Scripting Guide - JMP

20 Introducing JSL Chapter 1
Samples of JSL Scripts
matrix multiplication and division, determinants, eigenvalue decomposition, and so on. Thus you can
now perform custom calculations of your own.
For example, JSL has a straightforward notation for entering matrices:
L=[1 2 3, 4 5 6, 7 8 9, 10 11 12];
M=[0 1 2, 2 1 0, 0 1 1, 2 0 0];
N=[1 2 3 4, 4 3 2 1, 0 1 0 1];
O=[0 1 2, 2 1 0, 1 2 0];
Simple operations look like this:
R = L+M; // matrix addition
[ 1 3 5,
6 6 6,
7 9 10,
12 11 12]
Q=L*M`; // matrix multiplication of L by M-transpose
[ 8 4 5 2,
17 13 11 8,
26 22 17 14,
35 31 23 20]
You can even solve a linear system, that is, find the vector x for the square, nonsingular matrix A and
vector b you specify such that x = A – 1 b :
A=[1 -4 2, 3 3 2, 0 4 -1];
b=[1, 2, 1];
x=solve(A,b);
[-17,5,19]
For numerical work needing matrix factors, JMP offers operations such Cholesky, eigenvalue, and
singular-value decomposition:
E=[ 5 4 1 1, 4 5 1 1, 1 1 4 2, 1 1 2 4];
L=cholesky(E);
[ 2.2360679774998 0 0 0,
1.7888543819998 1.3416407864999 0 0,
0.4472135955 0.1490711985 1.9436506316151 0,
0.4472135955 0.1490711985 0.91465912076 1.7149858514251]
You can read the numeric columns of a data table into a matrix to perform custom calculations:
my matrix = current data table()