def compute_partials(self, inputs, partials):
"""
Calculate and save derivatives. (i.e., Jacobian)
"""
nn = self.options['num_nodes']
Ja1, Ja2 = computepositionsphericaljacobian(nn, 3 * nn,
inputs['r_e2s_B'])
partials['azimuth', 'r_e2s_B'] = Ja1
partials['elevation', 'r_e2s_B'] = Ja2
def compute_partials(self, inputs, partials):
"""
Calculate and save derivatives. (i.e., Jacobian)
"""
n = self.n
Ja1, Ja2 = computepositionsphericaljacobian(n, 3 * n,
inputs['r_b2g_A'])
partials['azimuthGS', 'r_b2g_A'] = Ja1
partials['elevationGS', 'r_b2g_A'] = Ja2
def linearize(self, params, unknowns, resids):
""" Calculate and save derivatives. (i.e., Jacobian) """
self.Ja1, self.Ji1, self.Jj1, self.Ja2, self.Ji2, self.Jj2 = \
computepositionsphericaljacobian(self.n, 3*self.n, params['r_e2s_B'])
self.J1 = scipy.sparse.csc_matrix((self.Ja1, (self.Ji1, self.Jj1)),
shape=(self.n, 3*self.n))
self.J2 = scipy.sparse.csc_matrix((self.Ja2, (self.Ji2, self.Jj2)),
shape=(self.n, 3*self.n))
self.J1T = self.J1.transpose()
self.J2T = self.J2.transpose()
def linearize(self):
""" Calculate and save derivatives. (i.e., Jacobian) """
self.Ja1, self.Ji1, self.Jj1, self.Ja2, self.Ji2, self.Jj2 = \
computepositionsphericaljacobian(self.n, 3 * self.n, self.r_b2g_A)
self.J1 = scipy.sparse.csc_matrix((self.Ja1, (self.Ji1, self.Jj1)),
shape=(self.n, 3 * self.n))
self.J2 = scipy.sparse.csc_matrix((self.Ja2, (self.Ji2, self.Jj2)),
shape=(self.n, 3 * self.n))
self.J1T = self.J1.transpose()
self.J2T = self.J2.transpose()
def provideJ(self):
""" Calculate and save derivatives (i.e., Jacobian). """
self.Ja1, self.Ji1, self.Jj1, self.Ja2, self.Ji2, self.Jj2 = \
computepositionsphericaljacobian(self.n, 3 * self.n, self.r_b2g_A)
self.J1 = scipy.sparse.csc_matrix((self.Ja1, (self.Ji1, self.Jj1)),
shape=(self.n, 3 * self.n))
self.J2 = scipy.sparse.csc_matrix((self.Ja2, (self.Ji2, self.Jj2)),
shape=(self.n, 3 * self.n))
self.J1T = self.J1.transpose()
self.J2T = self.J2.transpose()
def jacobian(self, params, unknowns, resids):
""" Calculate and save derivatives. (i.e., Jacobian) """
self.Ja1, self.Ji1, self.Jj1, self.Ja2, self.Ji2, self.Jj2 = \
computepositionsphericaljacobian(self.n, 3 * self.n, params['r_b2g_A'])
self.J1 = scipy.sparse.csc_matrix((self.Ja1, (self.Ji1, self.Jj1)),
shape=(self.n, 3 * self.n))
self.J2 = scipy.sparse.csc_matrix((self.Ja2, (self.Ji2, self.Jj2)),
shape=(self.n, 3 * self.n))
self.J1T = self.J1.transpose()
self.J2T = self.J2.transpose()
def compute_partials(self, inputs, partials):
"""
Calculate and save derivatives. (i.e., Jacobian)
"""
self.Ja1, self.Ji1, self.Jj1, self.Ja2, self.Ji2, self.Jj2 = \
computepositionsphericaljacobian(self.n, 3*self.n, inputs['r_e2s_B'])
self.J1 = scipy.sparse.csc_matrix((self.Ja1, (self.Ji1, self.Jj1)),
shape=(self.n, 3*self.n))
self.J2 = scipy.sparse.csc_matrix((self.Ja2, (self.Ji2, self.Jj2)),
shape=(self.n, 3*self.n))
self.J1T = self.J1.transpose()
self.J2T = self.J2.transpose()
def compute_partials(self, inputs, partials):
"""
Calculate and save derivatives. (i.e., Jacobian)
"""
self.Ja1, self.Ji1, self.Jj1, self.Ja2, self.Ji2, self.Jj2 = \
computepositionsphericaljacobian(self.n, 3 * self.n, inputs['r_b2g_A'])
self.J1 = scipy.sparse.csc_matrix((self.Ja1, (self.Ji1, self.Jj1)),
shape=(self.n, 3 * self.n))
self.J2 = scipy.sparse.csc_matrix((self.Ja2, (self.Ji2, self.Jj2)),
shape=(self.n, 3 * self.n))
self.J1T = self.J1.transpose()
self.J2T = self.J2.transpose()
