我正在学习Processing 4 编程应用程序以及它使用的Java。我已经创建了一个草图，现在想要添加一个我下载的库（名为 Jama）来求解线性方程组。根据处理帮助，我需要在草图文件夹中创建一个名为库的目录并将库放在那里，我就是这样做的。但是，当我尝试导入它（导入 Jama.*）时，应用程序抱怨找不到它。下载后，Jama 包包含每个类的 .java 和 .class 文件。我还需要做些什么才能使这个库可用吗？
对于贡献管理器（“导入库...”子菜单中的添加库...”）要与 Jama 库一起使用，理想情况下需要将其包装为处理库。
如果您只是想在测试草图中使用该库，则无需将 Jama 包装为处理库：
您应该能够测试导入库并运行草图（例如
import Jama.*;这里是 Jama 示例 作为处理草图：
import Jama.*;
import java.util.Date;
Matrix magic (int n) {
double[][] M = new double[n][n];
// Odd order
if ((n % 2) == 1) {
int a = (n+1)/2;
int b = (n+1);
for (int j = 0; j < n; j++) {
for (int i = 0; i < n; i++) {
M[i][j] = n*((i+j+a) % n) + ((i+2*j+b) % n) + 1;
}
}
// Doubly Even Order
} else if ((n % 4) == 0) {
for (int j = 0; j < n; j++) {
for (int i = 0; i < n; i++) {
if (((i+1)/2)%2 == ((j+1)/2)%2) {
M[i][j] = n*n-n*i-j;
} else {
M[i][j] = n*i+j+1;
}
}
}
// Singly Even Order
} else {
int p = n/2;
int k = (n-2)/4;
Matrix A = magic(p);
for (int j = 0; j < p; j++) {
for (int i = 0; i < p; i++) {
double aij = A.get(i,j);
M[i][j] = aij;
M[i][j+p] = aij + 2*p*p;
M[i+p][j] = aij + 3*p*p;
M[i+p][j+p] = aij + p*p;
}
}
for (int i = 0; i < p; i++) {
for (int j = 0; j < k; j++) {
double t = M[i][j]; M[i][j] = M[i+p][j]; M[i+p][j] = t;
}
for (int j = n-k+1; j < n; j++) {
double t = M[i][j]; M[i][j] = M[i+p][j]; M[i+p][j] = t;
}
}
double t = M[k][0]; M[k][0] = M[k+p][0]; M[k+p][0] = t;
t = M[k][k]; M[k][k] = M[k+p][k]; M[k+p][k] = t;
}
return new Matrix(M);
}
String fixedWidthDoubletoString (double x, int w, int d) {
java.text.DecimalFormat fmt = new java.text.DecimalFormat();
fmt.setMaximumFractionDigits(d);
fmt.setMinimumFractionDigits(d);
fmt.setGroupingUsed(false);
String s = fmt.format(x);
while (s.length() < w) {
s = " " + s;
}
return s;
}
String fixedWidthIntegertoString (int n, int w) {
String s = Integer.toString(n);
while (s.length() < w) {
s = " " + s;
}
return s;
}
/*
| Tests LU, QR, SVD and symmetric Eig decompositions.
|
| n = order of magic square.
| trace = diagonal sum, should be the magic sum, (n^3 + n)/2.
| max_eig = maximum eigenvalue of (A + A')/2, should equal trace.
| rank = linear algebraic rank,
| should equal n if n is odd, be less than n if n is even.
| cond = L_2 condition number, ratio of singular values.
| lu_res = test of LU factorization, norm1(L*U-A(p,:))/(n*eps).
| qr_res = test of QR factorization, norm1(Q*R-A)/(n*eps).
*/
void setup(){
print("\n Test of Matrix Class, using magic squares.\n");
println("Test");
print(" See MagicSquareExample.main() for an explanation.\n");
print("\n n trace max_eig rank cond lu_res qr_res\n\n");
Date start_time = new Date();
double eps = Math.pow(2.0,-52.0);
for (int n = 3; n <= 32; n++) {
print(fixedWidthIntegertoString(n,7));
Matrix M = magic(n);
int t = (int) M.trace();
print(fixedWidthIntegertoString(t,10));
EigenvalueDecomposition E =
new EigenvalueDecomposition(M.plus(M.transpose()).times(0.5));
double[] d = E.getRealEigenvalues();
print(fixedWidthDoubletoString(d[n-1],14,3));
int r = M.rank();
print(fixedWidthIntegertoString(r,7));
double c = M.cond();
print(c < 1/eps ? fixedWidthDoubletoString(c,12,3) :
" Inf");
LUDecomposition LU = new LUDecomposition(M);
Matrix L = LU.getL();
Matrix U = LU.getU();
int[] p = LU.getPivot();
Matrix R = L.times(U).minus(M.getMatrix(p,0,n-1));
double res = R.norm1()/(n*eps);
print(fixedWidthDoubletoString(res,12,3));
QRDecomposition QR = new QRDecomposition(M);
Matrix Q = QR.getQ();
R = QR.getR();
R = Q.times(R).minus(M);
res = R.norm1()/(n*eps);
print(fixedWidthDoubletoString(res,12,3));
print("\n");
}
Date stop_time = new Date();
double etime = (stop_time.getTime() - start_time.getTime())/1000.;
print("\nElapsed Time = " +
fixedWidthDoubletoString(etime,12,3) + " seconds\n");
print("Adios\n");
}
输出：
Test of Matrix Class, using magic squares.
Test
See MagicSquareExample.main() for an explanation.
n trace max_eig rank cond lu_res qr_res
3 15 15.000 3 4.330 0.000 11.333
4 34 34.000 3 Inf 0.000 13.500
5 65 65.000 5 5.462 0.000 14.400
6 111 111.000 5 Inf 5.333 16.000
7 175 175.000 7 7.111 2.286 37.714
8 260 260.000 3 Inf 0.000 59.000
9 369 369.000 9 9.102 7.111 53.333
10 505 505.000 7 Inf 3.200 159.200
11 671 671.000 11 11.102 2.909 215.273
12 870 870.000 3 Inf 0.000 185.333
13 1105 1105.000 13 13.060 4.923 313.846
14 1379 1379.000 9 Inf 4.571 540.571
15 1695 1695.000 15 15.062 4.267 242.133
16 2056 2056.000 3 Inf 0.000 488.500
17 2465 2465.000 17 17.042 7.529 267.294
18 2925 2925.000 11 Inf 7.111 520.889
19 3439 3439.000 19 19.048 16.842 387.368
20 4010 4010.000 3 Inf 14.400 584.800
21 4641 4641.000 21 21.035 6.095 1158.095
22 5335 5335.000 13 Inf 6.545 1132.364
23 6095 6095.000 23 23.037 11.130 1268.870
24 6924 6924.000 3 Inf 10.667 827.500
25 7825 7825.000 25 25.029 35.840 1190.400
26 8801 8801.000 15 Inf 4.923 1859.077
27 9855 9855.000 27 27.032 37.926 1365.333
28 10990 10990.000 3 Inf 34.286 1365.714
29 12209 12209.000 29 29.025 30.897 1647.448
30 13515 13515.000 17 Inf 8.533 2571.733
31 14911 14911.000 31 31.027 33.032 1426.581
32 16400 16400.000 3 Inf 0.000 1600.125
Elapsed Time = 0.046 seconds
Adios
如果您不想继续将 Jama-1.0.3.jar 文件复制到每个新草图中，您可以尝试以下操作：
Documents/Processing/libraries/Jama/libraryDocuments/Processing/libraries/Jama/library重新启动处理后，您应该能够从任何新草图中
import Jama.*;请注意，如果您切换计算机/想要协作工作，您需要共享
Jama/libraryDocuments/Processing/libraries