Fix No-AxisType bug (#122)

* add rules of local axis for NoAxisType * add test for NoAxisType --------- Co-authored-by: plumbum082 <[email protected]>
deepmodeling · Oct 20, 2023 · 5c153bc · 5c153bc
1 parent cd199e4
commit 5c153bc
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diff --git a/dmff/admp/spatial.py b/dmff/admp/spatial.py
@@ -72,6 +72,7 @@ def generate_construct_local_frames(axis_types, axis_indices):
     Bisector_filter = (axis_types == Bisector)
     ZBisect_filter = (axis_types == ZBisect)
     ThreeFold_filter = (axis_types == ThreeFold)
+    NoAxisType_filter = (axis_types == NoAxisType)
 
     def construct_local_frames(positions, box):
         '''
@@ -139,6 +140,13 @@ def construct_local_frames(positions, box):
         vec_x = normalize(vec_x - vec_z * xz_projection, axis=1)
         # up to this point, x-axis should be ready
         vec_y = jnp.cross(vec_z, vec_x)
+
+        # NoAxisType
+        if np.sum(NoAxisType_filter) > 0:
+            vec_y = vec_y.at[NoAxisType_filter].set(jnp.array([0,1,0]))
+            vec_z = vec_z.at[NoAxisType_filter].set(jnp.array([0,0,1]))
+            vec_x = vec_x.at[NoAxisType_filter].set(jnp.array([1,0,0]))
+
 
         return jnp.stack((vec_x, vec_y, vec_z), axis=1)
 

diff --git a/tests/test_admp/test_noaxistype.py b/tests/test_admp/test_noaxistype.py
@@ -0,0 +1,50 @@
+import jax.numpy as jnp
+import numpy as np
+import numpy.testing as npt
+import pytest
+from dmff.admp.spatial import (build_quasi_internal,
+                          generate_construct_local_frames, pbc_shift,
+                          v_pbc_shift)
+
+
+class TestSpatial:
+
+    @pytest.mark.parametrize(
+        "axis_types, axis_indices, positions, box, expected_local_frames",
+        [
+            (
+                np.array([5]),
+                np.array(
+                    [
+                        [-1, -1, -1],
+                    ]
+                ),
+                jnp.array(
+                    [
+                        [0.992, 0.068, -0.073],
+                    ]
+                ),
+                jnp.array([[50.000, 0.0, 0.0], [0.0, 50.000, 0.0], [0.0, 0.0, 50.000]]),
+                np.array(
+                    [
+                        [
+                            [1, 0, 0],
+                            [0, 1, 0],
+                            [0, 0, 1],
+                        ],
+                    ]
+                ),
+            )
+        ],
+    )
+    def test_generate_construct_local_frames(
+        self, axis_types, axis_indices, positions, box, expected_local_frames
+    ):
+        construct_local_frame_fn = generate_construct_local_frames(
+            axis_types, axis_indices
+        )
+        assert construct_local_frame_fn
+        npt.assert_allclose(
+            construct_local_frame_fn(positions, box), expected_local_frames, rtol=1e-5
+        )
+