30 lines
770 B
Python
30 lines
770 B
Python
import math
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import numpy as np
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from scipy.optimize import fsolve
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def parallel2gap(K, phi_in_degree, undudict):
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phi = math.radians(phi_in_degree)
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gLH = K2gap(K, undudict['K-value_LH'])
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if phi >= 0.0:
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gLV = K2gap(K, undudict['K-value_LV+'])
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gC = K2gap(K, undudict['K-value_C+'])
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dgLV = gLV - gLH
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dgC = gC - gLH - dgLV/2
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else:
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gLV = K2gap(K, undudict['K-value_LV-'])
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gC = K2gap(K, undudict['K-value_C-'])
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dgLV = gLV - gLH
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dgC = gC - gLH - dgLV/2
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return gLH + dgLV * np.sin(0.5 * phi)**2 + dgC * np.sin(phi)**2
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def K2gap(Kval, fitparam):
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g2K_func = np.poly1d(fitparam[::-1])
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tau_init = 1.0
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k_log = float(np.log(Kval))
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return float(fsolve(k_log - g2K_func, tau_init))
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