def update_concept_maps():
ncm_fields, ecm_fields, nedm_fields = load()
datatables = m.DataTable.objects.all()
print 'Getting or creating data sources'
for i,x in enumerate(datatables):
prog(i,datatables.count())
m.DataSource.objects.get_or_create(data_table=x)
anon_user = m.get_anon_user()
robot_user = m.get_robot_user()
print 'Updating nedm fields'
for i,nedm_field in enumerate(nedm_fields):
prog(i, len(nedm_fields))
nedm=m.NeuronEphysDataMap.objects.get(pk=nedm_field['pk'])
data_source = m.DataSource.objects.get(data_table=nedm_field['fields']['data_table'])
nedm.source = data_source
# if nedm.added_by_old == 'human':
# nedm.added_by = anon_user
# else:
# nedm.added_by = robot_user
nedm.save()
print 'Updating ncm fields'
for i,ncm_field in enumerate(ncm_fields):
prog(i, len(ncm_fields))
ncm=m.NeuronConceptMap.objects.get(pk=ncm_field['pk'])
data_source = m.DataSource.objects.get(data_table=ncm_field['fields']['data_table'])
ncm.source = data_source
# if ncm.added_by_old == 'human':
# ncm.added_by = anon_user
# else:
# ncm.added_by = robot_user
ncm.save()
print 'Updating ecm fields'
for ecm_field in ecm_fields:
prog(i, len(ecm_fields))
ecm=m.EphysConceptMap.objects.get(pk=ecm_field['pk'])
data_source = m.DataSource.objects.get(data_table=ecm_field['fields']['data_table'])
ecm.source = data_source
# if ecm.added_by_old == 'human':
# ecm.added_by = anon_user
# else:
# ecm.added_by = robot_user
ecm.save()
def get_old_shreejoy_user_list():
old_shreejoy_user_list = list(m.User.objects.filter(email='*****@*****.**'))
old_shreejoy_user_list.append(m.User.objects.get(username = '******'))
old_shreejoy_user_list.append(m.get_anon_user())
return old_shreejoy_user_list
afts.save()
us_ob = m.UserSubmission.objects.get_or_create(user = user, article = a)[0]
ds_ob = m.DataSource.objects.get_or_create(user_submission = us_ob)[0]
ncm_ob = m.NeuronConceptMap.objects.get_or_create(source = ds_ob, added_by = user, neuron = n,
times_validated = 1)[0]
add_ephys_nedm(tm_mean, tm_sem, 4, ds_ob, ncm_ob, user)
add_ephys_nedm(hw_mean, hw_sem, 6, ds_ob, ncm_ob, user)
add_ephys_nedm(thresh_mean, thresh_sem, 7, ds_ob, ncm_ob, user)
add_ephys_nedm(ir_mean, ir_sem, 2, ds_ob, ncm_ob, user)
add_ephys_nedm(rmp_mean, rmp_sem, 3, ds_ob, ncm_ob, user)
add_ephys_nedm(amp_mean, amp_sem, 5, ds_ob, ncm_ob, user)
anon_user = m.get_anon_user()
def process_table(table, ncols, nrows):
user = m.User.objects.get(username = '******')
table_norm = [ [ 0 for i in range(6) ] for j in range(nrows ) ]
table_norm = np.zeros([nrows, 6], dtype='a16')
for i in range(1,nrows):
ref = table[i][0]
# neuron_type = table[i][5]
#n = m.Neuron.objects.filter(name = neuron_type)[0]
species = table[i][2]
strain = table[i][3]
age = table[i][4]
electrode = table[i][6]
prep_type = table[i][7]
temp = table[i][5]
neuron_type = table[i][1]