write proto to setup mask for interpolated pixels

python/lsst/meas/algorithms/gp_interpolation.py

@@ -78,6 +78,13 @@ def jax_rbf_h(x1, x2, sigma, correlation_length):
     K = (sigma**2) * jnp.exp(-0.5 * l1 / (correlation_length**2))
     return K
 
+def updateMaskFromArray(mask, bad_pixel, interpBit):
+        x0 = mask.getX0()
+        y0 = mask.getY0()
+        for row in bad_pixel:
+            x = int(row[0] - x0)
+            y = int(row[1] - y0)
+            mask.array[x, y] |= interpBit
 
 class GaussianProcessJax:
     def __init__(self, std=1.0, correlation_length=1.0, white_noise=0.0, mean=0.0):
@@ -239,6 +246,8 @@ def __init__(
         self.defects = defects
         self.correlation_length = fwhm
 
+        self.interpBit = self.maskedImage.mask.getPlaneBitMask("INTRP")
+
     def interpolate_over_defects(self):
         """
         Interpolates over defects using the spanset method.
@@ -345,6 +354,7 @@ def interpolate_sub_masked_image(self, sub_masked_image):
 
             # update_value
             ctUtils.updateImageFromArray(sub_masked_image.image, bad_pixel)
+            updateMaskFromArray(sub_masked_image.mask, bad_pixel, self.interpBit)
             return sub_masked_image
 
 def interpolateOverDefectsGP(image, fwhm, badList, method="treegp", bin_spacing=15, threshold_subdivide=20000):