Add Export Fused ROI CSV export

Lets a user export the current ROI as one CSV with a column per selected
angle's value (RF peak freq, Bias A, Bias B, or velocity), once angles share
a common (x, y) grid -- either via a live Fusion alignment result or because
the open file is itself a previous Alignment Wizard export whose angles
already share one grid on disk. Never triggers a background compute; angles
without cached/stored data for the chosen value type are simply unavailable
in the picker.

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

sras_format.py

@@ -770,6 +770,24 @@ class SrasFile:
     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