treadmill

For running the calibration of the treadmill refer to this repository.

pydantic model aind_behavior_services.calibration.treadmill.CalibrationLogic[source]

Bases: AindBehaviorTaskLogicModel

Treadmill operation control model that is used to run a calibration data acquisition workflow

Config:

  • extra: str = forbid

  • validate_assignment: bool = True

  • validate_defaults: bool = True

  • strict: bool = True

  • str_strip_whitespace: bool = True

Fields:
Validators:
field name: str = 'TreadmillCalibrationLogic'[source]
field task_parameters: CalibrationParameters = CalibrationParameters(rng_seed=None, aind_behavior_services_pkg_version='0.8.8')[source]
field version: Literal['0.0.0'] = '0.0.0'[source]
Validated by:

  • coerce_version

pydantic model aind_behavior_services.calibration.treadmill.CalibrationParameters[source]

Bases: TaskParameters

Config:

  • extra: str = allow

  • validate_assignment: bool = True

  • validate_defaults: bool = True

  • strict: bool = True

  • str_strip_whitespace: bool = True

Fields:

Validators:

pydantic model aind_behavior_services.calibration.treadmill.CalibrationRig[source]

Bases: AindBehaviorRigModel

Fields:
Validators:
field treadmill: Treadmill [Required][source]
field version: Literal['0.0.0'] = '0.0.0'[source]
Validated by:
pydantic model aind_behavior_services.calibration.treadmill.Treadmill[source]

Bases: HarpTreadmill

Fields:
field calibration: TreadmillCalibration | None = None[source]
pydantic model aind_behavior_services.calibration.treadmill.TreadmillCalibration[source]

Bases: Calibration

Treadmill calibration class

Fields:
field description: Literal['Calibration of the treadmill system'] = 'Calibration of the treadmill system'[source]
field device_name: str = 'Treadmill'[source]

Must match a device name in rig/instrument

field input: TreadmillCalibrationInput [Required][source]
field output: TreadmillCalibrationOutput [Required][source]
pydantic model aind_behavior_services.calibration.treadmill.TreadmillCalibrationInput[source]

Bases: BaseModel

pydantic model aind_behavior_services.calibration.treadmill.TreadmillCalibrationOutput[source]

Bases: BaseModel

Fields:
Validators:
field brake_lookup_calibration: List[List[float]] [Required][source]

Brake lookup calibration. Each pair of values define (input [torque], output [brake set-point U16])

Constraints:

  • min_length = 2

Validated by:
field invert_direction: bool = False[source]

Invert direction

field pulses_per_revolution: int = 28800[source]

Pulses per revolution

Constraints:

  • ge = 1

field wheel_diameter: float = 15[source]

Wheel diameter

Constraints:

  • ge = 0

validator validate_brake_lookup_calibration  »  brake_lookup_calibration[source]

Example

import os

from aind_behavior_services.base import get_commit_hash
from aind_behavior_services.calibration import treadmill
from aind_behavior_services.session import AindBehaviorSessionModel
from aind_behavior_services.utils import utcnow

treadmill_calibration = treadmill.TreadmillCalibrationOutput(
    wheel_diameter=10,
    pulses_per_revolution=10000,
    invert_direction=False,
    brake_lookup_calibration=[[0, 0], [0.5, 32768], [1, 65535]],
)

calibration = treadmill.TreadmillCalibration(
    device_name="Treadmill",
    input=treadmill.TreadmillCalibrationInput(),
    output=treadmill_calibration,
    date=utcnow(),
)

calibration_logic = treadmill.CalibrationLogic()

calibration_session = AindBehaviorSessionModel(
    root_path="C:\\Data",
    allow_dirty_repo=False,
    experiment="Calibration",
    date=utcnow(),
    subject="00000",
    experiment_version="treadmill",
    commit_hash=get_commit_hash(),
)

rig = treadmill.CalibrationRig(
    treadmill=treadmill.Treadmill(calibration=calibration, port_name="COM4"),
    rig_name="TreadmillCalibrationRig",
)

seed_path = "local/treadmill_{suffix}.json"
os.makedirs(os.path.dirname(seed_path), exist_ok=True)

with open(seed_path.format(suffix="calibration_logic"), "w") as f:
    f.write(calibration_logic.model_dump_json(indent=3))
with open(seed_path.format(suffix="session"), "w") as f:
    f.write(calibration_session.model_dump_json(indent=3))
with open(seed_path.format(suffix="rig"), "w") as f:
    f.write(rig.model_dump_json(indent=3))