ibllib.pipes.ephys_tasks
Classes
This mixin class is used to compute the cell QC metrics and update the json field of the probe insertion The compute_cell_qc method is static and can be used independently. |
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Compresses NP2.4 data by splitting into N binary files, corresponding to N shanks |
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Extract Pulses from raw electrophysiology data into numpy arrays Perform the probes synchronisation with nidq (3B) or main probe (3A) First the job extract the sync pulses from the synchronisation task in all probes, and then perform the synchronisation with the nidq |
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Creates the probe insertions and uploads the probe descriptions file, also compresses the nidq files and uploads |
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Task to rename, compress and register raw daq data with .bin format collected using NIDAQ |
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Pykilosort 2.5 pipeline |
- class EphysRegisterRaw(session_path, **kwargs)[source]
Bases:
DynamicTask
Creates the probe insertions and uploads the probe descriptions file, also compresses the nidq files and uploads
- priority = 100
- job_size = 'small'
- property signature
dict() -> new empty dictionary dict(mapping) -> new dictionary initialized from a mapping object’s
(key, value) pairs
- dict(iterable) -> new dictionary initialized as if via:
d = {} for k, v in iterable:
d[k] = v
- dict(**kwargs) -> new dictionary initialized with the name=value pairs
in the keyword argument list. For example: dict(one=1, two=2)
- class EphysSyncRegisterRaw(session_path, **kwargs)[source]
Bases:
DynamicTask
Task to rename, compress and register raw daq data with .bin format collected using NIDAQ
- priority = 90
- cpu = 2
- io_charge = 30
- job_size = 'small'
- property signature
dict() -> new empty dictionary dict(mapping) -> new dictionary initialized from a mapping object’s
(key, value) pairs
- dict(iterable) -> new dictionary initialized as if via:
d = {} for k, v in iterable:
d[k] = v
- dict(**kwargs) -> new dictionary initialized with the name=value pairs
in the keyword argument list. For example: dict(one=1, two=2)
- class EphysCompressNP1(session_path, **kwargs)[source]
Bases:
EphysTask
- priority = 90
- cpu = 2
- io_charge = 100
- job_size = 'small'
- property signature
dict() -> new empty dictionary dict(mapping) -> new dictionary initialized from a mapping object’s
(key, value) pairs
- dict(iterable) -> new dictionary initialized as if via:
d = {} for k, v in iterable:
d[k] = v
- dict(**kwargs) -> new dictionary initialized with the name=value pairs
in the keyword argument list. For example: dict(one=1, two=2)
- class EphysCompressNP21(session_path, **kwargs)[source]
Bases:
EphysTask
- priority = 90
- cpu = 2
- io_charge = 100
- job_size = 'large'
- property signature
dict() -> new empty dictionary dict(mapping) -> new dictionary initialized from a mapping object’s
(key, value) pairs
- dict(iterable) -> new dictionary initialized as if via:
d = {} for k, v in iterable:
d[k] = v
- dict(**kwargs) -> new dictionary initialized with the name=value pairs
in the keyword argument list. For example: dict(one=1, two=2)
- class EphysCompressNP24(session_path, *args, pname=None, device_collection='raw_ephys_data', nshanks=None, **kwargs)[source]
Bases:
EphysTask
Compresses NP2.4 data by splitting into N binary files, corresponding to N shanks
- Parameters:
pname – a probe name string
device_collection – the collection containing the probes (usually ‘raw_ephys_data’)
nshanks – number of shanks used (usually 4 but it may be less depending on electrode map), optional
- priority = 90
- cpu = 2
- io_charge = 100
- job_size = 'large'
- property signature
dict() -> new empty dictionary dict(mapping) -> new dictionary initialized from a mapping object’s
(key, value) pairs
- dict(iterable) -> new dictionary initialized as if via:
d = {} for k, v in iterable:
d[k] = v
- dict(**kwargs) -> new dictionary initialized with the name=value pairs
in the keyword argument list. For example: dict(one=1, two=2)
- class EphysSyncPulses(session_path, **kwargs)[source]
Bases:
SyncPulses
- priority = 90
- cpu = 2
- io_charge = 30
- job_size = 'small'
- property signature
dict() -> new empty dictionary dict(mapping) -> new dictionary initialized from a mapping object’s
(key, value) pairs
- dict(iterable) -> new dictionary initialized as if via:
d = {} for k, v in iterable:
d[k] = v
- dict(**kwargs) -> new dictionary initialized with the name=value pairs
in the keyword argument list. For example: dict(one=1, two=2)
- class EphysPulses(*args, **kwargs)[source]
Bases:
EphysTask
Extract Pulses from raw electrophysiology data into numpy arrays Perform the probes synchronisation with nidq (3B) or main probe (3A) First the job extract the sync pulses from the synchronisation task in all probes, and then perform the
synchronisation with the nidq
- Parameters:
pname – a list of probes names or a single probe name string
device_collection – the collection containing the probes (usually ‘raw_ephys_data’)
sync_collection – the collection containing the synchronisation device - nidq (usually ‘raw_ephys_data’)
- priority = 90
- cpu = 2
- io_charge = 30
- job_size = 'small'
- property signature
dict() -> new empty dictionary dict(mapping) -> new dictionary initialized from a mapping object’s
(key, value) pairs
- dict(iterable) -> new dictionary initialized as if via:
d = {} for k, v in iterable:
d[k] = v
- dict(**kwargs) -> new dictionary initialized with the name=value pairs
in the keyword argument list. For example: dict(one=1, two=2)
- class RawEphysQC(session_path, **kwargs)[source]
Bases:
EphysTask
- cpu = 2
- io_charge = 30
- priority = 10
- job_size = 'small'
- property signature
dict() -> new empty dictionary dict(mapping) -> new dictionary initialized from a mapping object’s
(key, value) pairs
- dict(iterable) -> new dictionary initialized as if via:
d = {} for k, v in iterable:
d[k] = v
- dict(**kwargs) -> new dictionary initialized with the name=value pairs
in the keyword argument list. For example: dict(one=1, two=2)
- class CellQCMixin[source]
Bases:
object
This mixin class is used to compute the cell QC metrics and update the json field of the probe insertion The compute_cell_qc method is static and can be used independently.
- class SpikeSorting(session_path, **kwargs)[source]
Bases:
EphysTask
,CellQCMixin
Pykilosort 2.5 pipeline
- gpu = 1
- io_charge = 100
- priority = 60
- job_size = 'large'
- force = True
- SHELL_SCRIPT = PosixPath('/home/runner/Documents/PYTHON/iblscripts/deploy/serverpc/iblsorter/run_iblsorter.sh')
- SPIKE_SORTER_NAME = 'iblsorter'
- PYKILOSORT_REPO = PosixPath('/home/runner/Documents/PYTHON/SPIKE_SORTING/ibl-sorter')
- property signature
dict() -> new empty dictionary dict(mapping) -> new dictionary initialized from a mapping object’s
(key, value) pairs
- dict(iterable) -> new dictionary initialized as if via:
d = {} for k, v in iterable:
d[k] = v
- dict(**kwargs) -> new dictionary initialized with the name=value pairs
in the keyword argument list. For example: dict(one=1, two=2)
- class EphysCellsQc(session_path, **kwargs)[source]
Bases:
EphysTask
,CellQCMixin
- priority = 90
- job_size = 'small'
- property signature
dict() -> new empty dictionary dict(mapping) -> new dictionary initialized from a mapping object’s
(key, value) pairs
- dict(iterable) -> new dictionary initialized as if via:
d = {} for k, v in iterable:
d[k] = v
- dict(**kwargs) -> new dictionary initialized with the name=value pairs
in the keyword argument list. For example: dict(one=1, two=2)