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()