def test_micro_pyawk(self):
filename = os.path.join(test_dir, "OUTCAR")
data = []
def f(x, y):
data.append(y.group(1).strip())
f2 = lambda x, y: y
micro_pyawk(filename, [["POTCAR:(.*)", f2, f]])
self.assertEqual(len(data), 6)
def test_micro_pyawk(self):
filename = os.path.join(test_dir, "OUTCAR")
data = []
def f(x, y):
data.append(y.group(1).strip())
f2 = lambda x, y: y
micro_pyawk(filename, [["POTCAR:(.*)", f2, f]])
self.assertEqual(len(data), 6)
def test_micro_pyawk(self):
filename = os.path.join(PymatgenTest.TEST_FILES_DIR, "OUTCAR")
data = []
def f(x, y):
data.append(y.group(1).strip())
def f2(x, y):
return y
micro_pyawk(filename, [["POTCAR:(.*)", f2, f]])
self.assertEqual(len(data), 6)
def read_berry_ev(self, fname):
"""
Read berry_ev in pymatgen way.
"""
berry_ev = []
for spin in [1, 2]:
search = []
def func_berry_ev(results, match):
results.berry = np.array([
float(match.group(1)),
float(match.group(2)),
float(match.group(3)),
])
search.append([
r"Spin component " + str(spin) + "\s"
r"*e<r>_ev=\( *([-0-9.Ee+]*) *([-0-9.Ee+]*) "
r"*([-0-9.Ee+]*) *\)", None, func_berry_ev
])
results = micro_pyawk(fname, search, self)
berry_ev.append(results.berry)
# average over spin components 1 and 2
berry_ev = np.mean(berry_ev, axis=0)
return (berry_ev)