def plot_configuration_grid(snapshots: HoomdFrame,
categories: np.ndarray,
max_frames=3,
remove_styling=False) -> Figure:
factors = np.unique(categories).astype(str)
if len(factors) < 10:
colormap = palettes.Category10_10
else:
colormap = palettes.Category20_20
cluster_assignment = np.split(categories, len(snapshots))
grid = []
for snap, cluster, i in zip(snapshots, cluster_assignment, count()):
if i > max_frames:
break
fig = plot_frame(
snap,
order_list=cluster,
categorical_colour=True,
colormap=colormap,
factors=factors,
)
if remove_styling:
fig = style_snapshot(fig)
grid.append(fig)
return _plot_grid(grid)
def plot_clustering(algorithm, X, snapshots, fit=True):
if fit:
clusters = algorithm.fit_predict(X)
else:
clusters = algorithm.predict(X)
cluster_assignment = np.split(clusters, len(snapshots))
fig = plot_grid([
plot_frame(snap, order_list=cluster, categorical_colour=True)
for snap, cluster in zip(snapshots, cluster_assignment)
])
return fig
def plot_labelled_config(snapshot: HoomdFrame) -> Figure:
"""Plot an input configuration indicating the labelling scheme.
This plots the configuration with an overlay indicating the regions in which
particles are classified as liquid (blue) and the regions where they are classified
as crystal (red).
Args:
snapshot: The snapshot configuration to display
"""
x_len, y_len = snapshot.box[:2]
cell, liq, crys = cell_regions(x_len, y_len)
fig = plot_frame(snapshot)
# use the canvas backend which supports transparency and other effects.
fig.output_backend = "canvas"
# Plot the liquid region, being the cell boundary with a hole in the middle
fig.multi_polygons(
xs=[[[cell[0], liq[0]]]],
ys=[[[cell[1], liq[1]]]],
fill_alpha=0.3,
fill_color="blue",
line_color=None,
)
# Plot the crystal region being a central rectangle
fig.multi_polygons(
xs=[[[crys[0]]]],
ys=[[[crys[1]]]],
fill_alpha=0.3,
fill_color="red",
line_color=None,
)
return style_snapshot(fig)
def plot_snapshots(snapshots):
return plot_grid([plot_frame(snap) for snap in snapshots])
def plot_snapshots(snapshots: HoomdFrame) -> Figure:
"""Plot a collection of snapshots as a grid."""
return _plot_grid([style_snapshot(plot_frame(snap)) for snap in snapshots])