mirror of
https://gitlab.science.ru.nl/mthesis-edeboone/m-thesis-introduction.git
synced 2024-11-13 18:13:31 +01:00
Eric Teunis de Boone
bca152c9cd
Except that the initial guess seems to massively impact the fitted phase. If the initial_phase is submitted, it seems to fit quite fine
53 lines
1.3 KiB
Python
53 lines
1.3 KiB
Python
"""
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Various utilities
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"""
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import numpy as np
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rng = np.random.default_rng()
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def phasemod(phase, low=np.pi):
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"""
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Modulo phase such that it falls within the
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interval $[-low, 2\pi - low)$.
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"""
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return (phase + low) % (2*np.pi) - low
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# Alias phase_mod to phasemod
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phase_mod = phasemod
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def sine_fitfunc(t, amp=1, freq=1, phase=0, baseline=0, t_delay=0):
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"""Simple sine wave for fitting purposes"""
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return amp*np.cos( 2*np.pi*freq*(t-t_delay) + phase) + baseline
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def sin_delay(f, t, phase=0):
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return sine_fitfunc(t, amp=1, freq=f, phase=phase, baseline=1, t_delay=0)
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def sampled_time(sample_rate=1, start=0, end=1, offset=0):
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return offset + np.arange(start, end, 1/sample_rate)
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def normalise_sine_params(params):
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params[2] = phase_mod(params[2])
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return params
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def noisy_sine_sampling(time, init_params, noise_sigma=1, rng=rng):
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if init_params[2] is None:
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init_params[2] = phasemod(2*np.pi*rng.random())
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samples = sine_fitfunc(time, *init_params)
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noise = rng.normal(0, noise_sigma, size=len(samples))
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return samples, noise
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# Alias noisy_sine
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noisy_sine = noisy_sine_sampling
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def find_nearest(value, array, return_idx=True):
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array = np.asarray(array)
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idx = (np.abs(array - value)).argmin()
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if return_idx:
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return idx
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else:
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return array[idx]
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