2ab1119596b420cc696a783271d617562ccf7e28,cesium/featurize.py,,featurize_single_ts,#,22

Before Change

        channel) as values.
    
    // Initialize empty feature array for all channels
    all_feature_lists = {feature: [0.] * ts.n_channels
                         for feature in features_to_use}
    for (t_i, m_i, e_i), i in zip(ts.channels(), range(ts.n_channels)):
        feature_graph = generate_dask_graph(t_i, m_i, e_i)
        feature_graph.update(ts.meta_features)

After Change

        // series in serial.
        feature_values[:, i] = dask.async.get_sync(feature_graph, features_to_use)

    index = pd.MultiIndex.from_product((features_to_use, range(ts.n_channels)),
                                       names=("feature", "channel"))
    return pd.Series(feature_values.ravel(), index=index)

Instances