Reduce duplicate test code with centralized TEST_FILE_PATH constant

kinisi/tests/__init__.py

@@ -0,0 +1,10 @@
+"""
+Tests for kinisi package
+"""
+
+# Copyright (c) kinisi developers.
+# Distributed under the terms of the MIT License.
+
+from pathlib import Path
+
+TEST_FILE_PATH = Path(__file__).parent / 'inputs'

kinisi/tests/test_analyzer.py

@@ -14,19 +14,19 @@
 from ase.io import Trajectory
 from pymatgen.io.vasp import Xdatcar
 
-import kinisi
 from kinisi.analyzer import Analyzer, _flatten_list
+from kinisi.tests import TEST_FILE_PATH
 
-file_path = os.path.join(os.path.dirname(kinisi.__file__), 'tests/inputs/example_XDATCAR.gz')
+file_path = TEST_FILE_PATH / 'example_XDATCAR.gz'
 xd = Xdatcar(file_path)
 da_params = {'specie': 'Li', 'time_step': 2.0 * sc.Unit('ps'), 'step_skip': 50 * sc.Unit('dimensionless')}
 md = mda.Universe(
-    os.path.join(os.path.dirname(kinisi.__file__), 'tests/inputs/example_LAMMPS.data'),
-    os.path.join(os.path.dirname(kinisi.__file__), 'tests/inputs/example_LAMMPS.dcd'),
+    TEST_FILE_PATH / 'example_LAMMPS.data',
+    TEST_FILE_PATH / 'example_LAMMPS.dcd',
     format='LAMMPS',
 )
 db_params = {'specie': '1', 'time_step': 0.005 * sc.Unit('ps'), 'step_skip': 250 * sc.Unit('dimensionless')}
-ase_file_path = os.path.join(os.path.dirname(kinisi.__file__), 'tests/inputs/example_ase.traj')
+ase_file_path = TEST_FILE_PATH / 'example_ase.traj'
 traj = Trajectory(ase_file_path, 'r')
 dc_params = {'specie': 'Li', 'time_step': 1.0 * 1e-3 * sc.Unit('fs'), 'step_skip': 1 * sc.Unit('dimensionless')}
 
@@ -37,7 +37,7 @@ class TestAnalyzer(unittest.TestCase):
     """
 
     def test_to_hdf5(self):
-        xd = Xdatcar(os.path.join(os.path.dirname(kinisi.__file__), 'tests/inputs/example_XDATCAR.gz'))
+        xd = Xdatcar(TEST_FILE_PATH / 'example_XDATCAR.gz')
         da_params = {'specie': 'Li', 'time_step': 2.0 * sc.Unit('fs'), 'step_skip': 50 * sc.Unit('dimensionless')}
         analyzer = Analyzer._from_xdatcar(xd, **da_params)
         test_file = 'test_save.h5'
@@ -47,12 +47,12 @@ def test_to_hdf5(self):
         assert file_exists
 
     def test_load_hdf5(self):
-        test_file = os.path.join(os.path.dirname(kinisi.__file__), 'tests/inputs/example_Analyzer.h5')
+        test_file = TEST_FILE_PATH / 'example_Analyzer.h5'
         analyzer = Analyzer.from_hdf5(test_file)
         assert type(analyzer) is Analyzer
 
     def test_round_trip_hdf5(self):
-        xd = Xdatcar(os.path.join(os.path.dirname(kinisi.__file__), 'tests/inputs/example_XDATCAR.gz'))
+        xd = Xdatcar(TEST_FILE_PATH / 'example_XDATCAR.gz')
         da_params = {'specie': 'Li', 'time_step': 2.0 * sc.Unit('fs'), 'step_skip': 50 * sc.Unit('dimensionless')}
         analyzer = Analyzer._from_xdatcar(xd, **da_params)
         test_file = 'test_save.h5'

kinisi/tests/test_ase.py

@@ -6,16 +6,15 @@
 # Distributed under the terms of the MIT License.
 # author: Oskar G. Soulas (osoulas)
 
-import os
 import unittest
 
 import numpy as np
 import scipp as sc
 from ase.io import Trajectory
 
-import kinisi
 from kinisi import parser
 from kinisi.ase import ASEParser
+from kinisi.tests import TEST_FILE_PATH
 
 
 class TestASEParser(unittest.TestCase):
@@ -24,7 +23,7 @@ class TestASEParser(unittest.TestCase):
     """
 
     def test_ase_datagroup_round_trip(self):
-        traj = Trajectory(os.path.join(os.path.dirname(kinisi.__file__), 'tests/inputs/example_ase.traj'))
+        traj = Trajectory(TEST_FILE_PATH / 'example_ase.traj')
         da_params = {'specie': 'Li', 'time_step': 1e-3 * sc.Unit('fs'), 'step_skip': 1 * sc.Unit('dimensionless')}
         data = ASEParser(traj, **da_params)
         datagroup = data._to_datagroup()

kinisi/tests/test_conductivity_analyzer.py

@@ -17,22 +17,22 @@
 from pymatgen.io.vasp import Xdatcar
 from scipp.testing import assert_allclose
 
-import kinisi
 from kinisi.analyze import ConductivityAnalyzer
 from kinisi.analyzer import Analyzer
 from kinisi.samples import Samples
+from kinisi.tests import TEST_FILE_PATH
 
-file_path = os.path.join(os.path.dirname(kinisi.__file__), 'tests/inputs/example_XDATCAR.gz')
+file_path = TEST_FILE_PATH / 'example_XDATCAR.gz'
 xd = Xdatcar(file_path)
 da_params = {'specie': 'Li', 'time_step': 2.0 * sc.Unit('ps'), 'step_skip': 50 * sc.Unit('dimensionless')}
 
-ase_file_path = os.path.join(os.path.dirname(kinisi.__file__), 'tests/inputs/example_ase.traj')
+ase_file_path = TEST_FILE_PATH / 'example_ase.traj'
 traj = Trajectory(ase_file_path, 'r')
 ase_params = {'specie': 'Li', 'time_step': 1.0 * 1e-3 * sc.Unit('fs'), 'step_skip': 1 * sc.Unit('dimensionless')}
 
 mda_universe = mda.Universe(
-    os.path.join(os.path.dirname(kinisi.__file__), 'tests/inputs/example_LAMMPS.data'),
-    os.path.join(os.path.dirname(kinisi.__file__), 'tests/inputs/example_LAMMPS.dcd'),
+    TEST_FILE_PATH / 'example_LAMMPS.data',
+    TEST_FILE_PATH / 'example_LAMMPS.dcd',
     format='LAMMPS',
 )
 mda_params = {'specie': '1', 'time_step': 0.005 * sc.Unit('fs'), 'step_skip': 250 * sc.Unit('dimensionless')}
@@ -53,14 +53,14 @@ def test_to_hdf5(cls):
         assert file_exists
 
     def test_load_hdf(cls):
-        test_file = os.path.join(os.path.dirname(kinisi.__file__), 'tests/inputs/example_DiffusionAnalyzer.h5')
+        test_file = TEST_FILE_PATH / 'example_DiffusionAnalyzer.h5'
         analyzer = ConductivityAnalyzer.from_hdf5(test_file)
         analyzer_2 = Analyzer.from_hdf5(test_file)
         assert analyzer.trajectory._to_datagroup() == analyzer_2.trajectory._to_datagroup()
         assert type(analyzer) is type(analyzer_2)
 
     def test_round_trip_hdf5(self):
-        xd = Xdatcar(os.path.join(os.path.dirname(kinisi.__file__), 'tests/inputs/example_XDATCAR.gz'))
+        xd = Xdatcar(TEST_FILE_PATH / 'example_XDATCAR.gz')
         da_params = {'specie': 'Li', 'time_step': 2.0 * sc.Unit('fs'), 'step_skip': 50 * sc.Unit('dimensionless')}
         analyzer = ConductivityAnalyzer._from_xdatcar(xd, **da_params)
         test_file = 'test_save.h5'

kinisi/tests/test_diffusion.py

@@ -6,15 +6,14 @@
 # Distributed under the terms of the MIT License.
 # @author: Andrew R. McCluskey (arm61) & Harry Richardson (Harry-Rich)
 
-import os
 import unittest
 
 import numpy as np
 import pytest
 import scipp as sc
 
-import kinisi
 from kinisi.diffusion import Diffusion, _straight_line, minimum_eigenvalue_method
+from kinisi.tests import TEST_FILE_PATH
 
 # Random seed setting not yet implemented into bayesian regression and so cannot almost_equal
 
@@ -41,9 +40,7 @@ def test_straight_line(self):
 class TestDiffusion(unittest.TestCase):
     @classmethod
     def setUpClass(cls):
-        cls.msd_load = sc.io.load_hdf5(
-            filename=os.path.join(os.path.dirname(kinisi.__file__), 'tests/inputs/example_msd2.hdf5')
-        )['_dg']
+        cls.msd_load = sc.io.load_hdf5(filename=TEST_FILE_PATH / 'example_msd2.hdf5')['_dg']
         cls.RNG = np.random.RandomState(42)
         cls.diff = Diffusion(dg=cls.msd_load)
 
@@ -79,9 +76,7 @@ def test__jump_diffusion(self):
         assert self.diff.D_J.to_unit('cm2/s').unit == sc.Unit('cm2/s')
 
     def test__conductivity(self):
-        msd_load = sc.io.load_hdf5(
-            filename=os.path.join(os.path.dirname(kinisi.__file__), 'tests/inputs/example_msd2.hdf5')
-        )['_dg']
+        msd_load = sc.io.load_hdf5(filename=TEST_FILE_PATH / 'example_msd2.hdf5')['_dg']
         diff_cond = Diffusion(dg=msd_load)
         diff_cond.dg['da'] = diff_cond.dg['da'] * sc.scalar(1.0, unit=sc.Unit('coulomb2'))
         start_dt = 300 * sc.Unit('femtosecond')
@@ -126,9 +121,7 @@ def test_posterior_predictive(self):
         custom_samp2 = self.diff.posterior_predictive(n_posterior_samples=1, n_predictive_samples=400, progress=False)
         assert custom_samp2.dims == ('samples', 'time interval')
 
-        msd_load = sc.io.load_hdf5(
-            filename=os.path.join(os.path.dirname(kinisi.__file__), 'tests/inputs/example_msd2.hdf5')
-        )['_dg']
+        msd_load = sc.io.load_hdf5(filename=TEST_FILE_PATH / 'example_msd2.hdf5')['_dg']
         diff_exc = Diffusion(dg=msd_load)
         diff_exc.dg['da'] = diff_exc.dg['da'] * sc.scalar(1.0, unit=sc.Unit('watts'))
 

kinisi/tests/test_diffusion_analyzer.py

@@ -15,12 +15,12 @@
 from pymatgen.io.vasp import Xdatcar
 from scipp.testing import assert_allclose
 
-import kinisi
 from kinisi.analyze import DiffusionAnalyzer
 from kinisi.analyzer import Analyzer
 from kinisi.samples import Samples
+from kinisi.tests import TEST_FILE_PATH
 
-xd = Xdatcar(os.path.join(os.path.dirname(kinisi.__file__), 'tests/inputs/example_XDATCAR.gz'))
+xd = Xdatcar(TEST_FILE_PATH / 'example_XDATCAR.gz')
 da_params = {'specie': 'Li', 'time_step': 2.0 * sc.Unit('fs'), 'step_skip': 50 * sc.Unit('dimensionless')}
 
 
@@ -38,7 +38,7 @@ def test_to_hdf5(cls):
         assert file_exists
 
     def test_load_hdf(cls):
-        test_file = os.path.join(os.path.dirname(kinisi.__file__), 'tests/inputs/example_DiffusionAnalyzer.h5')
+        test_file = TEST_FILE_PATH / 'example_DiffusionAnalyzer.h5'
         analyzer = DiffusionAnalyzer.from_hdf5(test_file)
         analyzer_2 = Analyzer.from_hdf5(test_file)
         assert analyzer.trajectory._to_datagroup() == analyzer_2.trajectory._to_datagroup()

kinisi/tests/test_jump_diffusion_analyzer.py

@@ -16,12 +16,12 @@
 from pymatgen.io.vasp import Xdatcar
 from scipp.testing import assert_allclose
 
-import kinisi
 from kinisi.analyze import JumpDiffusionAnalyzer
 from kinisi.analyzer import Analyzer
 from kinisi.samples import Samples
+from kinisi.tests import TEST_FILE_PATH
 
-file_path = os.path.join(os.path.dirname(kinisi.__file__), 'tests/inputs/example_XDATCAR.gz')
+file_path = TEST_FILE_PATH / 'example_XDATCAR.gz'
 xd = Xdatcar(file_path)
 ase_traj = [AseAtomsAdaptor.get_atoms(struct) for struct in xd.structures]
 da_params = {'specie': 'Li', 'time_step': 2.0 * sc.Unit('ps'), 'step_skip': 50 * sc.Unit('dimensionless')}
@@ -41,14 +41,14 @@ def test_to_hdf5(cls):
         assert file_exists
 
     def test_load_hdf(cls):
-        test_file = os.path.join(os.path.dirname(kinisi.__file__), 'tests/inputs/example_DiffusionAnalyzer.h5')
+        test_file = TEST_FILE_PATH / 'example_DiffusionAnalyzer.h5'
         analyzer = JumpDiffusionAnalyzer.from_hdf5(test_file)
         analyzer_2 = Analyzer.from_hdf5(test_file)
         assert analyzer.trajectory._to_datagroup() == analyzer_2.trajectory._to_datagroup()
         assert type(analyzer) is type(analyzer_2)
 
     def test_round_trip_hdf5(self):
-        xd = Xdatcar(os.path.join(os.path.dirname(kinisi.__file__), 'tests/inputs/example_XDATCAR.gz'))
+        xd = Xdatcar(TEST_FILE_PATH / 'example_XDATCAR.gz')
         da_params = {'specie': 'Li', 'time_step': 2.0 * sc.Unit('fs'), 'step_skip': 50 * sc.Unit('dimensionless')}
         analyzer = JumpDiffusionAnalyzer._from_xdatcar(xd, **da_params)
         test_file = 'test_save.h5'

kinisi/tests/test_mdanalysis.py

@@ -6,7 +6,6 @@
 # Distributed under the terms of the MIT License.
 # author: Oskar G. Soulas (osoulas)
 
-import os
 import unittest
 
 import MDAnalysis as mda
@@ -15,9 +14,9 @@
 from numpy.testing import assert_almost_equal
 from scipp.testing.assertions import assert_allclose, assert_identical
 
-import kinisi
 from kinisi import parser
 from kinisi.mdanalysis import MDAnalysisParser
+from kinisi.tests import TEST_FILE_PATH
 
 
 class TestMDAnalysisParser(unittest.TestCase):
@@ -27,8 +26,8 @@ class TestMDAnalysisParser(unittest.TestCase):
 
     def test_mdanalysis_datagroup_round_trip(self):
         xd = mda.Universe(
-            os.path.join(os.path.dirname(kinisi.__file__), 'tests/inputs/example_LAMMPS.data'),
-            os.path.join(os.path.dirname(kinisi.__file__), 'tests/inputs/example_LAMMPS.dcd'),
+            TEST_FILE_PATH / 'example_LAMMPS.data',
+            TEST_FILE_PATH / 'example_LAMMPS.dcd',
             format='LAMMPS',
         )
         da_params = {'specie': '1', 'time_step': 0.005 * sc.Unit('fs'), 'step_skip': 250 * sc.Unit('dimensionless')}
@@ -43,8 +42,8 @@ def test_mdanalysis_datagroup_round_trip(self):
 
     def test_mda_init(self):
         xd = mda.Universe(
-            os.path.join(os.path.dirname(kinisi.__file__), 'tests/inputs/example_LAMMPS.data'),
-            os.path.join(os.path.dirname(kinisi.__file__), 'tests/inputs/example_LAMMPS.dcd'),
+            TEST_FILE_PATH / 'example_LAMMPS.data',
+            TEST_FILE_PATH / 'example_LAMMPS.dcd',
             format='LAMMPS',
         )
         da_params = {'specie': '1', 'time_step': 0.005, 'step_skip': 250}
@@ -57,8 +56,8 @@ def test_mda_init(self):
 
     def test_mda_init_with_indices(self):
         xd = mda.Universe(
-            os.path.join(os.path.dirname(kinisi.__file__), 'tests/inputs/example_LAMMPS.data'),
-            os.path.join(os.path.dirname(kinisi.__file__), 'tests/inputs/example_LAMMPS.dcd'),
+            TEST_FILE_PATH / 'example_LAMMPS.data',
+            TEST_FILE_PATH / 'example_LAMMPS.dcd',
             format='LAMMPS',
         )
         specie_indices = sc.array(dims=['particle'], values=[208, 212], unit=sc.units.dimensionless)

kinisi/tests/test_parser.py

@@ -7,7 +7,6 @@
 # author: Andrew R. McCluskey (arm61), Josh Dunn (jd15489) & Oskar G. Soulas (osoulas)
 # pylint: disable=R0201
 
-import os
 import unittest
 
 import MDAnalysis as mda
@@ -16,8 +15,8 @@
 import scipp as sc
 from numpy.testing import assert_almost_equal, assert_equal
 
-import kinisi
 from kinisi import parser
+from kinisi.tests import TEST_FILE_PATH
 
 
 class mda_universe_generator:
@@ -208,7 +207,7 @@ def test_non_orthorhombic_calculate_displacements(self):
         assert_almost_equal(disp.values, test_disp.values)
 
 
-dg = sc.io.load_hdf5(os.path.join(os.path.dirname(kinisi.__file__), 'tests/inputs/example_drift.h5'))
+dg = sc.io.load_hdf5(TEST_FILE_PATH / 'example_drift.h5')
 coords = dg['coords']
 latt = dg['latt']
 time_step = dg['time_step']

kinisi/tests/test_pymatgen.py

@@ -6,16 +6,15 @@
 # Distributed under the terms of the MIT License.
 # author: Oskar G. Soulas (osoulas)
 
-import os
 import unittest
 
 import numpy as np
 import scipp as sc
 from pymatgen.io.vasp import Xdatcar
 
-import kinisi
 from kinisi import parser
 from kinisi.pymatgen import PymatgenParser
+from kinisi.tests import TEST_FILE_PATH
 
 
 class TestPymatgenParser(unittest.TestCase):
@@ -24,7 +23,7 @@ class TestPymatgenParser(unittest.TestCase):
     """
 
     def test_pymatgen_datagroup_round_trip(self):
-        xd = Xdatcar(os.path.join(os.path.dirname(kinisi.__file__), 'tests/inputs/example_XDATCAR.gz'))
+        xd = Xdatcar(TEST_FILE_PATH / 'example_XDATCAR.gz')
         da_params = {'specie': 'Li', 'time_step': 2.0 * sc.Unit('fs'), 'step_skip': 50 * sc.Unit('dimensionless')}
         data = PymatgenParser(xd.structures, **da_params)
         datagroup = data._to_datagroup()