bolero.representation.ConstantBehavior¶

class bolero.representation.ConstantBehavior(outputs=None)[source]¶

Generates constant outputs.

Parameters:	outputs : array-like, shape (n_outputs,), optional (default: zeros) Values of constant outputs.

__init__(outputs=None)[source]¶

can_step()¶

Returns if step() can be called again.

Returns:	can_step : bool Can we call step() again?

get_args()¶

Get parameters for this estimator.

Returns:	params : mapping of string to any Parameter names mapped to their values.

get_n_params()[source]¶

Get number of parameters.

Returns:	n_params : int Number of parameters that will be optimized.

get_outputs(outputs)[source]¶

Get outputs of the last step.

Parameters:	outputs : array-like, shape = (n_outputs,) outputs, e.g. next action, will be updated

get_params()[source]¶

Get current parameters.

Returns:	params : array-like, shape = (n_params,) Current parameters.

init(n_inputs, n_outputs)[source]¶

Initialize the behavior.

Parameters:	n_inputs : int number of inputs n_outputs : int number of outputs

reset()[source]¶

Reset behavior.

Does nothing.

set_inputs(inputs)[source]¶

Set input for the next step.

Parameters:	inputs : array-like, shape = (n_inputs,) inputs, e.g. current state of the system

set_meta_parameters(keys, meta_parameters)[source]¶

Set meta parameters (none defined for constant behavior).

set_params(params)[source]¶

Set new parameter values.

Parameters:	params : array-like, shape = (n_params,) New parameters.

step()[source]¶

Compute output for the received input.

Use the inputs and meta-parameters to compute the outputs.