Function plot_one_class_3

tools/visualize.py:557–608

(
    umap_Y,
    umap_T,
    train_Y,
    train_T,
    test_Y,
    test_T,
    target=0,
    col="red",
    total_train_size="",
    total_test_size="",
    info="",
    output_dir="",
    orig_space_dim=0,
)

def plot_one_class_3(
    umap_Y,
    umap_T,
    train_Y,
    train_T,
    test_Y,
    test_T,
    target=0,
    col="red",
    total_train_size="",
    total_test_size="",
    info="",
    output_dir="",
    orig_space_dim=0,
):
    size = 1

    fig, (ax0, ax1, ax2) = plt.subplots(1, 3)
    fig.suptitle("UMAP: " + info + " space dim " + str(orig_space_dim))

    ind_l_umap = [i for i, x in enumerate(umap_T) if x == target]
    Y_umap_l = np.array([umap_Y[i, :] for i in ind_l_umap])

    ax0.scatter(Y_umap_l[:, 0], Y_umap_l[:, 1], s=size, c=col, marker=".", linewidth=0)
    ax0.set_title(
        "UMAP, (" + str(len(umap_T)) + " of " + total_train_size + ")", fontsize=7
    )

    if train_Y is not None and train_T is not None:
        ind_l_test = [i for i, x in enumerate(train_T) if x == target]
        Y_test_l = np.array([train_Y[i, :] for i in ind_l_test])

        ax1.scatter(
            Y_test_l[:, 0], Y_test_l[:, 1], s=size, c=col, marker=".", linewidth=0
        )
        ax1.set_title(
            "Train, (" + str(len(train_T)) + " of " + total_train_size + ")", fontsize=7
        )

    if test_Y is not None and test_T is not None:
        ind_l_test = [i for i, x in enumerate(test_T) if x == target]
        Y_test_l = np.array([test_Y[i, :] for i in ind_l_test])

        ax2.scatter(
            Y_test_l[:, 0], Y_test_l[:, 1], s=size, c=col, marker=".", linewidth=0
        )
        ax2.set_title(
            "Test, (" + str(len(test_T)) + " of " + total_test_size + ")", fontsize=7
        )

    plt.savefig(output_dir + "/" + info + "-umap.png")
    plt.close()


def visualize_umap_data(