annoviko / pyclustering

                waiting_differential = False;

            else:

                waiting_differential = True;

    return number_oscillations;

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

    """!

    """

    number_oscillations = 0;

    waiting_differential = False;

    threshold_passed = False;

    high_level_trigger = True if (osc_dyn[0][index] > amplitude_threshold) else False;

    for values in osc_dyn:

        if ( (values[index] >= amplitude_threshold) and (high_level_trigger is False) ):

        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:

    @param[in] display_result (bool): If specified then matplotlib axes will be used for drawing and plot will not be shown.

    @return (ax) Matplotlib axes where drawn clusters are presented.

    """

    # Get dimension

    dimension = 0;

    if ( (data is not None) and (clusters is not None) ):

        dimension = len(data[0]);

    elif ( (data is None) and (clusters is not None) ):

        dimension = len(clusters[0][0]);

    """!

    @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.

            ax.grid(visible_grid);

        if (display is True):

            plt.show();

        return cluster_figure;

    """!

    @brief Draw canvas cluster descriptor.