def redistribute_forces(self, p, grad_com, grad_p):
R, R1, R2, R3 = aautils.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 = aautils.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 = aautils.rotMatDeriv(p, False)
return com + np.dot(R, np.transpose(self.atom_positions)).transpose()