pathsim.blocks.rng module

class pathsim.blocks.rng.RNG(sampling_rate=None)

Bases: Block

Generates a random output value beteween -1 and 1 from a uniform distribution.

If no ‘sampling_rate’ (None) is specified, every simulation timestep gets a random value.

Parameters:

sampling_rate (float, None) – number of random samples per time unit

n_samples

internal sample counter

Type:

int

val

internal random number state

Type:

float

reset()

Reset the blocks inputs and outputs and also its internal solver, if the block has a solver instance.

sample(t)

Sample from a normal distribution after successful timestep.

Parameters:

t (float) – evaluation time for sampling

update(t)

update system equation for fixed point loop, here just setting the outputs

Note

no direct passthrough, so the ‘update’ method is optimized for this case

Parameters:

t (float) – evaluation time

Returns:

error – deviation to previous iteration for convergence control

Return type:

float