def plot_nugrid_chern(chern, hlat, xyvec, nugrids, repi, outdir=None, name_exten='', ax=None, fontsize=8):
"""Plot a pcolormesh of the spatially-resolved chern calcs on ax and plot the lattice on top of this.
Parameters
----------
chern : HaldaneChern instance
hlat : haldaneLattice instance
xyvec :
nugrids :
nugsum :
repi :
outdir : str or None
name_exten
"""
leplt.plot_pcolormesh(xyvec[:, 0], xyvec[:, 1], nugrids[repi].T.ravel(), 100, ax=ax,
method='nearest', cmap='rwb0',
vmin=-1.0, vmax=1.0, xlabel='x', ylabel='y', cax_label=r'$\nu$', fontsize=fontsize)
netvis.movie_plot_2D(hlat.lattice.xy, hlat.lattice.BL, 0 * hlat.lattice.BL[:, 0],
None, None, ax=plt.gca(), axcb=None, bondcolor='k',
colorz=False, ptcolor=None, figsize='auto',
colormap='BlueBlackRed', bgcolor='#ffffff', axis_off=False, axis_equal=True,
lw=0.2)
kpfns.add_kitaev_regions_to_plot(chern=chern, ksize_ind=repi, offsetxy=np.array([15, 0]))
plt.title(r'$\nu$')
plt.ylabel(r'$y$')
plt.xlabel(r'$x$')
if outdir is not None:
plt.savefig(outdir + '_nugrid' + name_exten + '.png')
def plot_gradnusum_chern(chern, hlat, xyvec, nugsum, repi, outdir=None, name_exten='', ax=None, fontsize=8):
"""Plot the gradient of the computed chern number -- plots the sum of abs(del_i nu) where the sum is taken over
the two directions (x and y).
Parameters
----------
chern : HaldaneChern instance
hlat : HaldaneLattice instance
xyvec :
nugrids :
nugsum :
repi :
outdir : str or None
name_exten
"""
leplt.plot_pcolormesh(xyvec[:, 0], xyvec[:, 1], nugsum[repi].T.ravel(), 100, ax=ax,
method='nearest', cmap='viridis',
vmin=None, vmax=None, xlabel='x', ylabel='y', cax_label=r'$\sum_j |\nabla_j \nu|$',
fontsize=fontsize)
netvis.movie_plot_2D(hlat.lattice.xy, hlat.lattice.BL, 0 * hlat.lattice.BL[:, 0],
None, None, ax=plt.gca(), axcb=None, bondcolor='k',
colorz=False, ptcolor=None, figsize='auto',
colormap='BlueBlackRed', bgcolor='#ffffff', axis_off=False, axis_equal=True,
lw=0.2)
kpfns.add_kitaev_regions_to_plot(chern=chern, ksize_ind=repi, offsetxy=np.array([15, 0]))
plt.title(r'$|\sum_j \nabla_j \nu|$')
plt.ylabel(r'$y$')
plt.xlabel(r'$x$')
if outdir is None:
plt.show()
else:
plt.savefig(outdir + '_nugradsumabs' + name_exten + '.png')
def expo(args):
def filename_fn(args):
rs = 'N({}, {})'.format(args.radius, args.sigma)
return rs
def fpath(fname):
_fpath = os.path.join(args.output_dir, fname)
return _fpath
length = 5 * args.radius
linspace, data = SyntheticDataset.grid_data(args.num_points, length=length)
# loader = dataset[args.dataset](args)
# trainData = loader.train
# for batch_idx, samples in enumerate(trainData):
# data,labels = samples[DatasetType.InD]
plt.xlim(-1 * length, length)
plt.ylim(-1 * length, length)
for scale in tqdm([1, 2, 3, 4]):
sigma = scale * args.sigma
scale_args = deepcopy(args)
scale_args.sigma = sigma
fname = filename_fn(scale_args)
checkpoint_dir = os.path.join(args.work_dir, 'checkpoints')
saver = Saver(checkpoint_dir) # makes directory if already not present
payload = saver.load(hash_args(
scale_args)) #hash_args(scale_args) generates the hex string
def run_and_save(scale_args):
export = main(scale_args) #Model creation??
payload = export['model']
saver.save(hash_args(scale_args), payload)
return payload
export = payload or run_and_save(scale_args)
with torch.no_grad():
scores = inference(export, data)
np_x = data.cpu().numpy()
for key in scores:
score = scores[key].cpu().numpy()
plot_pcolormesh(np_x, linspace, score)
score_fname = '{}_{}'.format(fname, key)
plt.title(score_fname)
flush_plot(plt, fpath(score_fname) + '.png')
def plot_spectrum_with_dos(hlat,
ksys_fracM,
omegacM,
nuM,
ngrid,
Wfig=90,
Hfig=None,
x0frac=0.15,
y0frac=0.1,
wsfrac=0.4,
hs=None,
wsdosfrac=0.3,
vspace=8,
hspace=8,
tspace=10,
FSFS=8,
xlabel=None,
ylabel=None,
title=None):
"""Plot chern spectrum vs ksize (or other variable on x axis), with corresponding DOS plot aligned with y axis
(increasing in frequency).
Parameters
----------
hlat : haldane_lattice
Wfig : int or float
width of the figure in mm
Hfig : int or float or None
Height of the figure in mm
x0frac : fraction of Wfig to leave blank left of plot
y0frac : fraction of Wfig to leave blank below plot
wsfrac : fraction of Wfig to make width of subplot
hs : height of subplot in mm. If none, uses ws = wsfrac * Wfig
vspace : vertical space between subplots
hspace : horizontal space btwn subplots
tspace : space above top figure
fontsize : size of text labels, title
Returns
-------
fig : matplotlib.pyplot figure instance
ax : matplotlib.pyplot axis instance
"""
# Make figure
fig, ax = initialize_spectrum_with_dos_plot(Wfig=Wfig,
Hfig=Hfig,
x0frac=x0frac,
y0frac=y0frac,
wsfrac=wsfrac,
hs=hs,
wsdosfrac=wsdosfrac,
vspace=vspace,
hspace=hspace,
tspace=tspace,
fontsize=FSFS)
# ax[2].xaxis.set_major_locator( MaxNLocator(nbins = 3) ) #, prune = 'lower') )
# ax[3].xaxis.set_major_locator( MaxNLocator(nbins = 3) )
# Plot sideways DOS colored by PR: http://matplotlib.org/examples/pylab_examples/scatter_hist.html
print 'kpfns: adding ipr to axis...'
hlat.add_ipr_to_ax(ax[0],
ipr=None,
alpha=1.0,
inverse_PR=False,
norm=None,
nbins=75,
fontsize=FSFS,
cbar_ax=ax[2],
vmin=None,
vmax=None,
linewidth=0,
cax_label=r'$p$',
make_cbar=True,
climbars=True,
cbar_labelpad=3,
orientation='horizontal',
cbar_orientation='horizontal',
invert_xaxis=True,
ylabel=r'$D(\omega)$',
xlabel='Oscillation frequency $\omega$',
cbar_nticks=3,
cbar_tickfmt='%0.1f')
leplt.plot_pcolormesh(ksys_fracM,
omegacM,
nuM,
ngrid,
ax=ax[1],
cax=ax[3],
method='nearest',
cmap=cmaps.diverging_cmap(250, 10, l=30),
vmin=-1.0,
vmax=1.0,
title=title,
xlabel=xlabel,
ylabel=ylabel,
cax_label=r'$\nu$',
cbar_labelpad=3,
cbar_orientation='horizontal',
ticks=[-1, 0, 1],
fontsize=FSFS)
# plt.show()
# sys.exit()
# Add title
ax[0].annotate(title,
xy=(0.5, .95),
xycoords='figure fraction',
horizontalalignment='center',
verticalalignment='center')
# Match axes
ax[0].set_ylim(ax[1].get_ylim())
ax[0].xaxis.set_major_locator(MaxNLocator(nbins=2)) # , prune = 'upper') )
ax[1].yaxis.set_label_position("right")
ax[1].yaxis.set_ticks_position('both')
plt.setp(ax[1].get_yticklabels(), visible=False)
ax[2].xaxis.set_label_position("top")
ax[3].xaxis.set_label_position("top")
return fig, ax
def plot_chern_spectrum_on_axis(kcoll, ax, dos_ax, cbar_ipr_ax, cbar_nu_ax, fontsize=8, alpha=1.0,
ipr_vmin=None, ipr_vmax=None, cbar_labelpad=3, invert_xaxis=True,
ipr_cax_label='participation\nratio,' + r' $p$',
chern_cax_label='Chern\nnumber, ' + r'$\nu$'):
"""
Parameters
----------
kcoll : HaldaneCollection instance
The chern collection to add to the plot
ax : matplotlib axis instance
the axis on which to add the spectrum
dos_ax : matplotlib axis instance
the axis on which to add
alpha : float
opacity of the spectrum and DOS added to the plot
Returns
-------
ax, dos_ax
"""
dmyi = 0
for hlat_name in kcoll.cherns:
# Grab a pointer to the haldane_lattice
hlat = kcoll.cherns[hlat_name][0].haldane_lattice
dmyi += 1
if dmyi > 1:
raise RuntimeError('This function takes a HaldaneCollection which is allowed only ONE haldane_lattice-- ' +
'ie, a chern spectrum for a single haldaneLattice instance')
print 'Opening hlat_name = ', hlat_name
ngrid = len(kcoll.cherns[hlat_name][0].chern_finsize)
# Assume all ksize elements are the same size for now
ksys_frac = kcoll.cherns[hlat_name][0].chern_finsize[:, -2]*0.5
ksys_fracM = np.array([ksys_frac for i in range(len(kcoll.cherns[hlat_name]))])
# Build omegacV
omegacV = np.zeros(len(kcoll.cherns[hlat_name]))
nuM = np.zeros((len(kcoll.cherns[hlat_name]), len(ksys_frac)))
for ind in range(len(kcoll.cherns[hlat_name])):
print 'ind = ', ind
cp_ii = kcoll.cherns[hlat_name][ind].cp
omegacV[ind] = cp_ii['omegac']
nuM[ind, :] = kcoll.cherns[hlat_name][ind].chern_finsize[:, -1]
omegacM = omegacV.reshape(len(nuM), 1) * np.ones_like(nuM)
print 'omegacM = ', omegacM
print 'kpfns: adding ipr and chern spectrum to axes...'
print 'Adding chern spectrum to axis: ax = ', ax
leplt.plot_pcolormesh(ksys_fracM, omegacM, nuM, ngrid, ax=ax, cax=cbar_nu_ax, method='nearest',
cmap=cmaps.diverging_cmap(250, 10, l=30),
vmin=-1.0, vmax=1.0, title=None, xlabel=None, ylabel=None, cax_label=chern_cax_label,
cbar_labelpad=cbar_labelpad, cbar_orientation='horizontal', ticks=[-1, 0, 1],
fontsize=fontsize, alpha=alpha)
if dos_ax is not None and dos_ax != 'none':
print 'Adding ipr to DOS axis: dos_ax = ', dos_ax
hlat.add_ipr_to_ax(dos_ax, ipr=None, alpha=alpha, inverse_PR=False,
norm=None, nbins=75, fontsize=fontsize, cbar_ax=cbar_ipr_ax,
vmin=ipr_vmin, vmax=ipr_vmax, linewidth=0, cax_label=ipr_cax_label,
make_cbar=True, climbars=True,
cbar_labelpad=cbar_labelpad, orientation='horizontal', cbar_orientation='horizontal',
invert_xaxis=invert_xaxis, ylabel=None, xlabel=None,
cbar_nticks=2, cbar_tickfmt='%0.1f')
ax.set_ylim(dos_ax.get_ylim())
return ax, dos_ax, cbar_ipr_ax, cbar_nu_ax