def __init__(self,
cache=True,
manifest_file='brain_observatory_manifest.json',
base_uri=None):
super(BrainObservatoryCache, self).__init__(manifest=manifest_file,
cache=cache)
self.api = BrainObservatoryApi(base_uri=base_uri)
def bo_api_save_ophys():
bo = BrainObservatoryApi('http://testwarehouse:9000')
bo.json_msg_query = \
MagicMock(name='json_msg_query',
return_value=[{'download_link': '/url/path/to/file'}])
return bo
def bo_api_save_ophys():
bo = BrainObservatoryApi('http://testwarehouse:9000')
bo.json_msg_query = \
MagicMock(name='json_msg_query',
return_value=[ {'download_link': '/url/path/to/file' } ])
return bo
def cell_specimen_table(md_temp_dir):
# download a zipped version of the cell specimen table for filter tests
# as it is orders of magnitude faster
api = BrainObservatoryApi()
zipped = os.path.join(md_temp_dir, "cell_specimens.zip")
api.retrieve_file_over_http(CELL_SPECIMEN_ZIP_URL, zipped)
df = pd.read_csv(ZipFile(zipped).open("cell_metrics.csv"),
true_values="t", false_values="f")
js = json.loads(df.to_json(orient="records"))
table_file = os.path.join(md_temp_dir, "cell_specimens.json")
with open(table_file, "w") as f:
json.dump(js, f, indent=1)
return table_file
def cell_specimen_table(tmpdir_factory):
# download a zipped version of the cell specimen table for filter tests
# as it is orders of magnitude faster
api = BrainObservatoryApi()
data_dir = str(tmpdir_factory.mktemp("data"))
zipped = os.path.join("cell_specimens.zip")
api.retrieve_file_over_http(CELL_SPECIMEN_ZIP_URL, zipped)
df = pd.read_csv(ZipFile(zipped).open("cell_metrics.csv"),
true_values="t", false_values="f")
js = json.loads(df.to_json(orient="records"))
table_file = os.path.join(data_dir, "cell_specimens.json")
with open(table_file, "w") as f:
json.dump(js, f, indent=1)
return table_file
def __init__(self,
cache=True,
manifest_file='brain_observatory_manifest.json',
base_uri=None,
api=None):
super(BrainObservatoryCache,
self).__init__(manifest=manifest_file,
cache=cache,
version=self.MANIFEST_VERSION)
if api is None:
self.api = BrainObservatoryApi(base_uri=base_uri)
else:
self.api = api
def __init__(self,
cache=True,
manifest_file=None,
base_uri=None,
api=None):
if manifest_file is None:
manifest_file = get_default_manifest_file('brain_observatory')
super(BrainObservatoryCache,
self).__init__(manifest=manifest_file,
cache=cache,
version=self.MANIFEST_VERSION)
if api is None:
self.api = BrainObservatoryApi(base_uri=base_uri)
else:
self.api = api
def __init__(self, cache=True, manifest_file=None, base_uri=None, api=None):
if manifest_file is None:
manifest_file = get_default_manifest_file('brain_observatory')
super(BrainObservatoryCache, self).__init__(
manifest=manifest_file, cache=cache, version=self.MANIFEST_VERSION)
if api is None:
self.api = BrainObservatoryApi(base_uri=base_uri)
else:
self.api = api
def bo_api():
bo = BrainObservatoryApi('http://testwarehouse:9000')
bo.json_msg_query = MagicMock(name='json_msg_query')
return bo
def api():
boi = BrainObservatoryApi()
return boi
def __init__(self, cache=True, manifest_file='brain_observatory_manifest.json', base_uri=None):
super(BrainObservatoryCache, self).__init__(
manifest=manifest_file, cache=cache)
self.api = BrainObservatoryApi(base_uri=base_uri)
class BrainObservatoryCache(Cache):
"""
Cache class for storing and accessing data from the Brain Observatory.
By default, this class will cache any downloaded metadata or files in
well known locations defined in a manifest file. This behavior can be
disabled.
Attributes
----------
api: BrainObservatoryApi instance
The object used for making API queries related to the Brain
Observatory.
Parameters
----------
cache: boolean
Whether the class should save results of API queries to locations specified
in the manifest file. Queries for files (as opposed to metadata) must have a
file location. If caching is disabled, those locations must be specified
in the function call (e.g. get_ophys_experiment_data(file_name='file.nwb')).
manifest_file: string
File name of the manifest to be read. Default is "brain_observatory_manifest.json".
"""
EXPERIMENT_CONTAINERS_KEY = 'EXPERIMENT_CONTAINERS'
EXPERIMENTS_KEY = 'EXPERIMENTS'
CELL_SPECIMENS_KEY = 'CELL_SPECIMENS'
EXPERIMENT_DATA_KEY = 'EXPERIMENT_DATA'
STIMULUS_MAPPINGS_KEY = 'STIMULUS_MAPPINGS'
def __init__(self, cache=True, manifest_file='brain_observatory_manifest.json', base_uri=None):
super(BrainObservatoryCache, self).__init__(
manifest=manifest_file, cache=cache)
self.api = BrainObservatoryApi(base_uri=base_uri)
def get_all_targeted_structures(self):
""" Return a list of all targeted structures in the data set. """
containers = self.get_experiment_containers(simple=False)
targeted_structures = set(
[c['targeted_structure']['acronym'] for c in containers])
return sorted(list(targeted_structures))
def get_all_cre_lines(self):
""" Return a list of all cre driver lines in the data set. """
containers = self.get_experiment_containers(simple=False)
cre_lines = set([_find_specimen_cre_line(c['specimen'])
for c in containers])
return sorted(list(cre_lines))
def get_all_reporter_lines(self):
""" Return a list of all reporter lines in the data set. """
containers = self.get_experiment_containers(simple=False)
reporter_lines = set([_find_specimen_reporter_line(c['specimen'])
for c in containers])
return sorted(list(reporter_lines))
def get_all_imaging_depths(self):
""" Return a list of all imaging depths in the data set. """
containers = self.get_experiment_containers(simple=False)
imaging_depths = set([c['imaging_depth'] for c in containers])
return sorted(list(imaging_depths))
def get_all_session_types(self):
""" Return a list of all stimulus sessions in the data set. """
exps = self.get_ophys_experiments(simple=False)
names = set([exp['stimulus_name'] for exp in exps])
return sorted(list(names))
def get_all_stimuli(self):
""" Return a list of all stimuli in the data set. """
return sorted(list(stim_info.all_stimuli()))
def get_experiment_containers(self, file_name=None,
ids=None,
targeted_structures=None,
imaging_depths=None,
cre_lines=None,
transgenic_lines=None,
simple=True):
""" Get a list of experiment containers matching certain criteria.
Parameters
----------
file_name: string
File name to save/read the experiment containers. If file_name is None,
the file_name will be pulled out of the manifest. If caching
is disabled, no file will be saved. Default is None.
ids: list
List of experiment container ids.
targeted_structures: list
List of structure acronyms. Must be in the list returned by
BrainObservatoryCache.get_all_targeted_structures().
imaging_depths: list
List of imaging depths. Must be in the list returned by
BrainObservatoryCache.get_all_imaging_depths().
cre_lines: list
List of cre lines. Must be in the list returned by
BrainObservatoryCache.get_all_cre_lines().
transgenic_lines: list
List of transgenic lines. Must be in the list returned by
BrainObservatoryCache.get_all_cre_lines() or.
BrainObservatoryCache.get_all_reporter_lines().
simple: boolean
Whether or not to simplify the dictionary properties returned by this method
to a more concise subset.
Returns
-------
list of dictionaries
"""
_assert_not_string(targeted_structures, "targeted_structures")
_assert_not_string(cre_lines, "cre_lines")
_assert_not_string(transgenic_lines, "transgenic_lines")
file_name = self.get_cache_path(
file_name, self.EXPERIMENT_CONTAINERS_KEY)
if os.path.exists(file_name):
containers = ju.read(file_name)
else:
containers = self.api.get_experiment_containers()
if self.cache:
ju.write(file_name, containers)
transgenic_lines = _merge_transgenic_lines(cre_lines, transgenic_lines)
containers = self.api.filter_experiment_containers(containers, ids=ids,
targeted_structures=targeted_structures,
imaging_depths=imaging_depths,
transgenic_lines=transgenic_lines)
if simple:
containers = [{
'id': c['id'],
'imaging_depth': c['imaging_depth'],
'targeted_structure': c['targeted_structure']['acronym'],
'cre_line': _find_specimen_cre_line(c['specimen']),
'reporter_line': _find_specimen_reporter_line(c['specimen']),
'age_days': c['specimen']['donor']['age']['days'],
'donor_name': c['specimen']['donor']['external_donor_name'],
'specimen_name': c['specimen']['name']
} for c in containers]
return containers
def get_ophys_experiments(self, file_name=None,
ids=None,
experiment_container_ids=None,
targeted_structures=None,
imaging_depths=None,
cre_lines=None,
transgenic_lines=None,
stimuli=None,
session_types=None,
simple=True):
""" Get a list of ophys experiments matching certain criteria.
Parameters
----------
file_name: string
File name to save/read the ophys experiments. If file_name is None,
the file_name will be pulled out of the manifest. If caching
is disabled, no file will be saved. Default is None.
ids: list
List of ophys experiment ids.
experiment_container_ids: list
List of experiment container ids.
targeted_structures: list
List of structure acronyms. Must be in the list returned by
BrainObservatoryCache.get_all_targeted_structures().
imaging_depths: list
List of imaging depths. Must be in the list returned by
BrainObservatoryCache.get_all_imaging_depths().
cre_lines: list
List of cre lines. Must be in the list returned by
BrainObservatoryCache.get_all_cre_lines().
transgenic_lines: list
List of transgenic lines. Must be in the list returned by
BrainObservatoryCache.get_all_cre_lines() or.
BrainObservatoryCache.get_all_reporter_lines().
stimuli: list
List of stimulus names. Must be in the list returned by
BrainObservatoryCache.get_all_stimuli().
session_types: list
List of stimulus session type names. Must be in the list returned by
BrainObservatoryCache.get_all_session_types().
simple: boolean
Whether or not to simplify the dictionary properties returned by this method
to a more concise subset.
Returns
-------
list of dictionaries
"""
_assert_not_string(targeted_structures, "targeted_structures")
_assert_not_string(cre_lines, "cre_lines")
_assert_not_string(transgenic_lines, "transgenic_lines")
_assert_not_string(stimuli, "stimuli")
_assert_not_string(session_types, "session_types")
file_name = self.get_cache_path(file_name, self.EXPERIMENTS_KEY)
if os.path.exists(file_name):
exps = ju.read(file_name)
else:
exps = self.api.get_ophys_experiments()
if self.cache:
ju.write(file_name, exps)
transgenic_lines = _merge_transgenic_lines(cre_lines, transgenic_lines)
exps = self.api.filter_ophys_experiments(exps,
ids=ids,
experiment_container_ids=experiment_container_ids,
targeted_structures=targeted_structures,
imaging_depths=imaging_depths,
transgenic_lines=transgenic_lines,
stimuli=stimuli,
session_types=session_types)
if simple:
exps = [{
'id': e['id'],
'imaging_depth': e['imaging_depth'],
'targeted_structure': e['targeted_structure']['acronym'],
'cre_line': _find_specimen_cre_line(e['specimen']),
'reporter_line': _find_specimen_reporter_line(e['specimen']),
'age_days': e['specimen']['donor']['age']['days'],
'experiment_container_id': e['experiment_container_id'],
'session_type': e['stimulus_name'],
'donor_name': e['specimen']['donor']['external_donor_name'],
'specimen_name': e['specimen']['name']
} for e in exps]
return exps
def _get_stimulus_mappings(self, file_name=None):
""" Returns a mapping of which metrics are related to which stimuli. Internal use only. """
file_name = self.get_cache_path(file_name, self.STIMULUS_MAPPINGS_KEY)
if os.path.exists(file_name):
mappings = ju.read(file_name)
else:
mappings = self.api.get_stimulus_mappings()
if self.cache:
ju.write(file_name, mappings)
return mappings
def get_cell_specimens(self,
file_name=None,
ids=None,
experiment_container_ids=None,
simple=True,
filters=None):
""" Return cell specimens that have certain properies.
Parameters
----------
file_name: string
File name to save/read the cell specimens. If file_name is None,
the file_name will be pulled out of the manifest. If caching
is disabled, no file will be saved. Default is None.
ids: list
List of cell specimen ids.
experiment_container_ids: list
List of experiment container ids.
simple: boolean
Whether or not to simplify the dictionary properties returned by this method
to a more concise subset.
filters: list of dicts
List of filter dictionaries. The Allen Brain Observatory web site can
generate filters in this format to reproduce a filtered set of cells
found there. To see what these look like, visit
http://observatory.brain-map.org/visualcoding, perform a cell search
and apply some filters (e.g. find cells in a particular area), then
click the "view these cells in the AllenSDK" link on the bottom-left
of the search results page. This will take you to a page that contains
a code sample you can use to apply those same filters via this argument.
For more detail on the filter syntax, see BrainObservatoryApi.dataframe_query.
Returns
-------
list of dictionaries
"""
file_name = self.get_cache_path(file_name, self.CELL_SPECIMENS_KEY)
if os.path.exists(file_name):
cell_specimens = ju.read(file_name)
else:
cell_specimens = self.api.get_cell_metrics()
if self.cache:
ju.write(file_name, cell_specimens)
cell_specimens = self.api.filter_cell_specimens(cell_specimens,
ids=ids,
experiment_container_ids=experiment_container_ids,
filters=filters)
# drop the thumbnail columns
if simple:
mappings = self._get_stimulus_mappings()
thumbnails = [m['item'] for m in mappings if m[
'item_type'] == 'T' and m['level'] == 'R']
for cs in cell_specimens:
for t in thumbnails:
del cs[t]
return cell_specimens
def get_ophys_experiment_data(self, ophys_experiment_id, file_name=None):
""" Download the NWB file for an ophys_experiment (if it hasn't already been
downloaded) and return a data accessor object.
Parameters
----------
file_name: string
File name to save/read the data set. If file_name is None,
the file_name will be pulled out of the manifest. If caching
is disabled, no file will be saved. Default is None.
ophys_experiment_id: integer
id of the ophys_experiment to retrieve
Returns
-------
BrainObservatoryNwbDataSet
"""
file_name = self.get_cache_path(
file_name, self.EXPERIMENT_DATA_KEY, ophys_experiment_id)
if not os.path.exists(file_name):
self.api.save_ophys_experiment_data(ophys_experiment_id, file_name)
return BrainObservatoryNwbDataSet(file_name)
def build_manifest(self, file_name):
"""
Construct a manifest for this Cache class and save it in a file.
Parameters
----------
file_name: string
File location to save the manifest.
"""
mb = ManifestBuilder()
mb.add_path('BASEDIR', '.')
mb.add_path(self.EXPERIMENT_CONTAINERS_KEY,
'experiment_containers.json', typename='file', parent_key='BASEDIR')
mb.add_path(self.EXPERIMENTS_KEY, 'ophys_experiments.json',
typename='file', parent_key='BASEDIR')
mb.add_path(self.EXPERIMENT_DATA_KEY, 'ophys_experiment_data/%d.nwb',
typename='file', parent_key='BASEDIR')
mb.add_path(self.CELL_SPECIMENS_KEY, 'cell_specimens.json',
typename='file', parent_key='BASEDIR')
mb.add_path(self.STIMULUS_MAPPINGS_KEY, 'stimulus_mappings.json',
typename='file', parent_key='BASEDIR')
mb.write_json_file(file_name)
def bo_api():
endpoint = os.environ[
'TEST_API_ENDPOINT'] if 'TEST_API_ENDPOINT' in os.environ else 'http://twarehouse-backup'
return BrainObservatoryApi(endpoint)
class BrainObservatoryCache(Cache):
"""
Cache class for storing and accessing data from the Brain Observatory.
By default, this class will cache any downloaded metadata or files in
well known locations defined in a manifest file. This behavior can be
disabled.
Attributes
----------
api: BrainObservatoryApi instance
The object used for making API queries related to the Brain
Observatory.
Parameters
----------
cache: boolean
Whether the class should save results of API queries to locations specified
in the manifest file. Queries for files (as opposed to metadata) must have a
file location. If caching is disabled, those locations must be specified
in the function call (e.g. get_ophys_experiment_data(file_name='file.nwb')).
manifest_file: string
File name of the manifest to be read. Default is "brain_observatory_manifest.json".
"""
EXPERIMENT_CONTAINERS_KEY = 'EXPERIMENT_CONTAINERS'
EXPERIMENTS_KEY = 'EXPERIMENTS'
CELL_SPECIMENS_KEY = 'CELL_SPECIMENS'
EXPERIMENT_DATA_KEY = 'EXPERIMENT_DATA'
STIMULUS_MAPPINGS_KEY = 'STIMULUS_MAPPINGS'
def __init__(self,
cache=True,
manifest_file='brain_observatory_manifest.json',
base_uri=None):
super(BrainObservatoryCache, self).__init__(manifest=manifest_file,
cache=cache)
self.api = BrainObservatoryApi(base_uri=base_uri)
def get_all_targeted_structures(self):
""" Return a list of all targeted structures in the data set. """
containers = self.get_experiment_containers(simple=False)
targeted_structures = set(
[c['targeted_structure']['acronym'] for c in containers])
return sorted(list(targeted_structures))
def get_all_cre_lines(self):
""" Return a list of all cre driver lines in the data set. """
containers = self.get_experiment_containers(simple=False)
cre_lines = set(
[_find_specimen_cre_line(c['specimen']) for c in containers])
return sorted(list(cre_lines))
def get_all_imaging_depths(self):
""" Return a list of all imaging depths in the data set. """
containers = self.get_experiment_containers(simple=False)
imaging_depths = set([c['imaging_depth'] for c in containers])
return sorted(list(imaging_depths))
def get_all_session_types(self):
""" Return a list of all stimulus sessions in the data set. """
exps = self.get_ophys_experiments()
names = set([exp['stimulus_name'] for exp in exps])
return sorted(list(names))
def get_all_stimuli(self):
""" Return a list of all stimuli in the data set. """
return sorted(list(stim_info.all_stimuli()))
def get_experiment_containers(self,
file_name=None,
ids=None,
targeted_structures=None,
imaging_depths=None,
cre_lines=None,
simple=True):
""" Get a list of experiment containers matching certain criteria.
Parameters
----------
file_name: string
File name to save/read the experiment containers. If file_name is None,
the file_name will be pulled out of the manifest. If caching
is disabled, no file will be saved. Default is None.
ids: list
List of experiment container ids.
targeted_structures: list
List of structure acronyms. Must be in the list returned by
BrainObservatoryCache.get_all_targeted_structures().
imaging_depths: list
List of imaging depths. Must be in the list returned by
BrainObservatoryCache.get_all_imaging_depths().
cre_lines: list
List of cre lines. Must be in the list returned by
BrainObservatoryCache.get_all_cre_lines().
simple: boolean
Whether or not to simplify the dictionary properties returned by this method
to a more concise subset.
Returns
-------
list of dictionaries
"""
file_name = self.get_cache_path(file_name,
self.EXPERIMENT_CONTAINERS_KEY)
if os.path.exists(file_name):
containers = ju.read(file_name)
else:
containers = self.api.get_experiment_containers()
if self.cache:
ju.write(file_name, containers)
containers = self.api.filter_experiment_containers(
containers,
ids=ids,
targeted_structures=targeted_structures,
imaging_depths=imaging_depths,
transgenic_lines=cre_lines)
if simple:
containers = [{
'id':
c['id'],
'imaging_depth':
c['imaging_depth'],
'targeted_structure':
c['targeted_structure']['acronym'],
'cre_line':
_find_specimen_cre_line(c['specimen']),
'age_days':
c['specimen']['donor']['age']['days']
} for c in containers]
return containers
def get_ophys_experiments(self,
file_name=None,
ids=None,
experiment_container_ids=None,
targeted_structures=None,
imaging_depths=None,
cre_lines=None,
stimuli=None,
session_types=None,
simple=True):
""" Get a list of ophys experiments matching certain criteria.
Parameters
----------
file_name: string
File name to save/read the ophys experiments. If file_name is None,
the file_name will be pulled out of the manifest. If caching
is disabled, no file will be saved. Default is None.
ids: list
List of ophys experiment ids.
experiment_container_ids: list
List of experiment container ids.
targeted_structures: list
List of structure acronyms. Must be in the list returned by
BrainObservatoryCache.get_all_targeted_structures().
imaging_depths: list
List of imaging depths. Must be in the list returned by
BrainObservatoryCache.get_all_imaging_depths().
cre_lines: list
List of cre lines. Must be in the list returned by
BrainObservatoryCache.get_all_cre_lines().
stimuli: list
List of stimulus names. Must be in the list returned by
BrainObservatoryCache.get_all_stimuli().
session_types: list
List of stimulus session type names. Must be in the list returned by
BrainObservatoryCache.get_all_session_types().
simple: boolean
Whether or not to simplify the dictionary properties returned by this method
to a more concise subset.
Returns
-------
list of dictionaries
"""
file_name = self.get_cache_path(file_name, self.EXPERIMENTS_KEY)
if os.path.exists(file_name):
exps = ju.read(file_name)
else:
exps = self.api.get_ophys_experiments()
if self.cache:
ju.write(file_name, exps)
exps = self.api.filter_ophys_experiments(
exps,
ids=ids,
experiment_container_ids=experiment_container_ids,
targeted_structures=targeted_structures,
imaging_depths=imaging_depths,
transgenic_lines=cre_lines,
stimuli=stimuli,
session_types=session_types)
if simple:
exps = [{
'id': e['id'],
'imaging_depth': e['imaging_depth'],
'targeted_structure': e['targeted_structure']['acronym'],
'cre_line': _find_specimen_cre_line(e['specimen']),
'age_days': e['specimen']['donor']['age']['days'],
'experiment_container_id': e['experiment_container_id'],
'session_type': e['stimulus_name']
} for e in exps]
return exps
def _get_stimulus_mappings(self, file_name=None):
""" Returns a mapping of which metrics are related to which stimuli. Internal use only. """
file_name = self.get_cache_path(file_name, self.STIMULUS_MAPPINGS_KEY)
if os.path.exists(file_name):
mappings = ju.read(file_name)
else:
mappings = self.api.get_stimulus_mappings()
if self.cache:
ju.write(file_name, mappings)
return mappings
def get_cell_specimens(self,
file_name=None,
ids=None,
experiment_container_ids=None,
simple=True):
""" Return cell specimens that have certain properies.
Parameters
----------
file_name: string
File name to save/read the cell specimens. If file_name is None,
the file_name will be pulled out of the manifest. If caching
is disabled, no file will be saved. Default is None.
ids: list
List of cell specimen ids.
experiment_container_ids: list
List of experiment container ids.
simple: boolean
Whether or not to simplify the dictionary properties returned by this method
to a more concise subset.
Returns
-------
list of dictionaries
"""
file_name = self.get_cache_path(file_name, self.CELL_SPECIMENS_KEY)
if os.path.exists(file_name):
cell_specimens = ju.read(file_name)
else:
cell_specimens = self.api.get_cell_metrics()
if self.cache:
ju.write(file_name, cell_specimens)
cell_specimens = self.api.filter_cell_specimens(
cell_specimens,
ids=ids,
experiment_container_ids=experiment_container_ids)
# drop the thumbnail columns
if simple:
mappings = self._get_stimulus_mappings()
thumbnails = [
m['item'] for m in mappings
if m['item_type'] == 'T' and m['level'] == 'R'
]
for cs in cell_specimens:
for t in thumbnails:
del cs[t]
return cell_specimens
def get_ophys_experiment_data(self, ophys_experiment_id, file_name=None):
""" Download the NWB file for an ophys_experiment (if it hasn't already been
downloaded) and return a data accessor object.
Parameters
----------
file_name: string
File name to save/read the data set. If file_name is None,
the file_name will be pulled out of the manifest. If caching
is disabled, no file will be saved. Default is None.
ophys_experiment_id: integer
id of the ophys_experiment to retrieve
Returns
-------
BrainObservatoryNwbDataSet
"""
file_name = self.get_cache_path(file_name, self.EXPERIMENT_DATA_KEY,
ophys_experiment_id)
if not os.path.exists(file_name):
self.api.save_ophys_experiment_data(ophys_experiment_id, file_name)
return BrainObservatoryNwbDataSet(file_name)
def build_manifest(self, file_name):
"""
Construct a manifest for this Cache class and save it in a file.
Parameters
----------
file_name: string
File location to save the manifest.
"""
mb = ManifestBuilder()
mb.add_path('BASEDIR', '.')
mb.add_path(self.EXPERIMENT_CONTAINERS_KEY,
'experiment_containers.json',
typename='file',
parent_key='BASEDIR')
mb.add_path(self.EXPERIMENTS_KEY,
'ophys_experiments.json',
typename='file',
parent_key='BASEDIR')
mb.add_path(self.EXPERIMENT_DATA_KEY,
'ophys_experiment_data/%d.nwb',
typename='file',
parent_key='BASEDIR')
mb.add_path(self.CELL_SPECIMENS_KEY,
'cell_specimens.json',
typename='file',
parent_key='BASEDIR')
mb.add_path(self.STIMULUS_MAPPINGS_KEY,
'stimulus_mappings.json',
typename='file',
parent_key='BASEDIR')
mb.write_json_file(file_name)
class BrainObservatoryCache(Cache):
"""
Cache class for storing and accessing data from the Brain Observatory.
By default, this class will cache any downloaded metadata or files in
well known locations defined in a manifest file. This behavior can be
disabled.
Attributes
----------
api: BrainObservatoryApi instance
The object used for making API queries related to the Brain
Observatory.
Parameters
----------
cache: boolean
Whether the class should save results of API queries to locations specified
in the manifest file. Queries for files (as opposed to metadata) must have a
file location. If caching is disabled, those locations must be specified
in the function call (e.g. get_ophys_experiment_data(file_name='file.nwb')).
manifest_file: string
File name of the manifest to be read. Default is "brain_observatory_manifest.json".
"""
EXPERIMENT_CONTAINERS_KEY = 'EXPERIMENT_CONTAINERS'
EXPERIMENTS_KEY = 'EXPERIMENTS'
CELL_SPECIMENS_KEY = 'CELL_SPECIMENS'
EXPERIMENT_DATA_KEY = 'EXPERIMENT_DATA'
ANALYSIS_DATA_KEY = 'ANALYSIS_DATA'
EVENTS_DATA_KEY = 'EVENTS_DATA'
STIMULUS_MAPPINGS_KEY = 'STIMULUS_MAPPINGS'
MANIFEST_VERSION='1.2'
def __init__(self, cache=True, manifest_file=None, base_uri=None, api=None):
if manifest_file is None:
manifest_file = get_default_manifest_file('brain_observatory')
super(BrainObservatoryCache, self).__init__(
manifest=manifest_file, cache=cache, version=self.MANIFEST_VERSION)
if api is None:
self.api = BrainObservatoryApi(base_uri=base_uri)
else:
self.api = api
def get_all_targeted_structures(self):
""" Return a list of all targeted structures in the data set. """
containers = self.get_experiment_containers(simple=False)
targeted_structures = set(
[c['targeted_structure']['acronym'] for c in containers])
return sorted(list(targeted_structures))
def get_all_cre_lines(self):
""" Return a list of all cre driver lines in the data set. """
containers = self.get_experiment_containers(simple=True)
cre_lines = set([c['cre_line'] for c in containers])
return sorted(list(cre_lines))
def get_all_reporter_lines(self):
""" Return a list of all reporter lines in the data set. """
containers = self.get_experiment_containers(simple=True)
reporter_lines = set([c['reporter_line'] for c in containers])
return sorted(list(reporter_lines))
def get_all_imaging_depths(self):
""" Return a list of all imaging depths in the data set. """
containers = self.get_experiment_containers(simple=True)
imaging_depths = set([c['imaging_depth'] for c in containers])
return sorted(list(imaging_depths))
def get_all_session_types(self):
""" Return a list of all stimulus sessions in the data set. """
exps = self.get_ophys_experiments(simple=False)
names = set([exp['stimulus_name'] for exp in exps])
return sorted(list(names))
def get_all_stimuli(self):
""" Return a list of all stimuli in the data set. """
return sorted(list(stim_info.all_stimuli()))
def get_experiment_containers(self, file_name=None,
ids=None,
targeted_structures=None,
imaging_depths=None,
cre_lines=None,
reporter_lines=None,
transgenic_lines=None,
include_failed=False,
simple=True):
""" Get a list of experiment containers matching certain criteria.
Parameters
----------
file_name: string
File name to save/read the experiment containers. If file_name is None,
the file_name will be pulled out of the manifest. If caching
is disabled, no file will be saved. Default is None.
ids: list
List of experiment container ids.
targeted_structures: list
List of structure acronyms. Must be in the list returned by
BrainObservatoryCache.get_all_targeted_structures().
imaging_depths: list
List of imaging depths. Must be in the list returned by
BrainObservatoryCache.get_all_imaging_depths().
cre_lines: list
List of cre lines. Must be in the list returned by
BrainObservatoryCache.get_all_cre_lines().
reporter_lines: list
List of reporter lines. Must be in the list returned by
BrainObservatoryCache.get_all_reporter_lines().
transgenic_lines: list
List of transgenic lines. Must be in the list returned by
BrainObservatoryCache.get_all_cre_lines() or.
BrainObservatoryCache.get_all_reporter_lines().
include_failed: boolean
Whether or not to include failed experiment containers.
simple: boolean
Whether or not to simplify the dictionary properties returned by this method
to a more concise subset.
Returns
-------
list of dictionaries
"""
_assert_not_string(targeted_structures, "targeted_structures")
_assert_not_string(cre_lines, "cre_lines")
_assert_not_string(reporter_lines, "reporter_lines")
_assert_not_string(transgenic_lines, "transgenic_lines")
file_name = self.get_cache_path(
file_name, self.EXPERIMENT_CONTAINERS_KEY)
containers = self.api.get_experiment_containers(path=file_name,
strategy='lazy',
**Cache.cache_json())
containers = self.api.filter_experiment_containers(containers, ids=ids,
targeted_structures=targeted_structures,
imaging_depths=imaging_depths,
cre_lines=cre_lines,
reporter_lines=reporter_lines,
transgenic_lines=transgenic_lines,
include_failed=include_failed,
simple=simple)
return containers
def get_ophys_experiment_stimuli(self, experiment_id):
""" For a single experiment, return the list of stimuli present in that experiment. """
exps = self.get_ophys_experiments(ids=[experiment_id])
if len(exps) == 0:
return None
return stim_info.stimuli_in_session(exps[0]['session_type'])
def get_ophys_experiments(self, file_name=None,
ids=None,
experiment_container_ids=None,
targeted_structures=None,
imaging_depths=None,
cre_lines=None,
reporter_lines=None,
transgenic_lines=None,
stimuli=None,
session_types=None,
cell_specimen_ids=None,
include_failed=False,
require_eye_tracking=False,
simple=True):
""" Get a list of ophys experiments matching certain criteria.
Parameters
----------
file_name: string
File name to save/read the ophys experiments. If file_name is None,
the file_name will be pulled out of the manifest. If caching
is disabled, no file will be saved. Default is None.
ids: list
List of ophys experiment ids.
experiment_container_ids: list
List of experiment container ids.
targeted_structures: list
List of structure acronyms. Must be in the list returned by
BrainObservatoryCache.get_all_targeted_structures().
imaging_depths: list
List of imaging depths. Must be in the list returned by
BrainObservatoryCache.get_all_imaging_depths().
cre_lines: list
List of cre lines. Must be in the list returned by
BrainObservatoryCache.get_all_cre_lines().
reporter_lines: list
List of reporter lines. Must be in the list returned by
BrainObservatoryCache.get_all_reporter_lines().
transgenic_lines: list
List of transgenic lines. Must be in the list returned by
BrainObservatoryCache.get_all_cre_lines() or.
BrainObservatoryCache.get_all_reporter_lines().
stimuli: list
List of stimulus names. Must be in the list returned by
BrainObservatoryCache.get_all_stimuli().
session_types: list
List of stimulus session type names. Must be in the list returned by
BrainObservatoryCache.get_all_session_types().
cell_specimen_ids: list
Only include experiments that contain cells with these ids.
include_failed: boolean
Whether or not to include experiments from failed experiment containers.
simple: boolean
Whether or not to simplify the dictionary properties returned by this method
to a more concise subset.
require_eye_tracking: boolean
If True, only return experiments that have eye tracking results. Default: False.
Returns
-------
list of dictionaries
"""
_assert_not_string(targeted_structures, "targeted_structures")
_assert_not_string(cre_lines, "cre_lines")
_assert_not_string(reporter_lines, "reporter_lines")
_assert_not_string(transgenic_lines, "transgenic_lines")
_assert_not_string(stimuli, "stimuli")
_assert_not_string(session_types, "session_types")
file_name = self.get_cache_path(file_name, self.EXPERIMENTS_KEY)
exps = self.api.get_ophys_experiments(path=file_name,
strategy='lazy',
**Cache.cache_json())
if cell_specimen_ids is not None:
cells = self.get_cell_specimens(ids=cell_specimen_ids)
cell_container_ids = set([cell['experiment_container_id'] for cell in cells])
if experiment_container_ids is not None:
experiment_container_ids = list(set(experiment_container_ids) - cell_container_ids)
else:
experiment_container_ids = list(cell_container_ids)
exps = self.api.filter_ophys_experiments(exps,
ids=ids,
experiment_container_ids=experiment_container_ids,
targeted_structures=targeted_structures,
imaging_depths=imaging_depths,
cre_lines=cre_lines,
reporter_lines=reporter_lines,
transgenic_lines=transgenic_lines,
stimuli=stimuli,
session_types=session_types,
include_failed=include_failed,
require_eye_tracking=require_eye_tracking,
simple=simple)
return exps
def _get_stimulus_mappings(self, file_name=None):
""" Returns a mapping of which metrics are related to which stimuli. Internal use only. """
file_name = self.get_cache_path(file_name, self.STIMULUS_MAPPINGS_KEY)
mappings = self.api.get_stimulus_mappings(path=file_name,
strategy='lazy',
**Cache.cache_json())
return mappings
def get_cell_specimens(self,
file_name=None,
ids=None,
experiment_container_ids=None,
include_failed=False,
simple=True,
filters=None):
""" Return cell specimens that have certain properies.
Parameters
----------
file_name: string
File name to save/read the cell specimens. If file_name is None,
the file_name will be pulled out of the manifest. If caching
is disabled, no file will be saved. Default is None.
ids: list
List of cell specimen ids.
experiment_container_ids: list
List of experiment container ids.
include_failed: bool
Whether to include cells from failed experiment containers
simple: boolean
Whether or not to simplify the dictionary properties returned by this method
to a more concise subset.
filters: list of dicts
List of filter dictionaries. The Allen Brain Observatory web site can
generate filters in this format to reproduce a filtered set of cells
found there. To see what these look like, visit
http://observatory.brain-map.org/visualcoding, perform a cell search
and apply some filters (e.g. find cells in a particular area), then
click the "view these cells in the AllenSDK" link on the bottom-left
of the search results page. This will take you to a page that contains
a code sample you can use to apply those same filters via this argument.
For more detail on the filter syntax, see BrainObservatoryApi.dataframe_query.
Returns
-------
list of dictionaries
"""
file_name = self.get_cache_path(file_name, self.CELL_SPECIMENS_KEY)
cell_specimens = self.api.get_cell_metrics(path=file_name,
strategy='lazy',
pre= lambda x: [y for y in x],
**Cache.cache_json())
cell_specimens = self.api.filter_cell_specimens(cell_specimens,
ids=ids,
experiment_container_ids=experiment_container_ids,
include_failed=include_failed,
filters=filters)
# drop the thumbnail columns
if simple:
mappings = self._get_stimulus_mappings()
thumbnails = [m['item'] for m in mappings if m[
'item_type'] == 'T' and m['level'] == 'R']
for cs in cell_specimens:
for t in thumbnails:
del cs[t]
return cell_specimens
def get_ophys_experiment_data(self, ophys_experiment_id, file_name=None):
""" Download the NWB file for an ophys_experiment (if it hasn't already been
downloaded) and return a data accessor object.
Parameters
----------
file_name: string
File name to save/read the data set. If file_name is None,
the file_name will be pulled out of the manifest. If caching
is disabled, no file will be saved. Default is None.
ophys_experiment_id: integer
id of the ophys_experiment to retrieve
Returns
-------
BrainObservatoryNwbDataSet
"""
file_name = self.get_cache_path(
file_name, self.EXPERIMENT_DATA_KEY, ophys_experiment_id)
self.api.save_ophys_experiment_data(ophys_experiment_id, file_name, strategy='lazy')
return BrainObservatoryNwbDataSet(file_name)
def get_ophys_experiment_analysis(self, ophys_experiment_id, stimulus_type, file_name=None):
""" Download the h5 analysis file for a stimulus set, for a particular ophys_experiment
(if it hasn't already been downloaded) and return a data accessor object.
Parameters
----------
file_name: string
File name to save/read the data set. If file_name is None,
the file_name will be pulled out of the manifest. If caching
is disabled, no file will be saved. Default is None.
ophys_experiment_id: int
id of the ophys_experiment to retrieve
stimulus_name: str
stimulus type; should be an element of self.list_stimuli()
Returns
-------
BrainObservatoryNwbDataSet
"""
data_set = self.get_ophys_experiment_data(ophys_experiment_id, file_name=None)
session_type = data_set.get_session_type()
if not stimulus_type in stim_info.SESSION_STIMULUS_MAP[session_type]:
raise RuntimeError('Stimulus %s not available session type: %s' % (stimulus_type, stim_info.SESSION_STIMULUS_MAP[stimulus_type]))
# Use manifest to figure out where to cache the file:
file_name = self.get_cache_path(file_name, self.ANALYSIS_DATA_KEY, ophys_experiment_id, session_type)
# Cache the analsis file from an RMA query:
self.api.save_ophys_experiment_analysis_data(ophys_experiment_id, file_name, strategy='lazy')
# Get the analysis class from ANALYSIS_CLASS_DICT, and build from the static method:
if stimulus_type in stim_info.LOCALLY_SPARSE_NOISE_STIMULUS_TYPES+stim_info.NATURAL_MOVIE_STIMULUS_TYPES:
return ANALYSIS_CLASS_DICT[stimulus_type].from_analysis_file(data_set, file_name, stimulus_type)
else:
return ANALYSIS_CLASS_DICT[stimulus_type].from_analysis_file(data_set, file_name)
def get_ophys_experiment_events(self, ophys_experiment_id, file_name=None):
""" Download the npz events file for an ophys_experiment if it hasn't
already been downloaded and return the events array.
Parameters
----------
file_name: string
File name to save/read the data set. If file_name is None,
the file_name will be pulled out of the manifest. If caching
is disabled, no file will be saved. Default is None.
ophys_experiment_id: int
id of the ophys_experiment to retrieve events for
Returns
-------
events: numpy.ndarray
[N_cells,N_times] array of events.
"""
file_name = self.get_cache_path(
file_name, self.EVENTS_DATA_KEY, ophys_experiment_id)
self.api.save_ophys_experiment_event_data(ophys_experiment_id, file_name, strategy='lazy')
return np.load(file_name, allow_pickle=False)["ev"]
def build_manifest(self, file_name):
"""
Construct a manifest for this Cache class and save it in a file.
Parameters
----------
file_name: string
File location to save the manifest.
"""
mb = ManifestBuilder()
mb.set_version(self.MANIFEST_VERSION)
mb.add_path('BASEDIR', '.')
mb.add_path(self.EXPERIMENT_CONTAINERS_KEY,
'experiment_containers.json', typename='file', parent_key='BASEDIR')
mb.add_path(self.EXPERIMENTS_KEY, 'ophys_experiments.json',
typename='file', parent_key='BASEDIR')
mb.add_path(self.EXPERIMENT_DATA_KEY, 'ophys_experiment_data/%d.nwb',
typename='file', parent_key='BASEDIR')
mb.add_path(self.ANALYSIS_DATA_KEY, 'ophys_experiment_analysis/%d_%s_analysis.h5',
typename='file', parent_key='BASEDIR')
mb.add_path(self.EVENTS_DATA_KEY, 'ophys_experiment_events/%d_events.npz',
typename='file', parent_key='BASEDIR')
mb.add_path(self.CELL_SPECIMENS_KEY, 'cell_specimens.json',
typename='file', parent_key='BASEDIR')
mb.add_path(self.STIMULUS_MAPPINGS_KEY, 'stimulus_mappings.json',
typename='file', parent_key='BASEDIR')
mb.write_json_file(file_name)
def bo_api():
bo = BrainObservatoryApi('http://testwarehouse:9000')
bo.json_msg_query = MagicMock(name='json_msg_query')
return bo
class BrainObservatoryCache(Cache):
"""
Cache class for storing and accessing data from the Brain Observatory.
By default, this class will cache any downloaded metadata or files in
well known locations defined in a manifest file. This behavior can be
disabled.
Attributes
----------
api: BrainObservatoryApi instance
The object used for making API queries related to the Brain
Observatory.
Parameters
----------
cache: boolean
Whether the class should save results of API queries to locations specified
in the manifest file. Queries for files (as opposed to metadata) must have a
file location. If caching is disabled, those locations must be specified
in the function call (e.g. get_ophys_experiment_data(file_name='file.nwb')).
manifest_file: string
File name of the manifest to be read. Default is "brain_observatory_manifest.json".
"""
EXPERIMENT_CONTAINERS_KEY = 'EXPERIMENT_CONTAINERS'
EXPERIMENTS_KEY = 'EXPERIMENTS'
CELL_SPECIMENS_KEY = 'CELL_SPECIMENS'
EXPERIMENT_DATA_KEY = 'EXPERIMENT_DATA'
STIMULUS_MAPPINGS_KEY = 'STIMULUS_MAPPINGS'
MANIFEST_VERSION = None
def __init__(self,
cache=True,
manifest_file='brain_observatory_manifest.json',
base_uri=None):
super(BrainObservatoryCache,
self).__init__(manifest=manifest_file,
cache=cache,
version=self.MANIFEST_VERSION)
self.api = BrainObservatoryApi(base_uri=base_uri)
def get_all_targeted_structures(self):
""" Return a list of all targeted structures in the data set. """
containers = self.get_experiment_containers(simple=False)
targeted_structures = set(
[c['targeted_structure']['acronym'] for c in containers])
return sorted(list(targeted_structures))
def get_all_cre_lines(self):
""" Return a list of all cre driver lines in the data set. """
containers = self.get_experiment_containers(simple=False)
cre_lines = set(
[_find_specimen_cre_line(c['specimen']) for c in containers])
return sorted(list(cre_lines))
def get_all_reporter_lines(self):
""" Return a list of all reporter lines in the data set. """
containers = self.get_experiment_containers(simple=False)
reporter_lines = set(
[_find_specimen_reporter_line(c['specimen']) for c in containers])
return sorted(list(reporter_lines))
def get_all_imaging_depths(self):
""" Return a list of all imaging depths in the data set. """
containers = self.get_experiment_containers(simple=False)
imaging_depths = set([c['imaging_depth'] for c in containers])
return sorted(list(imaging_depths))
def get_all_session_types(self):
""" Return a list of all stimulus sessions in the data set. """
exps = self.get_ophys_experiments(simple=False)
names = set([exp['stimulus_name'] for exp in exps])
return sorted(list(names))
def get_all_stimuli(self):
""" Return a list of all stimuli in the data set. """
return sorted(list(stim_info.all_stimuli()))
def get_experiment_containers(self,
file_name=None,
ids=None,
targeted_structures=None,
imaging_depths=None,
cre_lines=None,
transgenic_lines=None,
include_failed=False,
simple=True):
""" Get a list of experiment containers matching certain criteria.
Parameters
----------
file_name: string
File name to save/read the experiment containers. If file_name is None,
the file_name will be pulled out of the manifest. If caching
is disabled, no file will be saved. Default is None.
ids: list
List of experiment container ids.
targeted_structures: list
List of structure acronyms. Must be in the list returned by
BrainObservatoryCache.get_all_targeted_structures().
imaging_depths: list
List of imaging depths. Must be in the list returned by
BrainObservatoryCache.get_all_imaging_depths().
cre_lines: list
List of cre lines. Must be in the list returned by
BrainObservatoryCache.get_all_cre_lines().
transgenic_lines: list
List of transgenic lines. Must be in the list returned by
BrainObservatoryCache.get_all_cre_lines() or.
BrainObservatoryCache.get_all_reporter_lines().
include_failed: boolean
Whether or not to include failed experiment containers.
simple: boolean
Whether or not to simplify the dictionary properties returned by this method
to a more concise subset.
Returns
-------
list of dictionaries
"""
_assert_not_string(targeted_structures, "targeted_structures")
_assert_not_string(cre_lines, "cre_lines")
_assert_not_string(transgenic_lines, "transgenic_lines")
file_name = self.get_cache_path(file_name,
self.EXPERIMENT_CONTAINERS_KEY)
containers = self.api.get_experiment_containers(path=file_name,
strategy='lazy',
**Cache.cache_json())
transgenic_lines = _merge_transgenic_lines(cre_lines, transgenic_lines)
containers = self.api.filter_experiment_containers(
containers,
ids=ids,
targeted_structures=targeted_structures,
imaging_depths=imaging_depths,
transgenic_lines=transgenic_lines,
include_failed=include_failed)
if simple:
containers = [{
'id':
c['id'],
'imaging_depth':
c['imaging_depth'],
'targeted_structure':
c['targeted_structure']['acronym'],
'cre_line':
_find_specimen_cre_line(c['specimen']),
'reporter_line':
_find_specimen_reporter_line(c['specimen']),
'donor_name':
c['specimen']['donor']['external_donor_name'],
'specimen_name':
c['specimen']['name'],
'tags':
_find_container_tags(c),
'failed':
c['failed']
} for c in containers]
return containers
def get_ophys_experiment_stimuli(self, experiment_id):
""" For a single experiment, return the list of stimuli present in that experiment. """
exps = self.get_ophys_experiments(ids=[experiment_id])
if len(exps) == 0:
return None
return stim_info.stimuli_in_session(exps[0]['session_type'])
def get_ophys_experiments(self,
file_name=None,
ids=None,
experiment_container_ids=None,
targeted_structures=None,
imaging_depths=None,
cre_lines=None,
transgenic_lines=None,
stimuli=None,
session_types=None,
cell_specimen_ids=None,
include_failed=False,
require_eye_tracking=False,
simple=True):
""" Get a list of ophys experiments matching certain criteria.
Parameters
----------
file_name: string
File name to save/read the ophys experiments. If file_name is None,
the file_name will be pulled out of the manifest. If caching
is disabled, no file will be saved. Default is None.
ids: list
List of ophys experiment ids.
experiment_container_ids: list
List of experiment container ids.
targeted_structures: list
List of structure acronyms. Must be in the list returned by
BrainObservatoryCache.get_all_targeted_structures().
imaging_depths: list
List of imaging depths. Must be in the list returned by
BrainObservatoryCache.get_all_imaging_depths().
cre_lines: list
List of cre lines. Must be in the list returned by
BrainObservatoryCache.get_all_cre_lines().
transgenic_lines: list
List of transgenic lines. Must be in the list returned by
BrainObservatoryCache.get_all_cre_lines() or.
BrainObservatoryCache.get_all_reporter_lines().
stimuli: list
List of stimulus names. Must be in the list returned by
BrainObservatoryCache.get_all_stimuli().
session_types: list
List of stimulus session type names. Must be in the list returned by
BrainObservatoryCache.get_all_session_types().
cell_specimen_ids: list
Only include experiments that contain cells with these ids.
include_failed: boolean
Whether or not to include experiments from failed experiment containers.
simple: boolean
Whether or not to simplify the dictionary properties returned by this method
to a more concise subset.
require_eye_tracking: boolean
If True, only return experiments that have eye tracking results. Default: False.
Returns
-------
list of dictionaries
"""
_assert_not_string(targeted_structures, "targeted_structures")
_assert_not_string(cre_lines, "cre_lines")
_assert_not_string(transgenic_lines, "transgenic_lines")
_assert_not_string(stimuli, "stimuli")
_assert_not_string(session_types, "session_types")
file_name = self.get_cache_path(file_name, self.EXPERIMENTS_KEY)
exps = self.api.get_ophys_experiments(path=file_name,
strategy='lazy',
**Cache.cache_json())
transgenic_lines = _merge_transgenic_lines(cre_lines, transgenic_lines)
if cell_specimen_ids is not None:
cells = self.get_cell_specimens(ids=cell_specimen_ids)
cell_container_ids = set(
[cell['experiment_container_id'] for cell in cells])
if experiment_container_ids is not None:
experiment_container_ids = list(
set(experiment_container_ids) - cell_container_ids)
else:
experiment_container_ids = list(cell_container_ids)
exps = self.api.filter_ophys_experiments(
exps,
ids=ids,
experiment_container_ids=experiment_container_ids,
targeted_structures=targeted_structures,
imaging_depths=imaging_depths,
transgenic_lines=transgenic_lines,
stimuli=stimuli,
session_types=session_types,
include_failed=include_failed,
require_eye_tracking=require_eye_tracking)
if simple:
exps = [{
'id':
e['id'],
'imaging_depth':
e['imaging_depth'],
'targeted_structure':
e['targeted_structure']['acronym'],
'cre_line':
_find_specimen_cre_line(e['specimen']),
'reporter_line':
_find_specimen_reporter_line(e['specimen']),
'acquisition_age_days':
_find_experiment_acquisition_age(e),
'experiment_container_id':
e['experiment_container_id'],
'session_type':
e['stimulus_name'],
'donor_name':
e['specimen']['donor']['external_donor_name'],
'specimen_name':
e['specimen']['name'],
'fail_eye_tracking':
e.get('fail_eye_tracking', None)
} for e in exps]
return exps
def _get_stimulus_mappings(self, file_name=None):
""" Returns a mapping of which metrics are related to which stimuli. Internal use only. """
file_name = self.get_cache_path(file_name, self.STIMULUS_MAPPINGS_KEY)
mappings = self.api.get_stimulus_mappings(path=file_name,
strategy='lazy',
**Cache.cache_json())
return mappings
def get_cell_specimens(self,
file_name=None,
ids=None,
experiment_container_ids=None,
include_failed=False,
simple=True,
filters=None):
""" Return cell specimens that have certain properies.
Parameters
----------
file_name: string
File name to save/read the cell specimens. If file_name is None,
the file_name will be pulled out of the manifest. If caching
is disabled, no file will be saved. Default is None.
ids: list
List of cell specimen ids.
experiment_container_ids: list
List of experiment container ids.
include_failed: bool
Whether to include cells from failed experiment containers
simple: boolean
Whether or not to simplify the dictionary properties returned by this method
to a more concise subset.
filters: list of dicts
List of filter dictionaries. The Allen Brain Observatory web site can
generate filters in this format to reproduce a filtered set of cells
found there. To see what these look like, visit
http://observatory.brain-map.org/visualcoding, perform a cell search
and apply some filters (e.g. find cells in a particular area), then
click the "view these cells in the AllenSDK" link on the bottom-left
of the search results page. This will take you to a page that contains
a code sample you can use to apply those same filters via this argument.
For more detail on the filter syntax, see BrainObservatoryApi.dataframe_query.
Returns
-------
list of dictionaries
"""
file_name = self.get_cache_path(file_name, self.CELL_SPECIMENS_KEY)
cell_specimens = self.api.get_cell_metrics(path=file_name,
strategy='lazy',
**Cache.cache_json())
cell_specimens = self.api.filter_cell_specimens(
cell_specimens,
ids=ids,
experiment_container_ids=experiment_container_ids,
include_failed=include_failed,
filters=filters)
# drop the thumbnail columns
if simple:
mappings = self._get_stimulus_mappings()
thumbnails = [
m['item'] for m in mappings
if m['item_type'] == 'T' and m['level'] == 'R'
]
for cs in cell_specimens:
for t in thumbnails:
del cs[t]
return cell_specimens
def get_ophys_experiment_data(self, ophys_experiment_id, file_name=None):
""" Download the NWB file for an ophys_experiment (if it hasn't already been
downloaded) and return a data accessor object.
Parameters
----------
file_name: string
File name to save/read the data set. If file_name is None,
the file_name will be pulled out of the manifest. If caching
is disabled, no file will be saved. Default is None.
ophys_experiment_id: integer
id of the ophys_experiment to retrieve
Returns
-------
BrainObservatoryNwbDataSet
"""
file_name = self.get_cache_path(file_name, self.EXPERIMENT_DATA_KEY,
ophys_experiment_id)
self.api.save_ophys_experiment_data(ophys_experiment_id,
file_name,
strategy='lazy')
return BrainObservatoryNwbDataSet(file_name)
def build_manifest(self, file_name):
"""
Construct a manifest for this Cache class and save it in a file.
Parameters
----------
file_name: string
File location to save the manifest.
"""
mb = ManifestBuilder()
mb.set_version(self.MANIFEST_VERSION)
mb.add_path('BASEDIR', '.')
mb.add_path(self.EXPERIMENT_CONTAINERS_KEY,
'experiment_containers.json',
typename='file',
parent_key='BASEDIR')
mb.add_path(self.EXPERIMENTS_KEY,
'ophys_experiments.json',
typename='file',
parent_key='BASEDIR')
mb.add_path(self.EXPERIMENT_DATA_KEY,
'ophys_experiment_data/%d.nwb',
typename='file',
parent_key='BASEDIR')
mb.add_path(self.CELL_SPECIMENS_KEY,
'cell_specimens.json',
typename='file',
parent_key='BASEDIR')
mb.add_path(self.STIMULUS_MAPPINGS_KEY,
'stimulus_mappings.json',
typename='file',
parent_key='BASEDIR')
mb.write_json_file(file_name)
class BrainObservatoryCache(Cache):
"""
Cache class for storing and accessing data from the Brain Observatory.
By default, this class will cache any downloaded metadata or files in
well known locations defined in a manifest file. This behavior can be
disabled.
Attributes
----------
api: BrainObservatoryApi instance
The object used for making API queries related to the Brain
Observatory.
Parameters
----------
cache: boolean
Whether the class should save results of API queries to locations specified
in the manifest file. Queries for files (as opposed to metadata) must have a
file location. If caching is disabled, those locations must be specified
in the function call (e.g. get_ophys_experiment_data(file_name='file.nwb')).
manifest_file: string
File name of the manifest to be read. Default is "brain_observatory_manifest.json".
"""
EXPERIMENT_CONTAINERS_KEY = 'EXPERIMENT_CONTAINERS'
EXPERIMENTS_KEY = 'EXPERIMENTS'
CELL_SPECIMENS_KEY = 'CELL_SPECIMENS'
EXPERIMENT_DATA_KEY = 'EXPERIMENT_DATA'
ANALYSIS_DATA_KEY = 'ANALYSIS_DATA'
EVENTS_DATA_KEY = 'EVENTS_DATA'
STIMULUS_MAPPINGS_KEY = 'STIMULUS_MAPPINGS'
EYE_GAZE_DATA_KEY = 'EYE_GAZE_DATA'
MANIFEST_VERSION = '1.3'
def __init__(self,
cache=True,
manifest_file=None,
base_uri=None,
api=None):
if manifest_file is None:
manifest_file = get_default_manifest_file('brain_observatory')
super(BrainObservatoryCache,
self).__init__(manifest=manifest_file,
cache=cache,
version=self.MANIFEST_VERSION)
if api is None:
self.api = BrainObservatoryApi(base_uri=base_uri)
else:
self.api = api
def get_all_targeted_structures(self):
""" Return a list of all targeted structures in the data set. """
containers = self.get_experiment_containers(simple=False)
targeted_structures = set(
[c['targeted_structure']['acronym'] for c in containers])
return sorted(list(targeted_structures))
def get_all_cre_lines(self):
""" Return a list of all cre driver lines in the data set. """
containers = self.get_experiment_containers(simple=True)
cre_lines = set([c['cre_line'] for c in containers])
return sorted(list(cre_lines))
def get_all_reporter_lines(self):
""" Return a list of all reporter lines in the data set. """
containers = self.get_experiment_containers(simple=True)
reporter_lines = set([c['reporter_line'] for c in containers])
return sorted(list(reporter_lines))
def get_all_imaging_depths(self):
""" Return a list of all imaging depths in the data set. """
containers = self.get_experiment_containers(simple=True)
imaging_depths = set([c['imaging_depth'] for c in containers])
return sorted(list(imaging_depths))
def get_all_session_types(self):
""" Return a list of all stimulus sessions in the data set. """
exps = self.get_ophys_experiments(simple=False)
names = set([exp['stimulus_name'] for exp in exps])
return sorted(list(names))
def get_all_stimuli(self):
""" Return a list of all stimuli in the data set. """
return sorted(list(stim_info.all_stimuli()))
def get_experiment_containers(self,
file_name=None,
ids=None,
targeted_structures=None,
imaging_depths=None,
cre_lines=None,
reporter_lines=None,
transgenic_lines=None,
include_failed=False,
simple=True):
""" Get a list of experiment containers matching certain criteria.
Parameters
----------
file_name: string
File name to save/read the experiment containers. If file_name is None,
the file_name will be pulled out of the manifest. If caching
is disabled, no file will be saved. Default is None.
ids: list
List of experiment container ids.
targeted_structures: list
List of structure acronyms. Must be in the list returned by
BrainObservatoryCache.get_all_targeted_structures().
imaging_depths: list
List of imaging depths. Must be in the list returned by
BrainObservatoryCache.get_all_imaging_depths().
cre_lines: list
List of cre lines. Must be in the list returned by
BrainObservatoryCache.get_all_cre_lines().
reporter_lines: list
List of reporter lines. Must be in the list returned by
BrainObservatoryCache.get_all_reporter_lines().
transgenic_lines: list
List of transgenic lines. Must be in the list returned by
BrainObservatoryCache.get_all_cre_lines() or.
BrainObservatoryCache.get_all_reporter_lines().
include_failed: boolean
Whether or not to include failed experiment containers.
simple: boolean
Whether or not to simplify the dictionary properties returned by this method
to a more concise subset.
Returns
-------
list of dictionaries
"""
_assert_not_string(targeted_structures, "targeted_structures")
_assert_not_string(cre_lines, "cre_lines")
_assert_not_string(reporter_lines, "reporter_lines")
_assert_not_string(transgenic_lines, "transgenic_lines")
file_name = self.get_cache_path(file_name,
self.EXPERIMENT_CONTAINERS_KEY)
containers = self.api.get_experiment_containers(path=file_name,
strategy='lazy',
**Cache.cache_json())
containers = self.api.filter_experiment_containers(
containers,
ids=ids,
targeted_structures=targeted_structures,
imaging_depths=imaging_depths,
cre_lines=cre_lines,
reporter_lines=reporter_lines,
transgenic_lines=transgenic_lines,
include_failed=include_failed,
simple=simple)
return containers
def get_ophys_experiment_stimuli(self, experiment_id):
""" For a single experiment, return the list of stimuli present in that experiment. """
exps = self.get_ophys_experiments(ids=[experiment_id])
if len(exps) == 0:
return None
return stim_info.stimuli_in_session(exps[0]['session_type'])
def get_ophys_experiments(self,
file_name=None,
ids=None,
experiment_container_ids=None,
targeted_structures=None,
imaging_depths=None,
cre_lines=None,
reporter_lines=None,
transgenic_lines=None,
stimuli=None,
session_types=None,
cell_specimen_ids=None,
include_failed=False,
require_eye_tracking=False,
simple=True):
""" Get a list of ophys experiments matching certain criteria.
Parameters
----------
file_name: string
File name to save/read the ophys experiments. If file_name is None,
the file_name will be pulled out of the manifest. If caching
is disabled, no file will be saved. Default is None.
ids: list
List of ophys experiment ids.
experiment_container_ids: list
List of experiment container ids.
targeted_structures: list
List of structure acronyms. Must be in the list returned by
BrainObservatoryCache.get_all_targeted_structures().
imaging_depths: list
List of imaging depths. Must be in the list returned by
BrainObservatoryCache.get_all_imaging_depths().
cre_lines: list
List of cre lines. Must be in the list returned by
BrainObservatoryCache.get_all_cre_lines().
reporter_lines: list
List of reporter lines. Must be in the list returned by
BrainObservatoryCache.get_all_reporter_lines().
transgenic_lines: list
List of transgenic lines. Must be in the list returned by
BrainObservatoryCache.get_all_cre_lines() or.
BrainObservatoryCache.get_all_reporter_lines().
stimuli: list
List of stimulus names. Must be in the list returned by
BrainObservatoryCache.get_all_stimuli().
session_types: list
List of stimulus session type names. Must be in the list returned by
BrainObservatoryCache.get_all_session_types().
cell_specimen_ids: list
Only include experiments that contain cells with these ids.
include_failed: boolean
Whether or not to include experiments from failed experiment containers.
simple: boolean
Whether or not to simplify the dictionary properties returned by this method
to a more concise subset.
require_eye_tracking: boolean
If True, only return experiments that have eye tracking results. Default: False.
Returns
-------
list of dictionaries
"""
_assert_not_string(targeted_structures, "targeted_structures")
_assert_not_string(cre_lines, "cre_lines")
_assert_not_string(reporter_lines, "reporter_lines")
_assert_not_string(transgenic_lines, "transgenic_lines")
_assert_not_string(stimuli, "stimuli")
_assert_not_string(session_types, "session_types")
file_name = self.get_cache_path(file_name, self.EXPERIMENTS_KEY)
exps = self.api.get_ophys_experiments(path=file_name,
strategy='lazy',
**Cache.cache_json())
# NOTE: Ugly hack to update the 'fail_eye_tracking' field
# which is using True/False values for the previous eye mapping
# implementation. This will also need to be fixed in warehouse.
# ----- Start of ugly hack -----
response = self.api.template_query('brain_observatory_queries',
'all_eye_mapping_files')
session_ids_with_eye_tracking: set = {
entry['attachable_id']
for entry in response if entry['attachable_type'] == "OphysSession"
}
for indx, exp in enumerate(exps):
try:
ophys_session_id = ophys_experiment_session_id_map[exp['id']]
if ophys_session_id in session_ids_with_eye_tracking:
exps[indx]['fail_eye_tracking'] = False
else:
exps[indx]['fail_eye_tracking'] = True
except KeyError:
exps[indx]['fail_eye_tracking'] = True
# ----- End of ugly hack -----
if cell_specimen_ids is not None:
cells = self.get_cell_specimens(ids=cell_specimen_ids)
cell_container_ids = set(
[cell['experiment_container_id'] for cell in cells])
if experiment_container_ids is not None:
experiment_container_ids = list(
set(experiment_container_ids) - cell_container_ids)
else:
experiment_container_ids = list(cell_container_ids)
exps = self.api.filter_ophys_experiments(
exps,
ids=ids,
experiment_container_ids=experiment_container_ids,
targeted_structures=targeted_structures,
imaging_depths=imaging_depths,
cre_lines=cre_lines,
reporter_lines=reporter_lines,
transgenic_lines=transgenic_lines,
stimuli=stimuli,
session_types=session_types,
include_failed=include_failed,
require_eye_tracking=require_eye_tracking,
simple=simple)
return exps
def _get_stimulus_mappings(self, file_name=None):
""" Returns a mapping of which metrics are related to which stimuli. Internal use only. """
file_name = self.get_cache_path(file_name, self.STIMULUS_MAPPINGS_KEY)
mappings = self.api.get_stimulus_mappings(path=file_name,
strategy='lazy',
**Cache.cache_json())
return mappings
def get_cell_specimens(self,
file_name=None,
ids=None,
experiment_container_ids=None,
include_failed=False,
simple=True,
filters=None):
""" Return cell specimens that have certain properies.
Parameters
----------
file_name: string
File name to save/read the cell specimens. If file_name is None,
the file_name will be pulled out of the manifest. If caching
is disabled, no file will be saved. Default is None.
ids: list
List of cell specimen ids.
experiment_container_ids: list
List of experiment container ids.
include_failed: bool
Whether to include cells from failed experiment containers
simple: boolean
Whether or not to simplify the dictionary properties returned by this method
to a more concise subset.
filters: list of dicts
List of filter dictionaries. The Allen Brain Observatory web site can
generate filters in this format to reproduce a filtered set of cells
found there. To see what these look like, visit
http://observatory.brain-map.org/visualcoding, perform a cell search
and apply some filters (e.g. find cells in a particular area), then
click the "view these cells in the AllenSDK" link on the bottom-left
of the search results page. This will take you to a page that contains
a code sample you can use to apply those same filters via this argument.
For more detail on the filter syntax, see BrainObservatoryApi.dataframe_query.
Returns
-------
list of dictionaries
"""
file_name = self.get_cache_path(file_name, self.CELL_SPECIMENS_KEY)
cell_specimens = self.api.get_cell_metrics(
path=file_name,
strategy='lazy',
pre=lambda x: [y for y in x],
**Cache.cache_json())
cell_specimens = self.api.filter_cell_specimens(
cell_specimens,
ids=ids,
experiment_container_ids=experiment_container_ids,
include_failed=include_failed,
filters=filters)
# drop the thumbnail columns
if simple:
mappings = self._get_stimulus_mappings()
thumbnails = [
m['item'] for m in mappings
if m['item_type'] == 'T' and m['level'] == 'R'
]
for cs in cell_specimens:
for t in thumbnails:
del cs[t]
return cell_specimens
def get_nwb_filepath(self, ophys_experiment_id=None):
cache_nwb_filepath = self.get_cache_path(None,
self.EXPERIMENT_DATA_KEY,
ophys_experiment_id)
if os.path.exists(cache_nwb_filepath):
return cache_nwb_filepath
else:
return None
def get_ophys_experiment_data(self, ophys_experiment_id, file_name=None):
""" Download the NWB file for an ophys_experiment (if it hasn't already been
downloaded) and return a data accessor object.
Parameters
----------
file_name: string
File name to save/read the data set. If file_name is None,
the file_name will be pulled out of the manifest. If caching
is disabled, no file will be saved. Default is None.
ophys_experiment_id: integer
id of the ophys_experiment to retrieve
Returns
-------
BrainObservatoryNwbDataSet
"""
file_name = self.get_cache_path(file_name, self.EXPERIMENT_DATA_KEY,
ophys_experiment_id)
self.api.save_ophys_experiment_data(ophys_experiment_id,
file_name,
strategy='lazy')
return BrainObservatoryNwbDataSet(file_name)
def get_ophys_experiment_analysis(self,
ophys_experiment_id,
stimulus_type,
file_name=None):
""" Download the h5 analysis file for a stimulus set, for a particular ophys_experiment
(if it hasn't already been downloaded) and return a data accessor object.
Parameters
----------
file_name: string
File name to save/read the data set. If file_name is None,
the file_name will be pulled out of the manifest. If caching
is disabled, no file will be saved. Default is None.
ophys_experiment_id: int
id of the ophys_experiment to retrieve
stimulus_name: str
stimulus type; should be an element of self.list_stimuli()
Returns
-------
BrainObservatoryNwbDataSet
"""
data_set = self.get_ophys_experiment_data(ophys_experiment_id,
file_name=None)
session_type = data_set.get_session_type()
if not stimulus_type in stim_info.SESSION_STIMULUS_MAP[session_type]:
raise RuntimeError(
'Stimulus %s not available session type: %s' %
(stimulus_type, stim_info.SESSION_STIMULUS_MAP[stimulus_type]))
# Use manifest to figure out where to cache the file:
file_name = self.get_cache_path(file_name, self.ANALYSIS_DATA_KEY,
ophys_experiment_id, session_type)
# Cache the analsis file from an RMA query:
self.api.save_ophys_experiment_analysis_data(ophys_experiment_id,
file_name,
strategy='lazy')
# Get the analysis class from ANALYSIS_CLASS_DICT, and build from the static method:
if stimulus_type in stim_info.LOCALLY_SPARSE_NOISE_STIMULUS_TYPES + stim_info.NATURAL_MOVIE_STIMULUS_TYPES:
return ANALYSIS_CLASS_DICT[stimulus_type].from_analysis_file(
data_set, file_name, stimulus_type)
else:
return ANALYSIS_CLASS_DICT[stimulus_type].from_analysis_file(
data_set, file_name)
def get_ophys_experiment_events(self, ophys_experiment_id, file_name=None):
""" Download the npz events file for an ophys_experiment if it hasn't
already been downloaded and return the events array.
Parameters
----------
file_name: string
File name to save/read the data set. If file_name is None,
the file_name will be pulled out of the manifest. If caching
is disabled, no file will be saved. Default is None.
ophys_experiment_id: int
id of the ophys_experiment to retrieve events for
Returns
-------
events: numpy.ndarray
[N_cells,N_times] array of events.
"""
file_name = self.get_cache_path(file_name, self.EVENTS_DATA_KEY,
ophys_experiment_id)
self.api.save_ophys_experiment_event_data(ophys_experiment_id,
file_name,
strategy='lazy')
return np.load(file_name, allow_pickle=False)["ev"]
def get_ophys_pupil_data(self,
ophys_experiment_id: int,
file_name: str = None,
suppress_pupil_data: bool = True) -> pd.DataFrame:
"""Download the h5 eye gaze mapping file for an ophys_experiment if
it hasn't already been downloaded and return it as a pandas.DataFrame.
Parameters
----------
file_name: string
File name to save/read the data set. If file_name is None,
the file_name will be pulled out of the manifest. If caching
is disabled, no file will be saved. Default is None.
ophys_experiment_id: int
id of the ophys_experiment to retrieve pupil data for.
suppress_pupil_data: bool
Whether or not to suppress pupil data from dataset.
Default is True.
Returns
-------
pd.DataFrame
If 'suppress_eye_gaze_data' is set to 'False':
Contains raw/filtered columns for gaze mapping:
*_eye_area
*_pupil_area
*_screen_coordinates_x_cm
*_screen_coordinates_y_cm
*_screen_coordinates_spherical_x_deg
*_screen_coorindates_spherical_y_deg
Otherwise:
An empty pandas DataFrame
"""
if suppress_pupil_data:
print(
"This pupil data is obtained using a new eye "
"tracking algorithm and is in the process of being validated. "
"If you would like to view the data anyways, "
"please set the 'suppress_pupil_data' parameter to 'False'.")
return pd.DataFrame()
# NOTE: This is a really ugly hack to get around the fact that warehouse does
# not have Ophys session ids associated with experiment ids. This should be
# removed when warehouse session ids have associations with experiment ids.
# ----- Start of ugly hack -----
try:
ophys_session_id = ophys_experiment_session_id_map[
ophys_experiment_id]
except KeyError:
raise RuntimeError(
f"Experiment id '{ophys_experiment_id}' has no associated session!"
)
# ----- End of ugly hack -----
file_name = self.get_cache_path(file_name, self.EYE_GAZE_DATA_KEY,
ophys_session_id)
if not file_name:
raise RuntimeError("Could not obtain a file_name for pupil data "
f"with experiment id: {ophys_experiment_id} "
f"(session id: {ophys_session_id})")
# NOTE: `save_ophys_experiment_eye_gaze_data` will also need to be
# updated to remove ophy_session_id param when ugly hack is removed.
self.api.save_ophys_experiment_eye_gaze_data(ophys_experiment_id,
ophys_session_id,
file_name,
strategy='lazy')
gaze_mapping_data = read_eye_gaze_mappings(Path(file_name))
return create_eye_gaze_mapping_dataframe(gaze_mapping_data)
def build_manifest(self, file_name):
"""
Construct a manifest for this Cache class and save it in a file.
Parameters
----------
file_name: string
File location to save the manifest.
"""
mb = ManifestBuilder()
mb.set_version(self.MANIFEST_VERSION)
mb.add_path('BASEDIR', '.')
mb.add_path(self.EXPERIMENT_CONTAINERS_KEY,
'experiment_containers.json',
typename='file',
parent_key='BASEDIR')
mb.add_path(self.EXPERIMENTS_KEY,
'ophys_experiments.json',
typename='file',
parent_key='BASEDIR')
mb.add_path(self.EXPERIMENT_DATA_KEY,
'ophys_experiment_data/%d.nwb',
typename='file',
parent_key='BASEDIR')
mb.add_path(self.ANALYSIS_DATA_KEY,
'ophys_experiment_analysis/%d_%s_analysis.h5',
typename='file',
parent_key='BASEDIR')
mb.add_path(self.EVENTS_DATA_KEY,
'ophys_experiment_events/%d_events.npz',
typename='file',
parent_key='BASEDIR')
mb.add_path(self.CELL_SPECIMENS_KEY,
'cell_specimens.json',
typename='file',
parent_key='BASEDIR')
mb.add_path(self.STIMULUS_MAPPINGS_KEY,
'stimulus_mappings.json',
typename='file',
parent_key='BASEDIR')
mb.add_path(
self.EYE_GAZE_DATA_KEY,
'ophys_eye_gaze_mapping/%d_eyetracking_dlc_to_screen_mapping.h5',
typename='file',
parent_key='BASEDIR')
mb.write_json_file(file_name)
def make_bo_api():
from allensdk.api.queries.brain_observatory_api import BrainObservatoryApi
endpoint = os.environ['TEST_API_ENDPOINT'] if 'TEST_API_ENDPOINT' in os.environ else 'http://twarehouse-backup'
return BrainObservatoryApi(endpoint)