def redistribute_forces(self, p, grad_com, grad_p): R, R1, R2, R3 = aatopology.rotMatDeriv(p, True) grad = np.dot(R1, np.transpose(self.atom_positions)).transpose()*grad_p[0] grad += np.dot(R2, np.transpose(self.atom_positions)).transpose()*grad_p[1] grad += np.dot(R3, np.transpose(self.atom_positions)).transpose()*grad_p[2] grad += grad_com grad = (self.atom_masses * grad.transpose()).transpose()/self.M return grad
def redistribute_forces(self, p, grad_com, grad_p): R, R1, R2, R3 = aatopology.rotMatDeriv(p, True) grad = np.dot(R1, np.transpose( self.atom_positions)).transpose() * grad_p[0] grad += np.dot(R2, np.transpose( self.atom_positions)).transpose() * grad_p[1] grad += np.dot(R3, np.transpose( self.atom_positions)).transpose() * grad_p[2] grad += grad_com grad = (self.atom_masses * grad.transpose()).transpose() / self.M return grad
def transform_grad(self, p, g): g_com = np.sum(g, axis=0) R, R1, R2, R3 = aatopology.rotMatDeriv(p, True) g_p = np.zeros_like(g_com) for ga, x in zip(g, self.atom_positions): g_p[0] += np.dot(ga, np.dot(R1, x)) g_p[1] += np.dot(ga, np.dot(R2, x)) g_p[2] += np.dot(ga, np.dot(R3, x)) # # g_p[0] = -np.sum( # np.dot(g, np.dot(R1, np.transpose(self.atom_positions)).transpose()) # ) # g_p[1] = np.sum( # np.dot(g, np.dot(R2, np.transpose(self.atom_positions)).transpose()) # ) # g_p[2] = np.sum( # np.dot(g, np.dot(R3, np.transpose(self.atom_positions)).transpose()) # ) return g_com, g_p
def to_atomistic(self, com, p): R, R1, R2, R3 = aatopology.rotMatDeriv(p, False) return com + np.dot(R, np.transpose(self.atom_positions)).transpose()