def get_raw_dataset(self):
# Note: This is lazy to avoid building on import time, since import is part of nose's discovery and executed
# before the dependencies. This leads to datalad's ui backend not yet being correctly set, which in turn
# let's the cloning hang within progressbar generation.
if not self._dspath:
import tempfile
kwargs = get_tempfile_kwargs()
path = tempfile.mkdtemp(**kwargs)
f_dicoms = get_dicom_dataset('functional')
s_dicoms = get_dicom_dataset('structural')
ds = Dataset.create(path, cfg_proc=['hirni'])
ds.install(source=f_dicoms, path=op.join('func_acq', 'dicoms'))
ds.install(source=s_dicoms, path=op.join('struct_acq', 'dicoms'))
# Note: Recursive, since aggregation wasn't performed in the installed dastasets
ds.meta_aggregate([
op.join('func_acq', 'dicoms'),
op.join('struct_acq', 'dicoms')
],
into='top',
recursive=True)
# TODO: Figure how to add it to things to be removed after tests ran
self._dspath = ds.path
return self._dspath
def test_dicom2spec(path):
# ### SETUP ###
dicoms = get_dicom_dataset('structural')
ds = Dataset.create(path, cfg_proc=['hirni'])
ds.install(source=dicoms, path='acq100')
# Note: Recursive, since aggregation wasn't performed in the installed dastasets
# TODO: Use get_raw_sd from above instead of this setup
ds.meta_aggregate('acq100', into='top', recursive=True)
# ### END SETUP ###
# TODO: should it be specfile or acq/specfile? => At least doc needed,
# if not change
res = ds.hirni_dicom2spec(path='acq100', spec='spec_structural.json')
# check for actual location of spec_structural!
# => studyds root!
assert_result_count(res, 2)
assert_result_count(res, 1, path=op.join(ds.path, 'spec_structural.json'))
assert_result_count(res, 1, path=op.join(ds.path, '.gitattributes'))
ok_clean_git(ds.path)
# multiple execution shouldn't change .gitattributes again:
from os import stat
mtime = stat(op.join(ds.path, '.gitattributes')).st_mtime
res = ds.hirni_dicom2spec(path='acq100', spec='spec_structural.json')
assert_equal(stat(op.join(ds.path, '.gitattributes')).st_mtime, mtime)
def test_dicom_metadata_aggregation(path):
dicoms = get_dicom_dataset('structural')
ds = Dataset.create(path)
ds.install(source=dicoms, path='acq100')
ds.aggregate_metadata(recursive=True)
res = ds.metadata(get_aggregates=True)
assert_result_count(res, 2)
assert_result_count(res, 1, path=opj(ds.path, 'acq100'))
def test_dicom_metadata_aggregation(path):
dicoms = get_dicom_dataset('structural')
ds = Dataset.create(path)
ds.install(source=dicoms, path='acq100')
# Note: Recursive, since aggregation wasn't performed in the installed dastasets
ds.meta_aggregate('acq100', into='top', recursive=True)
res = ds.meta_dump(reporton='aggregates', recursive=True)
assert_result_count(res, 2)
assert_result_count(res, 1, path=op.join(ds.path, 'acq100'))
def _single_session_dicom2bids(label, path, toolbox_url):
with patch.dict('os.environ',
{'DATALAD_HIRNI_TOOLBOX_URL': toolbox_url}):
ds = Dataset.create(path, cfg_proc=['hirni'])
subject = "02"
acquisition = "{sub}_{label}".format(sub=subject, label=label)
dicoms = get_dicom_dataset(label)
ds.install(source=dicoms, path=op.join(acquisition, 'dicoms'))
# Note: Recursive, since aggregation wasn't performed in the installed dastasets
ds.meta_aggregate(op.join(acquisition, 'dicoms'), into='top', recursive=True)
spec_file = 'spec_{label}.json'.format(label=label)
ds.hirni_dicom2spec(path=op.join(acquisition, 'dicoms'),
spec=op.join(acquisition, spec_file))
ds.hirni_spec2bids(op.join(acquisition, spec_file))
def test_spec2bids(study_path, bids_path, toolbox_url):
with patch.dict('os.environ',
{'DATALAD_HIRNI_TOOLBOX_URL': toolbox_url}):
study_ds = Dataset(study_path).create(cfg_proc=['hirni'])
subject = "02"
acquisition = "{sub}_functional".format(sub=subject)
dicoms = get_dicom_dataset('functional')
study_ds.install(source=dicoms, path=op.join(acquisition, 'dicoms'))
# Note: Recursive, since aggregation wasn't performed in the installed dastasets
study_ds.meta_aggregate(op.join(acquisition, 'dicoms'), into='top', recursive=True)
study_ds.hirni_dicom2spec(path=op.join(acquisition, 'dicoms'),
spec=op.join(acquisition, 'studyspec.json'))
# add a custom converter script which is just a copy converter
from shutil import copy
copy(op.join(op.dirname(datalad_hirni.__file__),
'resources', 'dummy_executable.sh'),
op.join(study_ds.path, 'code', 'my_script.sh'))
study_ds.save(op.join('code', 'my_script.sh'), to_git=True,
message="add a copy converter script")
# add dummy data to be 'converted' by the copy converter
makedirs(op.join(study_ds.path, acquisition, 'my_fancy_data'))
with open(op.join(study_ds.path, acquisition, 'my_fancy_data',
'my_raw_data.txt'), 'w') as f:
f.write("some content")
study_ds.save(op.join(study_ds.path, acquisition, 'my_fancy_data', 'my_raw_data.txt'),
message="added fancy data")
# add specification snippet for that data:
# ############
# TODO: Needs procedure now
#
# snippet = {"type": "my_new_type",
# "location": op.join('my_fancy_data', 'my_raw_data.txt'),
# "subject": {"value": "{sub}".format(sub=subject),
# "approved": True},
# "converter": {"value": "{_hs[converter_path]} {_hs[location]} {dspath}/sub-{_hs[bids_subject]}/my_converted_data.txt",
# "approved": True},
# "converter_path": {"value": op.join(op.pardir, 'code', 'my_script.sh'),
# "approved": True}
# }
#
# # TODO: proper spec save helper, not just sort (also to be used in webapp!)
# from datalad.support import json_py
# spec_list = [r for r in json_py.load_stream(op.join(study_ds.path, acquisition, spec_file))]
# spec_list.append(snippet)
# from ..support.helpers import sort_spec
# spec_list = sorted(spec_list, key=lambda x: sort_spec(x))
# json_py.dump2stream(spec_list, op.join(study_ds.path, acquisition, spec_file))
#
# study_ds.add(op.join(acquisition, spec_file),
# message="Add spec snippet for fancy data",
# to_git=True)
#
# ##############
# create the BIDS dataset:
with patch.dict('os.environ',
{'DATALAD_HIRNI_TOOLBOX_URL': toolbox_url}):
bids_ds = Dataset.create(bids_path, cfg_proc=['hirni'])
# install the study dataset as "sourcedata":
bids_ds.install(source=study_ds.path, path="sourcedata")
# get the toolbox, since procedures can't be discovered otherwise
bids_ds.get(op.join('sourcedata', 'code', 'hirni-toolbox', 'converters',
'heudiconv', 'heudiconv.simg'))
# make sure, we have the target directory "sub-02" for the copy converter,
# even if heudiconv didn't run before (order of execution of the converters
# depends on order in the spec). This could of course also be part of the
# converter script itself.
makedirs(op.join(bids_ds.path, "sub-{sub}".format(sub=subject)))
bids_ds.hirni_spec2bids(op.join("sourcedata", acquisition, "studyspec.json"))