annoviko / pyclustering

    """

    descriptors = [] * len(dynamic);

    # Check from the end for obtaining result

    for index_dyn in range(0, len(dynamic[0]), 1):

        if ((ignore is not None) and (index_dyn in ignore)):

            continue;

        time_stop_simulation = len(dynamic) - 1;

                waiting_differential = False;

            else:

                waiting_differential = True;

    return number_oscillations;

def allocate_sync_ensembles(dynamic, tolerance = 0.1, threshold = 1.0, ignore = None):

    """!

                    axes.plot(data[item][0], 0.0, color = color, marker = marker_descr);

            if (dimension == 2):

                if (data is None):

                    axes.plot(item[0], item[1], color = color, marker = marker_descr);

                else:

                    axes.plot(data[item][0], data[item][1], color = color, marker = marker_descr);

            elif (dimension == 3):

                if (data is None):

                    axes.scatter(item[0], item[1], item[2], c = color, marker = marker_descr);

        raise NameError('Impossible to represent clusters due to number of specified colors.');

    fig = plt.figure();

    if (axes is None):

        # Check for dimensions

        if ((dimension) == 1 or (dimension == 2)):

            axes = fig.add_subplot(111);

        elif (dimension == 3):

            axes = fig.gca(projection='3d');

        else:

    @return (fig) Figure where clusters are shown.

    """

    def __draw_canvas_cluster(self, ax, dimension, cluster_descr):

        cluster = cluster_descr.cluster;

        data = cluster_descr.data;

        marker = cluster_descr.marker;

        markersize = cluster_descr.markersize;

        color = cluster_descr.color;

    """!

    @brief Draw canvas cluster descriptor.

    @param[in] ax (Axis): Axis of the canvas where canvas cluster descriptor should be displayed.

    @param[in] dimension (uint): Canvas dimension.

    @param[in] cluster_descr (canvas_cluster_descr): Canvas cluster descriptor that should be displayed.

    @return (fig) Figure where clusters are shown.

    """

    def __draw_canvas_cluster(self, ax, dimension, cluster_descr):