feat(transform): add mask projection to full regridder

draco/analysis/transform.py

@@ -819,6 +819,12 @@ class Regridder(task.SingleTask):
     mask_zero_weight: bool
         Mask the output noise weights at frequencies where the weights were
         zero for all time samples.
+    mask_thresh : float
+        Fraction of lanczos kernel sum below which the projected mask is flagged.
+        The boolean data mask is projected into RA using the lanczos kernel, and
+        samples below this fraction of the kernel weight are flagged. The default
+        value should ensure that only weights equal to zero are flagged.
+        Default is 1e-3.
     """
 
     samples = config.Property(proptype=int, default=1024)
@@ -827,6 +833,7 @@ class Regridder(task.SingleTask):
     lanczos_width = config.Property(proptype=int, default=5)
     snr_cov = config.Property(proptype=float, default=1e-8)
     mask_zero_weight = config.Property(proptype=bool, default=False)
+    mask_thresh = config.Property(proptype=float, default=1e-3)
 
     def setup(self, observer):
         """Set the local observers position.
@@ -904,6 +911,10 @@ def _regrid(self, vis_data, weight, times):
             interp_grid, times, self.lanczos_width
         ).T.copy()
 
+        # Make a projection of the mask
+        mp = np.any(weight > 0, axis=1) @ lzf.T
+        mp = mp > self.mask_thresh * np.mean(np.sum(lzf, axis=1))
+
         # Reshape data
         vr = vis_data.reshape(-1, vis_data.shape[-1])
         nr = weight.reshape(-1, vis_data.shape[-1])
@@ -925,8 +936,7 @@ def _regrid(self, vis_data, weight, times):
 
         if self.mask_zero_weight:
             # set weights to zero where there is no data
-            w_mask = weight.sum(axis=-1) != 0.0
-            ni *= w_mask[..., np.newaxis]
+            ni *= mp[:, np.newaxis][..., pad:-pad]
 
         return interp_grid, sts, ni