def fft_and_extrapolate(f, k, dr, direction, n_pots_for_extrap=6):
""" uses pubfft.sinfti routine
computes sinfti(f, dr, direction)/k and extrapolates to 0
"""
f_c = f.copy()
f_k = pubfft.sinfti(f_c[1:], dr, direction) / k[1:]
# extrapolates to 0
r_for_extrp = [dr * (i + 1) for i in range(n_pots_for_extrap)]
return extrapolate_to_0(f_k, r_for_extrp, n_pots_for_extrap)
def compute_xvvr(self):
""" Return xvv(r) matrix """
r = np.array([i * self.dr for i in range(self.ngrid)])
k = self.get_k()
xvvr = [["" for i in range(self.nsites)] for j in range(self.nsites)]
for i in range(self.nsites):
for j in range(self.nsites):
xvvk_ij = self.xvv_data[:, i, j]
xvvr_ij = pubfft.sinfti(xvvk_ij * k, self.dr, -1) / r
# n_pots_for_interp = 6
# r_for_interp = r[1:n_pots_for_interp+1]
# xvvr_for_interp = xvvr_ij[:n_pots_for_interp]
# poly_coefs = np.polyfit(r_for_interp, xvvr_for_interp, 3)
# poly_f = np.poly1d(poly_coefs)
# xvvr[i][j] = [poly_f(0)]
xvvr[i][j] = xvvr_ij
return r, np.swapaxes(xvvr, 0, 2)
def compute_xvvr(self):
""" Return xvv(r) matrix """
r = np.array([i*self.dr for i in range(self.ngrid)])
k = self.get_k()
xvvr = [["" for i in range(self.nsites)] for j in range(self.nsites)]
for i in range(self.nsites):
for j in range(self.nsites):
xvvk_ij = self.xvv_data[:,i,j]
xvvr_ij = pubfft.sinfti(xvvk_ij*k, self.dr, -1)/r
# n_pots_for_interp = 6
# r_for_interp = r[1:n_pots_for_interp+1]
# xvvr_for_interp = xvvr_ij[:n_pots_for_interp]
# poly_coefs = np.polyfit(r_for_interp, xvvr_for_interp, 3)
# poly_f = np.poly1d(poly_coefs)
# xvvr[i][j] = [poly_f(0)]
xvvr[i][j] = xvvr_ij
return r, np.swapaxes(xvvr, 0, 2)
def compute_zr(self):
""" Return z(r) matrix """
r = np.array([i * self.dr for i in range(self.ngrid)])
k, zk = self.compute_zk()
print 'computed zk', zk.shape
zr = [["" for i in range(self.nsites)] for j in range(self.nsites)]
for i in range(self.nsites):
for j in range(self.nsites):
zk_ij = zk[1:, i, j]
zr_ij = pubfft.sinfti(zk_ij * k[1:], self.dr, -1) / r[1:]
#zr_ij = np.abs(fftpack.fft(zk_ij))
n_pots_for_interp = 6
r_for_interp = r[1:n_pots_for_interp + 1]
zr_for_interp = zr_ij[:n_pots_for_interp]
poly_coefs = np.polyfit(r_for_interp, zr_for_interp, 3)
poly_f = np.poly1d(poly_coefs)
zr[i][j] = [poly_f(0)]
zr[i][j].extend(zr_ij)
return r, np.swapaxes(zr, 0, 2)
def compute_zr(self):
""" Return z(r) matrix """
r = np.array([i*self.dr for i in range(self.ngrid)])
k, zk = self.compute_zk()
print 'computed zk',zk.shape
zr = [["" for i in range(self.nsites)] for j in range(self.nsites)]
for i in range(self.nsites):
for j in range(self.nsites):
zk_ij = zk[1:,i,j]
zr_ij = pubfft.sinfti(zk_ij*k[1:], self.dr, -1)/r[1:]
#zr_ij = np.abs(fftpack.fft(zk_ij))
n_pots_for_interp = 6
r_for_interp = r[1:n_pots_for_interp+1]
zr_for_interp = zr_ij[:n_pots_for_interp]
poly_coefs = np.polyfit(r_for_interp, zr_for_interp, 3)
poly_f = np.poly1d(poly_coefs)
zr[i][j] = [poly_f(0)]
zr[i][j].extend(zr_ij)
return r, np.swapaxes(zr, 0, 2)