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')
def plot_field(out):
plt.figure(figsize=(3.25 * 2, 8))
for p in out.data:
subp = [2, 1, 1]
ax = plt.subplot(*subp)
subp[-1] += 1
oplotr(p.G_tau['up'], 'b', alpha=0.25)
oplotr(p.G_tau['dn'], 'g', alpha=0.25)
ax.legend().set_visible(False)
plt.subplot(*subp)
subp[-1] += 1
plt.title(r'$\chi \approx %2.2f$' % out.chi)
plt.plot(out.h_vec, out.m_vec, '-og', alpha=0.5)
plt.plot(out.h_vec, out.m_ref_vec, 'xb', alpha=0.5)
plt.plot(out.h_vec, -out.chi * out.h_vec, '-r', alpha=0.5)
plt.tight_layout()
plt.savefig('figure_static_field.pdf')
#assert( diff == Operator() )
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()
a['Delta_iw'] = Delta_iw
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()
filename = 'data_pyed_h_field_0.0000.h5'
print '--> Loading:', filename
with HDFArchive(filename, 'r') as s:
pyed = s['p']
plt.figure(figsize=(3.25 * 2, 8))
subp = [3, 1, 1]
plt.subplot(*subp)
subp[-1] += 1
#oplotr(O_tau_regr, '-', label=r'cthyb regr $-\langle n_\uparrow(\tau) n_\downarrow \rangle$ (should be bad)', alpha=1.0, lw=1.0, zorder=100)
oplotr(cthyb.O_tau,
'-',
label=r'cthyb $\langle n_\uparrow(\tau) n_\downarrow \rangle$',
alpha=0.5,
lw=0.5)
oplotr(pyed.O_tau,
label=r'pyed $\langle n_\uparrow(\tau) n_\downarrow \rangle$')
plt.plot(0, cthyb.exp_val, 'or', alpha=0.25, clip_on=False)
plt.plot(0, pyed.exp_val, 'xg', alpha=0.25, clip_on=False)
plt.subplot(*subp)
subp[-1] += 1
tau = np.array([float(t) for t in cthyb.O_tau.mesh])
tau_ref = np.array([float(t) for t in pyed.O_tau.mesh])
O_ref = pyed.O_tau.data.copy()
O_interp = np.interp(tau, tau_ref, O_ref)
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:
assert (np.abs(prefactor) < 1e-12)
#assert( diff == Operator() )
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)
oplotr(Delta_tau_ref)
plt.show()
exit()
# ----------------------------------------------------------------------
import itertools
import numpy as np
# ----------------------------------------------------------------------
import matplotlib.pyplot as plt
# ----------------------------------------------------------------------
from pytriqs.gf import Gf
from pytriqs.archive import HDFArchive
from pytriqs.plot.mpl_interface import oplotr
# ----------------------------------------------------------------------
if __name__ == '__main__':
with HDFArchive('data_ed.h5', 'r') as res:
oplotr(res['tot'], name='pyed')
with HDFArchive('spinless.ed.h5', 'r') as res:
oplotr(res['tot'], name='ed')
plt.savefig('figure_ed_vs_pyed.pdf')
plt.show()
plt.figure(figsize=(3.25 * 2, 5))
subp = [2, 2, 1]
plt.subplot(*subp)
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])