Matrix Multiplication in C[++]

thomthom

transformation * transformation works.

The docs says

point1
A Point3d, Vector3d, or Transformation object.

MartinRinehart

transformation * transformation works.

The docs says

@unknownuser said:

point1
A Point3d, Vector3d, or Transformation object.

Blind me! Many thanks.

MartinRinehart

Blind me? Maybe it was, "Lucky me."

Transformation * Transformation multiplies the 3x3 rotation/scale matrix. It does not handle location. My code multiplies the 4x4 matrices. Here are the results:

xform:
1.0, 0.0, 0.0, 0.0 0.0, 1.0, 0.0, 0.0 0.0, 0.0, 1.0, 0.0 20.0, 0.0, 0.0, 1.0

Asked for Transformation.rotation( [0,0,0], [0,1,0], 30 ). Got:

0.866025403784439, 0.0, -0.5, 0.0 0.0, 1.0, 0.0, 0.0 0.5, 0.0, 0.866025403784439, 0.0 0.0, 0.0, 0.0, 1.0

Used Transformation * Transformation, then move!().

xform:
0.866025403784439, 0.0, -0.5, 0.0 0.0, 1.0, 0.0, 0.0 0.5, 0.0, 0.866025403784439, 0.0 20.0, 0.0, 0.0, 1.0

Not my idea of rotating around the origin. So I tried again, using my own matrix multiplication:

xform:
0.866025403784439, 0.0, -0.5, 0.0 0.0, 1.0, 0.0, 0.0 0.5, 0.0, 0.866025403784439, 0.0 17.3205080756888, 0.0, -10, 1.0

My own version appears to rotate around the origin.

Anybody wanting to fiddle with this, here's a little Matrix class. You create a Matrix with Matrix.new( nrows, ncols, [array of values] ). From a Transformation, that's Matrix.new( 4, 4, xform.to_a() ). Individual values may be retrieved by subscripting: m1[3,3] is the global scale factor, Wt. You multiply by multiplying: m1 * m2. ( instance_xform * new_xform. It's not commutative.)

class Matrix
=begin
You can multiply one matrix by another with this class.

In m1 * m2, the number of rows in m1 must equal the number of columns in m2. This code does absolutely no checking. Program must check sizes before calling this code! (Application herein; square matrices of equal size, where this is not an issue.) 
=end
    
    attr_reader ;nrows, ;ncols, ;values
    
    def initialize( nrows, ncols, values )
        @nrows = nrows
        @ncols = ncols
        @values = values
    end # of initialize()
    
    def * ( m2 )
        vals = []
        for r in 0..(@nrows-1)
            for c in 0..(m2.ncols-1)
                vals.push( row_col(row( r ), m2.col( c )) )
            end
        end
        return Matrix.new( @nrows, m2.ncols, vals )
    end # of *()

    def [] ( row, col )
        return @values[ row * @ncols + col ]
    end # of []()
    
    def col( c )
        ret = []
        for r in 0..(@nrows-1)
            ret.push( @values[r*@ncols + c] )
        end
        return ret
    end # of col()

    def row( r )
        start = r * @ncols
        return @values[ start .. (start + @ncols - 1) ]
    end # of row()
    
    def row_col( row, col )
        ret = 0
        for i in 0..(row.length()-1)
            ret += row[ i ] * col[ i ]
        end
        return ret
    end
    
    def inspect()
        ret = ''
        for r in 0..(@nrows-1)
            for c in 0..(@ncols-1)
                ret += self[r, c].to_s
                ret += ', ' if c < (@ncols-1)
            end
            ret += "\n"
        end
        return ret
    end # of inspect()
    
end # of class Matrix

Anybody not believing what I say (that included me!) is invited to try for themselves.

Chris Fullmer

I have not read much of this thread yet, just enough to see that you can multiply a transformation by a point3d?????

That might be the missing link for moving an object to a specified point, retaining scale/rotation and not having to tweak the matrix manually. I'll investigate that, along with Martin's code later tonight if all goes well,

Chris - I'm excited about this development.

Chris Fullmer

Nope, my mistake. Now that i've had a chance to look at it, and think it through, multiplying a transformation by a point 3d moves the transformation by the vector defined by the point at the component axis to the point specified.

I guess my prefered way to translate to a specific point is still done be finding the vector to that point from the given point and then .transform! to that point.

Chris

Now its time to read Martin's post thoroughly.

MartinRinehart

My third screenshot could have been clearer. This is an elaboration:

Pixero

This is what I learned when I wrote my MentalRay transformation matrix plugin.
Maybe this info can be of some help:

A transformation matrix is made of these components and multipled in the following order:

Scale pivot point: point around which scales are performed [Sp]

Scale: scaling about x, y, z axes [S]

Shear: shearing in xy, xz, yx [Sh]

Scale pivot translation: translation introduced to preserve existing scale transformations when moving pivot.
This is used to prevent the object from moving when the objects pivot point is not at the origin and a non-unit scale is applied to the object [St].

Rotate pivot: point point about which rotations are performed [Rp]

Rotation orientation: rotation to orient local rotation space [Ro]

Rotation: rotation [R]

Rotate pivot translation: translation introduced to preserve exisiting rotate transformations when moving pivot.
This is used to prevent the object from moving when the objects pivot point is not at the origin and the pivot is moved. [Rt]

Translate: translation in x, y, z axes [T]

The transformation matrix is then constructed as follows:

[Sp(Inverse)] x [S] x [Sh] x [Sp] x [St] x [Rp(Inverse)] x [Ro] x [R] x [Rp] x [Rt] x [T]

cjthompson

Can anyone explain why (transformation1 * transformation2) isn't the same as (transformation2 * transformation1)?

Anyways, it looks like if you use move!, you have two options, from a practical standpoint:
instance.move!(newTransformation*instance.transformation), which is essentially the same as (instance.transform!(newTransformation)) and
instance.move!(instance.transformation*newTransformation), which will apply the transformation according to the component's axes.

thomthom

@cjthompson said:

Can anyone explain why (transformation1 * transformation2) isn't the same as (transformation2 * transformation1)?

+1

Chris Fullmer

I like those lines of code Chris, I want to test those later tonight.

Chris