def fcn_all_twostate_theta(x, p):
ans = {}
Zc1 = p["Zc1"]
Zc2 = p["Zc2"]
Zcg = p["Zcg"]
Mc1 = p["Mc1"]
Mc2 = p["Mc2"]
Zg1 = p["Zg1"]
Zg2 = p["Zg2"]
Mg1 = p["Mg1"]
Mg2 = p["Mg2"]
theta_1 = p["theta_1"]
theta_2 = p["theta_2"]
corr_cc_1 = gv.exp(-Mc1 * x["tc"]) + gv.exp(-Mc1 * (NT - x["tc"]))
corr_cc_2 = gv.exp(-Mc2 * x["tc"]) + gv.exp(-Mc2 * (NT - x["tc"]))
corr_gg_1 = gv.exp(-Mg1 * x["tc"]) + gv.exp(-Mg1 * (NT - x["tc"]))
corr_gg_2 = gv.exp(-Mg2 * x["tc"]) + gv.exp(-Mg2 * (NT - x["tc"]))
ans["CC"] = Zc1 * (gv.cos(theta_1)**2 * corr_cc_1 + gv.sin(theta_1)**2 *
corr_gg_1) + Zc2 * (gv.cos(theta_2)**2 * corr_cc_2 +
gv.sin(theta_2)**2 * corr_gg_2)
corr_cc_1 = gv.exp(-Mc1 * x["tg"]) + gv.exp(-Mc1 * (NT - x["tg"]))
corr_cc_2 = gv.exp(-Mc2 * x["tg"]) + gv.exp(-Mc2 * (NT - x["tg"]))
corr_gg_1 = gv.exp(-Mg1 * x["tg"]) + gv.exp(-Mg1 * (NT - x["tg"]))
corr_gg_2 = gv.exp(-Mg2 * x["tg"]) + gv.exp(-Mg2 * (NT - x["tg"]))
ans["GG"] = Zg1 * (gv.cos(theta_1)**2 * corr_gg_1 + gv.sin(theta_1)**2 *
corr_cc_1) + Zg2 * (gv.cos(theta_2)**2 * corr_gg_2 +
gv.sin(theta_2)**2 * corr_cc_2)
ans["GC"] = -(
np.sqrt(gv.abs(Zg1 * Zc1)) * gv.cos(theta_1) * gv.sin(theta_1) *
(gv.exp(-Mg1 * x["tgc"]) - gv.exp(-Mg1 * (NT - x["tgc"])) -
gv.exp(-Mc1 * x["tgc"]) + gv.exp(-Mc1 * (NT - x["tgc"]))) +
np.sqrt(gv.abs(Zg2 * Zc2)) * gv.cos(theta_2) * gv.sin(theta_2) *
(gv.exp(-Mg2 * x["tgc"]) - gv.exp(-Mg2 * (NT - x["tgc"])) -
gv.exp(-Mc2 * x["tgc"]) + gv.exp(-Mc2 * (NT - x["tgc"]))))
return ans
def deriv(t, y):
""" Calculate [d/d theta(t), d/dt d/dt theta(t)]. """
theta, dtheta_dt = y
return np.array([dtheta_dt, - g_l * gv.sin(theta)])
def deriv(self, t, y, data=None):
" Calculate [dtheta/dt, d2theta/dt2] from [theta, dtheta/dt]."
theta, dtheta_dt = y
return np.array([dtheta_dt, - self.g_l * gv.sin(theta)])
def deriv(t, y):
""" Calculate [d/d theta(t), d/dt d/dt theta(t)]. """
theta, dtheta_dt = y
return np.array([dtheta_dt, -g_l * gv.sin(theta)])
def deriv(self, t, y, data=None):
" Calculate [dtheta/dt, d2theta/dt2] from [theta, dtheta/dt]."
theta, dtheta_dt = y
return np.array([dtheta_dt, - self.g_l * gv.sin(theta)])