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")