6fa78eebb531215d2fb5f5955a9ff353b6b8ddf7,examples/tangent_pca_so3.py,,main,#,19

Before Change

    eigenvalues, tangent_eigenvecs = METRIC.tangent_pca(data, base_point=mean)
    n_eigenvalues = min(N_SAMPLES, SO3_GROUP.dimension)

    explained_variances = np.cumsum(eigenvalues)
    explained_variances = explained_variances / explained_variances[-1]

    ax_eig = fig.add_subplot(131)
    xticks = np.arange(0, n_eigenvalues, 1)
    ax_eig.xaxis.set_ticks(xticks)

After Change

    tpca = TangentPCA(metric=METRIC, n_components=N_COMPONENTS)
    tpca = tpca.fit(data, base_point=mean)
    tangent_projected_data = tpca.transform(data)
    print(
        "Coordinates of the Log of the first 5 data points at the mean, "
        "projected on the principal components:")
    print(tangent_projected_data[:5])

    ax_var = fig.add_subplot(121)
    xticks = np.arange(1, N_COMPONENTS+1, 1)

Instances