lks/reverse-goertzel
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more accurate state initialization

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This commit is contained in:
Lucas Schumacher 2023-11-15 15:36:46 -05:00
parent d1df8fdf97
commit e36773a9ac
1 changed files with 12 additions and 8 deletions
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reverse_goertzel.py
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@ -7,22 +7,25 @@ def goertzel_sinusoid(freq, duration, sample_rate, amplitude):
omega = (2.0 * math.pi * freq) / sample_rate omega = (2.0 * math.pi * freq) / sample_rate
coeff = 2.0 * math.cos(omega) coeff = 2.0 * math.cos(omega)
# Initialize state variables # Initialize state variables for cos wave
q1 = 1.0 # previous sample in sinusoid (1.0 for sample 1) # You can use 1.0 for q1 and q2 for a cos wave with slightly larger amplitude and a phase shift of 1/2 a sample
q2 = 1.0 # previous previous sample (approximately 1.0 for sample 1) # q1 previous sample in sinusoid
result = [] q1 = math.cos(omega * (n - 1)) # use math.sin(omega * (n-1)) for sin wave
# q2 previous previous sample
q2 = math.cos(omega * (n - 2)) # use math.sin(omega * (n-2)) for sin wave
result = np.zeros(n)
for i in range(n): for i in range(n):
sample = coeff * q1 - q2 sample = coeff * q1 - q2
q2 = q1 q2 = q1
q1 = sample q1 = sample
result.append(sample * amplitude) result[i] = sample * amplitude
return result return result
def sinusoid(n, cycles=1): def sinusoid(n, cycles=1, phase=0):
result = [] result = []
for i in range(1, n+1): for i in range(phase, n+phase):
sample = math.cos(2.0 * cycles * math.pi * (i/n)) sample = math.cos(2.0 * cycles * math.pi * (i/n))
result.append(sample) result.append(sample)
return result return result
@ -34,12 +37,13 @@ def main():
signal = goertzel_sinusoid(1, cycles, samp_per_cycle, 1) signal = goertzel_sinusoid(1, cycles, samp_per_cycle, 1)
reference = np.array(sinusoid(len, cycles)) reference = np.array(sinusoid(len, cycles))
error = reference - signal error = reference - signal
print("max amplitude:", signal.max())
print("max error:", error.max()) print("max error:", error.max())
x = np.array(range(0, len)) x = np.array(range(0, len))
plt.plot(x, signal) plt.plot(x, signal)
plt.plot(x, reference) plt.plot(x, reference)
plt.plot(x, error) plt.plot(x, error)
#plt.plot(x, error*100) #plt.plot(x, error*100000000000)
plt.show() plt.show()
if __name__ == "__main__": if __name__ == "__main__":