larvaworld.lib.model.modules.turner

Classes

`Turner`	Base turner module for directional control.
`ConstantTurner`	Constant-output turner for simple directional control.
`SinTurner`	Sinusoidal turner for oscillatory directional control.
`NeuralOscillator`	Neural oscillator turner using Wilson-Cowan dynamics.

Module Contents

class larvaworld.lib.model.modules.turner.Turner(**kwargs: Any)

Bases: larvaworld.lib.model.modules.basic.Effector

Base turner module for directional control.

Abstract base class for body-bending modules that control angular velocity and directional changes during locomotion.

Attributes:

input_range: Valid input range for sensory activation (-1 to 1)

Example:

>>> # Use concrete subclasses like ConstantTurner, SinTurner, NeuralOscillator
>>> turner = SinTurner(freq=0.58, amp=0.5)

input_range

class larvaworld.lib.model.modules.turner.ConstantTurner(**kwargs: Any)

Bases: Turner, larvaworld.lib.model.modules.basic.StepEffector

Constant-output turner for simple directional control.

Provides step-based turning behavior with constant angular velocity when active. Simplest turner implementation for baseline locomotion.

Example:

>>> turner = ConstantTurner(amp=0.3)
>>> angular_velocity = turner.step()

class larvaworld.lib.model.modules.turner.SinTurner(**kwargs: Any)

Bases: Turner, larvaworld.lib.model.modules.basic.SinOscillator

Sinusoidal turner for oscillatory directional control.

Extends Turner with sinusoidal oscillation, producing periodic left-right turning patterns. Commonly used for exploratory behavior.

Attributes:

freq: Oscillation frequency in Hz (0.0-2.0)

Example:

>>> turner = SinTurner(freq=0.58, amp=0.4)
>>> angular_velocity = turner.step()

freq

class larvaworld.lib.model.modules.turner.NeuralOscillator(**kwargs: Any)

Bases: Turner

Neural oscillator turner using Wilson-Cowan dynamics.

Implements biologically realistic central pattern generator (CPG) for directional control using coupled excitatory/inhibitory neural populations. Produces emergent oscillatory turning behavior from neural dynamics rather than prescribed waveforms.

Attributes:

base_activation: Baseline neural activation level (10-40 Hz) activation_range: Valid activation range bounds (0-100 Hz) tau: Neural time constant for population dynamics (seconds) w_ee, w_ce, w_ec, w_cc: Synaptic connection weights between populations m: Maximum neural spike rate (Hz) n: Spike-rate response steepness coefficient E_l, E_r: Left/right excitatory population activities C_l, C_r: Left/right inhibitory population activities H_E_l, H_E_r, H_C_l, H_C_r: Hysteresis variables for populations

Example:

>>> neural_turner = NeuralOscillator(
...     base_activation=20.0,
...     tau=0.1,
...     w_ee=3.0,
...     w_ec=4.0
... )
>>> angular_velocity = neural_turner.step(A_in=0.5)