class CellTypesCache(Cache):
"""
Cache class for storing and accessing data from the Cell Types Database.
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: CellTypesApi instance
The object used for making API queries related to the Cell Types Database
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_ephys_data(file_name='file.nwb')).
manifest_file: string
File name of the manifest to be read. Default is "cell_types_manifest.json".
"""
# manifest keys
CELLS_KEY = 'CELLS'
EPHYS_FEATURES_KEY = 'EPHYS_FEATURES'
MORPHOLOGY_FEATURES_KEY = 'MORPHOLOGY_FEATURES'
EPHYS_DATA_KEY = 'EPHYS_DATA'
EPHYS_SWEEPS_KEY = 'EPHYS_SWEEPS'
RECONSTRUCTION_KEY = 'RECONSTRUCTION'
MARKER_KEY = 'MARKER'
MANIFEST_VERSION = "1.1"
def __init__(self, cache=True, manifest_file=None, base_uri=None):
if manifest_file is None:
manifest_file = get_default_manifest_file('cell_types')
super(CellTypesCache, self).__init__(
manifest=manifest_file, cache=cache, version=self.MANIFEST_VERSION)
self.api = CellTypesApi(base_uri=base_uri)
def get_cells(self, file_name=None,
require_morphology=False,
require_reconstruction=False,
reporter_status=None,
species=None,
simple=True):
"""
Download metadata for all cells in the database and optionally return a
subset filtered by whether or not they have a morphology or reconstruction.
Parameters
----------
file_name: string
File name to save/read the cell metadata as JSON. 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.
require_morphology: boolean
Filter out cells that have no morphological images.
require_reconstruction: boolean
Filter out cells that have no morphological reconstructions.
reporter_status: list
Filter for cells that have one or more cell reporter statuses.
species: list
Filter for cells that belong to one or more species. If None, return all.
Must be one of [ CellTypesApi.MOUSE, CellTypesApi.HUMAN ].
"""
file_name = self.get_cache_path(file_name, self.CELLS_KEY)
cells = self.api.list_cells_api(path=file_name,
strategy='lazy',
**Cache.cache_json())
if isinstance(reporter_status, string_types):
reporter_status = [reporter_status]
# filter the cells on the way out
cells = self.api.filter_cells_api(cells,
require_morphology,
require_reconstruction,
reporter_status,
species,
simple)
return cells
def get_ephys_sweeps(self, specimen_id, file_name=None):
"""
Download sweep metadata for a single cell specimen.
Parameters
----------
specimen_id: int
ID of a cell.
"""
file_name = self.get_cache_path(
file_name, self.EPHYS_SWEEPS_KEY, specimen_id)
sweeps = self.api.get_ephys_sweeps(specimen_id,
strategy='lazy',
path=file_name,
**Cache.cache_json())
return sweeps
def get_ephys_features(self, dataframe=False, file_name=None):
"""
Download electrophysiology features for all cells in the database.
Parameters
----------
file_name: string
File name to save/read the ephys features metadata as CSV.
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.
dataframe: boolean
Return the output as a Pandas DataFrame. If False, return
a list of dictionaries.
"""
file_name = self.get_cache_path(file_name, self.EPHYS_FEATURES_KEY)
if self.cache:
if dataframe:
warnings.warn("dataframe argument is deprecated.")
args = Cache.cache_csv_dataframe()
else:
args = Cache.cache_csv_json()
args['strategy'] = 'lazy'
else:
args = Cache.nocache_json()
features_df = self.api.get_ephys_features(path=file_name,
**args)
return features_df
def get_morphology_features(self, dataframe=False, file_name=None):
"""
Download morphology features for all cells with reconstructions in the database.
Parameters
----------
file_name: string
File name to save/read the ephys features metadata as CSV.
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.
dataframe: boolean
Return the output as a Pandas DataFrame. If False, return
a list of dictionaries.
"""
file_name = self.get_cache_path(
file_name, self.MORPHOLOGY_FEATURES_KEY)
if self.cache:
if dataframe:
warnings.warn("dataframe argument is deprecated.")
args = Cache.cache_csv_dataframe()
else:
args = Cache.cache_csv_json()
else:
args = Cache.nocache_json()
args['strategy'] = 'lazy'
args['path'] = file_name
return self.api.get_morphology_features(**args)
def get_all_features(self, dataframe=False, require_reconstruction=True):
"""
Download morphology and electrophysiology features for all cells and merge them
into a single table.
Parameters
----------
dataframe: boolean
Return the output as a Pandas DataFrame. If False, return
a list of dictionaries.
require_reconstruction: boolean
Only return ephys and morphology features for cells that have
reconstructions. Default True.
"""
ephys_features = pd.DataFrame(self.get_ephys_features())
morphology_features = pd.DataFrame(self.get_morphology_features())
how = 'inner' if require_reconstruction else 'outer'
all_features = ephys_features.merge(morphology_features,
how=how,
on='specimen_id')
if dataframe:
warnings.warn("dataframe argument is deprecated.")
return all_features
else:
return all_features.to_dict('records')
def get_ephys_data(self, specimen_id, file_name=None):
"""
Download electrophysiology traces for a single cell in the database.
Parameters
----------
specimen_id: int
The ID of a cell specimen to download.
file_name: string
File name to save/read the ephys features metadata as CSV.
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.
Returns
-------
NwbDataSet
A class instance with helper methods for retrieving stimulus
and response traces out of an NWB file.
"""
file_name = self.get_cache_path(
file_name, self.EPHYS_DATA_KEY, specimen_id)
self.api.save_ephys_data(specimen_id, file_name, strategy='lazy')
return NwbDataSet(file_name)
def get_reconstruction(self, specimen_id, file_name=None):
"""
Download and open a reconstruction for a single cell in the database.
Parameters
----------
specimen_id: int
The ID of a cell specimen to download.
file_name: string
File name to save/read the reconstruction SWC.
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.
Returns
-------
Morphology
A class instance with methods for accessing morphology compartments.
"""
file_name = self.get_cache_path(
file_name, self.RECONSTRUCTION_KEY, specimen_id)
if file_name is None:
raise Exception(
"Please enable caching (CellTypes.cache = True) or specify a save_file_name.")
if not os.path.exists(file_name):
self.api.save_reconstruction(specimen_id, file_name)
return swc.read_swc(file_name)
def get_reconstruction_markers(self, specimen_id, file_name=None):
"""
Download and open a reconstruction marker file for a single cell in the database.
Parameters
----------
specimen_id: int
The ID of a cell specimen to download.
file_name: string
File name to save/read the reconstruction marker.
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.
Returns
-------
Morphology
A class instance with methods for accessing morphology compartments.
"""
file_name = self.get_cache_path(
file_name, self.MARKER_KEY, specimen_id)
if file_name is None:
raise Exception(
"Please enable caching (CellTypes.cache = True) or specify a save_file_name.")
if not os.path.exists(file_name):
try:
self.api.save_reconstruction_markers(specimen_id, file_name)
except LookupError as e:
logging.warning(e.args)
return []
return swc.read_marker_file(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.CELLS_KEY, 'cells.json',
typename='file', parent_key='BASEDIR')
mb.add_path(self.EPHYS_DATA_KEY, 'specimen_%d/ephys.nwb',
typename='file', parent_key='BASEDIR')
mb.add_path(self.EPHYS_FEATURES_KEY, 'ephys_features.csv',
typename='file', parent_key='BASEDIR')
mb.add_path(self.MORPHOLOGY_FEATURES_KEY, 'morphology_features.csv',
typename='file', parent_key='BASEDIR')
mb.add_path(self.RECONSTRUCTION_KEY, 'specimen_%d/reconstruction.swc',
typename='file', parent_key='BASEDIR')
mb.add_path(self.MARKER_KEY, 'specimen_%d/reconstruction.marker',
typename='file', parent_key='BASEDIR')
mb.add_path(self.EPHYS_SWEEPS_KEY, 'specimen_%d/ephys_sweeps.json',
typename='file', parent_key='BASEDIR')
mb.write_json_file(file_name)
cwriter = csv.writer( csvfile, delimiter=',', quotechar='"' )
header = ['cell_specimen_id', 'mouse_line', 'structure_acronym', 'graph_order', 'normalized_depth', 'ccf_soma_x', 'ccf_soma_y', 'ccf_soma_z']
for r in radii :
header.append( str(r) )
cwriter.writerow( header )
for idx, cell in enumerate(cells) :
#if cell['id'] != 397351623:
# continue
print '%d: %d' % (idx,cell['id'])
fname = os.path.join( 'swc', '%d_morphology.swc' % cell['id'] )
if download_file :
ct.save_reconstruction( cell['id'], fname )
morphology = swc.read_swc(fname)
compartment_list = morphology.compartment_list
root = compartment_list[0]
if root['type'] != 1 :
print 'first node is not soma'
continue
sholl = np.zeros( radii.shape )
for n in morphology.compartment_list :
node_soma_diff = np.array([root['x'],root['y'],root['z']]) - np.array([n['x'],n['y'], n['z']])
node_soma_diff_norm = np.linalg.norm( node_soma_diff )
class CellTypesCache(Cache):
"""
Cache class for storing and accessing data from the Cell Types Database.
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: CellTypesApi instance
The object used for making API queries related to the Cell Types Database
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_ephys_data(file_name='file.nwb')).
manifest_file: string
File name of the manifest to be read. Default is "cell_types_manifest.json".
"""
# manifest keys
CELLS_KEY = 'CELLS'
EPHYS_FEATURES_KEY = 'EPHYS_FEATURES'
MORPHOLOGY_FEATURES_KEY = 'MORPHOLOGY_FEATURES'
EPHYS_DATA_KEY = 'EPHYS_DATA'
EPHYS_SWEEPS_KEY = 'EPHYS_SWEEPS'
RECONSTRUCTION_KEY = 'RECONSTRUCTION'
MARKER_KEY = 'MARKER'
MANIFEST_VERSION = "1.1"
def __init__(self, cache=True, manifest_file=None, base_uri=None):
if manifest_file is None:
manifest_file = get_default_manifest_file('cell_types')
super(CellTypesCache, self).__init__(manifest=manifest_file,
cache=cache,
version=self.MANIFEST_VERSION)
self.api = CellTypesApi(base_uri=base_uri)
def get_cells(self,
file_name=None,
require_morphology=False,
require_reconstruction=False,
reporter_status=None,
species=None,
simple=True):
"""
Download metadata for all cells in the database and optionally return a
subset filtered by whether or not they have a morphology or reconstruction.
Parameters
----------
file_name: string
File name to save/read the cell metadata as JSON. 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.
require_morphology: boolean
Filter out cells that have no morphological images.
require_reconstruction: boolean
Filter out cells that have no morphological reconstructions.
reporter_status: list
Filter for cells that have one or more cell reporter statuses.
species: list
Filter for cells that belong to one or more species. If None, return all.
Must be one of [ CellTypesApi.MOUSE, CellTypesApi.HUMAN ].
"""
file_name = self.get_cache_path(file_name, self.CELLS_KEY)
cells = self.api.list_cells_api(path=file_name,
strategy='lazy',
**Cache.cache_json())
if isinstance(reporter_status, string_types):
reporter_status = [reporter_status]
# filter the cells on the way out
cells = self.api.filter_cells_api(cells, require_morphology,
require_reconstruction,
reporter_status, species, simple)
return cells
def get_ephys_sweeps(self, specimen_id, file_name=None):
"""
Download sweep metadata for a single cell specimen.
Parameters
----------
specimen_id: int
ID of a cell.
"""
file_name = self.get_cache_path(file_name, self.EPHYS_SWEEPS_KEY,
specimen_id)
sweeps = self.api.get_ephys_sweeps(specimen_id,
strategy='lazy',
path=file_name,
**Cache.cache_json())
return sweeps
def get_ephys_features(self, dataframe=False, file_name=None):
"""
Download electrophysiology features for all cells in the database.
Parameters
----------
file_name: string
File name to save/read the ephys features metadata as CSV.
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.
dataframe: boolean
Return the output as a Pandas DataFrame. If False, return
a list of dictionaries.
"""
file_name = self.get_cache_path(file_name, self.EPHYS_FEATURES_KEY)
if self.cache:
if dataframe:
warnings.warn("dataframe argument is deprecated.")
args = Cache.cache_csv_dataframe()
else:
args = Cache.cache_csv_json()
args['strategy'] = 'lazy'
else:
args = Cache.nocache_json()
features_df = self.api.get_ephys_features(path=file_name, **args)
return features_df
def get_morphology_features(self, dataframe=False, file_name=None):
"""
Download morphology features for all cells with reconstructions in the database.
Parameters
----------
file_name: string
File name to save/read the ephys features metadata as CSV.
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.
dataframe: boolean
Return the output as a Pandas DataFrame. If False, return
a list of dictionaries.
"""
file_name = self.get_cache_path(file_name,
self.MORPHOLOGY_FEATURES_KEY)
if self.cache:
if dataframe:
warnings.warn("dataframe argument is deprecated.")
args = Cache.cache_csv_dataframe()
else:
args = Cache.cache_csv_json()
else:
args = Cache.nocache_json()
args['strategy'] = 'lazy'
args['path'] = file_name
return self.api.get_morphology_features(**args)
def get_all_features(self, dataframe=False, require_reconstruction=True):
"""
Download morphology and electrophysiology features for all cells and merge them
into a single table.
Parameters
----------
dataframe: boolean
Return the output as a Pandas DataFrame. If False, return
a list of dictionaries.
require_reconstruction: boolean
Only return ephys and morphology features for cells that have
reconstructions. Default True.
"""
ephys_features = pd.DataFrame(self.get_ephys_features())
morphology_features = pd.DataFrame(self.get_morphology_features())
how = 'inner' if require_reconstruction else 'outer'
all_features = ephys_features.merge(morphology_features,
how=how,
on='specimen_id')
if dataframe:
warnings.warn("dataframe argument is deprecated.")
return all_features
else:
return all_features.to_dict('records')
def get_ephys_data(self, specimen_id, file_name=None):
"""
Download electrophysiology traces for a single cell in the database.
Parameters
----------
specimen_id: int
The ID of a cell specimen to download.
file_name: string
File name to save/read the ephys features metadata as CSV.
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.
Returns
-------
NwbDataSet
A class instance with helper methods for retrieving stimulus
and response traces out of an NWB file.
"""
file_name = self.get_cache_path(file_name, self.EPHYS_DATA_KEY,
specimen_id)
self.api.save_ephys_data(specimen_id, file_name, strategy='lazy')
return NwbDataSet(file_name)
def get_reconstruction(self, specimen_id, file_name=None):
"""
Download and open a reconstruction for a single cell in the database.
Parameters
----------
specimen_id: int
The ID of a cell specimen to download.
file_name: string
File name to save/read the reconstruction SWC.
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.
Returns
-------
Morphology
A class instance with methods for accessing morphology compartments.
"""
file_name = self.get_cache_path(file_name, self.RECONSTRUCTION_KEY,
specimen_id)
if file_name is None:
raise Exception(
"Please enable caching (CellTypes.cache = True) or specify a save_file_name."
)
if not os.path.exists(file_name):
self.api.save_reconstruction(specimen_id, file_name)
return swc.read_swc(file_name)
def get_reconstruction_markers(self, specimen_id, file_name=None):
"""
Download and open a reconstruction marker file for a single cell in the database.
Parameters
----------
specimen_id: int
The ID of a cell specimen to download.
file_name: string
File name to save/read the reconstruction marker.
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.
Returns
-------
Morphology
A class instance with methods for accessing morphology compartments.
"""
file_name = self.get_cache_path(file_name, self.MARKER_KEY,
specimen_id)
if file_name is None:
raise Exception(
"Please enable caching (CellTypes.cache = True) or specify a save_file_name."
)
if not os.path.exists(file_name):
try:
self.api.save_reconstruction_markers(specimen_id, file_name)
except LookupError as e:
logging.warning(e.args)
return []
return swc.read_marker_file(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.CELLS_KEY,
'cells.json',
typename='file',
parent_key='BASEDIR')
mb.add_path(self.EPHYS_DATA_KEY,
'specimen_%d/ephys.nwb',
typename='file',
parent_key='BASEDIR')
mb.add_path(self.EPHYS_FEATURES_KEY,
'ephys_features.csv',
typename='file',
parent_key='BASEDIR')
mb.add_path(self.MORPHOLOGY_FEATURES_KEY,
'morphology_features.csv',
typename='file',
parent_key='BASEDIR')
mb.add_path(self.RECONSTRUCTION_KEY,
'specimen_%d/reconstruction.swc',
typename='file',
parent_key='BASEDIR')
mb.add_path(self.MARKER_KEY,
'specimen_%d/reconstruction.marker',
typename='file',
parent_key='BASEDIR')
mb.add_path(self.EPHYS_SWEEPS_KEY,
'specimen_%d/ephys_sweeps.json',
typename='file',
parent_key='BASEDIR')
mb.write_json_file(file_name)
class CellTypesCache(Cache):
'''
Cache class for storing and accessing data from the Cell Types Database.
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: CellTypesApi instance
The object used for making API queries related to the Cell Types Database
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_ephys_data(file_name='file.nwb')).
manifest_file: string
File name of the manifest to be read. Default is "manifest.json".
'''
CELLS_KEY = 'CELLS'
EPHYS_FEATURES_KEY = 'EPHYS_FEATURES'
MORPHOLOGY_FEATURES_KEY = 'MORPHOLOGY_FEATURES'
EPHYS_DATA_KEY = 'EPHYS_DATA'
EPHYS_SWEEPS_KEY = 'EPHYS_SWEEPS'
RECONSTRUCTION_KEY = 'RECONSTRUCTION'
def __init__(self, cache=True, manifest_file='manifest.json'):
super(CellTypesCache, self).__init__(manifest=manifest_file, cache=cache)
self.api = CellTypesApi()
def get_cells(self, file_name=None, require_morphology=False, require_reconstruction=False):
'''
Download metadata for all cells in the database and optionally return a
subset filtered by whether or not they have a morphology or reconstruction.
Parameters
----------
file_name: string
File name to save/read the cell metadata as JSON. 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.
require_morphology: boolean
Filter out cells that have no morphological images.
require_reconstruction: boolean
Filter out cells that have no morphological reconstructions.
'''
file_name = self.get_cache_path(file_name, self.CELLS_KEY)
if os.path.exists(file_name):
cells = json_utilities.read(file_name)
else:
cells = self.api.list_cells(False, False)
if self.cache:
json_utilities.write(file_name, cells)
# filter the cells on the way out
return self.api.filter_cells(cells, require_morphology, require_reconstruction)
def get_ephys_sweeps(self, specimen_id, file_name=None):
'''
Download sweep metadata for a single cell specimen.
Parameters
----------
specimen_id: int
ID of a cell.
'''
file_name = self.get_cache_path(file_name, self.EPHYS_SWEEPS_KEY, specimen_id)
if os.path.exists(file_name):
sweeps = json_utilities.read(file_name)
else:
sweeps = self.api.get_ephys_sweeps(specimen_id)
if self.cache:
json_utilities.write(file_name, sweeps)
return sweeps
def get_ephys_features(self, dataframe=False, file_name=None):
'''
Download electrophysiology features for all cells in the database.
Parameters
----------
file_name: string
File name to save/read the ephys features metadata as CSV.
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.
dataframe: boolean
Return the output as a Pandas DataFrame. If False, return
a list of dictionaries.
'''
file_name = self.get_cache_path(file_name, self.EPHYS_FEATURES_KEY)
if os.path.exists(file_name):
features_df = pd.DataFrame.from_csv(file_name)
else:
features_df = self.api.get_ephys_features(dataframe=True)
if self.cache:
features_df.to_csv(file_name)
if dataframe:
return features_df
else:
return features_df.to_dict('records')
def get_morphology_features(self, dataframe=False, file_name=None):
'''
Download morphology features for all cells with reconstructions in the database.
Parameters
----------
file_name: string
File name to save/read the ephys features metadata as CSV.
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.
dataframe: boolean
Return the output as a Pandas DataFrame. If False, return
a list of dictionaries.
'''
file_name = self.get_cache_path(file_name, self.MORPHOLOGY_FEATURES_KEY)
if os.path.exists(file_name):
features_df = pd.DataFrame.from_csv(file_name)
else:
features_df = self.api.get_morphology_features(dataframe=True)
if self.cache:
features_df.to_csv(file_name)
if dataframe:
return features_df
else:
return features_df.to_dict('records')
def get_all_features(self, dataframe=False, require_reconstruction=True):
'''
Download morphology and electrophysiology features for all cells and merge them
into a single table.
Parameters
----------
dataframe: boolean
Return the output as a Pandas DataFrame. If False, return
a list of dictionaries.
require_reconstruction: boolean
Only return ephys and morphology features for cells that have
reconstructions. Default True.
'''
ephys_features = self.get_ephys_features(dataframe=True)
morphology_features = self.get_morphology_features(dataframe=True)
how = 'inner' if require_reconstruction else 'outer'
all_features = ephys_features.merge(morphology_features,
how=how,
on='specimen_id')
if dataframe:
return all_features
else:
return all_features.to_dict('records')
def get_ephys_data(self, specimen_id, file_name=None):
'''
Download electrophysiology traces for a single cell in the database.
Parameters
----------
specimen_id: int
The ID of a cell specimen to download.
file_name: string
File name to save/read the ephys features metadata as CSV.
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.
Returns
-------
NwbDataSet
A class instance with helper methods for retrieving stimulus
and response traces out of an NWB file.
'''
file_name = self.get_cache_path(file_name, self.EPHYS_DATA_KEY, specimen_id)
if not os.path.exists(file_name):
self.api.save_ephys_data(specimen_id, file_name)
return NwbDataSet(file_name)
def get_reconstruction(self, specimen_id, file_name=None):
'''
Download and open a reconstruction for a single cell in the database.
Parameters
----------
specimen_id: int
The ID of a cell specimen to download.
file_name: string
File name to save/read the ephys features metadata as CSV.
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.
Returns
-------
Morphology
A class instance with methods for accessing morphology compartments.
'''
file_name = self.get_cache_path(file_name, self.RECONSTRUCTION_KEY, specimen_id)
if file_name is None:
raise Exception("Please enable caching (CellTypes.cache = True) or specify a save_file_name.")
if not os.path.exists(file_name):
self.api.save_reconstruction(specimen_id, file_name)
return swc.read_swc(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.CELLS_KEY, 'cells.json', typename='file', parent_key='BASEDIR')
mb.add_path(self.EPHYS_DATA_KEY, 'specimen_%d/ephys.nwb', typename='file', parent_key='BASEDIR')
mb.add_path(self.EPHYS_FEATURES_KEY, 'ephys_features.csv', typename='file', parent_key='BASEDIR')
mb.add_path(self.MORPHOLOGY_FEATURES_KEY, 'morphology_features.csv', typename='file', parent_key='BASEDIR')
mb.add_path(self.RECONSTRUCTION_KEY, 'specimen_%d/reconstruction.swc', typename='file', parent_key='BASEDIR')
mb.add_path(self.EPHYS_SWEEPS_KEY, 'specimen_%d/ephys_sweeps.json', typename='file', parent_key='BASEDIR')
mb.write_json_file(file_name)
from allensdk.api.queries.cell_types_api import CellTypesApi ct = CellTypesApi() # a list of dictionaries containing metadata for cells with reconstructions cells = ct.list_cells(require_reconstruction=True) # download the electrophysiology data for one cell ct.save_ephys_data(cells[0]['id'], 'example.nwb') # download the reconstruction for the same cell ct.save_reconstruction(cells[0]['id'], 'example.swc')
'normalized_depth', 'ccf_soma_x', 'ccf_soma_y', 'ccf_soma_z'
]
for r in radii:
header.append(str(r))
cwriter.writerow(header)
for idx, cell in enumerate(cells):
#if cell['id'] != 397351623:
# continue
print '%d: %d' % (idx, cell['id'])
fname = os.path.join('swc', '%d_morphology.swc' % cell['id'])
if download_file:
ct.save_reconstruction(cell['id'], fname)
morphology = swc.read_swc(fname)
compartment_list = morphology.compartment_list
root = compartment_list[0]
if root['type'] != 1:
print 'first node is not soma'
continue
sholl = np.zeros(radii.shape)
for n in morphology.compartment_list:
node_soma_diff = np.array([root['x'], root['y'], root['z']
]) - np.array([n['x'], n['y'], n['z']])
# print some summary metadata for the cell
print('\n-----------------------------------------------\nCell name: %s' % cell_meta_dict[dataset_id]['name'])
print(' Cell ID: %i' % cell_meta_dict[dataset_id]['id'])
print(' Brain region: %s' % cell_meta_dict[dataset_id]['structure']['name'])
print(' Dendrite info: ')
for tag in cell_meta_dict[dataset_id]['specimen_tags']:
print(' %s'%tag['name'])
x = cell_meta_dict[dataset_id]['cell_soma_locations'][0]['x']
y = cell_meta_dict[dataset_id]['cell_soma_locations'][0]['y']
z = cell_meta_dict[dataset_id]['cell_soma_locations'][0]['z']
print(' Soma loc: (%s, %s, %s)'%(x,y,z))
#pp.pprint(cell_meta_dict[dataset_id])
morphology_file_name = '%d.swc' % dataset_id
ct.save_reconstruction(dataset_id, morphology_file_name)
# Requires: https://github.com/pgleeson/Cvapp-NeuroMorpho.org
command = 'java -cp ../../../Cvapp-NeuroMorpho.org/build/ cvapp.main %s -exportnml2'%morphology_file_name
print("Executing: %s"%command)
return_string = subprocess.check_output(command, cwd='.', shell=True)
nml2_file_name = '%d.cell.nml' % dataset_id
nml_doc.includes.append(IncludeType(nml2_file_name))
pop = Population(id="Pop_%i"%dataset_id, component=dataset_id, type="populationList")
net.populations.append(pop)
inst = Instance(id="0")
% cell_meta_dict[dataset_id]['name'])
print(' Cell ID: %i' % cell_meta_dict[dataset_id]['id'])
print(' Brain region: %s' %
cell_meta_dict[dataset_id]['structure']['name'])
print(' Dendrite info: ')
for tag in cell_meta_dict[dataset_id]['specimen_tags']:
print(' %s' % tag['name'])
x = cell_meta_dict[dataset_id]['cell_soma_locations'][0]['x']
y = cell_meta_dict[dataset_id]['cell_soma_locations'][0]['y']
z = cell_meta_dict[dataset_id]['cell_soma_locations'][0]['z']
print(' Soma loc: (%s, %s, %s)' % (x, y, z))
#pp.pprint(cell_meta_dict[dataset_id])
morphology_file_name = '%d.swc' % dataset_id
ct.save_reconstruction(dataset_id, morphology_file_name)
# Requires: https://github.com/pgleeson/Cvapp-NeuroMorpho.org
command = 'java -cp ../../../Cvapp-NeuroMorpho.org/build/ cvapp.main %s -exportnml2' % morphology_file_name
print("Executing: %s" % command)
return_string = subprocess.check_output(command,
cwd='.',
shell=True)
nml2_file_name = '%d.cell.nml' % dataset_id
nml_doc.includes.append(IncludeType(nml2_file_name))
pop = Population(id="Pop_%i" % dataset_id,
component=dataset_id,
type="populationList")
