def setUp(self):
# Load the object
# Imports
from opan.grad import OrcaEngrad
# Create the object
self.oe = OrcaEngrad(path=self.file_name)
# Enable long messages
self.longMessage = True
def test_ENGRAD_AltDataAtomicSymbol(self):
from opan.grad import OrcaEngrad
# Fail if any exception raised while loading the modified file
# with copper specified as the atomic symbol
try:
oe = OrcaEngrad(path=(self.file_name + self.names.atomicsym))
except Exception:
self.fail("Failed to load .engrad file with atomic symbol")
def test_ENGRAD_LiveData(self):
import os
from opan.grad import OrcaEngrad
from opan.error import GradError
for fname in os.listdir(self.resourcedir):
if fname.startswith("test_orca") and fname.endswith("engrad"):
print("\nTesting file '" + fname + "' ... ")
try:
OrcaEngrad(path=os.path.join(self.resourcedir, fname))
except (IOError, GradError) as e: # pragma: no cover
self.longMessage = True
self.fail("Load of test file '" + str(fname) +
"' failed:\n" + str(e))
class TestOrcaEngradKnownGood(SuperOrcaEngrad):
# Testing errors related to file parsing of a known-good ENGRAD file
@classmethod
def setUpClass(cls):
from opan.test.utils import setUpTestDir
# Set up the directory
setUpTestDir(cls.testdir)
# Write the file
with open(cls.file_name, 'w') as f:
f.write(cls.file_text_good)
@classmethod
def tearDownClass(cls):
import os
from opan.test.utils import tearDownTestDir
# Delete the engrad file
os.remove(cls.file_name)
# Remove the working directory
tearDownTestDir(cls.testdir)
def setUp(self):
# Load the object
# Imports
from opan.grad import OrcaEngrad
# Create the object
self.oe = OrcaEngrad(path=self.file_name)
# Enable long messages
self.longMessage = True
def test_ENGRAD_KnownGoodAtomVec(self):
# Confirm the values coming out of the ENGRAD match the known-good
# example file.
# Confirm the atom list is good
for i in range(len(self.oe.atom_syms)):
self.assertEqual(self.oe.atom_syms[i], self.atoms[i])
def test_ENGRAD_KnownGoodGradient(self):
# Confirm the known-good gradient matches what's expected.
# Confirm the gradient vector is good
for i in range(self.oe.gradient.shape[0]):
self.assertAlmostEqual(self.oe.gradient[i],
self.gradient[i], delta=1e-10,
msg="Gradient index " + str(i))
def test_ENGRAD_KnownGoodEnergy(self):
# Confirm the known-good energy matches what's expected
self.assertAlmostEqual(self.energy, self.oe.energy, delta=1e-12)
def test_ENGRAD_KnownGoodGeom(self):
for i in range(self.oe.geom.shape[0]):
self.assertAlmostEqual(self.oe.geom[i],
self.geom[i], delta=1e-7,
msg="Coordinate index " + str(i))
def test_ENGRAD_KnownGoodCheckGeomMatches(self):
self.assertTrue(self.oe.check_geom(self.oe.geom, self.oe.atom_syms))