pymoto.SetValue

class pymoto.SetValue(indices, value)

Sets the values of a numpy array at specified indices to a given value

Input signal:: x (np.ndarray): Input numpy array to modify
Output signal:: y (np.ndarray): Modified vector with specified indices set to a given value

__init__(indices, value)

Initialize the SetValue module

Parameters:

indices (any valid slice type) – Indices in the input vector to set to the specified value
value (float or np.ndarray) – Value(s) to set at the specified indices

Methods

`__init__`(indices, value)	Initialize the SetValue module
`connect`(sig_in[, sig_out])	Connect without automatic adding to a function network
`get_input_sensitivities`([as_list])
`get_input_states`([as_list])
`get_output_sensitivities`([as_list])
`get_output_states`([as_list])
`reset`()	Reset the state of the sensitivities (they are set to zero or to None)
`response`()	Calculate the response from sig_in and output this to sig_out
`sensitivity`()	Calculate sensitivities using backpropagation

Attributes

`n_in`	Get the number of input signals
`n_out`	Get the number of output signals
`sig_in`
`sig_out`

connect(sig_in: Signal | Iterable[Signal], sig_out: Signal | Iterable[Signal] = None): Connect without automatic adding to a function network

property n_out: int

Get the number of output signals

Note: Cannot be used in the initial __call__()

reset(): Reset the state of the sensitivities (they are set to zero or to None)

sensitivity()

Calculate sensitivities using backpropagation

Based on the sensitivity we get from sig_out, reverse the process and output the new sensitivities to sig_in