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source = ColumnDataSource(stat_data_df)
#curdoc().theme = 'light_minimal'


#Add plot main
def create_marginal_plot(source,x_axis_label, y_axis_label, n_bin_h, n_bin_v):       
    plot_options_main = dict(width=700, plot_height=500, 
                            tools=('pan,wheel_zoom,box_zoom,reset, crosshair'))
    
    plot_main = figure(
        toolbar_location=None,
        x_axis_label = x_axis_label,
        y_axis_label = y_axis_label,
        **plot_options_main
        )
    plot_main.background_fill_color = "#fafafa"
    plot_main.scatter(x ="x", y = "y", 
              source = source,color="#3A5785")
    
    #create the horizontal histo
    hhist, hedges = np.histogram(source.data['x'], bins=n_bin_h)
    hzeros = np.zeros(len(hedges)-1)
    hmax = max(hhist)*1.1
    
    LINE_ARGS = dict(color="#3A5785", line_color=None)
    
    ph = figure(toolbar_location=None,
                plot_width=plot_main.plot_width, 
                plot_height=200, 
                min_border=10, min_border_left=50, y_axis_location="left")
    #ph.xgrid.grid_line_color = None
    ph.yaxis.major_label_orientation = np.pi/4
    ph.background_fill_color = "#fafafa"
    
    ph.quad(bottom=0, left=hedges[:-1], right=hedges[1:], top=hhist, 
            color="white", line_color="#3A5785")
    ph.quad(bottom=0, left=hedges[:-1], right=hedges[1:], top=hzeros, 
            alpha=0.5, **LINE_ARGS)
    ph.quad(bottom=0, left=hedges[:-1], right=hedges[1:], top=hzeros, 
            alpha=0.1, **LINE_ARGS)
    
    
    # create the vertical histogram
    vhist, vedges = np.histogram(source.data['y'], bins=n_bin_v)
    vzeros = np.zeros(len(vedges)-1)
    vmax = max(vhist)*1.1
    
    pv = figure(toolbar_location=None, plot_width=200,y_axis_location=None,
                plot_height=plot_main.plot_height,
                
                min_border=10)
    pv.ygrid.grid_line_color = None
    pv.xaxis.major_label_orientation = np.pi/4
    pv.background_fill_color = "#fafafa"
    
    pv.quad(left=0, bottom=vedges[:-1], top=vedges[1:], right=vhist, 
            color="white", line_color="#3A5785")
    pv.quad(left=0, bottom=vedges[:-1], top=vedges[1:], right=vzeros, 
            alpha=0.5, **LINE_ARGS)
    pv.quad(left=0, bottom=vedges[:-1], top=vedges[1:], right=vzeros, 
            alpha=0.1, **LINE_ARGS)
 
    return plot_main, pv, ph 



x_axis_label = stat_data[stat_data_df.columns[5]]['unit_x']
y_axis_label = stat_data[stat_data_df.columns[7]]['unit_y']

output_file('Dashboard.html')
plot_main, pv, ph = create_marginal_plot(source,x_axis_label, y_axis_label, n_bin_h, n_bin_v)



callback_x = CustomJS(args={'source':source},code="""
        // print the selectd value of the select widget - 
        // this is printed in the browser console.
        // cb_obj is the callback object, in this case the select 
        // widget. cb_obj.value is the selected value.
        console.log(' changed selected option', cb_obj.value);

        // create a new variable for the data of the column data source
        // this is linked to the plot
        var data = source.data;

        // allocate the selected column to the field for the y values
        data['x'] = data[cb_obj.value];

        // register the change - this is required to process the change in 
        // the y values
        source.change.emit();
""")

callback_y = CustomJS(args={'source':source},code="""
        // print the selectd value of the select widget - 
        // this is printed in the browser console.
        // cb_obj is the callback object, in this case the select 
        // widget. cb_obj.value is the selected value.
        console.log(' changed selected option', cb_obj.value);

        // create a new variable for the data of the column data source
        // this is linked to the plot
        var data = source.data;

        // allocate the selected column to the field for the y values
        data['y'] = data[cb_obj.value];

        // register the change - this is required to process the change in 
        // the y values
        source.change.emit();
""")

#add dropdown menu
select_x = Select(title="Value X:", value=def_x_channel, options=channel_list,
                  callback=callback_x)
select_y = Select(title="Value Y", value=def_y_channel, options=channel_list,
                  callback = callback_y)

p = gridplot([[ ph,None], [plot_main,pv ]], merge_tools=False,
                 toolbar_location=None)

layout = gridplot([[column(select_x, select_y),None], [p,None]],
                  toolbar_location=None)

   
show(layout)