def __init__(self, archive_dir=None):
self.bp = BiophysicalApi('http://api.brain-map.org')
self.bp.cache_stimulus = True # change to False to not download the large stimulus NWB file
self.cta = CellTypesApi()
self.rma = RmaApi()
self.neuronal_model_download_endpoint = 'http://celltypes.brain-map.org/neuronal_model/download/'
self.template_names = {}
self.nwb_list = []
if archive_dir == None:
archive_dir = '.'
self.archive_dir = archive_dir
def GetAllenCells(neuronal_model_ids):
from allensdk.api.queries.biophysical_api import BiophysicalApi
bp = BiophysicalApi()
bp.cache_stimulus = False # change to True to download the large stimulus NWB file
for neuronal_model_id in neuronal_model_ids:
os.system('mkdir models/' + str(neuronal_model_id))
bp.cache_data(neuronal_model_id,
working_directory=str(neuronal_model_id))
os.system('cd ' + str(neuronal_model_id) +
'; nrnivmodl ./modfiles; cd ../../')
def prepareModelRun(model_filename, ephys_filename, swc_filename, sweeps,
sweeps_by_type):
bp = BiophysicalApi()
bp.create_manifest(fit_path=os.path.basename(model_filename),
model_type='Biophysical - all active',
stimulus_filename=os.path.basename(ephys_filename),
swc_morphology_path=os.path.basename(swc_filename),
sweeps=sweeps)
bp.manifest['runs'][0]['sweeps_by_type'] = sweeps_by_type
manifest_file = os.path.join(os.path.dirname(model_filename),
'manifest.json')
with open(manifest_file, 'w') as manifest_json:
json.dump(bp.manifest, manifest_json, indent=2)
return manifest_file
def getCells():
from allensdk.api.queries.biophysical_api import BiophysicalApi
bp = BiophysicalApi()
bp.cache_stimulus = True # change to False to not download the large stimulus NWB file
# # E2 cell (L2/3 Pyr) - https://senselab.med.yale.edu/modeldb/showmodel.cshtml?model=184161
neuronal_model_id = 472299294 # get this from the web site as above
bp.cache_data(neuronal_model_id, working_directory='E2full')
os.system('cd E2full; nrnivmodl ./modfiles; cd ..')
os.system('cp %s %s' % ('E2/cell_template.hoc', 'E2full/.'))
os.system('cp %s %s' % ('E2/cell_utils.py', 'E2full/.'))
# E4 cell (L4 Pyr) - https://senselab.med.yale.edu/modeldb/showmodel.cshtml?model=184142
neuronal_model_id = 329321704 # get this from the web site as above
bp.cache_data(neuronal_model_id, working_directory='E4')
os.system('cd E4; nrnivmodl ./modfiles; cd ..')
os.system('cp %s %s' % ('E2/cell_template.hoc', 'E4/.'))
os.system('cp %s %s' % ('E2/cell_utils.py', 'E4/.'))
# E5 cell (L5 Pyr) - https://senselab.med.yale.edu/modeldb/showmodel.cshtml?model=184159
neuronal_model_id = 471087975 # get this from the web site as above
bp.cache_data(neuronal_model_id, working_directory='E5')
os.system('cd E5; nrnivmodl ./modfiles; cd ..')
os.system('cp %s %s' % ('E2/cell_template.hoc', 'E5/.'))
os.system('cp %s %s' % ('E2/cell_utils.py', 'E5/.'))
# IF cell (L5 Parv) - https://senselab.med.yale.edu/modeldb/showmodel.cshtml?model=184152
neuronal_model_id = 471085845 # get this from the web site as above
bp.cache_data(neuronal_model_id, working_directory='IF')
os.system('cd IF; nrnivmodl ./modfiles; cd ..')
os.system('cp %s %s' % ('E2/cell_template.hoc', 'IF/.'))
os.system('cp %s %s' % ('E2/cell_utils.py', 'IF/.'))
# IL cell (L5 Sst) - https://senselab.med.yale.edu/modeldb/showmodel.cshtml?model=184163
neuronal_model_id = 472299363 # get this from the web site as above
bp.cache_data(neuronal_model_id, working_directory='IL')
os.system('cd IL; nrnivmodl ./modfiles; cd ..')
os.system('cp %s %s' % ('E2/cell_template.hoc', 'IL/.'))
os.system('cp %s %s' % ('E2/cell_utils.py', 'IL/.'))
# AA cell (all active model L5 Pyr) - http://celltypes.brain-map.org/experiment/electrophysiology/485574832
neuronal_model_id = 497232312
bp.cache_data(neuronal_model_id, working_directory='AA')
os.system('cd AA; nrnivmodl ./modfiles; cd ..')
os.system('cp %s %s' % ('E2/cell_template.hoc', 'AA/.'))
os.system('nrnivmodl ./E2/modfiles')
def __init__(self, model_id, cache_stim=False):
self.model_id = model_id
self.bp = BiophysicalApi()
self.model_dir = os.path.join(os.getcwd(), 'model_' + str(model_id),
'')
self.bp.cache_stimulus = cache_stim
self.h = None
self.utils = None
self.description = None
self.section_output = {}
############################
self.reference_sweep = None
self.reference_output = None
self.j_history = []
self.theta_history = []
self.theta = None
self.theta_name = ''
self.fit_section = None
def model_props(cell_id):
cell_metadata = {}
# download existing model (if exists)
bp = BiophysicalApi()
try:
model_list = bp.get_neuronal_models(cell_id)
model_dict = {key: '' for key in template_model_dict.keys()}
for model_type, template_id in template_model_dict.items():
for model_meta in model_list:
if model_meta['neuronal_model_template_id'] == template_id:
model_dict[model_type] = model_meta['id']
except:
logger.debug('No biophysical model available')
api = allensdk.api.queries.rma_api.RmaApi() # Get the model metadata
for model_type, model_id in model_dict.items():
if model_id != '':
bp.cache_data(model_id, working_directory=model_dir[model_type])
model_metadata = api.model_query(
"NeuronalModelRun",
criteria="[neuronal_model_id$eq%s]" % model_id)
model_metadata_select = [
model_metadata[0]['rheobase_feature_average'],
model_metadata[0]['explained_variance_ratio']
]
model_path = glob.glob('%s/*fit*.json' % model_dir[model_type])[0]
for file_ in glob.glob('%s/*' % model_dir[model_type]):
if file_ != model_path:
try:
os.remove(file_)
except:
shutil.rmtree(file_, ignore_errors=True)
cell_metadata['model_path_{}'.format(
model_type)] = os.path.abspath(model_path)
cell_metadata['{}_id'.format(
model_dir[model_type])] = str(model_id)
for i, metadata_key in enumerate(opt_metric_dict[model_type]):
cell_metadata[metadata_key] = model_metadata_select[i]
return cell_metadata
def test_biophysical():
neuronal_model_id = 472451419 # get this from the web site
model_directory = '.'
bp = BiophysicalApi('http://api.brain-map.org')
bp.cache_stimulus = False # don't want to download the large stimulus NWB file
bp.cache_data(neuronal_model_id, working_directory=model_directory)
os.system('nrnivmodl modfiles')
description = Config().load('manifest.json')
utils = Utils(description)
h = utils.h
manifest = description.manifest
morphology_path = manifest.get_path('MORPHOLOGY')
utils.generate_morphology(morphology_path.encode('ascii', 'ignore'))
utils.load_cell_parameters()
stim = h.IClamp(h.soma[0](0.5))
stim.amp = 0.18
stim.delay = 1000.0
stim.dur = 1000.0
h.tstop = 3000.0
vec = utils.record_values()
h.finitialize()
h.run()
output_path = 'output_voltage.dat'
junction_potential = description.data['fitting'][0]['junction_potential']
mV = 1.0e-3
ms = 1.0e-3
output_data = (numpy.array(vec['v']) - junction_potential) * mV
output_times = numpy.array(vec['t']) * ms
DatUtilities.save_voltage(output_path, output_data, output_times)
assert numpy.count_nonzero(output_data) > 0
s = os.path.join(src, item)
d = os.path.join(dst, item)
if os.path.isdir(s):
shutil.copytree(s, d, symlinks, ignore)
else:
shutil.copy2(s, d)
#%% Pick a cell and a sweep to run from the available set of protocols
cell_id = 468193142 # get this from the web site: http://celltypes.brain-map.org
sweep_num = 46 # Select a Long Square sweep : 1s DC
#%% Download all-acive model
sdk_model_templates = {'all_active': 491455321, 'perisomatic': 329230710}
bp = BiophysicalApi()
bp.cache_stimulus = True
model_list = bp.get_neuronal_models(cell_id, model_type_ids=[sdk_model_templates['all_active']]) # Only get the all-active model for the cell
model_dict = model_list[0]
model_dir = 'all_active_models'
bp.cache_data(model_dict['id'], working_directory=model_dir)
new_model_file = 'fit_parameters_new.json'
shutil.copyfile(new_model_file, os.path.join(model_dir, new_model_file))
copytree('modfiles', os.path.join(model_dir, 'modfiles'))
#%% Running the legacy all-active models
os.chdir(model_dir)
subprocess.check_call(['nrnivmodl', 'modfiles/'])
manifest_file = 'manifest.json'
def biophys_api():
endpoint = 'http://twarehouse-backup'
return BiophysicalApi(endpoint)
rma::criteria,[m__biophys_perisomatic$gt0],rma::criteria,[donor__species$il%27homo%20sapiens%27]'
tree = ET.fromstring(urllib.urlopen(url_spec).read())
neurons = []
# here we go through all the results and ask for the neuronal-model
for spec in tree.iter('specimen--id'):
url_model = "http://api.brain-map.org/api/v2/data/query.xml?criteria=model::NeuronalModel,\
rma::critera,[specimen_id$eq" + spec.text + "],neuronal_model_template[name$il'*Bio*']"
neurons.append(ET.fromstring(urllib.urlopen(url_model).read()).iter('id').next().text)
print("Found {0} neurons").format(len(neurons))
base_dir = os.getcwd()
working_directory = 'morphologies/ABI/' # where the model files will be downloaded
bp = BiophysicalApi('http://api.brain-map.org')
bp.cache_stimulus = False # set to True to download the large stimulus NWB file
for i, neuron in enumerate(neurons):
# os.mkdir(os.path.join(working_directory, neuron))
bp.cache_data(int(neuron), working_directory=os.path.join(working_directory, neuron))
# change directory
os.chdir(os.path.join(working_directory, neuron))
# compile and load NEURON NMODL files
os.system('nrnivmodl modfiles')
print("{} mechanism(s) compiled out of {}").format(i + 1, len(neurons))
os.chdir(base_dir)
# neuronal_model_id = 472451419 # get this from the web site as above
def download():
neuronal_model_ids = [
'478047737', '472430904', '479234506', '478513451', '472352327',
'478043748', '480633088', '478513443', '489931963', '478513224',
'478047816', '480632594', '472440759', '485694403', '478513459',
'471081668', '477840124', '479234530', '473835796', '329322394',
'486557284', '479234670', '478513445', '472306616', '486509010',
'478045347', '486509232', '480051220', '485611914', '480631402',
'472451419', '483108201', '496930338', '482525264', '479427516',
'488461970', '477876583', '479427369', '472306544', '478810017',
'482657381', '478513187', '486511108', '479694721', '476630478',
'486052412', '482655070', '472306460', '472442377', '478513396',
'482525598', '476637699', '487245869', '485510685', '478513398',
'477494382', '482657528', '478513461', '485507735', '478513411',
'480629276', '473863510', '485591806', '488462820', '472447460',
'480633809', '476637723', '478047588', '482524837', '477839613',
'478809991', '486556597', '480624051', '473465456', '472300877',
'476679102', '480630211', '480633479', '480631048', '479427443',
'478045081', '477313251', '483156585', '329321704', '472299363',
'480613522', '482934212', '485591776', '472434498', '472304676',
'488462783', '489932435', '473863578', '486052435', '486508758',
'486556811', '473834758', '477880244', '478047618', '485602029',
'478513407', '485513184', '472421285', '477510985', '480631286',
'491517388', '483066358', '479234441', '488763268', '473872986',
'488462965', '472455509', '489932597', '480624251', '480056382',
'477876559', '478809612', '473863035', '480632564', '473862421',
'486556714', '485909152', '486508647', '473871773', '471086533',
'482529696', '478045202', '489931686', '473465774', '471085845',
'480624414', '480631187', '480624126', '485476031', '480630857',
'473862496', '471087975', '485909125', '472912177', '478513437',
'477838913', '478045226', '486558444', '478048947', '486909496',
'477878284', '476630516', '484628276', '479694359', '485513255',
'484620556', '479694384', '483106906', '489932183', '485510712',
'477510918', '472363762', '473862845', '486144663', '479695152',
'483109057', '478513415', '482583564', '488759006', '472912107',
'485904766', '480630395', '480361288', '485720616', '477878554',
'476637796', '479694856', '478049069', '476637747', '472450023',
'478513441', '472299294'
]
neuronal_model_ids = [472450023, 483108201, 486556811]
print("---- Downloading %i cell models..." % len(neuronal_model_ids))
for neuronal_model_id in neuronal_model_ids:
print("---- Downloading cell model: %s..." % neuronal_model_id)
try:
bp = BiophysicalApi('http://api.brain-map.org')
bp.cache_stimulus = False # change to False to not download the large stimulus NWB file
working_directory = '%i' % neuronal_model_id
bp.cache_data(neuronal_model_id,
working_directory=working_directory)
print("---- Saved model into %s, included NWB file: %s" %
(working_directory, bp.cache_stimulus))
with open(working_directory + '/manifest.json', "r") as json_file:
manifest_info = json.load(json_file)
metadata = {}
exp_id = int(manifest_info["biophys"][0]["model_file"][1][:9])
metadata['exp_id'] = exp_id
metadata[
'URL'] = 'http://celltypes.brain-map.org/mouse/experiment/electrophysiology/%s' % exp_id
for m in manifest_info['manifest']:
if m['key'] == "output_path":
nwb_file = working_directory + '/' + m['spec']
if os.path.isfile(nwb_file):
print("---- Extracting metadate from NWB file: %s" %
(nwb_file))
h5file = tables.open_file(nwb_file, mode='r')
metadata['AIBS:aibs_dendrite_type'] = str(
h5file.root.general.aibs_dendrite_type.read())
metadata['AIBS:aibs_cre_line'] = str(
h5file.root.general.aibs_cre_line.read())
metadata['AIBS:aibs_specimen_id'] = str(
h5file.root.general.aibs_specimen_id.read())
metadata['AIBS:aibs_specimen_name'] = str(
h5file.root.general.aibs_specimen_name.read())
metadata[
'AIBS:intracellular_ephys:Electrode 1:location'] = str(
h5file.root.general.intracellular_ephys.
_v_children['Electrode 1'].location.read())
metadata['AIBS:session_id'] = str(
h5file.root.general.session_id.read())
metadata['AIBS:subject:age'] = str(
h5file.root.general.subject.age.read())
metadata['AIBS:subject:description'] = str(
h5file.root.general.subject.description.read())
metadata['AIBS:subject:genotype'] = str(
h5file.root.general.subject.genotype.read())
metadata['AIBS:subject:sex'] = str(
h5file.root.general.subject.sex.read())
metadata['AIBS:subject:species'] = str(
h5file.root.general.subject.species.read())
else:
print("---- Can't find NWB file: %s!" % (nwb_file))
print(' Metadata:')
pp.pprint(metadata)
with open(working_directory + '/metadata.json', 'w') as f:
json.dump(metadata, f, indent=4)
except IndexError:
print("Problem!")