这段代码什么意思sample = (b * math.cos(2 * math.pi * a / b), b * math.sin(2 * math.pi * a / b))
时间: 2023-12-22 11:06:39 浏览: 32
这段代码用于生成一个二维平面上的坐标点,其横坐标为 b * cos(2πa/b),纵坐标为 b * sin(2πa/b)。其中 math 是 Python 中的数学模块,cos 和 sin 分别表示余弦函数和正弦函数,2π 表示圆周率的倍数,a 和 b 是两个变量。将 a 和 b 替换成具体的数值,可以得到对应的坐标点。这种生成坐标点的方式通常被用于生成数据集,或者在二维平面上进行可视化。
相关问题
Java代码实现 6. order butterworth filter with F(0) 20Hz.
下面是一个简单的 Java 代码实现,可以生成一个6阶的Butterworth滤波器,截止频率为20Hz。
```java
import org.apache.commons.math3.analysis.UnivariateFunction;
import org.apache.commons.math3.analysis.function.Sigmoid;
import org.apache.commons.math3.analysis.function.Sinc;
import org.apache.commons.math3.complex.Complex;
import org.apache.commons.math3.complex.ComplexUtils;
import org.apache.commons.math3.transform.FastFourierTransformer;
import org.apache.commons.math3.transform.TransformType;
import java.util.ArrayList;
public class ButterworthFilter {
private final int order;
private final double cutoff;
public ButterworthFilter(int order, double cutoff) {
this.order = order;
this.cutoff = cutoff;
}
public double[] apply(double[] input) {
// 计算采样频率
double sampleRate = 1.0 / input.length;
// 计算截止频率在频域中的位置
double normalizedCutoff = cutoff / (sampleRate / 2);
// 构建巴特沃斯滤波器的极点
ArrayList<Complex> poles = new ArrayList<>();
for (int i = 0; i < order; i++) {
double real = -Math.sin(Math.PI * (2 * i + 1) / (2 * order));
double imag = Math.cos(Math.PI * (2 * i + 1) / (2 * order));
poles.add(new Complex(real, imag));
}
// 构建巴特沃斯滤波器的传递函数
UnivariateFunction transferFunction = new UnivariateFunction() {
@Override
public double value(double frequency) {
Complex numerator = Complex.ONE;
Complex denominator = Complex.ONE;
for (Complex pole : poles) {
double real = pole.getReal();
double imag = pole.getImaginary();
Complex term = ComplexUtils.polarToCartesian(1, -2 * Math.PI * frequency * real, -2 * Math.PI * frequency * imag);
numerator = numerator.multiply(term);
denominator = denominator.multiply(new Complex(1, -2 * Math.PI * frequency * real, -2 * Math.PI * frequency * imag));
}
return numerator.divide(denominator).getReal();
}
};
// 计算滤波器的频率响应
int fftSize = input.length * 2;
double[] frequencyResponse = new double[fftSize];
for (int i = 0; i < fftSize; i++) {
double frequency = i / (double)fftSize * sampleRate;
frequencyResponse[i] = transferFunction.value(frequency);
}
// 将频率响应进行反变换,得到滤波器的时域响应
FastFourierTransformer transformer = new FastFourierTransformer();
double[] impulseResponse = transformer.transform(frequencyResponse, TransformType.INVERSE);
// 将时域响应进行归一化,并截取前一半,得到滤波器的实际响应
double[] filter = new double[input.length];
for (int i = 0; i < input.length; i++) {
filter[i] = impulseResponse[i] / input.length;
}
filter = java.util.Arrays.copyOfRange(filter, 0, input.length / 2);
// 将滤波器应用到输入信号上
double[] output = new double[input.length];
for (int i = 0; i < input.length; i++) {
double t = i * sampleRate;
double sum = 0;
for (int j = 0; j < filter.length; j++) {
double tau = (j - filter.length / 2) * sampleRate;
sum += filter[j] * new Sinc().value((t - tau) * normalizedCutoff);
}
output[i] = sum;
}
return output;
}
}
```
在这个实现中,使用了 Apache Commons Math 库来进行一些数学计算,比如傅里叶变换。这个实现中的巴特沃斯滤波器是基于极点的实现方法,通过计算滤波器的传递函数,然后进行反傅里叶变换,得到滤波器的时域响应,最后将滤波器应用到输入信号上,得到滤波后的输出信号。
pycharm能编译出的爱心代码
Sure, here's a sample code in Python that will draw a heart in Pycharm:
```python
import math
def drawHeart():
for i in range(0, 360):
angle = i * math.pi / 180
x = 16 * (math.sin(angle) ** 3)
y = 13 * math.cos(angle) - 5 * math.cos(2 * angle) - 2 * math.cos(3 * angle) - math.cos(4 * angle)
print(" ", "x" if y < 0 else " ", end="")
if i % 30 == 0:
print()
drawHeart()
```
Hope this helps!