#!/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 # 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): 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 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) 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. 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): 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 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, compute.get_fft_backend(), per_proc_workers, pad_factor=self._pad_factor, dc_threshold_mv=self._dc_threshold, row_avg_n=self._row_avg_n): 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.get_fft_backend(), compute.default_max_workers(), pad_factor=self._pad_factor, dc_threshold_mv=self._dc_threshold, row_avg_n=self._row_avg_n) 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): """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.""" fig = Figure(figsize=(7, 5), 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. 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): 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 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) 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)) 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 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))