def get_session_user():
'''
Determine desired 'session user' for a session.
- 1st, try dj.config['custom']['session.user']
- 2nd, try dj.config['database.user']
- else, use 'unknown'
TODO: multi-user / bulk ingest support
'''
session_user = dj.config.get('custom', {}).get('session.user', None)
session_user = (dj.config.get('database.user')
if not session_user else session_user)
if len(lab.Person() & {'username': session_user}):
return session_user
else:
return 'unknown'
def mockdata():
print('populating with mock data')
reload(ccf)
reload(lab)
reload(experiment)
reload(ephys)
reload(publication)
try:
# TODO: these should be loaded in a more 'official' way
lab.Person().insert1({
'username': '******',
'fullname': 'Dave Liu'
},
skip_duplicates=True)
lab.ModifiedGene().insert1(
{
'gene_modification': 'VGAT-Chr2-EYFP Jax',
'gene_modification_description': 'VGAT'
},
skip_duplicates=True)
lab.ModifiedGene().insert1(
{
'gene_modification': 'PV-ires-Cre X Ai32',
'gene_modification_description': 'PV'
},
skip_duplicates=True)
lab.ModifiedGene().insert1(
{
'gene_modification':
'Rosa26 Cag lsl reachR-citrine 1A4 X PV-ires-Cre',
'gene_modification_description': 'reachR PV'
},
skip_duplicates=True)
# Subject 399752 / dl7
lab.Subject().insert1(
{
'subject_id': 399752,
'username': '******',
'cage_number': 145375,
'date_of_birth': '2017-08-03',
'sex': 'M',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.Subject.GeneModification().insert1(
{
'subject_id': 399752,
'gene_modification': 'VGAT-Chr2-EYFP Jax'
},
skip_duplicates=True)
lab.Surgery().insert1(
{
'subject_id': 399752,
'surgery_id': 1,
'username': '******',
'start_time': '2017-11-03',
'end_time': '2017-11-03',
'surgery_description': 'Headbar anterior'
},
skip_duplicates=True)
lab.Surgery.Procedure().insert1(
{
'subject_id': 399752,
'surgery_id': 1,
'procedure_id': 1,
'skull_reference': 'Bregma',
'ml_location': 0,
'ap_location': -4,
'surgery_procedure_description': 'Fiducial marker'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 399752,
'water_restriction_number': 'dl7',
'cage_number': 148861,
'wr_start_date': '2017-11-07',
'wr_start_weight': 25
},
skip_duplicates=True)
# Subject 397853 / dl14
lab.Subject().insert1(
{
'subject_id': 397853,
'username': '******',
'cage_number': 144545,
'date_of_birth': '2017-07-15',
'sex': 'M',
'animal_source': 'Allen Institute'
},
skip_duplicates=True)
lab.Subject.GeneModification().insert1(
{
'subject_id': 397853,
'gene_modification': 'PV-ires-Cre X Ai32'
},
skip_duplicates=True)
lab.Surgery().insert1(
{
'subject_id': 397853,
'surgery_id': 1,
'username': '******',
'start_time': '2017-11-20',
'end_time': '2017-11-20',
'surgery_description': 'Headbar posterior'
},
skip_duplicates=True)
lab.Surgery.Procedure().insert1(
{
'subject_id': 397853,
'surgery_id': 1,
'procedure_id': 1,
'skull_reference': 'Bregma',
'ml_location': 0,
'ap_location': -1.75,
'surgery_procedure_description': 'Fiducial marker'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 397853,
'water_restriction_number': 'dl14',
'cage_number': 149595,
'wr_start_date': '2017-11-27',
'wr_start_weight': 24.1
},
skip_duplicates=True)
# Subject 400480 / dl15
lab.Subject().insert1(
{
'subject_id': 400480,
'username': '******',
'cage_number': 145700,
'date_of_birth': '2017-08-09',
'sex': 'M',
'animal_source': 'Allen Institute'
},
skip_duplicates=True)
lab.Subject.GeneModification().insert1(
{
'subject_id': 400480,
'gene_modification': 'PV-ires-Cre X Ai32'
},
skip_duplicates=True)
lab.Surgery().insert1(
{
'subject_id': 400480,
'surgery_id': 1,
'username': '******',
'start_time': '2017-11-21',
'end_time': '2017-11-21',
'surgery_description': 'Headbar posterior'
},
skip_duplicates=True)
lab.Surgery.Procedure().insert1(
{
'subject_id': 400480,
'surgery_id': 1,
'procedure_id': 1,
'skull_reference': 'Bregma',
'ml_location': 0,
'ap_location': -1.75,
'surgery_procedure_description': 'Fiducial marker'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 400480,
'water_restriction_number': 'dl15',
'cage_number': 149598,
'wr_start_date': '2017-11-27',
'wr_start_weight': 27.6
},
skip_duplicates=True)
# Subject 406680 / dl20
lab.Subject().insert1(
{
'subject_id': 406680,
'username': '******',
'cage_number': 148859,
'date_of_birth': '2017-10-06',
'sex': 'F',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.Subject.GeneModification().insert1(
{
'subject_id': 406680,
'gene_modification': 'VGAT-Chr2-EYFP Jax'
},
skip_duplicates=True)
lab.Surgery().insert1(
{
'subject_id': 406680,
'surgery_id': 1,
'username': '******',
'start_time': '2018-01-04',
'end_time': '2018-01-04',
'surgery_description': 'Headbar posterior'
},
skip_duplicates=True)
lab.Surgery.Procedure().insert1(
{
'subject_id': 406680,
'surgery_id': 1,
'procedure_id': 1,
'skull_reference': 'Bregma',
'ml_location': 0,
'ap_location': -1.75,
'surgery_procedure_description': 'Fiducial marker'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 406680,
'water_restriction_number': 'dl20',
'cage_number': 151282,
'wr_start_date': '2018-01-10',
'wr_start_weight': 22.7
},
skip_duplicates=True)
# Subject 408022 / dl21
lab.Subject().insert1(
{
'subject_id': 408022,
'username': '******',
'cage_number': 148859,
'date_of_birth': '2017-10-19',
'sex': 'F',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.Subject.GeneModification().insert1(
{
'subject_id': 408022,
'gene_modification': 'VGAT-Chr2-EYFP Jax'
},
skip_duplicates=True)
lab.Surgery().insert1(
{
'subject_id': 408022,
'surgery_id': 1,
'username': '******',
'start_time': '2018-01-05',
'end_time': '2018-01-05',
'surgery_description': 'Headbar posterior'
},
skip_duplicates=True)
lab.Surgery.Procedure().insert1(
{
'subject_id': 408022,
'surgery_id': 1,
'procedure_id': 1,
'skull_reference': 'Bregma',
'ml_location': 0,
'ap_location': -1.75,
'surgery_procedure_description': 'Fiducial marker'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 408022,
'water_restriction_number': 'dl21',
'cage_number': 151283,
'wr_start_date': '2018-01-10',
'wr_start_weight': 21.1
},
skip_duplicates=True)
# Subject 408021 / dl22
lab.Subject().insert1(
{
'subject_id': 408021,
'username': '******',
'cage_number': 148859,
'date_of_birth': '2017-10-19',
'sex': 'F',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.Subject.GeneModification().insert1(
{
'subject_id': 408021,
'gene_modification': 'VGAT-Chr2-EYFP Jax'
},
skip_duplicates=True)
lab.Surgery().insert1(
{
'subject_id': 408021,
'surgery_id': 1,
'username': '******',
'start_time': '2018-01-15',
'end_time': '2018-01-15',
'surgery_description': 'Headbar posterior'
},
skip_duplicates=True)
lab.Surgery.Procedure().insert1(
{
'subject_id': 408021,
'surgery_id': 1,
'procedure_id': 1,
'skull_reference': 'Bregma',
'ml_location': 0,
'ap_location': -1.75,
'surgery_procedure_description': 'Fiducial marker'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 408021,
'water_restriction_number': 'dl22',
'cage_number': 151704,
'wr_start_date': '2018-01-19',
'wr_start_weight': 21
},
skip_duplicates=True)
# Subject 407512 / dl24
lab.Subject().insert1(
{
'subject_id': 407512,
'username': '******',
'cage_number': 151629,
'date_of_birth': '2017-10-13',
'sex': 'M',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.Subject.GeneModification().insert1(
{
'subject_id': 407512,
'gene_modification': 'VGAT-Chr2-EYFP Jax'
},
skip_duplicates=True)
lab.Surgery().insert1(
{
'subject_id': 407512,
'surgery_id': 1,
'username': '******',
'start_time': '2018-01-16',
'end_time': '2018-01-16',
'surgery_description': 'Headbar posterior'
},
skip_duplicates=True)
lab.Surgery.Procedure().insert1(
{
'subject_id': 407512,
'surgery_id': 1,
'procedure_id': 1,
'skull_reference': 'Bregma',
'ml_location': 0,
'ap_location': -1.75,
'surgery_procedure_description': 'Fiducial marker'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 407512,
'water_restriction_number': 'dl24',
'cage_number': 151793,
'wr_start_date': '2018-01-22',
'wr_start_weight': 26
},
skip_duplicates=True)
# 407513 / dl25
lab.Subject().insert1(
{
'subject_id': 407513,
'username': '******',
'cage_number': 148636,
'date_of_birth': '2017-10-13',
'sex': 'M',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.Subject.GeneModification().insert1(
{
'subject_id': 407513,
'gene_modification': 'VGAT-Chr2-EYFP Jax'
},
skip_duplicates=True)
lab.Surgery().insert1(
{
'subject_id': 407513,
'surgery_id': 1,
'username': '******',
'start_time': '2018-01-17',
'end_time': '2018-01-17',
'surgery_description': 'Headbar posterior'
},
skip_duplicates=True)
lab.Surgery.Procedure().insert1(
{
'subject_id': 407513,
'surgery_id': 1,
'procedure_id': 1,
'skull_reference': 'Bregma',
'ml_location': 0,
'ap_location': -1.75,
'surgery_procedure_description': 'Fiducial marker'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 407513,
'water_restriction_number': 'dl25',
'cage_number': 151794,
'wr_start_date': '2018-01-22',
'wr_start_weight': 25.5
},
skip_duplicates=True)
# Subject 407986 / dl28
lab.Subject().insert1(
{
'subject_id': 407986,
'username': '******',
'cage_number': 152268,
'date_of_birth': '2017-10-18',
'sex': 'F',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.Subject.GeneModification().insert1(
{
'subject_id': 407986,
'gene_modification': 'VGAT-Chr2-EYFP Jax'
},
skip_duplicates=True)
lab.Surgery().insert1(
{
'subject_id': 407986,
'surgery_id': 1,
'username': '******',
'start_time': '2018-02-01',
'end_time': '2018-02-01',
'surgery_description': 'Headbar anterior'
},
skip_duplicates=True)
lab.Surgery.Procedure().insert1(
{
'subject_id': 407986,
'surgery_id': 1,
'procedure_id': 1,
'skull_reference': 'Bregma',
'ml_location': 0,
'ap_location': -4,
'surgery_procedure_description': 'Fiducial marker'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 407986,
'water_restriction_number': 'dl28',
'cage_number': 152312,
'wr_start_date': '2018-02-05',
'wr_start_weight': 19.8
},
skip_duplicates=True)
# Subject 123457 / tw5
lab.Subject().insert1(
{
'subject_id': 123457,
'username': '******',
'cage_number': 145375,
'date_of_birth': '2017-08-03',
'sex': 'M',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 123457,
'water_restriction_number': 'tw5',
'cage_number': 148861,
'wr_start_date': '2017-11-07',
'wr_start_weight': 20.5
},
skip_duplicates=True)
# Subject 412330 / tw34
lab.Subject().insert1(
{
'subject_id': 412330,
'username': '******',
'cage_number': 154522,
'date_of_birth': '2017-12-05',
'sex': 'M',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 412330,
'water_restriction_number': 'tw34',
'cage_number': 154522,
'wr_start_date': '2018-03-18',
'wr_start_weight': 21.0
},
skip_duplicates=True)
# subject 432998 / dl55
lab.Subject().insert1(
{
'subject_id': 432998,
'username': '******',
'cage_number': 160920,
'date_of_birth': '2018-07-02',
'sex': 'M',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 432998,
'water_restriction_number': 'dl55',
'cage_number': 160920,
'wr_start_date': '2018-09-05',
'wr_start_weight': 21.0
},
skip_duplicates=True)
# Subject 435884 / dl59
lab.Subject().insert1(
{
'subject_id': 435884,
'username': '******',
'cage_number': 161908,
'date_of_birth': '2018-08-06',
'sex': 'M',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 435884,
'water_restriction_number': 'dl59',
'cage_number': 154522,
'wr_start_date': '2018-09-30',
'wr_start_weight': 21.0
},
skip_duplicates=True)
lab.Rig().insert1(
{
'rig': 'TRig1',
'room': '2w.334',
'rig_description': 'Training rig 1'
},
skip_duplicates=True)
lab.Rig().insert1(
{
'rig': 'TRig2',
'room': '2w.334',
'rig_description': 'Training rig 2'
},
skip_duplicates=True)
lab.Rig().insert1(
{
'rig': 'TRig3',
'room': '2w.334',
'rig_description': 'Training rig 3'
},
skip_duplicates=True)
lab.Rig().insert1(
{
'rig': 'RRig',
'room': '2w.334',
'rig_description': 'Recording rig'
},
skip_duplicates=True)
lab.Rig().insert1(
{
'rig': 'Ephys1',
'room': '2w.334',
'rig_description': 'Recording computer'
},
skip_duplicates=True)
# ---- Brain Location ----
experiment.BrainLocation.insert1(
{
'brain_location_name': 'left_alm',
'brain_area': 'ALM',
'hemisphere': 'left',
'skull_reference': 'Bregma'
},
skip_duplicates=True)
experiment.BrainLocation.insert1(
{
'brain_location_name': 'right_alm',
'brain_area': 'ALM',
'hemisphere': 'right',
'skull_reference': 'Bregma'
},
skip_duplicates=True)
experiment.BrainLocation.insert1(
{
'brain_location_name': 'both_alm',
'brain_area': 'ALM',
'hemisphere': 'both',
'skull_reference': 'Bregma'
},
skip_duplicates=True)
experiment.BrainLocation.insert1(
{
'brain_location_name': 'left_medulla',
'brain_area': 'Medulla',
'hemisphere': 'left',
'skull_reference': 'Bregma'
},
skip_duplicates=True)
experiment.BrainLocation.insert1(
{
'brain_location_name': 'right_medulla',
'brain_area': 'Medulla',
'hemisphere': 'right',
'skull_reference': 'Bregma'
},
skip_duplicates=True)
experiment.BrainLocation.insert1(
{
'brain_location_name': 'both_medulla',
'brain_area': 'Medulla',
'hemisphere': 'both',
'skull_reference': 'Bregma'
},
skip_duplicates=True)
# Probe (Neuropixel)
npx_probe_model = '15131808323' # using Model No. - SN TBD?
lab.Probe.insert1(
{
'probe': npx_probe_model,
'probe_type': 'neuropixel'
},
skip_duplicates=True,
)
lab.Probe.Electrode.insert(
({
'probe': npx_probe_model,
'electrode': x
} for x in range(1, 961)),
skip_duplicates=True,
)
except Exception as e:
print("error creating mock data: {e}".format(e=e), file=sys.stderr)
raise
def populatemetadata():
#%% save metadata from google drive if necessairy
lastmodify = online_notebook.fetch_lastmodify_time_animal_metadata()
with open(dj.config['locations.metadata_surgery_experiment'] +
'last_modify_time.json') as timedata:
lastmodify_prev = json.loads(timedata.read())
if lastmodify != lastmodify_prev:
print('updating surgery and WR metadata from google drive')
dj.config['locations.metadata_surgery_experiment']
df_surgery = online_notebook.fetch_animal_metadata()
df_surgery.to_csv(dj.config['locations.metadata_surgery_experiment'] +
'Surgery.csv')
IDs = df_surgery['ID'].tolist()
for ID in IDs:
df_wr = online_notebook.fetch_water_restriction_metadata(ID)
if type(df_wr) == pd.DataFrame:
df_wr.to_csv(
dj.config['locations.metadata_surgery_experiment'] + ID +
'.csv')
with open(
dj.config['locations.metadata_surgery_experiment'] +
'last_modify_time.json', "w") as write_file:
json.dump(lastmodify, write_file)
print('surgery and WR metadata updated')
lastmodify = online_notebook.fetch_lastmodify_time_lab_metadata()
with open(dj.config['locations.metadata_lab'] +
'last_modify_time.json') as timedata:
lastmodify_prev = json.loads(timedata.read())
if lastmodify != lastmodify_prev:
print('updating Lab metadata from google drive')
dj.config['locations.metadata_lab']
IDs = ['Experimenter', 'Rig', 'Virus']
for ID in IDs:
df_wr = online_notebook.fetch_lab_metadata(ID)
if type(df_wr) == pd.DataFrame:
df_wr.to_csv(dj.config['locations.metadata_lab'] + ID + '.csv')
with open(
dj.config['locations.metadata_lab'] + 'last_modify_time.json',
"w") as write_file:
json.dump(lastmodify, write_file)
print('Lab metadata updated')
#%% add users
df_experimenters = pd.read_csv(dj.config['locations.metadata_lab'] +
'Experimenter.csv')
experimenterdata = list()
for experimenter in df_experimenters.iterrows():
experimenter = experimenter[1]
dictnow = {
'username': experimenter['username'],
'fullname': experimenter['fullname']
}
experimenterdata.append(dictnow)
print('adding experimenters')
for experimenternow in experimenterdata:
try:
lab.Person().insert1(experimenternow)
except dj.errors.DuplicateError:
print('duplicate. experimenter: ', experimenternow['username'],
' already exists')
#%% add rigs
df_rigs = pd.read_csv(dj.config['locations.metadata_lab'] + 'Rig.csv')
rigdata = list()
for rig in df_rigs.iterrows():
rig = rig[1]
dictnow = {
'rig': rig['rig'],
'room': rig['room'],
'rig_description': rig['rig_description']
}
rigdata.append(dictnow)
print('adding rigs')
for rignow in rigdata:
try:
lab.Rig().insert1(rignow)
except dj.errors.DuplicateError:
print('duplicate. rig: ', rignow['rig'], ' already exists')
#%% add viruses
df_viruses = pd.read_csv(dj.config['locations.metadata_lab'] + 'Virus.csv')
virusdata = list()
serotypedata = list()
for virus in df_viruses.iterrows():
virus = virus[1]
if type(virus['remarks']) != str:
virus['remarks'] = ''
dictnow = {
'virus_id': virus['virus_id'],
'virus_source': virus['virus_source'],
'serotype': virus['serotype'],
'username': virus['username'],
'virus_name': virus['virus_name'],
'titer': virus['titer'],
'order_date': virus['order_date'],
'remarks': virus['remarks']
}
virusdata.append(dictnow)
dictnow = {'serotype': virus['serotype']}
serotypedata.append(dictnow)
print('adding rigs')
for virusnow, serotypenow in zip(virusdata, serotypedata):
try:
lab.Serotype().insert1(serotypenow)
except dj.errors.DuplicateError:
print('duplicate serotype: ', serotypenow['serotype'],
' already exists')
try:
lab.Virus().insert1(virusnow)
except dj.errors.DuplicateError:
print('duplicate virus: ', virusnow['virus_name'],
' already exists')
#%% populate subjects, surgeries and water restrictions
print('adding surgeries and stuff')
df_surgery = pd.read_csv(
dj.config['locations.metadata_surgery_experiment'] + 'Surgery.csv')
#%%
for item in df_surgery.iterrows():
if item[1]['project'] == dj.config['project'] and (
item[1]['status'] == 'training'
or item[1]['status'] == 'sacrificed'):
subjectdata = {
'subject_id': item[1]['animal#'],
'cage_number': item[1]['cage#'],
'date_of_birth': item[1]['DOB'],
'sex': item[1]['sex'],
'username': item[1]['experimenter'],
}
try:
lab.Subject().insert1(subjectdata)
except dj.errors.DuplicateError:
print('duplicate. animal :', item[1]['animal#'],
' already exists')
surgeryidx = 1
while 'surgery date (' + str(surgeryidx) + ')' in item[1].keys(
) and item[1]['surgery date (' + str(surgeryidx) + ')'] and type(
item[1]['surgery date (' + str(surgeryidx) + ')']) == str:
start_time = datetime.strptime(
item[1]['surgery date (' + str(surgeryidx) + ')'] + ' ' +
item[1]['surgery time (' + str(surgeryidx) + ')'],
'%Y-%m-%d %H:%M')
end_time = start_time + timedelta(
minutes=int(item[1]['surgery length (min) (' +
str(surgeryidx) + ')']))
surgerydata = {
'surgery_id':
surgeryidx,
'subject_id':
item[1]['animal#'],
'username':
item[1]['experimenter'],
'start_time':
start_time,
'end_time':
end_time,
'surgery_description':
item[1]['surgery type (' + str(surgeryidx) + ')'] +
':-: comments: ' +
str(item[1]['surgery comments (' + str(surgeryidx) + ')']),
}
try:
lab.Surgery().insert1(surgerydata)
except dj.errors.DuplicateError:
print('duplicate. surgery for animal ', item[1]['animal#'],
' already exists: ', start_time)
#checking craniotomies
#%
cranioidx = 1
while 'craniotomy diameter (' + str(
cranioidx) + ')' in item[1].keys() and item[1][
'craniotomy diameter (' + str(cranioidx) +
')'] and (
type(item[1]['craniotomy surgery id (' +
str(cranioidx) + ')']) == int or
type(item[1]['craniotomy surgery id (' +
str(cranioidx) + ')']) == float):
if item[1]['craniotomy surgery id (' + str(cranioidx) +
')'] == surgeryidx:
proceduredata = {
'surgery_id':
surgeryidx,
'subject_id':
item[1]['animal#'],
'procedure_id':
cranioidx,
'skull_reference':
item[1]['craniotomy reference (' + str(cranioidx) +
')'],
'ml_location':
item[1]['craniotomy lateral (' + str(cranioidx) +
')'],
'ap_location':
item[1]['craniotomy anterior (' + str(cranioidx) +
')'],
'surgery_procedure_description':
'craniotomy: ' + item[1]['craniotomy comments (' +
str(cranioidx) + ')'],
}
try:
lab.Surgery.Procedure().insert1(proceduredata)
except dj.errors.DuplicateError:
print('duplicate cranio for animal ',
item[1]['animal#'], ' already exists: ',
cranioidx)
cranioidx += 1
#%
virusinjidx = 1
while 'virus inj surgery id (' + str(
virusinjidx) + ')' in item[1].keys() and item[1][
'virus inj virus id (' + str(virusinjidx) +
')'] and item[1]['virus inj surgery id (' +
str(virusinjidx) + ')']:
if item[1]['virus inj surgery id (' + str(virusinjidx) +
')'] == surgeryidx:
# =============================================================================
# print('waiting')
# timer.sleep(1000)
# =============================================================================
if '[' in item[1]['virus inj lateral (' +
str(virusinjidx) + ')']:
virus_ml_locations = eval(
item[1]['virus inj lateral (' +
str(virusinjidx) + ')'])
virus_ap_locations = eval(
item[1]['virus inj anterior (' +
str(virusinjidx) + ')'])
virus_dv_locations = eval(
item[1]['virus inj ventral (' +
str(virusinjidx) + ')'])
virus_volumes = eval(
item[1]['virus inj volume (nl) (' +
str(virusinjidx) + ')'])
else:
virus_ml_locations = [
int(item[1]['virus inj lateral (' +
str(virusinjidx) + ')'])
]
virus_ap_locations = [
int(item[1]['virus inj anterior (' +
str(virusinjidx) + ')'])
]
virus_dv_locations = [
int(item[1]['virus inj ventral (' +
str(virusinjidx) + ')'])
]
virus_volumes = [
int(item[1]['virus inj volume (nl) (' +
str(virusinjidx) + ')'])
]
for virus_ml_location, virus_ap_location, virus_dv_location, virus_volume in zip(
virus_ml_locations, virus_ap_locations,
virus_dv_locations, virus_volumes):
injidx = len(lab.Surgery.VirusInjection()
& surgerydata) + 1
virusinjdata = {
'surgery_id':
surgeryidx,
'subject_id':
item[1]['animal#'],
'injection_id':
injidx,
'virus_id':
item[1]['virus inj virus id (' +
str(virusinjidx) + ')'],
'skull_reference':
item[1]['virus inj reference (' +
str(virusinjidx) + ')'],
'ml_location':
virus_ml_location,
'ap_location':
virus_ap_location,
'dv_location':
virus_dv_location,
'volume':
virus_volume,
'dilution':
item[1]['virus inj dilution (' +
str(virusinjidx) + ')'],
'description':
'virus injection: ' +
item[1]['virus inj comments (' +
str(virusinjidx) + ')'],
}
try:
lab.Surgery.VirusInjection().insert1(
virusinjdata)
except dj.errors.DuplicateError:
print('duplicate virus injection for animal ',
item[1]['animal#'], ' already exists: ',
injidx)
virusinjidx += 1
#%
surgeryidx += 1
#%
if item[1]['ID']:
#df_wr = online_notebook.fetch_water_restriction_metadata(item[1]['ID'])
try:
df_wr = pd.read_csv(
dj.config['locations.metadata_surgery_experiment'] +
item[1]['ID'] + '.csv')
except:
df_wr = None
if type(df_wr) == pd.DataFrame:
wrdata = {
'subject_id': item[1]['animal#'],
'water_restriction_number': item[1]['ID'],
'cage_number': item[1]['cage#'],
'wr_start_date': df_wr['Date'][0],
'wr_start_weight': df_wr['Weight'][0],
}
try:
lab.WaterRestriction().insert1(wrdata)
except dj.errors.DuplicateError:
print('duplicate. water restriction :',
item[1]['animal#'], ' already exists')
def populatemetadata():
#%% save metadata from google drive if necessairy
lastmodify = online_notebook.fetch_lastmodify_time_animal_metadata()
#print(lastmodify)
with open(dj.config['locations.metadata_behavior'] +
'last_modify_time.json') as timedata:
lastmodify_prev = json.loads(timedata.read())
if lastmodify != lastmodify_prev:
print('updating surgery and WR metadata from google drive')
dj.config['locations.metadata_behavior']
df_surgery = online_notebook.fetch_animal_metadata()
df_surgery.to_csv(dj.config['locations.metadata_behavior'] +
'Surgery.csv')
IDs = df_surgery['ID'].tolist()
for ID in IDs:
df_wr = online_notebook.fetch_water_restriction_metadata(ID)
if type(df_wr) == pd.DataFrame:
df_wr.to_csv(dj.config['locations.metadata_behavior'] + ID +
'.csv')
with open(
dj.config['locations.metadata_behavior'] +
'last_modify_time.json', "w") as write_file:
json.dump(lastmodify, write_file)
print('surgery and WR metadata updated')
lastmodify = online_notebook.fetch_lastmodify_time_lab_metadata()
with open(dj.config['locations.metadata_lab'] +
'last_modify_time.json') as timedata:
lastmodify_prev = json.loads(timedata.read())
if lastmodify != lastmodify_prev:
print('updating Lab metadata from google drive')
dj.config['locations.metadata_lab']
IDs = ['Experimenter', 'Rig']
for ID in IDs:
df_wr = online_notebook.fetch_lab_metadata(ID)
if type(df_wr) == pd.DataFrame:
df_wr.to_csv(dj.config['locations.metadata_lab'] + ID + '.csv')
with open(
dj.config['locations.metadata_lab'] + 'last_modify_time.json',
"w") as write_file:
json.dump(lastmodify, write_file)
print('Lab metadata updated')
#%% add users
df_experimenters = pd.read_csv(dj.config['locations.metadata_lab'] +
'Experimenter.csv')
experimenterdata = list()
for experimenter in df_experimenters.iterrows():
experimenter = experimenter[1]
dictnow = {
'username': experimenter['username'],
'fullname': experimenter['fullname']
}
experimenterdata.append(dictnow)
print('adding experimenters')
for experimenternow in experimenterdata:
try:
lab.Person().insert1(experimenternow)
except: # dj.DuplicateError:
print('duplicate. experimenter: ', experimenternow['username'],
' already exists')
#%% add rigs
df_rigs = pd.read_csv(dj.config['locations.metadata_lab'] + 'Rig.csv')
rigdata = list()
for rig in df_rigs.iterrows():
rig = rig[1]
dictnow = {
'rig': rig['rig'],
'room': rig['room'],
'rig_description': rig['rig_description']
}
rigdata.append(dictnow)
print('adding rigs')
for rignow in rigdata:
try:
lab.Rig().insert1(rignow)
except dj.errors.DuplicateError:
print('duplicate. rig: ', rignow['rig'], ' already exists')
#%% populate subjects, surgeries and water restrictions
print('adding surgeries and stuff')
df_surgery = pd.read_csv(dj.config['locations.metadata_behavior'] +
'Surgery.csv')
#%%
for item in df_surgery.iterrows():
if item[1]['status'] == 'experiment':
subjectdata = {
'subject_id': int(item[1]['animal#']),
'username': item[1]['experimenter'],
'cage_number': item[1]['cage#'],
'date_of_birth': item[1]['DOB'],
'sex': item[1]['sex'],
'animal_source': None,
}
#print(subjectdata)
try:
lab.Subject.insert1(subjectdata)
except dj.errors.DuplicateError:
print('duplicate. animal :', item[1]['animal#'],
' already exists')
surgeryidx = 1
#while 'surgery date ('+str(surgeryidx)+')' in item[1].keys() and item[1]['surgery date ('+str(surgeryidx)+')'] and type(item[1]['surgery date ('+str(surgeryidx)+')']) == str:
# start_time = datetime.strptime(item[1]['surgery date ('+str(surgeryidx)+')']+' '+item[1]['surgery time ('+str(surgeryidx)+')'],'%Y-%m-%d %H:%M')
# end_time = start_time + timedelta(minutes = int(item[1]['surgery length (min) ('+str(surgeryidx)+')']))
surgerydata = {
'surgery_id': surgeryidx,
'subject_id': item[1]['animal#'],
'username': item[1]['experimenter'],
'surgery_description': 'lesion',
}
# 'subject_id':int(item[1]['animal#']),
# 'username': item[1]['experimenter'],
# 'brain_area': item[1]['BrainArea'],
# 'hemisphere': item[1]['Hemisphere'],
try:
lab.Surgery.insert1(surgerydata)
except dj.errors.DuplicateError:
print('duplicate. surgery for animal ', item[1]['animal#'],
' already exists: ')
surgerylesiondata = {
'surgery_id': surgeryidx,
'lesion_id': surgeryidx,
'subject_id': item[1]['animal#'],
'method': item[1]['LesionMethod']
}
try:
lab.Surgery.Lesion.insert1(surgerylesiondata)
except dj.errors.DuplicateError:
print('duplicate. surgery lesion animal ', item[1]['animal#'],
' already exists: ')
brainareadata = {
#'surgery_id': surgeryidx,
'brain_area': item[1]['BrainArea'],
'subject_id': item[1]['animal#'],
}
try:
lab.BrainArea.insert1(brainareadata)
except dj.errors.DuplicateError:
print('duplicate. surgery brain area animal ',
item[1]['animal#'], ' already exists: ')
hemispheredata = {
#'surgery_id': surgeryidx,
'hemisphere': item[1]['Hemisphere'],
'subject_id': item[1]['animal#'],
}
try:
lab.Hemisphere.insert1(hemispheredata)
except dj.errors.DuplicateError:
print('duplicate. surgery hemisphere area animal ',
item[1]['animal#'], ' already exists: ')
trainingmethoddata = {
'training_method': item[1]['TrainingMethod'],
'subject_id': item[1]['animal#'],
}
try:
lab.Training.insert1(trainingmethoddata)
except dj.errors.DuplicateError:
print('duplicate. training animal ', item[1]['animal#'],
' already exists: ')
#print(surgerydata)
#%% #checking craniotomies
#%
# cranioidx = 1
# while 'craniotomy diameter ('+str(cranioidx)+')' in item[1].keys() and item[1]['craniotomy diameter ('+str(cranioidx)+')'] and (type(item[1]['craniotomy surgery id ('+str(cranioidx)+')']) == int or type(item[1]['craniotomy surgery id ('+str(cranioidx)+')']) == float):
# if item[1]['craniotomy surgery id ('+str(cranioidx)+')'] == surgeryidx:
# proceduredata = {
# 'surgery_id': surgeryidx,
# 'subject_id':item[1]['animal#'],
# 'procedure_id':cranioidx,
# 'skull_reference':item[1]['craniotomy reference ('+str(cranioidx)+')'],
# 'ml_location':item[1]['craniotomy lateral ('+str(cranioidx)+')'],
# 'ap_location':item[1]['craniotomy anterior ('+str(cranioidx)+')'],
# 'surgery_procedure_description': 'craniotomy: ' + item[1]['craniotomy comments ('+str(cranioidx)+')'],
# }
# try:
# lab.Surgery.Procedure().insert1(proceduredata)
# except dj.DuplicateError:
# print('duplicate cranio for animal ',item[1]['animal#'], ' already exists: ', cranioidx)
# cranioidx += 1
# #%
# virusinjidx = 1
# while 'virus inj surgery id ('+str(virusinjidx)+')' in item[1].keys() and item[1]['virus inj virus id ('+str(virusinjidx)+')'] and item[1]['virus inj surgery id ('+str(virusinjidx)+')']:
# if item[1]['virus inj surgery id ('+str(virusinjidx)+')'] == surgeryidx:
# # =============================================================================
# # print('waiting')
# # timer.sleep(1000)
# # =============================================================================
# if '[' in item[1]['virus inj lateral ('+str(virusinjidx)+')']:
# virus_ml_locations = eval(item[1]['virus inj lateral ('+str(virusinjidx)+')'])
# virus_ap_locations = eval(item[1]['virus inj anterior ('+str(virusinjidx)+')'])
# virus_dv_locations = eval(item[1]['virus inj ventral ('+str(virusinjidx)+')'])
# virus_volumes = eval(item[1]['virus inj volume (nl) ('+str(virusinjidx)+')'])
# else:
# virus_ml_locations = [int(item[1]['virus inj lateral ('+str(virusinjidx)+')'])]
# virus_ap_locations = [int(item[1]['virus inj anterior ('+str(virusinjidx)+')'])]
# virus_dv_locations = [int(item[1]['virus inj ventral ('+str(virusinjidx)+')'])]
# virus_volumes = [int(item[1]['virus inj volume (nl) ('+str(virusinjidx)+')'])]
#
# for virus_ml_location,virus_ap_location,virus_dv_location,virus_volume in zip(virus_ml_locations,virus_ap_locations,virus_dv_locations,virus_volumes):
# injidx = len(lab.Surgery.VirusInjection() & surgerydata) +1
# virusinjdata = {
# 'surgery_id': surgeryidx,
# 'subject_id':item[1]['animal#'],
# 'injection_id':injidx,
# 'virus_id':item[1]['virus inj virus id ('+str(virusinjidx)+')'],
# 'skull_reference':item[1]['virus inj reference ('+str(virusinjidx)+')'],
# 'ml_location':virus_ml_location,
# 'ap_location':virus_ap_location,
# 'dv_location':virus_dv_location,
# 'volume':virus_volume,
# 'dilution':item[1]['virus inj dilution ('+str(virusinjidx)+')'],
# 'description': 'virus injection: ' + item[1]['virus inj comments ('+str(virusinjidx)+')'],
# }
# try:
# lab.Surgery.VirusInjection().insert1(virusinjdata)
# except dj.DuplicateError:
# print('duplicate virus injection for animal ',item[1]['animal#'], ' already exists: ', injidx)
# virusinjidx += 1
# #%
#
# surgeryidx += 1
#%%
if item[1]['ID']:
#df_wr = online_notebook.fetch_water_restriction_metadata(item[1]['ID'])
try:
df_wr = pd.read_csv(
dj.config['locations.metadata_behavior'] +
item[1]['ID'] + '.csv')
except:
df_wr = None
if type(df_wr) == pd.DataFrame:
wrdata = {
'water_restriction_number': item[1]['ID'],
'subject_id': int(item[1]['animal#']),
'cage_number': item[1]['cage#'],
'wr_start_date': '0001-01-01',
'wr_start_weight': 0,
}
try:
lab.WaterRestriction().insert1(wrdata)
except dj.errors.DuplicateError:
print('duplicate. water restriction :', item[1]['animal#'],
' already exists')
def load_meta_foraging():
'''
Load metadata for the foraging task
Adapted from Marton's code: https://github.com/rozmar/DataPipeline/blob/master/ingest/datapipeline_metadata.py
'''
import pathlib
meta_dir = dj.config.get('custom', {}).get('behavior_bpod',
[]).get('meta_dir')
meta_lab_dir = dj.config.get('custom', {}).get('behavior_bpod',
[]).get('meta_lab_dir')
# --- Add experimenters ---
print('Adding experimenters...')
df_experimenters = pd.read_csv(
pathlib.Path(meta_lab_dir) / 'Experimenter.csv')
duplicate_num = 0
for experimenter in df_experimenters.iterrows():
experimenter = experimenter[1]
experimenternow = {
'username': experimenter['username'],
'fullname': experimenter['fullname']
}
try:
lab.Person().insert1(experimenternow)
print(' added experimenter: ', experimenternow['username'])
except dj.errors.DuplicateError:
duplicate_num += 1
# print(' duplicate. experimenter: ',experimenternow['username'], ' already exists')
print(f' {duplicate_num} experimenters already exist')
# --- Add rigs ---
print('Adding rigs... ')
df_rigs = pd.read_csv(pathlib.Path(meta_lab_dir) / 'Rig.csv')
duplicate_num = 0
for rig in df_rigs.iterrows():
rig = rig[1]
rignow = {
'rig': rig['rig'],
'room': rig['room'],
'rig_description': rig['rig_description']
}
try:
lab.Rig().insert1(rignow)
print(' added rig: ', rignow['rig'])
except dj.errors.DuplicateError:
duplicate_num += 1
# print(' duplicate. rig: ',rignow['rig'], ' already exists')
print(f' {duplicate_num} rigs already exist')
# --- Add viruses ---
# Not implemented for now. Han
# --- Add subjects and water restrictions ---
print('Adding subjects and water restrictions...')
df_surgery = pd.read_csv(pathlib.Path(meta_dir) / 'Surgery.csv')
# For each entry
duplicate_subject_num = 0
duplicate_WR_num = 0
for item in df_surgery.iterrows():
item = item[1]
if item['project'] == 'foraging' and (item['status'] == 'training' or
item['status'] == 'sacrificed'):
# -- Add lab.Subject() --
subjectdata = {
'subject_id': item['animal#'],
'cage_number': item['cage#'],
'date_of_birth': item['DOB'],
'sex': item['sex'],
'username': item['experimenter'],
}
try:
lab.Subject().insert1(subjectdata)
print(' added subject: ', item['animal#'])
except dj.errors.DuplicateError:
duplicate_subject_num += 1
# print(' duplicate. animal :',item['animal#'], ' already exists')
# -- Add lab.Surgery() --
# Not implemented. Han
# -- Virus injection --
# Not implemented. Han
# -- Add lab.WaterRestriction() --
if item['ID']:
# Get water restriction start date and weight
subject_csv = pathlib.Path(meta_dir) / '{}.csv'.format(
item['ID'])
if subject_csv.exists():
df_wr = pd.read_csv(subject_csv)
else:
print(' No metadata csv found for {}'.format(item['ID']))
continue
wrdata = {
'subject_id': item['animal#'],
'water_restriction_number': item['ID'],
'cage_number': item['cage#'],
'wr_start_date': df_wr['Date'][0],
'wr_start_weight': df_wr['Weight'][0],
}
try:
lab.WaterRestriction().insert1(wrdata)
print(' added WR: ', item['ID'])
except dj.errors.DuplicateError:
duplicate_WR_num += 1
# print(' duplicate. water restriction:', item['ID'], ' already exists')
print(
f' {duplicate_subject_num} subjects and {duplicate_WR_num} WRs already exist'
)
def mockdata():
print('populating with mock data')
reload(ccf)
reload(lab)
reload(experiment)
reload(ephys)
reload(publication)
try:
# TODO: these should be loaded in a more 'official' way
lab.Person().insert1({
'username': '******',
'fullname': 'Dave Liu'
},
skip_duplicates=True)
lab.ModifiedGene().insert1(
{
'gene_modification': 'VGAT-Chr2-EYFP Jax',
'gene_modification_description': 'VGAT'
},
skip_duplicates=True)
lab.ModifiedGene().insert1(
{
'gene_modification': 'PV-ires-Cre X Ai32',
'gene_modification_description': 'PV'
},
skip_duplicates=True)
lab.ModifiedGene().insert1(
{
'gene_modification':
'Rosa26 Cag lsl reachR-citrine 1A4 X PV-ires-Cre',
'gene_modification_description': 'reachR PV'
},
skip_duplicates=True)
lab.Subject().insert1(
{
'subject_id': 399752,
'username': '******',
'cage_number': 145375,
'date_of_birth': '2017-08-03',
'sex': 'M',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.Subject.GeneModification().insert1(
{
'subject_id': 399752,
'gene_modification': 'VGAT-Chr2-EYFP Jax'
},
skip_duplicates=True)
lab.Surgery().insert1(
{
'subject_id': 399752,
'surgery_id': 1,
'username': '******',
'start_time': '2017-11-03',
'end_time': '2017-11-03',
'surgery_description': 'Headbar anterior'
},
skip_duplicates=True)
lab.Surgery.Procedure().insert1(
{
'subject_id': 399752,
'surgery_id': 1,
'procedure_id': 1,
'skull_reference': 'Bregma',
'ml_location': 0,
'ap_location': -4,
'surgery_procedure_description': 'Fiducial marker'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 399752,
'water_restriction_number': 'dl7',
'cage_number': 148861,
'wr_start_date': '2017-11-07',
'wr_start_weight': 25
},
skip_duplicates=True)
lab.Subject().insert1(
{
'subject_id': 397853,
'username': '******',
'cage_number': 144545,
'date_of_birth': '2017-07-15',
'sex': 'M',
'animal_source': 'Allen Institute'
},
skip_duplicates=True)
lab.Subject.GeneModification().insert1(
{
'subject_id': 397853,
'gene_modification': 'PV-ires-Cre X Ai32'
},
skip_duplicates=True)
lab.Surgery().insert1(
{
'subject_id': 397853,
'surgery_id': 1,
'username': '******',
'start_time': '2017-11-20',
'end_time': '2017-11-20',
'surgery_description': 'Headbar posterior'
},
skip_duplicates=True)
lab.Surgery.Procedure().insert1(
{
'subject_id': 397853,
'surgery_id': 1,
'procedure_id': 1,
'skull_reference': 'Bregma',
'ml_location': 0,
'ap_location': -1.75,
'surgery_procedure_description': 'Fiducial marker'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 397853,
'water_restriction_number': 'dl14',
'cage_number': 149595,
'wr_start_date': '2017-11-27',
'wr_start_weight': 24.1
},
skip_duplicates=True)
lab.Subject().insert1(
{
'subject_id': 400480,
'username': '******',
'cage_number': 145700,
'date_of_birth': '2017-08-09',
'sex': 'M',
'animal_source': 'Allen Institute'
},
skip_duplicates=True)
lab.Subject.GeneModification().insert1(
{
'subject_id': 400480,
'gene_modification': 'PV-ires-Cre X Ai32'
},
skip_duplicates=True)
lab.Surgery().insert1(
{
'subject_id': 400480,
'surgery_id': 1,
'username': '******',
'start_time': '2017-11-21',
'end_time': '2017-11-21',
'surgery_description': 'Headbar posterior'
},
skip_duplicates=True)
lab.Surgery.Procedure().insert1(
{
'subject_id': 400480,
'surgery_id': 1,
'procedure_id': 1,
'skull_reference': 'Bregma',
'ml_location': 0,
'ap_location': -1.75,
'surgery_procedure_description': 'Fiducial marker'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 400480,
'water_restriction_number': 'dl15',
'cage_number': 149598,
'wr_start_date': '2017-11-27',
'wr_start_weight': 27.6
},
skip_duplicates=True)
lab.Subject().insert1(
{
'subject_id': 406680,
'username': '******',
'cage_number': 148859,
'date_of_birth': '2017-10-06',
'sex': 'F',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.Subject.GeneModification().insert1(
{
'subject_id': 406680,
'gene_modification': 'VGAT-Chr2-EYFP Jax'
},
skip_duplicates=True)
lab.Surgery().insert1(
{
'subject_id': 406680,
'surgery_id': 1,
'username': '******',
'start_time': '2018-01-04',
'end_time': '2018-01-04',
'surgery_description': 'Headbar posterior'
},
skip_duplicates=True)
lab.Surgery.Procedure().insert1(
{
'subject_id': 406680,
'surgery_id': 1,
'procedure_id': 1,
'skull_reference': 'Bregma',
'ml_location': 0,
'ap_location': -1.75,
'surgery_procedure_description': 'Fiducial marker'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 406680,
'water_restriction_number': 'dl20',
'cage_number': 151282,
'wr_start_date': '2018-01-10',
'wr_start_weight': 22.7
},
skip_duplicates=True)
lab.Subject().insert1(
{
'subject_id': 408022,
'username': '******',
'cage_number': 148859,
'date_of_birth': '2017-10-19',
'sex': 'F',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.Subject.GeneModification().insert1(
{
'subject_id': 408022,
'gene_modification': 'VGAT-Chr2-EYFP Jax'
},
skip_duplicates=True)
lab.Surgery().insert1(
{
'subject_id': 408022,
'surgery_id': 1,
'username': '******',
'start_time': '2018-01-05',
'end_time': '2018-01-05',
'surgery_description': 'Headbar posterior'
},
skip_duplicates=True)
lab.Surgery.Procedure().insert1(
{
'subject_id': 408022,
'surgery_id': 1,
'procedure_id': 1,
'skull_reference': 'Bregma',
'ml_location': 0,
'ap_location': -1.75,
'surgery_procedure_description': 'Fiducial marker'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 408022,
'water_restriction_number': 'dl21',
'cage_number': 151283,
'wr_start_date': '2018-01-10',
'wr_start_weight': 21.1
},
skip_duplicates=True)
lab.Subject().insert1(
{
'subject_id': 408021,
'username': '******',
'cage_number': 148859,
'date_of_birth': '2017-10-19',
'sex': 'F',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.Subject.GeneModification().insert1(
{
'subject_id': 408021,
'gene_modification': 'VGAT-Chr2-EYFP Jax'
},
skip_duplicates=True)
lab.Surgery().insert1(
{
'subject_id': 408021,
'surgery_id': 1,
'username': '******',
'start_time': '2018-01-15',
'end_time': '2018-01-15',
'surgery_description': 'Headbar posterior'
},
skip_duplicates=True)
lab.Surgery.Procedure().insert1(
{
'subject_id': 408021,
'surgery_id': 1,
'procedure_id': 1,
'skull_reference': 'Bregma',
'ml_location': 0,
'ap_location': -1.75,
'surgery_procedure_description': 'Fiducial marker'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 408021,
'water_restriction_number': 'dl22',
'cage_number': 151704,
'wr_start_date': '2018-01-19',
'wr_start_weight': 21
},
skip_duplicates=True)
lab.Subject().insert1(
{
'subject_id': 407512,
'username': '******',
'cage_number': 151629,
'date_of_birth': '2017-10-13',
'sex': 'M',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.Subject.GeneModification().insert1(
{
'subject_id': 407512,
'gene_modification': 'VGAT-Chr2-EYFP Jax'
},
skip_duplicates=True)
lab.Surgery().insert1(
{
'subject_id': 407512,
'surgery_id': 1,
'username': '******',
'start_time': '2018-01-16',
'end_time': '2018-01-16',
'surgery_description': 'Headbar posterior'
},
skip_duplicates=True)
lab.Surgery.Procedure().insert1(
{
'subject_id': 407512,
'surgery_id': 1,
'procedure_id': 1,
'skull_reference': 'Bregma',
'ml_location': 0,
'ap_location': -1.75,
'surgery_procedure_description': 'Fiducial marker'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 407512,
'water_restriction_number': 'dl24',
'cage_number': 151793,
'wr_start_date': '2018-01-22',
'wr_start_weight': 26
},
skip_duplicates=True)
lab.Subject().insert1(
{
'subject_id': 407513,
'username': '******',
'cage_number': 148636,
'date_of_birth': '2017-10-13',
'sex': 'M',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.Subject.GeneModification().insert1(
{
'subject_id': 407513,
'gene_modification': 'VGAT-Chr2-EYFP Jax'
},
skip_duplicates=True)
lab.Surgery().insert1(
{
'subject_id': 407513,
'surgery_id': 1,
'username': '******',
'start_time': '2018-01-17',
'end_time': '2018-01-17',
'surgery_description': 'Headbar posterior'
},
skip_duplicates=True)
lab.Surgery.Procedure().insert1(
{
'subject_id': 407513,
'surgery_id': 1,
'procedure_id': 1,
'skull_reference': 'Bregma',
'ml_location': 0,
'ap_location': -1.75,
'surgery_procedure_description': 'Fiducial marker'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 407513,
'water_restriction_number': 'dl25',
'cage_number': 151794,
'wr_start_date': '2018-01-22',
'wr_start_weight': 25.5
},
skip_duplicates=True)
lab.Subject().insert1(
{
'subject_id': 407986,
'username': '******',
'cage_number': 152268,
'date_of_birth': '2017-10-18',
'sex': 'F',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.Subject.GeneModification().insert1(
{
'subject_id': 407986,
'gene_modification': 'VGAT-Chr2-EYFP Jax'
},
skip_duplicates=True)
lab.Surgery().insert1(
{
'subject_id': 407986,
'surgery_id': 1,
'username': '******',
'start_time': '2018-02-01',
'end_time': '2018-02-01',
'surgery_description': 'Headbar anterior'
},
skip_duplicates=True)
lab.Surgery.Procedure().insert1(
{
'subject_id': 407986,
'surgery_id': 1,
'procedure_id': 1,
'skull_reference': 'Bregma',
'ml_location': 0,
'ap_location': -4,
'surgery_procedure_description': 'Fiducial marker'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 407986,
'water_restriction_number': 'dl28',
'cage_number': 152312,
'wr_start_date': '2018-02-05',
'wr_start_weight': 19.8
},
skip_duplicates=True)
lab.Subject().insert1(
{
'subject_id': 123457,
'username': '******',
'cage_number': 145375,
'date_of_birth': '2017-08-03',
'sex': 'M',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 123457,
'water_restriction_number': 'tw5',
'cage_number': 148861,
'wr_start_date': '2017-11-07',
'wr_start_weight': 20.5
},
skip_duplicates=True)
lab.Rig().insert1(
{
'rig': 'TRig1',
'room': '2w.334',
'rig_description': 'Training rig 1'
},
skip_duplicates=True)
lab.Rig().insert1(
{
'rig': 'TRig2',
'room': '2w.334',
'rig_description': 'Training rig 2'
},
skip_duplicates=True)
lab.Rig().insert1(
{
'rig': 'TRig3',
'room': '2w.334',
'rig_description': 'Training rig 3'
},
skip_duplicates=True)
lab.Rig().insert1(
{
'rig': 'RRig',
'room': '2w.334',
'rig_description': 'Recording rig'
},
skip_duplicates=True)
lab.Rig().insert1(
{
'rig': 'Ephys1',
'room': '2w.334',
'rig_description': 'Recording computer'
},
skip_duplicates=True)
except Exception as e:
print("error creating mock data: {e}".format(e=e), file=sys.stderr)
raise
def mockdata():
print('populating with mock data')
reload(lab)
reload(ccf)
reload(experiment)
reload(ephys)
reload(histology)
reload(tracking)
try:
lab.Person().insert1({
'username': '******',
'fullname': 'Unknown'
},
skip_duplicates=True)
lab.Person().insert1({
'username': '******',
'fullname': 'Dave Liu'
},
skip_duplicates=True)
lab.Person().insert1({
'username': '******',
'fullname': 'Susu Chen'
},
skip_duplicates=True)
lab.Person().insert1({
'username': '******',
'fullname': 'Thinh Nguyen'
},
skip_duplicates=True)
lab.ModifiedGene().insert1(
{
'gene_modification': 'VGAT-Chr2-EYFP Jax',
'gene_modification_description': 'VGAT'
},
skip_duplicates=True)
lab.ModifiedGene().insert1(
{
'gene_modification': 'PV-ires-Cre X Ai32',
'gene_modification_description': 'PV'
},
skip_duplicates=True)
lab.ModifiedGene().insert1(
{
'gene_modification':
'Rosa26 Cag lsl reachR-citrine 1A4 X PV-ires-Cre',
'gene_modification_description': 'reachR PV'
},
skip_duplicates=True)
# Subject 399752 / dl7
lab.Subject().insert1(
{
'subject_id': 399752,
'username': '******',
'cage_number': 145375,
'date_of_birth': '2017-08-03',
'sex': 'M',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.Subject.GeneModification().insert1(
{
'subject_id': 399752,
'gene_modification': 'VGAT-Chr2-EYFP Jax'
},
skip_duplicates=True)
lab.Surgery().insert1(
{
'subject_id': 399752,
'surgery_id': 1,
'username': '******',
'start_time': '2017-11-03',
'end_time': '2017-11-03',
'surgery_description': 'Headbar anterior'
},
skip_duplicates=True)
lab.Surgery.Procedure().insert1(
{
'subject_id': 399752,
'surgery_id': 1,
'procedure_id': 1,
'skull_reference': 'Bregma',
'ml_location': 0,
'ap_location': -4,
'surgery_procedure_description': 'Fiducial marker'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 399752,
'water_restriction_number': 'dl7',
'cage_number': 148861,
'wr_start_date': '2017-11-07',
'wr_start_weight': 25
},
skip_duplicates=True)
# Subject 397853 / dl14
lab.Subject().insert1(
{
'subject_id': 397853,
'username': '******',
'cage_number': 144545,
'date_of_birth': '2017-07-15',
'sex': 'M',
'animal_source': 'Allen Institute'
},
skip_duplicates=True)
lab.Subject.GeneModification().insert1(
{
'subject_id': 397853,
'gene_modification': 'PV-ires-Cre X Ai32'
},
skip_duplicates=True)
lab.Surgery().insert1(
{
'subject_id': 397853,
'surgery_id': 1,
'username': '******',
'start_time': '2017-11-20',
'end_time': '2017-11-20',
'surgery_description': 'Headbar posterior'
},
skip_duplicates=True)
lab.Surgery.Procedure().insert1(
{
'subject_id': 397853,
'surgery_id': 1,
'procedure_id': 1,
'skull_reference': 'Bregma',
'ml_location': 0,
'ap_location': -1.75,
'surgery_procedure_description': 'Fiducial marker'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 397853,
'water_restriction_number': 'dl14',
'cage_number': 149595,
'wr_start_date': '2017-11-27',
'wr_start_weight': 24.1
},
skip_duplicates=True)
# Subject 400480 / dl15
lab.Subject().insert1(
{
'subject_id': 400480,
'username': '******',
'cage_number': 145700,
'date_of_birth': '2017-08-09',
'sex': 'M',
'animal_source': 'Allen Institute'
},
skip_duplicates=True)
lab.Subject.GeneModification().insert1(
{
'subject_id': 400480,
'gene_modification': 'PV-ires-Cre X Ai32'
},
skip_duplicates=True)
lab.Surgery().insert1(
{
'subject_id': 400480,
'surgery_id': 1,
'username': '******',
'start_time': '2017-11-21',
'end_time': '2017-11-21',
'surgery_description': 'Headbar posterior'
},
skip_duplicates=True)
lab.Surgery.Procedure().insert1(
{
'subject_id': 400480,
'surgery_id': 1,
'procedure_id': 1,
'skull_reference': 'Bregma',
'ml_location': 0,
'ap_location': -1.75,
'surgery_procedure_description': 'Fiducial marker'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 400480,
'water_restriction_number': 'dl15',
'cage_number': 149598,
'wr_start_date': '2017-11-27',
'wr_start_weight': 27.6
},
skip_duplicates=True)
# Subject 406680 / dl20
lab.Subject().insert1(
{
'subject_id': 406680,
'username': '******',
'cage_number': 148859,
'date_of_birth': '2017-10-06',
'sex': 'F',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.Subject.GeneModification().insert1(
{
'subject_id': 406680,
'gene_modification': 'VGAT-Chr2-EYFP Jax'
},
skip_duplicates=True)
lab.Surgery().insert1(
{
'subject_id': 406680,
'surgery_id': 1,
'username': '******',
'start_time': '2018-01-04',
'end_time': '2018-01-04',
'surgery_description': 'Headbar posterior'
},
skip_duplicates=True)
lab.Surgery.Procedure().insert1(
{
'subject_id': 406680,
'surgery_id': 1,
'procedure_id': 1,
'skull_reference': 'Bregma',
'ml_location': 0,
'ap_location': -1.75,
'surgery_procedure_description': 'Fiducial marker'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 406680,
'water_restriction_number': 'dl20',
'cage_number': 151282,
'wr_start_date': '2018-01-10',
'wr_start_weight': 22.7
},
skip_duplicates=True)
# Subject 408022 / dl21
lab.Subject().insert1(
{
'subject_id': 408022,
'username': '******',
'cage_number': 148859,
'date_of_birth': '2017-10-19',
'sex': 'F',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.Subject.GeneModification().insert1(
{
'subject_id': 408022,
'gene_modification': 'VGAT-Chr2-EYFP Jax'
},
skip_duplicates=True)
lab.Surgery().insert1(
{
'subject_id': 408022,
'surgery_id': 1,
'username': '******',
'start_time': '2018-01-05',
'end_time': '2018-01-05',
'surgery_description': 'Headbar posterior'
},
skip_duplicates=True)
lab.Surgery.Procedure().insert1(
{
'subject_id': 408022,
'surgery_id': 1,
'procedure_id': 1,
'skull_reference': 'Bregma',
'ml_location': 0,
'ap_location': -1.75,
'surgery_procedure_description': 'Fiducial marker'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 408022,
'water_restriction_number': 'dl21',
'cage_number': 151283,
'wr_start_date': '2018-01-10',
'wr_start_weight': 21.1
},
skip_duplicates=True)
# Subject 408021 / dl22
lab.Subject().insert1(
{
'subject_id': 408021,
'username': '******',
'cage_number': 148859,
'date_of_birth': '2017-10-19',
'sex': 'F',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.Subject.GeneModification().insert1(
{
'subject_id': 408021,
'gene_modification': 'VGAT-Chr2-EYFP Jax'
},
skip_duplicates=True)
lab.Surgery().insert1(
{
'subject_id': 408021,
'surgery_id': 1,
'username': '******',
'start_time': '2018-01-15',
'end_time': '2018-01-15',
'surgery_description': 'Headbar posterior'
},
skip_duplicates=True)
lab.Surgery.Procedure().insert1(
{
'subject_id': 408021,
'surgery_id': 1,
'procedure_id': 1,
'skull_reference': 'Bregma',
'ml_location': 0,
'ap_location': -1.75,
'surgery_procedure_description': 'Fiducial marker'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 408021,
'water_restriction_number': 'dl22',
'cage_number': 151704,
'wr_start_date': '2018-01-19',
'wr_start_weight': 21
},
skip_duplicates=True)
# Subject 407512 / dl24
lab.Subject().insert1(
{
'subject_id': 407512,
'username': '******',
'cage_number': 151629,
'date_of_birth': '2017-10-13',
'sex': 'M',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.Subject.GeneModification().insert1(
{
'subject_id': 407512,
'gene_modification': 'VGAT-Chr2-EYFP Jax'
},
skip_duplicates=True)
lab.Surgery().insert1(
{
'subject_id': 407512,
'surgery_id': 1,
'username': '******',
'start_time': '2018-01-16',
'end_time': '2018-01-16',
'surgery_description': 'Headbar posterior'
},
skip_duplicates=True)
lab.Surgery.Procedure().insert1(
{
'subject_id': 407512,
'surgery_id': 1,
'procedure_id': 1,
'skull_reference': 'Bregma',
'ml_location': 0,
'ap_location': -1.75,
'surgery_procedure_description': 'Fiducial marker'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 407512,
'water_restriction_number': 'dl24',
'cage_number': 151793,
'wr_start_date': '2018-01-22',
'wr_start_weight': 26
},
skip_duplicates=True)
# 407513 / dl25
lab.Subject().insert1(
{
'subject_id': 407513,
'username': '******',
'cage_number': 148636,
'date_of_birth': '2017-10-13',
'sex': 'M',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.Subject.GeneModification().insert1(
{
'subject_id': 407513,
'gene_modification': 'VGAT-Chr2-EYFP Jax'
},
skip_duplicates=True)
lab.Surgery().insert1(
{
'subject_id': 407513,
'surgery_id': 1,
'username': '******',
'start_time': '2018-01-17',
'end_time': '2018-01-17',
'surgery_description': 'Headbar posterior'
},
skip_duplicates=True)
lab.Surgery.Procedure().insert1(
{
'subject_id': 407513,
'surgery_id': 1,
'procedure_id': 1,
'skull_reference': 'Bregma',
'ml_location': 0,
'ap_location': -1.75,
'surgery_procedure_description': 'Fiducial marker'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 407513,
'water_restriction_number': 'dl25',
'cage_number': 151794,
'wr_start_date': '2018-01-22',
'wr_start_weight': 25.5
},
skip_duplicates=True)
# Subject 407986 / dl28
lab.Subject().insert1(
{
'subject_id': 407986,
'username': '******',
'cage_number': 152268,
'date_of_birth': '2017-10-18',
'sex': 'F',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.Subject.GeneModification().insert1(
{
'subject_id': 407986,
'gene_modification': 'VGAT-Chr2-EYFP Jax'
},
skip_duplicates=True)
lab.Surgery().insert1(
{
'subject_id': 407986,
'surgery_id': 1,
'username': '******',
'start_time': '2018-02-01',
'end_time': '2018-02-01',
'surgery_description': 'Headbar anterior'
},
skip_duplicates=True)
lab.Surgery.Procedure().insert1(
{
'subject_id': 407986,
'surgery_id': 1,
'procedure_id': 1,
'skull_reference': 'Bregma',
'ml_location': 0,
'ap_location': -4,
'surgery_procedure_description': 'Fiducial marker'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 407986,
'water_restriction_number': 'dl28',
'cage_number': 152312,
'wr_start_date': '2018-02-05',
'wr_start_weight': 19.8
},
skip_duplicates=True)
# Subject 123457 / tw5
lab.Subject().insert1(
{
'subject_id': 123457,
'username': '******',
'cage_number': 145375,
'date_of_birth': '2017-08-03',
'sex': 'M',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 123457,
'water_restriction_number': 'tw5',
'cage_number': 148861,
'wr_start_date': '2017-11-07',
'wr_start_weight': 20.5
},
skip_duplicates=True)
# Subject 412330 / tw34
lab.Subject().insert1(
{
'subject_id': 412330,
'username': '******',
'cage_number': 154522,
'date_of_birth': '2017-12-05',
'sex': 'M',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 412330,
'water_restriction_number': 'tw34',
'cage_number': 154522,
'wr_start_date': '2018-03-18',
'wr_start_weight': 21.0
},
skip_duplicates=True)
# subject 432998 / dl55
lab.Subject().insert1(
{
'subject_id': 432998,
'username': '******',
'cage_number': 160920,
'date_of_birth': '2018-07-02',
'sex': 'M',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 432998,
'water_restriction_number': 'dl55',
'cage_number': 160920,
'wr_start_date': '2018-09-05',
'wr_start_weight': 21.0
},
skip_duplicates=True)
# Subject 435884 / dl59
lab.Subject().insert1(
{
'subject_id': 435884,
'username': '******',
'cage_number': 161908,
'date_of_birth': '2018-08-06',
'sex': 'M',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 435884,
'water_restriction_number': 'dl59',
'cage_number': 154522,
'wr_start_date': '2018-09-30',
'wr_start_weight': 21.0
},
skip_duplicates=True)
# Subject 432572 / dl56
lab.Subject().insert1(
{
'subject_id': 432572,
'username': '******',
'cage_number': 161125,
'date_of_birth': '2018-06-28',
'sex': 'M',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 432572,
'water_restriction_number': 'dl56',
'cage_number': 161125,
'wr_start_date': '2018-09-10',
'wr_start_weight': 21.0
},
skip_duplicates=True)
# Subject 412753 / dl36
lab.Subject().insert1(
{
'subject_id': 412753,
'username': '******',
'cage_number': 154570,
'date_of_birth': '2017-12-07',
'sex': 'M',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 412753,
'water_restriction_number': 'dl36',
'cage_number': 154570,
'wr_start_date': '2017-03-30',
'wr_start_weight': 21.0
},
skip_duplicates=True)
# Subject 440010 / dl62
lab.Subject().insert1(
{
'subject_id': 440010,
'username': '******',
'cage_number': 163782,
'date_of_birth': '2018-09-24',
'sex': 'M',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 440010,
'water_restriction_number': 'dl62',
'cage_number': 163782,
'wr_start_date': '2018-11-24',
'wr_start_weight': 23.0
},
skip_duplicates=True)
# Subject 55004 / DL004
lab.Subject().insert1(
{
'subject_id': 550004,
'username': '******',
'cage_number': 163782,
'date_of_birth': '2018-09-24',
'sex': 'M',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 550004,
'water_restriction_number': 'DL004',
'cage_number': 163782,
'wr_start_date': '2018-11-24',
'wr_start_weight': 23.0
},
skip_duplicates=True)
# Subject 550009 / DL009
lab.Subject().insert1(
{
'subject_id': 550009,
'username': '******',
'cage_number': 163782,
'date_of_birth': '2018-09-24',
'sex': 'M',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 550009,
'water_restriction_number': 'DL009',
'cage_number': 163782,
'wr_start_date': '2018-11-24',
'wr_start_weight': 23.0
},
skip_duplicates=True)
# Subject 550010 / DL010
lab.Subject().insert1(
{
'subject_id': 550010,
'username': '******',
'cage_number': 163782,
'date_of_birth': '2018-09-24',
'sex': 'M',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 550010,
'water_restriction_number': 'DL010',
'cage_number': 163782,
'wr_start_date': '2018-11-24',
'wr_start_weight': 23.0
},
skip_duplicates=True)
# Subject 550022 / DL022
lab.Subject().insert1(
{
'subject_id': 550022,
'username': '******',
'cage_number': 163782,
'date_of_birth': '2018-09-24',
'sex': 'M',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 550022,
'water_restriction_number': 'DL022',
'cage_number': 163782,
'wr_start_date': '2018-11-24',
'wr_start_weight': 23.0
},
skip_duplicates=True)
# Subject 440959 / SC011
lab.Subject().insert1(
{
'subject_id': 440959,
'username': '******',
'cage_number': 440959,
'date_of_birth': '2018-10-09',
'sex': 'M',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 440959,
'water_restriction_number': 'SC011',
'cage_number': 440959,
'wr_start_date': '2018-12-21',
'wr_start_weight': 22.8
},
skip_duplicates=True)
# Subject 442571 / SC022
lab.Subject().insert1(
{
'subject_id': 442571,
'username': '******',
'cage_number': 442571,
'date_of_birth': '2018-10-29',
'sex': 'M',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 442571,
'water_restriction_number': 'SC022',
'cage_number': 442571,
'wr_start_date': '2019-01-02',
'wr_start_weight': 26.5
},
skip_duplicates=True)
# Subject 460432 / SC030
lab.Subject().insert1(
{
'subject_id': 456773,
'username': '******',
'cage_number': 171857,
'date_of_birth': '2019-05-29',
'sex': 'M',
'animal_source': 'Jackson Labs'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 456773,
'water_restriction_number': 'SC030',
'cage_number': 171857,
'wr_start_date': '2019-08-08',
'wr_start_weight': 25.700
},
skip_duplicates=True)
# Subject 460432 / SC032
lab.Subject().insert1(
{
'subject_id': 460432,
'username': '******',
'cage_number': 173167,
'date_of_birth': '2019-07-15',
'sex': 'M',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 460432,
'water_restriction_number': 'SC032',
'cage_number': 173167,
'wr_start_date': '2019-09-20',
'wr_start_weight': 22.8
},
skip_duplicates=True)
for num in range(1, 20):
lab.Subject().insert1(
{
'subject_id': 777000 + num,
'username': '******',
'cage_number': 173167,
'date_of_birth': '2019-07-15',
'sex': 'M',
'animal_source': 'Jackson labs'
},
skip_duplicates=True)
lab.WaterRestriction().insert1(
{
'subject_id': 777000 + num,
'water_restriction_number': 'FOR' + f'{num:02}',
'cage_number': 173167,
'wr_start_date': '2019-09-20',
'wr_start_weight': 22.8
},
skip_duplicates=True)
# Rig
lab.Rig().insert1(
{
'rig': 'TRig1',
'room': '2w.334',
'rig_description': 'Training rig 1'
},
skip_duplicates=True)
lab.Rig().insert1(
{
'rig': 'TRig2',
'room': '2w.334',
'rig_description': 'Training rig 2'
},
skip_duplicates=True)
lab.Rig().insert1(
{
'rig': 'TRig3',
'room': '2w.334',
'rig_description': 'Training rig 3'
},
skip_duplicates=True)
lab.Rig().insert1(
{
'rig': 'RRig',
'room': '2w.334',
'rig_description': 'Recording rig'
},
skip_duplicates=True)
lab.Rig().insert1(
{
'rig': 'RRig2',
'room': '2w.334',
'rig_description': 'Recording rig2'
},
skip_duplicates=True)
lab.Rig().insert1(
{
'rig': 'RRig3',
'room': '2w.334',
'rig_description': 'Recording rig3 for multi-target-licking'
},
skip_duplicates=True)
lab.Rig().insert1(
{
'rig': 'Ephys1',
'room': '2w.334',
'rig_description': 'Recording computer'
},
skip_duplicates=True)
lab.ProbeType.create_neuropixels_probe()
except Exception as e:
print("error creating mock data: {e}".format(e=e), file=sys.stderr)
raise
