annoviko / pyclustering

        active_state = False;

        if (dynamic[time_stop_simulation][index_dyn] > threshold):

            active_state = True;

        # if active state is detected, it means we don't have whole oscillatory period for the considered oscillator, should be skipped.

        if (active_state is True):

            while ( (dynamic[time_stop_simulation][index_dyn] > threshold) and (time_stop_simulation > 0) ):

                time_stop_simulation -= 1;

    @brief Allocate clusters in line with ensembles of synchronous oscillators where each

           synchronous ensemble corresponds to only one cluster.

    @param[in] dynamic (dynamic): Dynamic of each oscillator.

    @param[in] tolerance (double): Maximum error for allocation of synchronous ensemble oscillators.

    @param[in] threshold (double): Amlitude trigger when spike is taken into account.

    @param[in] ignore (bool): Set of indexes that shouldn't be taken into account.

    @return (list) Grours (lists) of indexes of synchronous oscillators, for example, 

            [ [index_osc1, index_osc3], [index_osc2], [index_osc4, index_osc5] ].

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

                else:

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

        color_index += 1;

    for item in noise:

        if (dimension == 1):

            if (data is None):

                axes.plot(item[0], 0.0, 'w' + marker_descr);

            else:

        else:

            raise NameError('Drawer supports only 2d and 3d data representation');

    color_index = 0;

    for cluster in clusters:

        color = colors[color_index];

        for item in cluster:

            if (dimension == 1):

                if (data is None):

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

                else:

                    ax.plot(data[item][0], 0.0, color = color, marker = marker, markersize = markersize);

            elif (dimension == 2):

                if (data is None):

                    ax.plot(item[0], item[1], color = color, marker = marker, markersize = markersize);

                else:

                    ax.plot(data[item][0], data[item][1], color = color, marker = marker, markersize = markersize);

            elif (dimension == 3):

                if (data is None):

        color = cluster_descr.color;

        for item in cluster:

            if (dimension == 1):

                if (data is None):

                    ax.plot(item[0], 0.0, color = color, marker = marker, markersize = markersize);

                else:

                    ax.plot(data[item][0], 0.0, color = color, marker = marker, markersize = markersize);

            elif (dimension == 2):

                if (data is None):