building

meteor/utils.py

@@ -21,6 +21,7 @@ def cut_resolution(dataset: rs.DataSet, *, dmax_limit: float | None = None, dmin
 @overload
 def canonicalize_amplitudes(
         dataset: rs.DataSet,
+        *,
         amplitude_label: str,
         phase_label: str,
         inplace: Literal[False],
@@ -31,6 +32,7 @@ def canonicalize_amplitudes(
 @overload
 def canonicalize_amplitudes(
         dataset: rs.DataSet,
+        *,
         amplitude_label: str,
         phase_label: str,
         inplace: Literal[True],
@@ -40,6 +42,7 @@ def canonicalize_amplitudes(
 
 def canonicalize_amplitudes(
         dataset: rs.DataSet,
+        *,
         amplitude_label: str,
         phase_label: str,
         inplace: bool = False,

test/conftest.py

@@ -28,4 +28,34 @@ def random_intensities() -> rs.DataSet:
     ).infer_mtz_dtypes()
     ds.set_index(["H", "K", "L"], inplace=True)
 
-    return ds
+    return ds
+
+
+@fixture
+def flat_difference_map() -> rs.DataSet:
+    """
+    A simple 3x3x3 P1 map, random
+    """
+
+    params = (10.0, 10.0, 10.0, 90.0, 90.0, 90.0)
+    cell = gm.UnitCell(*params)
+    sg_1 = gm.SpaceGroup(1)
+    Hall = rs.utils.generate_reciprocal_asu(cell, sg_1, 5.0, anomalous=False)
+
+    h, k, l = Hall.T
+    ds = rs.DataSet(
+        {
+            "H": h,
+            "K": k,
+            "L": l,
+            "DF": np.random.randn(len(h)),
+            "PHIC": np.zeros(len(h)),
+        },
+        spacegroup=sg_1,
+        cell=cell,
+    ).infer_mtz_dtypes()
+
+    ds.set_index(["H", "K", "L"], inplace=True)
+    ds["DF"] = ds["DF"].astype("SFAmplitude")
+
+    return ds

test/unit/test_tv.py

@@ -3,39 +3,9 @@
 import reciprocalspaceship as rs
 import gemmi as gm
 import numpy as np
-
-from pytest import fixture
 from meteor import tv
 
 
-@fixture
-def flat_difference_map() -> rs.DataSet:
-    """
-    A simple 3x3x3 P1 map, random
-    """
-
-    params = (10.0, 10.0, 10.0, 90.0, 90.0, 90.0)
-    cell = gm.UnitCell(*params)
-    sg_1 = gm.SpaceGroup(1)
-    Hall = rs.utils.generate_reciprocal_asu(cell, sg_1, 5.0, anomalous=False)
-
-    h, k, l = Hall.T
-    ds = rs.DataSet(
-        {
-            "H": h,
-            "K": k,
-            "L": l,
-            "DF": np.random.randn(len(h)),
-            "PHIC": np.zeros(len(h)),
-        },
-        spacegroup=sg_1,
-        cell=cell,
-    ).infer_mtz_dtypes()
-    ds.set_index(["H", "K", "L"], inplace=True)
-
-    return ds
-
-
 def test_tv_denoise_difference_map_smoke(flat_difference_map: rs.DataSet) -> None:
 
     # test sequence pf specified lambda

test/unit/test_utils.py

@@ -42,6 +42,7 @@ def test_cut_resolution(random_intensities: rs.DataSet, dmax_limit: float, dmin_
     assert dmax <= expected_max_dmax
     assert dmin >= expected_min_dmin
 
+
 @pytest.mark.parametrize("inplace", [False, True])
 def test_canonicalize_amplitudes(inplace: bool, flat_difference_map: rs.DataSet) -> None:
     amplitude_label = "DF"
@@ -83,31 +84,32 @@ def test_compute_map_from_coefficients(flat_difference_map: rs.DataSet) -> None:
     assert map.grid.shape == (6,6,6)
 
 
-# def test_map_round_trip_ccp4_format(flat_difference_map: rs.DataSet) -> None:
-#     amplitude_label = "DF"
-#     phase_label = "PHIC"
-#     map_sampling = 1
-
-#     flat_difference_map = utils.canonicalize_amplitudes(
-#         flat_difference_map,
-#         amplitude_label=amplitude_label,
-#         phase_label=phase_label
-#     )
-
-#     map = utils.compute_map_from_coefficients(
-#         map_coefficients=flat_difference_map,
-#         amplitude_label=amplitude_label,
-#         phase_label=phase_label,
-#         map_sampling=map_sampling,
-#     )
-
-#     _, dmin = utils.resolution_limits(flat_difference_map)
-
-#     output_coefficients = utils.compute_coefficients_from_map(
-#         map=map,
-#         high_resolution_limit=dmin,
-#         amplitude_label=amplitude_label,
-#         phase_label=phase_label,
-#     )
-
-#     pd.testing.assert_frame_equal(left=flat_difference_map, right=output_coefficients, check_exact=False) 
+def test_map_round_trip_ccp4_format(flat_difference_map: rs.DataSet) -> None:
+    amplitude_label = "DF"
+    phase_label = "PHIC"
+    map_sampling = 1
+
+    utils.canonicalize_amplitudes(
+        flat_difference_map,
+        amplitude_label=amplitude_label,
+        phase_label=phase_label,
+        inplace=True
+    )
+
+    map = utils.compute_map_from_coefficients(
+        map_coefficients=flat_difference_map,
+        amplitude_label=amplitude_label,
+        phase_label=phase_label,
+        map_sampling=map_sampling,
+    )
+
+    _, dmin = utils.resolution_limits(flat_difference_map)
+
+    output_coefficients = utils.compute_coefficients_from_map(
+        map=map,
+        high_resolution_limit=dmin,
+        amplitude_label=amplitude_label,
+        phase_label=phase_label,
+    )
+
+    pd.testing.assert_frame_equal(left=flat_difference_map, right=output_coefficients, atol=1e-5)