moved NAMD BAR test to test_fep

- moved test
- added test for the error (regression test)
- use fixture for NAMD dataset and parametrized test for forward/backward legs
  in order to simplify code

src/alchemlyb/tests/parsing/test_namd.py

@@ -1,46 +1,24 @@
 """NAMD parser tests.
 
 """
+import pytest
 
 from alchemlyb.parsing.namd import extract_u_nk
 from alchemtest.namd import load_tyr2ala
-from numpy.testing import assert_almost_equal
 
+@pytest.fixture(scope="module")
+def dataset():
+    return load_tyr2ala()
 
-def test_u_nk():
+@pytest.mark.parametrize("direction,shape",
+                         [('forward', (21021, 21)),
+                          ('backward', (21021, 21)),
+                          ])
+def test_u_nk(dataset, direction, shape):
     """Test that u_nk has the correct form when extracted from files.
     """
-    dataset = load_tyr2ala()
+    for filename in dataset['data'][direction]:
+        u_nk = extract_u_nk(filename)
 
-    for direction in dataset['data']:
-        for filename in dataset['data'][direction]:
-            u_nk = extract_u_nk(filename)
-
-            assert u_nk.index.names == ['timestep', 'fep-lambda']
-            if direction == 'forward':
-                assert u_nk.shape == (21021, 21)
-            elif direction == 'backward':
-                assert u_nk.shape == (21021, 21)
-
-def test_bar_namd():
-    """Test BAR calculation on NAMD data.
-    """
-    from alchemlyb.estimators import BAR
-    import numpy as np
-
-    # load data
-    dataset = load_tyr2ala()
-    u_nk1 = extract_u_nk(dataset['data']['forward'][0])
-    u_nk2 = extract_u_nk(dataset['data']['backward'][0])
-
-    # combine dataframes of fwd and rev directions
-    u_nk1.replace(0, np.nan, inplace=True)
-    u_nk1[u_nk1.isnull()] = u_nk2
-    u_nk1.replace(np.nan, 0, inplace=True)
-    u_nk = u_nk1.sort_index(level=u_nk1.index.names[1:])
-
-    # after loading BOTH fwd and rev data, do BAR calculation
-    bar = BAR()
-    bar.fit(u_nk)
-    dg = (bar.delta_f_.iloc[0].iloc[-1])
-    assert_almost_equal(dg, 6.03126982925, decimal=4)
+        assert u_nk.index.names == ['timestep', 'fep-lambda']
+        assert u_nk.shape == shape

src/alchemlyb/tests/test_fep_estimators.py

@@ -3,13 +3,15 @@
 """
 import pytest
 
+import numpy as np
 import pandas as pd
 
-from alchemlyb.parsing import gmx, amber
+from alchemlyb.parsing import gmx, amber, namd
 from alchemlyb.estimators import MBAR
 from alchemlyb.estimators import BAR
 import alchemtest.gmx
 import alchemtest.amber
+import alchemtest.namd
 
 def gmx_benzene_coul_u_nk():
     dataset = alchemtest.gmx.load_benzene()
@@ -82,6 +84,19 @@ def amber_bace_example_complex_vdw():
                       for filename in dataset['data']['complex']['vdw']])
     return u_nk
 
+def namd_tyr2ala():
+    dataset = alchemtest.namd.load_tyr2ala()
+    u_nk1 = namd.extract_u_nk(dataset['data']['forward'][0])
+    u_nk2 = namd.extract_u_nk(dataset['data']['backward'][0])
+
+    # combine dataframes of fwd and rev directions
+    u_nk1.replace(0, np.nan, inplace=True)
+    u_nk1[u_nk1.isnull()] = u_nk2
+    u_nk1.replace(np.nan, 0, inplace=True)
+    u_nk = u_nk1.sort_index(level=u_nk1.index.names[1:])
+
+    return u_nk
+
 class FEPestimatorMixin:
     """Mixin for all FEP Estimator test classes.
 
@@ -134,6 +149,7 @@ class TestBAR(FEPestimatorMixin):
         (gmx_water_particle_with_potential_energy(), -11.724, 0.064964),
         (gmx_water_particle_without_energy(), -11.660, 0.064914),
         (amber_bace_example_complex_vdw(), 2.37846, 0.050899),
+        (namd_tyr2ala(), 6.031269829, 0.069813058),
     ])
     def test_bar(self, X_delta_f):
         self.compare_delta_f(X_delta_f)