def abivalidate_work(self, work):
"""Invoke Abinit to test validity of the inputs of a |Work|"""
from abipy.flowtk import Flow
tmpdir = tempfile.mkdtemp()
flow = Flow(workdir=tmpdir)
flow.register_work(work)
return self.abivalidate_flow(flow)
def open(cls, obj, nids=None, **kwargs):
"""
Flexible constructor. obj can be a :class:`Flow` or a string with the directory containing the Flow.
nids is an optional list of :class:`Node` identifiers used to filter the set of :class:`Task` in the Flow.
"""
has_dirpath = False
if is_string(obj):
try:
obj = Flow.pickle_load(obj)
except:
has_dirpath = True
if not has_dirpath:
# We have a Flow. smeth is the name of the Task method used to open the file.
items = []
smeth = "open_" + cls.EXT.lower()
for task in obj.iflat_tasks(nids=nids): #, status=obj.S_OK):
open_method = getattr(task, smeth, None)
if open_method is None: continue
ncfile = open_method()
if ncfile is not None: items.append((task.pos_str, ncfile))
return cls(*items)
else:
# directory --> search for files with the appropriate extension and open it with abiopen.
if nids is not None:
raise ValueError(
"nids cannot be used when obj is a directory.")
return cls.from_dir(obj)
def test_g0w0_with_ppmodel_inputs(self):
"""Testing g0w0_with_ppmodel_input factory."""
scf_kppa, scf_nband, nscf_nband = 10, 10, 10
ecuteps, ecutsigx = 2, 2
multi = g0w0_with_ppmodel_inputs(self.si_structure,
self.si_pseudo,
scf_kppa,
nscf_nband,
ecuteps,
ecutsigx,
shifts=(0.5, 0.5, 0.5),
ecut=2)
scf_input, nscf_input, scr_input, sigma_input = multi.split_datasets()
self.abivalidate_multi(multi)
self.assertIn('many_body', scr_input.runlevel)
self.assertIn('screening', scr_input.runlevel)
self.abivalidate_input(sigma_input)
self.assertIn('many_body', sigma_input.runlevel)
self.assertIn('sigma', sigma_input.runlevel)
self.assertNotIn('hybrid', sigma_input.runlevel)
if write_inputs_to_json:
with open('g0w0_with_ppmodel_scf_input.json', mode='w') as fp:
json.dump(scf_input.as_dict(), fp, indent=2)
with open('g0w0_with_ppmodel_nscf_input.json', mode='w') as fp:
json.dump(nscf_input.as_dict(), fp, indent=2)
with open('g0w0_with_ppmodel_scr_input.json', mode='w') as fp:
json.dump(scr_input.as_dict(), fp, indent=2)
with open('g0w0_with_ppmodel_sigma_input.json', mode='w') as fp:
json.dump(sigma_input.as_dict(), fp, indent=2)
self.assert_input_equality('g0w0_with_ppmodel_scf_input.json',
scf_input)
self.assert_input_equality('g0w0_with_ppmodel_nscf_input.json',
nscf_input)
self.assert_input_equality('g0w0_with_ppmodel_scr_input.json',
scr_input)
self.assert_input_equality('g0w0_with_ppmodel_sigma_input.json',
sigma_input)
flow = Flow.temporary_flow()
flow.register_work(
G0W0Work(scf_input, nscf_input, scr_input, sigma_input))
assert flow.build_and_pickle_dump(abivalidate=True) == 0
# The default value of `shifts` changed in v0.3 from (0.5, 0.5, 0.5) to (0.0, 0.0, 0.0)
multi = g0w0_with_ppmodel_inputs(self.si_structure,
self.si_pseudo,
scf_kppa,
nscf_nband,
ecuteps,
ecutsigx,
ecut=2)
for inp in multi:
self.assert_equal(inp["shiftk"].flatten(), (0, 0, 0))
def test_ion_ioncell_relax_input(self):
"""Testing ion_ioncell_relax_input factory."""
multi = ion_ioncell_relax_input(self.si_structure, self.si_pseudo, kppa=10, ecut=2)
# scf_kppa, scf_nband #accuracy="normal", spin_mode="polarized",
# smearing="fermi_dirac:0.1 eV", charge=0.0, scf_algorithm=None)
ion_inp, ioncell_inp = multi.split_datasets()
self.assertIn('ion_relax', ion_inp.runlevel)
self.assertIn('relax', ion_inp.runlevel)
self.assertIn('ground_state', ion_inp.runlevel)
flow = Flow.temporary_flow()
flow.register_work(RelaxWork(ion_inp, ioncell_inp))
assert flow.build_and_pickle_dump(abivalidate=True) == 0
def test_ion_ioncell_relax_input(self):
"""Testing ion_ioncell_relax_input factory."""
multi = ion_ioncell_relax_input(self.si_structure, self.si_pseudo, kppa=10, ecut=2)
# scf_kppa, scf_nband #accuracy="normal", spin_mode="polarized",
# smearing="fermi_dirac:0.1 eV", charge=0.0, scf_algorithm=None)
ion_inp, ioncell_inp = multi.split_datasets()
self.assertIn('ion_relax', ion_inp.runlevel)
self.assertIn('relax', ion_inp.runlevel)
self.assertIn('ground_state', ion_inp.runlevel)
flow = Flow.temporary_flow()
flow.register_work(RelaxWork(ion_inp, ioncell_inp))
assert flow.build_and_pickle_dump(abivalidate=True) == 0
def test_flow(self):
"""
Testing flow creation and task registering
"""
flow = Flow(workdir=test_dir,
manager=TaskManager.from_file(
os.path.join(test_dir, "manager.yml")))
inp = {}
flow.register_task(input=inp)
flow.allocate()
self.assertTrue(flow.allocated)
self.assertIsInstance(flow[0], Work)
self.assertIsInstance(flow[0][0], AbinitTask)
self.assertEqual(flow.check_status(), None)
def test_g0w0_with_ppmodel_inputs(self):
"""Testing g0w0_with_ppmodel_input factory."""
scf_kppa, scf_nband, nscf_nband = 10, 10, 10
ecuteps, ecutsigx = 2, 2
multi = g0w0_with_ppmodel_inputs(self.si_structure, self.si_pseudo,
scf_kppa, nscf_nband, ecuteps, ecutsigx,
shifts=(0.5, 0.5, 0.5), ecut=2)
scf_input, nscf_input, scr_input, sigma_input = multi.split_datasets()
self.abivalidate_multi(multi)
self.assertIn('many_body', scr_input.runlevel)
self.assertIn('screening', scr_input.runlevel)
self.abivalidate_input(sigma_input)
self.assertIn('many_body', sigma_input.runlevel)
self.assertIn('sigma', sigma_input.runlevel)
self.assertNotIn('hybrid', sigma_input.runlevel)
if write_inputs_to_json:
with open('g0w0_with_ppmodel_scf_input.json', mode='w') as fp:
json.dump(scf_input.as_dict(), fp, indent=2)
with open('g0w0_with_ppmodel_nscf_input.json', mode='w') as fp:
json.dump(nscf_input.as_dict(), fp, indent=2)
with open('g0w0_with_ppmodel_scr_input.json', mode='w') as fp:
json.dump(scr_input.as_dict(), fp, indent=2)
with open('g0w0_with_ppmodel_sigma_input.json', mode='w') as fp:
json.dump(sigma_input.as_dict(), fp, indent=2)
self.assert_input_equality('g0w0_with_ppmodel_scf_input.json', scf_input)
self.assert_input_equality('g0w0_with_ppmodel_nscf_input.json', nscf_input)
self.assert_input_equality('g0w0_with_ppmodel_scr_input.json', scr_input)
self.assert_input_equality('g0w0_with_ppmodel_sigma_input.json', sigma_input)
flow = Flow.temporary_flow()
flow.register_work(G0W0Work(scf_input, nscf_input, scr_input, sigma_input))
assert flow.build_and_pickle_dump(abivalidate=True) == 0
# The default value of `shifts` changed in v0.3 from (0.5, 0.5, 0.5) to (0.0, 0.0, 0.0)
multi = g0w0_with_ppmodel_inputs(self.si_structure, self.si_pseudo,
scf_kppa, nscf_nband, ecuteps, ecutsigx,
ecut=2)
for inp in multi:
self.assert_equal(inp["shiftk"].flatten(), (0, 0, 0))
def test_g0w0_with_ppmodel_inputs(self):
"""Testing g0w0_with_ppmodel_input factory."""
scf_kppa, scf_nband, nscf_nband = 10, 10, 10
ecuteps, ecutsigx = 2, 2
multi = g0w0_with_ppmodel_inputs(self.si_structure,
self.si_pseudo,
scf_kppa,
nscf_nband,
ecuteps,
ecutsigx,
ecut=2)
scf_input, nscf_input, scr_input, sigma_input = multi.split_datasets()
flow = Flow.temporary_flow()
flow.register_work(
G0W0Work(scf_input, nscf_input, scr_input, sigma_input))
assert flow.build_and_pickle_dump(abivalidate=True) == 0
def abiopen(filepath):
"""
Factory function that opens any file supported by abipy.
File type is detected from the extension
Args:
filepath: string with the filename.
"""
if os.path.basename(filepath) == "__AbinitFlow__.pickle":
return Flow.pickle_load(filepath)
# Handle old output files produced by Abinit.
import re
outnum = re.compile(r".+\.out[\d]+")
abonum = re.compile(r".+\.abo[\d]+")
if outnum.match(filepath) or abonum.match(filepath):
return AbinitOutputFile.from_file(filepath)
cls = abifile_subclass_from_filename(filepath)
return cls.from_file(filepath)
def abiopen(filepath):
"""
Factory function that opens any file supported by abipy.
File type is detected from the extension
Args:
filepath: string with the filename.
"""
if os.path.basename(filepath) == "__AbinitFlow__.pickle":
return Flow.pickle_load(filepath)
# Handle old output files produced by Abinit.
import re
outnum = re.compile(r".+\.out[\d]+")
abonum = re.compile(r".+\.abo[\d]+")
if outnum.match(filepath) or abonum.match(filepath):
return AbinitOutputFile.from_file(filepath)
cls = abifile_subclass_from_filename(filepath)
return cls.from_file(filepath)
def abiopen(filepath):
"""
Factory function that opens any file supported by abipy.
File type is detected from the extension
Args:
filepath: string with the filename.
"""
# Handle ~ in filepath.
filepath = os.path.expanduser(filepath)
# Handle zipped files by creating temporary file with correct extension.
root, ext = os.path.splitext(filepath)
if ext in (".bz2", ".gz", ".z"):
from monty.io import zopen
with zopen(filepath, "rt") as f:
import tempfile
_, tmp_path = tempfile.mkstemp(suffix=os.path.basename(root),
text=True)
cprint("Creating temporary file: %s" % tmp_path, "yellow")
with open(tmp_path, "wt") as t:
t.write(f.read())
filepath = tmp_path
if os.path.basename(filepath) == "__AbinitFlow__.pickle":
return Flow.pickle_load(filepath)
# Handle old output files produced by Abinit.
import re
outnum = re.compile(r".+\.out[\d]+")
abonum = re.compile(r".+\.abo[\d]+")
if outnum.match(filepath) or abonum.match(filepath):
return AbinitOutputFile.from_file(filepath)
if os.path.basename(filepath) == "log":
# Assume Abinit log file.
return AbinitLogFile.from_file(filepath)
cls = abifile_subclass_from_filename(filepath)
return cls.from_file(filepath)