dwave.embedding.chain_breaks.discard#
- discard(samples, chains)[source]#
Discard broken chains.
- Parameters:
samples (samples_like) – A collection of samples. samples_like is an extension of NumPy’s array_like. See
dimod.as_samples()
.chains (list[array_like]) – List of chains, where each chain is an array_like collection of the variables in the same order as their represention in the given samples.
- Returns:
A 2-tuple containing:
numpy.ndarray
: Unembedded samples as an array of dtype ‘int8’. Broken chains are discarded.numpy.ndarray
: Indicies of rows with unbroken chains.- Return type:
Examples
This example unembeds two samples that chains nodes 0 and 1 to represent a single source node. The first sample has an unbroken chain, the second a broken chain.
>>> import dimod >>> import numpy as np ... >>> chains = [(0, 1), (2,)] >>> samples = np.array([[1, 1, 0], [1, 0, 0]], dtype=np.int8) >>> unembedded, idx = dwave.embedding.discard(samples, chains) >>> unembedded array([[1, 0]], dtype=int8) >>> print(idx) [0]