img = ax.imshow(event, **cmap_args)
plt.colorbar(img)

palette=mpl.cm.get_cmap("viridis",lut=levels).copy()     #simulate the level arg of other plot methods
palette.set_under((0,0,0,0))                             #So vmin has an effect
if add_colorbar:

vmax = np.max(NPArr)                                    #NPArr is the data being plotted
norm = mpl.colors.Normalize(0,vmax)                     #Necessary because there is no mappable from voxels, instead of normalizing the data it is easier to normalize the "cmap"
m = cm.ScalarMappable(cmap=palette,norm=norm)           #Creates Mappable
m.set_array([])                                         #Makes it the right type so get() methods exist
ticks = np.linspace(1,vmax,levels+1)
fig.colorbar(m, ax=ax, extend="min", ticks=ticks)       #Finally creates the cmap with other cmap arguments that can't be passed to the mappable