我目前正在尝试在java中实现FFT算法并且遇到了一些麻烦!我已经很好地测试了算法的所有其他部分,它们似乎工作正常。
我遇到的麻烦是,在基本情况下,它返回一个复数数组,在基本情况下A[0]
已填充。在执行基本案例之后,尽管将它们分配给基本案例,但在发现为null的地方执行了 for 循环y0[0]
,对此非常困惑。这显示在该行中y1[0]
System.out.println
谁能告诉我我的方式的错误?
//This method implements the recursive FFT algorithm, it assumes the input length
//N is some power of two
private static Complex[] FFT(Complex[] A, int N) {
double real, imag;
Complex A0[] = new Complex[((int) Math.ceil(N/2))];
Complex A1[] = new Complex[((int) Math.ceil(N/2))];
Complex[] omega = new Complex[N];
Complex[] y = new Complex[N];
Complex[] y0 = new Complex[((int) Math.ceil(N/2))];
Complex[] y1 = new Complex[((int) Math.ceil(N/2))];
//base case
if (N == 1) {
return A;
}
else {
real = Math.cos((2*Math.PI)/N); if (real < 1E-10 && real > 0) real = 0;
imag = Math.sin((2*Math.PI)/N); if (imag < 1E-10 && imag > 0) imag = 0;
omega[N-1] = new Complex(real, imag);
omega[0] = new Complex(1, 0);
A0 = splitInput(A, 1);
A1 = splitInput(A, 0);
//recursive calls
y0 = FFT(A0, N/2);
y1 = FFT(A1, N/2);
for (int k = 0; k < ((N/2)-1); k++) {
System.out.print("k: " + k + ", y0: " + y0[k]); System.out.println(", y1: " + y1[k]);
y[k] = y0[k].plus(omega[k].times(y1[k]));
y[k+(N/2)] = y0[k].minus(omega[k].times(y1[k]));
omega[0] = omega[0].times(omega[N]);
}
return y;
}
}
这是我请求的 splitInput 方法的代码
//This method takes a double array as an argument and returns every even or odd
//element according to the second int argument being 1 or 0
private static Complex[] splitInput(Complex[] input, int even) {
Complex[] newArray = new Complex[(input.length/2)];
//Return all even elements of double array, including 0
if (even == 1) {
for (int i = 0; i < (input.length/2); i++) {
newArray[i] = new Complex(input[i*2].re, 0.0);
}
return newArray;
}
//Return all odd elements of double array
else {
for (int i = 0; i < (input.length/2); i++) {
newArray[i] = new Complex (input[(i*2) + 1].re, 0.0);
}
return newArray;
}
}
编辑:我已经根据你的建议更新了我的代码,仍然从行中得到一个空指针异常,y[k] = y0[k].plus(omega[k].times(y1[k]));
因为y0
&y1
仍然null
在基本情况之后 :( 任何进一步的想法?这是更新的算法
//This method implements the recursive FFT algorithm, it assumes the input length
//N is some power of two
private static Complex[] FFT(Complex[] A, int N) {
double real, imag;
Complex[] omega = new Complex[N];
Complex[] y = new Complex[N];
Complex[] A0;
Complex[] A1;
Complex[] y0;
Complex[] y1;
//base case
if (N == 1) {
return A;
}
else {
real = Math.cos((2*Math.PI)/N); if (real < 1E-10 && real > 0) real = 0;
imag = Math.sin((2*Math.PI)/N); if (imag < 1E-10 && imag > 0) imag = 0;;
omega[N-1] = new Complex(real, imag);
omega[0] = new Complex(1, 0);
A0 = splitInput(A, 1);
A1 = splitInput(A, 0);
//recursive calls
y0 = FFT(A0, N/2);
y1 = FFT(A1, N/2);
for (int k = 0; k < ((N/2)-1); k++) {
y[k] = y0[k].plus(omega[k].times(y1[k]));
y[k+(N/2)] = y0[k].minus(omega[k].times(y1[k]));
omega[0] = omega[0].times(omega[N-1]);
}
return y;
}
}