heatmap(dm, partition=None, cmap=CM.Blues, fontsize=10)
    
    Produce a 2D plot of the distance matrix, with values encoded by
    coloured cells.

    Args:
        partition: treeCl.Partition object - if supplied, will reorder
                   rows and columns of the distance matrix to reflect
                   the groups defined by the partition
        cmap: matplotlib colourmap object  - the colour palette to use
        fontsize: int or None - sets the size of the locus lab

    Returns:
        matplotlib plottable object

def heatmap(dm, partition=None, cmap=CM.Blues, fontsize=10):
    """ heatmap(dm, partition=None, cmap=CM.Blues, fontsize=10)
    
    Produce a 2D plot of the distance matrix, with values encoded by
    coloured cells.

    Args:
        partition: treeCl.Partition object - if supplied, will reorder
                   rows and columns of the distance matrix to reflect
                   the groups defined by the partition
        cmap: matplotlib colourmap object  - the colour palette to use
        fontsize: int or None - sets the size of the locus lab

    Returns:
        matplotlib plottable object
    """
    assert isinstance(dm, DistanceMatrix)
    datamax = float(np.abs(dm.values).max())
    length = dm.shape[0]

    if partition:
        sorting = np.array(flatten_list(partition.get_membership()))
        new_dm = dm.reorder(dm.df.columns[sorting])
    else:
        new_dm = dm

    fig = plt.figure()
    ax = fig.add_subplot(111)
    
    ax.xaxis.tick_top()
    ax.grid(False)

    tick_positions = np.array(list(range(length))) + 0.5
    if fontsize is not None:
        ax.set_yticks(tick_positions)
        ax.set_xticks(tick_positions)
        ax.set_xticklabels(new_dm.df.columns, rotation=90, fontsize=fontsize, ha='center')
        ax.set_yticklabels(new_dm.df.index, fontsize=fontsize, va='center')

    cbar_ticks_at = [0, 0.5 * datamax, datamax]
    
    cax = ax.imshow(
        new_dm.values,
        interpolation='nearest',
        extent=[0., length, length, 0.],
        vmin=0,
        vmax=datamax,
        cmap=cmap,
    )
    cbar = fig.colorbar(cax, ticks=cbar_ticks_at, format='%1.2g')
    cbar.set_label('Distance')
    return fig