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]