def plot_single_snapshot_results_qm_gaps(snapnum,
snapnums_results_d,
results_d,
name='frequency',
func_to_apply=lambda x: x,
ylabel=r'$\nu_{3}$ frequency (cm$^{-1}$)',
symbol='\omega'):
results_snap_d = get_single_snapshot_results(snapnum,
snapnums_results_d,
results_d)
fig, ax = plt.subplots()
gaps_0_1 = []
gaps_1_2 = []
gaps_2_3 = []
n_mm_ticks_0_1 = []
n_mm_ticks_1_2 = []
n_mm_ticks_2_3 = []
for n_mm in possible_keys:
try:
gap_0_1 = func_to_apply(results_snap_d[1][n_mm][0]) - func_to_apply(results_snap_d[0][n_mm][0])
gaps_0_1.append(gap_0_1)
n_mm_ticks_0_1.append(n_mm)
except:
pass
try:
gap_1_2 = func_to_apply(results_snap_d[2][n_mm][0]) - func_to_apply(results_snap_d[1][n_mm][0])
gaps_1_2.append(gap_1_2)
n_mm_ticks_1_2.append(n_mm)
except:
pass
try:
gap_2_3 = func_to_apply(results_snap_d[3][n_mm][0]) - func_to_apply(results_snap_d[2][n_mm][0])
gaps_2_3.append(gap_2_3)
n_mm_ticks_2_3.append(n_mm)
except:
pass
ax.plot(n_mm_ticks_0_1, gaps_0_1, marker='s', color='red',
label='$\Delta {symbol}_{{1-0\,\mathrm{{QM}}}}$'.format(**locals()))
ax.plot(n_mm_ticks_1_2, gaps_1_2, marker='p', color='green',
label='$\Delta {symbol}_{{2-1\,\mathrm{{QM}}}}$'.format(**locals()))
ax.plot(n_mm_ticks_2_3, gaps_2_3, marker='*', color='blue',
label='$\Delta {symbol}_{{3-2\,\mathrm{{QM}}}}$'.format(**locals()))
ax.set_xscale('symlog', basex=2)
ax.xaxis.set_major_formatter(mpl.ticker.ScalarFormatter())
ax.set_ylim(ax.get_ylim()[::-1])
y_formatter = mpl.ticker.ScalarFormatter(useOffset=False)
ax.yaxis.set_major_formatter(y_formatter)
ax.tick_params(direction='out')
ax.set_xlabel('# IL pairs treated as point charges')
ax.set_ylabel(r'difference in {}'.format(ylabel))
# ax.set_title('snapshot {} gaps'.format(snapnum))
ax.legend(loc='best', fancybox=True, framealpha=0.50)
filename = '{}_convergence_snap{}_gaps.pdf'.format(name, snapnum)
print('Saving {}'.format(filename))
fig.savefig(filename, bbox_inches='tight')
ax.set_xscale('linear')
rlim = -5
ax.set_xticks(possible_keys[:rlim + 1])
ax.set_xlim((possible_keys[0], possible_keys[rlim]))
filename = '{}_convergence_snap{}_{}_gaps.pdf'.format(name, snapnum, possible_keys[rlim])
print('Saving {}'.format(filename))
fig.savefig(filename, bbox_inches='tight')
plt.close(fig)
return
def plot_single_snapshot_results(snapnum,
snapnums_results_d,
results_d,
name='frequency',
func_to_apply=lambda x: x,
ylabel=r"$\nu_{3}$ frequency (cm$^{-1}$)",
inp_fig=None,
inp_ax=None,
do_manip_fig=True,
do_manip_ax=True):
results_snap_d = get_single_snapshot_results(snapnum, snapnums_results_d, results_d)
fig, ax = plt.subplots()
if inp_fig:
fig = inp_fig
if inp_ax:
ax = inp_ax
for n_qm in sorted(results_snap_d):
ticks = []
results = []
for n_mm in possible_keys:
if len(results_snap_d[n_qm][n_mm]) > 0:
if n_mm + n_qm >= 256:
ticks.append(256)
else:
ticks.append(n_mm + n_qm)
results.append(func_to_apply(results_snap_d[n_qm][n_mm][0]))
ax.plot(ticks,
results,
marker=markers[n_qm],
label=labels[n_qm],
color=colors[n_qm])
if do_manip_ax:
ax.set_xscale('symlog', basex=2)
ax.xaxis.set_major_formatter(mpl.ticker.ScalarFormatter())
y_formatter = mpl.ticker.ScalarFormatter(useOffset=False)
ax.yaxis.set_major_formatter(y_formatter)
ax.tick_params(direction='out')
ax.set_xlabel("total # of IL pairs included")
ax.set_ylabel(ylabel)
# ax.set_title("snapshot {}".format(snapnum))
ax.legend(loc='best', fancybox=True, framealpha=0.50)
if do_manip_fig:
filename = '{}_convergence_snap{}.pdf'.format(name, snapnum)
print('Saving {}'.format(filename))
fig.savefig(filename, bbox_inches='tight')
if do_manip_ax:
ax.set_xscale('linear')
rlim = -5
ax.set_xticks(possible_keys[:rlim + 1])
ax.set_xlim((possible_keys[0], possible_keys[rlim]))
if do_manip_fig:
filename = '{}_convergence_snap{}_{}.pdf'.format(name, snapnum, possible_keys[rlim])
print('Saving {}'.format(filename))
fig.savefig(filename, bbox_inches='tight')
plt.close(fig)
return