import numpy as np
from scipy.fft import fft, fftfreq


sample_rate = 200.0
duration = 1.0
sample_count = int(sample_rate * duration)
time = np.arange(sample_count) / sample_rate

signal = (
    1.2 * np.sin(2.0 * np.pi * 30.0 * time)
    + 0.4 * np.sin(2.0 * np.pi * 75.0 * time)
)

spectrum = fft(signal)
frequencies = fftfreq(sample_count, d=1.0 / sample_rate)

positive = frequencies >= 0
positive_frequencies = frequencies[positive]
amplitudes = (2.0 / sample_count) * np.abs(spectrum[positive])

peak_indexes = np.flatnonzero(amplitudes > 0.1)
detected_peaks = positive_frequencies[peak_indexes]
expected_peaks = np.array([30.0, 75.0])

print(f"sample_count: {sample_count}")
print(f"bin_spacing_hz: {sample_rate / sample_count:.1f}")
print("detected peaks:")
for index in peak_indexes:
    print(f"  {positive_frequencies[index]:5.1f} Hz  amplitude {amplitudes[index]:.3f}")
print(f"dominant_frequency_hz: {positive_frequencies[np.argmax(amplitudes)]:.1f}")
print(f"matches_expected_peaks: {np.allclose(detected_peaks, expected_peaks)}")