dlantb function
Implementation
double dlantb(
final String NORM,
final String UPLO,
final String DIAG,
final int N,
final int K,
final Matrix<double> AB_,
final int LDAB,
final Array<double> WORK_,
) {
final AB = AB_.having(ld: LDAB);
final WORK = WORK_.having();
const ONE = 1.0, ZERO = 0.0;
bool UDIAG;
int I, J, L;
double VALUE = 0;
final SCALE = Box(0.0), SUM = Box(0.0);
if (N == 0) {
VALUE = ZERO;
} else if (lsame(NORM, 'M')) {
// Find max(abs(A(i,j))).
if (lsame(DIAG, 'U')) {
VALUE = ONE;
if (lsame(UPLO, 'U')) {
for (J = 1; J <= N; J++) {
for (I = max(K + 2 - J, 1); I <= K; I++) {
SUM.value = AB[I][J].abs();
if (VALUE < SUM.value || disnan(SUM.value)) VALUE = SUM.value;
}
}
} else {
for (J = 1; J <= N; J++) {
for (I = 2; I <= min(N + 1 - J, K + 1); I++) {
SUM.value = AB[I][J].abs();
if (VALUE < SUM.value || disnan(SUM.value)) VALUE = SUM.value;
}
}
}
} else {
VALUE = ZERO;
if (lsame(UPLO, 'U')) {
for (J = 1; J <= N; J++) {
for (I = max(K + 2 - J, 1); I <= K + 1; I++) {
SUM.value = AB[I][J].abs();
if (VALUE < SUM.value || disnan(SUM.value)) VALUE = SUM.value;
}
}
} else {
for (J = 1; J <= N; J++) {
for (I = 1; I <= min(N + 1 - J, K + 1); I++) {
SUM.value = AB[I][J].abs();
if (VALUE < SUM.value || disnan(SUM.value)) VALUE = SUM.value;
}
}
}
}
} else if ((lsame(NORM, 'O')) || (NORM == '1')) {
// Find norm1(A).
VALUE = ZERO;
UDIAG = lsame(DIAG, 'U');
if (lsame(UPLO, 'U')) {
for (J = 1; J <= N; J++) {
if (UDIAG) {
SUM.value = ONE;
for (I = max(K + 2 - J, 1); I <= K; I++) {
SUM.value += AB[I][J].abs();
}
} else {
SUM.value = ZERO;
for (I = max(K + 2 - J, 1); I <= K + 1; I++) {
SUM.value += AB[I][J].abs();
}
}
if (VALUE < SUM.value || disnan(SUM.value)) VALUE = SUM.value;
}
} else {
for (J = 1; J <= N; J++) {
if (UDIAG) {
SUM.value = ONE;
for (I = 2; I <= min(N + 1 - J, K + 1); I++) {
SUM.value += AB[I][J].abs();
}
} else {
SUM.value = ZERO;
for (I = 1; I <= min(N + 1 - J, K + 1); I++) {
SUM.value += AB[I][J].abs();
}
}
if (VALUE < SUM.value || disnan(SUM.value)) VALUE = SUM.value;
}
}
} else if (lsame(NORM, 'I')) {
// Find normI(A).
VALUE = ZERO;
if (lsame(UPLO, 'U')) {
if (lsame(DIAG, 'U')) {
for (I = 1; I <= N; I++) {
WORK[I] = ONE;
}
for (J = 1; J <= N; J++) {
L = K + 1 - J;
for (I = max(1, J - K); I <= J - 1; I++) {
WORK[I] += AB[L + I][J].abs();
}
}
} else {
for (I = 1; I <= N; I++) {
WORK[I] = ZERO;
}
for (J = 1; J <= N; J++) {
L = K + 1 - J;
for (I = max(1, J - K); I <= J; I++) {
WORK[I] += AB[L + I][J].abs();
}
}
}
} else {
if (lsame(DIAG, 'U')) {
for (I = 1; I <= N; I++) {
WORK[I] = ONE;
}
for (J = 1; J <= N; J++) {
L = 1 - J;
for (I = J + 1; I <= min(N, J + K); I++) {
WORK[I] += AB[L + I][J].abs();
}
}
} else {
for (I = 1; I <= N; I++) {
WORK[I] = ZERO;
}
for (J = 1; J <= N; J++) {
L = 1 - J;
for (I = J; I <= min(N, J + K); I++) {
WORK[I] += AB[L + I][J].abs();
}
}
}
}
for (I = 1; I <= N; I++) {
SUM.value = WORK[I];
if (VALUE < SUM.value || disnan(SUM.value)) VALUE = SUM.value;
}
} else if ((lsame(NORM, 'F')) || (lsame(NORM, 'E'))) {
// Find normF(A).
if (lsame(UPLO, 'U')) {
if (lsame(DIAG, 'U')) {
SCALE.value = ONE;
SUM.value = N.toDouble();
if (K > 0) {
for (J = 2; J <= N; J++) {
dlassq(min(J - 1, K), AB(max(K + 2 - J, 1), J).asArray(), 1, SCALE,
SUM);
}
}
} else {
SCALE.value = ZERO;
SUM.value = ONE;
for (J = 1; J <= N; J++) {
dlassq(
min(J, K + 1), AB(max(K + 2 - J, 1), J).asArray(), 1, SCALE, SUM);
}
}
} else {
if (lsame(DIAG, 'U')) {
SCALE.value = ONE;
SUM.value = N.toDouble();
if (K > 0) {
for (J = 1; J <= N - 1; J++) {
dlassq(min(N - J, K), AB(2, J).asArray(), 1, SCALE, SUM);
}
}
} else {
SCALE.value = ZERO;
SUM.value = ONE;
for (J = 1; J <= N; J++) {
dlassq(min(N - J + 1, K + 1), AB(1, J).asArray(), 1, SCALE, SUM);
}
}
}
VALUE = SCALE.value * sqrt(SUM.value);
}
return VALUE;
}