def calculate_gga(self, e_g, n_sg, dedn_sg, sigma_xg, dedsigma_xg):
GGA.calculate_gga(self, e_g, n_sg, dedn_sg, sigma_xg, dedsigma_xg)
eLDAc_g = self.gd.empty()
vLDAc_sg = self.gd.zeros(1)
if self.vdwcoef == 0.0:
return
if len(n_sg) == 1:
self.LDAc.calculate(eLDAc_g, n_sg, vLDAc_sg)
e = self.get_non_local_energy(n_sg[0], sigma_xg[0], eLDAc_g, vLDAc_sg[0], dedn_sg[0], dedsigma_xg[0])
else:
n_sg = n_sg.sum(0)
n_sg.shape = (1,) + n_sg.shape
self.LDAc.calculate(eLDAc_g, n_sg, vLDAc_sg)
v_g = np.zeros_like(e_g)
deda2nl_g = np.zeros_like(e_g)
a2_g = sigma_xg[0] + 2 * sigma_xg[1] + sigma_xg[2]
e = self.get_non_local_energy(n_sg[0], a2_g, eLDAc_g, vLDAc_sg[0], v_g, deda2nl_g)
dedsigma_xg[0] += self.vdwcoef * deda2nl_g
dedsigma_xg[1] += self.vdwcoef * 2 * deda2nl_g
dedsigma_xg[2] += self.vdwcoef * deda2nl_g
dedn_sg += self.vdwcoef * v_g
if self.gd.comm.rank == 0:
e_g[0, 0, 0] += self.vdwcoef * e / self.gd.dv
def calculate_gga(self, e_g, n_sg, dedn_sg, sigma_xg, dedsigma_xg):
GGA.calculate_gga(self, e_g, n_sg, dedn_sg, sigma_xg, dedsigma_xg)
eLDAc_g = self.gd.empty()
vLDAc_sg = self.gd.zeros(1)
if self.vdwcoef == 0.0:
return
if len(n_sg) == 1:
self.LDAc.calculate(eLDAc_g, n_sg, vLDAc_sg)
e = self.get_non_local_energy(n_sg[0], sigma_xg[0], eLDAc_g,
vLDAc_sg[0], dedn_sg[0],
dedsigma_xg[0])
else:
n_sg = n_sg.sum(0)
n_sg.shape = (1, ) + n_sg.shape
self.LDAc.calculate(eLDAc_g, n_sg, vLDAc_sg)
v_g = np.zeros_like(e_g)
deda2nl_g = np.zeros_like(e_g)
a2_g = sigma_xg[0] + 2 * sigma_xg[1] + sigma_xg[2]
e = self.get_non_local_energy(n_sg[0], a2_g, eLDAc_g, vLDAc_sg[0],
v_g, deda2nl_g)
dedsigma_xg[0] += self.vdwcoef * deda2nl_g
dedsigma_xg[1] += self.vdwcoef * 2 * deda2nl_g
dedsigma_xg[2] += self.vdwcoef * deda2nl_g
dedn_sg += self.vdwcoef * v_g
if self.gd.comm.rank == 0:
e_g[0, 0, 0] += self.vdwcoef * e / self.gd.dv
def calculate_gga(self, *args):
GGA.calculate_gga(self, *args)
RealSpaceVDWFunctional.calculate_gga(self, *args)
def calculate_gga(self, *args):
GGA.calculate_gga(self, *args)
FFTVDWFunctional.calculate_gga(self, *args)
