bluecellulab.stimulus.stimulus

Classes

CombinedStimulus(dt, time, current)	Represents the Stimulus created by combining multiple stimuli.
DelayedZap()
Empty(dt, duration)	Represents empty stimulus (all zeros) that has no impact on the cell.
Flat(dt, duration, amplitude)
OUProcess(dt, duration, tau, sigma, mean[, seed])	Generates an Ornstein-Uhlenbeck noise signal.
OrnsteinUhlenbeck()	Factory-compatible Ornstein-Uhlenbeck noise stimulus.
Pulse()	Factory-compatible Pulse Stimulus.
PulseTrain(dt, duration, amplitude, ...)	Generates a pulse train signal.
Ramp()
ShotNoise()	Factory-compatible Shot Noise Stimulus.
ShotNoiseProcess(dt, duration, rate, mean, ...)	Generates a shot noise signal, modeling discrete synaptic events occurring at random intervals.
Sinusoidal()	Factory-compatible Sinusoidal Stimulus.
SinusoidalWave(dt, duration, amplitude, ...)	Generates a sinusoidal current wave.
Slope(dt, duration, amplitude_start, ...)
Step()
StepNoise()	Factory-compatible Step Noise Stimulus.
StepNoiseProcess(dt, duration, ...[, seed])	Generates step noise: A step current with noise variations.
Stimulus(dt)
Zap(dt, duration, amplitude)

class bluecellulab.stimulus.stimulus.CombinedStimulus(dt, time, current)[source]

Represents the Stimulus created by combining multiple stimuli.

Parameters:

• dt (float)

• time (ndarray)

• current (ndarray)

property current: ndarray

Current values of the stimulus.

property time: ndarray

Time values of the stimulus.

class bluecellulab.stimulus.stimulus.DelayedZap[source]

classmethod amplitude_based(dt, pre_delay, duration, post_delay, amplitude)[source]

Create a DelayedZap stimulus from given time events and amplitude.

Parameters:

• dt (float) – The time step of the stimulus.

• pre_delay (float) – The delay before the start of the step.

• duration (float) – The duration of the step.

• post_delay (float) – The time to wait after the end of the step.

• amplitude (float) – The amplitude of the step.

Return type:

CombinedStimulus

classmethod threshold_based(dt, pre_delay, duration, post_delay, threshold_current, threshold_percentage)[source]

Creates a SineSpec stimulus with respect to the threshold current.

Parameters:

• dt (float) – The time step of the stimulus.

• pre_delay (float) – The delay before the start of the step.

• duration (float) – The duration of the step.

• post_delay (float) – The time to wait after the end of the step.

• threshold_current (float) – The threshold current of the Cell.

• threshold_percentage (float) – Percentage of desired threshold_current amplification.

Return type:

CombinedStimulus

class bluecellulab.stimulus.stimulus.Empty(dt, duration)[source]

Represents empty stimulus (all zeros) that has no impact on the cell.

This is required by some Stimuli that expect the cell to rest.

Parameters:

• dt (float)

• duration (float)

property current: ndarray

Current values of the stimulus.

property time: ndarray

Time values of the stimulus.

class bluecellulab.stimulus.stimulus.Flat(dt, duration, amplitude)[source]

Parameters:

• dt (float)

• duration (float)

• amplitude (float)

property current: ndarray

Current values of the stimulus.

property time: ndarray

Time values of the stimulus.

class bluecellulab.stimulus.stimulus.OUProcess(dt, duration, tau, sigma, mean, seed=None)[source]

Generates an Ornstein-Uhlenbeck noise signal.

Parameters:

• dt (float)

• duration (float)

• tau (float)

• sigma (float)

• mean (float)

• seed (Optional[int])

property current: ndarray

Returns the Ornstein-Uhlenbeck noise signal.

property time: ndarray

Returns the time array for the stimulus duration.

class bluecellulab.stimulus.stimulus.OrnsteinUhlenbeck[source]

Factory-compatible Ornstein-Uhlenbeck noise stimulus.

classmethod amplitude_based(dt, pre_delay, duration, post_delay, tau, sigma, mean, seed=None)[source]

Create an Ornstein-Uhlenbeck stimulus from given time events and amplitude.

Parameters:

• dt (float)

• pre_delay (float)

• duration (float)

• post_delay (float)

• tau (float)

• sigma (float)

• mean (float)

• seed (Optional[int])

Return type:

CombinedStimulus

classmethod threshold_based(dt, pre_delay, duration, post_delay, mean_percent, sigma_percent, threshold_current, tau, seed=None)[source]

Creates an Ornstein-Uhlenbeck stimulus with respect to the threshold current.

Parameters:

• dt (float)

• pre_delay (float)

• duration (float)

• post_delay (float)

• mean_percent (float)

• sigma_percent (float)

• threshold_current (float)

• tau (float)

• seed (Optional[int])

Return type:

CombinedStimulus

class bluecellulab.stimulus.stimulus.Pulse[source]

Factory-compatible Pulse Stimulus.

classmethod amplitude_based(dt, pre_delay, duration, post_delay, amplitude, frequency, width)[source]

Creates a Pulse stimulus from given time events and amplitude.

Parameters:

• dt (float)

• pre_delay (float)

• duration (float)

• post_delay (float)

• amplitude (float)

• frequency (float)

• width (float)

Return type:

CombinedStimulus

classmethod threshold_based(dt, pre_delay, duration, post_delay, threshold_current, threshold_percentage, frequency, width)[source]

Creates a Pulse stimulus with respect to the threshold current.

Parameters:

• dt (float)

• pre_delay (float)

• duration (float)

• post_delay (float)

• threshold_current (float)

• threshold_percentage (float)

• frequency (float)

• width (float)

Return type:

CombinedStimulus

class bluecellulab.stimulus.stimulus.PulseTrain(dt, duration, amplitude, frequency, width)[source]

Generates a pulse train signal.

Parameters:

• dt (float)

• duration (float)

• amplitude (float)

• frequency (float)

• width (float)

property current: ndarray

Current values of the stimulus.

property time: ndarray

Time values of the stimulus.

class bluecellulab.stimulus.stimulus.Ramp[source]

classmethod amplitude_based(dt, pre_delay, duration, post_delay, amplitude)[source]

Create a Ramp stimulus from given time events and amplitudes.

Parameters:

• dt (float) – The time step of the stimulus.

• pre_delay (float) – The delay before the start of the ramp.

• duration (float) – The duration of the ramp.

• post_delay (float) – The time to wait after the end of the ramp.

• amplitude (float) – The final amplitude of the ramp.

Return type:

CombinedStimulus

classmethod threshold_based(dt, pre_delay, duration, post_delay, threshold_current, threshold_percentage)[source]

Creates a Ramp stimulus with respect to the threshold current.

Parameters:

• dt (float) – The time step of the stimulus.

• pre_delay (float) – The delay before the start of the ramp.

• duration (float) – The duration of the ramp.

• post_delay (float) – The time to wait after the end of the ramp.

• threshold_current (float) – The threshold current of the Cell.

• threshold_percentage (float) – Percentage of desired threshold_current amplification.

Return type:

CombinedStimulus

class bluecellulab.stimulus.stimulus.ShotNoise[source]

Factory-compatible Shot Noise Stimulus.

classmethod amplitude_based(dt, pre_delay, duration, post_delay, rate, mean, sigma, rise_time, decay_time, seed=None)[source]

Creates a shot noise stimulus with a specified amplitude.

Parameters:

• dt (float) – Time step of the stimulus.

• pre_delay (float) – Delay before the noise starts.

• duration (float) – Duration of the noise signal.

• post_delay (float) – Delay after the noise ends.

• rate (float) – Frequency of synaptic-like events.

• mean (float) – Mean amplitude of the events.

• sigma (float) – Standard deviation of event amplitudes.

• rise_time (float) – Time constant for the event’s rise phase.

• decay_time (float) – Time constant for the event’s decay phase.

• seed (Optional[int]) – Random seed for reproducibility.

Return type:

CombinedStimulus

classmethod threshold_based(dt, pre_delay, duration, post_delay, rise_time, decay_time, mean_percent, sigma_percent, threshold_current, relative_skew=0.5, seed=None)[source]

Creates a shot noise stimulus based on a neuron’s threshold current.

Parameters:

• dt (float) – Time step of the stimulus.

• pre_delay (float) – Delay before the noise starts.

• duration (float) – Duration of the noise signal.

• post_delay (float) – Delay after the noise ends.

• rise_time (float) – Rise time constant of events.

• decay_time (float) – Decay time constant of events.

• mean_percent (float) – Mean value as a percentage of the threshold current.

• sigma_percent (float) – Standard deviation as a percentage of the threshold current.

• threshold_current (float) – Baseline threshold current.

• relative_skew (float) – Skew factor affecting noise distribution.

• seed (Optional[int]) – Random seed for reproducibility.

Return type:

CombinedStimulus

class bluecellulab.stimulus.stimulus.ShotNoiseProcess(dt, duration, rate, mean, sigma, rise_time, decay_time, seed=None)[source]

Generates a shot noise signal, modeling discrete synaptic events occurring at random intervals.

Parameters:

• dt (float)

• duration (float)

• rate (float)

• mean (float)

• sigma (float)

• rise_time (float)

• decay_time (float)

• seed (Optional[int])

property current: ndarray

Current values of the stimulus.

property time: ndarray

Time values of the stimulus.

class bluecellulab.stimulus.stimulus.Sinusoidal[source]

Factory-compatible Sinusoidal Stimulus.

classmethod amplitude_based(dt, pre_delay, duration, post_delay, amplitude, frequency)[source]

Creates a sinusoidal stimulus with a specified amplitude.

Parameters:

• dt (float) – Time step of the stimulus.

• pre_delay (float) – Delay before the sinusoidal wave starts.

• duration (float) – Duration of the sinusoidal signal.

• post_delay (float) – Delay after the wave ends.

• amplitude (float) – Amplitude of the sinusoidal wave.

• frequency (float) – Frequency of the wave in Hz.

Return type:

CombinedStimulus

classmethod threshold_based(dt, pre_delay, duration, post_delay, frequency, threshold_current, amplitude_percent)[source]

Creates a sinusoidal stimulus relative to the threshold current.

Parameters:

• dt (float) – Time step of the stimulus.

• pre_delay (float) – Delay before the sinusoidal wave starts.

• duration (float) – Duration of the sinusoidal signal.

• post_delay (float) – Delay after the wave ends.

• frequency (float) – Frequency of the wave in Hz.

• threshold_current (float) – Baseline threshold current.

• amplitude_percent (float) – Amplitude as a percentage of the threshold current.

Return type:

CombinedStimulus

class bluecellulab.stimulus.stimulus.SinusoidalWave(dt, duration, amplitude, frequency)[source]

Generates a sinusoidal current wave.

Parameters:

• dt (float)

• duration (float)

• amplitude (float)

• frequency (float)

property current: ndarray

Current values of the stimulus.

property time: ndarray

Time values of the stimulus.

class bluecellulab.stimulus.stimulus.Slope(dt, duration, amplitude_start, amplitude_end)[source]

Parameters:

• dt (float)

• duration (float)

• amplitude_start (float)

• amplitude_end (float)

property current: ndarray

Current values of the stimulus.

property time: ndarray

Time values of the stimulus.

class bluecellulab.stimulus.stimulus.Step[source]

classmethod amplitude_based(dt, pre_delay, duration, post_delay, amplitude)[source]

Create a Step stimulus from given time events and amplitude.

Parameters:

• dt (float) – The time step of the stimulus.

• pre_delay (float) – The delay before the start of the step.

• duration (float) – The duration of the step.

• post_delay (float) – The time to wait after the end of the step.

• amplitude (float) – The amplitude of the step.

Return type:

CombinedStimulus

classmethod threshold_based(dt, pre_delay, duration, post_delay, threshold_current, threshold_percentage)[source]

Creates a Step stimulus with respect to the threshold current.

Parameters:

• dt (float) – The time step of the stimulus.

• pre_delay (float) – The delay before the start of the step.

• duration (float) – The duration of the step.

• post_delay (float) – The time to wait after the end of the step.

• threshold_current (float) – The threshold current of the Cell.

• threshold_percentage (float) – Percentage of desired threshold_current amplification.

Return type:

CombinedStimulus

class bluecellulab.stimulus.stimulus.StepNoise[source]

Factory-compatible Step Noise Stimulus.

classmethod amplitude_based(dt, pre_delay, duration, post_delay, step_interval, mean, sigma, seed=None)[source]

Creates a step noise stimulus with a specified amplitude.

Parameters:

• dt (float) – Time step of the stimulus.

• pre_delay (float) – Delay before the step noise starts.

• duration (float) – Duration of the noise signal.

• post_delay (float) – Delay after the step noise ends.

• step_interval (float) – Interval at which noise amplitude changes.

• mean (float) – Mean amplitude of step noise.

• sigma (float) – Standard deviation of step noise.

• seed (Optional[int]) – Random seed for reproducibility.

Return type:

CombinedStimulus

classmethod threshold_based(dt, pre_delay, duration, post_delay, step_interval, mean_percent, sigma_percent, threshold_current, seed=None)[source]

Creates a step noise stimulus relative to the threshold current.

Parameters:

• dt (float) – Time step of the stimulus.

• pre_delay (float) – Delay before the step noise starts.

• duration (float) – Duration of the noise signal.

• post_delay (float) – Delay after the step noise ends.

• step_interval (float) – Interval at which noise amplitude changes.

• mean_percent (float) – Mean current as a percentage of threshold current.

• sigma_percent (float) – Standard deviation as a percentage of threshold current.

• threshold_current (float) – Baseline threshold current.

• seed (Optional[int]) – Random seed for reproducibility.

Return type:

CombinedStimulus

class bluecellulab.stimulus.stimulus.StepNoiseProcess(dt, duration, step_interval, mean, sigma, seed=None)[source]

Generates step noise: A step current with noise variations.

Parameters:

• dt (float)

• duration (float)

• step_interval (float)

• mean (float)

• sigma (float)

• seed (Optional[int])

property current: ndarray

Current values of the stimulus.

property time: ndarray

Time values of the stimulus.

class bluecellulab.stimulus.stimulus.Stimulus(dt)[source]

Parameters:

dt (float)

abstract property current: ndarray

Current values of the stimulus.

abstract property time: ndarray

Time values of the stimulus.

class bluecellulab.stimulus.stimulus.Zap(dt, duration, amplitude)[source]

Parameters:

• dt (float)

• duration (float)

• amplitude (float)

property current: ndarray

Current values of the stimulus.

property time: ndarray

Time values of the stimulus.