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- import numpy as np
- def prepare_data(freq, re, im):
- """the function takes raw data and gives vectors of eq (8)"""
- fl = freq[re.index(max(re))]
- # fl is the frequency of loaded resonance
- f0 = fl
- # f0 is the frequency of unloaded resonance
- e1, e2, e3, gamma, p = [], [], [], [], []
- for i in range(0, len(freq)):
- # filling vectors
- t = 2*(freq[i] - fl)/f0
- g = re[i] + im[i] * j
- e1.append(t)
- e2.append(1)
- e3.append(-t*g)
- gamma.append(g)
- p.append(1/(1 + t**2*(1 + re[i]**2 + im[i]**2)))
- data = np.array([e1, e2, e3, gamma, p], dtype=complex)
- return data
- def scalar_product ():
- pass
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