# brainpy.compat.runners.IntegratorRunner#

class brainpy.compat.runners.IntegratorRunner(*args, **kwargs)[source]#

Integrator runner class.

__init__(*args, **kwargs)[source]#

Initialization of structural runner for integrators.

Parameters
• target (Integrator) –

• monitors (sequence of str) –

• fun_monitors (dict) –

• inits (sequence, dict) – The initial value of variables. With this parameter, you can easily control the number of variables to simulate. For example, if one of the variable has the shape of 10, then all variables will be an instance of brainpy.math.Variable with the shape of $$(10,)$$.

• args (dict) – The equation arguments to update. Note that if one of the arguments are heterogeneous (i.e., a tensor), it means we should run multiple trials. However, you can set the number of the elements in the variables so that each pair of variables can corresponds to one set of arguments.

• dyn_args (dict) – The dynamically changed arguments. This means this argument can control the argument dynamically changed. For example, if you want to inject a time varied currents into the HH neuron model, you can pack the currents into this dyn_args argument.

• dt (float, int) –

• dyn_vars (dict) –

• jit (bool) –

• progress_bar (bool) –

• numpy_mon_after_run (bool) –

Methods

 __init__(*args, **kwargs) Initialization of structural runner for integrators. run(duration[, start_t])