Need Ternary Algorithms for 3D Graphics

[hemuman]

Hello All,

I am working on a separate project for displaying 3D objects on an applet, and allowing rotation and scaling of the objects.

I expect that ternary logic will give me faster display..as we require lots of mathematical operations during display/rotation and scaling.

I just wanted to know if any one has developed any code/theory on this topic using Ternary Logic? if not lets start....

[Mac Buster]

I know no attempts to use ternary logic to speed up 3D calculations. You'll be first there

[hemuman]

Lets get started then, first thing I would need is Ternary algorithm for Matrix Addition ,Multiplication and Transform...

I will start working on these, if any one is interested in contributing...u r most welcome

[hemuman]

As first Step for 3D Ternary logic, I am working on creating a virtual 3D space which will contain the 3D objects.

It is going to sound strange but I am representing 3D space in a singular space , to reduce the time complexity from
n^3 to n
And i need to check space complexity.
.... i.e. in a 1D array,

And the 3D space will be compressible.

Will keep posting as I progress...

[Mac Buster]

It sounds intriguing. Any news?

[hemuman]

yes,

today while attending a training session i formulated the way to relate 1D(Singular) universe to 3D with something like this:

1. For Rotation:
Singular_1D_(x)=f(theta);

where as,

f(theta)
{
Function of x,y,z and theta

return x;
}

2. For Transformation:
Singular_1D_(x)=f(x,y,z);

where as,

f(x,y,z)
{

Function of x,y,z

theta=constant

return x;
}

And 1D-Universe is represented in "Trytes"

and still working to display 1D in 3D display, i.e. figure out way to efficiently use the advantage of 1D array in calculations for 3D display.

I also found something interesting here:
Ternary Display

[hemuman]

I have started coding it and hv got a doubt i.e.

i am doing all 3D matrix operations in a 1D matrix.
Des it mean that here time colplexity O(T) has reduced from N^2 to N ?

[eudoxie]

It's hard to say without seeing your code, but in general, it's quite easy to make algorithms appear to have different complexity.

What happens is that you shift your algorithm from say O(Q^2) to apparent complexity O(P), where in reality P=Q^2.

Matrix transforms are usually so small that complexity is a bad metric to look at. You're better off looking at runtime, or number of operations or something.

[hemuman]

you got it right....it consumes time at runtime....

[Shaos]

moving up