d01c5b805e49346914b3b5ace081cae8cbb2a99a,modAL/density.py,,information_density,#,32

Before Change

        The information density for each sample.
    
    inf_density = np.zeros(shape=(X.shape[0],))
    for X_idx, X_inst in enumerate(X):
        inf_density[X_idx] = sum(similarity_measure(X_inst, X_j) for X_j in X)

    return inf_density/X.shape[0]

After Change

    //
    // return inf_density/X.shape[0]

    similarity_mtx = 1/(1+pairwise_distances(X, X, metric=metric))

    return similarity_mtx.mean(axis=1)

Instances