I've recently been playing around with the Reverse Projection trick that I have read about on these forums. I'm a little confused though.
I plotted a graph of a normal projection matrix over a range of values from the near/far planes, and as expected, I got a graph that wasn't at all linear. Only values very close to the near plane had a range of say[0, 0.99], but 98% of the values were 0.99 or higher.
Having read about the Reverse Projection trick, and how it's supposed to give more of a linear distribution, I set up the same example with a Reverse Projection matrix, expecting to see more of a linear graph. So for example values half way between Near and Far to have a depth of around 0.5? .. but the graph looked exactly the same as without the Reverse Projection trick, just that it's upside down? so I don't understand how the Reverse Projection trick is actually working? how is it giving a better distribution if the graph is not more linear?
Or have I done something wrong, and the graph should look more linear?