Replace zoom FFT peak search with a budget-bounded PyFFTW direct transform

Drop the coarse+fine zoom refinement, the SciPy FFT backend, and the
exact= audit path in favor of a single always-on full-transform peak
search (_peak_bins). Block size is now derived from a per-thread memory
budget (_fft_block_for/SRAS_FFT_PLAN_BUDGET_MB) instead of a fixed
constant, so the existing block-parallel PyFFTW pool stays memory-safe
at high pad factors without the zoom algorithm's bookkeeping. Also
removes the now-unused threadpoolctl dependency and the FFT backend
selector from the UI.

Also includes a pre-existing min_freq_mhz peak-search floor (excludes
bins below a caller-supplied frequency from the argmax) that was
already implemented and tested in the working tree.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>

sras_viewer/canvases.py

@@ -166,11 +166,14 @@ class ImageCanvas(FigureCanvasQTAgg):
 
     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):
+                   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."""
+        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.
@@ -179,6 +182,10 @@ class ImageCanvas(FigureCanvasQTAgg):
         self._extent = extent
         self._img_shape = img.shape
 
+        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 = self.ax.imshow(