def test_03_alignments_disagree(self):
alignments = {
'2020-06-26T16:40:14_Karolina_Socha':
self.alignments['2020-06-26T16:40:14_Karolina_Socha'],
'2020-06-12T00:39:15_nate':
self.alignments['2020-06-12T00:39:15_nate']
}
trajectory = copy.deepcopy(self.trajectory)
trajectory.update({'json': alignments})
traj = one.alyx.rest('trajectories',
'update',
id=self.prev_traj_id,
data=trajectory)
traj_id = traj['id']
align_qc = AlignmentQC(self.probe_id,
one=one,
brain_atlas=brain_atlas,
channels=False)
insertion = one.alyx.rest('insertions', 'read', id=self.probe_id)
align_qc.load_data(prev_alignments=traj['json'],
xyz_picks=np.array(self.xyz_picks) / 1e6,
cluster_chns=self.cluster_chns)
align_qc.run(update=True, upload_alyx=True, upload_flatiron=False)
insertion = one.alyx.rest('insertions', 'read', id=self.probe_id)
assert (insertion['json']['qc'] == 'NOT_SET')
assert (insertion['json']['extended_qc']['alignment_count'] == 2)
assert (insertion['json']['extended_qc']['alignment_stored'] ==
'2020-06-26T16:40:14_Karolina_Socha')
assert (insertion['json']['extended_qc']['alignment_resolved'] == 0)
assert (insertion['json']['extended_qc']['alignment_qc'] < 0.8)
traj = one.alyx.rest('trajectories',
'list',
probe_id=self.probe_id,
provenance='Ephys aligned histology track')
assert (traj_id == traj[0]['id'])
def test_05_not_latest_alignments_agree(self):
alignments = copy.deepcopy(self.alignments)
trajectory = copy.deepcopy(self.trajectory)
trajectory.update({'json': alignments})
traj = one.alyx.rest('trajectories',
'update',
id=self.prev_traj_id,
data=trajectory)
assert (self.prev_traj_id == traj['id'])
align_qc = AlignmentQC(self.probe_id,
one=one,
brain_atlas=brain_atlas,
channels=False)
align_qc.load_data(prev_alignments=traj['json'],
xyz_picks=np.array(self.xyz_picks) / 1e6,
cluster_chns=self.cluster_chns)
align_qc.resolved = 0
align_qc.run(update=True, upload_alyx=True, upload_flatiron=False)
insertion = one.alyx.rest('insertions', 'read', id=self.probe_id)
assert (insertion['json']['qc'] == 'NOT_SET')
assert (insertion['json']['extended_qc']['alignment_count'] == 4)
assert (insertion['json']['extended_qc']['alignment_stored'] ==
'2020-06-19T10:52:36_noam.roth')
assert (insertion['json']['extended_qc']['alignment_resolved'] == 1)
assert (
insertion['json']['extended_qc']['alignment_resolved_by'] == 'qc')
assert (insertion['json']['extended_qc']['alignment_qc'] > 0.8)
assert (np.isclose(insertion['json']['extended_qc']['alignment_qc'],
0.952319))
traj = one.alyx.rest('trajectories',
'list',
probe_id=self.probe_id,
provenance='Ephys aligned histology track')
assert (self.prev_traj_id != traj[0]['id'])
def setUpClass(cls) -> None:
data = np.load(Path(
Path(__file__).parent.parent.joinpath(
'fixtures', 'qc', 'data_alignmentqc_manual.npz')),
allow_pickle=True)
cls.xyz_picks = (data['xyz_picks'] * 1e6).tolist()
cls.alignments = data['alignments'].tolist()
cls.cluster_chns = data['cluster_chns']
data = np.load(Path(
Path(__file__).parent.parent.joinpath(
'fixtures', 'qc', 'data_alignmentqc_existing.npz')),
allow_pickle=True)
insertion = data['insertion'].tolist()
insertion['json'] = {'xyz_picks': cls.xyz_picks}
probe_insertion = one.alyx.rest('insertions', 'create', data=insertion)
cls.probe_id = probe_insertion['id']
cls.probe_name = probe_insertion['name']
cls.trajectory = data['trajectory'].tolist()
cls.trajectory.update({'probe_insertion': cls.probe_id})
cls.trajectory.update({'json': cls.alignments})
cls.traj = one.alyx.rest('trajectories', 'create', data=cls.trajectory)
align_qc = AlignmentQC(cls.probe_id,
one=one,
brain_atlas=brain_atlas,
channels=False)
align_qc.load_data(prev_alignments=cls.traj['json'],
xyz_picks=np.array(cls.xyz_picks) / 1e6,
cluster_chns=cls.cluster_chns)
cls.file_paths = align_qc.resolve_manual('2020-09-28T15:57:25_mayo',
update=True,
upload_alyx=True,
upload_flatiron=True)
print(cls.file_paths)
def test_03_manual_resolution_not_latest(self):
align_qc = AlignmentQC(self.probe_id,
one=one,
brain_atlas=brain_atlas,
channels=False)
align_qc.load_data(prev_alignments=self.traj['json'],
xyz_picks=np.array(self.xyz_picks) / 1e6,
cluster_chns=self.cluster_chns)
align_qc.resolve_manual('2020-09-28T10:03:06_alejandro',
update=True,
upload_alyx=True,
upload_flatiron=False,
force=True)
insertion = one.alyx.rest('insertions', 'read', id=self.probe_id)
assert (insertion['json']['qc'] == 'NOT_SET')
assert (insertion['json']['extended_qc']['alignment_count'] == 3)
assert (insertion['json']['extended_qc']['alignment_stored'] ==
'2020-09-28T10:03:06_alejandro')
assert (insertion['json']['extended_qc']['alignment_resolved'] == 1)
assert (insertion['json']['extended_qc']['alignment_resolved_by'] ==
'experimenter')
assert (insertion['json']['extended_qc']['alignment_qc'] < 0.8)
assert (np.isclose(insertion['json']['extended_qc']['alignment_qc'],
0.604081))
traj = one.alyx.rest('trajectories',
'list',
probe_id=self.probe_id,
provenance='Ephys aligned histology track')
assert (self.prev_traj_id != traj[0]['id'])
def _05_not_latest_alignments_agree(self):
alignments = copy.deepcopy(self.alignments)
trajectory = copy.deepcopy(self.trajectory)
trajectory.update({'json': alignments})
traj = one.alyx.rest('trajectories',
'update',
id=self.prev_traj_id,
data=trajectory)
self.assertEqual(self.prev_traj_id, traj['id'])
align_qc = AlignmentQC(self.probe_id,
one=one,
brain_atlas=brain_atlas,
channels=False)
align_qc.load_data(prev_alignments=traj['json'],
xyz_picks=np.array(self.xyz_picks) / 1e6,
cluster_chns=self.cluster_chns,
depths=SITES_COORDINATES[:, 1],
chn_coords=SITES_COORDINATES)
align_qc.resolved = 0
align_qc.run(update=True, upload_alyx=True, upload_flatiron=False)
_verify(self,
alignment_resolved='qc',
alignment_qc=0.952319,
alignment_count=4,
alignment_stored='2020-06-19T10:52:36_noam.roth',
trajectory_created=True)
def _04_alignments_agree(self):
alignments = {
'2020-06-19T10:52:36_noam.roth':
self.alignments['2020-06-19T10:52:36_noam.roth'],
'2020-06-12T00:39:15_nate':
self.alignments['2020-06-12T00:39:15_nate']
}
trajectory = copy.deepcopy(self.trajectory)
trajectory.update({'json': alignments})
traj = one.alyx.rest('trajectories',
'update',
id=self.prev_traj_id,
data=trajectory)
assert (self.prev_traj_id == traj['id'])
align_qc = AlignmentQC(self.probe_id,
one=one,
brain_atlas=brain_atlas,
channels=False)
align_qc.load_data(cluster_chns=self.cluster_chns,
depths=SITES_COORDINATES[:, 1],
chn_coords=SITES_COORDINATES)
align_qc.run(update=True, upload_alyx=True, upload_flatiron=False)
_verify(self,
alignment_resolved='qc',
alignment_qc=0.952319,
trajectory_created=False,
alignment_count=2,
alignment_stored='2020-06-19T10:52:36_noam.roth')
def _03_alignments_disagree(self):
alignments = {
'2020-06-26T16:40:14_Karolina_Socha':
self.alignments['2020-06-26T16:40:14_Karolina_Socha'],
'2020-06-12T00:39:15_nate':
self.alignments['2020-06-12T00:39:15_nate']
}
trajectory = copy.deepcopy(self.trajectory)
trajectory.update({'json': alignments})
traj = one.alyx.rest('trajectories',
'update',
id=self.prev_traj_id,
data=trajectory)
align_qc = AlignmentQC(self.probe_id,
one=one,
brain_atlas=brain_atlas,
channels=False)
align_qc.load_data(prev_alignments=traj['json'],
xyz_picks=np.array(self.xyz_picks) / 1e6,
cluster_chns=self.cluster_chns,
depths=SITES_COORDINATES[:, 1],
chn_coords=SITES_COORDINATES)
align_qc.run(update=True, upload_alyx=True, upload_flatiron=False)
_verify(self,
alignment_qc=0.782216,
alignment_resolved=False,
alignment_count=2,
alignment_stored='2020-06-26T16:40:14_Karolina_Socha',
trajectory_created=False)
def test_04_alignments_agree(self):
alignments = {
'2020-06-19T10:52:36_noam.roth':
self.alignments['2020-06-19T10:52:36_noam.roth'],
'2020-06-12T00:39:15_nate':
self.alignments['2020-06-12T00:39:15_nate']
}
trajectory = copy.deepcopy(self.trajectory)
trajectory.update({'json': alignments})
traj = one.alyx.rest('trajectories',
'update',
id=self.prev_traj_id,
data=trajectory)
assert (self.prev_traj_id == traj['id'])
align_qc = AlignmentQC(self.probe_id,
one=one,
brain_atlas=brain_atlas,
channels=False)
align_qc.load_data(cluster_chns=self.cluster_chns)
align_qc.run(update=True, upload_alyx=True, upload_flatiron=False)
insertion = one.alyx.rest('insertions', 'read', id=self.probe_id)
assert (insertion['json']['qc'] == 'NOT_SET')
assert (insertion['json']['extended_qc']['alignment_count'] == 2)
assert (insertion['json']['extended_qc']['alignment_stored'] ==
'2020-06-19T10:52:36_noam.roth')
assert (insertion['json']['extended_qc']['alignment_resolved'] == 1)
assert (
insertion['json']['extended_qc']['alignment_resolved_by'] == 'qc')
assert (insertion['json']['extended_qc']['alignment_qc'] > 0.8)
traj = one.alyx.rest('trajectories',
'list',
probe_id=self.probe_id,
provenance='Ephys aligned histology track')
assert (self.prev_traj_id == traj[0]['id'])
def test_01_no_alignments(self):
align_qc = AlignmentQC(self.probe_id,
one=one,
brain_atlas=brain_atlas,
channels=False)
align_qc.run(update=True, upload_alyx=True, upload_flatiron=False)
insertion = one.alyx.rest('insertions', 'read', id=self.probe_id)
assert (insertion['json']['qc'] == 'NOT_SET')
assert (len(insertion['json']['extended_qc']) == 0)
def _01_no_alignments(self):
align_qc = AlignmentQC(self.probe_id,
one=one,
brain_atlas=brain_atlas,
channels=False)
align_qc.run(update=True, upload_alyx=True, upload_flatiron=False)
insertion = one.alyx.get(f'/insertions/{self.probe_id}', clobber=True)
self.assertEqual('NOT_SET', insertion['json']['qc'])
self.assertTrue(len(insertion['json']['extended_qc']) == 0)
def update_qc(self, upload_alyx=True, upload_flatiron=True):
# if resolved just update the alignment_number
align_qc = AlignmentQC(self.probe_id, one=self.one, brain_atlas=self.brain_atlas)
align_qc.load_data(prev_alignments=self.alignments, xyz_picks=self.xyz_picks,
depths=self.chn_depths, cluster_chns=self.cluster_chns)
results = align_qc.run(update=True, upload_alyx=upload_alyx,
upload_flatiron=upload_flatiron)
align_qc.update_experimenter_evaluation(prev_alignments=self.alignments)
self.resolved = results['alignment_resolved']
return self.resolved
def test_02_one_alignment(self):
alignments = {'2020-06-26T16:40:14_Karolina_Socha':
self.alignments['2020-06-26T16:40:14_Karolina_Socha']}
trajectory = copy.deepcopy(self.trajectory)
trajectory.update({'json': alignments})
_ = one.alyx.rest('trajectories', 'create', data=trajectory)
align_qc = AlignmentQC(self.probe_id, one=one, brain_atlas=brain_atlas, channels=False)
align_qc.run(update=True, upload_alyx=True, upload_flatiron=False)
insertion = one.alyx.rest('insertions', 'read', id=self.probe_id)
assert (insertion['json']['qc'] == 'NOT_SET')
assert (insertion['json']['extended_qc']['alignment_count'] == 1)
assert (insertion['json']['extended_qc']['alignment_stored'] ==
'2020-06-26T16:40:14_Karolina_Socha')
assert (insertion['json']['extended_qc']['alignment_resolved'] == 0)
def test_01_normal_computation(self):
align_qc = AlignmentQC(self.probe_id, one=one, brain_atlas=brain_atlas, channels=False)
align_qc.load_data(prev_alignments=self.traj['json'],
xyz_picks=np.array(self.xyz_picks) / 1e6,
cluster_chns=self.cluster_chns)
align_qc.run(update=True, upload_alyx=True, upload_flatiron=False)
insertion = one.alyx.rest('insertions', 'read', id=self.probe_id)
assert (insertion['json']['qc'] == 'NOT_SET')
assert (insertion['json']['extended_qc']['alignment_count'] == 3)
assert (insertion['json']['extended_qc']['alignment_stored'] ==
'2020-09-28T15:57:25_mayo')
assert (insertion['json']['extended_qc']['alignment_resolved'] == 0)
assert (insertion['json']['extended_qc']['alignment_qc'] < 0.8)
traj = one.alyx.rest('trajectories', 'list', probe_id=self.probe_id,
provenance='Ephys aligned histology track')
assert(self.prev_traj_id == traj[0]['id'])
def _01_normal_computation(self):
align_qc = AlignmentQC(self.probe_id,
one=one,
brain_atlas=brain_atlas,
channels=False)
align_qc.load_data(prev_alignments=self.traj['json'],
xyz_picks=np.array(self.xyz_picks) / 1e6,
cluster_chns=self.cluster_chns,
depths=SITES_COORDINATES[:, 1],
chn_coords=SITES_COORDINATES)
align_qc.run(update=True, upload_alyx=True, upload_flatiron=False)
_verify(self,
alignment_resolved=False,
alignment_stored='2020-09-28T15:57:25_mayo',
alignment_count=3,
trajectory_created=False,
alignment_qc=0.604081)
def _02_one_alignment(self):
alignments = {
'2020-06-26T16:40:14_Karolina_Socha':
self.alignments['2020-06-26T16:40:14_Karolina_Socha']
}
trajectory = copy.deepcopy(self.trajectory)
trajectory.update({'json': alignments})
_ = one.alyx.rest('trajectories', 'create', data=trajectory)
align_qc = AlignmentQC(self.probe_id,
one=one,
brain_atlas=brain_atlas,
channels=False)
align_qc.run(update=True, upload_alyx=True, upload_flatiron=False)
_verify(self,
alignment_count=1,
alignment_stored='2020-06-26T16:40:14_Karolina_Socha',
alignment_resolved=False)
def _03_manual_resolution_not_latest(self):
align_qc = AlignmentQC(self.probe_id,
one=one,
brain_atlas=brain_atlas,
channels=False)
align_qc.load_data(prev_alignments=self.traj['json'],
xyz_picks=np.array(self.xyz_picks) / 1e6,
cluster_chns=self.cluster_chns,
depths=SITES_COORDINATES[:, 1],
chn_coords=SITES_COORDINATES)
align_qc.resolve_manual('2020-09-28T10:03:06_alejandro',
update=True,
upload_alyx=True,
upload_flatiron=False,
force=True)
_verify(self,
alignment_resolved='experimenter',
alignment_stored='2020-09-28T10:03:06_alejandro',
alignment_count=3,
trajectory_created=True,
alignment_qc=0.604081)
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Oct 28 08:57:24 2020
@author: guido
"""
from oneibl.one import ONE
one = ONE()
probe_id = one.alyx.rest('insertions', 'list', subject='SWC_014', date='2019-12-10', name='probe01')[0]['id']
traj = one.alyx.rest('trajectories', 'list', probe_insertion=probe_id, provenance='Ephys aligned histology track')[0]
alignment_keys = traj['json'].keys()
print(alignment_keys)
from ibllib.qc.alignment_qc import AlignmentQC
align_key = "2020-06-15T10:03:50_guido" # change this to your chosen alignment key
align_qc = AlignmentQC(probe_id, one=one)
align_qc.resolve_manual(align_key)
from oneibl.one import ONE
one = ONE()
probe_id = one.alyx.rest('insertions', 'list', subject='SWC_014', date='2019-12-10', name='probe01')[0]['id']
align_key = '2020-06-15T10:03:50_guido'
from ibllib.qc.alignment_qc import AlignmentQC
align_qc = AlignmentQC(probe_id, one=one)
align_qc.resolve_manual(align_key, force=True)