stimpyp.base.AbstractLog#

class stimpyp.base.AbstractLog#

Bases: Generic[S, P]

ABC class for different stimpy/pyvstim log files. i.e., .log, .riglog

__init__(root_path, log_suffix, diode_offset=True, reset_mapping=None)#
Parameters:

  • root_path (str | Path | bytes | BinaryIO | BufferedIOBase | BufferedReader) – log file path or log directory

  • log_suffix (Literal['.log', '.riglog']) – log file suffix

  • diode_offset (bool) – whether do the diode offset

  • reset_mapping (dict[int, list[str]] | None) – Customized mapping

Methods

__init__(root_path, log_suffix[, ...])

get_encoder_factor([count, length])

Get a factor for mapping encoder to actual length in cm

get_preferences()

get preferences file

get_protocol()

get protocol (TypeVar P)

get_stimlog(*args)

get stimlog (TypeVar S)

get_stimulus_type()

get stimulus type name based on protocol

unwarp_circular_position([neg_threshold])

unwarp circular position to cumulative displacement

Attributes

act_event

todo

camera_event

camera event.

exp_end_time

experimental end time (in sec)

exp_start_time

experimental start time (in sec)

imaging_event

imaging rig event.

lap_event

lap rig event.

lick_event

lick rig event.

opto_event

todo

position_event

position rig event.

pref_file

preferences file path

prot_file

protocol file path

reward_event

reward rig event.

screen_event

screen rig event.

total_duration

experimental duration (in sec)

log_config

config dict for the log file
__init__(root_path, log_suffix, diode_offset=True, reset_mapping=None)#
Parameters:

  • root_path (str | Path | bytes | BinaryIO | BufferedIOBase | BufferedReader) – log file path or log directory

  • log_suffix (Literal['.log', '.riglog']) – log file suffix

  • diode_offset (bool) – whether do the diode offset

  • reset_mapping (dict[int, list[str]] | None) – Customized mapping

log_config: RigConfig#

config dict for the log file

property exp_start_time: float#

experimental start time (in sec)

property exp_end_time: float#

experimental end time (in sec)

property total_duration: float#

experimental duration (in sec)

property screen_event: RigEvent#

screen rig event. i.e., diode pulse

property imaging_event: RigEvent#

imaging rig event. i.e., 2photon pulse

property position_event: RigEvent#

position rig event. i.e., encoder pulse

property lick_event: RigEvent#

lick rig event. i.e., lick meter pulse

property reward_event: RigEvent#

reward rig event. i.e., reward given pulse from lick meter

property lap_event: RigEvent#

lap rig event. i.e., optic sensing for the reflective taps

property act_event: RigEvent#

todo

property opto_event: RigEvent#

todo

class CameraEvent#

Bases: object

camera event

__init__(rig)#

:param rig:Baselog

Parameters:

rig (R)

camera: dict[Literal['facecam', 'eyecam', '1P_cam'], int]#
property camera_event: CameraEvent#

camera event. including {‘facecam’, ‘eyecam’, ‘1P_cam’} implemented by __getitem__()

property prot_file: Path#

protocol file path

abstract get_protocol()#

get protocol (TypeVar P)

Returns:

AbstractStimProtocol()

Return type:

P

get_stimulus_type()#

get stimulus type name based on protocol

Return type:

str

property pref_file: Path#

preferences file path

get_preferences()#

get preferences file

Return type:

PreferenceDict

abstract get_stimlog(*args)#

get stimlog (TypeVar S)

Returns:

AbstractStimlog

Return type:

S

get_encoder_factor(count=1, length=150)#

Get a factor for mapping encoder to actual length in cm

Parameters:

  • count (int) – number of photosensing for each trial

  • length (float) – length in cm for each trial

Returns:

Return type:

tuple[float, ndarray]

unwarp_circular_position(neg_threshold=200)#

unwarp circular position to cumulative displacement

Parameters:

neg_threshold (float) – a negative jump larger in magnitude than this is considered a wrap-around

Return type:

ndarray