def srtmb_asl_basis(tac, b, r1):
tac[tac < 0] = 0.0
n_beta = b['beta'].size
ssq = np.zeros(n_beta)
if b['w'] is None:
b['w'] = 1
y = tac - r1 * b['input']
for i in range(0, n_beta):
theta = r1
theta = np.append(
theta,
np.dot(y, b['basis'][i, :]) /
np.dot(b['basis'][i, :],
b['basis'][i, :])) # w won't make a difference here
a = np.column_stack((b['input'], b['basis'][i, :]))
tacf = np.dot(a, theta)
res = (tac - tacf) * b['w'] # w works here
ssq[i] = np.sum(res**2)
i = np.argmin(ssq)
theta = r1
theta = np.append(
theta,
np.dot(y, b['basis'][i, :]) /
np.dot(b['basis'][i, :], b['basis'][i, :]))
a = np.column_stack((b['input'], b['basis'][i, :]))
tacf = np.dot(a, theta)
theta = np.append(theta, b['beta'][i])
r1, k2, bp = kp.srtm_theta2kp(theta)
kps = {'r1': r1, 'k2': k2, 'bp': bp, 'tacf': tacf}
return kps
def srtmb_basis(tac, b):
tac[tac < 0] = 0.0
n_beta = b['beta'].size
ssq = np.zeros(n_beta)
if b['w'] is None:
b['w'] = 1
for i in range(0, n_beta):
theta = np.dot(b['m_w'][i * 2:i * 2 + 2, :], b['w'] * tac)
a = np.column_stack((b['input'], b['basis'][i, :]))
tacf = np.dot(a, theta)
res = (tac - tacf) * b['w']
ssq[i] = np.sum(res**2)
i = np.argmin(ssq)
theta = np.dot(b['m_w'][i * 2:i * 2 + 2, :], b['w'] * tac)
a = np.column_stack((b['input'], b['basis'][i, :]))
tacf = np.dot(a, theta)
theta = np.append(theta, b['beta'][i])
r1, k2, bp = kp.srtm_theta2kp(theta)
kps = {'r1': r1, 'k2': k2, 'bp': bp, 'tacf': tacf}
return kps
def srtm_fun_k2p(inputf1_dt_k2p, theta_0, theta_2):
inputf1, dt, k2p = inputf1_dt_k2p
inputf1_dt = (inputf1, dt)
theta_1 = theta_0 * (k2p - theta_2)
theta = np.array([theta_0, theta_1, theta_2])
r1, k2, bp = kp.srtm_theta2kp(theta)
tac = srtm_fun(inputf1_dt, r1, k2, bp)
return tac
def srtm_k2p(tac, dt, inputf1, w, k2p):
inputf1_dt_k2p = inputf1, dt, k2p
inputf1_dt_k2p_w = inputf1, dt, k2p, w
if w is None:
w = 1
p, _ = curve_fit(srtm_fun_k2p_w, inputf1_dt_k2p_w, tac*w, p0=(1, 0.5), bounds=(0, [3, 10]))
theta_0 = p[0]
theta_2 = p[1]
theta_1 = theta_0 * (k2p - theta_2)
theta = np.array([theta_0, theta_1, theta_2])
r1, k2, bp = kp.srtm_theta2kp(theta)
tacf = srtm_fun_k2p(inputf1_dt_k2p, theta_0, theta_2)
kps = {'r1': r1, 'k2': k2, 'bp': bp, 'tacf': tacf}
return kps
def srtmb_k2p_basis(tac, b):
n_beta = b['beta'].size
ssq = np.zeros(n_beta)
if b['w'] is None:
b['w'] = 1
for i in range(0, n_beta):
r1 = np.sum(b['w'] * b['basis_k2p'][i] * tac) / np.sum(b['w'] * b['basis_k2p'][i] ** 2)
ssq[i] = np.sum(b['w'] * (tac - r1 * b['basis_k2p'][i]) ** 2)
i = np.argmin(ssq)
r1 = np.sum(b['w'] * b['basis_k2p'][i] * tac) / np.sum(b['w'] * b['basis_k2p'][i] ** 2)
tacf = r1 * b['basis_k2p'][i]
theta = r1
theta = np.append(theta, r1 * (b['k2p'] - b['beta'][i]))
theta = np.append(theta, b['beta'][i])
r1, k2, bp = kp.srtm_theta2kp(theta)
kps = {'r1': r1, 'k2': k2, 'bp': bp, 'tacf': tacf}
return kps