代码拉取完成,页面将自动刷新
//-----------------------------------------------------------------------------
//
// Compute eigenvalues and eigenvectors
//
// Input: stack[tos - 1] symmetric matrix
//
// Output: D diagnonal matrix
//
// Q eigenvector matrix
//
// D and Q have the property that
//
// A == dot(transpose(Q),D,Q)
//
// where A is the original matrix.
//
// The eigenvalues are on the diagonal of D.
//
// The eigenvectors are row vectors in Q.
//
// The eigenvalue relation
//
// A X = lambda X
//
// can be checked as follows:
//
// lambda = D[1,1]
//
// X = Q[1]
//
// dot(A,X) - lambda X
//
//-----------------------------------------------------------------------------
#include "stdafx.h"
#include "defs.h"
#define D(i, j) yydd[n * (i) + (j)]
#define Q(i, j) yyqq[n * (i) + (j)]
extern void copy_tensor(void);
static void eigen(int);
static int check_arg(void);
static int step(void);
static void step2(int, int);
static int n;
static double *yydd, *yyqq;
void
eval_eigen(void)
{
if (check_arg() == 0)
stop("eigen: argument is not a square matrix");
eigen(EIGEN);
p1 = usr_symbol("D");
set_binding(p1, p2);
p1 = usr_symbol("Q");
set_binding(p1, p3);
push(symbol(NIL));
}
void
eval_eigenval(void)
{
if (check_arg() == 0) {
push_symbol(EIGENVAL);
push(p1);
list(2);
return;
}
eigen(EIGENVAL);
push(p2);
}
void
eval_eigenvec(void)
{
if (check_arg() == 0) {
push_symbol(EIGENVEC);
push(p1);
list(2);
return;
}
eigen(EIGENVEC);
push(p3);
}
static int
check_arg(void)
{
int i, j;
push(cadr(p1));
eval();
yyfloat();
eval();
p1 = pop();
if (!istensor(p1))
return 0;
if (p1->u.tensor->ndim != 2 || p1->u.tensor->dim[0] != p1->u.tensor->dim[1])
stop("eigen: argument is not a square matrix");
n = p1->u.tensor->dim[0];
for (i = 0; i < n; i++)
for (j = 0; j < n; j++)
if (!isdouble(p1->u.tensor->elem[n * i + j]))
stop("eigen: matrix is not numerical");
for (i = 0; i < n - 1; i++)
for (j = i + 1; j < n; j++)
if (fabs(p1->u.tensor->elem[n * i + j]->u.d - p1->u.tensor->elem[n * j + i]->u.d) > 1e-10)
stop("eigen: matrix is not symmetrical");
return 1;
}
//-----------------------------------------------------------------------------
//
// Input: p1 matrix
//
// Output: p2 eigenvalues
//
// p3 eigenvectors
//
//-----------------------------------------------------------------------------
static void
eigen(int op)
{
int i, j;
// malloc working vars
yydd = (double *) malloc(n * n * sizeof (double));
if (yydd == NULL)
stop("malloc failure");
yyqq = (double *) malloc(n * n * sizeof (double));
if (yyqq == NULL)
stop("malloc failure");
// initialize D
for (i = 0; i < n; i++) {
D(i, i) = p1->u.tensor->elem[n * i + i]->u.d;
for (j = i + 1; j < n; j++) {
D(i, j) = p1->u.tensor->elem[n * i + j]->u.d;
D(j, i) = p1->u.tensor->elem[n * i + j]->u.d;
}
}
// initialize Q
for (i = 0; i < n; i++) {
Q(i, i) = 1.0;
for (j = i + 1; j < n; j++) {
Q(i, j) = 0.0;
Q(j, i) = 0.0;
}
}
// step up to 100 times
for (i = 0; i < 100; i++)
if (step() == 0)
break;
if (i == 100)
printstr("\nnote: eigen did not converge\n");
// p2 = D
if (op == EIGEN || op == EIGENVAL) {
push(p1);
copy_tensor();
p2 = pop();
for (i = 0; i < n; i++) {
for (j = 0; j < n; j++) {
push_double(D(i, j));
p2->u.tensor->elem[n * i + j] = pop();
}
}
}
// p3 = Q
if (op == EIGEN || op == EIGENVEC) {
push(p1);
copy_tensor();
p3 = pop();
for (i = 0; i < n; i++) {
for (j = 0; j < n; j++) {
push_double(Q(i, j));
p3->u.tensor->elem[n * i + j] = pop();
}
}
}
// free working vars
free(yydd);
free(yyqq);
}
//-----------------------------------------------------------------------------
//
// Example: p = 1, q = 3
//
// c 0 s 0
//
// 0 1 0 0
// G =
// -s 0 c 0
//
// 0 0 0 1
//
// The effect of multiplying G times A is...
//
// row 1 of A = c (row 1 of A ) + s (row 3 of A )
// n+1 n n
//
// row 3 of A = c (row 3 of A ) - s (row 1 of A )
// n+1 n n
//
// In terms of components the overall effect is...
//
// row 1 = c row 1 + s row 3
//
// A[1,1] = c A[1,1] + s A[3,1]
//
// A[1,2] = c A[1,2] + s A[3,2]
//
// A[1,3] = c A[1,3] + s A[3,3]
//
// A[1,4] = c A[1,4] + s A[3,4]
//
// row 3 = c row 3 - s row 1
//
// A[3,1] = c A[3,1] - s A[1,1]
//
// A[3,2] = c A[3,2] - s A[1,2]
//
// A[3,3] = c A[3,3] - s A[1,3]
//
// A[3,4] = c A[3,4] - s A[1,4]
//
// T
// The effect of multiplying A times G is...
//
// col 1 of A = c (col 1 of A ) + s (col 3 of A )
// n+1 n n
//
// col 3 of A = c (col 3 of A ) - s (col 1 of A )
// n+1 n n
//
// In terms of components the overall effect is...
//
// col 1 = c col 1 + s col 3
//
// A[1,1] = c A[1,1] + s A[1,3]
//
// A[2,1] = c A[2,1] + s A[2,3]
//
// A[3,1] = c A[3,1] + s A[3,3]
//
// A[4,1] = c A[4,1] + s A[4,3]
//
// col 3 = c col 3 - s col 1
//
// A[1,3] = c A[1,3] - s A[1,1]
//
// A[2,3] = c A[2,3] - s A[2,1]
//
// A[3,3] = c A[3,3] - s A[3,1]
//
// A[4,3] = c A[4,3] - s A[4,1]
//
// What we want to do is just compute the upper triangle of A since we
// know the lower triangle is identical.
//
// In other words, we just want to update components A[i,j] where i < j.
//
//-----------------------------------------------------------------------------
//
// Example: p = 2, q = 5
//
// p q
//
// j=1 j=2 j=3 j=4 j=5 j=6
//
// i=1 . A[1,2] . . A[1,5] .
//
// p i=2 A[2,1] A[2,2] A[2,3] A[2,4] A[2,5] A[2,6]
//
// i=3 . A[3,2] . . A[3,5] .
//
// i=4 . A[4,2] . . A[4,5] .
//
// q i=5 A[5,1] A[5,2] A[5,3] A[5,4] A[5,5] A[5,6]
//
// i=6 . A[6,2] . . A[6,5] .
//
//-----------------------------------------------------------------------------
//
// This is what B = GA does:
//
// row 2 = c row 2 + s row 5
//
// B[2,1] = c * A[2,1] + s * A[5,1]
// B[2,2] = c * A[2,2] + s * A[5,2]
// B[2,3] = c * A[2,3] + s * A[5,3]
// B[2,4] = c * A[2,4] + s * A[5,4]
// B[2,5] = c * A[2,5] + s * A[5,5]
// B[2,6] = c * A[2,6] + s * A[5,6]
//
// row 5 = c row 5 - s row 2
//
// B[5,1] = c * A[5,1] + s * A[2,1]
// B[5,2] = c * A[5,2] + s * A[2,2]
// B[5,3] = c * A[5,3] + s * A[2,3]
// B[5,4] = c * A[5,4] + s * A[2,4]
// B[5,5] = c * A[5,5] + s * A[2,5]
// B[5,6] = c * A[5,6] + s * A[2,6]
//
// T
// This is what BG does:
//
// col 2 = c col 2 + s col 5
//
// B[1,2] = c * A[1,2] + s * A[1,5]
// B[2,2] = c * A[2,2] + s * A[2,5]
// B[3,2] = c * A[3,2] + s * A[3,5]
// B[4,2] = c * A[4,2] + s * A[4,5]
// B[5,2] = c * A[5,2] + s * A[5,5]
// B[6,2] = c * A[6,2] + s * A[6,5]
//
// col 5 = c col 5 - s col 2
//
// B[1,5] = c * A[1,5] - s * A[1,2]
// B[2,5] = c * A[2,5] - s * A[2,2]
// B[3,5] = c * A[3,5] - s * A[3,2]
// B[4,5] = c * A[4,5] - s * A[4,2]
// B[5,5] = c * A[5,5] - s * A[5,2]
// B[6,5] = c * A[6,5] - s * A[6,2]
//
//-----------------------------------------------------------------------------
//
// Step 1: Just do upper triangle (i < j), B[2,5] = 0
//
// B[1,2] = c * A[1,2] + s * A[1,5]
//
// B[2,3] = c * A[2,3] + s * A[5,3]
// B[2,4] = c * A[2,4] + s * A[5,4]
// B[2,6] = c * A[2,6] + s * A[5,6]
//
// B[1,5] = c * A[1,5] - s * A[1,2]
// B[3,5] = c * A[3,5] - s * A[3,2]
// B[4,5] = c * A[4,5] - s * A[4,2]
//
// B[5,6] = c * A[5,6] + s * A[2,6]
//
//-----------------------------------------------------------------------------
//
// Step 2: Transpose where i > j since A[i,j] == A[j,i]
//
// B[1,2] = c * A[1,2] + s * A[1,5]
//
// B[2,3] = c * A[2,3] + s * A[3,5]
// B[2,4] = c * A[2,4] + s * A[4,5]
// B[2,6] = c * A[2,6] + s * A[5,6]
//
// B[1,5] = c * A[1,5] - s * A[1,2]
// B[3,5] = c * A[3,5] - s * A[2,3]
// B[4,5] = c * A[4,5] - s * A[2,4]
//
// B[5,6] = c * A[5,6] + s * A[2,6]
//
//-----------------------------------------------------------------------------
//
// Step 3: Same as above except reorder
//
// k < p (k = 1)
//
// A[1,2] = c * A[1,2] + s * A[1,5]
// A[1,5] = c * A[1,5] - s * A[1,2]
//
// p < k < q (k = 3..4)
//
// A[2,3] = c * A[2,3] + s * A[3,5]
// A[3,5] = c * A[3,5] - s * A[2,3]
//
// A[2,4] = c * A[2,4] + s * A[4,5]
// A[4,5] = c * A[4,5] - s * A[2,4]
//
// q < k (k = 6)
//
// A[2,6] = c * A[2,6] + s * A[5,6]
// A[5,6] = c * A[5,6] - s * A[2,6]
//
//-----------------------------------------------------------------------------
static int
step(void)
{
int count, i, j;
count = 0;
// for each upper triangle "off-diagonal" component do step2
for (i = 0; i < n - 1; i++) {
for (j = i + 1; j < n; j++) {
if (D(i, j) != 0.0) {
step2(i, j);
count++;
}
}
}
return count;
}
static void
step2(int p, int q)
{
int k;
double t, theta;
double c, cc, s, ss;
// compute c and s
// from Numerical Recipes (except they have a_qq - a_pp)
theta = 0.5 * (D(p, p) - D(q, q)) / D(p, q);
t = 1.0 / (fabs(theta) + sqrt(theta * theta + 1.0));
if (theta < 0.0)
t = -t;
c = 1.0 / sqrt(t * t + 1.0);
s = t * c;
// D = GD
// which means "add rows"
for (k = 0; k < n; k++) {
cc = D(p, k);
ss = D(q, k);
D(p, k) = c * cc + s * ss;
D(q, k) = c * ss - s * cc;
}
// D = D transpose(G)
// which means "add columns"
for (k = 0; k < n; k++) {
cc = D(k, p);
ss = D(k, q);
D(k, p) = c * cc + s * ss;
D(k, q) = c * ss - s * cc;
}
// Q = GQ
// which means "add rows"
for (k = 0; k < n; k++) {
cc = Q(p, k);
ss = Q(q, k);
Q(p, k) = c * cc + s * ss;
Q(q, k) = c * ss - s * cc;
}
D(p, q) = 0.0;
D(q, p) = 0.0;
}
#if SELFTEST
static const char *s[] = {
"eigen(A)",
"Stop: eigen: argument is not a square matrix",
"eigenval(A)",
"eigenval(A)",
"eigenvec(A)",
"eigenvec(A)",
"eigen((1,2))",
"Stop: eigen: argument is not a square matrix",
"eigen(((1,2),(1,2)))",
"Stop: eigen: matrix is not symmetrical",
"eigenval(((1,1,1,1),(1,2,3,4),(1,3,6,10),(1,4,10,20)))",
"((0.038016,0,0,0),(0,0.453835,0,0),(0,0,2.20345,0),(0,0,0,26.3047))",
"eigenvec(((1,1,1,1),(1,2,3,4),(1,3,6,10),(1,4,10,20)))",
"((0.308686,-0.72309,0.594551,-0.168412),(0.787275,-0.163234,-0.532107,0.265358),(0.530366,0.640332,0.391832,-0.393897),(0.0601867,0.201173,0.458082,0.863752))",
"eigen(hilbert(50))",
"",
"1+trace(hilbert(50))-trace(dot(transpose(Q),D,Q))",
"1",
"D=quote(D)",
"",
"Q=quote(Q)",
"",
"A=hilbert(3)",
"",
"eigen(A)",
"",
"D-eigenval(A)",
"((0,0,0),(0,0,0),(0,0,0))",
"Q-eigenvec(A)",
"((0,0,0),(0,0,0),(0,0,0))",
"A=quote(A)",
"",
"D=quote(D)",
"",
"Q=quote(Q)",
"",
};
void
test_eigen(void)
{
test(__FILE__, s, sizeof s / sizeof (char *));
}
#endif
此处可能存在不合适展示的内容,页面不予展示。您可通过相关编辑功能自查并修改。
如您确认内容无涉及 不当用语 / 纯广告导流 / 暴力 / 低俗色情 / 侵权 / 盗版 / 虚假 / 无价值内容或违法国家有关法律法规的内容,可点击提交进行申诉,我们将尽快为您处理。