ndarray, np.ndarray]:
        # max_workers=1 *and* a budget share: this call is one of several
        # concurrent angles, and both the thread count and the buffer size
        # have to be divided (see compute.plan_angle_level).
        kw = dict(max_workers=1, budget=self._angle_budget,
                  should_stop=self._stopped)
        return (a,
                dc_image_mv(self._sras, a, CH3_IDX, **kw),
                dc_image_mv(self._sras, a, CH4_IDX, **kw))
    def _emit(self, result):
        self.angle_done.emit(*result)
 class BatchCacheWorker(QObject):
    """Batch-computes and stores DC or FFT images into each of *paths*'s v7
    CACH tail, in place — converting v6 sources to v7 on first use, or updating
    an existing v7 file's cache blocks without disturbing whatever the other
    block already holds.
    *mode* is ``"dc"`` (CH3/CH4 mean images), ``"fft"`` (CH1 peak-frequency
    images, unmasked — masking is applied at display time, same as v5's PREC
    convention), or ``"fft_rowavg"`` (same-row, distance-weighted CH1
    averaging before the FFT — needs *dc_threshold_mv* and a positive
    *row_avg_n*; see ``sras_compute.cache_file``).
    Both FFT modes cache at *pad_factor*, which the caller sets from the
    viewer's own padding — a cache stored at a pad the user is not viewing
    at is one the display can never use. *min_freq_mhz* travels the same
    way: the viewer's live min-peak-freq floor, recorded in the store as
    provenance so a reader knows which bins the peak search considered.
    Files are processed one per subprocess: they are fully independent, each
    opens its own memmap and writes only its own bytes, and only path strings
    and scalars cross the process boundary. Emits ``progress(int)`` (0–100 by
    files completed), ``file_done(str, str)`` (path, error message or "") so
    one file's failure doesn't abort the batch, and ``finished()``.
    """
    progress = pyqtSignal(int)
    file_done = pyqtSignal(str, str)
    finished = pyqtSignal()
    def __init__(self, paths: list[str], mode: str, apply_bg_sub: bool,
                dc_threshold_mv: float | None = None, row_avg_n: int = 0,
                pad_factor: int = 1, min_freq_mhz: float = 0.0):
        super().__init__()
        self._paths = paths
        self._mode = mode
        self._apply_bg_sub = apply_bg_sub
        self._dc_threshold = dc_threshold_mv
        self._row_avg_n = row_avg_n
        self._pad_factor = pad_factor
        self._min_freq_mhz = min_freq_mhz
    def _report(self, path: str, err: str, done: int, total: int):
        self.file_done.emit(path, err)
        self.progress.emit(int(done / max(1, total) * 100))
    def _run_pooled(self, paths: list[str], n_procs: int) -> list[str]:
        """Process the batch across *n_procs* subprocesses. Returns the paths
        that never got a real answer because the pool itself died, so the
        caller can retry them in-process.
        Under spawn each child re-imports the entry module, so the batch must
        survive that going wrong (an unguarded __main__, a frozen build, a
        sandbox that forbids subprocesses) rather than reporting every file as
        failed — hence the retry list instead of a per-file error.
        """
        # Each child threads internally; divide the machine rather than
        # letting every process claim every core.
        per_proc_workers = max(1, (os.cpu_count() or 4) // n_procs)
        unresolved: list[str] = []
        done = 0
        with ProcessPoolExecutor(max_workers=n_procs) as executor:
            futures = {
                executor.submit(cache_file, p, self._mode, self._apply_bg_sub,
                                per_proc_workers,
                                pad_factor=self._pad_factor,
                                dc_threshold_mv=self._dc_threshold,
                                row_avg_n=self._row_avg_n,
                                min_freq_mhz=self._min_freq_mhz): p
                for p in paths
            }
            for fut in as_completed(futures):
                path = futures[fut]
                try:
                    err = fut.result()
                except BrokenProcessPool:
                    unresolved.append(path)
                    continue
                except Exception as exc:
                    err = str(exc)
                done += 1
                self._report(path, err, done, len(paths))
        return unresolved
    def _run_inline(self, paths: list[str], done: int, total: int):
        """Fallback / single-file path: compute in this thread. Still uses the
        full core count internally, since nothing else is competing."""
        for path in paths:
            try:
                err = cache_file(path, self._mode, self._apply_bg_sub,
                                 compute.default_max_workers(),
                                 pad_factor=self._pad_factor,
                                 dc_threshold_mv=self._dc_threshold,
                                 row_avg_n=self._row_avg_n,
                                 min_freq_mhz=self._min_freq_mhz)
            except Exception as exc:
                err = str(exc)
            done += 1
            self._report(path, err, done, total)
    def _worth_pooling(self, paths: list[str]) -> bool:
        if len(paths) < 2:
            return False
        total = 0
        for p in paths:
            try:
                total += os.path.getsize(p)
            except OSError:
                pass          # unreadable files are reported by cache_file
        return total >= _BATCH_POOL_MIN_BYTES
    def run(self):
        paths = self._paths
        n_procs = max(1, min(_BATCH_MAX_PROCS, len(paths)))
        if not self._worth_pooling(paths):
            self._run_inline(paths, 0, len(paths))
            self.finished.emit()
            return
        try:
            unresolved = self._run_pooled(paths, n_procs)
        except Exception:
            # The pool could not be created or collapsed wholesale.
            unresolved = list(paths)
        if unresolved:
            self._run_inline(unresolved, len(paths) - len(unresolved), len(paths))
        self.finished.emit()
@dataclass
 class ExportChannel:
    """One row of a batch image export: which raw channel to read, whether
    to apply the Velocity post-multiply, and the fixed display range/labels
    to render it with.
    Kept free of sras_viewer's display constants (CH_LABELS, VELOCITY_MODE_IDX,
    etc.) so BatchExportWorker has no dependency on the GUI module — the
    caller resolves labels/units/filename tags once, up front.
    """
    ch_idx: int        # CH1_IDX, CH3_IDX, or CH4_IDX -- which raw data to read
    is_velocity: bool  # True only for the derived Velocity map (post-multiply of CH1 freq)
    vmin: float
    vmax: float
    label: str          # e.g. "CH3 -- Bias A (DC mean)"
    unit: str           # colorbar units, e.g. "mV"
    tag: str            # filename tag: "CH1", "CH3", "CH4", "VEL"
 def _render_map_png(img: np.ndarray, extent: list[float], *, cmap: str,
                    vmin: float, vmax: float, title: str, colorbar_label: str,
                    out_path: str, figsize: tuple[float, float] | None = None):
    """Render one map image to *out_path* with a fixed vmin/vmax, using a
    headless Agg canvas so this never touches the GUI thread's interactive
    matplotlib backend. Layout mirrors ImageCanvas.show_image.
    *figsize* is the live canvas's size in inches, so the PNG comes out at
    the shape the view was being read at instead of a fixed 7x5 -- with
    aspect="auto" below, the figure box is what sets the map's proportions.
    None falls back to sras_render.DEFAULT_FIGSIZE."""
    fig = Figure(figsize=sanitize_figsize(figsize), tight_layout=True)
    FigureCanvasAgg(fig)
    ax = fig.add_subplot(111)
    im = ax.imshow(img, aspect="auto", origin="upper", extent=extent,
                   cmap=cmap, vmin=vmin, vmax=vmax, interpolation="nearest")
    cb = fig.colorbar(im, ax=ax, fraction=0.046, pad=0.04)
    if colorbar_label:
        cb.set_label(colorbar_label)
    ax.set_xlabel("X (mm)")
    ax.set_ylabel("Y (mm)")
    ax.set_title(title)
    fig.savefig(out_path, dpi=150)
 class BatchExportWorker(CancellableWorker):
    """Renders and saves one PNG per (angle, selected channel) for an
    already-open SrasFile, with each channel's vmin/vmax held fixed across
    every angle so the colorbar is directly comparable image to image.
    Takes the SrasFile object directly (like ComputeWorker/DcPrecomputeWorker)
    rather than a path -- this runs against the file already open in the GUI,
    not an arbitrary batch of files, so there is no need to reopen it in a
    subprocess the way BatchCacheWorker does.
    Every setting that decides what an FFT-derived pixel *is* has to arrive
    here explicitly, because compute_rf_image defaults each one to "off" and
    an omitted argument is therefore not a no-op -- it silently exports a
    different image than the one on screen. *min_freq_mhz* is the one with
    teeth: dropping it does not just skip a mask, it also makes this file's
    stored cache (written by Batch Compute FFT at some earlier floor) look
    like a match, so the export hands back the pre-floor peaks the user
    raised the floor to get rid of. It mirrors
    SrasViewerWindow._stored_fft_image, which takes the floor live for the
    same reason -- re-masking a stored image against a *higher* floor is
    free, so the displayed map always honors the spin box.
    Emits progress(int) (0-100 over all angle x channel pairs), file_done(str,
    str) (output path, error message or ""), and finished() -- same shape as
    BatchCacheWorker.
    """
    progress = pyqtSignal(int)
    file_done = pyqtSignal(str, str)
    finished = pyqtSignal()
    def __init__(self, sras: SrasFile, channels: list[ExportChannel],
                 output_dir: str, prefix: str, *, cmap: str,
                 apply_bg_sub: bool, dc_threshold_mv: float,
                 n_fft: int | None, grating_um: float,
                 min_freq_mhz: float = 0.0,
                 figsize: tuple[float, float] | None = None):
        super().__init__()
        self._sras = sras
        self._channels = channels
        self._output_dir = Path(output_dir)
        self._prefix = prefix
        self._cmap = cmap
        self._apply_bg_sub = apply_bg_sub
        self._dc_threshold_mv = dc_threshold_mv
        self._n_fft = n_fft
        self._grating_um = grating_um
        self._min_freq_mhz = min_freq_mhz
        self._figsize = figsize
    def _angle_extent(self, angle_idx: int) -> list[float]:
        s = self._sras
        x_axis = s.x_axis_mm(angle_idx)
        y_axis = s.y_positions_mm(angle_idx)
        dx = x_axis[1] - x_axis[0] if len(x_axis) > 1 else s.pixel_x_mm
        dy = float(y_axis[1] - y_axis[0]) if len(y_axis) > 1 else 1.0
        return [x_axis[0] - dx / 2, x_axis[-1] + dx / 2,
                y_axis[-1] + dy / 2, y_axis[0] - dy / 2]
    def run(self):
        try:
            s = self._sras
            n_angles = s.n_angles
            total = n_angles * len(self._channels)
            done = 0
            needs_freq = any(c.ch_idx == CH1_IDX for c in self._channels)
            for angle_idx in range(n_angles):
                if self._stop:
                    break
                extent = self._angle_extent(angle_idx)
                angle_deg = s.angles_deg[angle_idx]
                freq_mhz = None
                if needs_freq:
                    freq_mhz = compute_rf_image(
                        s, angle_idx, dc_threshold_mv=self._dc_threshold_mv,
                        apply_bg_sub=self._apply_bg_sub, n_fft=self._n_fft,
                        should_stop=self._stopped, row_avg_n=s.precomputed_row_avg_n,
                        min_freq_mhz=self._min_freq_mhz)
                for channel in self._channels:
                    if self._stop:
                        break
                    out_path = (self._output_dir
                               / f"{self._prefix}_angle{angle_idx:02d}_{channel.tag}.png")
                    try:
                        if channel.ch_idx == CH1_IDX:
                            img = (freq_mhz * self._grating_um if channel.is_velocity
                                  else freq_mhz)
                        else:
                            img = dc_image_mv(s, angle_idx, channel.ch_idx,
                                              should_stop=self._stopped)
                        title = f"{channel.tag}  |  {angle_deg:.1f}°"
                        colorbar_label = (f"{channel.label} ({channel.unit})"
                                         if channel.unit else channel.label)
                        _render_map_png(
                            img, extent, cmap=self._cmap,
                            vmin=channel.vmin, vmax=channel.vmax,
                            title=title, colorbar_label=colorbar_label,
                            out_path=str(out_path), figsize=self._figsize)
                        self.file_done.emit(str(out_path), "")
                    except Exception as exc:
                        self.file_done.emit(str(out_path), str(exc))
                    done += 1
                    self.progress.emit(int(done / max(1, total) * 100))
            self.finished.emit()
        except Exception as exc:
            self.file_done.emit("", str(exc))
            self.finished.emit()
 class BatchExportImagesWorker(QObject):
    """Renders the view settings captured by the caller at trigger time
    (angle/channel/threshold/etc.) to one PNG per file in *paths*, via
    sras_render.export_view_image.
    Same process-pool-with-inline-fallback strategy as BatchCacheWorker
    above (same _BATCH_MAX_PROCS / _BATCH_POOL_MIN_BYTES thresholds): an
    FFT-derived (CH1/Velocity) view is exactly the same expensive per-file
    compute Batch Compute FFT already parallelizes this way. Never mutates
    *paths* — each file is opened read-only — so unlike BatchCacheWorker
    there is no version gate.
    Emits progress(int) (0-100 by files completed), file_done(str, str, str)
    (path, error message or "", output filename this file targeted — set
    even on most failures so the caller can flag same-stem collisions across
    the batch without any cross-process bookkeeping), and finished().
    """
    progress = pyqtSignal(int)
    file_done = pyqtSignal(str, str, str)
    finished = pyqtSignal()
    def __init__(self, paths: list[str], **render_kwargs):
        """*render_kwargs* is exactly export_view_image's keyword-only
        settings (out_dir, angle_idx, ch_idx, is_fft_mode, is_velocity,
        dc_threshold_mv, apply_bg_sub, pad_factor, min_freq_mhz, grating_um,
        cmap, auto_scale, vmin, vmax, highlight_masked, mode_str,
        colorbar_label, mask_color) — bundled rather than repeated as
        positional params across __init__/_run_pooled/_run_inline."""
        super().__init__()
        self._paths = paths
        self._kw = render_kwargs
    def _report(self, path: str, err: str, out_name: str, done: int, total: int):
        self.file_done.emit(path, err, out_name)
        self.progress.emit(int(done / max(1, total) * 100))
    def _run_pooled(self, paths: list[str], n_procs: int) -> list[str]:
        """Same contract as BatchCacheWorker._run_pooled: returns the paths
        that never got a real answer because the pool itself died, so the
        caller can retry them in-process."""
        per_proc_workers = max(1, (os.cpu_count() or 4) // n_procs)
        unresolved: list[str] = []
        done = 0
        with ProcessPoolExecutor(max_workers=n_procs) as executor:
            futures = {
                executor.submit(export_view_image, p,
                                max_workers=per_proc_workers, **self._kw): p
                for p in paths
            }
            for fut in as_completed(futures):
                path = futures[fut]
                try:
                    err, out_name = fut.result()
                except BrokenProcessPool:
                    unresolved.append(path)
                    continue
                except Exception as exc:
                    err, out_name = str(exc), ""
                done += 1
                self._report(path, err, out_name, done, len(paths))
        return unresolved
    def _run_inline(self, paths: list[str], done: int, total: int):
        for path in paths:
            try:
                err, out_name = export_view_image(
                    path, max_workers=compute.default_max_workers(), **self._kw)
            except Exception as exc:
                err, out_name = str(exc), ""
            done += 1
            self._report(path, err, out_name, done, total)
    def _worth_pooling(self, paths: list[str]) -> bool:
        if len(paths) < 2:
            return False
        total = 0
        for p in paths:
            try:
                total += os.path.getsize(p)
            except OSError:
                pass          # unreadable files are reported by export_view_image
        return total >= _BATCH_POOL_MIN_BYTES
    def run(self):
        paths = self._paths
        n_procs = max(1, min(_BATCH_MAX_PROCS, len(paths)))
        if not self._worth_pooling(paths):
            self._run_inline(paths, 0, len(paths))
            self.finished.emit()
            return
        try:
            unresolved = self._run_pooled(paths, n_procs)
        except Exception:
            # The pool could not be created or collapsed wholesale.
            unresolved = list(paths)
        if unresolved:
            self._run_inline(unresolved, len(paths) - len(unresolved), len(paths))
        self.finished.emit()
 class Ch4MaskWorker(_PooledWorker):
    """Fetches each requested angle's CH4 (Bias B) DC image in mV, for the
    alignment wizard's initial threshold-mask stack.
    Reuses dc_image_mv, which prefers a stored v5/v7 cache over recomputing
    from raw waveforms, so this only does real work for a file that hasn't
    gone through the v7 "Convert" batch step and for angles the main
    window's own DcPrecomputeWorker (which runs automatically right after
    every file load) hasn't reached yet. In the common case — the user opens
    Fusion -> Manual Alignment after DC precompute has already finished —
    *angle_indices* is empty and this worker is never even constructed (see
    CorrelatePage._start_mask_prep).
    """
    angle_done = pyqtSignal(int, np.ndarray)   # angle_idx, dc4_mv
    def __init__(self, sras: SrasFile, angle_indices: list[int]):
        super().__init__()
        self._sras = sras
        self._angles = angle_indices
        self._budget = 0
    def _plan(self) -> int:
        n_workers, self._budget = compute.plan_angle_level(self._sras)
        return n_workers
    def _items(self):
        return self._angles
    def _one(self, a: int) -> tuple[int, np.ndarray]:
        return a, dc_image_mv(self._sras, a, CH4_IDX,
                              max_workers=1, budget=self._budget)
    def _emit(self, result):
        self.angle_done.emit(*result)
 class CrossCorrelateWorker(_PooledWorker):
    """Rigid registration (rotation + translation, never scale) of each of
    *angle_indices* against *ref_angle_idx*, for the alignment wizard's
    Run/Re-run Correlation button.
    Runs on a background thread — registering a real many-angle,
    high-resolution scan takes long enough that doing it on the GUI thread
    would visibly freeze the dialog. Rotation is *searched*, not taken from the
    stage's reported angle: see compute.register_angle_to_reference, which
    seeds from that angle but scores both of its signs and refines from there.
    dc4_mv is the dialog's own already-in-memory per-angle CH4 image — this
    worker does no fetching of its own.
    """
    # angle_idx, rotation_deg, shift_x_mm, shift_y_mm, score, source
    angle_done = pyqtSignal(int, float, float, float, float, str)
    def __init__(self, sras: SrasFile, ref_angle_idx: int, angle_indices: list[int],
                dc4_mv: dict[int, np.ndarray], *, reg_kwargs: dict | None = None):
        """*reg_kwargs* is splatted into register_angle_to_reference — every
        registration setting the wizard exposes (sources, threshold, search
        width, seed, signs, refine, grid sizes) travels in it, so this class
        holds no opinion about which knobs exist and exposing another needs no
        change here."""
        super().__init__()
        self._sras = sras
        self._ref = ref_angle_idx
        self._angles = angle_indices
        self._dc4_mv = dc4_mv
        self._reg_kwargs = dict(reg_kwargs or {})
    def _plan(self) -> int:
        return compute.registration_workers(self._sras)
    def _items(self):
        return self._angles
    def _one(self, a: int) -> tuple[int, compute.RigidFit]:
        return a, compute.register_angle_to_reference(
            self._sras, a, self._ref, self._dc4_mv, **self._reg_kwargs)
    def _emit(self, result):
        a, fit = result
        self.angle_done.emit(a, fit.rotation_deg, fit.shift_mm[0],
                             fit.shift_mm[1], fit.score, fit.source)
 class AlignedExportWorker(CancellableWorker):
    """Writes the aligned, cropped .sras on a background thread.
    Unlike every other worker here this one produces a *file*, which changes
    what cancellation has to mean: write_aligned_sras stages into a ".part"
    sibling and removes it when should_stop() fires, so a cancelled or crashed
    export leaves nothing behind. That matters more than it sounds — a
    truncated .sras is not detectably broken, since the v6 parser reads a short
    file as an aborted scan and opens it happily.
    Cancellation is polled per output row chunk, the same granularity
    CancellableWorker's docstring justifies, so closing the window never waits
    on a multi-gigabyte write.
    """
    progress = pyqtSignal(int)                  # 0-100
    finished = pyqtSignal(str, str)             # written path ("" = none), error
    def __init__(self, sras: SrasFile, result, out_path: str):
        super().__init__()
        self._sras = sras
        self._result = result
        self._out_path = out_path
    def run(self):
        try:
            written = write_aligned_sras(
                self._sras, self._result, self._out_path,
                progress_cb=self.progress.emit, should_stop=self._stopped)
            if self._stopped():
                self.finished.emit("", "")      # cancelled: no file, no error
            else:
                self.finished.emit(str(written), "")
        except Exception as exc:
            self.finished.emit("", str(exc))
@@ -0,0 +1,16 @@
 """Shared test setup: repo-root imports, the offscreen Qt platform, and
 hermetic QSettings (tests must not read or write the user's real viewer
 settings)."""
 import os
 import sys
 import tempfile
 from pathlib import Path
 os.environ.setdefault("QT_QPA_PLATFORM", "offscreen")
 sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
 from PyQt6.QtCore import QSettings  # noqa: E402
 QSettings.setPath(QSettings.Format.IniFormat, QSettings.Scope.UserScope,
                  tempfile.mkdtemp(prefix="sras_qsettings_"))
@@ -0,0 +1,646 @@
 """Aligned/cropped .sras export: does the written file actually hold the
 alignment the viewer showed?
 The export is the one place an alignment stops being a transform applied on the
 fly and becomes bytes on disk, so these tests care about two things above all:
 the file's geometry describes what was written, and the pixels in it are the
 same pixels apply_alignment would have drawn. The strongest check is the
 round-trip — register the exported file against itself and demand identity,
 which no amount of self-consistent-but-wrong index math can fake.
 No Qt: this exercises sras_align_export and sras_compute directly.
 """
 import struct
 import numpy as np
 import pytest
 import sras_align_export as export
 import sras_compute as compute
 from sras_format import CH3_IDX, CH4_IDX, HDR_SIZE_V6, SrasFile, adc_to_mv, mv_to_adc
 import tools.make_test_sras as gen
 _THRESHOLD_MV = 80.0
 # Same reasoning as tests/test_alignment.py: a quarter degree is already
 # sub-pixel for this sample at the registration pitch.
 _ROT_TOL_DEG = 0.5
 _SHIFT_TOL_MM = 0.02
 def dc_mv(sras: SrasFile, angle_idx: int, ch: int = CH4_IDX) -> np.ndarray:
    return adc_to_mv(compute.compute_dc_image(sras, angle_idx, ch), *sras.cal(ch))
@pytest.fixture(scope="module")
 def rig(tmp_path_factory):
    """The rotating-sample scan, its truth alignment, and its export."""
    tmpdir = tmp_path_factory.mktemp("sras_export")
    src_path = tmpdir / "rotating.sras"
    meta = gen.write_rotating(src_path, n_angles=4)
    sras = SrasFile(str(src_path))
    params = {a: compute.ManualAngleParams(rot, shift)
              for a, (rot, shift) in meta["truth"].items()}
    result = compute.build_manual_alignment(sras, 0, _THRESHOLD_MV, params)
    out_path = tmpdir / "rotating_aligned.sras"
    export.write_aligned_sras(sras, result, out_path)
    return type("Rig", (), dict(
        tmpdir=tmpdir, src_path=src_path, sras=sras, meta=meta,
        result=result, out_path=out_path, out=SrasFile(str(out_path))))
 # ---------------------------------------------------------------------------
 # Geometry and file structure
 # ---------------------------------------------------------------------------
 def test_output_is_v6_with_uniform_geometry(rig):
    out, result = rig.out, rig.result
    n_rows, n_cols = result.canvas_shape
    assert out.version == 6
    assert out.n_angles == rig.sras.n_angles
    assert set(out.n_rows) == {n_rows}, "every angle must share the canvas rows"
    assert set(out.n_frames) == {n_cols}, "every angle must share the canvas frames"
    assert np.allclose(out.x_start_mm, result.canvas_origin_mm[0])
    # x_delta must stay velocity/laser_freq or x_axis_mm() contradicts the
    # geometry table; the canvas pitch is the reference angle's own pitch, so
    # this is exact rather than approximate.
    assert np.allclose(out.x_delta_mm_per_angle, rig.sras.pixel_x_mm)
    assert out.pixel_x_mm == pytest.approx(rig.sras.pixel_x_mm)
 def test_row_table_matches_the_canvas(rig):
    expected = (rig.result.canvas_origin_mm[1]
                + np.arange(rig.result.canvas_shape[0]) * rig.result.canvas_dy_mm)
    for a in range(rig.out.n_angles):
        assert rig.out.y_positions_mm(a) == pytest.approx(expected, abs=1e-4)
 def test_angle_table_and_calibration_round_trip(rig):
    assert rig.out.angles_deg == pytest.approx(rig.sras.angles_deg)
    for ch in range(rig.sras.n_channels):
        assert rig.out.cal(ch) == pytest.approx(rig.sras.cal(ch))
    assert rig.out.samples_per_frame == rig.sras.samples_per_frame
    assert rig.out.bytes_per_sample == rig.sras.bytes_per_sample
    assert rig.out.n_channels == rig.sras.n_channels
    assert rig.out.background == pytest.approx(rig.sras.background)
 def test_no_cache_tail(rig):
    """File ends exactly at the waveform data — nothing trailing.
    A stale cache tail would be indexed by the *input's* grid, so the export
    must not carry one; asserting on the exact file size is what proves it,
    since a v7 tail would simply be ignored by a v6 parser.
    """
    end = max(off + n for _, off, n in rig.out.iter_angle_blocks())
    assert rig.out_path.stat().st_size == end
    assert all(img is None for img in rig.out.precomputed_dc4_mv)
 def test_declared_header_size_is_v6(rig):
    raw = rig.out_path.read_bytes()[:HDR_SIZE_V6]
    magic, version, n_angles = struct.unpack(">4sBH", raw[:7])
    assert (magic, version, n_angles) == (b"SRAS", 6, rig.sras.n_angles)
 # ---------------------------------------------------------------------------
 # The pixels themselves
 # ---------------------------------------------------------------------------
 def test_export_matches_apply_alignment(rig):
    """The exported waveforms decode to the same DC image the viewer drew —
    over the *whole* canvas, padding included.
    Two rules have to be exactly right for this, and each fails differently:
      * rounding must be floor(x + 0.5), not np.rint, or pixels on exact
        half-integer boundaries pick the neighbouring source pixel;
      * out-of-bounds must be tested on the fractional coordinate against
        [0, n-1], not on the rounded index, or a one-pixel rim gets real data
        where the preview shows padding.
    Comparing every pixel rather than only the interior is what catches the
    second one, since a rim discrepancy hides inside a `preview != 0` mask.
    """
    for a in range(rig.sras.n_angles):
        preview = compute.apply_alignment(rig.result, a, dc_mv(rig.sras, a))
        actual = dc_mv(rig.out, a)
        assert actual.shape == preview.shape
        # Padding matches to within half an ADC step: apply_alignment pads with
        # literal 0.0 mV, the export with the nearest integer ADC code to 0 mV.
        tol = abs(rig.sras.cal(CH4_IDX)[0]) / 2.0 + 1e-4
        # Exclude the epsilon rim the export deliberately keeps and scipy drops
        # (see test_edge_tolerance_only_affects_the_epsilon_rim).
        sr, sc = export._src_coords(rig.result.per_angle[a],
                                    np.arange(preview.shape[0]), preview.shape[1])
        rim = export._in_bounds(sr, sc, *rig.sras.image_shape(a)) & (preview == 0.0)
        cmp = ~rim
        assert actual[cmp] == pytest.approx(preview[cmp], abs=tol), \
            f"angle {a}: exported pixels differ from the aligned preview"
        # And exactly, wherever there is real data.
        inside = (preview != 0.0)
        assert inside.any(), f"angle {a}: preview is entirely padding"
        assert actual[inside] == pytest.approx(preview[inside], abs=1e-6), \
            f"angle {a}: exported data pixels are not bit-equal to the preview"
 def test_reference_angle_is_exported_whole(rig):
    """The reference angle must survive as a complete, exact integer crop.
    It is the coordinate authority — its transform is the identity with an
    integer offset by construction — so every one of its source pixels has to
    appear in the export. This is what _EDGE_TOL exists for: that offset comes
    out of the mm-space affine chain as -20 - 7e-15, and a bare `>= 0` bounds
    test silently drops the angle's entire first row and last column.
    """
    ref = rig.result.ref_angle_idx
    src_rows, src_frames = rig.sras.image_shape(ref)
    plan = export.plan_export(rig.sras, rig.result)
    assert plan.valid_px[ref] == src_rows * src_frames, \
        "reference angle lost pixels to the in-bounds test"
    # And the values themselves land as an exact, unrotated block.
    src_img = dc_mv(rig.sras, ref)
    out_img = dc_mv(rig.out, ref)
    t = rig.result.per_angle[ref]
    row0, col0 = (int(round(-t.offset[0])), int(round(-t.offset[1])))
    assert np.array_equal(out_img[row0:row0 + src_rows, col0:col0 + src_frames],
                          src_img), \
        "reference angle is not a verbatim block in the export"
 def test_edge_tolerance_only_affects_the_epsilon_rim(rig):
    """Where the export's bounds test and scipy's disagree, the coordinate must
    be within _EDGE_TOL of the boundary — i.e. only pixels whose scipy answer
    was itself decided by float noise, never a real half-pixel decision."""
    for a in range(rig.sras.n_angles):
        t = rig.result.per_angle[a]
        src_rows, src_frames = rig.sras.image_shape(a)
        n_rows, n_cols = rig.result.canvas_shape
        ones = np.ones((src_rows, src_frames), dtype=np.float32)
        scipy_valid = compute.apply_alignment(rig.result, a, ones) > 0.5
        sr, sc = export._src_coords(t, np.arange(n_rows), n_cols)
        ours = export._in_bounds(sr, sc, src_rows, src_frames)
        differ = ours != scipy_valid
        assert not (scipy_valid & ~ours).any(), \
            f"angle {a}: export drops pixels scipy keeps"
        if differ.any():
            # Every disagreement sits within the tolerance of an edge.
            near = (np.abs(sr) <= export._EDGE_TOL)
            near |= (np.abs(sr - (src_rows - 1)) <= export._EDGE_TOL)
            near |= (np.abs(sc) <= export._EDGE_TOL)
            near |= (np.abs(sc - (src_frames - 1)) <= export._EDGE_TOL)
            assert near[differ].all(), \
                f"angle {a}: bounds differ away from the epsilon rim"
 def test_export_matches_apply_alignment_on_ch3(rig):
    """Channel-agnostic: the gather moves whole pixels, not per-channel images."""
    for a in range(rig.sras.n_angles):
        preview = compute.apply_alignment(rig.result, a,
                                          dc_mv(rig.sras, a, CH3_IDX))
        actual = dc_mv(rig.out, a, CH3_IDX)
        inside = preview != 0.0
        assert actual[inside] == pytest.approx(preview[inside], abs=1e-3)
 def test_padding_is_zero_mv_not_zero_adc(rig):
    """Unreachable canvas pixels must read as ~0 mV on every channel.
    Filling with literal zero ADC would decode to (0 - yoff) * ymult + yzero —
    for this fixture's CH4 calibration that is +100 mV, well above any sensible
    mask threshold, so the padding would masquerade as valid sample everywhere.
    """
    a = rig.sras.n_angles - 1
    t = rig.result.per_angle[a]
    n_rows, n_cols = rig.result.canvas_shape
    src_rows, src_frames = rig.sras.image_shape(a)
    sr, sc = export._src_coords(t, np.arange(n_rows), n_cols)
    outside = ~export._in_bounds(sr, sc, src_rows, src_frames)
    assert outside.any(), "rotated angle should leave unreachable canvas corners"
    for ch in (CH3_IDX, CH4_IDX):
        img = dc_mv(rig.out, a, ch)
        half_step = abs(rig.sras.cal(ch)[0]) / 2.0
        assert np.abs(img[outside]).max() <= half_step + 1e-6, \
            f"CH{ch} padding is not within half an ADC step of 0 mV"
    # And the sanity check that makes the above meaningful: zero ADC would not
    # have passed it.
    assert abs(adc_to_mv(0, *rig.sras.cal(CH4_IDX))) > 10.0
 def test_reregistering_the_export_is_identity(rig):
    """The export really is aligned: registering it against its own angle 0
    recovers no rotation and no shift.
    The end-to-end check — it fails for any index error, sign flip, wrong pivot
    or origin mistake anywhere in crop/affine/gather, in a way the
    self-consistency tests above cannot.
    """
    dc4 = {a: dc_mv(rig.out, a) for a in range(rig.out.n_angles)}
    for a in range(1, rig.out.n_angles):
        fit = compute.register_angle_to_reference(
            rig.out, a, 0, dc4, dc_threshold_mv=_THRESHOLD_MV,
            seed_deg=0.0, seed_signs=(1,))
        assert abs(fit.rotation_deg) <= _ROT_TOL_DEG, \
            f"angle {a} still rotated by {fit.rotation_deg:.3f}° after export"
        assert float(np.hypot(*fit.shift_mm)) <= _SHIFT_TOL_MM, \
            f"angle {a} still shifted by {fit.shift_mm} mm after export"
 def test_export_of_int16_input(rig, tmp_path):
    """bps=2 inputs keep their big-endian int16 dtype through the gather."""
    src_path = tmp_path / "i16.sras"
    gen.write(src_path, n_angles=2, samples_per_frame=16, bps=2)
    sras = SrasFile(str(src_path))
    result = compute.build_manual_alignment(sras, 0, 0.0, {})
    out_path = tmp_path / "i16_aligned.sras"
    export.write_aligned_sras(sras, result, out_path)
    out = SrasFile(str(out_path))
    assert out.bytes_per_sample == 2
    assert out.data[0].dtype == np.dtype(">i2")
    for a in range(sras.n_angles):
        preview = compute.apply_alignment(result, a, dc_mv(sras, a))
        actual = dc_mv(out, a)
        inside = preview != 0.0
        assert actual[inside] == pytest.approx(preview[inside], abs=1e-3)
 # ---------------------------------------------------------------------------
 # Cropping
 # ---------------------------------------------------------------------------
 def test_crop_is_a_window_of_the_full_canvas(rig):
    """crop_alignment_result must resample exactly the sub-rectangle it names.
    Asserted as bit-exact equality, not approximately: the crop composes into
    the affine's offset by an integer number of canvas pixels, so anything but
    an exact match means the composition is wrong.
    """
    n_rows, n_cols = rig.result.canvas_shape
    row0, col0 = n_rows // 5, n_cols // 4
    nr, nc = n_rows // 2, n_cols // 3
    cropped = compute.crop_alignment_result(rig.result, row0, col0, nr, nc)
    assert cropped.canvas_shape == (nr, nc)
    assert cropped.canvas_origin_mm[0] == pytest.approx(
        rig.result.canvas_origin_mm[0] + col0 * rig.result.canvas_dx_mm)
    assert cropped.canvas_origin_mm[1] == pytest.approx(
        rig.result.canvas_origin_mm[1] + row0 * rig.result.canvas_dy_mm)
    for a in range(rig.sras.n_angles):
        img = dc_mv(rig.sras, a)
        full = compute.apply_alignment(rig.result, a, img)
        assert np.array_equal(
            compute.apply_alignment(cropped, a, img),
            full[row0:row0 + nr, col0:col0 + nc]), \
            f"angle {a}: cropped resample is not the same window"
        # Rotation/shift are properties of the angle, not of the canvas.
        assert cropped.per_angle[a].rotation_deg == rig.result.per_angle[a].rotation_deg
        assert cropped.per_angle[a].shift_mm == rig.result.per_angle[a].shift_mm
 def test_cropped_export_round_trips(rig, tmp_path):
    n_rows, n_cols = rig.result.canvas_shape
    row0, col0, nr, nc = n_rows // 4, n_cols // 4, n_rows // 2, n_cols // 2
    cropped = compute.crop_alignment_result(rig.result, row0, col0, nr, nc)
    out_path = tmp_path / "cropped.sras"
    export.write_aligned_sras(rig.sras, cropped, out_path)
    out = SrasFile(str(out_path))
    assert set(out.n_rows) == {nr} and set(out.n_frames) == {nc}
    assert out.x_start_mm[0] == pytest.approx(cropped.canvas_origin_mm[0], abs=1e-4)
    for a in range(rig.sras.n_angles):
        preview = compute.apply_alignment(cropped, a, dc_mv(rig.sras, a))
        actual = dc_mv(out, a)
        inside = preview != 0.0
        if inside.any():
            assert actual[inside] == pytest.approx(preview[inside], abs=1e-3)
 def test_crop_rejects_empty_window(rig):
    with pytest.raises(ValueError, match="empty crop"):
        compute.crop_alignment_result(rig.result, 0, 0, 0, 10)
    with pytest.raises(ValueError, match="empty crop"):
        compute.crop_alignment_result(rig.result, 0, 0, 10, -1)
 # ---------------------------------------------------------------------------
 # plan_export and overlap_stats
 # ---------------------------------------------------------------------------
 def test_plan_export_matches_what_was_written(rig):
    plan = export.plan_export(rig.sras, rig.result)
    n_rows, n_cols = rig.result.canvas_shape
    assert (plan.n_rows, plan.n_frames) == (n_rows, n_cols)
    assert plan.n_angles == rig.sras.n_angles
    data_bytes = sum(n for _, _, n in rig.out.iter_angle_blocks())
    assert plan.total_bytes == data_bytes
    assert plan.bytes_per_angle * plan.n_angles == plan.total_bytes
    # Coverage must agree with the pixels that actually carry data. The
    # reference angle is unrotated, so its whole footprint lands inside.
    ref_px = np.prod(rig.sras.image_shape(0))
    assert plan.valid_px[0] == ref_px
    for a in range(1, rig.sras.n_angles):
        assert 0 < plan.valid_px[a] <= n_rows * n_cols
        assert 0.0 < plan.coverage_frac(a) < 1.0
 def test_plan_export_flags_a_crop_that_misses_an_angle(rig):
    """A crop over a corner the rotated angles cannot reach must warn, and the
    export must still succeed by writing that angle as padding."""
    n_rows, n_cols = rig.result.canvas_shape
    corner = compute.crop_alignment_result(rig.result, 0, 0,
                                           max(1, n_rows // 12),
                                           max(1, n_cols // 12))
    plan = export.plan_export(rig.sras, corner)
    empty = [a for a in range(rig.sras.n_angles) if plan.valid_px[a] == 0]
    assert empty, "top-left canvas corner should be unreachable for some angle"
    assert any("all padding" in w for w in plan.warnings)
 def test_overlap_stats():
    counts = np.array([[0, 1, 2], [3, 3, 0], [0, 2, 3]])
    stats = compute.overlap_stats(counts, 3)
    assert stats["union_px"] == 6
    assert stats["full_px"] == 3
    assert stats["full_frac"] == pytest.approx(0.5)
    assert stats["max_count"] == 3
    assert stats["mean_count"] == pytest.approx((1 + 2 + 3 + 3 + 2 + 3) / 6)
    assert stats["empty"] is False
    empty = compute.overlap_stats(np.zeros((4, 4), dtype=int), 3)
    assert empty["empty"] is True
    assert empty["full_frac"] == 0.0 and empty["mean_count"] == 0.0
 def test_largest_rect_at_least():
    # A 2x3 block of 3s with a notch that a bounding box would swallow.
    counts = np.array([
        [0, 0, 0, 0, 0],
        [0, 3, 3, 3, 0],
        [0, 3, 3, 3, 0],
        [0, 3, 0, 3, 0],
    ])
    row0, col0, nr, nc = compute.largest_rect_at_least(counts, 3)
    assert (nr * nc) == 6 and (row0, col0, nr, nc) == (1, 1, 2, 3)
    assert (counts[row0:row0 + nr, col0:col0 + nc] >= 3).all()
    # A column taller than the wide block is the better rectangle.
    tall = np.array([[3, 3], [3, 0], [3, 0], [3, 0]])
    r0, c0, nr2, nc2 = compute.largest_rect_at_least(tall, 3)
    assert (r0, c0, nr2, nc2) == (0, 0, 4, 1)
    assert compute.largest_rect_at_least(np.zeros((3, 3), dtype=int), 1) is None
    # Whole-array case: no notch, so the answer is the array itself.
    assert compute.largest_rect_at_least(np.full((3, 4), 2), 2) == (0, 0, 3, 4)
 def test_largest_rect_matches_brute_force():
    """Randomized check against an O(n^4) reference.
    The histogram sweep is short and easy to get subtly wrong — an off-by-one in
    the stack unwind yields rectangles that are merely large, and "large but not
    maximal" is invisible by eye on real data.
    """
    def brute(good):
        n_rows, n_cols = good.shape
        best = 0
        for r0 in range(n_rows):
            for r1 in range(r0 + 1, n_rows + 1):
                run = 0
                for g in good[r0:r1].all(axis=0):
                    run = run + 1 if g else 0
                    best = max(best, run * (r1 - r0))
        return best
    rng = np.random.default_rng(0)
    for _ in range(200):
        counts = rng.integers(0, 3, size=(int(rng.integers(1, 9)),
                                          int(rng.integers(1, 9))))
        got = compute.largest_rect_at_least(counts, 2)
        expected = brute(counts >= 2)
        if got is None:
            assert expected == 0
            continue
        row0, col0, nr, nc = got
        assert (counts[row0:row0 + nr, col0:col0 + nc] >= 2).all(), \
            f"rectangle is not pure:\n{counts}\n{got}"
        assert nr * nc == expected, \
            f"not maximal ({nr * nc} < {expected}):\n{counts}\n{got}"
 def test_largest_rect_is_pure_on_the_real_fixture(rig):
    """On real overlap counts the returned rectangle must contain only
    full-overlap pixels — the property a bounding box would violate."""
    n = rig.sras.n_angles
    masks = {a: (dc_mv(rig.sras, a) >= _THRESHOLD_MV).astype(np.float32)
             for a in range(n)}
    counts = sum(compute.apply_alignment(rig.result, a, masks[a]) > 0.5
                 for a in range(n)).astype(int)
    assert counts.max() == n, "fixture alignment should have a full-overlap region"
    rect = compute.largest_rect_at_least(counts, n)
    assert rect is not None
    row0, col0, nr, nc = rect
    assert (counts[row0:row0 + nr, col0:col0 + nc] == n).all(), \
        "convenience crop must not include pixels some angle misses"
    # And it must beat the naive bounding box, which here is impure.
    rr, cc = np.nonzero(counts == n)
    bbox_pure = (counts[rr.min():rr.max() + 1, cc.min():cc.max() + 1] == n).all()
    assert not bbox_pure, "fixture no longer exercises the bounding-box hazard"
 # ---------------------------------------------------------------------------
 # Legacy inputs, validation and durability
 # ---------------------------------------------------------------------------
@pytest.mark.parametrize("version", [2, 4])
 def test_legacy_input_exports_as_v6(version, tmp_path):
    """v2-v5 inputs keep no verbatim preamble/background spans, so those
    sections have to be re-encoded. v2 additionally has neither."""
    src_path = tmp_path / f"legacy_v{version}.sras"
    gen.write_legacy(src_path, version=version, n_angles=2)
    sras = SrasFile(str(src_path))
    result = compute.build_manual_alignment(sras, 0, 0.0, {})
    out_path = tmp_path / f"legacy_v{version}_aligned.sras"
    export.write_aligned_sras(sras, result, out_path)
    out = SrasFile(str(out_path))
    assert out.version == 6
    assert out.n_angles == sras.n_angles
    # A zero background rather than a zero-length one: consumers subtract it
    # from a (spf,)-shaped row, which a length-0 array cannot broadcast against.
    assert out.background is not None
    assert out.background.size == sras.samples_per_frame
    if sras.background is None:
        assert np.all(out.background == 0)
        assert any("no background" in w for w in
                   export.plan_export(sras, result).warnings)
    # Calibration must survive: v2 has no preambles and falls back to the
    # hardcoded scope constants, and the re-encoded empty preambles must land on
    # exactly the same fallback.
    for ch in range(sras.n_channels):
        assert out.cal(ch) == pytest.approx(sras.cal(ch))
    for a in range(sras.n_angles):
        preview = compute.apply_alignment(result, a, dc_mv(sras, a))
        actual = dc_mv(out, a)
        inside = preview != 0.0
        assert actual[inside] == pytest.approx(preview[inside], abs=1e-3)
 def test_too_many_rows_is_rejected_before_writing(rig, tmp_path):
    """The geometry table stores n_rows as a u16; silently truncating would
    write a file whose header disagrees with its own waveform block."""
    huge = compute.crop_alignment_result(rig.result, 0, 0, 70000, 4)
    out_path = tmp_path / "huge.sras"
    with pytest.raises(ValueError, match="exceeds the .sras per-angle geometry"):
        export.write_aligned_sras(rig.sras, huge, out_path)
    assert not out_path.exists()
    assert not out_path.with_name(out_path.name + ".part").exists()
 def test_missing_transform_is_rejected(rig, tmp_path):
    broken = compute.crop_alignment_result(rig.result, 0, 0,
                                           *rig.result.canvas_shape)
    del broken.per_angle[1]
    with pytest.raises(ValueError, match="no transform for angle"):
        export.write_aligned_sras(rig.sras, broken, tmp_path / "broken.sras")
 def test_cancelled_export_leaves_nothing_behind(rig, tmp_path):
    out_path = tmp_path / "cancelled.sras"
    written = export.write_aligned_sras(rig.sras, rig.result, out_path,
                                        should_stop=lambda: True)
    assert written == out_path
    assert not out_path.exists(), "cancelled export must not leave an output file"
    assert not out_path.with_name(out_path.name + ".part").exists()
 def test_failed_write_leaves_nothing_behind(rig, tmp_path):
    """An exception mid-write must remove the partial file: a short .sras is
    not detectably broken — the v6 parser reads it as an aborted scan."""
    out_path = tmp_path / "boom.sras"
    def explode(_pct):
        raise RuntimeError("boom")
    with pytest.raises(RuntimeError, match="boom"):
        export.write_aligned_sras(rig.sras, rig.result, out_path,
                                  progress_cb=explode)
    assert not out_path.exists()
    assert not out_path.with_name(out_path.name + ".part").exists()
 def test_progress_is_monotonic_and_completes(rig, tmp_path):
    seen: list[int] = []
    export.write_aligned_sras(rig.sras, rig.result, tmp_path / "prog.sras",
                              progress_cb=seen.append)
    assert seen and seen[-1] == 100
    assert seen == sorted(seen)
    assert all(0 <= p <= 100 for p in seen)
 def test_band_reader_path_is_byte_identical(rig, tmp_path, monkeypatch):
    """A source block too large to hold in RAM is served from sliding bands
    instead. That path only runs on multi-gigabyte scans, so force it with a
    tiny budget and demand the same bytes — otherwise the one code path that
    matters on real data is the one never tested."""
    whole = tmp_path / "whole.sras"
    export.write_aligned_sras(rig.sras, rig.result, whole)
    monkeypatch.setattr(compute, "_TOTAL_BYTES_BUDGET", 4096)
    banded = tmp_path / "banded.sras"
    export.write_aligned_sras(rig.sras, rig.result, banded)
    assert banded.read_bytes() == whole.read_bytes()
 def test_row_chunking_is_invariant(rig, tmp_path, monkeypatch):
    """Output must not depend on how many rows are buffered per write."""
    base = tmp_path / "base.sras"
    export.write_aligned_sras(rig.sras, rig.result, base)
    monkeypatch.setattr(export, "_ROW_CHUNK", 1)
    one = tmp_path / "one.sras"
    export.write_aligned_sras(rig.sras, rig.result, one)
    assert one.read_bytes() == base.read_bytes()
 def test_refuses_to_overwrite_the_source(rig):
    """The source's waveform blocks are live read-only memmaps; writing over
    the file would corrupt the reads the gather is making from it."""
    with pytest.raises(ValueError, match="refusing to export onto the source"):
        export.write_aligned_sras(rig.sras, rig.result, rig.src_path)
    assert SrasFile(str(rig.src_path)).n_angles == rig.sras.n_angles
 def test_overwrites_an_existing_file(rig, tmp_path):
    out_path = tmp_path / "existing.sras"
    out_path.write_bytes(b"not a scan")
    export.write_aligned_sras(rig.sras, rig.result, out_path)
    assert SrasFile(str(out_path)).version == 6
 # ---------------------------------------------------------------------------
 # The registration knobs the wizard exposes
 # ---------------------------------------------------------------------------
 def test_locked_rotation_returns_exactly_the_seed(rig):
    """search_deg=0 + one sign + refine=False pins rotation to the seed, which
    is what "lock rotation to the stage angle" means on the wizard's first
    page. Only the translation may be searched."""
    dc4 = {a: dc_mv(rig.sras, a) for a in range(rig.sras.n_angles)}
    for a in range(1, rig.sras.n_angles):
        nominal = compute.nominal_delta_deg(rig.sras, a, 0)
        fit = compute.register_angle_to_reference(
            rig.sras, a, 0, dc4, dc_threshold_mv=_THRESHOLD_MV,
            search_deg=0.0, coarse_step_deg=2.0, seed_signs=(-1,), refine=False)
        assert fit.rotation_deg == pytest.approx(-nominal)
 def test_seed_deg_overrides_the_stage_angle(rig):
    """seed_deg=0.0 searches around no rotation at all, so a scan whose angles
    are genuinely ~37° apart must fail to find them within a ±2° window —
    proving the seed is what positions the search."""
    dc4 = {a: dc_mv(rig.sras, a) for a in range(rig.sras.n_angles)}
    fit = compute.register_angle_to_reference(
        rig.sras, 1, 0, dc4, dc_threshold_mv=_THRESHOLD_MV,
        search_deg=2.0, seed_deg=0.0, seed_signs=(1,), refine=False)
    truth_rot = rig.meta["truth"][1][0]
    assert abs(fit.rotation_deg) <= 2.0
    assert abs(fit.rotation_deg - truth_rot) > 10.0
 def test_rotation_candidates_signs():
    both = compute._rotation_candidates(10.0, 2.0, 2.0)
    assert both == compute._rotation_candidates(10.0, 2.0, 2.0, (-1, 1)), \
        "default must stay the both-signs sweep"
    assert compute._rotation_candidates(10.0, 0.0, 2.0, (1,)) == [10.0]
    assert compute._rotation_candidates(10.0, 0.0, 2.0, (-1,)) == [-10.0]
    # A zero seed collapses the two windows; the dedupe must keep one copy.
    assert compute._rotation_candidates(0.0, 2.0, 2.0) == [-2.0, 0.0, 2.0]
 def test_zero_mv_fill_code_is_clipped_to_dtype():
    """mv_to_adc is unclamped, so the fill code must be clipped or the int8
    cast wraps around to a large-magnitude value."""
    fake = type("S", (), dict(
        n_channels=1, samples_per_frame=2,
        cal=lambda self, ch: (1e-6, 0.0, 5000.0)))()
    row = export._fill_row(fake, 3, np.dtype(np.int8))
    assert row.shape == (1, 3, 2)
    assert row.min() == row.max() == np.iinfo(np.int8).min
    assert mv_to_adc(0.0, 1e-6, 0.0, 5000.0) < np.iinfo(np.int8).min
@@ -0,0 +1,212 @@
 """Angle-alignment tests: does registration actually stack the scans?
 Builds a synthetic scan in which one sample is imaged at several *known*
 rotations and offsets (tools/make_test_sras.write_rotating) and checks that the
 alignment path recovers them, that the shared canvas is angle 0's own pixel
 grid extended, and that nothing in the result depends on any other angle's
 stage coordinates.
 No Qt — this exercises sras_compute directly. See tests/test_gui.py for the
 dialog and Aligned-View plumbing.
 """
 from types import SimpleNamespace
 import numpy as np
 import pytest
 import sras_compute as compute
 from sras_format import CH4_IDX, SrasFile, adc_to_mv
 import tools.make_test_sras as gen
 # Registration is limited by how far a feature moves per degree: with this
 # sample's ~1 mm radius and a ~16 µm registration pitch, a quarter degree is
 # already sub-pixel, so it is the floor of what any metric can resolve here.
 _ROT_TOL_DEG = 0.5
 _SHIFT_TOL_MM = 0.02
 _STACK_IOU_MIN = 0.90
 _THRESHOLD_MV = 80.0
 def dc4_images(sras: SrasFile) -> dict[int, np.ndarray]:
    return {a: adc_to_mv(compute.compute_dc_image(sras, a, CH4_IDX), *sras.cal(CH4_IDX))
            for a in range(sras.n_angles)}
 def mm_transform(sras: SrasFile, result, angle_idx: int) -> np.ndarray:
    """Recover the pure mm-space rotation from a canvas->raw affine.
    matrix == D @ R^T @ A_out, where A_out and D only carry the canvas and
    per-angle pixel pitches; undoing both must leave something orthonormal, or
    the transform is smuggling in a scale or a shear.
    """
    dx_a, dy_a = compute.pixel_pitch_mm(sras, angle_idx)
    A_out = np.array([[0.0, result.canvas_dx_mm], [result.canvas_dy_mm, 0.0]])
    D = np.array([[0.0, 1.0 / dy_a], [1.0 / dx_a, 0.0]])
    return np.linalg.inv(D) @ result.per_angle[angle_idx].matrix @ np.linalg.inv(A_out)
@pytest.fixture(scope="module")
 def rig(tmp_path_factory):
    """The rotating-sample scan plus everything computed from it once."""
    tmpdir = tmp_path_factory.mktemp("sras_align")
    path = tmpdir / "rotating.sras"
    meta = gen.write_rotating(path, n_angles=5)
    sras = SrasFile(str(path))
    dc4 = dc4_images(sras)
    fits = {a: compute.register_angle_to_reference(
                sras, a, 0, dc4, dc_threshold_mv=_THRESHOLD_MV)
            for a in range(sras.n_angles)}
    result = compute.compute_angle_alignment(sras, 0, _THRESHOLD_MV)
    return SimpleNamespace(path=path, sras=sras, truth=meta["truth"],
                           dc4=dc4, fits=fits, result=result)
 def test_registration_recovers_truth(rig):
    """Per-angle rigid registration (rotation + translation, no scale)."""
    for a, fit in rig.fits.items():
        t_rot, t_shift = rig.truth[a]
        rot_err = abs(fit.rotation_deg - t_rot)
        shift_err = float(np.hypot(fit.shift_mm[0] - t_shift[0],
                                   fit.shift_mm[1] - t_shift[1]))
        assert rot_err <= _ROT_TOL_DEG, \
            (f"angle {a}: got {fit.rotation_deg:.3f}°, truth {t_rot:.3f}° "
             f"(err {rot_err:.3f}°)")
        assert shift_err <= _SHIFT_TOL_MM, f"angle {a}: err {shift_err:.4f} mm"
    assert rig.fits[0] == compute.RigidFit(0.0, (0.0, 0.0), 1.0, "reference"), \
        "reference angle registers as exact identity"
 def test_stage_angle_sign_is_not_trusted(rig):
    # The stage's rotational sense relative to this module's math-positive
    # convention is not knowable from the file, and the old code hardcoded a
    # guess. Flipping every reported angle must therefore change nothing: the
    # search scores both signs and the images decide.
    flipped = SrasFile(str(rig.path))
    flipped.angles_deg = -flipped.angles_deg
    flipped_fits = {a: compute.register_angle_to_reference(
                        flipped, a, 0, rig.dc4, dc_threshold_mv=_THRESHOLD_MV)
                    for a in range(1, flipped.n_angles)}
    mismatches = {a: (flipped_fits[a].rotation_deg, rig.fits[a].rotation_deg)
                  for a in flipped_fits if flipped_fits[a] != rig.fits[a]}
    assert not mismatches, \
        f"negating every reported stage angle changed fits: {mismatches}"
 def test_stage_coordinates_are_not_consulted(rig):
    # Move every non-reference angle's scan window somewhere else entirely.
    # Only angle 0's coordinates may matter, so every fit must be untouched.
    moved = SrasFile(str(rig.path))
    for a in range(1, moved.n_angles):
        moved.x_start_mm[a] += 13.5 * a
        moved.y_pos_per_angle[a] = moved.y_pos_per_angle[a] - 9.25 * a
    moved_dc4 = dc4_images(moved)
    moved_fits = {a: compute.register_angle_to_reference(
                      moved, a, 0, moved_dc4, dc_threshold_mv=_THRESHOLD_MV)
                  for a in range(1, moved.n_angles)}
    mismatches = {a: (round(moved_fits[a].rotation_deg, 4), rig.fits[a].rotation_deg)
                  for a in moved_fits if moved_fits[a] != rig.fits[a]}
    assert not mismatches, \
        f"relocating every other angle's scan window changed fits: {mismatches}"
 def test_canvas_is_reference_grid_extended(rig):
    sras, result = rig.sras, rig.result
    t0 = result.per_angle[0]
    assert np.allclose(t0.matrix, np.eye(2)), \
        f"angle 0's transform has rotation/scale/shear: {t0.matrix}"
    assert np.allclose(t0.offset, np.round(t0.offset)), \
        f"angle 0 does not land on whole canvas pixels: {t0.offset}"
    assert ((result.canvas_dx_mm, result.canvas_dy_mm)
            == compute.pixel_pitch_mm(sras, 0)), \
        "canvas pitch is angle 0's own pitch"
    n_rows, n_cols = result.canvas_shape
    x_axis = result.canvas_origin_mm[0] + np.arange(n_cols) * result.canvas_dx_mm
    y_axis = result.canvas_origin_mm[1] + np.arange(n_rows) * result.canvas_dy_mm
    row0, col0 = int(round(-t0.offset[0])), int(round(-t0.offset[1]))
    a0_rows, a0_cols = sras.image_shape(0)
    assert np.allclose(x_axis[col0:col0 + a0_cols], sras.x_axis_mm(0)), \
        "canvas X axis reproduces angle 0's own X coordinates"
    assert np.allclose(y_axis[row0:row0 + a0_rows], sras.y_positions_mm(0)), \
        "canvas Y axis reproduces angle 0's own Y coordinates"
    assert (n_rows >= max(int(sras.n_rows[a]) for a in range(sras.n_angles))
            and n_cols >= max(int(sras.n_frames[a]) for a in range(sras.n_angles))), \
        f"canvas does not cover every angle's footprint: {result.canvas_shape}"
 def test_transforms_are_pure_rotations(rig):
    """No scaling anywhere in the per-angle transforms."""
    for a in range(rig.sras.n_angles):
        R = mm_transform(rig.sras, rig.result, a)
        assert (np.allclose(R @ R.T, np.eye(2), atol=1e-9)
                and abs(abs(np.linalg.det(R)) - 1.0) < 1e-9), \
            f"angle {a}: det={np.linalg.det(R):.6f}"
 def test_all_angles_stack(rig):
    aligned = {a: compute.apply_alignment(rig.result, a, rig.dc4[a])
               for a in range(rig.sras.n_angles)}
    base = aligned[0] >= _THRESHOLD_MV
    for a in range(1, rig.sras.n_angles):
        other = aligned[a] >= _THRESHOLD_MV
        iou = float((base & other).sum()) / max(1, int((base | other).sum()))
        assert iou >= _STACK_IOU_MIN, f"angle {a}: IoU {iou:.4f}"
 def test_downsampled_preview_lands_with_full_res(rig):
    # The wizard reprojects block-mean-downsampled masks, so the
    # affine has to account for the factor. When it did not, every preview
    # layer came out magnified by that factor and offset — the overlay showed a
    # blown-up crop of each mask, which is not something you can align by eye.
    sras, result = rig.sras, rig.result
    pitch = (result.canvas_dx_mm, result.canvas_dy_mm)
    a = sras.n_angles - 1
    p = result.per_angle[a]
    full_mask = (rig.dc4[a] >= _THRESHOLD_MV).astype(np.float32)
    full = compute.reproject_mask(
        sras, a, 0, full_mask, p.rotation_deg, p.shift_mm, pitch,
        result.canvas_origin_mm, result.canvas_shape)
    fy, fx = 4, 16
    small = compute.reproject_mask(
        sras, a, 0, compute.block_mean_2d(full_mask, fy, fx),
        p.rotation_deg, p.shift_mm, (pitch[0] * fx, pitch[1] * fy),
        result.canvas_origin_mm,
        (result.canvas_shape[0] // fy, result.canvas_shape[1] // fx),
        src_downsample=(fy, fx))
    # Compare in mm, via each layer's own center of mass.
    def com_mm(layer, px, py):
        rows, cols = np.nonzero(layer > 0.5)
        return np.array([cols.mean() * px, rows.mean() * py])
    d = com_mm(small, pitch[0] * fx, pitch[1] * fy) - com_mm(full, *pitch)
    assert (abs(d[0]) <= abs(pitch[0] * fx) and abs(d[1]) <= abs(pitch[1] * fy)), \
        f"downsampled preview offset {d[0]:+.4f}, {d[1]:+.4f} mm"
 def test_manual_path_reproduces_geometry(rig):
    sras, result = rig.sras, rig.result
    params = {a: compute.ManualAngleParams(t.rotation_deg, t.shift_mm)
              for a, t in result.per_angle.items()}
    manual = compute.build_manual_alignment(sras, 0, _THRESHOLD_MV, params)
    assert (manual.canvas_shape == result.canvas_shape
            and np.allclose(manual.canvas_origin_mm, result.canvas_origin_mm)
            and all(np.allclose(manual.per_angle[a].matrix, result.per_angle[a].matrix)
                    and np.allclose(manual.per_angle[a].offset, result.per_angle[a].offset)
                    for a in range(sras.n_angles))), \
        "build_manual_alignment matches compute_angle_alignment for the same params"
 def test_sidecar_roundtrip(rig):
    sras, result = rig.sras, rig.result
    params = {a: compute.ManualAngleParams(t.rotation_deg, t.shift_mm)
              for a, t in result.per_angle.items()}
    compute.save_manual_alignment(sras, 0, _THRESHOLD_MV, params)
    loaded = compute.load_manual_alignment(sras)
    assert (loaded is not None
            and all(np.isclose(loaded.per_angle[a].rotation_deg, params[a].rotation_deg)
                    and np.allclose(loaded.per_angle[a].shift_mm, params[a].shift_mm)
                    for a in range(sras.n_angles))), \
        "sidecar reloads every angle's params"
    assert compute.delete_manual_alignment(sras), "sidecar deletes cleanly"
@@ -0,0 +1,719 @@
 """Both batch image exports -- Convert -> Batch Export View as Images (one
 PNG per *file*, via sras_render.export_view_image) and Export -> Batch
 Export Images (one PNG per *angle x channel* of the open file, via
 sras_workers.BatchExportWorker). Does the exported PNG actually match what
 the live view would show, and does the batch dispatch (menu action ->
 worker -> per-file render) behave like Batch Compute's proven pattern?
 The recurring hazard both halves guard is a dropped view setting: every
 parameter that decides what an FFT-derived pixel *is* (bg-sub, pad,
 row-averaging, the min peak frequency floor) defaults to "off" in
 compute_rf_image, so an argument the export forgets to forward does not
 degrade gracefully -- it silently renders a different image than the screen,
 and worse, makes this file's stored cache look like a match so the export
 hands back peaks from an earlier compute.
 sras_render.export_view_image is tested directly (no Qt) for the plumbing
 that decides *what* gets rendered -- pad_factor derived per file, masked-
 pixel NaN fill, per-file auto-scale, velocity scaling -- via a
 draw_view_image spy rather than pixel-diffing PNGs, the same "spy on the
 seam, don't inspect the rendered artifact" approach test_highlight_masked_
 pixels (tests/test_gui.py) uses for the live canvas.
 The GUI-dispatch half drives SrasViewerWindow._on_batch_export_images()
 end-to-end with patched file dialogs, the same shape as
 test_stored_cache.py's test_viewer_batch_row_average_dispatch.
 """
 from pathlib import Path
 from unittest.mock import patch
 import numpy as np
 import pytest
 from PyQt6.QtCore import QEventLoop, QTimer
 from PyQt6.QtWidgets import QApplication
 import sras_render
 import sras_workers
 from sras_compute import cache_file, compute_rf_image, dc_image_mv
 from sras_format import CH1_IDX, CH3_IDX, CH4_IDX, CH_NAMES, SrasFile
 from sras_render import DEFAULT_FIGSIZE, export_view_image, sanitize_figsize
 from sras_viewer import SrasViewerWindow, VELOCITY_MODE_IDX
 from sras_workers import (
    BatchExportImagesWorker, BatchExportWorker, ExportChannel,
 )
 import tools.make_test_sras as gen
 _THRESHOLD_MV = 50.0
 def pump(ms: int = 200):
    loop = QEventLoop()
    QTimer.singleShot(ms, loop.quit)
    loop.exec()
 def wait_until(pred, timeout_ms: int = 20000, step: int = 100) -> bool:
    waited = 0
    while waited < timeout_ms:
        if pred():
            return True
        pump(step)
        waited += step
    return pred()
 # ---------------------------------------------------------------------------
 # sras_render.export_view_image -- pure function, no Qt
 # ---------------------------------------------------------------------------
 _DEFAULT_KW = dict(
    is_fft_mode=False, is_velocity=False, dc_threshold_mv=_THRESHOLD_MV,
    apply_bg_sub=True, pad_factor=1, min_freq_mhz=0.0, grating_um=1.0,
    cmap="viridis", auto_scale=True, vmin=0.0, vmax=1.0,
    highlight_masked=False, mode_str="DC", colorbar_label="mV",
 )
 def _kw(**overrides):
    kw = dict(_DEFAULT_KW)
    kw.update(overrides)
    return kw
 def _png_size(path) -> tuple[int, int]:
    """(width, height) in pixels, read straight out of the PNG's IHDR chunk
    (two big-endian uint32s at byte 16) -- no image library needed just to
    check the shape of an export."""
    raw = Path(path).read_bytes()
    assert raw[:8] == b"\x89PNG\r\n\x1a\n", "not a valid PNG"
    return (int.from_bytes(raw[16:20], "big"),
            int.from_bytes(raw[20:24], "big"))
 def _spy_draw(monkeypatch):
    """Patches sras_render.draw_view_image to record the image array and
    vmin/vmax/bad_color it was called with, then delegates to the real
    implementation so the PNG is still written -- lets a test check *what*
    export_view_image computed without depending on rendered PNG pixels."""
    orig = sras_render.draw_view_image
    captured = {}
    def spy(ax, fig, img, extent, cmap, vmin, vmax, xlabel, ylabel, title,
            colorbar_label="", cb_ticks=None, norm=None, bad_color=None):
        captured["img"] = np.array(img, copy=True)
        captured["vmin"] = vmin
        captured["vmax"] = vmax
        captured["bad_color"] = bad_color
        return orig(ax, fig, img, extent, cmap, vmin, vmax, xlabel, ylabel,
                   title, colorbar_label, cb_ticks, norm, bad_color)
    monkeypatch.setattr(sras_render, "draw_view_image", spy)
    return captured
 def test_export_dc_channel_writes_png(tmp_path):
    path = tmp_path / "dc.sras"
    gen.write(path, n_angles=2, seed=1, samples_per_frame=64)
    out_dir = tmp_path / "out"
    out_dir.mkdir()
    err, out_name = export_view_image(
        str(path), out_dir=str(out_dir), angle_idx=0, ch_idx=CH4_IDX, **_kw())
    assert err == ""
    assert out_name == f"dc_angle0_{CH_NAMES[CH4_IDX]}.png"
    out_path = out_dir / out_name
    assert out_path.exists() and out_path.stat().st_size > 0
    assert out_path.read_bytes()[:8] == b"\x89PNG\r\n\x1a\n", "not a valid PNG"
 def test_export_out_of_range_angle(tmp_path):
    path = tmp_path / "short.sras"
    gen.write(path, n_angles=2, seed=2, samples_per_frame=64)
    out_dir = tmp_path / "out"
    out_dir.mkdir()
    err, out_name = export_view_image(
        str(path), out_dir=str(out_dir), angle_idx=5, ch_idx=CH4_IDX, **_kw())
    assert err != "" and "2" in err, "error should mention the file's actual angle count"
    assert out_name == ""
    assert list(out_dir.iterdir()) == [], "no file written for a failed export"
 def test_export_fft_mode_matches_compute_rf_image(tmp_path, monkeypatch):
    path = tmp_path / "fft.sras"
    gen.write(path, n_angles=1, seed=3, samples_per_frame=128)
    out_dir = tmp_path / "out"
    out_dir.mkdir()
    captured = _spy_draw(monkeypatch)
    err, _ = export_view_image(
        str(path), out_dir=str(out_dir), angle_idx=0, ch_idx=CH1_IDX,
        **_kw(is_fft_mode=True))
    assert err == ""
    sras = SrasFile(str(path))
    expected = compute_rf_image(sras, 0, dc_threshold_mv=_THRESHOLD_MV,
                                apply_bg_sub=True, n_fft=None, min_freq_mhz=0.0)
    assert np.array_equal(captured["img"], expected)
 def test_export_velocity_scales_frequency(tmp_path, monkeypatch):
    path = tmp_path / "vel.sras"
    gen.write(path, n_angles=1, seed=4, samples_per_frame=128)
    out_dir = tmp_path / "out"
    out_dir.mkdir()
    captured = _spy_draw(monkeypatch)
    grating_um = 3.5
    err, _ = export_view_image(
        str(path), out_dir=str(out_dir), angle_idx=0, ch_idx=VELOCITY_MODE_IDX,
        **_kw(is_fft_mode=True, is_velocity=True, grating_um=grating_um))
    assert err == ""
    sras = SrasFile(str(path))
    freq = compute_rf_image(sras, 0, dc_threshold_mv=_THRESHOLD_MV,
                            apply_bg_sub=True, n_fft=None, min_freq_mhz=0.0)
    assert np.array_equal(captured["img"], freq * grating_um)
 def test_pad_factor_uses_each_files_own_samples_per_frame(tmp_path, monkeypatch):
    """n_fft must be derived per file from that file's own samples_per_frame,
    never a value carried over from whichever file the caller had open --
    otherwise every file but one in a batch gets silently mis-padded."""
    orig_draw = sras_render.draw_view_image
    out_dir = tmp_path / "out"
    out_dir.mkdir()
    for i, spf in enumerate((64, 256)):
        path = tmp_path / f"pad_{spf}.sras"
        gen.write(path, n_angles=1, seed=5 + i, samples_per_frame=spf)
        captured = {}
        def spy(ax, fig, img, *a, __c=captured, **kw):
            __c["img"] = np.array(img, copy=True)
            return orig_draw(ax, fig, img, *a, **kw)
        monkeypatch.setattr(sras_render, "draw_view_image", spy)
        err, _ = export_view_image(
            str(path), out_dir=str(out_dir), angle_idx=0, ch_idx=CH1_IDX,
            **_kw(is_fft_mode=True, pad_factor=4))
        assert err == ""
        sras = SrasFile(str(path))
        expected = compute_rf_image(sras, 0, dc_threshold_mv=_THRESHOLD_MV,
                                    apply_bg_sub=True, n_fft=spf * 4,
                                    min_freq_mhz=0.0)
        assert np.array_equal(captured["img"], expected), \
            f"samples_per_frame={spf}: n_fft must use this file's own value"
 def test_highlight_masked_sets_nan_and_bad_color(tmp_path, monkeypatch):
    path = tmp_path / "mask.sras"
    gen.write(path, n_angles=1, seed=7, samples_per_frame=128)
    out_dir = tmp_path / "out"
    out_dir.mkdir()
    sras = SrasFile(str(path))
    dc4 = dc_image_mv(sras, 0, CH4_IDX)
    threshold = float(np.median(dc4))
    expect_masked = dc4 < threshold
    assert expect_masked.any() and not expect_masked.all(), \
        "fixture threshold should mask some but not all pixels"
    captured = _spy_draw(monkeypatch)
    err, _ = export_view_image(
        str(path), out_dir=str(out_dir), angle_idx=0, ch_idx=CH1_IDX,
        **_kw(is_fft_mode=True, dc_threshold_mv=threshold,
              highlight_masked=True, mask_color="magenta"))
    assert err == ""
    assert captured["bad_color"] == "magenta"
    # The export masks by value too (0 == the "no valid peak" sentinel, same
    # rule as the viewer's _redraw_image); on this fixture every
    # above-threshold pixel has a nonzero peak, so the value mask coincides
    # with the DC mask and the NaN set is exactly expect_masked.
    assert np.array_equal(np.isnan(captured["img"]), expect_masked)
    valid_vals = captured["img"][~expect_masked]
    assert not np.isnan(valid_vals).any() and (valid_vals != 0).all(), \
        "fixture precondition: every valid pixel has a nonzero peak"
    captured2 = _spy_draw(monkeypatch)
    err, _ = export_view_image(
        str(path), out_dir=str(out_dir), angle_idx=0, ch_idx=CH1_IDX,
        **_kw(is_fft_mode=True, dc_threshold_mv=threshold, highlight_masked=False))
    assert err == ""
    assert captured2["bad_color"] is None
    assert not np.isnan(captured2["img"]).any()
 def test_auto_scale_uses_per_file_min_max(tmp_path, monkeypatch):
    path = tmp_path / "scale.sras"
    gen.write(path, n_angles=1, seed=8, samples_per_frame=64)
    out_dir = tmp_path / "out"
    out_dir.mkdir()
    captured = _spy_draw(monkeypatch)
    err, _ = export_view_image(
        str(path), out_dir=str(out_dir), angle_idx=0, ch_idx=CH4_IDX,
        **_kw(auto_scale=True))
    assert err == ""
    img = captured["img"]
    assert captured["vmin"] == pytest.approx(float(np.nanmin(img)))
    assert captured["vmax"] == pytest.approx(float(np.nanmax(img)))
    captured2 = _spy_draw(monkeypatch)
    err, _ = export_view_image(
        str(path), out_dir=str(out_dir), angle_idx=0, ch_idx=CH4_IDX,
        **_kw(auto_scale=False, vmin=-5.0, vmax=5.0))
    assert err == ""
    assert captured2["vmin"] == -5.0
    assert captured2["vmax"] == 5.0
@pytest.mark.parametrize("figsize", [(12.0, 4.0), (4.0, 9.0)])
 def test_export_matches_requested_figsize(tmp_path, figsize):
    """The PNG comes out at the caller's figure size, so a view the user has
    sized wide (or tall) doesn't get squeezed into a fixed 7x5 -- the image
    is drawn with aspect="auto", so the figure box *is* the map's shape."""
    path = tmp_path / "shape.sras"
    gen.write(path, n_angles=1, seed=70, samples_per_frame=64)
    out_dir = tmp_path / "out"
    out_dir.mkdir()
    dpi = 100
    err, out_name = export_view_image(
        str(path), out_dir=str(out_dir), angle_idx=0, ch_idx=CH4_IDX,
        figsize=figsize, dpi=dpi, **_kw())
    assert err == ""
    w_px, h_px = _png_size(out_dir / out_name)
    # Agg truncates inches*dpi to whole pixels; a pixel of slack, not an
    # aspect-ratio tolerance, is what's being allowed for here.
    assert abs(w_px - figsize[0] * dpi) <= 1
    assert abs(h_px - figsize[1] * dpi) <= 1
 def test_export_default_figsize_when_unspecified(tmp_path):
    """No figsize (a caller with no live canvas to match) still renders at
    the viewer's starting size rather than failing or guessing."""
    path = tmp_path / "default_shape.sras"
    gen.write(path, n_angles=1, seed=71, samples_per_frame=64)
    out_dir = tmp_path / "out"
    out_dir.mkdir()
    err, out_name = export_view_image(
        str(path), out_dir=str(out_dir), angle_idx=0, ch_idx=CH4_IDX,
        dpi=100, **_kw())
    assert err == ""
    w_px, h_px = _png_size(out_dir / out_name)
    assert abs(w_px - DEFAULT_FIGSIZE[0] * 100) <= 1
    assert abs(h_px - DEFAULT_FIGSIZE[1] * 100) <= 1
@pytest.mark.parametrize("bad", [None, (0.0, 0.0), (-3.0, 5.0), (np.nan, 5.0),
                                 (float("inf"), 5.0), (7.0,), "7x5"])
 def test_sanitize_figsize_never_yields_an_unrenderable_size(bad):
    """A degenerate canvas size (collapsed pane, minimized window) must cost
    at most a wrong-looking image, never a failed export."""
    w, h = sanitize_figsize(bad)
    assert np.isfinite(w) and np.isfinite(h)
    assert w >= 1.0 and h >= 1.0
 def test_sanitize_figsize_passes_through_a_normal_canvas_size():
    assert sanitize_figsize(np.array([12.8, 6.4])) == pytest.approx((12.8, 6.4))
 # ---------------------------------------------------------------------------
 # GUI dispatch: SrasViewerWindow._on_batch_export_images end-to-end
 # ---------------------------------------------------------------------------
 def _make_window(path) -> SrasViewerWindow:
    app = QApplication.instance() or QApplication([])   # noqa: F841
    win = SrasViewerWindow()
    win.show()
    win._load_file(str(path))
    assert wait_until(lambda: win._sras is not None), "file loaded"
    assert wait_until(lambda: all((a, CH4_IDX) in win._dc_cache
                                  for a in range(win._sras.n_angles))), \
        "DC precompute finished"
    return win
 def test_batch_export_images_writes_one_png_per_file(tmp_path):
    path = tmp_path / "src.sras"
    gen.write(path, n_angles=2, seed=10, samples_per_frame=64)
    paths = [str(path)]
    for i in range(2):
        p2 = tmp_path / f"other{i}.sras"
        gen.write(p2, n_angles=2, seed=20 + i, samples_per_frame=64)
        paths.append(str(p2))
    out_dir = tmp_path / "images"
    out_dir.mkdir()
    win = _make_window(path)
    try:
        with patch("sras_viewer.main_window.QFileDialog.getOpenFileNames",
                   return_value=(paths, "")), \
             patch("sras_viewer.main_window.QFileDialog.getExistingDirectory",
                   return_value=str(out_dir)):
            win._on_batch_export_images()
        assert wait_until(lambda: not win._job_running("batch"), 60000), "batch ran"
        angle = win.spin_angle.value()
        ch_name = CH_NAMES[win.combo_channel.currentIndex()]
        expected_names = {f"{Path(p).stem}_angle{angle}_{ch_name}.png" for p in paths}
        actual_names = {p.name for p in out_dir.iterdir()}
        assert actual_names == expected_names
        assert "Batch export: 3/3 image(s)" in win.statusBar().currentMessage()
    finally:
        win.close()
        pump(200)
 def test_batch_export_out_of_range_angle_reports_error_continues(tmp_path):
    good_path = tmp_path / "good.sras"
    short_path = tmp_path / "short.sras"
    gen.write(good_path, n_angles=3, seed=30, samples_per_frame=64)
    gen.write(short_path, n_angles=1, seed=31, samples_per_frame=64)
    out_dir = tmp_path / "images"
    out_dir.mkdir()
    win = _make_window(good_path)
    try:
        win.spin_angle.setValue(2)   # valid for good_path, out of range for short_path
        with patch("sras_viewer.main_window.QFileDialog.getOpenFileNames",
                   return_value=([str(good_path), str(short_path)], "")), \
             patch("sras_viewer.main_window.QFileDialog.getExistingDirectory",
                   return_value=str(out_dir)):
            win._on_batch_export_images()
        assert wait_until(lambda: not win._job_running("batch"), 60000), "batch ran"
        msg = win.statusBar().currentMessage()
        assert "Batch export: 1/2 image(s)" in msg, msg
        assert "1 failed" in msg, msg
        assert len(list(out_dir.iterdir())) == 1, \
            "the batch must not abort — the good file still exports"
    finally:
        win.close()
        pump(200)
 def test_batch_export_busy_guard_skips_dialogs(tmp_path, monkeypatch):
    path = tmp_path / "busy.sras"
    gen.write(path, n_angles=1, seed=40, samples_per_frame=64)
    win = _make_window(path)
    try:
        monkeypatch.setattr(win, "_job_running", lambda key: True)
        with patch("sras_viewer.main_window.QFileDialog.getOpenFileNames") as mock_dlg:
            win._on_batch_export_images()
        assert mock_dlg.call_count == 0, \
            "the Jobs.BATCH busy guard must return before opening any dialog"
    finally:
        win.close()
        pump(200)
 def test_batch_export_ignores_aligned_view_toggle(tmp_path):
    """Aligned View is geometry specific to whichever single file the
    Alignment Wizard last ran against and cannot be meaningfully applied
    across a batch of different files -- _on_batch_export_images must not
    read chk_aligned_view / self._alignment_result at all, regardless of
    what's checked in the live view."""
    path = tmp_path / "aligned.sras"
    gen.write(path, n_angles=1, seed=41, samples_per_frame=64)
    out_dir = tmp_path / "images"
    out_dir.mkdir()
    win = _make_window(path)
    try:
        captured_kwargs = []
        orig_init = BatchExportImagesWorker.__init__
        def spy_init(self, paths, **kw):
            captured_kwargs.append(kw)
            return orig_init(self, paths, **kw)
        win.chk_aligned_view.setChecked(True)
        with patch.object(BatchExportImagesWorker, "__init__", spy_init), \
             patch("sras_viewer.main_window.QFileDialog.getOpenFileNames",
                   return_value=([str(path)], "")), \
             patch("sras_viewer.main_window.QFileDialog.getExistingDirectory",
                   return_value=str(out_dir)):
            win._on_batch_export_images()
        assert wait_until(lambda: not win._job_running("batch"), 60000), "batch ran"
        assert len(captured_kwargs) == 1
        assert not any("align" in k.lower() for k in captured_kwargs[0]), \
            captured_kwargs[0].keys()
    finally:
        win.close()
        pump(200)
 def test_batch_export_uses_the_live_canvas_aspect_ratio(tmp_path):
    """The exported PNG has the shape of the view on screen, not a fixed
    7x5 -- resize the window and the export follows it."""
    path = tmp_path / "aspect.sras"
    gen.write(path, n_angles=1, seed=45, samples_per_frame=64)
    out_dir = tmp_path / "images"
    out_dir.mkdir()
    win = _make_window(path)
    try:
        win.resize(1400, 700)
        pump(300)   # let the canvas' resizeEvent reach the figure
        canvas_w, canvas_h = win.image_canvas.figure.get_size_inches()
        captured_kwargs = []
        orig_init = BatchExportImagesWorker.__init__
        def spy_init(self, paths, **kw):
            captured_kwargs.append(kw)
            return orig_init(self, paths, **kw)
        with patch.object(BatchExportImagesWorker, "__init__", spy_init), \
             patch("sras_viewer.main_window.QFileDialog.getOpenFileNames",
                   return_value=([str(path)], "")), \
             patch("sras_viewer.main_window.QFileDialog.getExistingDirectory",
                   return_value=str(out_dir)):
            win._on_batch_export_images()
        assert wait_until(lambda: not win._job_running("batch"), 60000), "batch ran"
        assert captured_kwargs[0]["figsize"] == pytest.approx(
            (canvas_w, canvas_h)), "the live canvas size must travel to the worker"
        out_files = list(out_dir.iterdir())
        assert len(out_files) == 1
        w_px, h_px = _png_size(out_files[0])
        assert w_px / h_px == pytest.approx(canvas_w / canvas_h, rel=0.01)
    finally:
        win.close()
        pump(200)
 def test_batch_export_filename_collision_note(tmp_path):
    dir_a, dir_b = tmp_path / "dir_a", tmp_path / "dir_b"
    dir_a.mkdir()
    dir_b.mkdir()
    path_a, path_b = dir_a / "dup.sras", dir_b / "dup.sras"
    gen.write(path_a, n_angles=1, seed=50, samples_per_frame=64)
    gen.write(path_b, n_angles=1, seed=51, samples_per_frame=64)
    out_dir = tmp_path / "images"
    out_dir.mkdir()
    win = _make_window(path_a)
    try:
        with patch("sras_viewer.main_window.QFileDialog.getOpenFileNames",
                   return_value=([str(path_a), str(path_b)], "")), \
             patch("sras_viewer.main_window.QFileDialog.getExistingDirectory",
                   return_value=str(out_dir)):
            win._on_batch_export_images()
        assert wait_until(lambda: not win._job_running("batch"), 60000), "batch ran"
        msg = win.statusBar().currentMessage()
        assert "Batch export: 2/2 image(s)" in msg, msg
        assert "collision" in msg, msg
        assert len(list(out_dir.iterdir())) == 1, \
            "same-stem inputs silently overwrite to one output file"
    finally:
        win.close()
        pump(200)
 def test_batch_export_does_not_modify_source_files(tmp_path):
    path = tmp_path / "untouched.sras"
    gen.write(path, n_angles=1, seed=60, samples_per_frame=64)
    before = path.read_bytes()
    out_dir = tmp_path / "images"
    out_dir.mkdir()
    win = _make_window(path)
    try:
        with patch("sras_viewer.main_window.QFileDialog.getOpenFileNames",
                   return_value=([str(path)], "")), \
             patch("sras_viewer.main_window.QFileDialog.getExistingDirectory",
                   return_value=str(out_dir)):
            win._on_batch_export_images()
        assert wait_until(lambda: not win._job_running("batch"), 60000), "batch ran"
    finally:
        win.close()
        pump(200)
    assert path.read_bytes() == before, "export must never write to the source file"
 # ---------------------------------------------------------------------------
 # Export menu: BatchExportWorker (every angle of the open file)
 # ---------------------------------------------------------------------------
 # High enough to sit above several of the generator's synthetic peak bins
 # (bin spacing is 6.25 GS/s / 64 = 97.66 MHz, peaks land at bins 3-19), so a
 # floor at this value genuinely changes which peak each pixel resolves to --
 # without that, a test that the floor is honored would pass either way.
 _FLOOR_MHZ = 1000.0
 _GRATING_UM = 2.0
 def _velocity_channel() -> ExportChannel:
    return ExportChannel(ch_idx=CH1_IDX, is_velocity=True, vmin=0.0, vmax=1e5,
                         label="Velocity", unit="m/s", tag="VEL")
 def _run_export_worker(monkeypatch, sras, out_dir, **overrides) -> list[np.ndarray]:
    """Runs BatchExportWorker to completion on the calling thread (its run()
    is a plain loop; the QThread in _run_worker is a GUI concern) and returns
    the image arrays it rendered, captured at the _render_map_png seam."""
    captured = []
    orig = sras_workers._render_map_png
    def spy(img, extent, **kw):
        captured.append(np.array(img, copy=True))
        return orig(img, extent, **kw)
    monkeypatch.setattr(sras_workers, "_render_map_png", spy)
    kw = dict(cmap="viridis", apply_bg_sub=True, dc_threshold_mv=_THRESHOLD_MV,
              n_fft=None, grating_um=_GRATING_UM, min_freq_mhz=_FLOOR_MHZ)
    kw.update(overrides)
    BatchExportWorker(sras, [_velocity_channel()], str(out_dir), "vel", **kw).run()
    return captured
 def test_batch_export_applies_the_min_peak_freq_floor(tmp_path, monkeypatch):
    """The exported Velocity map is the floored one the viewer shows, not the
    unfloored peaks the floor was raised to reject."""
    path = tmp_path / "floor.sras"
    gen.write(path, n_angles=1, seed=80, samples_per_frame=64, geometry=[(6, 9)])
    out_dir = tmp_path / "out"
    out_dir.mkdir()
    sras = SrasFile(str(path))
    def expected(floor):
        return compute_rf_image(sras, 0, dc_threshold_mv=_THRESHOLD_MV,
                                apply_bg_sub=True, n_fft=None,
                                min_freq_mhz=floor) * _GRATING_UM
    floored, unfloored = expected(_FLOOR_MHZ), expected(0.0)
    assert not np.allclose(floored, unfloored), \
        "fixture must be one where the floor changes the image"
    exported = _run_export_worker(monkeypatch, sras, out_dir)
    assert len(exported) == 1
    assert np.allclose(exported[0], floored)
 def test_batch_export_does_not_serve_an_unfloored_stored_cache(tmp_path,
                                                               monkeypatch):
    """A file batch-computed before the floor existed has a stored cache with
    no floor recorded. Asking for that cache at floor 0 (rather than the live
    floor) makes it a match, so the export would render the stored pre-floor
    peaks -- the map the user raised the floor to get rid of."""
    path = tmp_path / "stored_floor.sras"
    gen.write(path, n_angles=1, seed=81, samples_per_frame=64, geometry=[(6, 9)])
    assert cache_file(str(path), "fft", apply_bg_sub=True) == ""
    sras = SrasFile(str(path))
    assert sras.precomputed_freq_mhz[0] is not None, "stored cache written"
    assert sras.precomputed_min_freq_mhz == 0.0
    out_dir = tmp_path / "out"
    out_dir.mkdir()
    exported = _run_export_worker(monkeypatch, sras, out_dir)[0]
    # 0.0 is the "no valid peak" sentinel; anything else below the floor is a
    # peak that only an unfloored search could have reported.
    below = (exported > 0) & (exported < _FLOOR_MHZ * _GRATING_UM)
    assert not below.any(), \
        f"{below.sum()} sub-floor pixel(s) survived the export"
 def test_batch_export_dispatch_passes_the_live_view_settings(tmp_path):
    """The Export menu hands the worker what the panel currently says --
    the floor in particular, which is a display control and so persists
    across file loads while the window's own FFT cache does not."""
    path = tmp_path / "dispatch.sras"
    gen.write(path, n_angles=1, seed=82, samples_per_frame=64)
    out_dir = tmp_path / "out"
    out_dir.mkdir()
    win = _make_window(path)
    try:
        win.spin_min_freq_mhz.setValue(_FLOOR_MHZ)
        win.spin_grating_um.setValue(_GRATING_UM)
        win.spin_threshold_mv.setValue(_THRESHOLD_MV)
        class StubDialog:
            def __init__(self, parent, **kw):
                pass
            def exec(self):
                from PyQt6.QtWidgets import QDialog
                return QDialog.DialogCode.Accepted
            def get_output_dir(self):
                return str(out_dir)
            def get_prefix(self):
                return "vel"
            def get_selected_channels(self):
                return [_velocity_channel()]
        captured_kwargs = []
        orig_init = BatchExportWorker.__init__
        def spy_init(self, sras, channels, output_dir, prefix, **kw):
            captured_kwargs.append(kw)
            return orig_init(self, sras, channels, output_dir, prefix, **kw)
        with patch.object(BatchExportWorker, "__init__", spy_init), \
             patch("sras_viewer.main_window.BatchExportDialog", StubDialog):
            win._on_batch_export()
        assert wait_until(lambda: not win._job_running("export"), 60000), "export ran"
        kw = captured_kwargs[0]
        assert kw["min_freq_mhz"] == _FLOOR_MHZ
        assert kw["grating_um"] == _GRATING_UM
        assert kw["dc_threshold_mv"] == _THRESHOLD_MV
    finally:
        win.close()
        pump(200)
 def test_export_view_image_serves_a_row_averaged_stored_cache(tmp_path,
                                                              monkeypatch):
    """Batch Export View as Images must ask this file's cache the question the
    viewer asks it. _stored_fft_image reads at the file's own
    precomputed_row_avg_n; requesting raw per-pixel instead makes a
    row-averaged cache a mismatch, and the export silently renders a full raw
    recompute where the screen shows the smoothed stored image."""
    path = tmp_path / "rowavg_cache.sras"
    gen.write(path, n_angles=1, seed=83, samples_per_frame=64, geometry=[(6, 9)])
    # A planted stored image rather than a real row-averaged compute: the
    # question here is *which* source the export reads, and a distinctive
    # array answers it without depending on the synthetic waveforms being
    # smooth enough for averaging to move the numbers.
    sras = SrasFile(str(path))
    shape = sras.image_shape(0)
    stored = (100.0 + 10.0 * np.arange(shape[0] * shape[1], dtype=np.float32)
              ).reshape(shape)
    sras.write_v7_cache(new_freq_mhz=[stored], new_row_avg_n=5,
                        new_bg_sub=True, new_pad_factor=1)
    reread = SrasFile(str(path))
    raw = compute_rf_image(reread, 0, dc_threshold_mv=None, apply_bg_sub=True,
                           n_fft=None, row_avg_n=0, use_stored=False)
    assert not np.allclose(stored, raw), "planted cache must be distinguishable"
    out_dir = tmp_path / "out"
    out_dir.mkdir()
    captured = _spy_draw(monkeypatch)
    err, _out_name = export_view_image(
        str(path), out_dir=str(out_dir), angle_idx=0, ch_idx=CH1_IDX,
        **_kw(is_fft_mode=True, dc_threshold_mv=-1e9, colorbar_label="MHz",
              mode_str="RF"))
    assert err == ""
    assert np.allclose(captured["img"], stored), \
        "export rendered a recompute instead of the stored image on screen"
@@ -0,0 +1,478 @@
 """Behavioural tests for the compute/format layer.
 Covers what the golden-hash harness can't: the v6->v7 cache round-trip
 (including block carry-forward), parallel-vs-serial identity, the no-mask
 fast path, and the ROI bounding-box mask optimisation.
 """
 import subprocess
 import sys
 from pathlib import Path
 import numpy as np
 import pytest
 import sras_average
 import sras_compute as compute
 from sras_compute import (
    cache_file, compute_dc_image, compute_rf_image, dc_image_mv,
 )
 from sras_format import CH3_IDX, CH4_IDX, SrasFile, adc_to_mv
 import tools.make_test_sras as gen
 REPO = Path(__file__).resolve().parent.parent
 def test_cache_roundtrip(tmp_path):
    """v6 -> v7 for DC, then FFT, asserting the first block survives the
    second write (the carry-forward path in write_v7_cache)."""
    path = tmp_path / "roundtrip.sras"
    gen.write(path, n_angles=3, seed=1, samples_per_frame=64)
    src = SrasFile(str(path))
    assert src.version == 6, f"got v{src.version}"
    expect_dc3 = [dc_image_mv(src, a, CH3_IDX) for a in range(src.n_angles)]
    expect_dc4 = [dc_image_mv(src, a, CH4_IDX) for a in range(src.n_angles)]
    expect_fft = [compute_rf_image(src, a, dc_threshold_mv=None, apply_bg_sub=True)
                  for a in range(src.n_angles)]
    err = cache_file(str(path), "dc", True)
    assert err == "", err
    after_dc = SrasFile(str(path))
    assert after_dc.version == 7, f"got v{after_dc.version}"
    assert all(x is not None for x in after_dc.precomputed_dc3_mv)
    assert all(np.allclose(after_dc.precomputed_dc3_mv[a], expect_dc3[a], atol=1e-4)
               for a in range(after_dc.n_angles))
    assert all(np.allclose(after_dc.precomputed_dc4_mv[a], expect_dc4[a], atol=1e-4)
               for a in range(after_dc.n_angles))
    assert all(x is None for x in after_dc.precomputed_freq_mhz), "no fft block yet"
    assert (after_dc.precomputed_dc3_mv[0].dtype == np.float32
            and after_dc.precomputed_dc3_mv[0].dtype.byteorder in ("=", "|")), \
        "cached images are native float32"
    assert after_dc.precomputed_dc3_mv[0].flags.writeable
    err = cache_file(str(path), "fft", True)
    assert err == "", err
    both = SrasFile(str(path))
    assert all(x is not None for x in both.precomputed_freq_mhz)
    assert all(np.allclose(both.precomputed_freq_mhz[a], expect_fft[a], atol=1e-3)
               for a in range(both.n_angles))
    assert all(np.allclose(both.precomputed_dc3_mv[a], expect_dc3[a], atol=1e-4)
               for a in range(both.n_angles)), \
        "DC block carried forward through the FFT write"
    assert both.precomputed_bg_sub is True
    # The fast path must reproduce a fresh compute, and masking must still
    # apply on top of a cached (unmasked) image.
    fresh = SrasFile(str(path))
    fresh.precomputed_freq_mhz = [None] * fresh.n_angles
    dc4 = dc_image_mv(both, 0, CH4_IDX)
    thr = float(np.median(dc4))
    assert np.allclose(
        compute_rf_image(both, 0, dc_threshold_mv=None, apply_bg_sub=True),
        compute_rf_image(fresh, 0, dc_threshold_mv=None, apply_bg_sub=True),
        atol=1e-3), "cached fast path == fresh compute (unmasked)"
    assert np.allclose(
        compute_rf_image(both, 0, dc_threshold_mv=thr, apply_bg_sub=True),
        compute_rf_image(fresh, 0, dc_threshold_mv=thr, apply_bg_sub=True),
        atol=1e-3), "cached fast path == fresh compute (masked)"
    # Waveform data must be byte-identical to the pre-cache file.
    orig = tmp_path / "roundtrip_orig.sras"
    gen.write(orig, n_angles=3, seed=1, samples_per_frame=64)
    o, n = SrasFile(str(orig)), SrasFile(str(path))
    assert all(np.array_equal(np.asarray(o.data[a]), np.asarray(n.data[a]))
               for a in range(o.n_angles)), \
        "waveform data untouched by the cache write"
 def test_partial_v7_cache(tmp_path):
    """Only some angles cached: uncached angles must compute, not read zeros.
    This is the v5 bug the ragged normalisation fixed, checked via v7."""
    path = tmp_path / "partial.sras"
    gen.write(path, n_angles=3, seed=2, samples_per_frame=64)
    src = SrasFile(str(path))
    expected = [compute_rf_image(src, a, dc_threshold_mv=None, apply_bg_sub=True)
                for a in range(src.n_angles)]
    partial = [expected[0], None, expected[2]]     # angle 1 deliberately absent
    src.write_v7_cache(new_freq_mhz=partial, new_bg_sub=True)
    reread = SrasFile(str(path))
    assert reread.precomputed_freq_mhz[1] is None
    assert (reread.precomputed_freq_mhz[0] is not None
            and reread.precomputed_freq_mhz[2] is not None)
    img1 = compute_rf_image(reread, 1, dc_threshold_mv=None, apply_bg_sub=True)
    assert np.any(img1 != 0) and np.allclose(img1, expected[1], atol=1e-3), \
        "uncached angle computes rather than returning zeros"
 def test_parallel_identity(tmp_path, monkeypatch):
    """Forcing 1 worker vs many must give identical output — catches
    chunk-boundary and race bugs."""
    path = tmp_path / "parallel.sras"
    # Many rows, so the row loop actually splits into several chunks.
    n_rows, n_frames, spf = 48, 9, 256
    gen.write(path, n_angles=1, seed=3, samples_per_frame=spf,
              geometry=[(n_rows, n_frames)])
    sras = SrasFile(str(path))
    # Shrink the budget so the outer row loop splits into many chunks, and
    # the block size so every chunk splits into many FFT tasks — the worst
    # case for boundary bugs.
    monkeypatch.setattr(compute, "_TOTAL_BYTES_BUDGET", 8 * n_frames * spf * 4)
    monkeypatch.setattr(compute, "_FFT_BLOCK_MAX", 4)
    fft_rows = compute._plan_fft_rows(n_frames, spf, compute._TOTAL_BYTES_BUDGET)
    assert fft_rows < n_rows, \
        f"FFT work actually splits into multiple chunks ({fft_rows} of {n_rows})"
    dc_rows = compute._chunk_rows_for(n_frames, spf, compute._TOTAL_BYTES_BUDGET)
    assert dc_rows < n_rows, \
        f"DC work actually splits into multiple chunks ({dc_rows} of {n_rows})"
    monkeypatch.setattr(compute, "_MAX_WORKERS", 1)
    dc_serial = compute_dc_image(sras, 0, CH4_IDX)
    rf_serial = compute_rf_image(sras, 0, dc_threshold_mv=None, apply_bg_sub=True)
    dc4 = adc_to_mv(dc_serial, *sras.cal(CH4_IDX))
    thr = float(np.median(dc4))
    rf_masked_serial = compute_rf_image(sras, 0, dc_threshold_mv=thr,
                                        apply_bg_sub=True)
    rf_pad_serial = compute_rf_image(sras, 0, dc_threshold_mv=thr,
                                     apply_bg_sub=True, n_fft=spf * 8)
    monkeypatch.setattr(compute, "_MAX_WORKERS", 8)
    dc_par = compute_dc_image(sras, 0, CH4_IDX)
    rf_par = compute_rf_image(sras, 0, dc_threshold_mv=None, apply_bg_sub=True)
    rf_masked_par = compute_rf_image(sras, 0, dc_threshold_mv=thr, apply_bg_sub=True)
    rf_pad_par = compute_rf_image(sras, 0, dc_threshold_mv=thr,
                                  apply_bg_sub=True, n_fft=spf * 8)
    assert np.array_equal(dc_serial, dc_par), "dc image identical"
    assert np.array_equal(rf_serial, rf_par), "rf image identical (unmasked)"
    assert np.array_equal(rf_masked_serial, rf_masked_par), \
        "rf image identical (masked)"
    assert np.array_equal(rf_pad_serial, rf_pad_par), \
        "rf image identical (masked, padded/zoom)"
 def test_peak_bins_fuzz():
    """Hammer _peak_bins directly with adversarial spectra: noise,
    un-subtracted DC offsets, on-bin and off-bin tones, near-tie tone pairs,
    and all-zero rows — against an independent scipy.fft reference."""
    import scipy.fft as scipy_fft
    rng = np.random.default_rng(42)
    for _ in range(25):
        spf = int(rng.integers(16, 220))
        pad = int(rng.choice([4, 5, 8, 16, 40]))
        n_fft = spf * pad
        n_wf = 24
        w = rng.normal(scale=20.0, size=(n_wf, spf))
        t = np.arange(spf)
        # rows 0-5: pure/noisy tones (some off-bin), row 6-7: near-tie pair,
        # row 8: big DC offset, row 9: all zeros, rest: plain noise.
        for r in range(6):
            f = rng.uniform(1.0, spf / 2 - 1)
            w[r] = 60 * np.sin(2 * np.pi * f * t / spf) + w[r] * (r % 2)
        f1, f2 = rng.uniform(2.0, spf / 2 - 2, size=2)
        w[6] = 50 * np.sin(2 * np.pi * f1 * t / spf) \
            + 49.9 * np.sin(2 * np.pi * f2 * t / spf)
        w[7] = 50 * np.sin(2 * np.pi * f1 * t / spf) \
            + 50 * np.cos(2 * np.pi * f2 * t / spf)
        w[8] = 90 + rng.normal(scale=5.0, size=spf)
        w[9] = 0.0
        w = w.astype(np.float32)
        S = scipy_fft.rfft(w, n=n_fft, axis=-1, workers=1)
        P = S.real ** 2
        P += S.imag ** 2
        P[:, 0] = 0.0
        ref = np.argmax(P, axis=1)
        got = compute._peak_bins(w, n_fft)
        bad = np.nonzero(ref != got)[0]
        assert not len(bad), \
            (f"spf={spf} pad={pad}: rows {bad.tolist()} picked "
             f"{got[bad].tolist()} instead of {ref[bad].tolist()}")
 def test_peak_bins_fuzz_min_freq():
    """Same adversarial-spectra fuzz as test_peak_bins_fuzz, but with a swept
    min_bin floor: bins below the floor must be excluded from the argmax
    exactly as the independent scipy.fft reference is, when zeroed the same
    way before argmax."""
    import scipy.fft as scipy_fft
    rng = np.random.default_rng(43)
    for _ in range(25):
        spf = int(rng.integers(16, 220))
        pad = int(rng.choice([4, 5, 8, 16, 40]))
        n_fft = spf * pad
        n_wf = 24
        w = rng.normal(scale=20.0, size=(n_wf, spf))
        t = np.arange(spf)
        for r in range(6):
            f = rng.uniform(1.0, spf / 2 - 1)
            w[r] = 60 * np.sin(2 * np.pi * f * t / spf) + w[r] * (r % 2)
        f1, f2 = rng.uniform(2.0, spf / 2 - 2, size=2)
        w[6] = 50 * np.sin(2 * np.pi * f1 * t / spf) \
            + 49.9 * np.sin(2 * np.pi * f2 * t / spf)
        w[7] = 50 * np.sin(2 * np.pi * f1 * t / spf) \
            + 50 * np.cos(2 * np.pi * f2 * t / spf)
        w[8] = 90 + rng.normal(scale=5.0, size=spf)
        w[9] = 0.0
        w = w.astype(np.float32)
        S = scipy_fft.rfft(w, n=n_fft, axis=-1, workers=1)
        P = S.real ** 2
        P += S.imag ** 2
        n_bins_fine = n_fft // 2 + 1
        min_bin = int(rng.integers(1, max(2, n_bins_fine // 3)))
        P[:, :min_bin] = 0.0
        ref = np.argmax(P, axis=1)
        got = compute._peak_bins(w, n_fft, min_bin)
        bad = np.nonzero(ref != got)[0]
        assert not len(bad), \
            (f"spf={spf} pad={pad} min_bin={min_bin}: rows {bad.tolist()} picked "
             f"{got[bad].tolist()} instead of {ref[bad].tolist()}")
@pytest.mark.parametrize("spf", [64, 500, 2500])
 def test_fft_block_for(spf):
    """Block size == _FFT_BLOCK_MAX at natural resolution, shrinks and stays
    >= _FFT_BLOCK_MIN as n_len grows, and the implied per-thread byte
    estimate respects _FFT_PLAN_BYTES_BUDGET except when the floor is
    engaged."""
    block_natural = compute._fft_block_for(spf, spf)
    assert block_natural == compute._FFT_BLOCK_MAX
    prev = compute._FFT_BLOCK_MAX
    for pad in (2, 4, 8, 40, 500):
        n_len = spf * pad
        block = compute._fft_block_for(spf, n_len)
        assert compute._FFT_BLOCK_MIN <= block <= prev
        bytes_per_wf = 4 * spf + 8 * (n_len // 2 + 1)
        if block > compute._FFT_BLOCK_MIN:
            assert block * bytes_per_wf <= compute._FFT_PLAN_BYTES_BUDGET
        prev = block
 def test_compute_rf_image_min_freq_mhz(tmp_path):
    """min_freq_mhz threads through compute_rf_image end-to-end, for both
    the natural-resolution and padded paths: 0.0 (default) must reproduce
    the pre-existing image exactly, and a floor above every real peak must
    collapse the image to bin 0 (0 MHz) — the same fallback the low-level
    search uses when nothing survives the floor."""
    path = tmp_path / "floor_e2e.sras"
    gen.write(path, n_angles=1, seed=12, samples_per_frame=64)
    sras = SrasFile(str(path))
    huge_floor = float(sras.freq_axis_mhz(None)[-1]) + 1.0   # above Nyquist
    for n_fft in (None, 64 * 8):
        unfiltered = compute_rf_image(sras, 0, dc_threshold_mv=None,
                                      apply_bg_sub=False, n_fft=n_fft)
        same = compute_rf_image(sras, 0, dc_threshold_mv=None, apply_bg_sub=False,
                                n_fft=n_fft, min_freq_mhz=0.0)
        assert np.array_equal(unfiltered, same), \
            f"n_fft={n_fft}: min_freq_mhz=0.0 changed the output"
        assert unfiltered.any(), \
            f"n_fft={n_fft}: fixture should have real signal"
        collapsed = compute_rf_image(sras, 0, dc_threshold_mv=None, apply_bg_sub=False,
                                     n_fft=n_fft, min_freq_mhz=huge_floor)
        assert not collapsed.any(), \
            f"n_fft={n_fft}: floor above Nyquist should collapse to 0 MHz"
 def test_nomask_equals_low_threshold(tmp_path):
    """dc_threshold_mv=None must equal a threshold below every pixel, while
    skipping the CH4 read."""
    path = tmp_path / "nomask.sras"
    gen.write(path, n_angles=2, seed=4, samples_per_frame=128)
    sras = SrasFile(str(path))
    for a in range(sras.n_angles):
        none_img = compute_rf_image(sras, a, dc_threshold_mv=None, apply_bg_sub=True)
        low_img = compute_rf_image(sras, a, dc_threshold_mv=-1e9, apply_bg_sub=True)
        assert np.array_equal(none_img, low_img), \
            f"angle {a}: None == -1e9 threshold"
        assert len(np.unique(none_img)) > 1, \
            f"angle {a}: image is degenerate ({len(np.unique(none_img))} unique)"
 def test_roi_mask():
    """The bbox-restricted mask must equal a full-grid point-in-polygon test."""
    from matplotlib.path import Path as MplPath
    from sras_viewer import RoiQuad
    rng = np.random.default_rng(0)
    x = np.linspace(-2.0, 3.0, 137)
    y = np.linspace(1.0, 4.0, 91)
    cases = {
        "axis-aligned rect": np.array([[0.0, 1.5], [1.0, 1.5], [1.0, 3.0], [0.0, 3.0]]),
        "skewed quad": np.array([[-0.5, 1.2], [1.7, 1.9], [1.2, 3.4], [-1.0, 2.6]]),
        "entirely outside": np.array([[8.0, 8.0], [9.0, 8.0], [9.0, 9.0], [8.0, 9.0]]),
        "covers whole grid": np.array([[-9.0, -9.0], [9.0, -9.0], [9.0, 9.0], [-9.0, 9.0]]),
        "straddles left edge": np.array([[-4.0, 2.0], [0.5, 2.0], [0.5, 3.0], [-4.0, 3.0]]),
    }
    for _ in range(5):
        cases[f"random {_}"] = rng.uniform([-2.5, 0.5], [3.5, 4.5], size=(4, 2))
    for name, pts in cases.items():
        roi = RoiQuad(pts)
        fast = roi.mask_for_grid(x, y)
        X, Y = np.meshgrid(x.astype(np.float64), y.astype(np.float64))
        slow = MplPath(pts).contains_points(
            np.column_stack([X.ravel(), Y.ravel()])).reshape(X.shape)
        assert np.array_equal(fast, slow), f"{name} ({int(slow.sum())} px inside)"
    # Descending y axis (images are stored top-down in some scans).
    roi = RoiQuad(cases["skewed quad"])
    y_desc = y[::-1]
    fast = roi.mask_for_grid(x, y_desc)
    X, Y = np.meshgrid(x.astype(np.float64), y_desc.astype(np.float64))
    slow = MplPath(cases["skewed quad"]).contains_points(
        np.column_stack([X.ravel(), Y.ravel()])).reshape(X.shape)
    assert np.array_equal(fast, slow), "descending y axis"
 def test_legacy_parse(tmp_path):
    """v2-v4 parsing against known written data."""
    for version in (2, 3, 4):
        path = tmp_path / f"legacy_v{version}.sras"
        meta = gen.write_legacy(path, version=version, n_angles=2, n_rows=4,
                                n_frames=12, samples_per_frame=32, seed=version)
        s = SrasFile(str(path))
        assert s.version == version, f"got v{s.version}"
        assert list(s.n_rows) == [4, 4] and list(s.n_frames) == [12, 12], \
            f"rows={list(s.n_rows)} frames={list(s.n_frames)}"
        assert all(np.array_equal(np.asarray(s.data[a]), meta["data"][a])
                   for a in range(s.n_angles)), \
            f"v{version} waveform data matches what was written"
        assert (s.background is not None) == (version >= 4), \
            f"v{version} background {'present' if version >= 4 else 'absent'}"
        assert (isinstance(s.precomputed_freq_mhz, list)
                and len(s.precomputed_freq_mhz) == s.n_angles), \
            f"v{version} precomputed stores are ragged lists"
        # DC image must equal a direct mean of the known input.
        expect = meta["data"][0][:, CH3_IDX, :, :].astype(np.float64).mean(axis=-1)
        assert np.allclose(compute_dc_image(s, 0, CH3_IDX), expect, atol=1e-3), \
            f"v{version} DC image equals a direct mean"
 def test_sras_average(tmp_path):
    """The sras_average.py CLI: v6 frame averaging with remainder handling,
    per-angle ragged geometry, and the laser_freq_hz X-axis correction."""
    src = tmp_path / "v6.sras"
    meta = gen.write(src, n_angles=2, seed=4, samples_per_frame=32,
                     geometry=[(4, 12)])
    src_sras = SrasFile(str(src))
    dst = tmp_path / "v6_avg.sras"
    proc = subprocess.run(
        [sys.executable, str(REPO / "sras_average.py"), str(src), str(dst), "--n", "4"],
        capture_output=True, text=True, cwd=REPO)
    assert proc.returncode == 0, (proc.stderr or proc.stdout).strip()[-200:]
    avg = SrasFile(str(dst))
    assert avg.version == 6
    assert list(avg.n_frames) == [3, 3], f"{list(avg.n_frames)}"
    assert (avg.n_angles == 2 and list(avg.n_rows) == [4, 4]
            and avg.n_channels == src_sras.n_channels == 3)
    assert np.allclose(avg.ch_ymult_mv, src_sras.ch_ymult_mv), \
        "calibration preserved"
    assert np.array_equal(avg.background, src_sras.background), \
        "background preserved"
    assert avg.laser_freq_hz == pytest.approx(src_sras.laser_freq_hz / 4), \
        "laser_freq_hz divided by N keeps pixel_x_mm correct after binning"
    assert np.array_equal(avg.x_start_mm, src_sras.x_start_mm), \
        "per-angle x_start unchanged"
    src_waves = meta["waveforms"]
    # int16 (not float32) before .mean(): matches _average_block's own
    # float64-accumulator behavior for integer input, so this doesn't
    # drift from what _average_block actually guarantees.
    expect0 = src_waves[0][:, :, 0:4, :].astype(np.int16).mean(axis=2).astype(np.int16)
    assert np.array_equal(np.asarray(avg.data[0])[:, :, 0, :], expect0), \
        "first averaged group equals the mean of its 4 source frames"
    # Remainder handling: 12 frames / 5 -> 2 full groups + 1 partial.
    dst2 = tmp_path / "v6_avg5.sras"
    proc2 = subprocess.run([sys.executable, str(REPO / "sras_average.py"),
                            str(src), str(dst2), "--n", "5"],
                           capture_output=True, text=True, cwd=REPO)
    assert proc2.returncode == 0, (proc2.stderr or proc2.stdout).strip()[-200:]
    assert list(SrasFile(str(dst2)).n_frames) == [3, 3], \
        "partial trailing group kept by default"
    dst3 = tmp_path / "v6_avg5d.sras"
    proc3 = subprocess.run([sys.executable, str(REPO / "sras_average.py"),
                            str(src), str(dst3), "--n", "5", "--discard-remainder"],
                           capture_output=True, text=True, cwd=REPO)
    assert proc3.returncode == 0, (proc3.stderr or proc3.stdout).strip()[-200:]
    assert list(SrasFile(str(dst3)).n_frames) == [2, 2], \
        "--discard-remainder drops the partial group"
 def test_sras_average_v7_cache_dropped(tmp_path):
    """A v7 input's cache tail is indexed by frame count, so it's invalid
    after averaging changes that count -- the output must always be plain
    v6, never a v7 carrying a stale cache."""
    src = tmp_path / "v7.sras"
    gen.write(src, n_angles=2, seed=1, samples_per_frame=32, geometry=[(3, 8)])
    src_sras = SrasFile(str(src))
    src_sras.write_v7_cache(
        new_dc3_mv=[compute_dc_image(src_sras, a, CH3_IDX) for a in range(src_sras.n_angles)],
        new_dc4_mv=[compute_dc_image(src_sras, a, CH4_IDX) for a in range(src_sras.n_angles)])
    assert SrasFile(str(src)).version == 7
    dst = tmp_path / "v7_avg.sras"
    proc = subprocess.run(
        [sys.executable, str(REPO / "sras_average.py"), str(src), str(dst), "--n", "2"],
        capture_output=True, text=True, cwd=REPO)
    assert proc.returncode == 0, (proc.stderr or proc.stdout).strip()[-200:]
    assert SrasFile(str(dst)).version == 6, "cache-bearing input still writes plain v6"
 def test_sras_average_rejects_legacy(tmp_path):
    """This tool only speaks v6/v7 now; a legacy file must fail clearly
    rather than being silently misparsed."""
    src = tmp_path / "legacy_v4.sras"
    gen.write_legacy(src, version=4, n_angles=1, n_rows=2, n_frames=8,
                     samples_per_frame=16, seed=0)
    dst = tmp_path / "legacy_v4_avg.sras"
    proc = subprocess.run(
        [sys.executable, str(REPO / "sras_average.py"), str(src), str(dst), "--n", "2"],
        capture_output=True, text=True, cwd=REPO)
    assert proc.returncode != 0
    assert "v6" in proc.stderr and "v7" in proc.stderr
 def test_sras_average_chunking_matches_unchunked(tmp_path):
    """A tiny memory budget (forcing one row per chunk) must produce
    byte-identical output to a huge budget (everything in one chunk) -- the
    load-bearing correctness claim of the memory-bounded rewrite: chunk
    boundaries must never affect the averaged result."""
    src = tmp_path / "v6.sras"
    gen.write(src, n_angles=2, seed=7, samples_per_frame=48,
             geometry=[(6, 10), (5, 13)])
    sras = SrasFile(str(src))
    dst_tiny = tmp_path / "avg_tiny.sras"
    dst_big = tmp_path / "avg_big.sras"
    sras_average.write_v6_averaged(sras, dst_tiny, 3, False, budget=1)
    sras_average.write_v6_averaged(sras, dst_big, 3, False, budget=1 << 30)
    assert dst_tiny.read_bytes() == dst_big.read_bytes(), \
        "chunk size must not affect the averaged output"
 def test_unsupported_version_reported(tmp_path):
    """cache_file must report, not raise, for a file it can't handle."""
    bogus = tmp_path / "bogus.sras"
    bogus.write_bytes(b"SRAS" + bytes([99]) + b"\x00" * 200)
    err = cache_file(str(bogus), "dc", True)
    assert err, "bad version returns an error string"
    missing = cache_file(str(tmp_path / "does_not_exist.sras"), "dc", True)
    assert missing, "missing file returns an error string"
@@ -0,0 +1,75 @@
 """SrasFile.angles_share_raw_grid(): the no-alignment-needed gating path for
 Export Fused ROI.
 A plain multi-angle scan gives each angle its own bounding box and stage
 x_start (scan_format.md's whole reason v6 geometry is per-angle), so it must
 read as "not shareable" without a live alignment. A file the viewer's own
 Alignment Wizard exported repeats one Per-Angle Geometry record and one Row
 Table span for every angle (scan_format.md, "Files written by the viewer's
 Alignment Wizard"), so it must read as "shareable" with no alignment needed
 at all.
 No Qt: this exercises sras_format/sras_compute/sras_align_export directly,
 mirroring tests/test_align_export.py.
 """
 import sras_align_export as export
 import sras_compute as compute
 from sras_format import SrasFile
 import tools.make_test_sras as gen
 _THRESHOLD_MV = 80.0
 def test_single_angle_file_always_shares_its_grid(tmp_path):
    path = tmp_path / "one_angle.sras"
    gen.write(path, n_angles=1)
    sras = SrasFile(str(path))
    assert sras.angles_share_raw_grid()
 def test_plain_multi_angle_file_does_not_share_its_grid(tmp_path):
    """tools.make_test_sras.write gives every angle its own geometry and
    stage x_start (build()'s `x_start = -0.5 + 0.1 * a`), matching how real
    v6 scans vary per angle — so this must read as "not shareable"."""
    path = tmp_path / "plain.sras"
    gen.write(path, n_angles=3)
    sras = SrasFile(str(path))
    assert not sras.angles_share_raw_grid()
 def test_wizard_exported_file_shares_its_grid(tmp_path):
    src_path = tmp_path / "rotating.sras"
    meta = gen.write_rotating(src_path, n_angles=4)
    sras = SrasFile(str(src_path))
    params = {a: compute.ManualAngleParams(rot, shift)
              for a, (rot, shift) in meta["truth"].items()}
    result = compute.build_manual_alignment(sras, 0, _THRESHOLD_MV, params)
    out_path = tmp_path / "rotating_aligned.sras"
    export.write_aligned_sras(sras, result, out_path)
    out = SrasFile(str(out_path))
    assert not sras.angles_share_raw_grid(), (
        "sanity check: the *source* rotating scan must NOT already share a "
        "grid, or this test would not actually exercise the wizard export")
    assert out.angles_share_raw_grid()
 def test_mutated_angle_breaks_the_shared_grid(tmp_path):
    """A loaded SrasFile's x_start_mm is a public per-angle array (as
    tests/test_gui.py::test_alignment_geometry_is_stage_independent also
    relies on) -- mutating one angle's start must be visible here too."""
    src_path = tmp_path / "rotating.sras"
    meta = gen.write_rotating(src_path, n_angles=3)
    sras = SrasFile(str(src_path))
    params = {a: compute.ManualAngleParams(rot, shift)
              for a, (rot, shift) in meta["truth"].items()}
    result = compute.build_manual_alignment(sras, 0, _THRESHOLD_MV, params)
    out_path = tmp_path / "rotating_aligned.sras"
    export.write_aligned_sras(sras, result, out_path)
    out = SrasFile(str(out_path))
    assert out.angles_share_raw_grid()
    out.x_start_mm[1] += 1.0
    assert not out.angles_share_raw_grid()
@@ -0,0 +1,929 @@
 """Headless GUI test: drives SrasViewerWindow through the real Qt widgets,
 signals and worker threads under the offscreen platform plugin.
 Covers the interactions a manual smoke test would: load, switch angles and
 channels, background DC precompute, lazy FFT compute, threshold and bg-sub
 changes, the alignment wizard end to end (pre-rotation, correlation, manual
 nudging, crop, export), aligned view, ROI draw/move, and CSV export.
 NOTE: this module is one ordered integration sequence over a single shared
 window — the tests build on each other's state and must run in definition
 order (pytest's default within a module). Run the whole module, not single
 tests.
 """
 import json
 from types import SimpleNamespace
 from unittest.mock import patch
 import numpy as np
 import pytest
 from PyQt6.QtCore import QEventLoop, Qt, QTimer
 from PyQt6.QtTest import QTest
 from PyQt6.QtWidgets import QApplication, QDialog, QMessageBox
 import sras_compute as compute
 from sras_format import CH1_IDX, CH3_IDX, CH4_IDX, SrasFile
 from sras_viewer import (
    FusedRoiExportDialog, RoiQuad, SrasViewerWindow, VELOCITY_MODE_IDX,
 )
 import tools.make_test_sras as gen
 def pump(ms: int = 250):
    """Run the event loop for a while so queued signals and worker threads
    make progress."""
    loop = QEventLoop()
    QTimer.singleShot(ms, loop.quit)
    loop.exec()
 def wait_until(pred, timeout_ms: int = 20000, step: int = 100) -> bool:
    waited = 0
    while waited < timeout_ms:
        if pred():
            return True
        pump(step)
        waited += step
    return pred()
@pytest.fixture(scope="module")
 def ctx(tmp_path_factory):
    """The shared window, test file, and cross-test state for the sequence."""
    app = QApplication.instance() or QApplication([])
    tmpdir = tmp_path_factory.mktemp("sras_gui")
    path = tmpdir / "gui.sras"
    gen.write(path, n_angles=4, seed=11, samples_per_frame=256)
    win = SrasViewerWindow()
    win.show()
    errors: list[str] = []
    # Capture anything the app reports as an error via the status bar.
    win.statusBar().messageChanged.connect(
        lambda m: errors.append(m) if m and "error" in m.lower() else None)
    c = SimpleNamespace(app=app, win=win, path=path, tmpdir=tmpdir,
                        errors=errors, s=None)
    yield c
    if win.isVisible():
        win.close()
        pump(400)
 def test_load(ctx):
    win = ctx.win
    win._load_file(str(ctx.path))
    assert wait_until(lambda: win._sras is not None), "file loaded"
    ctx.s = s = win._sras
    assert s.version == 6, f"v{s.version}"
    assert win.combo_channel.currentIndex() == CH4_IDX, "defaults to CH4"
    assert win._current_image is not None, "image displayed"
    assert win.spin_angle.maximum() == s.n_angles - 1, \
        "angle spinbox ranges over all angles"
    assert win._info["Angles"].text() == f"Angles: {s.n_angles}", \
        win._info["Angles"].text()
 def test_dc_precompute_all_angles(ctx):
    win, s = ctx.win, ctx.s
    ok = wait_until(lambda: all((a, CH4_IDX) in win._dc_cache
                                and (a, CH3_IDX) in win._dc_cache
                                for a in range(s.n_angles)))
    assert ok, f"every angle cached for CH3 and CH4 ({len(win._dc_cache)} entries)"
    assert "ready for all angles" in win.lbl_dc_precompute.text(), \
        win.lbl_dc_precompute.text()
 def test_angle_switching_from_cache(ctx):
    win, s = ctx.win, ctx.s
    for a in range(s.n_angles):
        win.spin_angle.setValue(a)
        win._on_view_changed()
        pump(60)
        expected = win._sras.image_shape(a)
        assert win._current_image.shape == expected, \
            f"angle {a} shows its own geometry {expected}, got {win._current_image.shape}"
    assert not win._job_running("compute"), \
        "no compute job needed for cached DC angles"
 def test_stepping_the_angle_spinbox_redraws(ctx):
    """Clicking the angle spinbox's arrows (or pressing Up/Down in it) must
    move the display, not just the number.
    This is the ordinary way to walk a scan, and it used to do nothing: the
    spinbox was wired on editingFinished, which QAbstractSpinBox emits only
    on Return or focus-out — never on a step. Every other test in this module
    called _on_view_changed() by hand and so could not have caught it.
    """
    win, s = ctx.win, ctx.s
    assert s.n_angles >= 3, "need room to step in both directions"
    win.spin_angle.setValue(0)
    assert wait_until(lambda: win._current_angle == 0), "settled on angle 0"
    for expected in range(1, s.n_angles):
        win.spin_angle.stepUp()
        assert wait_until(lambda e=expected: win._current_angle == e), \
            f"stepping up to angle {expected} redrew the display"
    win.spin_angle.stepDown()
    assert wait_until(lambda: win._current_angle == s.n_angles - 2), \
        "stepping down redraws too"
    # Keyboard stepping goes through the same signal, so it must work as well.
    QTest.keyClick(win.spin_angle, Qt.Key.Key_Down)
    assert wait_until(lambda: win._current_angle == s.n_angles - 3), \
        "Key_Down redraws"
    win.spin_angle.setValue(0)
    assert wait_until(lambda: win._current_angle == 0), "back to angle 0"
 def test_typing_an_angle_does_not_compute_intermediate_angles(ctx):
    """Keyboard tracking must stay off: with it on, valueChanged fires per
    keystroke, so typing "12" would dispatch a compute for angle 1 first —
    on a real scan, a whole wasted FFT for an angle the user never asked for.
    """
    win, s = ctx.win, ctx.s
    assert not win.spin_angle.keyboardTracking(), \
        "keyboard tracking off is what makes valueChanged safe to connect"
    target = s.n_angles - 1
    assert target >= 2, "need a multi-digit-ish range to make the point"
    win.spin_angle.setValue(0)
    wait_until(lambda: win._current_angle == 0)
    seen = []
    win.spin_angle.valueChanged.connect(seen.append)
    try:
        win.spin_angle.lineEdit().selectAll()
        QTest.keyClicks(win.spin_angle, str(target))
        pump(60)
        assert seen == [], f"no signal while typing, got {seen}"
        QTest.keyClick(win.spin_angle, Qt.Key.Key_Return)
        pump(60)
        assert seen == [target], f"one signal on commit, got {seen}"
    finally:
        win.spin_angle.valueChanged.disconnect(seen.append)
    assert wait_until(lambda: win._current_angle == target), "committed angle shown"
    win.spin_angle.setValue(0)
    assert wait_until(lambda: win._current_angle == 0), "back to angle 0"
 def test_channel_switching(ctx):
    win = ctx.win
    win.spin_angle.setValue(0)
    win._on_view_changed()
    pump(60)
    win.combo_channel.setCurrentIndex(CH3_IDX)
    assert wait_until(lambda: win._current_ch == CH3_IDX), "CH3 displayed"
    win.combo_channel.setCurrentIndex(CH1_IDX)
    assert wait_until(
        lambda: win._current_ch == CH1_IDX and not win._job_running("compute")), \
        "CH1 (FFT) computed"
    assert len(win._fft_cache) > 0, "FFT result cached"
    ctx.rf_img = win._current_image
    assert len(np.unique(ctx.rf_img)) > 1, \
        f"FFT image is degenerate ({len(np.unique(ctx.rf_img))} unique values)"
 def test_velocity_mode(ctx):
    """Velocity mode is a pure post-multiply, no recompute."""
    win = ctx.win
    ctx.n_fft_before = len(win._fft_cache)
    win.combo_channel.setCurrentIndex(VELOCITY_MODE_IDX)
    assert wait_until(
        lambda: win._current_ch == VELOCITY_MODE_IDX
        and not win._job_running("compute")), "velocity displayed"
    grating = win.spin_grating_um.value()
    assert np.allclose(win._current_image, ctx.rf_img * grating, atol=1e-3), \
        "velocity == freq x grating"
    assert len(win._fft_cache) == ctx.n_fft_before, \
        f"velocity reused the cached FFT ({ctx.n_fft_before} -> {len(win._fft_cache)})"
    assert win.grp_velocity.isVisible(), "grating spinbox visible in velocity mode"
 def test_threshold_change_recomputes(ctx):
    """A threshold change is a genuine cache-key change."""
    win = ctx.win
    win.combo_channel.setCurrentIndex(CH1_IDX)
    wait_until(lambda: not win._job_running("compute"))
    dc4 = win._dc_cache[(0, CH4_IDX)]
    win.spin_threshold_mv.setValue(float(np.median(dc4)))
    win._on_threshold_changed()
    assert wait_until(
        lambda: not win._job_running("compute")
        and len(win._fft_cache) > ctx.n_fft_before), "recomputed at new threshold"
    n_zero = int((win._current_image == 0).sum())
    assert n_zero > 0, \
        f"masking zeroed some pixels ({n_zero} of {win._current_image.size})"
 def test_highlight_masked_pixels(ctx):
    """Masked (below-threshold) pixels are drawn as NaN - filled with a
    highlight color, separate from the normal colormap - so they can't be
    mistaken for a real, possibly-low-frequency pixel; unchecking restores
    the old behavior where both blend into the same plain 0."""
    win = ctx.win
    assert win.chk_highlight_masked.isChecked(), "on by default"
    dc4 = win._dc_cache[(0, CH4_IDX)]
    expect_masked = dc4 < win.spin_threshold_mv.value()
    assert expect_masked.any() and not expect_masked.all(), \
        "fixture threshold should mask some but not all pixels"
    calls = []
    orig = win.image_canvas.show_image
    def spy(img, *a, **kw):
        calls.append((np.array(img, copy=True), kw.get("bad_color")))
        return orig(img, *a, **kw)
    with patch.object(win.image_canvas, "show_image", side_effect=spy):
        win._redraw_image(win._current_image)
    shown, bad_color = calls[-1]
    assert bad_color is not None, "highlight color set while checkbox is on"
    # The highlight masks by value too: in an FFT mode, exactly 0 is the
    # "no valid peak" sentinel (DC-masked, below the min-freq floor, or an
    # empty spectrum), so the NaN set is the union of the DC mask and the
    # zero-valued pixels. On this fixture every above-threshold pixel has a
    # nonzero peak, so the union equals the DC mask alone.
    expect_nan = expect_masked | (win._current_image == 0)
    assert np.array_equal(np.isnan(shown), expect_nan), \
        "NaN where DC4 is below threshold or the value-0 sentinel, nowhere else"
    assert np.array_equal(expect_nan, expect_masked), \
        "fixture precondition: every valid pixel has a nonzero peak"
    win.chk_highlight_masked.setChecked(False)
    calls.clear()
    with patch.object(win.image_canvas, "show_image", side_effect=spy):
        win._redraw_image(win._current_image)
    shown2, bad_color2 = calls[-1]
    assert bad_color2 is None, "no highlight color once unchecked"
    assert not np.isnan(shown2).any(), "unchecked: no pixel pulled out to NaN"
    assert np.array_equal(shown2, win._current_image), \
        "unchecked: displayed array is the raw, unmodified image"
    win.chk_highlight_masked.setChecked(True)
    pump(60)
 def test_bg_sub_toggle(ctx):
    """bg-sub no longer gates the display: it only affects a future live
    compute for an angle with nothing cached yet, or an explicit batch
    recompute. Toggling it on an angle that already has an FFT image must
    leave that image on screen, untouched."""
    win = ctx.win
    n_before = len(win._fft_cache)
    img_before = win._current_image
    win.chk_bg_sub.setChecked(False)
    pump(200)
    assert not win._job_running("compute"), \
        "toggling bg-sub alone must not dispatch a recompute"
    assert len(win._fft_cache) == n_before, "no new cache entry from the toggle"
    assert np.array_equal(win._current_image, img_before), \
        "displayed image unchanged by the bg-sub toggle"
    win.chk_bg_sub.setChecked(True)
    pump(200)
    assert not win._job_running("compute")
    assert len(win._fft_cache) == n_before
    assert np.array_equal(win._current_image, img_before)
 def test_roi_and_csv_export(ctx):
    win, s = ctx.win, ctx.s
    x = s.x_axis_mm(0)
    y = s.y_positions_mm(0)
    roi = RoiQuad.from_bbox(float(x[1]), float(y[1]),
                            float(x[-2]), float(y[-2]))
    win.image_canvas.set_roi(roi)
    pump(120)
    assert win.image_canvas.get_roi() is not None, "ROI registered"
    assert ("pixels inside" in win.lbl_roi_npix.text()
            and win.lbl_roi_npix.text() != "pixels inside: —"), \
        win.lbl_roi_npix.text()
    npix = int(win.lbl_roi_npix.text().split(":")[1])
    assert 0 < npix <= win._current_image.size, f"{npix}"
    assert win.btn_export_roi.isEnabled(), "Export ROI enabled"
    csv_path = ctx.tmpdir / "roi.csv"
    with patch("sras_viewer.main_window.QFileDialog.getSaveFileName",
               return_value=(str(csv_path), "")):
        win._on_export_roi_csv()
    assert csv_path.exists(), "ROI CSV written"
    body = [l for l in csv_path.read_text().splitlines() if not l.startswith("#")]
    assert len(body) == npix + 1, \
        f"ROI CSV has {len(body)} lines for {npix} pixels (want header + one per pixel)"
    img_csv = ctx.tmpdir / "img.csv"
    with patch("sras_viewer.main_window.QFileDialog.getSaveFileName",
               return_value=(str(img_csv), "")):
        win._on_export_csv()
    assert img_csv.exists(), "image CSV written"
    arr = np.loadtxt(img_csv, delimiter=",")
    assert (arr.shape == win._current_image.shape
            and np.allclose(arr, win._current_image, rtol=1e-5, atol=1e-4)), \
        "image CSV round-trips the displayed image"
 def test_roi_survives_switches(ctx):
    win = ctx.win
    win.spin_angle.setValue(1)
    win._on_view_changed()
    wait_until(lambda: not win._job_running("compute"))
    assert win.image_canvas.get_roi() is not None, \
        "ROI still present after angle switch"
    win.combo_channel.setCurrentIndex(CH4_IDX)
    wait_until(lambda: win._current_ch == CH4_IDX)
    assert win.image_canvas.get_roi() is not None, \
        "ROI still present after channel switch"
 def test_alignment_geometry_is_stage_independent(ctx):
    """Local mm is anchored on each angle's array center, not its stage
    position: that is what makes a scan's placement independent of where its
    window happened to sit. (Registration accuracy itself is covered by
    tests/test_alignment.py, which has a synthetic sample to register.)"""
    win, s = ctx.win, ctx.s
    win.spin_angle.setValue(0)
    win._on_view_changed()
    wait_until(lambda: not win._job_running("compute"))
    assert win._wizard_act.isEnabled(), "alignment wizard action enabled"
    n_rows, n_frames = s.image_shape(0)
    assert np.allclose(compute._center_idx(s, 0),
                       [(n_rows - 1) / 2, (n_frames - 1) / 2]), \
        "array center is the geometric center of the pixel grid"
    dx0, dy0 = compute.pixel_pitch_mm(s, 0)
    assert np.allclose(compute._local_half_extent_mm(s, 0),
                       [(n_frames - 1) / 2 * abs(dx0), (n_rows - 1) / 2 * abs(dy0)]), \
        "local half-extent is derived from shape and pitch alone"
    identity = {a: compute.ManualAngleParams() for a in range(s.n_angles)}
    origin_a, shape_a = compute.canvas_for_params(s, 0, (dx0, dy0), identity)
    moved = SrasFile(str(ctx.path))
    for a in range(1, moved.n_angles):
        moved.x_start_mm[a] += 7.5
        moved.y_pos_per_angle[a] = moved.y_pos_per_angle[a] + 3.25
    origin_b, shape_b = compute.canvas_for_params(moved, 0, (dx0, dy0), identity)
    assert shape_a == shape_b and np.allclose(origin_a, origin_b), \
        ("moving every non-reference angle's scan window must leave the canvas "
         f"unchanged: {origin_a} {shape_a} vs {origin_b} {shape_b}")
    # Both signs of the stage's reported angle are searched by default.
    cands = compute._rotation_candidates(30.0, 6.0, 2.0)
    assert min(cands) < -29.0 and max(cands) > 29.0, f"{min(cands)}..{max(cands)}"
    # Whole-pixel translation must not wrap content around the edge.
    arr = np.zeros((6, 6), dtype=np.float32)
    arr[0, 0] = 1.0
    assert compute._shift_into(arr, -1, -1).sum() == 0.0, \
        "_shift_into zero-fills rather than wrapping"
    assert compute._shift_into(arr, 2, 3)[2, 3] == 1.0, \
        "_shift_into moves content by exactly the requested offset"
 def test_wizard_opens_prerotated(ctx):
    """The wizard shows a mask stack before any correlation has run, built from
    the stage angles in the file — the "pre-rotate" step. Nothing may seed from
    the still-live automatic result; only a saved sidecar."""
    win, s = ctx.win, ctx.s
    win._on_alignment_wizard()
    assert win._align_wizard is not None, "wizard opened"
    ctx.wiz = wiz = win._align_wizard
    ctx.p1 = p1 = wiz.page(wiz.PAGE_CORRELATE)
    assert not win._job_running("align_masks"), \
        "mask prep needed no background worker (already DC-cached)"
    assert wait_until(lambda: p1.isComplete()), "masks ready, Next enabled"
    assert not win._wizard_act.isEnabled(), \
        "wizard action disabled while a wizard is open"
    st = wiz.state
    assert st.result is not None, "an AlignmentResult exists from pre-rotation alone"
    assert st.counts is not None and st.counts.shape == st.preview_shape
    assert 0 <= st.counts.max() <= s.n_angles
    assert not st.fits, "no fits before a correlation has run"
    for a in range(s.n_angles):
        nominal = compute.nominal_delta_deg(s, a, st.ref_angle_idx)
        expected = 0.0 if a == st.ref_angle_idx else nominal
        assert abs(st.params[a].rotation_deg - expected) < 1e-9, \
            f"angle {a} not pre-rotated to its stage angle"
        assert st.params[a].shift_mm == (0.0, 0.0), \
            "pre-rotation must not invent a translation"
 def test_wizard_reference_angle_is_locked(ctx):
    p1, wiz = ctx.p1, ctx.wiz
    p1.combo_active.setCurrentIndex(wiz.state.ref_angle_idx)
    pump(30)
    before = wiz.state.params[wiz.state.ref_angle_idx]
    p1._on_nudge_translate(1, 0, False)
    p1._on_nudge_rotate(1, False)
    assert wiz.state.params[wiz.state.ref_angle_idx] == before, \
        "reference angle untouched by nudge attempts"
 def test_wizard_nudges(ctx):
    """Manual correction, which the wizard absorbed from the old dialog."""
    p1, wiz, s = ctx.p1, ctx.wiz, ctx.s
    ctx.active = active = 1 if s.n_angles > 1 else 0
    p1.combo_active.setCurrentIndex(active)
    pump(30)
    before = wiz.state.params[active].shift_mm
    p1._on_nudge_translate(1, 0, False)
    fine = p1.spin_step_translate.value()
    assert abs(wiz.state.params[active].shift_mm[0] - (before[0] + fine)) < 1e-9, \
        "fine translate nudge moved shift_x by exactly one fine step"
    before = wiz.state.params[active].shift_mm
    p1._on_nudge_translate(0, -1, True)
    coarse = fine * p1.spin_step_mult.value()
    assert abs(wiz.state.params[active].shift_mm[1] - (before[1] - coarse)) < 1e-9, \
        "coarse translate nudge uses the multiplier"
    before_rot = wiz.state.params[active].rotation_deg
    p1._on_nudge_rotate(1, False)
    assert wiz.state.params[active].rotation_deg != before_rot
    assert len(wiz.state.layers) == s.n_angles, \
        "stack rebuilt for every angle after a rotation nudge"
    # A nudge only reprojects the angle that moved, patching the overlap counts
    # in place. That shortcut is only sound if it lands on exactly what a full
    # rebuild would have produced.
    incremental = wiz.state.counts.copy()
    wiz.rebuild_stack()
    assert np.array_equal(wiz.state.counts, incremental), \
        "incremental nudge update matches a full stack rebuild"
    # Real key-event wiring (keyPressEvent -> signal -> slot).
    before = wiz.state.params[active].shift_mm
    QTest.keyClick(p1.canvas, Qt.Key.Key_Right)
    assert wiz.state.params[active].shift_mm[0] > before[0], \
        "a real Right-arrow key event nudged shift_x"
    # Both views render from the same reprojected layers.
    p1.combo_view.setCurrentIndex(1)
    pump(50)
    p1.combo_view.setCurrentIndex(0)
    pump(50)
 def test_wizard_correlate(ctx):
    """Cross-correlation, for every source option, retryable."""
    win, p1, wiz, s = ctx.win, ctx.p1, ctx.wiz, ctx.s
    from sras_viewer.align_wizard import _CORRELATE_SOURCES
    for idx, (label, _sources) in enumerate(_CORRELATE_SOURCES):
        p1.combo_source.setCurrentIndex(idx)
        p1.btn_correlate.click()
        assert not p1.isComplete(), \
            f"Next must be disabled while correlating ({label})"
        assert wait_until(lambda: not win._job_running("align_correlate"),
                          timeout_ms=60000), f"correlation finished ({label})"
        assert p1.isComplete(), f"Next re-enabled ({label})"
        assert all(a in wiz.state.fits for a in range(s.n_angles)
                   if a != wiz.state.ref_angle_idx), \
            f"every non-reference angle got a fit ({label})"
    assert wiz.state.params[wiz.state.ref_angle_idx] == compute.ManualAngleParams(), \
        "reference angle stays identity after correlation"
    assert p1.btn_correlate.isEnabled(), "controls re-enabled when done"
    assert p1.table.rowCount() == s.n_angles and p1.table.item(0, 0) is not None, \
        "per-angle fit table populated"
    assert p1.lbl_overlap.text(), "overlap summary reported"
    r = wiz.state.result
    assert len(r.per_angle) == s.n_angles, "transform for every angle"
    assert r.per_angle[r.ref_angle_idx].shift_mm == (0.0, 0.0), \
        "reference angle has zero shift"
 def test_wizard_retry_changes_geometry(ctx):
    """Editing a parameter and re-running is the retry path, and it must
    invalidate anything indexed against the old canvas."""
    p1, wiz = ctx.p1, ctx.wiz
    gen_before = wiz.state.geometry_generation
    p1.spin_threshold.setValue(p1.spin_threshold.value() + 5.0)
    p1.spin_threshold.editingFinished.emit()
    pump(60)
    assert wiz.state.geometry_generation > gen_before, \
        "a threshold change rebuilt the geometry"
    # Reset drops the fits and returns to pre-rotation only.
    p1.btn_reset.click()
    pump(60)
    assert not wiz.state.fits, "reset cleared the fits"
    nominal = compute.nominal_delta_deg(ctx.s, ctx.active, wiz.state.ref_angle_idx)
    assert abs(wiz.state.params[ctx.active].rotation_deg - nominal) < 1e-9
    assert wiz.state.params[ctx.active].shift_mm == (0.0, 0.0), \
        "reset also drops nudged translation"
    # Put a real correlation back for the pages that follow.
    p1.btn_correlate.click()
    assert wait_until(lambda: not ctx.win._job_running("align_correlate"),
                      timeout_ms=60000)
 def test_wizard_roi_page(ctx):
    """The crop page: presets, and two-way sync between the drawn rectangle and
    the numeric canvas-pixel boxes."""
    wiz = ctx.wiz
    wiz.next()
    pump(150)
    assert wiz.currentId() == wiz.PAGE_ROI, "advanced to the ROI page"
    ctx.p2 = p2 = wiz.page(wiz.PAGE_ROI)
    st = wiz.state
    assert st.crop is not None and p2.isComplete(), \
        "a default crop is offered on entry"
    n_rows, n_cols = st.result.canvas_shape
    assert st.crop[2] > 1 or n_rows == 1, \
        f"default crop must not collapse to a single row: {st.crop}"
    p2.btn_whole.click()
    pump(50)
    assert st.crop == (0, 0, n_rows, n_cols), "whole-canvas preset"
    p2.btn_fit_union.click()
    pump(50)
    assert st.counts[st.crop[0]:st.crop[0] + st.crop[2],
                     st.crop[1]:st.crop[1] + st.crop[3]].sum() == st.counts.sum(), \
        "fit-to-union must keep every covered pixel"
    if p2.btn_fit_overlap.isEnabled():
        p2.btn_fit_overlap.click()
        pump(50)
        row0, col0, nr, nc = st.crop
        assert (st.counts[row0:row0 + nr, col0:col0 + nc] >= 1).all(), \
            "full-overlap crop must not include uncovered pixels"
    # Numeric -> drawn rectangle.
    p2.btn_whole.click()
    pump(50)
    target = (0, 0, max(1, n_rows // 2), max(1, n_cols // 2))
    p2.spin_rows.setValue(target[2])
    p2.spin_cols.setValue(target[3])
    pump(50)
    assert st.crop == target, f"spin boxes drive the crop: {st.crop} vs {target}"
    # Drawn rectangle -> numeric, round-tripping exactly.
    x0, y0 = wiz.canvas_to_mm(target[1] - 0.5, target[0] - 0.5)
    x1, y1 = wiz.canvas_to_mm(target[1] + target[3] - 0.5,
                              target[0] + target[2] - 0.5)
    p2.canvas.set_roi(RoiQuad.from_bbox(min(x0, x1), min(y0, y1),
                                        max(x0, x1), max(y0, y1)))
    pump(80)
    assert st.crop == target, \
        f"drawn rectangle round-trips to the same crop: {st.crop} vs {target}"
    # A degenerate crop blocks Next.
    st.crop = None
    p2.completeChanged.emit()
    assert not p2.isComplete(), "an absent crop blocks Next"
    p2._set_crop(*target)
    assert p2.isComplete()
    ctx.crop = target
 def test_wizard_crop_dropped_when_going_back(ctx):
    """A crop is canvas-pixel indexed, so it cannot survive a re-correlation."""
    wiz, p2 = ctx.wiz, ctx.p2
    wiz.back()
    pump(120)
    assert wiz.currentId() == wiz.PAGE_CORRELATE
    assert wiz.state.crop is None, "cleanupPage discarded the stale crop"
    assert wiz.cropped_plan() == (None, None), \
        "nothing derived from the dropped crop survives either"
    wiz.next()
    pump(150)
    assert wiz.state.crop is not None, "a fresh default crop is offered again"
    p2._set_crop(*ctx.crop)
 def test_wizard_export(ctx):
    """Writing the file: Finish stays unavailable until a write succeeds."""
    win, wiz = ctx.win, ctx.wiz
    out = ctx.tmpdir / "wizard_aligned.sras"
    with patch("sras_viewer.align_wizard.QMessageBox.question",
               return_value=QMessageBox.StandardButton.Yes):
        wiz.next()
        pump(150)
    assert wiz.currentId() == wiz.PAGE_SAVE, "advanced to the save page"
    ctx.p3 = p3 = wiz.page(wiz.PAGE_SAVE)
    cropped, _ = wiz.cropped_plan()
    assert cropped is not None, "crop applied on leaving page 2"
    assert cropped.canvas_shape == ctx.crop[2:], \
        "cropped result carries the chosen shape"
    assert not p3.isComplete(), "Finish unavailable before anything is written"
    assert p3.lbl_summary.text(), "a summary of what will be written is shown"
    with patch("sras_viewer.align_wizard.QFileDialog.getSaveFileName",
               return_value=(str(out), "")):
        p3.btn_browse.click()
    assert wiz.state.out_path == str(out)
    p3.btn_export.click()
    assert wait_until(lambda: not win._job_running("align_export"),
                      timeout_ms=60000), "export finished"
    assert wiz.state.exported_path == str(out), p3.lbl_status.text()
    assert p3.isComplete(), "Finish available once the file exists"
    assert out.exists()
    written = SrasFile(str(out))
    ctx.written = written
    assert written.version == 6, "export is a v6 file"
    assert written.n_angles == ctx.s.n_angles
    assert all(written.image_shape(a) == ctx.crop[2:]
               for a in range(written.n_angles)), \
        "every angle shares the cropped grid"
    assert not out.with_name(out.name + ".part").exists(), \
        "no staging file left behind"
 def test_wizard_finish_applies_and_persists(ctx):
    """Finish makes the session match the file: Aligned View shows the exported
    extent, and the sidecar records it for the input scan."""
    win, wiz = ctx.win, ctx.wiz
    wiz.accept()
    pump(250)
    assert win._align_wizard is None, "wizard reference released"
    assert win._wizard_act.isEnabled(), "wizard action available again"
    assert win._alignment_result is not None
    assert win._alignment_result.canvas_shape == ctx.crop[2:], \
        "the *cropped* result is what the view now uses"
    assert win.chk_aligned_view.isEnabled() and win.chk_aligned_view.isChecked()
    pump(200)
    assert win.image_canvas._img_shape == ctx.crop[2:], \
        f"canvas shows the cropped extent: {win.image_canvas._img_shape}"
    sidecar = compute.sidecar_path(ctx.s.path)
    assert sidecar.exists(), "sidecar written for the input scan"
    ctx.sidecar = sidecar
    ctx.sidecar_raw = raw = json.loads(sidecar.read_text())
    assert raw.get("schema_version") == compute._SIDECAR_SCHEMA_VERSION
    assert all(raw["per_angle"][str(a)]["rotation_deg"]
               == win._alignment_result.per_angle[a].rotation_deg
               for a in range(ctx.s.n_angles)), \
        "sidecar round-trips the applied rotations"
    win.chk_aligned_view.setChecked(False)
    pump(200)
    assert win.image_canvas._img_shape == ctx.s.image_shape(0), \
        f"unchecking returns to the raw per-angle grid: {win.image_canvas._img_shape}"
 def test_stale_schema_sidecar_ignored(ctx):
    """An old-schema sidecar (pre-pivot/sign fix) is treated as absent."""
    s, raw, sidecar = ctx.s, ctx.sidecar_raw, ctx.sidecar
    stale = dict(raw)
    stale["schema_version"] = compute._SIDECAR_SCHEMA_VERSION - 1
    sidecar.write_text(json.dumps(stale))
    assert compute.load_manual_alignment(s) is None, \
        "a sidecar with an old schema_version is not loaded"
    sidecar.write_text(json.dumps(raw))   # restore for the rest of the sequence
 def test_sidecar_restored_on_reload(ctx):
    win, active = ctx.win, ctx.active
    saved = json.loads(ctx.sidecar.read_text())["per_angle"][str(active)]
    old_sras_id = id(win._sras)
    win._load_file(str(ctx.path))   # reload the same file fresh
    assert wait_until(
        lambda: win._sras is not None and id(win._sras) != old_sras_id), \
        "file reloaded"
    ctx.s = win._sras
    assert win._align_wizard is None, "no wizard left open across a reload"
    assert win._alignment_result is not None, \
        "reload restores the saved alignment automatically"
    assert abs(win._alignment_result.per_angle[active].rotation_deg
               - saved["rotation_deg"]) < 1e-9, \
        "restored rotation matches what was saved"
    assert win.chk_aligned_view.isChecked(), \
        "Aligned View auto-checked after restoring a saved alignment"
 def test_wizard_closes_with_a_reload(ctx):
    """An open wizard belongs to the file it was opened on."""
    win = ctx.win
    win._on_alignment_wizard()
    assert win._align_wizard is not None
    assert wait_until(
        lambda: win._align_wizard.page(win._align_wizard.PAGE_CORRELATE).isComplete())
    win._load_file(str(ctx.path))
    assert wait_until(lambda: not win._job_running("load"))
    pump(200)
    assert win._align_wizard is None, "wizard force-closed by a reload"
    ctx.s = win._sras
 # ---------------------------------------------------------------------------
 # Export Fused ROI
 # ---------------------------------------------------------------------------
 #
 # Two independent ways angles can end up sharing one (x, y) grid to fuse
 # onto: a live alignment result (case a, exercised on ctx.win -- the reload
 # above restored one from the sidecar), or a file that is itself a previous
 # Alignment Wizard export, whose angles already share a grid on disk with no
 # alignment result needed at all (case b, exercised on a second window
 # opened on ctx.written from test_wizard_export).
 def test_fused_export_gating_case_a(ctx):
    """A live alignment result bridges the raw scan's per-angle grids --
    angles_share_raw_grid() alone would be False here."""
    win, s = ctx.win, ctx.s
    assert win._alignment_result is not None, "alignment restored from sidecar"
    assert not s.angles_share_raw_grid(), \
        "sanity check: the raw (un-aligned) scan must not already share a grid"
    x, y = win._aligned_canvas_axes()
    roi = RoiQuad.from_bbox(float(x[1]), float(y[1]), float(x[-2]), float(y[-2]))
    win.image_canvas.set_roi(roi)
    pump(120)
    assert win._fused_grid_ready()
    assert win.btn_export_fused_roi.isEnabled()
 def test_write_fused_roi_csv_case_a_content(ctx):
    win, s = ctx.win, ctx.s
    roi = win.image_canvas.get_roi()
    assert roi is not None, "ROI drawn by test_fused_export_gating_case_a"
    csv_path = ctx.tmpdir / "fused_roi_case_a.csv"
    win._write_fused_roi_csv(roi, CH4_IDX, [0, 1], str(csv_path))
    assert csv_path.exists()
    lines = csv_path.read_text().splitlines()
    body = [l for l in lines if not l.startswith("#")]
    header, *data_lines = body
    assert header == (
        f"x_mm,y_mm,v_{s.angles_deg[0]:.4g}deg,v_{s.angles_deg[1]:.4g}deg")
    x, y = win._fused_export_axes()
    mask = roi.mask_for_grid(x, y)
    assert len(data_lines) == int(mask.sum())
    data = np.array([[float(v) for v in line.split(",")] for line in data_lines])
    expect0 = win._fused_value_image(0, CH4_IDX)[mask]
    expect1 = win._fused_value_image(1, CH4_IDX)[mask]
    assert np.allclose(data[:, 2], expect0, rtol=1e-5, atol=1e-4)
    assert np.allclose(data[:, 3], expect1, rtol=1e-5, atol=1e-4)
 def test_fused_roi_dialog_availability_live_updates(ctx):
    """Switching the value-type radio re-evaluates every angle checkbox,
    disabling/auto-unchecking whichever ones are no longer available --
    independent of what actually backs availability_fn, so a synthetic
    stand-in keeps this a fast, deterministic test of the dialog itself."""
    win, s = ctx.win, ctx.s
    angles = [(a, float(s.angles_deg[a])) for a in range(s.n_angles)]
    only_angle0_has_ch1 = lambda a, c: (a == 0) if c == CH1_IDX else True
    dlg = FusedRoiExportDialog(
        win, angles=angles, availability_fn=only_angle0_has_ch1,
        default_ch_idx=CH1_IDX, out_dir=str(s.path.parent), stem=s.path.stem,
        grid_note="test")
    try:
        assert dlg._angle_checks[0].isEnabled()
        assert all(not dlg._angle_checks[a].isEnabled()
                   for a in range(1, s.n_angles))
        dlg._angle_checks[0].setChecked(True)
        dlg._val_buttons[CH4_IDX].click()
        assert all(dlg._angle_checks[a].isEnabled() for a in range(s.n_angles)), \
            "CH4 is available for every angle"
        assert dlg._angle_checks[0].isChecked(), \
            "stays checked -- still available under CH4"
        if s.n_angles > 1:
            dlg._angle_checks[1].setChecked(True)
        dlg._val_buttons[CH1_IDX].click()
        assert dlg._angle_checks[0].isChecked()
        if s.n_angles > 1:
            assert not dlg._angle_checks[1].isEnabled()
            assert not dlg._angle_checks[1].isChecked(), \
                "auto-unchecked: angle 1 has no data under CH1"
    finally:
        dlg.close()
 def test_fused_roi_dialog_select_all_none(ctx):
    win, s = ctx.win, ctx.s
    angles = [(a, float(s.angles_deg[a])) for a in range(s.n_angles)]
    dlg = FusedRoiExportDialog(
        win, angles=angles, availability_fn=lambda a, c: c == CH4_IDX,
        default_ch_idx=CH4_IDX, out_dir=str(s.path.parent), stem=s.path.stem,
        grid_note="test")
    try:
        assert not dlg._btn_export.isEnabled(), "nothing checked yet"
        dlg._on_select_all_available()
        assert all(cb.isChecked() for cb in dlg._angle_checks.values())
        assert dlg._btn_export.isEnabled()
        dlg._on_select_none()
        assert not any(cb.isChecked() for cb in dlg._angle_checks.values())
        assert not dlg._btn_export.isEnabled()
    finally:
        dlg.close()
 def test_on_export_fused_roi_csv_end_to_end(ctx):
    win, s = ctx.win, ctx.s
    roi = win.image_canvas.get_roi()
    assert roi is not None, "ROI from the earlier fused-export tests is still set"
    csv_path = ctx.tmpdir / "fused_roi_e2e.csv"
    with patch("sras_viewer.main_window.FusedRoiExportDialog") as MockDlg:
        inst = MockDlg.return_value
        inst.exec.return_value = QDialog.DialogCode.Accepted
        inst.get_ch_idx.return_value = CH4_IDX
        inst.get_selected_angles.return_value = [0, 1]
        inst.get_output_path.return_value = str(csv_path)
        win.btn_export_fused_roi.click()
    assert csv_path.exists()
    kwargs = MockDlg.call_args.kwargs
    assert kwargs["default_ch_idx"] == win.combo_channel.currentIndex()
    assert kwargs["out_dir"] == str(s.path.parent)
    assert kwargs["stem"] == s.path.stem
 def test_fused_export_no_alignment_shared_grid_path(ctx):
    """ctx.written (from test_wizard_export) is itself a previous Alignment
    Wizard export: opened fresh with no sidecar for its own path, so no
    alignment result is ever restored -- but its angles already share one
    grid on disk, so the export must work through the no-resample path."""
    win2 = SrasViewerWindow()
    try:
        win2._load_file(str(ctx.written.path))
        assert wait_until(lambda: win2._sras is not None)
        s2 = win2._sras
        assert win2._alignment_result is None, \
            "no sidecar exists for this path -- nothing auto-restored"
        assert s2.angles_share_raw_grid(), \
            "a wizard export already shares one grid across angles"
        assert wait_until(lambda: all((a, CH4_IDX) in win2._dc_cache
                                      for a in range(s2.n_angles))), \
            "DC precomputed for every angle"
        x, y = s2.x_axis_mm(0), s2.y_positions_mm(0)
        roi = RoiQuad.from_bbox(float(x[1]), float(y[1]), float(x[-2]), float(y[-2]))
        win2.image_canvas.set_roi(roi)
        pump(120)
        assert win2._fused_grid_ready()
        assert win2.btn_export_fused_roi.isEnabled()
        aligned_cache_before = len(win2._aligned_cache)
        angle_idxs = list(range(min(2, s2.n_angles)))
        csv_path = ctx.tmpdir / "fused_roi_case_b.csv"
        win2._write_fused_roi_csv(roi, CH4_IDX, angle_idxs, str(csv_path))
        assert csv_path.exists()
        assert len(win2._aligned_cache) == aligned_cache_before, \
            "no-resample path must never touch apply_alignment"
        header = next(l for l in csv_path.read_text().splitlines()
                     if not l.startswith("#"))
        expected_header = "x_mm,y_mm," + ",".join(
            f"v_{s2.angles_deg[a]:.4g}deg" for a in angle_idxs)
        assert header == expected_header
        # Break the shared grid and confirm gating flips off.
        mutate_idx = 1 if s2.n_angles > 1 else 0
        s2.x_start_mm[mutate_idx] += 1.0
        assert not s2.angles_share_raw_grid()
        win2._update_fused_export_enabled()
        assert not win2._fused_grid_ready()
        assert not win2.btn_export_fused_roi.isEnabled()
        assert "Alignment Wizard" in win2.btn_export_fused_roi.toolTip()
    finally:
        win2.close()
        pump(200)
 def test_pixel_inspector(ctx):
    win = ctx.win
    win.chk_aligned_view.setChecked(False)
    pump(100)
    win._on_pixel_clicked(0, 0)
    pump(150)
    assert win.lbl_wave_hint.isHidden(), "waveform hint hidden after a click"
    win.combo_channel.setCurrentIndex(CH1_IDX)
    wait_until(lambda: not win._job_running("compute"))
    win._on_pixel_clicked(1, 1)
    pump(150)
    assert len(win.wave_canvas.ax_wave.lines) > 0, \
        f"RF waveform panel rendered ({len(win.wave_canvas.ax_wave.lines)} lines)"
 def test_shutdown(ctx):
    win = ctx.win
    win.close()
    pump(400)
    assert len(win._jobs) == 0, f"all background jobs released: {list(win._jobs)}"
 def test_no_status_bar_errors(ctx):
    unexpected = [e for e in ctx.errors if e]
    assert not unexpected, f"status-bar errors seen: {unexpected}"
@@ -0,0 +1,297 @@
 """Row-averaged FFT: same-row, distance-weighted CH1 waveform smoothing.
 Covers the properties the design depends on: the kernel is symmetric and
 n=0 is a true no-op; the masked/renormalized convolution matches an
 independent brute-force reference and gives masked neighbors exactly zero
 weight regardless of their content; background subtraction after averaging
 is algebraically identical to subtracting before; chunking/worker count
 never changes the result; and a pixel that's itself masked is never
 "rescued" by averaging.
 """
 import numpy as np
 import pytest
 import sras_compute as compute
 from sras_compute import compute_rf_image, dc_image_mv
 from sras_format import CH1_IDX, CH4_IDX, SrasFile
 import tools.make_test_sras as gen
 def _reference_row_average(masked_waves: np.ndarray, valid: np.ndarray,
                           weights: np.ndarray) -> np.ndarray:
    """Independent, unvectorized reference for _row_average_waveforms: for
    each row position, sum weighted valid neighbors within the kernel's
    radius and normalize by the actual included weight sum. Same
    definition, computed by brute-force nested loops instead of
    correlate1d, so it can't share a bug with the implementation."""
    n_frames, spf = masked_waves.shape
    n = len(weights) // 2
    out = np.zeros_like(masked_waves)
    for i in range(n_frames):
        num = np.zeros(spf, dtype=np.float64)
        den = 0.0
        for d in range(-n, n + 1):
            j = i + d
            if 0 <= j < n_frames and valid[j]:
                w = float(weights[d + n])
                num += w * masked_waves[j].astype(np.float64)
                den += w
        out[i] = num / den if den > 0 else 0.0
    return out
 # ---------------------------------------------------------------------------
 # _row_average_weights
 # ---------------------------------------------------------------------------
 def test_row_average_weights_shape_and_symmetry():
    w0 = compute._row_average_weights(0)
    assert w0.shape == (1,) and w0[0] == 1.0
    for n in (1, 2, 5):
        w = compute._row_average_weights(n)
        assert w.shape == (2 * n + 1,)
        assert w[n] == pytest.approx(1.0), "center tap is the peak weight"
        assert np.allclose(w, w[::-1]), "symmetric about the center"
        half = w[n:]
        assert np.all(np.diff(half) < 0), "strictly decreasing away from center"
 # ---------------------------------------------------------------------------
 # _row_average_waveforms
 # ---------------------------------------------------------------------------
 def test_row_average_matches_hand_rolled_reference():
    rng = np.random.default_rng(0)
    n_frames, spf = 15, 6
    raw = rng.integers(-50, 51, size=(n_frames, spf)).astype(np.float32)
    valid = np.ones(n_frames, dtype=bool)
    valid[[2, 3, 9]] = False   # a run of two invalid, plus a lone invalid
    masked = raw.copy()
    masked[~valid] = 0.0
    weights = compute._row_average_weights(3)
    got = compute._row_average_waveforms(masked, valid, weights)
    ref = _reference_row_average(masked, valid, weights)
    assert np.allclose(got[valid], ref[valid], atol=1e-4)
 def test_row_average_edge_of_row():
    """A window wider than the row itself must still renormalize correctly
    at both ends -- mode='constant', cval=0.0 zero-pads both the numerator
    and denominator, so this is not a special case, but it's the one most
    likely to break if that padding were ever mismatched between the two."""
    n_frames, spf = 6, 3
    raw = np.arange(n_frames * spf, dtype=np.float32).reshape(n_frames, spf)
    valid = np.ones(n_frames, dtype=bool)
    weights = compute._row_average_weights(4)   # window (9 taps) > n_frames (6)
    got = compute._row_average_waveforms(raw, valid, weights)
    ref = _reference_row_average(raw, valid, weights)
    assert np.allclose(got, ref, atol=1e-4)
 def test_row_average_excludes_masked_neighbor_from_normalization():
    """A masked neighbor must contribute zero *weight* to the normalization,
    not participate as a legitimate zero-valued sample at full weight --
    the two give different answers, and only the former is correct. (Note:
    masked_waves must already be 0 at invalid positions per
    _row_average_waveforms's contract -- that's what read_row's zero-filled
    scratch buffer guarantees in production -- so the only way to vary
    "what a masked position looks like" while respecting that contract is
    whether its weight is excluded from the denominator at all.)"""
    n_frames, spf = 9, 4
    weights = compute._row_average_weights(2)
    # A: position 4 is masked -- excluded from the weight sum entirely.
    valid_a = np.ones(n_frames, dtype=bool)
    valid_a[4] = False
    masked_a = np.zeros((n_frames, spf), dtype=np.float32)
    masked_a[valid_a] = 1.0
    got_a = compute._row_average_waveforms(masked_a, valid_a, weights)
    # B: position 4 is valid but genuinely zero-valued -- included in the
    # weight sum, diluting neighbors' averages.
    valid_b = np.ones(n_frames, dtype=bool)
    masked_b = np.ones((n_frames, spf), dtype=np.float32)
    masked_b[4] = 0.0
    got_b = compute._row_average_waveforms(masked_b, valid_b, weights)
    # Every position whose window reaches index 4 must average *higher* in
    # A (excluded from the denominator) than in B (included as a real zero).
    affected = [2, 3, 5, 6]
    assert np.all(got_a[affected] > got_b[affected]), \
        "masking must exclude a neighbor from normalization, not just zero its value"
    # Positions outside the window (radius 2) are unaffected either way.
    assert np.allclose(got_a[[0, 1, 7, 8]], got_b[[0, 1, 7, 8]])
 def test_background_subtracted_once_equals_subtract_then_average():
    """Algebraic identity the implementation relies on: subtracting a fixed
    background from the already-averaged waveform equals subtracting it
    from every valid neighbor first, because the denominator is always the
    *actual* included weight sum (never a fixed total)."""
    rng = np.random.default_rng(1)
    n_frames, spf = 11, 8
    raw = rng.integers(-40, 41, size=(n_frames, spf)).astype(np.float32)
    valid = np.ones(n_frames, dtype=bool)
    valid[[1, 7]] = False
    masked = raw.copy()
    masked[~valid] = 0.0
    background = rng.integers(-5, 6, size=spf).astype(np.float32)
    weights = compute._row_average_weights(3)
    # Order A (what the code does): average first, subtract background once.
    order_a = compute._row_average_waveforms(masked, valid, weights) - background
    # Order B: subtract background from every valid neighbor first (restoring
    # the "0 at invalid positions" contract afterward), then average.
    bg_subbed = masked - background
    bg_subbed[~valid] = 0.0
    order_b = compute._row_average_waveforms(bg_subbed, valid, weights)
    assert np.allclose(order_a[valid], order_b[valid], atol=1e-3)
 # ---------------------------------------------------------------------------
 # compute_rf_image(row_avg_n=...) integration
 # ---------------------------------------------------------------------------
 def test_row_average_zero_is_identity(tmp_path):
    """row_avg_n=0 must take the exact same code path as before this
    feature existed (row_avg_weights stays None), not a single-tap kernel
    that merely computes to the same answer."""
    path = tmp_path / "zero.sras"
    gen.write(path, n_angles=1, seed=10, samples_per_frame=64)
    sras = SrasFile(str(path))
    plain = compute_rf_image(sras, 0, dc_threshold_mv=None, apply_bg_sub=True)
    explicit_zero = compute_rf_image(sras, 0, dc_threshold_mv=None,
                                     apply_bg_sub=True, row_avg_n=0)
    assert np.array_equal(plain, explicit_zero)
 def test_row_average_respects_own_center_mask(tmp_path):
    """A pixel that's itself below threshold stays masked (0) after row
    averaging -- averaging never rescues a masked pixel, matching the
    'valid neighbors only' design (masked pixels are excluded from other
    pixels' averages, and are never themselves smoothed)."""
    path = tmp_path / "center_mask.sras"
    gen.write(path, n_angles=1, seed=13, samples_per_frame=64)
    sras = SrasFile(str(path))
    dc4 = dc_image_mv(sras, 0, CH4_IDX)
    thr = float(np.percentile(dc4, 50))
    mask = dc4 >= thr
    assert mask.any() and not mask.all(), "threshold actually splits the image"
    img = compute_rf_image(sras, 0, dc_threshold_mv=thr, apply_bg_sub=True,
                           row_avg_n=4)
    assert np.array_equal(img == 0, ~mask), \
        "masked pixels stay exactly 0 after row averaging; valid ones don't"
 def test_row_average_composes_with_padding(tmp_path):
    """row_avg_n and n_fft (zero-padding) are independent knobs: using them
    together must not raise, and must agree bit-for-bit with an independent
    reference that row-averages the raw waveforms and background-subtracts
    them, then runs a plain scipy rfft + argmax at the same pad factor --
    i.e. row-averaging composes correctly with the padded peak search."""
    import scipy.fft as scipy_fft
    path = tmp_path / "padded_rowavg.sras"
    gen.write(path, n_angles=1, seed=12, samples_per_frame=64)
    sras = SrasFile(str(path))
    spf = sras.samples_per_frame
    n_rows, n_frames = sras.image_shape(0)
    n_fft = spf * 40
    raw_natural = compute_rf_image(sras, 0, dc_threshold_mv=None, apply_bg_sub=True)
    avg_natural = compute_rf_image(sras, 0, dc_threshold_mv=None, apply_bg_sub=True,
                                   row_avg_n=3)
    avg_padded = compute_rf_image(sras, 0, dc_threshold_mv=None, apply_bg_sub=True,
                                  row_avg_n=3, n_fft=n_fft)
    assert avg_natural.shape == raw_natural.shape == avg_padded.shape
    assert np.all(np.isfinite(avg_padded))
    weights = compute._row_average_weights(3)
    freq32 = sras.freq_axis_mhz(n_fft).astype(np.float32)
    data = sras.data[0]
    expected = np.zeros((n_rows, n_frames), dtype=np.float32)
    for r in range(n_rows):
        v = np.ones(n_frames, dtype=bool)
        avg = compute._row_average_waveforms(
            data[r, CH1_IDX].astype(np.float32), v, weights)
        avg = avg - sras.background
        S = scipy_fft.rfft(avg, n=n_fft, axis=-1, workers=1)
        power = S.real ** 2 + S.imag ** 2
        power[:, 0] = 0.0
        expected[r] = freq32[np.argmax(power, axis=1)]
    assert np.array_equal(avg_padded, expected), \
        "row-averaged waveforms feed the padded peak search identically " \
        "to an independent reference"
 def test_row_average_improves_snr_recovery():
    """The actual point of the feature: averaging same-row waveforms that
    share a true underlying tone but carry independent noise recovers that
    tone far more reliably than any single raw (unaveraged) waveform does."""
    rng = np.random.default_rng(42)
    n_frames, spf = 21, 128
    true_bin = 9
    t = np.arange(spf)
    tone = 15.0 * np.sin(2 * np.pi * true_bin * t / spf)   # same true signal
                                                             # at every position
    noise_sigma = 40.0   # much larger than the tone -- deliberately poor SNR
    raw = (tone[None, :] + rng.normal(scale=noise_sigma, size=(n_frames, spf))
          ).astype(np.float32)
    valid = np.ones(n_frames, dtype=bool)
    weights = compute._row_average_weights(8)   # wide window: lots of averaging
    averaged = compute._row_average_waveforms(raw, valid, weights)
    raw_bins = compute._peak_bins(raw, spf)
    avg_bins = compute._peak_bins(averaged, spf)
    raw_hits = int(np.sum(raw_bins == true_bin))
    avg_hits = int(np.sum(avg_bins == true_bin))
    assert avg_hits > raw_hits, (
        f"row averaging should recover the true bin ({true_bin}) more often "
        f"than raw per-pixel estimates: raw {raw_hits}/{n_frames}, "
        f"averaged {avg_hits}/{n_frames}")
    assert avg_hits >= n_frames * 0.7, \
        f"averaged recovery should be reliable, not just barely better: {avg_hits}/{n_frames}"
 def test_row_average_parallel_identity(tmp_path, monkeypatch):
    """Forcing 1 worker vs many must give an identical row-averaged image --
    catches chunk-boundary bugs (there should be none, since averaging never
    crosses rows, but this is the empirical proof, not just inspection)."""
    path = tmp_path / "parallel_rowavg.sras"
    n_rows, n_frames, spf = 40, 13, 128
    gen.write(path, n_angles=1, seed=11, samples_per_frame=spf,
              geometry=[(n_rows, n_frames)])
    sras = SrasFile(str(path))
    monkeypatch.setattr(compute, "_TOTAL_BYTES_BUDGET", 8 * n_frames * spf * 4)
    monkeypatch.setattr(compute, "_FFT_BLOCK_MAX", 4)
    # row_avg_n > 0 halves the effective budget before chunk planning.
    fft_rows = compute._plan_fft_rows(n_frames, spf, compute._TOTAL_BYTES_BUDGET // 2)
    assert fft_rows < n_rows, \
        f"row-averaged FFT work actually splits into multiple chunks ({fft_rows} of {n_rows})"
    dc4 = dc_image_mv(sras, 0, CH4_IDX)
    thr = float(np.median(dc4))
    monkeypatch.setattr(compute, "_MAX_WORKERS", 1)
    serial = compute_rf_image(sras, 0, dc_threshold_mv=thr, apply_bg_sub=True,
                              row_avg_n=4)
    monkeypatch.setattr(compute, "_MAX_WORKERS", 8)
    parallel = compute_rf_image(sras, 0, dc_threshold_mv=thr, apply_bg_sub=True,
                                row_avg_n=4)
    assert np.array_equal(serial, parallel), \
        "row-averaged rf image identical regardless of chunking/worker count"
@@ -0,0 +1,951 @@
 """Does a batch-computed FFT cache actually spare the viewer the FFT?
 Storing a peak-frequency image per angle in the file is only worth doing if
 displaying it is then free. The regression this module pins down is the
 viewer's *dispatch* decision: it used to find the stored image only inside
 ComputeWorker, so after a batch every angle change still queued a background
 job behind a "Computing FFT…" popup for an image already on disk.
 Both layers are covered — cached_rf_image's accept/reject rules, and the
 window never reaching _start_compute for a batch-cached angle.
 """
 import struct
 from types import SimpleNamespace
 from unittest.mock import patch
 import numpy as np
 import pytest
 from PyQt6.QtCore import QEventLoop, QTimer
 from PyQt6.QtWidgets import QApplication, QDialog
 import sras_compute as compute
 import sras_format as fmt
 from sras_compute import cache_file, cached_rf_image, compute_rf_image, dc_image_mv
 from sras_format import CH1_IDX, CH3_IDX, CH4_IDX, SrasFile
 from sras_viewer import SrasViewerWindow, VELOCITY_MODE_IDX
 import tools.make_test_sras as gen
 _THRESHOLD_MV = 50.0    # the viewer's own default
 def pump(ms: int = 200):
    loop = QEventLoop()
    QTimer.singleShot(ms, loop.quit)
    loop.exec()
 def wait_until(pred, timeout_ms: int = 20000, step: int = 100) -> bool:
    waited = 0
    while waited < timeout_ms:
        if pred():
            return True
        pump(step)
        waited += step
    return pred()
@pytest.fixture(scope="module")
 def rig(tmp_path_factory):
    """A v6 file, the FFT images a from-scratch compute gives for it, and the
    same file after Batch Compute FFT has written them into its v7 cache."""
    path = tmp_path_factory.mktemp("stored_cache") / "cached.sras"
    gen.write(path, n_angles=4, seed=7, samples_per_frame=256)
    src = SrasFile(str(path))
    fresh = {a: compute_rf_image(src, a, dc_threshold_mv=_THRESHOLD_MV,
                                 apply_bg_sub=True)
             for a in range(src.n_angles)}
    assert src.background is not None, "the fixture file must have a background"
    err = cache_file(str(path), "fft", True)
    assert err == "", err
    cached = SrasFile(str(path))
    assert all(x is not None for x in cached.precomputed_freq_mhz)
    assert all(x is None for x in cached.precomputed_dc4_mv), \
        "FFT-only batch: the mask has to come from the viewer, not the file"
    return SimpleNamespace(path=path, fresh=fresh, sras=cached,
                           n_angles=cached.n_angles)
@pytest.fixture(scope="module")
 def dc_rig(tmp_path_factory):
    """A file that has been through Batch Compute DC and Store."""
    path = tmp_path_factory.mktemp("stored_dc") / "dc_cached.sras"
    gen.write(path, n_angles=4, seed=9, samples_per_frame=128)
    err = cache_file(str(path), "dc", True)
    assert err == "", err
    sras = SrasFile(str(path))
    assert all(x is not None for x in sras.precomputed_dc3_mv)
    assert all(x is not None for x in sras.precomputed_dc4_mv)
    assert len(np.unique(sras.precomputed_dc4_mv[0])) > 1, \
        "a degenerate DC image would make the comparisons below vacuous"
    return SimpleNamespace(path=path, sras=sras, n_angles=sras.n_angles)
@pytest.fixture
 def no_fft(monkeypatch):
    """Make any real FFT work loud: returns a list that stays empty unless a
    peak search actually runs."""
    calls = []
    for name in ("_peak_bins",):
        original = getattr(compute, name)
        def spy(*args, _f=original, **kwargs):
            calls.append(_f.__name__)
            return _f(*args, **kwargs)
        monkeypatch.setattr(compute, name, spy)
    return calls
 # ---------------------------------------------------------------------------
 # cached_rf_image: when may the stored image stand in for a compute?
 # ---------------------------------------------------------------------------
 def test_stored_image_matches_a_fresh_compute(rig, no_fft):
    for a in range(rig.n_angles):
        dc4 = dc_image_mv(SrasFile(str(rig.path)), a, CH4_IDX)
        img = cached_rf_image(rig.sras, a, dc_threshold_mv=_THRESHOLD_MV,
                              apply_bg_sub=True, dc4_mv=dc4)
        assert img is not None, f"angle {a} is cached in the file"
        assert np.allclose(img, rig.fresh[a], atol=1e-3), \
            f"angle {a} differs from a from-scratch compute"
    assert not no_fft, f"the stored image was used, no FFT ran: {no_fft}"
 def test_unmasked_when_no_threshold(rig):
    img = cached_rf_image(rig.sras, 0, dc_threshold_mv=None, apply_bg_sub=True)
    assert img is not None and np.array_equal(img, rig.sras.precomputed_freq_mhz[0])
    img[:] = -1.0
    assert not np.any(rig.sras.precomputed_freq_mhz[0] == -1.0), \
        "callers get a copy, never the file's own array"
 def test_settings_the_stored_image_cannot_serve(rig):
    """A stored image carries one bg-sub state and one padding, so anything
    else must fall through to a real compute rather than lie."""
    spf = rig.sras.samples_per_frame
    assert cached_rf_image(rig.sras, 0, _THRESHOLD_MV, apply_bg_sub=True,
                           n_fft=spf * 4) is None, \
        "cache was written at pad 1, a pad-4 view resolves different peaks"
    assert cached_rf_image(rig.sras, 0, _THRESHOLD_MV, apply_bg_sub=False) is None, \
        "cache was written with bg-sub on"
    uncached = SrasFile(str(rig.path))
    uncached.precomputed_freq_mhz[1] = None
    assert cached_rf_image(uncached, 1, _THRESHOLD_MV, apply_bg_sub=True) is None
@pytest.mark.parametrize("pad", [2, 10])
 def test_cache_is_stored_at_the_configured_pad(tmp_path, pad):
    """Batching at a pad factor must produce a cache that view can read back —
    a pad-1-only cache is one the padded viewer can never use."""
    path = tmp_path / f"pad{pad}.sras"
    gen.write(path, n_angles=2, seed=13, samples_per_frame=256)
    spf = SrasFile(str(path)).samples_per_frame
    assert cache_file(str(path), "fft", True, 0, pad) == ""
    sras = SrasFile(str(path))
    assert sras.precomputed_pad_factor == pad, "pad factor survives the round trip"
    assert cached_rf_image(sras, 0, None, apply_bg_sub=True,
                           n_fft=spf * pad) is not None, f"usable at pad {pad}"
    assert cached_rf_image(sras, 0, None, apply_bg_sub=True) is None, \
        "not usable unpadded"
    assert cached_rf_image(sras, 0, None, apply_bg_sub=True,
                           n_fft=spf * (pad + 1)) is None, "not usable at another pad"
    # The stored numbers must be the padded ones, not pad-1 relabelled.
    fresh = SrasFile(str(path))
    fresh.precomputed_freq_mhz = [None] * fresh.n_angles
    for a in range(sras.n_angles):
        assert np.allclose(
            compute_rf_image(sras, a, dc_threshold_mv=None, apply_bg_sub=True,
                             n_fft=spf * pad),
            compute_rf_image(fresh, a, dc_threshold_mv=None, apply_bg_sub=True,
                             n_fft=spf * pad), atol=1e-3), \
            f"angle {a}: stored image is the pad-{pad} answer"
 def test_cach_v1_reads_as_natural_resolution(tmp_path):
    """Files cached before the pad factor existed must keep working: a v1 tail
    has no pad field and is pad 1 by construction."""
    path = tmp_path / "v1.sras"
    gen.write(path, n_angles=2, seed=14, samples_per_frame=256)
    assert cache_file(str(path), "fft", True) == ""
    # Rewrite the tail as a genuine CACH v1 block (old header, no pad field).
    v2 = SrasFile(str(path))
    freq, entries = v2.precomputed_freq_mhz, list(range(v2.n_angles))
    tail_offset = v2._cache_tail_offset()
    payload = struct.pack(fmt.CACH_HDR_FMT, fmt.CACH_MAGIC, 1, fmt.CACH_FLAG_FFT)
    payload += struct.pack(fmt.SFFT_HDR_FMT_V1, fmt.SFFT_MAGIC,
                           fmt.SFFT_FLAG_BG_SUB, len(entries))
    for a in entries:
        payload += struct.pack(">H", a) + freq[a].astype(">f4").tobytes()
    # Windows refuses to truncate a file with a live mapping (write_bytes
    # opens 'wb'), and every SrasFile holds its waveform memmaps for life —
    # drop the instance first. The parsed freq arrays are plain copies and
    # stay usable.
    del v2
    head = path.read_bytes()[:tail_offset]
    path.write_bytes(head + payload)
    v1 = SrasFile(str(path))
    assert v1.precomputed_pad_factor == 1
    assert v1.precomputed_bg_sub is True
    assert all(np.array_equal(v1.precomputed_freq_mhz[a], freq[a]) for a in entries), \
        "v1 images read back unchanged"
    assert cached_rf_image(v1, 0, None, apply_bg_sub=True) is not None
    assert cached_rf_image(v1, 0, None, apply_bg_sub=True,
                           n_fft=v1.samples_per_frame * 10) is None
 def test_mask_read_can_be_refused(rig, no_fft):
    """With no DC4 in hand, building the mask means reading a whole channel —
    the GUI thread asks for None instead."""
    assert cached_rf_image(rig.sras, 0, _THRESHOLD_MV, apply_bg_sub=True,
                           allow_dc_recompute=False) is None
    dc4 = dc_image_mv(SrasFile(str(rig.path)), 0, CH4_IDX)
    img = cached_rf_image(rig.sras, 0, _THRESHOLD_MV, apply_bg_sub=True,
                          dc4_mv=dc4, allow_dc_recompute=False)
    assert img is not None and np.allclose(img, rig.fresh[0], atol=1e-3)
    assert not no_fft, f"no FFT on either branch: {no_fft}"
 # ---------------------------------------------------------------------------
 # The viewer: no compute job at all for a batch-cached angle
 # ---------------------------------------------------------------------------
 def test_viewer_shows_stored_angles_without_computing(rig, no_fft, monkeypatch):
    app = QApplication.instance() or QApplication([])   # noqa: F841
    win = SrasViewerWindow()
    win.show()
    dispatched = []
    original_start = type(win)._start_compute
    monkeypatch.setattr(type(win), "_start_compute",
                        lambda self: (dispatched.append(self.spin_angle.value()),
                                      original_start(self))[1])
    try:
        win._load_file(str(rig.path))
        assert wait_until(lambda: win._sras is not None), "file loaded"
        # The file carries no DC block, so the mask comes from the window's own
        # background precompute — the state a user is in by the time they click.
        assert wait_until(lambda: all((a, CH4_IDX) in win._dc_cache
                                      for a in range(rig.n_angles))), \
            "DC precompute finished"
        dispatched.clear()
        win.combo_channel.setCurrentIndex(CH1_IDX)
        assert wait_until(lambda: win._current_ch == CH1_IDX), "CH1 displayed"
        for a in list(range(rig.n_angles)) + [1, 0]:
            win.spin_angle.setValue(a)
            win._on_view_changed()
            pump(60)
            assert win._current_angle == a, f"angle {a} displayed"
            assert np.allclose(win._current_image, rig.fresh[a], atol=1e-3), \
                f"angle {a} shows the stored image"
        assert dispatched == [], \
            f"stored angles need no compute job, dispatched for {dispatched}"
        assert not no_fft, f"no FFT ran for any stored angle: {no_fft}"
        # Velocity is still a post-multiply of the same stored image.
        win.combo_channel.setCurrentIndex(VELOCITY_MODE_IDX)
        pump(120)
        assert np.allclose(win._current_image,
                           rig.fresh[0] * win.spin_grating_um.value(), atol=1e-3)
        assert dispatched == [] and not no_fft
        # ...and a live control that no longer matches the stored image's own
        # provenance must NOT force a recompute either — the stored image is
        # shown as-is; only an explicit batch recompute changes what's shown.
        win.combo_channel.setCurrentIndex(CH1_IDX)
        pump(60)
        win.chk_bg_sub.setChecked(False)
        pump(200)
        assert not win._job_running("compute") and not no_fft, \
            "bg-sub off still shows the stored image, no real FFT"
        assert np.allclose(win._current_image, rig.fresh[0], atol=1e-3)
    finally:
        win.close()
        pump(300)
 def test_batch_caches_at_the_viewers_pad_factor(tmp_path, no_fft, monkeypatch):
    """The bug a pad-10 user hits: Batch Compute FFT used to store pad-1
    images regardless, so the padded view recomputed every angle forever.
    """
    path = tmp_path / "padded_gui.sras"
    gen.write(path, n_angles=3, seed=15, samples_per_frame=256)
    app = QApplication.instance() or QApplication([])   # noqa: F841
    win = SrasViewerWindow()
    win.show()
    dispatched = []
    original_start = type(win)._start_compute
    monkeypatch.setattr(type(win), "_start_compute",
                        lambda self: (dispatched.append(self.spin_angle.value()),
                                      original_start(self))[1])
    try:
        win._fft_pad_factor = 10
        win._load_file(str(path))
        assert wait_until(lambda: win._sras is not None), "file loaded"
        assert wait_until(lambda: all((a, CH4_IDX) in win._dc_cache
                                      for a in range(win._sras.n_angles))), \
            "DC precompute finished"
        # Convert -> Batch Compute FFT, on the open file, through the real slot.
        with patch("sras_viewer.main_window.QFileDialog.getOpenFileNames",
                   return_value=([str(path)], "")):
            win._on_batch_compute("fft")
        assert wait_until(lambda: not win._job_running("batch"), 60000), "batch ran"
        assert wait_until(lambda: win._sras is not None
                          and win._sras.version == 7), "file reloaded as v7"
        pump(200)
        assert win._sras.precomputed_pad_factor == 10, \
            f"cached at the viewer's pad, got {win._sras.precomputed_pad_factor}"
        expected = {a: compute.cached_rf_image(
                        win._sras, a, dc_threshold_mv=win.spin_threshold_mv.value(),
                        apply_bg_sub=win.chk_bg_sub.isChecked(),
                        n_fft=win._current_n_fft(),
                        dc4_mv=win._dc_cache.get((a, CH4_IDX)))
                    for a in range(win._sras.n_angles)}
        assert all(v is not None for v in expected.values()), "cache is readable at pad 10"
        no_fft.clear()
        dispatched.clear()
        win.combo_channel.setCurrentIndex(CH1_IDX)
        assert wait_until(lambda: win._current_ch == CH1_IDX), "CH1 displayed"
        for a in range(win._sras.n_angles):
            win.spin_angle.setValue(a)
            pump(60)
            assert np.allclose(win._current_image, expected[a], atol=1e-3), \
                f"angle {a} served from the pad-10 cache"
        assert dispatched == [] and not no_fft, \
            f"no recompute at pad 10 (jobs={dispatched}, fft={no_fft})"
        assert "unusable" not in win.lbl_frame_warn.text()
        # Change the live pad control so it no longer matches the stored
        # image's own provenance — the info panel has to say so rather than
        # leave it a mystery, but the stored pad-10 image keeps displaying;
        # only an explicit batch recompute would ever produce a pad-4 one.
        win._fft_pad_factor = 4
        win._update_scan_info_labels()
        assert "differ from the stored cache" in win.lbl_frame_warn.text(), \
            win.lbl_frame_warn.text()
        assert "pad 10x" in win.lbl_frame_warn.text()
        last_angle = win._current_angle
        win._refresh_display()
        assert wait_until(lambda: not win._job_running("compute")), "settled"
        assert not no_fft, "no real FFT ran — the pad-10 cache still served the view"
        assert np.allclose(win._current_image, expected[last_angle], atol=1e-3), \
            "pad-10 cache still shown after the live pad control diverged"
    finally:
        win.close()
        pump(300)
 def test_viewer_shows_stored_dc_without_computing(dc_rig, monkeypatch):
    """Same for the DC half, with the background precompute silenced so the
    file's stored block is the only thing that can be carrying the display."""
    app = QApplication.instance() or QApplication([])   # noqa: F841
    win = SrasViewerWindow()
    win.show()
    dispatched = []
    original_start = type(win)._start_compute
    monkeypatch.setattr(type(win), "_start_compute",
                        lambda self: (dispatched.append(self.spin_angle.value()),
                                      original_start(self))[1])
    monkeypatch.setattr(type(win), "_start_dc_precompute", lambda self: None)
    try:
        win._load_file(str(dc_rig.path))
        assert wait_until(lambda: win._sras is not None), "file loaded"
        pump(120)
        for ch in (CH3_IDX, CH4_IDX):
            win.combo_channel.setCurrentIndex(ch)
            for a in range(dc_rig.n_angles):
                win.spin_angle.setValue(a)
                pump(60)
                assert (win._current_angle, win._current_ch) == (a, ch), \
                    f"angle {a} on channel {ch} displayed"
                assert np.array_equal(win._current_image,
                                      dc_rig.sras.cached_dc_mv(a, ch)), \
                    f"angle {a} channel {ch} shows the file's stored DC image"
        assert dispatched == [], \
            f"stored DC angles need no compute job, dispatched for {dispatched}"
    finally:
        win.close()
        pump(300)
 # ---------------------------------------------------------------------------
 # Row-averaged FFT: cache_file("fft_rowavg", ...) and its on-disk provenance
 # ---------------------------------------------------------------------------
 def test_row_average_flag_and_n_round_trip(tmp_path):
    path = tmp_path / "rowavg_roundtrip.sras"
    gen.write(path, n_angles=2, seed=20, samples_per_frame=128)
    err = cache_file(str(path), "fft_rowavg", True, dc_threshold_mv=-1e9, row_avg_n=5)
    assert err == "", err
    sras = SrasFile(str(path))
    assert sras.version == 7
    assert sras.precomputed_row_avg_n == 5
    assert all(x is not None for x in sras.precomputed_freq_mhz)
 def test_fft_rowavg_mode_requires_positive_n_and_threshold(tmp_path):
    path = tmp_path / "rowavg_bad_args.sras"
    gen.write(path, n_angles=1, seed=27, samples_per_frame=64)
    assert cache_file(str(path), "fft_rowavg", True, dc_threshold_mv=0.0, row_avg_n=0)
    assert cache_file(str(path), "fft_rowavg", True, dc_threshold_mv=None, row_avg_n=5)
 def test_raw_and_row_averaged_caches_never_cross_served(tmp_path):
    """The central regression this feature must never allow: a raw request
    served a row-averaged image (or vice versa), or a request at one window
    size served a cache stored at a different one."""
    path = tmp_path / "cross_serve.sras"
    gen.write(path, n_angles=1, seed=21, samples_per_frame=128)
    err = cache_file(str(path), "fft_rowavg", True, dc_threshold_mv=-1e9, row_avg_n=5)
    assert err == "", err
    sras = SrasFile(str(path))
    assert cached_rf_image(sras, 0, None, apply_bg_sub=True, row_avg_n=0) is None, \
        "a raw request must not be served a row-averaged cache"
    assert cached_rf_image(sras, 0, None, apply_bg_sub=True, row_avg_n=3) is None, \
        "a request at the wrong window size must not be served either"
    served = cached_rf_image(sras, 0, None, apply_bg_sub=True, row_avg_n=5)
    assert served is not None
    assert np.array_equal(served, sras.precomputed_freq_mhz[0])
 def test_write_v7_cache_row_avg_n_carries_forward(tmp_path):
    """A later DC-only write must leave a previously-written row-averaged
    FFT block -- including its row_avg_n -- byte-for-byte unchanged."""
    path = tmp_path / "carry_forward.sras"
    gen.write(path, n_angles=2, seed=22, samples_per_frame=64)
    err = cache_file(str(path), "fft_rowavg", True, dc_threshold_mv=-1e9, row_avg_n=7)
    assert err == "", err
    before = SrasFile(str(path))
    assert before.precomputed_row_avg_n == 7
    freq_before = [x.copy() for x in before.precomputed_freq_mhz]
    err = cache_file(str(path), "dc", True)
    assert err == "", err
    after = SrasFile(str(path))
    assert after.precomputed_row_avg_n == 7, "row_avg_n survives a DC-only write"
    assert all(np.array_equal(after.precomputed_freq_mhz[a], freq_before[a])
               for a in range(after.n_angles)), \
        "the row-averaged FFT block itself is untouched by a DC-only write"
 def test_row_average_never_touches_dc_images(tmp_path):
    path = tmp_path / "dc_untouched.sras"
    gen.write(path, n_angles=2, seed=23, samples_per_frame=64)
    src = SrasFile(str(path))
    expect_dc3 = [dc_image_mv(src, a, CH3_IDX) for a in range(src.n_angles)]
    expect_dc4 = [dc_image_mv(src, a, CH4_IDX) for a in range(src.n_angles)]
    assert cache_file(str(path), "dc", True) == ""
    assert cache_file(str(path), "fft_rowavg", True,
                      dc_threshold_mv=-1e9, row_avg_n=6) == ""
    after = SrasFile(str(path))
    assert all(np.allclose(after.precomputed_dc3_mv[a], expect_dc3[a], atol=1e-4)
               for a in range(after.n_angles))
    assert all(np.allclose(after.precomputed_dc4_mv[a], expect_dc4[a], atol=1e-4)
               for a in range(after.n_angles))
 def test_row_average_never_modifies_raw_waveform_data(tmp_path):
    path = tmp_path / "waveform_untouched.sras"
    gen.write(path, n_angles=2, seed=24, samples_per_frame=64)
    orig = tmp_path / "waveform_untouched_orig.sras"
    gen.write(orig, n_angles=2, seed=24, samples_per_frame=64)
    assert cache_file(str(path), "fft_rowavg", True,
                      dc_threshold_mv=-1e9, row_avg_n=5) == ""
    o, n = SrasFile(str(orig)), SrasFile(str(path))
    assert all(np.array_equal(np.asarray(o.data[a]), np.asarray(n.data[a]))
               for a in range(o.n_angles)), \
        "waveform data untouched by a row-averaged cache write"
 def test_cach_v1_backward_compat_defaults_row_avg_n_zero(tmp_path):
    """A v1 CACH tail predates row-averaged FFT caching entirely (no
    row_avg_n byte at all) -- readers must still parse it in full, treating
    it as row_avg_n=0. This is what protects an existing real-world v7
    file's already-stored FFT cache from silently becoming unusable after
    this change ships."""
    path = tmp_path / "v1_rowavg.sras"
    gen.write(path, n_angles=2, seed=25, samples_per_frame=128)
    assert cache_file(str(path), "fft", True) == ""
    v2 = SrasFile(str(path))
    freq, entries = v2.precomputed_freq_mhz, list(range(v2.n_angles))
    tail_offset = v2._cache_tail_offset()
    payload = struct.pack(fmt.CACH_HDR_FMT, fmt.CACH_MAGIC, 1, fmt.CACH_FLAG_FFT)
    payload += struct.pack(fmt.SFFT_HDR_FMT_V1, fmt.SFFT_MAGIC,
                           fmt.SFFT_FLAG_BG_SUB, len(entries))
    for a in entries:
        payload += struct.pack(">H", a) + freq[a].astype(">f4").tobytes()
    # See test_cach_v1_reads_as_natural_resolution: release the memmaps
    # before write_bytes truncates, or Windows raises EINVAL.
    del v2
    head = path.read_bytes()[:tail_offset]
    path.write_bytes(head + payload)
    v1 = SrasFile(str(path))
    assert v1.precomputed_row_avg_n == 0
    assert all(np.array_equal(v1.precomputed_freq_mhz[a], freq[a]) for a in entries), \
        "v1 images read back unchanged"
    assert cached_rf_image(v1, 0, None, apply_bg_sub=True, row_avg_n=0) is not None
    assert cached_rf_image(v1, 0, None, apply_bg_sub=True, row_avg_n=5) is None, \
        "a v1 tail (predating this feature) can never satisfy a row-averaged request"
 # ---------------------------------------------------------------------------
 # Min peak frequency floor: serve-time masking, on-disk provenance, batch
 # ---------------------------------------------------------------------------
 def _biting_floor(stored: np.ndarray) -> float:
    """A floor that zeroes some-but-not-all of *stored*'s positive peaks:
    the median distinct positive value, so pixels below it get masked and
    pixels at/above it survive (the mask is a strict <)."""
    positive = np.unique(stored[stored > 0])
    assert len(positive) >= 2, "fixture must have varied peak frequencies"
    return float(positive[len(positive) // 2])
 def test_stored_image_served_with_raised_floor_masked(rig, no_fft):
    """The core of the 5 m/s bug fix: a floor above the stored one (here 0)
    is re-applied when the stored image is served — pixels whose stored
    peak falls below it come back as the 0.0 invalid sentinel, everything
    else passes through, and no FFT runs. Both directly through
    cached_rf_image and through compute_rf_image's fast path."""
    assert rig.sras.precomputed_min_freq_mhz == 0.0, "batched without a floor"
    stored = rig.sras.precomputed_freq_mhz[0]
    floor = _biting_floor(stored)
    expect = np.where(stored < floor, np.float32(0.0), stored)
    img = cached_rf_image(rig.sras, 0, None, apply_bg_sub=True,
                          min_freq_mhz=floor)
    assert img is not None, "an equal-or-higher floor is servable"
    assert np.array_equal(img, expect)
    assert (img == 0).any() and (img > 0).any(), \
        "the floor bites some pixels but not all"
    via_compute = compute_rf_image(rig.sras, 0, dc_threshold_mv=None,
                                   apply_bg_sub=True, min_freq_mhz=floor)
    assert np.array_equal(via_compute, expect), \
        "compute_rf_image's fast path applies the same serve-time mask"
    assert not no_fft, f"serving + masking must not run an FFT: {no_fft}"
 def test_min_freq_floor_round_trips_and_gates_serving(tmp_path):
    """cache_file records the floor in the SFFT header and the accept rule
    is asymmetric: an equal-or-higher request is servable, a lower one is
    refused (the stored search never looked below its floor). 20.1 pins the
    fixed-point kHz encoding — a float32 header field would read back as
    20.10000038…, above the requested 20.1, and mismatch forever."""
    path = tmp_path / "floor_roundtrip.sras"
    gen.write(path, n_angles=2, seed=31, samples_per_frame=128)
    floor = 20.1
    assert cache_file(str(path), "fft", True, min_freq_mhz=floor) == ""
    sras = SrasFile(str(path))
    assert sras.precomputed_min_freq_mhz == floor, "exact fixed-point round-trip"
    assert all(((img == 0) | (img >= floor)).all()
               for img in sras.precomputed_freq_mhz), \
        "no stored peak below the floor"
    def reasons(f):
        return compute.cache_mismatch_reasons(
            sras, n_fft=None, apply_bg_sub=True, row_avg_n=0, min_freq_mhz=f)
    assert reasons(floor) == []
    assert reasons(floor + 5.0) == [], "a higher request is servable (masked)"
    low = reasons(0.0)
    assert low and "min-peak-freq floor" in low[0], \
        "a lower request cannot be answered by the stored search"
    assert cached_rf_image(sras, 0, None, apply_bg_sub=True) is None, \
        "default floor-0 request refused against a floored store"
    assert cached_rf_image(sras, 0, None, apply_bg_sub=True,
                           min_freq_mhz=floor) is not None
 def test_batch_recompute_resolves_not_masks(tmp_path, no_fft):
    """Re-batching an already-cached file at a raised floor must run the
    real FFT and store re-resolved peaks — never let compute_rf_image's
    fast path serve the file's own stale cache back to it and bake the
    masked copy in as if it were a recompute (silent, permanent data
    loss: a masked pixel's true above-floor peak is unrecoverable)."""
    path = tmp_path / "rebatch.sras"
    gen.write(path, n_angles=2, seed=32, samples_per_frame=256)
    assert cache_file(str(path), "fft", True) == ""
    first = SrasFile(str(path))
    n_angles = first.n_angles
    # On the header's kHz grid up front (as the spinbox value would be), so
    # the recorded floor reads back equal — cache_file quantizes whatever it
    # is given, and this test wants that to be the identity.
    floor = round(_biting_floor(first.precomputed_freq_mhz[0]) * 1000) / 1000.0
    bites = [img < floor for img in first.precomputed_freq_mhz]
    assert bites[0].any(), "the floor must actually bite this fixture"
    # What a real floored compute gives, from a view blinded to the cache.
    first.precomputed_freq_mhz = [None] * n_angles
    expected = [compute_rf_image(first, a, dc_threshold_mv=None,
                                 apply_bg_sub=True, min_freq_mhz=floor)
                for a in range(n_angles)]
    del first   # release memmaps before cache_file rewrites the tail
    no_fft.clear()
    assert cache_file(str(path), "fft", True, min_freq_mhz=floor) == ""
    assert no_fft, "the re-batch ran a real FFT"
    after = SrasFile(str(path))
    assert after.precomputed_min_freq_mhz == floor
    for a in range(n_angles):
        assert np.array_equal(after.precomputed_freq_mhz[a], expected[a]), \
            f"angle {a}: stored image is a real floored recompute"
        assert (after.precomputed_freq_mhz[a][bites[a]] >= floor).all(), \
            f"angle {a}: bitten pixels re-resolved above the floor, not zeroed"
 def test_min_freq_carries_forward_through_dc_write(tmp_path):
    """A later DC-only write must leave the FFT block's recorded floor
    untouched, like row_avg_n and pad_factor."""
    path = tmp_path / "floor_carry.sras"
    gen.write(path, n_angles=2, seed=33, samples_per_frame=128)
    assert cache_file(str(path), "fft", True, min_freq_mhz=75.0) == ""
    assert cache_file(str(path), "dc", True) == ""
    after = SrasFile(str(path))
    assert after.precomputed_min_freq_mhz == 75.0, \
        "floor survives a DC-only write"
 def test_cach_v3_backward_compat_defaults_floor_zero(tmp_path):
    """A v3 CACH tail predates the min peak frequency floor entirely (no
    min_freq_khz field) — readers must still parse it in full, treating it
    as floor 0: servable as-is at floor 0, and serve-maskable at any higher
    one. This is what protects existing real-world v7 caches from silently
    becoming unusable after the v4 bump ships."""
    path = tmp_path / "v3_floor.sras"
    gen.write(path, n_angles=2, seed=34, samples_per_frame=128)
    assert cache_file(str(path), "fft", True) == ""
    # Rewrite the tail as a genuine CACH v3 block (no min_freq field).
    v4 = SrasFile(str(path))
    freq, entries = v4.precomputed_freq_mhz, list(range(v4.n_angles))
    tail_offset = v4._cache_tail_offset()
    payload = struct.pack(fmt.CACH_HDR_FMT, fmt.CACH_MAGIC, 3, fmt.CACH_FLAG_FFT)
    payload += struct.pack(fmt.SFFT_HDR_FMT_V3, fmt.SFFT_MAGIC,
                           fmt.SFFT_FLAG_BG_SUB, len(entries), 0, 1)
    for a in entries:
        payload += struct.pack(">H", a) + freq[a].astype(">f4").tobytes()
    # See test_cach_v1_reads_as_natural_resolution: release the memmaps
    # before write_bytes truncates, or Windows raises EINVAL.
    del v4
    head = path.read_bytes()[:tail_offset]
    path.write_bytes(head + payload)
    v3 = SrasFile(str(path))
    assert v3.precomputed_min_freq_mhz == 0.0
    assert v3.precomputed_pad_factor == 1 and v3.precomputed_bg_sub is True
    assert all(np.array_equal(v3.precomputed_freq_mhz[a], freq[a])
               for a in entries), "v3 images read back unchanged"
    assert cached_rf_image(v3, 0, None, apply_bg_sub=True) is not None
    floor = _biting_floor(freq[0])
    served = cached_rf_image(v3, 0, None, apply_bg_sub=True,
                             min_freq_mhz=floor)
    assert served is not None
    assert np.array_equal(served,
                          np.where(freq[0] < floor, np.float32(0.0), freq[0]))
 def test_min_freq_validation(tmp_path):
    path = tmp_path / "floor_bad.sras"
    gen.write(path, n_angles=1, seed=35, samples_per_frame=64)
    assert cache_file(str(path), "fft", True, min_freq_mhz=-1.0), \
        "negative floor must be an error, not a write"
    assert cache_file(str(path), "fft", True, min_freq_mhz=float("nan")), \
        "NaN floor must be an error, not a write"
    sras = SrasFile(str(path))
    with pytest.raises(ValueError):
        sras.write_v7_cache(new_min_freq_mhz=-0.5)
 def test_viewer_reapplies_floor_to_stored_images_without_computing(
        rig, no_fft, monkeypatch):
    """The session-cache poisoning bug behind the '95 MHz peak but 5 m/s'
    report: changing 'Min peak freq' against a stored cache used to re-file
    the identical un-floored image under a key claiming the new floor — the
    UI looked updated, the pixels weren't. Now the floor really is
    re-applied on serve (masked, still no compute), and clearing it
    restores the unmasked image, still without computing."""
    app = QApplication.instance() or QApplication([])   # noqa: F841
    win = SrasViewerWindow()
    win.show()
    dispatched = []
    original_start = type(win)._start_compute
    monkeypatch.setattr(type(win), "_start_compute",
                        lambda self: (dispatched.append(self.spin_angle.value()),
                                      original_start(self))[1])
    try:
        win._load_file(str(rig.path))
        assert wait_until(lambda: win._sras is not None), "file loaded"
        assert wait_until(lambda: all((a, CH4_IDX) in win._dc_cache
                                      for a in range(rig.n_angles))), \
            "DC precompute finished"
        win.combo_channel.setCurrentIndex(CH1_IDX)
        assert wait_until(lambda: win._current_ch == CH1_IDX), "CH1 displayed"
        assert np.allclose(win._current_image, rig.fresh[0], atol=1e-3)
        # Round to the spinbox's 3-decimal granularity; the chosen bin value
        # still survives its own (strict-<) floor after rounding down.
        floor = round(_biting_floor(rig.fresh[0]), 3)
        expect = np.where(rig.fresh[0] < floor, np.float32(0.0), rig.fresh[0])
        dispatched.clear()
        no_fft.clear()
        win.spin_min_freq_mhz.setValue(floor)
        win._on_min_freq_changed()
        pump(120)
        assert np.allclose(win._current_image, expect, atol=1e-3), \
            "raised floor re-masks the stored image on serve"
        assert (win._current_image == 0).any() and (win._current_image > 0).any()
        assert dispatched == [] and not no_fft, \
            f"re-masked serve needs no compute (jobs={dispatched}, fft={no_fft})"
        key = (0, win.spin_threshold_mv.value(), win.spin_min_freq_mhz.value())
        assert key in win._fft_cache
        assert np.allclose(win._fft_cache[key], expect, atol=1e-3), \
            "the session cache holds the value its key claims"
        win.spin_min_freq_mhz.setValue(0.0)
        win._on_min_freq_changed()
        pump(120)
        assert np.allclose(win._current_image, rig.fresh[0], atol=1e-3), \
            "clearing the floor restores the unmasked stored image"
        assert dispatched == [] and not no_fft
    finally:
        win.close()
        pump(300)
 def test_viewer_batch_fft_records_the_floor(tmp_path, no_fft, monkeypatch):
    """Convert → Batch Compute FFT with a floor set: the live spinbox value
    reaches cache_file, lands in the reloaded file's provenance and the
    info panel, and the viewer then serves the floored cache without
    recomputing — the tooltip's promised remedy, end to end."""
    path = tmp_path / "floor_gui.sras"
    gen.write(path, n_angles=2, seed=36, samples_per_frame=256)
    app = QApplication.instance() or QApplication([])   # noqa: F841
    win = SrasViewerWindow()
    win.show()
    dispatched = []
    original_start = type(win)._start_compute
    monkeypatch.setattr(type(win), "_start_compute",
                        lambda self: (dispatched.append(self.spin_angle.value()),
                                      original_start(self))[1])
    try:
        win._load_file(str(path))
        assert wait_until(lambda: win._sras is not None), "file loaded"
        assert wait_until(lambda: all((a, CH4_IDX) in win._dc_cache
                                      for a in range(win._sras.n_angles))), \
            "DC precompute finished"
        floor = 100.0
        win.spin_min_freq_mhz.setValue(floor)
        with patch("sras_viewer.main_window.QFileDialog.getOpenFileNames",
                   return_value=([str(path)], "")):
            win._on_batch_compute("fft")
        assert wait_until(lambda: not win._job_running("batch"), 60000), "batch ran"
        assert wait_until(lambda: win._sras is not None
                          and win._sras.version == 7), "file reloaded as v7"
        pump(200)
        assert win._sras.precomputed_min_freq_mhz == floor, \
            "the viewer's floor reached the stored provenance"
        assert "floor ≥ 100 MHz" in win.lbl_frame_warn.text()
        no_fft.clear()
        dispatched.clear()
        win.combo_channel.setCurrentIndex(CH1_IDX)
        assert wait_until(lambda: win._current_ch == CH1_IDX), "CH1 displayed"
        pump(120)
        assert dispatched == [] and not no_fft, \
            f"floored cache serves the view directly (jobs={dispatched}, fft={no_fft})"
        img = win._current_image
        assert ((img == 0) | (img >= floor)).all(), \
            "no displayed peak below the floor"
    finally:
        win.close()
        pump(300)
 def test_viewer_batch_row_average_dispatch(tmp_path, monkeypatch, no_fft):
    """Driving the new 'Batch Compute Row-Averaged FFT and Store' action
    end-to-end through the real menu handler: dialog values reach the
    worker, the worker reaches cache_file, and the written file is
    self-describing afterward. Also the exact scenario the row-averaged-FFT
    recompute bug reported: before the fix, the display always asked for
    row_avg_n=0 regardless of what the file actually had stored, so viewing
    an angle after this batch action saw a phantom mismatch and launched a
    full raw recompute on every view switch. This asserts that no longer
    happens -- the stored row-averaged image is shown directly, with no
    dispatched compute job and no real FFT."""
    path = tmp_path / "rowavg_gui.sras"
    gen.write(path, n_angles=2, seed=26, samples_per_frame=128)
    class _StubDialog:
        def __init__(self, *a, **k):
            pass
        def exec(self):
            return QDialog.DialogCode.Accepted
        def get_half_width(self):
            return 6
        def get_threshold_mv(self):
            return -1e9   # mask nothing, keep the comparison simple
    monkeypatch.setattr("sras_viewer.main_window.RowAverageFftOptionsDialog", _StubDialog)
    app = QApplication.instance() or QApplication([])   # noqa: F841
    win = SrasViewerWindow()
    win.show()
    dispatched = []
    original_start = type(win)._start_compute
    monkeypatch.setattr(type(win), "_start_compute",
                        lambda self: (dispatched.append(self.spin_angle.value()),
                                      original_start(self))[1])
    try:
        win._load_file(str(path))
        assert wait_until(lambda: win._sras is not None), "file loaded"
        assert wait_until(lambda: all((a, CH4_IDX) in win._dc_cache
                                      for a in range(win._sras.n_angles))), \
            "DC precompute finished"
        with patch("sras_viewer.main_window.QFileDialog.getOpenFileNames",
                   return_value=([str(path)], "")):
            win._on_batch_compute_row_avg()
        assert wait_until(lambda: not win._job_running("batch"), 60000), "batch ran"
        assert wait_until(lambda: win._sras is not None
                          and win._sras.version == 7), "file reloaded as v7"
        pump(200)
        assert win._sras.precomputed_row_avg_n == 6
        assert "row-averaged n=6" in win.lbl_frame_warn.text(), win.lbl_frame_warn.text()
        expected = compute.cached_rf_image(win._sras, 0, dc_threshold_mv=None,
                                           apply_bg_sub=win.chk_bg_sub.isChecked(),
                                           row_avg_n=6)
        assert expected is not None, "the batch write left a readable row-averaged cache"
        # The regression this batch action used to leave unfixed: viewing an
        # angle afterward must show the stored row-averaged image directly,
        # never fall through to a real (raw) recompute.
        no_fft.clear()
        dispatched.clear()
        win.combo_channel.setCurrentIndex(CH1_IDX)
        assert wait_until(lambda: win._current_ch == CH1_IDX), "CH1 displayed"
        for a in range(win._sras.n_angles):
            win.spin_angle.setValue(a)
            pump(60)
            assert np.allclose(win._current_image,
                               compute.cached_rf_image(
                                   win._sras, a,
                                   dc_threshold_mv=win.spin_threshold_mv.value(),
                                   apply_bg_sub=win.chk_bg_sub.isChecked(),
                                   row_avg_n=6), atol=1e-3), \
                f"angle {a} shows the stored row-averaged image"
        assert dispatched == [] and not no_fft, \
            f"no recompute for row-averaged angles (jobs={dispatched}, fft={no_fft})"
    finally:
        win.close()
        pump(300)
 def test_compute_worker_fallback_honors_row_avg_n(tmp_path, monkeypatch, no_fft):
    """The other half of the row-averaged recompute bug: _stored_fft_image
    isn't the only path that can serve a view. When the DC4 mask isn't known
    yet without I/O (e.g. background DC precompute hasn't reached this angle),
    _stored_fft_image's allow_dc_recompute=False guard bails and
    _refresh_display falls through to _start_compute's ComputeWorker instead.
    That worker must still ask compute_rf_image for the file's own
    row_avg_n -- not silently default to 0 -- so its own internal cache
    fast path also serves the stored row-averaged image rather than running
    a real, non-averaged FFT."""
    path = tmp_path / "rowavg_fallback.sras"
    gen.write(path, n_angles=2, seed=33, samples_per_frame=128)
    # Only fft_rowavg -- deliberately no DC block, exactly what "Batch
    # Compute Row-Averaged FFT and Store" leaves on disk by itself.
    err = cache_file(str(path), "fft_rowavg", True, dc_threshold_mv=-1e9, row_avg_n=5)
    assert err == "", err
    app = QApplication.instance() or QApplication([])   # noqa: F841
    win = SrasViewerWindow()
    win.show()
    # Keep _dc_cache empty so _stored_fft_image can't resolve a mask without
    # I/O and _refresh_display must fall through to _start_compute.
    monkeypatch.setattr(type(win), "_start_dc_precompute", lambda self: None)
    dispatched = []
    original_start = type(win)._start_compute
    monkeypatch.setattr(type(win), "_start_compute",
                        lambda self: (dispatched.append(self.spin_angle.value()),
                                      original_start(self))[1])
    try:
        win._load_file(str(path))
        assert wait_until(lambda: win._sras is not None), "file loaded"
        assert win._sras.precomputed_row_avg_n == 5
        # The initial default view (CH4, DC) has nothing cached either, so
        # it dispatches its own one-off DC compute for angle 0 on load --
        # unrelated to this bug. Let that settle, then clear it so no DC4 is
        # available for any angle, simulating "background DC precompute
        # hasn't reached this angle yet".
        assert wait_until(lambda: not win._job_running("compute")), "initial DC view settled"
        dispatched.clear()
        win._dc_cache.clear()
        no_fft.clear()
        win.combo_channel.setCurrentIndex(CH1_IDX)
        assert wait_until(lambda: win._current_ch == CH1_IDX
                          and not win._job_running("compute")), "CH1 displayed"
        assert dispatched == [0], \
            "with no DC cache available yet, the fallback compute must run"
        assert not no_fft, \
            f"the fallback's own compute_rf_image call must still hit the " \
            f"stored row-averaged cache internally: {no_fft}"
        expected = compute.cached_rf_image(
            win._sras, 0, dc_threshold_mv=win.spin_threshold_mv.value(),
            apply_bg_sub=win.chk_bg_sub.isChecked(), row_avg_n=5)
        assert expected is not None
        assert np.allclose(win._current_image, expected, atol=1e-3), \
            "the displayed image is the stored row-averaged one, not a raw recompute"
    finally:
        win.close()
        pump(300)
@@ -0,0 +1,109 @@
 #!/usr/bin/env python3
 """Benchmark the FFT peak-search path: serial vs pooled.
 Reports wall time, waveforms/s, CPU utilization (utime+stime over wall, in
 cores), the estimated per-thread resident pyFFTW plan footprint at each pad
 factor (see sras_compute._fft_block_for), and verifies pooled output against
 the serial reference.
 Usage:
    python tools/bench_fft.py                       # synthetic, pads 1/8/40
    python tools/bench_fft.py --pads 40 --spf 2500 --rows 8 --frames 1024
    python tools/bench_fft.py --real /path/big.sras --real-rows 32 --pads 40
 """
 import argparse
 import resource
 import sys
 import tempfile
 import time
 from pathlib import Path
 import numpy as np
 sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
 import sras_compute as compute                              # noqa: E402
 from sras_compute import compute_rf_image                    # noqa: E402
 from sras_format import SrasFile                             # noqa: E402
 import tools.make_test_sras as gen                           # noqa: E402
 from tools.check_equivalence import row_slice                # noqa: E402
 def _timed(fn):
    r0 = resource.getrusage(resource.RUSAGE_SELF)
    t0 = time.perf_counter()
    out = fn()
    wall = time.perf_counter() - t0
    r1 = resource.getrusage(resource.RUSAGE_SELF)
    cpu = (r1.ru_utime - r0.ru_utime) + (r1.ru_stime - r0.ru_stime)
    return out, wall, cpu / max(wall, 1e-9)
 def _plan_mb(spf: int, n_len: int, n_workers: int) -> float:
    """Estimated resident pyFFTW plan-buffer footprint across the whole
    pool at this transform length (see sras_compute._fft_block_for)."""
    block = compute._fft_block_for(spf, n_len)
    bytes_per_wf = 4 * spf + 8 * (n_len // 2 + 1)
    return block * bytes_per_wf * n_workers / (1024 * 1024)
 def bench(sras, pads):
    n_wf = sum(int(sras.n_rows[a]) * int(sras.n_frames[a])
               for a in range(sras.n_angles))
    spf = sras.samples_per_frame
    n_workers = compute._MAX_WORKERS
    print(f"{n_wf} waveforms x {spf} samples, {sras.n_angles} angle(s), "
          f"{n_workers} workers")
    print(f"{'pad':>4} {'variant':>8} {'wall':>9} {'wf/s':>10} {'util':>6} "
          f"{'plan MB':>9}  match")
    for pad in pads:
        n_fft = spf * pad if pad > 1 else None
        n_len = n_fft if n_fft is not None else spf
        plan_mb = _plan_mb(spf, n_len, n_workers)
        def run(**kw):
            imgs = [compute_rf_image(sras, a, dc_threshold_mv=None,
                                     apply_bg_sub=True, n_fft=n_fft, **kw)
                    for a in range(sras.n_angles)]
            return np.concatenate([i.ravel() for i in imgs])
        ref, wall, util = _timed(lambda: run(max_workers=1))
        rows = [("serial", ref, wall, util, True)]
        img, wall, util = _timed(lambda: run())
        rows.append(("pooled", img, wall, util, bool(np.array_equal(img, ref))))
        for label, img, wall, util, ok in rows:
            print(f"{pad:>4} {label:>8} {wall:>8.2f}s {n_wf / wall:>10.0f} "
                  f"{util:>5.1f}x {plan_mb:>8.1f}  {'OK' if ok else 'MISMATCH'}")
 def main():
    p = argparse.ArgumentParser(description=__doc__)
    p.add_argument("--pads", default="1,8,40",
                   help="comma-separated pad factors (default 1,8,40)")
    p.add_argument("--spf", type=int, default=2500)
    p.add_argument("--rows", type=int, default=8)
    p.add_argument("--frames", type=int, default=1024)
    p.add_argument("--real", help="path to a real .sras file")
    p.add_argument("--real-rows", type=int, default=32,
                   help="rows of angle 0 to use from the real file")
    args = p.parse_args()
    pads = [int(x) for x in args.pads.split(",")]
    if args.real:
        sras = row_slice(SrasFile(args.real), 0, args.real_rows)
        sras.data = [sras.data[0]]
        sras.n_angles = 1
        bench(sras, pads)
    else:
        with tempfile.TemporaryDirectory(prefix="sras_bench_") as tmp:
            path = Path(tmp) / "bench.sras"
            gen.write(path, n_angles=1, seed=0, samples_per_frame=args.spf,
                      geometry=[(args.rows, args.frames)])
            bench(SrasFile(str(path)), pads)
 if __name__ == "__main__":
    main()
@@ -0,0 +1,194 @@
 #!/usr/bin/env python3
 """Golden-output equivalence harness for compute-path refactors.
 Computes a battery of DC / FFT / alignment outputs and prints a stable hash
 for each. Run it before a refactor to capture a baseline, then again after
 and diff the two reports — every line must match.
 Hashes canonicalise to native little-endian float64 before hashing, so a
 deliberate dtype/byte-order change that preserves values does not show up as
 a false mismatch.
 Usage:
    python tools/check_equivalence.py --out baseline.txt
    python tools/check_equivalence.py --out after.txt --real /path/to/big.sras
    diff baseline.txt after.txt
 """
 import argparse
 import copy
 import hashlib
 import sys
 from pathlib import Path
 import numpy as np
 sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
 from sras_format import SrasFile, CH3_IDX, CH4_IDX, adc_to_mv   # noqa: E402
 from sras_compute import (                                      # noqa: E402
    apply_alignment, compute_angle_alignment, compute_dc_image, compute_rf_image,
 )
 import tools.make_test_sras as gen                              # noqa: E402
 def h(arr) -> str:
    """Stable hash of an array's *values*, independent of dtype/byte order."""
    a = np.ascontiguousarray(np.asarray(arr, dtype=np.float64))
    return hashlib.sha256(a.tobytes()).hexdigest()[:16]
 def row_slice(sras: SrasFile, angle_idx: int, n_rows: int) -> SrasFile:
    """A shallow view of *sras* restricted to the first *n_rows* rows of
    *angle_idx*, so the huge real file can be exercised in seconds."""
    view = copy.copy(sras)
    n = min(int(n_rows), int(sras.n_rows[angle_idx]))
    view.n_rows = np.array(sras.n_rows, copy=True)
    view.n_rows[angle_idx] = n
    view.data = list(sras.data)
    view.data[angle_idx] = sras.data[angle_idx][:n]
    view.y_pos_per_angle = list(sras.y_pos_per_angle)
    view.y_pos_per_angle[angle_idx] = sras.y_pos_per_angle[angle_idx][:n]
    return view
 def report(lines: list[str], label: str, value: str):
    lines.append(f"{label:<58} {value}")
 def check_file(path: Path, lines: list[str], tag: str,
               angles: list[int], n_rows: int | None):
    sras = SrasFile(str(path))
    report(lines, f"[{tag}] version/n_angles",
           f"v{sras.version} n={sras.n_angles}")
    report(lines, f"[{tag}] geometry",
           f"rows={list(map(int, sras.n_rows))} frames={list(map(int, sras.n_frames))}")
    report(lines, f"[{tag}] calibration",
           " ".join(f"{m:.6g}/{o:.6g}/{z:.6g}" for m, o, z in
                    zip(sras.ch_ymult_mv, sras.ch_yoff_adc, sras.ch_yzero_mv)))
    report(lines, f"[{tag}] angles_deg", h(sras.angles_deg))
    if sras.background is not None:
        report(lines, f"[{tag}] background", h(sras.background))
    for a in angles:
        if a >= sras.n_angles:
            continue
        s = row_slice(sras, a, n_rows) if n_rows else sras
        report(lines, f"[{tag}] x_axis_mm(a={a})", h(s.x_axis_mm(a)))
        report(lines, f"[{tag}] y_positions_mm(a={a})", h(s.y_positions_mm(a)))
        for ch, name in ((CH3_IDX, "CH3"), (CH4_IDX, "CH4")):
            raw = compute_dc_image(s, a, ch)
            report(lines, f"[{tag}] dc_adc(a={a},{name})", h(raw))
            mv = adc_to_mv(raw, s.ch_ymult_mv[ch], s.ch_yoff_adc[ch],
                           s.ch_yzero_mv[ch])
            report(lines, f"[{tag}] dc_mv(a={a},{name})", h(mv))
        dc4 = adc_to_mv(compute_dc_image(s, a, CH4_IDX),
                        s.ch_ymult_mv[CH4_IDX], s.ch_yoff_adc[CH4_IDX],
                        s.ch_yzero_mv[CH4_IDX])
        thresholds = [-1e9, float(np.median(dc4))]
        for bg in (False, True):
            if bg and s.background is None:
                continue
            for pad in (1, 2, 4, 8, 40):
                n_fft = s.samples_per_frame * pad if pad > 1 else None
                for ti, thr in enumerate(thresholds):
                    img = compute_rf_image(s, a, dc_threshold_mv=thr,
                                           apply_bg_sub=bg, n_fft=n_fft)
                    report(lines,
                           f"[{tag}] rf(a={a},bg={int(bg)},pad={pad},thr{ti})",
                           h(img))
                    # dc4_mv passthrough must give the identical result
                    img2 = compute_rf_image(s, a, dc_threshold_mv=thr,
                                            apply_bg_sub=bg, n_fft=n_fft,
                                            dc4_mv=dc4)
                    same = "SAME" if h(img) == h(img2) else "DIFFER"
                    report(lines,
                           f"[{tag}] rf-dc4arg(a={a},bg={int(bg)},pad={pad},thr{ti})",
                           same)
 def check_alignment(path: Path, lines: list[str], tag: str):
    sras = SrasFile(str(path))
    if sras.n_angles < 2:
        return
    dc4 = adc_to_mv(compute_dc_image(sras, 0, CH4_IDX),
                    sras.ch_ymult_mv[CH4_IDX], sras.ch_yoff_adc[CH4_IDX],
                    sras.ch_yzero_mv[CH4_IDX])
    thr = float(np.median(dc4))
    res = compute_angle_alignment(sras, 0, thr)
    report(lines, f"[{tag}] align canvas_shape", str(res.canvas_shape))
    report(lines, f"[{tag}] align canvas_origin",
           f"{res.canvas_origin_mm[0]:.9g},{res.canvas_origin_mm[1]:.9g}")
    report(lines, f"[{tag}] align canvas_pitch",
           f"{res.canvas_dx_mm:.9g},{res.canvas_dy_mm:.9g}")
    for a in sorted(res.per_angle):
        t = res.per_angle[a]
        report(lines, f"[{tag}] align shift_mm(a={a})",
               f"{t.shift_mm[0]:.9g},{t.shift_mm[1]:.9g}")
        report(lines, f"[{tag}] align rot(a={a})", f"{t.rotation_deg:.9g}")
        report(lines, f"[{tag}] align matrix(a={a})", h(t.matrix))
        report(lines, f"[{tag}] align offset(a={a})", h(t.offset))
        img = compute_dc_image(sras, a, CH4_IDX)
        report(lines, f"[{tag}] align resampled(a={a})",
               h(apply_alignment(res, a, img)))
 def main():
    p = argparse.ArgumentParser(description=__doc__)
    p.add_argument("--out", required=True, help="report file to write")
    p.add_argument("--real", help="optional path to a real .sras file")
    p.add_argument("--real-rows", type=int, default=2,
                   help="rows per angle to sample from the real file")
    p.add_argument("--real-angles", type=int, default=2,
                   help="how many angles to sample from the real file")
    p.add_argument("--scratch", default=".",
                   help="directory for generated synthetic files")
    args = p.parse_args()
    lines = [f"# numpy: {np.__version__}"]
    scratch = Path(args.scratch)
    synth = scratch / "equiv_synth.sras"
    gen.write(synth, n_angles=4, seed=0, samples_per_frame=64)
    check_file(synth, lines, "synth", angles=[0, 1, 2, 3], n_rows=None)
    check_alignment(synth, lines, "synth")
    # A second synthetic with an odd sample count, to catch off-by-one in
    # rfft bin handling and chunk-boundary arithmetic.
    synth_odd = scratch / "equiv_synth_odd.sras"
    gen.write(synth_odd, n_angles=2, seed=7, samples_per_frame=37)
    check_file(synth_odd, lines, "odd", angles=[0, 1], n_rows=None)
    # A legacy v4 file exercises the uniform-geometry legacy layout through
    # the same DC/FFT battery.
    synth_v4 = scratch / "equiv_synth_v4.sras"
    gen.write_legacy(synth_v4, version=4, n_angles=2, n_rows=6,
                     n_frames=14, samples_per_frame=48, seed=5)
    check_file(synth_v4, lines, "v4", angles=[0, 1], n_rows=None)
    # A big-endian int16 v6 file (real acquisitions are >i2; the other
    # synthetics are int8).
    synth_i16 = scratch / "equiv_synth_i16.sras"
    gen.write(synth_i16, n_angles=2, seed=9, samples_per_frame=64, bps=2)
    check_file(synth_i16, lines, "int16", angles=[0, 1], n_rows=None)
    if args.real:
        real = Path(args.real)
        if real.exists():
            check_file(real, lines, "real",
                       angles=list(range(args.real_angles)),
                       n_rows=args.real_rows)
        else:
            lines.append(f"# real file not found: {real}")
    Path(args.out).write_text("\n".join(lines) + "\n")
    print("\n".join(lines))
    print(f"\nWrote {args.out} ({len(lines)} lines)")
 if __name__ == "__main__":
    main()
@@ -0,0 +1,321 @@
 #!/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))
 # Single source of truth for the byte layout: the reader's own constants.
 # The byte *assembly* below stays independent, so a writer bug can't be
 # masked by a matching reader bug.
 from sras_format import HDR_FMT as HDR_FMT_LEGACY          # noqa: E402
 from sras_format import GEO_FMT_V6, HDR_FMT_V6             # noqa: E402
 from sras_compute import _rotation_matrix as _rot          # 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,
          bps: int = 1) -> 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
    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)
        # bps=2 stores the same values big-endian int16, exercising the
        # reader's >i2 memmap path.
        out += (block.astype(">i2") if bps == 2 else 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,
          bps: int = 1) -> dict:
    payload, meta = build(n_angles, seed, samples_per_frame, geometry, bps=bps)
    path.write_bytes(payload)
    return meta
 # ---------------------------------------------------------------------------
 # Rotating-sample scan: one shape, imaged at several known rotations
 # ---------------------------------------------------------------------------
 #
 # The scan the angle-alignment path actually has to solve: every angle images
 # the *same* sample at a different known rotation and offset, and a correct
 # alignment stacks them all back into one shape. Two properties are
 # deliberately hostile:
 #
 #   * every angle gets a different window size and a different, meaningless
 #     stage x_start / y0 — alignment must ignore per-angle stage coordinates
 #     entirely, so any code that reads them will visibly fail here;
 #   * the pixel grid is strongly anisotropic (5 µm along x, 50 µm along y),
 #     like the real instrument, so any registration that rotates raw indices
 #     instead of millimetres shears the image and cannot converge.
 _ROT_DX_MM = 0.005          # x pitch, from velocity/laser_freq below
 _ROT_DY_MM = 0.05           # row spacing
 _ROT_BG_MV = 4.0
 _ROT_FG_MV = 160.0
 # How far the sample sits from the rotation axis. Non-zero on purpose: on the
 # real instrument every angle's scan window is centred on the rotation axis
 # while the sample is not, so each scan sees the sample somewhere else along a
 # circle. That offset is exactly what a wrong rotation pivot turns into a ring
 # of scans instead of a stack, so a centred test sample would hide the bug.
 _ROT_SAMPLE_OFFSET_MM = (0.55, 0.40)
 def _sample_shape_mv(u: np.ndarray, v: np.ndarray) -> np.ndarray:
    """An asymmetric test sample in its own mm frame, chirally distinct at
    every rotation (no 180° ambiguity) and with structure at several radii so
    rotation is well determined."""
    u = u - _ROT_SAMPLE_OFFSET_MM[0]
    v = v - _ROT_SAMPLE_OFFSET_MM[1]
    img = np.full(u.shape, _ROT_BG_MV, dtype=np.float32)
    img[((u / 0.85) ** 2 + (v / 0.40) ** 2) <= 1.0] = _ROT_FG_MV          # bar
    img[(np.abs(u - 0.55) <= 0.22) & (np.abs(v - 0.62) <= 0.22)] = _ROT_FG_MV   # nub
    img[((u + 0.75) ** 2 + (v + 0.30) ** 2) <= 0.20 ** 2] = _ROT_FG_MV    # dot
    return img
 def write_rotating(path: Path, n_angles: int = 5, samples_per_frame: int = 4,
                   seed: int = 0) -> dict:
    """Write a v6 file whose CH4 DC image is one sample seen at n_angles known
    rotations, and return the ground truth each angle should register to.
    ``truth[a] = (rotation_deg, (shift_x_mm, shift_y_mm))`` is the rigid map
    from angle *a*'s local mm (origin at its own array center) to angle 0's —
    exactly what ``register_angle_to_reference`` is supposed to recover.
    """
    rng = np.random.default_rng(seed)
    n_ch, bps = 3, 1
    cal = [(1.5625e-3, -87.04, 0.0), (2.0e-3, -60.0, 1.0e-3), (2.5e-3, -40.0, -2.0e-3)]
    ymult_mv, yoff, yzero_mv = cal[2][0] * 1000, cal[2][1], cal[2][2] * 1000
    stage_angles, geom, x_starts, y_starts, thetas, offsets = [], [], [], [], [], []
    for a in range(n_angles):
        stage = -37.0 * a                       # what the rotation stage reports
        stage_angles.append(stage)
        # The true image rotation is the negative of the stage's reported
        # angle: the stage's positive sense is the opposite of math-positive
        # (x toward y) in scan mm. Nothing may depend on knowing that — the
        # registration search tries both signs.
        thetas.append(-stage)
        offsets.append((0.0, 0.0) if a == 0
                       else (float(rng.uniform(-0.3, 0.3)), float(rng.uniform(-0.3, 0.3))))
        # A different window per angle, all centred on the same array center —
        # the real instrument grows each angle's axis-aligned bounding box to
        # cover the rotated ROI. Sized so the off-axis sample stays inside every
        # window at every angle, keeping the expected result unambiguous.
        geom.append((88 + 8 * a, 780 + 60 * a))
        # Meaningless per-angle stage positions: correct alignment never reads
        # them, so scattering them proves it.
        x_starts.append(float(20.0 + rng.uniform(-6.0, 6.0)))
        y_starts.append(float(30.0 + rng.uniform(-6.0, 6.0)))
    out = bytearray()
    out += struct.pack(
        HDR_FMT_V6, b"SRAS", 6, n_angles,
        x_starts[0], y_starts[0], 1.0, 1.0, _ROT_DY_MM,
        _VELOCITY_MM_S, _VELOCITY_MM_S / _ROT_DX_MM,   # velocity/freq -> 5 µm pitch
        samples_per_frame, _SAMPLE_RATE_HZ, bps, n_ch,
    )
    out += np.array(stage_angles, dtype=">f4").tobytes()
    for a, (n_rows, n_frames) in enumerate(geom):
        out += struct.pack(GEO_FMT_V6, x_starts[a], 1.0, n_frames, n_rows)
    for a, (n_rows, _) in enumerate(geom):
        out += (y_starts[a] + np.arange(n_rows) * _ROT_DY_MM).astype(">f4").tobytes()
    for ymult_v, yoff_a, yzero_v in cal:
        p = _preamble(ymult_v, yoff_a, 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()
    truth, dc4_images = {}, []
    for a, (n_rows, n_frames) in enumerate(geom):
        # Local mm of every pixel, measured from this angle's own array center.
        lx = (np.arange(n_frames) - (n_frames - 1) / 2.0) * _ROT_DX_MM
        ly = (np.arange(n_rows) - (n_rows - 1) / 2.0) * _ROT_DY_MM
        gx, gy = np.meshgrid(lx, ly)
        # local = R(theta) @ sample + offset, so sample = R(theta)^T @ (local - offset)
        rel = np.stack([gx - offsets[a][0], gy - offsets[a][1]], axis=-1)
        s = rel @ _rot(thetas[a])                     # == rel @ R^T.T == R^T @ rel
        dc4 = _sample_shape_mv(s[..., 0], s[..., 1])
        dc4_images.append(dc4)
        inv = _rot(-thetas[a])
        truth[a] = (-thetas[a],
                    tuple(float(v) for v in -(inv @ np.array(offsets[a]))))
        adc4 = np.clip(np.round((dc4 - yzero_mv) / ymult_mv + yoff), -128, 127).astype(np.int8)
        block = np.zeros((n_rows, n_ch, n_frames, samples_per_frame), dtype=np.int8)
        block[:, 2] = adc4[:, :, None]                # CH4 carries the sample
        block[:, 1] = 10                              # CH3 flat
        block[:, 0] = rng.integers(-40, 41, size=(n_rows, n_frames, samples_per_frame),
                                   dtype=np.int8)     # CH1 noise
        out += block.tobytes()
    path.write_bytes(bytes(out))
    return {"n_angles": n_angles, "geometry": geom, "stage_angles_deg": stage_angles,
            "truth": truth, "dc4_mv": dc4_images, "x_starts": x_starts,
            "y_starts": y_starts, "dx_mm": _ROT_DX_MM, "dy_mm": _ROT_DY_MM}
 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."""
    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()