public void getModulus(float[] realIO) {
		int i, j, k, ir, j0 = 1, idx = FFT_N_LOG - 1;
		float cosv, sinv, tmpr, tmpi;
		for (i = 0; i != FFT_N; i++) {
			real[i] = realIO[bitReverse[i]];
			imag[i] = 0;
		}

		for (i = FFT_N_LOG; i != 0; i--) {
			for (j = 0; j != j0; j++) {
				cosv = costable[j << idx];
				sinv = sintable[j << idx];
				for (k = j; k < FFT_N; k += j0 << 1) {
					ir = k + j0;
					tmpr = cosv * real[ir] - sinv * imag[ir];
					tmpi = cosv * imag[ir] + sinv * real[ir];
					real[ir] = real[k] - tmpr;
					imag[ir] = imag[k] - tmpi;
					real[k] += tmpr;
					imag[k] += tmpi;
				}
			}
			j0 <<= 1;
			idx--;
		}

		j = FFT_N >> 1;
		/*
		 * 输出模的平方:
		 * for(i = 1; i <= j; i++)
		 * 	realIO[i-1] = real[i] * real[i] +  imag[i] * imag[i];
		 * 
		 * 如果FFT只用于频谱显示,可以"淘汰"幅值较小的而减少浮点乘法运算. MINY的值
		 * 和Spectrum.Y0,Spectrum.logY0对应.
		 */
		sinv = MINY;
		cosv = -MINY;
		for (i = j; i != 0; i--) {
			tmpr = real[i];
			tmpi = imag[i];
			if (tmpr > cosv && tmpr < sinv && tmpi > cosv && tmpi < sinv)
				realIO[i - 1] = 0;
			else
				realIO[i - 1] = tmpr * tmpr + tmpi * tmpi;
		}
	}