More 10081 fixes

gallery/experiments/experimental_abinitio_pipeline_10081.py

@@ -59,7 +59,11 @@
 
 # Create a source object for the experimental images
 src = RelionSource(
-    starfile_in, pixel_size=pixel_size, max_rows=n_imgs, data_folder=data_folder
+    starfile_in,
+    pixel_size=pixel_size,
+    max_rows=n_imgs,
+    data_folder=data_folder,
+    symmetry_group="C4",
 )
 
 # Downsample the images
@@ -115,12 +119,13 @@
 # Volume Reconstruction
 # ----------------------
 #
-# Using the oriented source, attempt to reconstruct a volume.
-# Since this is a Cn symmetric molecule, as indicated by
-# ``symmetry="C4"`` above, the ``avgs`` images set will be repeated
-# for each of the 3 additional rotations during the back-projection
-# step.  This boosts the effective number of images used in the
-# reconstruction from ``n_classes`` to ``4*n_classes``.
+# Using the oriented source, attempt to reconstruct a volume.  Since
+# this is a Cn symmetric molecule, as specified by ``RelionSource(...,
+# symmetry_group="C4", ...)``, the ``symmetry_group`` source attribute
+# will flow through the pipeline to ``avgs``. Then each image will be
+# repeated for each of the 3 additional rotations during
+# back-projection.  This boosts the effective number of images used in
+# the reconstruction from ``n_classes`` to ``4*n_classes``.
 
 logger.info("Begin Volume reconstruction")
 

src/aspire/abinitio/commonline_c3_c4.py

@@ -47,7 +47,7 @@ def __init__(
         n_theta=None,
         max_shift=0.15,
         shift_step=1,
-        epsilon=1e-3,
+        epsilon=1e-2,
         max_iters=1000,
         degree_res=1,
         seed=None,
@@ -691,7 +691,8 @@ def _J_sync_power_method(self, vijs):
         )
         while itr < max_iters and residual > epsilon:
             itr += 1
-            vec_new = self._signs_times_v(vijs, vec)
+            # Note, this appears to need double precision for accuracy in the following division.
+            vec_new = self._signs_times_v(vijs, vec).astype(np.float64, copy=False)
             vec_new = vec_new / norm(vec_new)
             residual = norm(vec_new - vec)
             vec = vec_new

src/aspire/denoising/class_avg.py

@@ -76,6 +76,7 @@ def __init__(
             L=self.averager.src.L,
             n=self.averager.src.n,
             dtype=self.averager.src.dtype,
+            symmetry_group=self.src.symmetry_group,
         )
 
         # Any further operations should not mutate this instance.

src/aspire/image/image.py

@@ -517,6 +517,8 @@ def backproject(self, rot_matrices, symmetry_group=None):
 
         # Get symmetry rotations from SymmetryGroup.
         symmetry_rots = SymmetryGroup.parse(symmetry_group, dtype=self.dtype).matrices
+        if len(symmetry_rots) > 1:
+            logger.info(f"Boosting with {len(symmetry_rots)} rotational symmetries.")
 
         # Compute Fourier transform of images.
         im_f = xp.asnumpy(fft.centered_fft2(xp.asarray(self._data))) / (L**2)

tests/test_class_src.py

@@ -128,7 +128,14 @@ def class_sim_fixture(dtype, img_size):
     # Note using a single volume via C=1 is critical to matching
     # alignment without the complexity of remapping via states etc.
     src = Simulation(
-        L=img_size, n=n, vols=v, offsets=0, amplitudes=1, C=1, angles=true_rots.angles
+        L=img_size,
+        n=n,
+        vols=v,
+        offsets=0,
+        amplitudes=1,
+        C=1,
+        angles=true_rots.angles,
+        symmetry_group="C4",  # For testing symmetry_group pass-through.
     )
     # Prefetch all the images
     src = src.cache()
@@ -193,6 +200,9 @@ class averages.
     k = len(src2.class_indices)
     np.testing.assert_equal(src2.class_indices, test_src.class_indices[::3][:k])
 
+    # Check symmetry_group pass-through.
+    assert test_src.symmetry_group == class_sim_fixture.symmetry_group
+
 
 # Test the _HeapItem helper class
 def test_heap_helper():

tests/test_indexed_source.py

@@ -13,7 +13,7 @@ def sim_fixture():
     """
     Generate a very small simulation and slice it.
     """
-    sim = Simulation(L=8, n=10, C=1)
+    sim = Simulation(L=8, n=10, C=1, symmetry_group="D3")
     sim2 = sim[0::2]  # Slice the evens
     return sim, sim2
 
@@ -31,6 +31,9 @@ def test_remapping(sim_fixture):
     # Check meta is served correctly.
     assert np.all(sim.get_metadata(indices=sim2.index_map) == sim2.get_metadata())
 
+    # Check symmetry_group pass-through.
+    assert sim.symmetry_group == sim2.symmetry_group
+
 
 def test_repr(sim_fixture):
     sim, sim2 = sim_fixture