stimpyp.pyvstim.PyVlog

final class stimpyp.pyvstim.PyVlog

Bases: AbstractLog

class for handle the log file (rig event specific) for pyvstim version (vb lab legacy)

__init__(*args, **kwargs)

Parameters:

• root_path – log file path or log directory

• log_suffix – log file suffix

• diode_offset – whether do the diode offset

• reset_mapping – Customized mapping

Methods

__init__(*args, **kwargs)
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()	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	masking vstim code
exp_start_time	masking vstim code
imaging_event	imaging rig event.
lap_event	lap rig event.
lick_event	lick rig event.
log_config	config dict for the log file
log_header
log_info
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: dict[str, Any] = {}

config dict for the log file

log_info: dict[int, str] = {}

log_header: dict[int, list[str]] = {}

__init__(*args, **kwargs)

Parameters:

• root_path – log file path or log directory

• log_suffix – log file suffix

• diode_offset – whether do the diode offset

• reset_mapping – Customized mapping

property exp_start_time: float

masking vstim code

property exp_end_time: float

masking vstim code

get_stimlog()

get stimlog (TypeVar S)

Returns:

AbstractStimlog

Return type:

StimlogPyVStim

get_protocol()

get protocol (TypeVar P)

Returns:

AbstractStimProtocol()

Return type:

PyVProtocol

class CameraEvent

Bases: object

camera event

__init__(rig)

:param rig:Baselog

Parameters:

rig (R)

camera: dict[Literal['facecam', 'eyecam', '1P_cam'], int]

property act_event: RigEvent

todo

property camera_event: CameraEvent

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

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]

get_preferences()

get preferences file

Return type:

PreferenceDict

get_stimulus_type()

get stimulus type name based on protocol

Return type:

str

property imaging_event: RigEvent

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

property lap_event: RigEvent

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

property lick_event: RigEvent

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

property opto_event: RigEvent

todo

property position_event: RigEvent

position rig event. i.e., encoder pulse

property pref_file: Path

preferences file path

property prot_file: Path

protocol file path

property reward_event: RigEvent

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

property screen_event: RigEvent

screen rig event. i.e., diode pulse

property total_duration: float

experimental duration (in sec)

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