def test_dict2builder(aiida_profile, sto_calc_inputs):
"""Test that we can use nested dict input for builder"""
from aiida_castep.calculations.castep import CastepCalculation
from aiida.engine import run_get_node
builder = CastepCalculation.get_builder()
builder._update(sto_calc_inputs)
run_get_node(builder)
def test_output_validation_error(self):
"""Test that a process is marked as failed if its output namespace validation fails."""
class TestProcess1(Process):
"""Defining a new TestProcess class for testing."""
_node_class = orm.WorkflowNode
@classmethod
def define(cls, spec):
super().define(spec)
spec.input('add_outputs', valid_type=orm.Bool, default=lambda: orm.Bool(False))
spec.output_namespace('integer.namespace', valid_type=orm.Int, dynamic=True)
spec.output('required_string', valid_type=orm.Str, required=True)
def run(self):
if self.inputs.add_outputs:
self.out('required_string', orm.Str('testing').store())
self.out('integer.namespace.two', orm.Int(2).store())
_, node = run_get_node(TestProcess1)
# For default inputs, no outputs will be attached, causing the validation to fail at the end so an internal
# exit status will be set, which is a negative integer
self.assertTrue(node.is_finished)
self.assertFalse(node.is_finished_ok)
self.assertEqual(node.exit_status, TestProcess1.exit_codes.ERROR_MISSING_OUTPUT.status)
self.assertEqual(node.exit_message, TestProcess1.exit_codes.ERROR_MISSING_OUTPUT.message)
# When settings `add_outputs` to True, the outputs should be added and validation should pass
_, node = run_get_node(TestProcess1, add_outputs=orm.Bool(True))
self.assertTrue(node.is_finished)
self.assertTrue(node.is_finished_ok)
self.assertEqual(node.exit_status, 0)
def test_submission(clear_database_before_test, sto_calc_inputs,
sto_spectral_inputs):
"""
Test submitting a CastepCalculation
"""
from aiida_castep.calculations.castep import CastepCalculation
from aiida.engine import run_get_node
_, return_node = run_get_node(CastepCalculation, **sto_calc_inputs)
assert return_node.exit_status == 106 # No castep output found
# test with extra kpoints
_, return_node = run_get_node(CastepCalculation, **sto_spectral_inputs)
assert return_node.exit_status == 106
def test_vasp_hf_wannier_input(
configure_with_daemon, # pylint: disable=unused-argument
assert_finished,
get_insb_input # pylint: disable=redefined-outer-name
):
"""
Runs the workflow that calculates Wannier90 inputs from VASP + hybrids on InSb with a coarse grid.
"""
from aiida import orm
from aiida.engine import run_get_node
from aiida_tbextraction.fp_run.wannier_input import VaspWannierInput
kpoints_mesh = orm.KpointsData()
kpoints_mesh.set_kpoints_mesh([2, 2, 2])
wannier_projections = orm.List()
wannier_projections.extend(['In : s; px; py; pz', 'Sb : px; py; pz'])
result, node = run_get_node(
VaspWannierInput,
kpoints_mesh=kpoints_mesh,
wannier_parameters=orm.Dict(
dict=dict(num_wann=14, num_bands=36, spinors=True)),
wannier_projections=wannier_projections,
**get_insb_input)
assert node.is_finished_ok
assert all(key in result for key in
['wannier_input_folder', 'wannier_parameters', 'wannier_bands'])
folder_list = result['wannier_input_folder'].get_folder_list()
assert all(
filename in folder_list
for filename in ['wannier90.amn', 'wannier90.mmn', 'wannier90.eig'])
def example_failure(cp2k_code):
"""Run failing calculation."""
print("Testing CP2K failure...")
# a broken CP2K input
parameters = Dict(dict={'GLOBAL': {'FOO_BAR_QUUX': 42}})
print("Submitted calculation...")
# Construct process builder
builder = cp2k_code.get_builder()
builder.parameters = parameters
builder.code = cp2k_code
builder.metadata.options.resources = {
"num_machines": 1,
"num_mpiprocs_per_machine": 1,
}
builder.metadata.options.max_wallclock_seconds = 1 * 2 * 60
_, calc_node = run_get_node(builder)
if calc_node.exit_status == 304:
print("CP2K failure correctly recognized.")
else:
print("ERROR!")
print("CP2K failure was not recognized.")
sys.exit(3)
def test_run_single_reaxff(db_test_app, get_structure,
pyrite_potential_reaxff_lowtol, data_regression):
# type: (AiidaTestApp) -> None
code = db_test_app.get_or_create_code("gulp.single")
builder = code.get_builder()
builder._update({
"metadata": {
"options": {
"withmpi": False,
"resources": {
"num_machines": 1,
"num_mpiprocs_per_machine": 1
},
"max_wallclock_seconds": 30,
}
}
})
builder.structure = get_structure("pyrite")
builder.potential = pyrite_potential_reaxff_lowtol
calc_node = run_get_node(builder).node
db_test_app.check_calculation(calc_node, ["results"])
result = recursive_round(calc_node.outputs.results.get_dict(), 6)
for key in [
"parser_version",
"peak_dynamic_memory_mb",
"opt_time_second",
"total_time_second",
]:
result.pop(key, None)
data_regression.check(result)
def test_optimize_process(
db_test_app,
get_potential_data,
potential_type,
data_regression,
):
"""Test the functionality of the optimization calculation type"""
calc_plugin = 'lammps.optimize'
code = db_test_app.get_or_create_code(calc_plugin)
pot_data = get_potential_data(potential_type)
potential = DataFactory('lammps.potential')(
potential_type=pot_data.type,
data=pot_data.data,
)
parameters = get_calc_parameters(
get_lammps_version(code),
calc_plugin,
potential.default_units,
potential_type,
)
builder = code.get_builder()
builder._update({ # pylint: disable=protected-access
'metadata': tests.get_default_metadata(),
'code': code,
'structure': pot_data.structure,
'potential': potential,
'parameters': parameters,
})
output = run_get_node(builder)
calc_node = output.node
if not calc_node.is_finished_ok:
print(calc_node.attributes)
print(get_calcjob_report(calc_node))
raise Exception(
f'finished with exit message: {calc_node.exit_message}')
link_labels = calc_node.get_outgoing().all_link_labels()
assert set(link_labels).issuperset(
['results', 'trajectory_data', 'structure'])
trajectory_data = calc_node.outputs.trajectory_data.attributes
# optimization steps may differ between lammps versions
trajectory_data = {
k: v
for k, v in trajectory_data.items() if k != 'number_steps'
}
data_regression.check({
'results':
sanitize_results(calc_node.outputs.results.get_dict(), 1),
'trajectory_data':
trajectory_data,
'structure': {
'kind_names': calc_node.outputs.structure.get_kind_names()
}
# "structure": tests.recursive_round(
# calc_node.outputs.structure.attributes, 1, apply_lists=True
# ),
})
def test_submit_HKUST1(clear_database, network_code, basic_options): # pylint: disable=unused-argument,invalid-name,invalid-name
"""Test submitting a calculation"""
from aiida_zeopp.tests import TEST_DIR
from aiida_zeopp.calculations.network import NetworkCalculation
from aiida.engine import run_get_node
# Prepare input parameters
from aiida.plugins import DataFactory
parameters = DataFactory('zeopp.parameters')(dict={'cssr': True})
structure = DataFactory('cif')(file=os.path.join(TEST_DIR, 'HKUST-1.cif'),
parse_policy='lazy')
inputs = {
'code': network_code,
'parameters': parameters,
'structure': structure,
'metadata': {
'options': basic_options,
'label': 'aiida_zeopp format conversion',
'description': 'Test converting .cif to .cssr format',
},
}
_result, node = run_get_node(NetworkCalculation, **inputs)
cssr = io.open(os.path.join(TEST_DIR, 'HKUST-1.cssr'),
'r',
encoding='utf8').read()
assert cssr == node.outputs.structure_cssr.get_content()
def test_filename(network_code, basic_options): # pylint: disable=unused-argument,invalid-name
"""Test submitting a calculation from autogenerated CifData.
Note: filenames of CifData generated from ASE may miss the .cif extension.
"""
from ase.build import bulk
# Prepare input parameters
parameters = NetworkParameters(dict={
'cssr': True,
})
atoms = bulk('Mg', 'fcc', a=3.6)
cif = CifData(ase=atoms)
atomic_radii = SinglefileData(file=os.path.join(TEST_DIR, 'MgO.rad'))
# set up calculation
inputs = {
'code': network_code,
'parameters': parameters,
'structure': cif,
'atomic_radii': atomic_radii,
'metadata': {
'options': basic_options,
},
}
input_filename = cif.filename if cif.filename.endswith(
'.cif') else cif.filename + '.cif'
result, node = run_get_node(NetworkCalculation, **inputs)
assert 'structure_cssr' in result
assert node.res.Input_structure_filename == input_filename
def test_run_prop_mgo_no_scf(db_test_app, sanitise_calc_attr, data_regression):
"""Test the workchains when a folder is supplied that contains the wavefunction file."""
clear_spec()
wc_builder = CryPropertiesWorkChain.get_builder()
with open_resource_binary("doss", "mgo_sto3g_scf", "fort.9") as handle:
wc_builder.wf_folder = SinglefileData(handle)
wc_builder.doss.code = db_test_app.get_or_create_code("crystal17.doss")
wc_builder.doss.parameters = get_parameters()["doss"]
wc_builder.doss.metadata = db_test_app.get_default_metadata()
wc_builder.ech3.code = db_test_app.get_or_create_code("crystal17.ech3")
wc_builder.ech3.parameters = get_parameters()["ech3"]
wc_builder.ech3.metadata = db_test_app.get_default_metadata()
outputs, wc_node = run_get_node(wc_builder)
sys.stderr.write(get_workchain_report(wc_node, "REPORT"))
wk_attributes = sanitise_calc_attr(wc_node.attributes)
data_regression.check({
"calc_node":
wk_attributes,
"incoming":
sorted(wc_node.get_incoming().all_link_labels()),
"outgoing":
sorted(wc_node.get_outgoing().all_link_labels()),
# "results": outputs["results"].attributes
})
def test_run_mgo_scf_folder(db_test_app, sanitise_calc_attr, data_regression):
# type: (AiidaTestApp) -> None
"""Test running a calculation."""
# set up calculation
builder = db_test_app.get_or_create_code("crystal17.newk").get_builder()
builder.metadata = get_metadata()
builder.parameters = Dict(dict={"k_points": [18, 36]})
wf_folder = FolderData()
with open_resource_binary("newk", "mgo_sto3g_scf", "fort.9") as handle:
wf_folder.put_object_from_filelike(handle, "fort.9", mode="wb")
builder.wf_folder = wf_folder
output = run_get_node(builder)
calc_node = output.node
db_test_app.check_calculation(calc_node, ["results"])
calc_attributes = sanitise_calc_attr(calc_node.attributes)
results = {
k: round(i, 7) if isinstance(i, float) else i
for k, i in calc_node.outputs.results.attributes.items()
if k not in ["execution_time_seconds"]
}
data_regression.check({
"calc": calc_attributes,
"results": results,
})
def test_output_dictionary(self):
"""Verify that a dictionary can be passed as an output for a namespace."""
class TestProcess1(Process):
"""Defining a new TestProcess class for testing."""
_node_class = orm.WorkflowNode
@classmethod
def define(cls, spec):
super().define(spec)
spec.input_namespace('namespace',
valid_type=orm.Int,
dynamic=True)
spec.output_namespace('namespace',
valid_type=orm.Int,
dynamic=True)
def run(self):
self.out('namespace', self.inputs.namespace)
results, node = run_get_node(TestProcess1,
namespace={
'alpha': orm.Int(1),
'beta': orm.Int(2)
})
self.assertTrue(node.is_finished_ok)
self.assertEqual(results['namespace']['alpha'], orm.Int(1))
self.assertEqual(results['namespace']['beta'], orm.Int(2))
def test_without_kinds(cp2k_code, cp2k_basissets, cp2k_pseudos,
clear_database): # pylint: disable=unused-argument
"""Testing CP2K with the Basis Set stored in gaussian.basisset but without a KIND section"""
# structure
atoms = ase.build.molecule("H2O")
atoms.center(vacuum=2.0)
structure = StructureData(ase=atoms)
# parameters
parameters = Dict(
dict={
"FORCE_EVAL": {
"METHOD": "Quickstep",
"DFT": {
"QS": {
"EPS_DEFAULT": 1.0e-12,
"WF_INTERPOLATION": "ps",
"EXTRAPOLATION_ORDER": 3,
},
"MGRID": {
"NGRIDS": 4,
"CUTOFF": 280,
"REL_CUTOFF": 30
},
"XC": {
"XC_FUNCTIONAL": {
"_": "LDA"
}
},
"POISSON": {
"PERIODIC": "none",
"PSOLVER": "MT"
},
},
}
})
options = {
"resources": {
"num_machines": 1,
"num_mpiprocs_per_machine": 1
},
"max_wallclock_seconds": 1 * 3 * 60,
}
inputs = {
"structure": structure,
"parameters": parameters,
"code": cp2k_code,
"metadata": {
"options": options
},
"basissets": cp2k_basissets,
"pseudos": cp2k_pseudos,
}
_, calc_node = run_get_node(CalculationFactory("cp2k"), **inputs)
assert calc_node.exit_status == 0
def test_FleurJobCalc_full_mock(aiida_profile, mock_code_factory,
create_fleurinp, clear_database,
hash_code_by_entrypoint): # pylint: disable=redefined-outer-name
"""
Tests the fleur inputgenerate with a mock executable if the datafiles are their,
otherwise runs inpgen itself if a executable was specified
"""
mock_code = mock_code_factory(
label='fleur',
data_dir_abspath=os.path.join(
os.path.dirname(os.path.abspath(__file__)), 'data_dir/'),
entry_point=CALC_ENTRY_POINT,
ignore_files=[
'_aiidasubmit.sh',
'cdnc',
'out',
'FleurInputSchema.xsd',
'cdn.hdf',
'usage.json', # 'cdn??']
'cdn00',
'cdn01',
'cdn02',
'cdn03',
'cdn04',
'cdn05',
'cdn06',
'cdn07',
'cdn08',
'cdn09',
'cdn10',
'cdn11'
])
#mock_code.append_text = 'rm cdn?? broyd* wkf2 inf cdnc stars pot* FleurInputSchema* cdn.hdf'
inputs = {
'fleurinpdata': create_fleurinp(TEST_INP_XML_PATH),
#'parameters': orm.Dict(dict=parameters),
'metadata': {
'options': {
'resources': {
'num_machines': 1,
'tot_num_mpiprocs': 1
},
'max_wallclock_seconds': int(600),
'withmpi': True
}
}
}
#calc = CalculationFactory(CALC_ENTRY_POINT, code=mock_code, **inputs)
res, node = run_get_node(CalculationFactory(CALC_ENTRY_POINT),
code=mock_code,
**inputs)
print((res['remote_folder'].list_objects()))
print((res['retrieved'].list_objects()))
assert node.is_finished_ok
def test_exit_codes_invalidate_cache(self):
"""
Test that returning an exit code with 'invalidates_cache' set to ``True``
indeed means that the ProcessNode will not be cached from.
"""
# Sanity check that caching works when the exit code is not returned.
with enable_caching():
_, node1 = run_get_node(test_processes.InvalidateCaching, return_exit_code=orm.Bool(False))
_, node2 = run_get_node(test_processes.InvalidateCaching, return_exit_code=orm.Bool(False))
self.assertEqual(node1.get_extra('_aiida_hash'), node2.get_extra('_aiida_hash'))
self.assertIn('_aiida_cached_from', node2.extras)
with enable_caching():
_, node3 = run_get_node(test_processes.InvalidateCaching, return_exit_code=orm.Bool(True))
_, node4 = run_get_node(test_processes.InvalidateCaching, return_exit_code=orm.Bool(True))
self.assertEqual(node3.get_extra('_aiida_hash'), node4.get_extra('_aiida_hash'))
self.assertNotIn('_aiida_cached_from', node4.extras)
def test_valid_cache_hook(self):
"""
Test that the is_valid_cache behavior can be specified from
the method in the Process sub-class.
"""
# Sanity check that caching works when the hook returns True.
with enable_caching():
_, node1 = run_get_node(test_processes.IsValidCacheHook)
_, node2 = run_get_node(test_processes.IsValidCacheHook)
self.assertEqual(node1.get_extra('_aiida_hash'), node2.get_extra('_aiida_hash'))
self.assertIn('_aiida_cached_from', node2.extras)
with enable_caching():
_, node3 = run_get_node(test_processes.IsValidCacheHook, not_valid_cache=orm.Bool(True))
_, node4 = run_get_node(test_processes.IsValidCacheHook, not_valid_cache=orm.Bool(True))
self.assertEqual(node3.get_extra('_aiida_hash'), node4.get_extra('_aiida_hash'))
self.assertNotIn('_aiida_cached_from', node4.extras)
def test_md_process(
db_test_app,
get_potential_data,
potential_type,
data_regression,
):
"""Test the functionality of the md calculation type"""
calc_plugin = 'lammps.md'
code = db_test_app.get_or_create_code(calc_plugin)
pot_data = get_potential_data(potential_type)
potential = DataFactory('lammps.potential')(
potential_type=pot_data.type,
data=pot_data.data,
)
version = get_lammps_version(code)
version_year = version[-4:]
parameters = get_calc_parameters(
version,
calc_plugin,
potential.default_units,
potential_type,
)
builder = code.get_builder()
builder._update({ # pylint: disable=protected-access
'metadata': tests.get_default_metadata(),
'code': code,
'structure': pot_data.structure,
'potential': potential,
'parameters': parameters,
})
output = run_get_node(builder)
calc_node = output.node
if not calc_node.is_finished_ok:
print(calc_node.attributes)
print(get_calcjob_report(calc_node))
raise Exception(
f'finished with exit message: {calc_node.exit_message}')
link_labels = calc_node.get_outgoing().all_link_labels()
assert set(link_labels).issuperset(
['results', 'trajectory_data', 'system_data'])
data_regression.check(
{
'results':
sanitize_results(
calc_node.outputs.results.get_dict(),
round_energy=1,
),
'system_data':
calc_node.outputs.system_data.attributes,
'trajectory_data':
calc_node.outputs.trajectory_data.attributes,
},
basename=f'test_md_process-{potential_type}-{version_year}',
)
def test_bad_settings(db_test_app):
"""test bad settings dict """
with pytest.raises(ValidationError):
results, node = run_get_node(
WorkflowFactory("crystal17.sym3d"),
settings=DataFactory("dict")(dict={
"a": 1
}),
)
def test_run_window_invalid(configure_with_daemon, run_window_builder,
window_values): # pylint:disable=unused-argument,redefined-outer-name
"""
Runs an the run_window workflow with invalid window values.
"""
result, node = run_get_node(
run_window_builder(window_values, slice_=True, symmetries=True))
assert node.is_finished_ok
assert result['cost_value'] > 1e10
def test_no_structure(db_test_app):
"""test no StructureData or CifData """
wflow_cls = WorkflowFactory("crystal17.sym3d")
results, node = run_get_node(wflow_cls,
settings=DataFactory("dict")(dict={
"symprec": 0.01
}))
assert node.is_failed, node.exit_status
assert node.exit_status == wflow_cls.exit_codes.ERROR_INVALID_INPUT_RESOURCES.status
def run_calculation(code, counter, inputval):
"""
Run a calculation through the Process layer.
"""
process, inputs, expected_result = create_calculation_process(
code=code, inputval=inputval)
result, calc = run_get_node(process, **inputs)
print('[{}] ran calculation {}, pk={}'.format(counter, calc.uuid, calc.pk))
return calc, expected_result
def test_run_optimize_lj_with_symm(db_test_app, get_structure,
pyrite_potential_lj, data_regression):
# type: (AiidaTestApp) -> None
from aiida.engine import run_get_node
structure = get_structure("pyrite")
symmetry = DataFactory("gulp.symmetry")(
data=compute_symmetry_dict(structure, 0.01, None))
parameters = db_test_app.get_data_node(
"dict",
dict={
"minimize": {
"style": "cg",
"max_iterations": 100
},
"relax": {
"type": "conp"
},
},
)
code = db_test_app.get_or_create_code("gulp.optimize")
builder = code.get_builder()
builder._update({
"metadata": {
"options": {
"withmpi": False,
"resources": {
"num_machines": 1,
"num_mpiprocs_per_machine": 1
},
"max_wallclock_seconds": 30,
}
}
})
builder.structure = structure
builder.potential = pyrite_potential_lj
builder.parameters = parameters
builder.symmetry = symmetry
calc_node = run_get_node(builder).node
db_test_app.check_calculation(calc_node,
["results", "structure", "retrieved"])
result = recursive_round(calc_node.outputs.results.get_dict(), 6)
for key in [
"parser_version",
"peak_dynamic_memory_mb",
"opt_time_second",
"total_time_second",
]:
result.pop(key, None)
data_regression.check(result)
def main(network_code_string):
"""Example usage:
$ verdi run submit.py network@localhost
Alternative use (creates network@localhost-test code):
$ verdi run submit.py createcode
"""
if network_code_string == 'createcode':
from aiida_zeopp import tests
code = tests.get_code(entry_point='zeopp.network')
else:
from aiida.orm import Code
code = Code.get_from_string(network_code_string)
# Prepare input parameters
NetworkParameters = DataFactory('zeopp.parameters')
# For allowed keys, print(NetworkParameters.schema)
parameters = NetworkParameters(
dict={
'ha': 'LOW', #just for speed; use 'DEF' for prodution!
'cssr': True, #converting to cssr
'sa': [1.86, 1.86, 1000], #computing surface area
'vol': [0.0, 0.0, 1000], #computing gemetric pore volume
})
CifData = DataFactory('cif')
this_dir = os.path.dirname(os.path.realpath(__file__))
structure = CifData(file=os.path.join(this_dir, 'HKUST-1.cif'))
# set up calculation
inputs = {
'code': code,
'parameters': parameters,
'structure': structure,
'metadata': {
'options': {
'max_wallclock_seconds': 1 * 60,
},
'label':
'aiida_zeopp example calculation',
'description':
'Converts .cif to .cssr format, computes surface area, and pore volume',
},
}
# or use aiida.engine.submit
print('Running NetworkCalculation: wait...')
result, node = run_get_node(NetworkCalculation, **inputs) # pylint: disable=unused-variable
print('Nitrogen accessible surface area (m^2/g): {:.3f}'.format(
node.outputs.output_parameters.get_attribute('ASA_m^2/g')))
print('Geometric pore volume (cm^3/g): {:.3f}'.format(
node.outputs.output_parameters.get_attribute('AV_cm^3/g')))
print('CSSR structure: SinglefileData<{}>'.format(
node.outputs.structure_cssr.pk))
def test_calcjob_submit_mgo(db_test_app, input_symmetry, get_structure,
data_regression, file_regression):
"""Test submitting a calculation."""
code = db_test_app.get_or_create_code("crystal17.main")
# Prepare input parameters
inparams = CryInputParamsData(data={
"title": "MgO Bulk",
"scf": {
"k_points": (8, 8)
}
})
instruct = get_structure("MgO")
sym_calc = run_get_node(
WorkflowFactory("crystal17.sym3d"),
structure=instruct,
settings=orm.Dict(dict={
"symprec": 0.01,
"compute_primitive": True
}),
).node
instruct = sym_calc.get_outgoing().get_node_by_label("structure")
symmetry = sym_calc.get_outgoing().get_node_by_label("symmetry")
with open_resource_text("basis_sets", "sto3g", "sto3g_Mg.basis") as handle:
mg_basis, _ = BasisSetData.get_or_create(handle)
with open_resource_text("basis_sets", "sto3g", "sto3g_O.basis") as handle:
o_basis, _ = BasisSetData.get_or_create(handle)
# set up calculation
builder = code.get_builder()
builder.metadata = db_test_app.get_default_metadata(dry_run=True)
builder.parameters = inparams
builder.structure = instruct
builder.basissets = {"Mg": mg_basis, "O": o_basis}
if input_symmetry:
builder.symmetry = symmetry
process_options = builder.process_class(inputs=builder).metadata.options
with db_test_app.sandbox_folder() as folder:
calc_info = db_test_app.generate_calcinfo("crystal17.main", folder,
builder)
with folder.open(process_options.input_file_name) as f:
input_content = f.read()
with folder.open("fort.34") as f:
gui_content = f.read() # noqa: F841
# TODO test fort.34 (but rounded)
file_regression.check(input_content)
data_regression.check(sanitize_calc_info(calc_info))
def test_run_window(configure_with_daemon, run_window_builder, slice_,
symmetries): # pylint:disable=unused-argument,redefined-outer-name
"""
Runs the workflow which evaluates an energy window.
"""
result, node = run_get_node(
run_window_builder([-4.5, -4, 6.5, 16],
slice_=slice_,
symmetries=symmetries))
assert node.is_finished_ok
assert all(key in result for key in ['cost_value', 'tb_model', 'plot'])
def test_run_reaxff_fes(db_test_app, get_structure, data_regression):
"""Test submitting a calculation."""
code = db_test_app.get_or_create_code("gulp.fitting")
builder = code.get_builder()
builder.metadata = db_test_app.get_default_metadata()
potential_cls = DataFactory("gulp.potential")
pot_data = read_lammps_format(
read_resource_text("gulp", "potentials",
"FeCrOSCH.reaxff").splitlines())
pot_data = filter_by_species(pot_data, ["Fe core", "S core"])
builder.settings = {"observables": {"energy": {}}}
builder.potential = potential_cls(
"reaxff",
pot_data,
fitting_data={
"species": ["Fe core", "S core"],
"global": ["reaxff0_boc1", "reaxff0_boc2"],
},
)
builder.structures = {
"pyrite": get_structure("pyrite"),
"marcasite": get_structure("marcasite"),
"zincblende": get_structure("zincblende"),
}
builder.observables = {
"pyrite": Dict(dict={
"energy": -1,
"energy_units": "eV"
}),
"marcasite": Dict(dict={
"energy": -1,
"energy_units": "eV"
}),
"zincblende": Dict(dict={
"energy": 1,
"energy_units": "eV"
}),
}
builder.metadata["options"]["allow_create_potential_fail"] = True
calc_node = run_get_node(builder).node
db_test_app.check_calculation(calc_node, ["results"])
result = recursive_round(calc_node.outputs.results.get_dict(), 6)
for key in [
"parser_version",
"peak_dynamic_memory_mb",
"opt_time_second",
"total_time_second",
]:
result.pop(key, None)
data_regression.check(result)
def test_md_multi_process(
db_test_app, get_potential_data, potential_type, data_regression
):
calc_plugin = "lammps.md.multi"
code = db_test_app.get_or_create_code(calc_plugin)
pot_data = get_potential_data(potential_type)
potential = DataFactory("lammps.potential")(type=pot_data.type, data=pot_data.data)
parameters = get_calc_parameters(
get_lammps_version(code), calc_plugin, potential.default_units, potential_type
)
builder = code.get_builder()
builder._update(
{
"metadata": tests.get_default_metadata(),
"code": code,
"structure": pot_data.structure,
"potential": potential,
"parameters": parameters,
}
)
output = run_get_node(builder)
calc_node = output.node
if not calc_node.is_finished_ok:
print(calc_node.attributes)
print(get_calcjob_report(calc_node))
raise Exception("finished with exit message: {}".format(calc_node.exit_message))
link_labels = calc_node.get_outgoing().all_link_labels()
assert set(link_labels).issuperset(
[
"results",
"retrieved",
"trajectory__thermalise",
"trajectory__equilibrate",
"system__thermalise",
"system__equilibrate",
]
)
data_regression.check(
{
"retrieved": calc_node.outputs.retrieved.list_object_names(),
"results": sanitize_results(
calc_node.outputs.results.get_dict(), round_energy=1
),
"system__thermalise": calc_node.outputs.system__thermalise.attributes,
"system__equilibrate": calc_node.outputs.system__equilibrate.attributes,
"trajectory__thermalise": calc_node.outputs.trajectory__thermalise.attributes,
"trajectory__equilibrate": calc_node.outputs.trajectory__equilibrate.attributes,
}
)
def example_dft(gaussian_code):
"""Run a simple gaussian optimization"""
# structure
structure = StructureData(
pymatgen_molecule=mg.Molecule.from_file('./ch4.xyz'))
num_cores = 1
memory_mb = 300
# Main parameters: geometry optimization
parameters = Dict(
dict={
'link0_parameters': {
'%chk': 'aiida.chk',
'%mem': "%dMB" % memory_mb,
'%nprocshared': num_cores,
},
'functional': 'BLYP',
'basis_set': '6-31g',
'charge': 0,
'multiplicity': 1,
'route_parameters': {
'scf': {
'cdiis': None,
},
'nosymm': None,
'opt': None,
},
})
# Construct process builder
builder = GaussianCalculation.get_builder()
builder.structure = structure
builder.parameters = parameters
builder.code = gaussian_code
builder.metadata.options.resources = {
"num_machines": 1,
"tot_num_mpiprocs": num_cores,
}
# Should ask for extra +25% extra memory
builder.metadata.options.max_memory_kb = int(1.25 * memory_mb) * 1024
builder.metadata.options.max_wallclock_seconds = 5 * 60
print("Running calculation...")
res, _node = run_get_node(builder)
print("Final scf energy: %.4f" %
res['output_parameters']['scfenergies'][-1])
def test_launchers(self):
"""Verify that the various launchers are working."""
result = run(self.function_return_true)
self.assertTrue(result)
result, node = run_get_node(self.function_return_true)
self.assertTrue(result)
self.assertEqual(result, get_true_node())
self.assertTrue(isinstance(node, orm.CalcFunctionNode))
with self.assertRaises(AssertionError):
submit(self.function_return_true)
def test_fleur_scf_fleurinp_Si(
#run_with_cache,
with_export_cache,
fleur_local_code,
create_fleurinp,
clear_database,
clear_spec):
"""
full example using scf workflow with just a fleurinp data as input.
Several fleur runs needed till convergence
"""
options = {
'resources': {
'num_machines': 1,
'num_mpiprocs_per_machine': 1
},
'max_wallclock_seconds': 5 * 60,
'withmpi': False,
'custom_scheduler_commands': ''
}
FleurCode = fleur_local_code
# create process builder to set parameters
builder = FleurScfWorkChain.get_builder()
builder.metadata.description = 'Simple Fleur SCF test for Si bulk with fleurinp data given'
builder.metadata.label = 'FleurSCF_test_Si_bulk'
builder.fleurinp = create_fleurinp(TEST_INP_XML_PATH).store()
builder.options = Dict(dict=options).store()
builder.fleur = FleurCode
#print(builder)
# now run calculation
#run_with_cache(builder)
data_dir_path = os.path.join(
aiida_path, '../tests/workflows/caches/fleur_scf_fleurinp_Si.tar.gz')
with with_export_cache(data_dir_abspath=data_dir_path):
out, node = run_get_node(builder)
#print(out)
#print(node)
print(get_workchain_report(node, 'REPORT'))
#assert node.is_finished_ok
# check output
n = out['output_scf_wc_para']
n = n.get_dict()
print(get_calcjob_report(load_node(n['last_calc_uuid'])))
#print(n)
assert abs(n.get('distance_charge') - 9.8993e-06) < 2.0e-6
assert n.get('errors') == []
