def quantity_yXL(fig, left, bottom, top, quantity=params.L_yXL, label=r'<STR_LIT>'):
layers = ['<STR_LIT>', '<STR_LIT>', '<STR_LIT>', '<STR_LIT>', '<STR_LIT>']<EOL>ncols = len(params.y) / <NUM_LIT:4><EOL>vmin = <NUM_LIT:0><EOL>vmax = <NUM_LIT:0><EOL>for y in params.y:<EOL><INDENT>if quantity[y].max() > vmax:<EOL><INDENT>vmax = quantity[y].max()<EOL><DEDENT><DEDENT>gs = gridspec.GridSpec(<NUM_LIT:4>, <NUM_LIT:4>, left=left, bottom=bottom, top=top)<EOL>for i, y in enumerate(params.y):<EOL><INDENT>ax = fig.add_subplot(gs[i/<NUM_LIT:4>, i%<NUM_LIT:4>])<EOL>masked_array = np.ma.array(quantity[y], mask=quantity[y]==<NUM_LIT:0>)<EOL>im = ax.pcolormesh(masked_array,<EOL>vmin=vmin, vmax=vmax,<EOL>cmap=cmap,<EOL>)<EOL>ax.invert_yaxis()<EOL>ax.axis(ax.axis('<STR_LIT>'))<EOL>ax.xaxis.set_ticks_position('<STR_LIT>')<EOL>ax.set_xticks(np.arange(<NUM_LIT:9>)+<NUM_LIT:0.5>)<EOL>ax.set_yticks(np.arange(<NUM_LIT:5>)+<NUM_LIT:0.5>)<EOL>if i % <NUM_LIT:4> == <NUM_LIT:0>:<EOL><INDENT>ax.set_yticklabels(layers, )<EOL>ax.set_ylabel('<STR_LIT>', labelpad=<NUM_LIT:0.>)<EOL><DEDENT>else:<EOL><INDENT>ax.set_yticklabels([])<EOL><DEDENT>if i < <NUM_LIT:4>:<EOL><INDENT>ax.set_xlabel(r'<STR_LIT>', labelpad=-<NUM_LIT:1>,fontsize=<NUM_LIT:8>)<EOL>ax.set_xticklabels(params.X, rotation=<NUM_LIT>)<EOL><DEDENT>else:<EOL><INDENT>ax.set_xticklabels([])<EOL><DEDENT>ax.xaxis.set_label_position('<STR_LIT>')<EOL>ax.text(<NUM_LIT:0.5>, -<NUM_LIT>, r'<STR_LIT>'+y,<EOL>horizontalalignment='<STR_LIT>',<EOL>verticalalignment='<STR_LIT>',<EOL>transform=ax.transAxes,fontsize=<NUM_LIT>)<EOL><DEDENT>rect = np.array(ax.get_position().bounds)<EOL>rect[<NUM_LIT:0>] += rect[<NUM_LIT:2>] + <NUM_LIT><EOL>rect[<NUM_LIT:1>] = bottom<EOL>rect[<NUM_LIT:2>] = <NUM_LIT><EOL>rect[<NUM_LIT:3>] = top-bottom<EOL>cax = fig.add_axes(rect)<EOL>cbar = plt.colorbar(im, cax=cax)<EOL>cbar.set_label(label, labelpad=<NUM_LIT:0>)<EOL>
make a bunch of image plots, each showing the spatial normalized
    connectivity of synapses