def multi_plot_time(DataArray, SubSampleN=1, units='s', xlim=None, ylim=None, LabelArray=[], show_fig=True):
    """
    plot the time trace for multiple data sets on the same axes.

    Parameters
    ----------
    DataArray : array-like
        array of DataObject instances for which to plot the PSDs
    SubSampleN : int, optional
        Number of intervals between points to remove (to sub-sample data so
        that you effectively have lower sample rate to make plotting easier
        and quicker.
    xlim : array-like, optional
        2 element array specifying the lower and upper x limit for which to
        plot the time signal
    LabelArray : array-like, optional
        array of labels for each data-set to be plotted
    show_fig : bool, optional
       If True runs plt.show() before returning figure
       if False it just returns the figure object.
       (the default is True, it shows the figure) 

    Returns
    -------
    fig : matplotlib.figure.Figure object
        The figure object created
    ax : matplotlib.axes.Axes object
        The axes object created
    """
    unit_prefix = units[:-1] # removed the last char
    if LabelArray == []:
        LabelArray = ["DataSet {}".format(i)
                      for i in _np.arange(0, len(DataArray), 1)]
    fig = _plt.figure(figsize=properties['default_fig_size'])
    ax = fig.add_subplot(111)
    
    for i, data in enumerate(DataArray):
        ax.plot(unit_conversion(data.time.get_array()[::SubSampleN], unit_prefix), data.voltage[::SubSampleN],
                alpha=0.8, label=LabelArray[i])
    ax.set_xlabel("time (s)")
    if xlim != None:
        ax.set_xlim(xlim)
    if ylim != None:
        ax.set_ylim(ylim)
    ax.grid(which="major")
    legend = ax.legend(loc="best", frameon = 1)
    frame = legend.get_frame()
    frame.set_facecolor('white')
    frame.set_edgecolor('white')

    ax.set_ylabel("voltage (V)")
    if show_fig == True:
        _plt.show()
    return fig, ax
def multi_plot_time ( DataArray , SubSampleN = 1 , units = 's' , xlim = None , ylim = None , LabelArray = [ ] , show_fig = True ) : unit_prefix = units [ : - 1 ] if LabelArray == [ ] : LabelArray = [ "DataSet {}" . format ( i ) for i in _np . arange ( 0 , len ( DataArray ) , 1 ) ] fig = _plt . figure ( figsize = properties [ 'default_fig_size' ] ) ax = fig . add_subplot ( 111 ) for i , data in enumerate ( DataArray ) : ax . plot ( unit_conversion ( data . time . get_array ( ) [ : : SubSampleN ] , unit_prefix ) , data . voltage [ : : SubSampleN ] , alpha = 0.8 , label = LabelArray [ i ] ) ax . set_xlabel ( "time (s)" ) if xlim != None : ax . set_xlim ( xlim ) if ylim != None : ax . set_ylim ( ylim ) ax . grid ( which = "major" ) legend = ax . legend ( loc = "best" , frameon = 1 ) frame = legend . get_frame ( ) frame . set_facecolor ( 'white' ) frame . set_edgecolor ( 'white' ) ax . set_ylabel ( "voltage (V)" ) if show_fig == True : _plt . show ( ) return fig , ax
plot the time trace for multiple data sets on the same axes.

    Parameters
    ----------
    DataArray : array-like
        array of DataObject instances for which to plot the PSDs
    SubSampleN : int, optional
        Number of intervals between points to remove (to sub-sample data so
        that you effectively have lower sample rate to make plotting easier
        and quicker.
    xlim : array-like, optional
        2 element array specifying the lower and upper x limit for which to
        plot the time signal
    LabelArray : array-like, optional
        array of labels for each data-set to be plotted
    show_fig : bool, optional
       If True runs plt.show() before returning figure
       if False it just returns the figure object.
       (the default is True, it shows the figure) 

    Returns
    -------
    fig : matplotlib.figure.Figure object
        The figure object created
    ax : matplotlib.axes.Axes object
        The axes object created