# Boost :

From: Janek Kozicki (janek_listy_at_[hidden])
Date: 2006-06-10 16:21:22

Janek Kozicki said: (by the date of Sat, 10 Jun 2006 22:07:36 +0200)

> I have found that excerpt in panda3d manual. But for whatever reasons in
> new release of manual they have removed this chapter. So I can't point
> some URL to it, instead I have added it as an attchment. (Note to
> readers: it is .html, you might want open it in your favourite browser).

oops. I see that this .html got stripped out for unknown reasons.

Copy/paste below. see pictures attached to previous post.

```--
Janek Kozicki                                                         |
Periodically, the question arises: does Panda store matrices in
column-major or row-major format? Unfortunately, people who ask that
question often fail to realize that there are four ways to represent
matrices, two of which are called "column major," and two of which are
called "row major." So the answer to the question is not very useful.
This section explains the four possible ways to represent matrices, and
then explains which one panda uses.
The Problem
In graphics, matrices are mainly used to transform vertices. So one way
to write a matrix is to write the four transform equations that it
represents. Assuming that the purpose of a matrix is to transform an
input-vector (Xi,Yi,Zi,Wi) into an output vector (Xo,Yo,Zo,Wo), the four
equations are:
Xo = A*Xi + B*Yi + C*Zi + D*Wi
Yo = E*Xi + F*Yi + G*Zi + H*Wi
Zo = J*Xi + K*Yi + L*Zi + M*Wi
Wo = N*Xi + O*Yi + P*Zi + Q*Wi
There are two different orders that you can store these coefficients in RAM:
Storage Option 1: A,B,C,D,E,F,G,H,J,K,L,M,N,O,P,Q
Storage Option 2: A,E,J,N,B,F,K,O,C,G,L,P,D,H,M,Q
Also, when you're typesetting these coefficients in a manual (or
printing them on the screen), there are two possible ways to typeset
them:
A B C D
E F G H
J K L M
N O P Q
Typesetting
Option 1

A E J N
B F K O
C G L P
D H M Q
Typesetting
Option 2
These are independent choices! There is no reliable relationship between
the order that people choose to store the numbers, and the order in
which they choose to typeset them. That means that any given system
could use one of four different notations.
So clearly, the two terms "row major" and "column major" are not enough
to distinguish the four possibilities. Worse yet, to my knowledge, there
is no established terminology to name the four possibilities. So the
next part of this section is dedicated to coming up with a usable
terminology.
The Coefficients are Derivatives
The equations above contain sixteen coefficients. Those coefficients are
derivatives. For example, the coefficient "G" could also be called "the
derivative of Yo with respect to Zi."
This gives us a handy way to refer to groups of coefficients.
Collectively, the coefficients "A,B,C,D" could also be called "the
derivatives of Xo with respect to Xi,Yi,Zi,Wi" or just "the derivatives
of Xo" for short. The coefficients "A,E,J,N" could also be called "the
derivatives of Xo,Yo,Zo,Wo with respect to Xi" or just "the derivatives
with respect to Xi" for short.
This is a good way to refer to groups of four coefficients because it
unambiguously names four of them without reference to which storage
option or which typesetting option you choose.
What to Call the Two Ways of Storing a Matrix.
So here, again, are the two ways of storing a matrix. But using this
newfound realization that the coefficients are derivatives, I have a
meaningful way to name the two different ways of storing a matrix:
Image:deriv-xo.png
Image:deriv-xi.png
In the first storage scheme, the derivatives of Xo are stored first. In
the second storage scheme, the derivatives with respect to Xi are stored
first.
What to Call the Two Ways of Printing a Matrix.
One way to write the four equations above is to write them out using
proper mathematical notation. There are two ways to do this, shown
below:
Image:matrix-c.png
Image:matrix-r.png
Notice that the two matrices shown above are laid out differently. The
first layout is the appropriate layout for use with column vectors. The
second layout is the appropriate layout for use with row vectors. So
that gives me a possible terminology for the two different ways of
typesetting a matrix: the "row-vector-compatible" notation, and the
"column-vector-compatible" notation.
The Four Possibilities
So now, the four possible representations that an engine could use are:
1. Store derivatives of Xo first, typeset in row-vector-compatible notation.
2. Store derivatives of Xo first, typeset in column-vector-compatible notation.
3. Store derivatives wrt Xi first, typeset in row-vector-compatible notation.
4. Store derivatives wrt Xi first, typeset in column-vector-compatible notation.
The Terms "Column Major" and "Row Major"
The term "row-major" means "the first four coefficients that you store,
are also the first row when you typeset." So the four possibilities
break down like this:
1. Store derivatives of Xo first, typeset in row-vector-compatible notation (COLUMN MAJOR)
2. Store derivatives of Xo first, typeset in column-vector-compatible notation (ROW MAJOR)
3. Store derivatives wrt Xi first, typeset in row-vector-compatible notation (ROW MAJOR)
4. Store derivatives wrt Xi first, typeset in column-vector-compatible notation (COLUMN MAJOR)
That makes the terms "row major" and "column major" singularly useless,
in my opinion. They tell you nothing about the actual storage or
typesetting order.
Panda Notation
Now that I've established my terminology, I can tell you what panda
uses. If you examine the panda source code, in the method
"LMatrix4f::xform," you will find the four transform equations. I have
simplified them somewhat (ie, removed some of the C++ quirks) in order
to put them here:
define VECTOR4_MATRIX4_PRODUCT(output, input, M) \
output._0 = input._0*M._00 + input._1*M._10 + input._2*M._20 + input._3*M._30; \
output._1 = input._0*M._01 + input._1*M._11 + input._2*M._21 + input._3*M._31; \
output._2 = input._0*M._02 + input._1*M._12 + input._2*M._22 + input._3*M._32; \
output._3 = input._0*M._03 + input._1*M._13 + input._2*M._23 + input._3*M._33;
Then, if you look in the corresponding header file for matrices, you
will see the matrix class definition:
struct {
FLOATTYPE _00, _01, _02, _03;
FLOATTYPE _10, _11, _12, _13;
FLOATTYPE _20, _21, _22, _23;
FLOATTYPE _30, _31, _32, _33;
} m;
So this class definition shows not only how the coefficients of the four
equations are stored, but also the layout in which they were intended to
be typeset. So from this, you can see that panda stores derivatives wrt
Xi first, and it typesets in row-vector-compatible notation.
Interoperability with OpenGL and DirectX
Panda is code-compatible with both OpenGL and DirectX. All three use the
same storage format: derivatives wrt Xi first. You can pass a panda
matrix directly to OpenGL's "glLoadMatrixf" or DirectX's "SetTransform".
However, remember that typesetting format and data storage format are
independent choices. Even though two engines are interoperable at the
code level (because their data storage formats match), their manuals
might disagree with each other (because their typesetting formats do not
match).
The panda typesetting conventions and the OpenGL typesetting conventions
are opposite from each other. The OpenGL manuals use a
column-vector-compatible notation. The Panda manuals use a
row-vector-compatible notation.
I do not know what typesetting conventions the DirectX manual uses.
```