def test_inline_export(self):
from aiida.tools.dbexporters.tcod import export_values
import tempfile
with tempfile.NamedTemporaryFile(mode='w+') as tmpf:
tmpf.write('''
data_test
_cell_length_a 10
_cell_length_b 10
_cell_length_c 10
_cell_angle_alpha 90
_cell_angle_beta 90
_cell_angle_gamma 90
loop_
_atom_site_label
_atom_site_fract_x
_atom_site_fract_y
_atom_site_fract_z
C 0 0 0
O 0.5 0.5 0.5
''')
tmpf.flush()
a = orm.CifData(filepath=tmpf.name)
s = a.get_structure(store=True)
val = export_values(s)
script = val.first_block()['_tcod_file_contents'][1]
function = '_get_aiida_structure_pymatgen_inline'
self.assertNotEqual(script.find(function), script.rfind(function))
def populate_restapi_database(clear_database_before_test):
"""Populates the database with a considerable set of nodes to test the restAPI"""
# pylint: disable=unused-argument
from aiida import orm
struct_forcif = orm.StructureData().store()
orm.StructureData().store()
orm.StructureData().store()
orm.Dict().store()
orm.Dict().store()
orm.CifData(ase=struct_forcif.get_ase()).store()
orm.KpointsData().store()
orm.FolderData().store()
orm.CalcFunctionNode().store()
orm.CalcJobNode().store()
orm.CalcJobNode().store()
orm.WorkFunctionNode().store()
orm.WorkFunctionNode().store()
orm.WorkChainNode().store()
def generate_class_instance(data_class):
"""Generate a dummy `Data` instance for the given sub class."""
dirpath_fixtures = os.path.abspath(
os.path.join(os.path.dirname(__file__), os.pardir, os.pardir,
'fixtures'))
if data_class is orm.CifData:
instance = data_class(
file=os.path.join(dirpath_fixtures, 'data', 'Si.cif'))
return instance
if data_class is orm.UpfData:
filename = os.path.join(
dirpath_fixtures, 'pseudos',
'Ba.pbesol-spn-rrkjus_psl.0.2.3-tot-pslib030.UPF')
instance = data_class(file=filename)
return instance
if data_class is orm.StructureData:
instance = orm.CifData(file=os.path.join(
dirpath_fixtures, 'data', 'Si.cif')).get_structure()
return instance
if data_class is orm.BandsData:
kpoints = orm.KpointsData()
kpoints.set_cell([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
kpoints.set_kpoints([[0., 0., 0.], [0.1, 0.1, 0.1]])
instance = data_class()
instance.set_kpointsdata(kpoints)
instance.set_bands([[1.0, 2.0], [3.0, 4.0]])
return instance
if data_class is orm.TrajectoryData:
instance = data_class()
stepids = numpy.array([60])
times = stepids * 0.01
cells = numpy.array([[[3., 0., 0.], [0., 3., 0.], [0., 0., 3.]]])
positions = numpy.array([[[0., 0., 0.]]])
instance.set_trajectory(stepids=stepids,
cells=cells,
symbols=['H'],
positions=positions,
times=times)
return instance
if data_class is orm.UpfData:
filepath_base = os.path.abspath(
os.path.join(__file__, os.pardir, os.pardir, os.pardir,
'fixtures', 'pseudos'))
filepath_carbon = os.path.join(filepath_base,
'C_pbe_v1.2.uspp.F.UPF')
instance = data_class(file=filepath_carbon)
return instance
raise RuntimeError(
'no instance generator implemented for class `{}`. If you have added a `_prepare_*` method '
'for this data class, add a generator of a dummy instance here'.
format(data_class))
def test_cif_structure_roundtrip(self):
from aiida.tools.dbexporters.tcod import export_cif, export_values
from aiida.common.folders import SandboxFolder
import tempfile
with tempfile.NamedTemporaryFile(mode='w+') as tmpf:
tmpf.write('''
data_test
_cell_length_a 10
_cell_length_b 10
_cell_length_c 10
_cell_angle_alpha 90
_cell_angle_beta 90
_cell_angle_gamma 90
loop_
_atom_site_label
_atom_site_fract_x
_atom_site_fract_y
_atom_site_fract_z
C 0 0 0
O 0.5 0.5 0.5
''')
tmpf.flush()
a = orm.CifData(filepath=tmpf.name)
c = a.get_structure()
c.store()
pd = orm.Dict()
code = orm.Code(local_executable='test.sh')
with tempfile.NamedTemporaryFile(mode='w+') as tmpf:
tmpf.write("#/bin/bash\n\necho test run\n")
tmpf.flush()
code.put_object_from_filelike(tmpf, 'test.sh')
code.store()
calc = orm.CalcJobNode(computer=self.computer)
calc.set_option('resources', {
'num_machines': 1,
'num_mpiprocs_per_machine': 1
})
calc.add_incoming(code, LinkType.INPUT_CALC, "code")
calc.set_option('environment_variables', {
'PATH': '/dev/null',
'USER': '******'
})
with tempfile.NamedTemporaryFile(mode='w+', prefix="Fe") as tmpf:
tmpf.write("<UPF version=\"2.0.1\">\nelement=\"Fe\"\n")
tmpf.flush()
upf = orm.UpfData(filepath=tmpf.name)
upf.store()
calc.add_incoming(upf, LinkType.INPUT_CALC, "upf")
with tempfile.NamedTemporaryFile(mode='w+') as tmpf:
tmpf.write("data_test")
tmpf.flush()
cif = orm.CifData(filepath=tmpf.name)
cif.store()
calc.add_incoming(cif, LinkType.INPUT_CALC, "cif")
with SandboxFolder() as fhandle:
calc.put_object_from_tree(fhandle.abspath)
calc.store()
fd = orm.FolderData()
with fd.open('_scheduler-stdout.txt', 'w') as fhandle:
fhandle.write(u"standard output")
with fd.open('_scheduler-stderr.txt', 'w') as fhandle:
fhandle.write(u"standard error")
fd.store()
fd.add_incoming(calc, LinkType.CREATE, calc.link_label_retrieved)
pd.add_incoming(calc, LinkType.CREATE, "create1")
pd.store()
with self.assertRaises(ValueError):
export_cif(c, parameters=pd)
c.add_incoming(calc, LinkType.CREATE, "create2")
export_cif(c, parameters=pd)
values = export_values(c, parameters=pd)
values = values['0']
self.assertEquals(values['_tcod_computation_environment'],
['PATH=/dev/null\nUSER=unknown'])
self.assertEquals(values['_tcod_computation_command'],
['cd 1; ./_aiidasubmit.sh'])
def setUpClass(cls, *args, **kwargs): # pylint: disable=too-many-locals, too-many-statements
"""
Basides the standard setup we need to add few more objects in the
database to be able to explore different requests/filters/orderings etc.
"""
# call parent setUpClass method
super(RESTApiTestCase, cls).setUpClass()
# connect the app and the api
# Init the api by connecting it the the app (N.B. respect the following
# order, api.__init__)
kwargs = dict(PREFIX=cls._url_prefix,
PERPAGE_DEFAULT=cls._PERPAGE_DEFAULT,
LIMIT_DEFAULT=cls._LIMIT_DEFAULT)
cls.app = App(__name__)
cls.app.config['TESTING'] = True
AiidaApi(cls.app, **kwargs)
# create test inputs
cell = ((2., 0., 0.), (0., 2., 0.), (0., 0., 2.))
structure = orm.StructureData(cell=cell)
structure.append_atom(position=(0., 0., 0.), symbols=['Ba'])
structure.store()
structure.add_comment('This is test comment.')
structure.add_comment('Add another comment.')
cif = orm.CifData(ase=structure.get_ase())
cif.store()
parameter1 = orm.Dict(dict={'a': 1, 'b': 2})
parameter1.store()
parameter2 = orm.Dict(dict={'c': 3, 'd': 4})
parameter2.store()
kpoint = orm.KpointsData()
kpoint.set_kpoints_mesh([4, 4, 4])
kpoint.store()
resources = {'num_machines': 1, 'num_mpiprocs_per_machine': 1}
calcfunc = orm.CalcFunctionNode(computer=cls.computer)
calcfunc.store()
calc = orm.CalcJobNode(computer=cls.computer)
calc.set_option('resources', resources)
calc.set_attribute('attr1', 'OK')
calc.set_attribute('attr2', 'OK')
calc.set_extra('extra1', False)
calc.set_extra('extra2', 'extra_info')
calc.add_incoming(structure,
link_type=LinkType.INPUT_CALC,
link_label='link_structure')
calc.add_incoming(parameter1,
link_type=LinkType.INPUT_CALC,
link_label='link_parameter')
aiida_in = 'The input file\nof the CalcJob node'
# Add the calcjob_inputs folder with the aiida.in file to the CalcJobNode repository
with tempfile.NamedTemporaryFile(mode='w+') as handle:
handle.write(aiida_in)
handle.flush()
handle.seek(0)
calc.put_object_from_filelike(handle,
key='calcjob_inputs/aiida.in',
force=True)
calc.store()
# create log message for calcjob
import logging
from aiida.common.log import LOG_LEVEL_REPORT
from aiida.common.timezone import now
from aiida.orm import Log
log_record = {
'time': now(),
'loggername': 'loggername',
'levelname': logging.getLevelName(LOG_LEVEL_REPORT),
'dbnode_id': calc.id,
'message': 'This is a template record message',
'metadata': {
'content': 'test'
},
}
Log(**log_record)
aiida_out = 'The output file\nof the CalcJob node'
retrieved_outputs = orm.FolderData()
# Add the calcjob_outputs folder with the aiida.out file to the FolderData node
with tempfile.NamedTemporaryFile(mode='w+') as handle:
handle.write(aiida_out)
handle.flush()
handle.seek(0)
retrieved_outputs.put_object_from_filelike(
handle, key='calcjob_outputs/aiida.out', force=True)
retrieved_outputs.store()
retrieved_outputs.add_incoming(calc,
link_type=LinkType.CREATE,
link_label='retrieved')
kpoint.add_incoming(calc,
link_type=LinkType.CREATE,
link_label='create')
calc1 = orm.CalcJobNode(computer=cls.computer)
calc1.set_option('resources', resources)
calc1.store()
dummy_computers = [{
'name': 'test1',
'hostname': 'test1.epfl.ch',
'transport_type': 'ssh',
'scheduler_type': 'pbspro',
}, {
'name': 'test2',
'hostname': 'test2.epfl.ch',
'transport_type': 'ssh',
'scheduler_type': 'torque',
}, {
'name': 'test3',
'hostname': 'test3.epfl.ch',
'transport_type': 'local',
'scheduler_type': 'slurm',
}, {
'name': 'test4',
'hostname': 'test4.epfl.ch',
'transport_type': 'ssh',
'scheduler_type': 'slurm',
}]
for dummy_computer in dummy_computers:
computer = orm.Computer(**dummy_computer)
computer.store()
# Prepare typical REST responses
cls.process_dummy_data()