test custom with scheduler fixture

conftest.py

@@ -0,0 +1,31 @@
+
+# -*- Mode: python; tab-width: 4; indent-tabs-mode:nil; coding:utf-8 -*-
+# vim: tabstop=4 expandtab shiftwidth=4 softtabstop=4
+#
+# PMDA
+# Copyright (c) 2017 The MDAnalysis Development Team and contributors
+# (see the file AUTHORS for the full list of names)
+#
+# Released under the GNU Public Licence, v2 or any higher version
+
+from dask import distributed, multiprocessing
+import pytest
+
+@pytest.fixture(scope="session", params=(1, 2))
+def client(tmpdir_factory, request):
+    with tmpdir_factory.mktemp("dask_cluster").as_cwd():
+        lc = distributed.LocalCluster(n_workers=request.param, processes=True)
+        client = distributed.Client(lc)
+
+        yield client
+
+        client.close()
+        lc.close()
+
+
+@pytest.fixture(scope='session', params=('distributed', 'multiprocessing'))
+def scheduler(request, client):
+    if request.param == 'distributed':
+        return client
+    else:
+        return multiprocessing

pmda/rdf.py

@@ -164,7 +164,7 @@ def _conclude(self, ):
     @staticmethod
     def _reduce(res, result_single_frame):
         """ 'add' action for an accumulator"""
-        if res == []:
+        if isinstance(res, list) and len(res) == 0:
             # Convert res from an empty list to a numpy array
             # which has the same shape as the single frame result
             res = result_single_frame

pmda/test/test_custom.py

@@ -8,32 +8,33 @@
 # Released under the GNU Public Licence, v2 or any higher version
 from __future__ import absolute_import, division
 
-import pytest
 
 import numpy as np
-
-from numpy.testing import assert_equal
-
 import MDAnalysis as mda
-from pmda import custom
-
 from MDAnalysisTests.datafiles import PSF, DCD
 from MDAnalysisTests.util import no_deprecated_call
+import pytest
+from numpy.testing import assert_equal
+
+from pmda import custom
 
 
 def custom_function(mobile):
     return mobile.center_of_geometry()
 
 
-def test_AnalysisFromFunction():
+def test_AnalysisFromFunction(scheduler):
     u = mda.Universe(PSF, DCD)
     step = 2
-    ana1 = custom.AnalysisFromFunction(custom_function, u,
-                                       u.atoms).run(step=step)
-    ana2 = custom.AnalysisFromFunction(custom_function, u,
-                                       u.atoms).run(step=step)
-    ana3 = custom.AnalysisFromFunction(custom_function, u,
-                                       u.atoms).run(step=step)
+    ana1 = custom.AnalysisFromFunction(custom_function, u, u.atoms).run(
+        step=step, scheduler=scheduler
+    )
+    ana2 = custom.AnalysisFromFunction(custom_function, u, u.atoms).run(
+        step=step, scheduler=scheduler
+    )
+    ana3 = custom.AnalysisFromFunction(custom_function, u, u.atoms).run(
+        step=step, scheduler=scheduler
+    )
 
     results = []
     for ts in u.trajectory[::step]:
@@ -53,8 +54,9 @@ def test_AnalysisFromFunction_otherAgs():
     u2 = mda.Universe(PSF, DCD)
     u3 = mda.Universe(PSF, DCD)
     step = 2
-    ana = custom.AnalysisFromFunction(custom_function_2, u, u.atoms, u2.atoms,
-                                      u3.atoms).run(step=step)
+    ana = custom.AnalysisFromFunction(
+        custom_function_2, u, u.atoms, u2.atoms, u3.atoms
+    ).run(step=step)
 
     results = []
     for ts in u.trajectory[::step]:

pmda/test/test_parallel.py

@@ -78,26 +78,6 @@ def test_sub_frames(analysis, n_jobs):
     np.testing.assert_almost_equal(analysis.res, [10, 20, 30, 40])
 
 
-@pytest.fixture(scope="session")
-def client(tmpdir_factory):
-    with tmpdir_factory.mktemp("dask_cluster").as_cwd():
-        lc = distributed.LocalCluster(n_workers=2, processes=True)
-        client = distributed.Client(lc)
-
-        yield client
-
-        client.close()
-        lc.close()
-
-
-@pytest.fixture(scope='session', params=('distributed', 'multiprocessing'))
-def scheduler(request, client):
-    if request.param == 'distributed':
-        return client
-    else:
-        return multiprocessing
-
-
 def test_scheduler(analysis, scheduler):
     analysis.run(scheduler=scheduler)