pwc_signal

Graph.pwc_signal(values, duration, *, name=None)

Create a piecewise-constant signal (scalar-valued function of time).

Use this function to create a piecewise-constant signal in which the constant segments all have the same duration.

Parameters:

values (np.ndarray or Tensor) – The values \(\{\alpha_n\}\) of the \(N\) constant segments. These can represent either a single sequence of segment values or a batch of them. To create a batch of \(B_1 \times \ldots \times B_n\) signals, represent these values as a tensor of shape \(B_1 \times \ldots \times B_n \times N\).
duration (float) – The total duration \(\tau\) of the signal.
name (str or None, optional) – The name of the node.

Returns:

The piecewise-constant function of time \(\alpha(t)\), satisfying \(\alpha(t)=\alpha_n\) for \(t_{n-1}\leq t\leq t_n\), where \(t_n=n\tau/N\) (where \(N\) is the number of values in \(\{\alpha_n\}\)). If you provide a batch of values, the returned Pwc represents a corresponding batch of \(B_1 \times \ldots \times B_n\) functions \(\alpha(t)\).

Return type:

Pwc

See also

Graph.complex_pwc_signal: Create complex Pwc signals from their moduli and phases.
Graph.pwc: Corresponding operation with support for segments of different durations.
Graph.pwc_operator: Create Pwc operators.
Graph.pwc_sum: Sum multiple Pwcs.
Graph.symmetrize_pwc: Symmetrize Pwcs.

Notes

For more information on Pwc nodes see the Working with time-dependent functions in Boulder Opal topic.

Examples

Create a piecewise-constant signal with uniform segment duration.

>>> graph.pwc_signal(duration=0.1, values=np.array([2, 3]), name="signal")
<Pwc: name="signal", operation_name="pwc_signal", value_shape=(), batch_shape=()>
>>> result = bo.execute_graph(graph=graph, output_node_names="signal")
>>> result["output"]["signal"]
{
    'durations': array([0.05, 0.05]),
    'values': array([2., 3.]),
    'time_dimension': 0
}

See more examples in the Get familiar with graphs tutorial.