def plot_p(p):
xlim = [-50, 50]
subp = [3, 1, 1]
plt.subplot(*subp)
subp[-1] += 1
oploti(p.g0_w[0, 0], label=r'$G_0(i\omega_n)$')
oploti(p.g_w[0, 0], label=r'$G(i\omega_n)$')
oploti(p.sigma_w[0, 0], label=r'$\Sigma(i\omega_n)$')
plt.legend(loc='best')
plt.xlim(xlim)
plt.subplot(*subp)
subp[-1] += 1
oplotr(p.G_tau_raw['up'], alpha=0.75)
oplotr(p.G_tau['up'])
plt.gca().legend().set_visible(False)
plt.subplot(*subp)
subp[-1] += 1
G_l = p.G_l.copy()
for b, g in G_l:
G_l[b].data[:] = np.abs(g.data)
oplotr(G_l['up'], 'o-')
plt.semilogy([], [])
plt.gca().legend().set_visible(False)
plt.tight_layout()
plt.savefig('figure_field_sc_gf.svg')
diff = np.max(np.abs(Delta_tau.data - Delta_tau_ref.data))
print 'Delta_tau diff =', diff
np.testing.assert_array_almost_equal(Delta_tau.data, Delta_tau_ref.data)
assert( diff < 1e-8 )
diff = np.max(np.abs(Delta_iw.data - Delta_iw_ref.data))
print 'Delta_iw diff =', diff
np.testing.assert_array_almost_equal(Delta_iw.data, Delta_iw_ref.data)
assert( diff < 1e-7 )
if False:
from pytriqs.plot.mpl_interface import oplot, oplotr, oploti, plt
plt.figure()
oplotr(Delta_tau - Delta_tau_ref)
plt.show()
plt.figure()
oplotr(Delta_tau)
oplotr(Delta_tau_ref)
plt.figure()
oplotr(Delta_iw)
oplotr(Delta_iw_ref)
plt.figure()
oploti(Delta_iw)
oploti(Delta_iw_ref)
plt.show()
nw=1,
nwf=p.n_iw / 2,
nwf_gf=p.n_iw,
)
a = analytic_hubbard_atom(**parm.dict())
a.G_iw.name = r'$G_{analytic}$'
plt.figure(figsize=(3.25 * 2, 3 * 2))
subp = [2, 2, 1]
plt.subplot(*subp)
subp[-1] += 1
oploti(p.G_iw)
oploti(a.G_iw)
plt.subplot(*subp)
subp[-1] += 1
diff = a.G_iw.copy()
diff << p.G_iw['up'] - a.G_iw
diff.name = r'$G_{ctint} - G_{analytic}$'
oplot(diff)
plt.subplot(*subp)
subp[-1] += 1
vmax = np.max(np.abs(p.chi_m.data.real))
opt = dict(vmax=vmax, vmin=-vmax, cmap='PuOr')
data = np.squeeze(p.chi_m.data.real)
plt.pcolormesh(data, **opt)
a['Delta_iw_ref'] = Delta_iw_ref
a['Delta_iw_fit'] = Delta_iw_fit
# -- Plot
from pytriqs.plot.mpl_interface import oplot, oplotr, oploti, plt
plt.figure(figsize=(10, 10))
ylim = [-4, 4]
plt.plot([w_min.imag]*2, ylim, 'sr-', lw=0.5)
plt.plot([w_max.imag]*2, ylim, 'sr-', lw=0.5)
for i1, i2 in itertools.product(range(2), repeat=2):
oplotr(Delta_iw[i1, i2], alpha=0.1)
oploti(Delta_iw[i1, i2], alpha=0.1)
oplotr(Delta_iw_ref[i1, i2], lw=4, alpha=0.25)
oploti(Delta_iw_ref[i1, i2], lw=4, alpha=0.25)
oplotr(Delta_iw_fit[i1, i2])
oploti(Delta_iw_fit[i1, i2])
ax = plt.gca()
ax.legend_ = None
plt.ylim([-1, 1])
plt.tight_layout()
plt.savefig(figure_filename)
plt.show(); exit()
print 'h_loc =\n', h_loc
print 'h_loc_ref =\n', h_loc_ref
Delta_tau_ref = S.Delta_tau['0']
Delta_iw_ref = Delta_iw.copy()
Delta_iw_ref << Fourier(Delta_tau_ref)
diff = h_loc - h_loc_ref
print 'h_loc diff =', diff
for ops, prefactor in diff:
print prefactor, ops
assert (np.abs(prefactor) < 1e-10)
diff = np.max(np.abs(Delta_tau.data - Delta_tau_ref.data))
print 'Delta_tau diff =', diff
np.testing.assert_array_almost_equal(Delta_tau.data, Delta_tau_ref.data)
assert (diff < 1e-8)
diff = np.max(np.abs(Delta_iw.data - Delta_iw_ref.data))
print 'Delta_iw diff =', diff
np.testing.assert_array_almost_equal(Delta_iw.data, Delta_iw_ref.data)
assert (diff < 1e-7)
if False:
from pytriqs.plot.mpl_interface import oplot, oplotr, oploti, plt
oplotr(Delta_tau - Delta_tau_ref)
oploti(Delta_tau - Delta_tau_ref)
plt.show()
exit()
subp[-1] += 1
plt.plot(ps.iter, ps.dG_l, 's-')
plt.ylabel('$\max | \Delta G_l |$')
plt.xlabel('Iteration')
plt.semilogy([], [])
plt.subplot(*subp)
subp[-1] += 1
for b, g in p.G_l:
p.G_l[b].data[:] = np.abs(g.data)
oplotr(p.G_l['up'], 'o-', label=None)
plt.ylabel('$| G_l |$')
plt.semilogy([], [])
plt.subplot(*subp)
subp[-1] += 1
oplotr(p.G_tau_raw['up'], alpha=0.75, label='Binned')
oplotr(p.G_tau['up'], label='Legendre')
plt.legend(loc='best', fontsize=8)
plt.ylabel(r'$G(\tau)$')
plt.subplot(*subp)
subp[-1] += 1
oploti(p.sigma_w[0, 0], '.-', label=None)
plt.ylabel(r'$\Sigma(i\omega_n)$')
plt.xlim([-100, 100])
plt.tight_layout()
plt.savefig('figure_sc.svg')
plt.show()
