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Signed-off-by: David Rotermund <54365609+davrot@users.noreply.github.com>
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numpy/power_mean/README.md
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@ -94,3 +94,47 @@ plt.show()
```
![image2.png](image2.png)
## How to do it correctly
First calculate the power and then average:
```python
import numpy as np
import matplotlib.pyplot as plt
t: np.ndarray = np.linspace(0, 1.0, 10000)
f: float = 10
sampling_frequency: float = 1.0 / (t[1] - t[0])
sinus_a = np.sin(f * t * 2.0 * np.pi)
sinus_b = np.sin(f * t * 2.0 * np.pi + np.pi)
sinus_a_fft: np.ndarray = np.fft.rfft(sinus_a)
sinus_b_fft: np.ndarray = np.fft.rfft(sinus_b)
frequency_axis: np.ndarray = np.fft.rfftfreq(sinus_a.shape[0]) * sampling_frequency
y_power_a: np.ndarray = (1 / (sampling_frequency * sinus_a.shape[0])) * np.abs(
sinus_a_fft
) ** 2
y_power_a[1:-1] *= 2
y_power_b: np.ndarray = (1 / (sampling_frequency * sinus_b.shape[0])) * np.abs(
sinus_b_fft
) ** 2
y_power_b[1:-1] *= 2
if frequency_axis[-1] != (sampling_frequency / 2.0):
y_power_a[-1] *= 2
y_power_b[-1] *= 2
y_power = (y_power_a + y_power_b) / 2.0
plt.plot(frequency_axis, y_power, label="Power")
plt.xlabel("Frequency [Hz]")
plt.xlim(0, 50)
plt.show()
```
![image3.png](image3.png)