35 lines
1.1 KiB
Python
35 lines
1.1 KiB
Python
import numpy as np
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from IPython import embed
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import matplotlib.pyplot as plt
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from thunderfish import fakefish
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from modules.filters import bandpass_filter
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from modules.datahandling import instantaneous_frequency
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from modules.simulations import create_chirp
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# trying thunderfish fakefish chirp simulation ---------------------------------
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samplerate = 44100
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freq, ampl = fakefish.chirps(eodf=500, chirp_contrast=0.2)
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data = fakefish.wavefish_eods(
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fish="Alepto", frequency=freq, phase0=3, samplerate=samplerate
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)
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# filter signal with bandpass_filter
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data_filterd = bandpass_filter(data * ampl + 1, samplerate, 0.01, 1.99)
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embed()
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data_freq_time, data_freq = instantaneous_frequency(data, samplerate, 5)
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fig, ax = plt.subplots(4, 1, figsize=(20 / 2.54, 12 / 2.54), sharex=True)
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ax[0].plot(np.arange(len(data)) / samplerate, data * ampl)
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# ax[0].scatter(true_zero, np.zeros_like(true_zero), color='red')
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ax[1].plot(np.arange(len(data_filterd)) / samplerate, data_filterd)
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ax[2].plot(np.arange(len(freq)) / samplerate, freq)
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ax[3].plot(data_freq_time, data_freq)
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plt.show()
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embed()
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