def test_plot_multi_segments(self, mocker, band_segments, kwargs,
expected_labels):
suptitle = mocker.patch.object(matplotlib.figure.Figure, 'suptitle')
fig = plot_1d(band_segments, **kwargs)
legend = fig.axes[0].get_legend()
if expected_labels is None:
assert legend == None
else:
for text, label in zip(legend.get_texts(), expected_labels):
assert text.get_text() == label
# Ensure legend only on first subplot
for ax in fig.axes[1:]:
assert ax.get_legend() == None
if 'x_label' in kwargs:
assert fig.axes[-1].get_xlabel() == kwargs['x_label']
if 'y_label' in kwargs:
assert fig.axes[-1].get_ylabel() == kwargs['y_label']
if 'title' in kwargs:
suptitle.assert_called_once_with(kwargs['title'])
for ax in fig.axes[:-1]:
if 'y_min' in kwargs:
assert ax.get_ylim()[0] == pytest.approx(kwargs.get('y_min'))
if 'y_max' in kwargs:
assert ax.get_ylim()[0] == pytest.approx(kwargs.get('y_max'))
def test_plot_single(self, mocker, spectrum, labels, kwargs):
core = self.mock_core(mocker)
fig = plot_1d(spectrum, labels=labels, **kwargs)
# Check args were as expected
assert core.call_args[0][0] == spectrum
assert core.call_args[0][1] in fig.axes
assert core.call_args[0][2] == labels
assert core.call_args[1] == kwargs
plt.close(fig)
def main(params: List[str] = None):
args = get_args(get_parser(), params)
data = load_data_from_file(args.filename)
if isinstance(data, euphonic.ForceConstants):
frequencies_only = not args.reorder # Need eigenvectors to reorder
print("Force Constants data was loaded. Getting band path...")
q_distance = _get_q_distance(args.length_unit, args.q_spacing)
(modes, x_tick_labels, split_args) = _bands_from_force_constants(
data,
q_distance=q_distance,
frequencies_only=frequencies_only,
**_calc_modes_kwargs(args))
elif isinstance(data, euphonic.QpointPhononModes):
print("Phonon band data was loaded.")
modes = data
split_args = {'btol': args.btol}
x_tick_labels = None
modes.frequencies_unit = args.energy_unit
print("Mapping modes to 1D band-structure")
if args.reorder:
modes.reorder_frequencies()
spectrum = modes.get_dispersion()
if args.y_label is None:
y_label = f"Energy / {spectrum.y_data.units:~P}"
else:
y_label = args.y_label
if args.x_label is None:
x_label = ""
else:
x_label = args.x_label
if x_tick_labels:
spectrum.x_tick_labels = x_tick_labels
spectra = spectrum.split(**split_args)
_ = plot_1d(spectra,
title=args.title,
x_label=x_label,
y_label=y_label,
y_min=args.e_min,
y_max=args.e_max,
lw=1.0)
matplotlib_save_or_show(save_filename=args.save_to)
def main():
args = get_parser().parse_args()
filename = args.file
temperature = args.temperature * ureg['K']
summary_name = os.path.basename(filename)
path = os.path.dirname(filename)
force_constants = ForceConstants.from_phonopy(path=path,
summary_name=summary_name)
dos_collection = {}
for npts in args.npts:
if args.neutron:
dos = sample_sphere_structure_factor(force_constants,
args.q,
sampling=args.sampling,
temperature=temperature,
npts=npts,
jitter=args.jitter)
else:
dos = sample_sphere_dos(force_constants,
args.q,
sampling=args.sampling,
npts=npts,
jitter=args.jitter)
broad_dos = dos.broaden(1 * ureg('meV'), shape='lorentz')
dos_collection.update({npts: broad_dos})
label_list, dos_list = map(list, zip(*dos_collection.items()))
fig = plot_1d(dos_list, y_min=0, labels=label_list, title=summary_name)
plt.show()
def main(params: List[str] = None):
parser = get_parser()
args = get_args(parser, params)
data = load_data_from_file(args.filename)
mode_widths = None
if isinstance(data, euphonic.ForceConstants):
recip_length_unit = euphonic.ureg(f'1 / {args.length_unit}')
grid_spec = _grid_spec_from_args(data.crystal,
grid=args.grid,
grid_spacing=(args.grid_spacing *
recip_length_unit))
print("Force Constants data was loaded. Calculating phonon modes "
"on {} q-point grid...".format(' x '.join(
[str(x) for x in grid_spec])))
if args.adaptive:
if args.shape != 'gauss':
raise ValueError('Currently only Gaussian shape is supported '
'with adaptive broadening')
cmkwargs = _calc_modes_kwargs(args)
cmkwargs['return_mode_widths'] = True
modes, mode_widths = data.calculate_qpoint_frequencies(
mp_grid(grid_spec), **cmkwargs)
if args.energy_broadening:
mode_widths *= args.energy_broadening
else:
modes = data.calculate_qpoint_frequencies(
mp_grid(grid_spec), **_calc_modes_kwargs(args))
elif isinstance(data, euphonic.QpointPhononModes):
print("Phonon band data was loaded.")
modes = data
modes.frequencies_unit = args.energy_unit
ebins, energy_unit = _get_energy_bins_and_units(args.energy_unit,
modes,
args.ebins,
emin=args.e_min,
emax=args.e_max)
dos = modes.calculate_dos(ebins, mode_widths=mode_widths)
if args.energy_broadening and not args.adaptive:
dos = dos.broaden(args.energy_broadening * energy_unit,
shape=args.shape)
if args.x_label is None:
x_label = f"Energy / {dos.x_data.units:~P}"
else:
x_label = args.x_label
if args.y_label is None:
y_label = ""
else:
y_label = args.y_label
fig = plot_1d(dos,
title=args.title,
x_label=x_label,
y_label=y_label,
y_min=0,
lw=1.0)
matplotlib_save_or_show(save_filename=args.save_to)
def test_plot_with_incorrect_labels_raises_valueerror(self, band_segments):
with pytest.raises(ValueError):
fig = plot_1d(band_segments, labels=['Band A', 'Band B'])
def test_plot_badunits(self, spec1_units, band_segments):
spec1, spec2 = band_segments
spec1.x_data_unit, spec1.y_data_unit = spec1_units
spec2.x_data_unit, spec2.y_data_unit = ('angstrom^-1', 'meV')
with pytest.raises(ValueError):
plot_1d([spec1, spec2])