def insert_pdf_data_document(name, input_filename=None,
atomic_config=None, exp_dict=None, time=None):
if time is None:
time = ttime.time()
# at some level, you dont actually care where this thing is on disk
file_uid = str(uuid4())
# create the filename
file_name = os.path.join(simdb.PDF_PATH, file_uid + '.gr')
generated = False
if atomic_config is not None:
# Then we should generate the PDF
s = Scatter(exp_dict)
# Just in case we use the exp_dict = None default params
params = s.exp
# get the atomic configuration from the DB
atomic_doc, = find_atomic_config_document(_id=atomic_config.id)
atoms = atomic_doc.file_payload[-1]
# Generate the PDF from the atomic configuration
gobs = s.get_pdf(atoms)
generated = True
# Save the gobs
# TODO: replace with context
f = open(file_name, 'w')
np.save(f, gobs)
f.close()
res = fsc.insert_resource('genpdf', file_name)
fsc.insert_datum(res, file_uid)
else:
# Then the pdf is experimental, thus we should let filestore know it
# exists, and load the PDF generating parameters into the Metadata
res = fsc.insert_resource('pdfgetx3', input_filename)
fsc.insert_datum(res, file_uid)
params = load_gr_file(input_filename)[-1]
# create an instance of a mongo document (metadata)
if generated is True:
a = PDFData(name=name, file_uid=file_uid, ase_config_id=atomic_config,
pdf_params=params, time=time)
else:
a = PDFData(name=name, file_uid=file_uid,
# will support when we merge this with metadata store
# experiment_uid=exp_uid,
pdf_params=params, time=time)
# save the document
a.save()
return a
def insert_atom_document(name, ase_object, time=None):
if time is None:
time = ttime.time()
# at some level, you dont actually care where this thing is on disk
file_uid = str(uuid4())
is_trajectory = False
if isinstance(ase_object, list):
is_trajectory = True
# create the filename
file_name = os.path.join(simdb.ATOM_PATH, file_uid + '.traj')
# save the object
aseio.write(file_name, ase_object)
# do the filestore magic
resource = fsc.insert_resource('ase', file_name)
fsc.insert_datum(resource, file_uid,
datum_kwargs={'is_trajectory': is_trajectory})
# create an instance of a mongo document (metadata)
a = AtomicConfig(name=name, file_uid=file_uid, time=time)
# save the document
a.save()
return a
def test_overwrite_global():
mock_base = dict(spec='syn-mod',
resource_path='',
resource_kwargs={'shape': (5, 7)})
res = fsc.insert_resource(**mock_base)
cache_key = (str(res.id), SynHandlerMod.__name__)
with fsr.handler_context({'syn-mod': SynHandlerMod}):
fsr.get_spec_handler(res.id)
assert_in(cache_key, fsr._HANDLER_CACHE)
fsr.register_handler('syn-mod', SynHandlerEcho, overwrite=True)
assert_not_in(cache_key, fsr._HANDLER_CACHE)
def test_get_handler_global():
mock_base = dict(spec='syn-mod',
resource_path='',
resource_kwargs={'shape': (5, 7)})
res = fsc.insert_resource(**mock_base)
cache_key = (str(res.id), SynHandlerMod.__name__)
with fsr.handler_context({'syn-mod': SynHandlerMod}):
handle = fsr.get_spec_handler(res.id)
assert_true(isinstance(handle, SynHandlerMod))
assert_in(cache_key, fsr._HANDLER_CACHE)
assert_not_in(cache_key, fsr._HANDLER_CACHE)
def add_data(self, data, uid=None, resource_kwargs=None):
"""
Parameters
----------
data : ndarray
The data to save
uid : str, optional
The uid to be used for this entry,
if not given use uuid1 to generate one
resource_kwargs : None, optional
Currently raises if not 'falsy' and is ignored.
Returns
-------
uid : str
The uid used to register this data with filestore, can
be used to retrieve it
"""
if not self._writable:
raise RuntimeError("This writer can only write one data entry "
"and has already been used")
if resource_kwargs:
raise ValueError("This writer does not support resource_kwargs")
if op.exists(self._fpath):
raise IOError("the requested file {fpath} "
"already exist".format(fpath=self._fpath))
if uid is None:
uid = str(uuid.uuid1())
np.save(self._fpath, np.asanyarray(data))
self._writable = False
fb = fsc.insert_resource(self.SPEC_NAME, self._fpath, self._f_custom)
evl = fsc.insert_datum(fb, uid)
return evl.datum_id