def plot_field(fig: plt.Figure, field: np.array, location: tuple, side: int):
n = np.sqrt(field.shape[0]).astype(int)
min_x, max_x = location[0] - side / 2, location[0] + side / 2
min_y, max_y = location[1] - side / 2, location[1] + side / 2
fig.gca().imshow(field.reshape(n, n),
extent=[min_x, max_x, max_y, min_y],
cmap=plt.get_cmap('Greens').reversed())
fig.gca().set_yticks([])
fig.gca().set_xticks([])
return fig
def plot_image_hierarchy(fig: plt.Figure, G: nx.Graph):
# Adapted from https://stackoverflow.com/questions/53967392/creating-a-graph-with-images-as-nodes
ax = fig.gca()
ax.set_aspect('equal', adjustable='box')
write_dot(G, 'test.dot')
pos = graphviz_layout(G, prog='dot', args='-Nsep="+1000,+1000";')
nx.draw_networkx_edges(G, pos, ax=ax)
trans = ax.transData.transform
trans2 = fig.transFigure.inverted().transform
piesize = 0.2 # this is the image size
p2 = piesize / 2.0
for n in G:
xx, yy = trans(pos[n]) # figure coordinates
xa, ya = trans2((xx, yy)) # axes coordinates
a = plt.axes([xa - p2, ya - p2, piesize, piesize])
a.set_aspect('equal')
a.imshow(plt.imread(G.node[n]['image']))
a.set_xticks([])
a.set_yticks([])
# a.set_title(n.name)
ax.axis('off')
def plot_learning_path(fig: plt.Figure, paths):
for history in paths:
# First point will be blue
sns.scatterplot(history[0:1, 0],
history[0:1, 1],
color='blue',
ax=fig.gca())
# Intermediate steps are red
sns.scatterplot(history[1:, 0],
history[1:, 1],
color='red',
ax=fig.gca())
# Last point will be black
sns.scatterplot(history[-1:, 0],
history[-1:, 1],
color='black',
ax=fig.gca())
return fig
def _fix_shap_force_figure(fig: plt.Figure) -> plt.Figure:
"""
Replaces the figure annotation in shap force plots with "absent" if value = 0.0 and
"present" if value = 1.0.
:param fig: a matplotlib.pyplot.Figure as produced by shap.force_plot.
:return: The same fig, modified as described.
"""
ax = fig.gca()
for c in ax.get_children():
if isinstance(c, plt.Text):
t = c.get_text()
if t.endswith(' = 1.0'):
c.set_text(t.replace(' = 1.0', ' present'))
elif t.endswith(' = 0.0'):
c.set_text(t.replace(' = 0.0', ' absent'))
else:
pass
return fig
def reset_figure(fig: pyplot.Figure, ax: pyplot.Axes) -> None:
"""清空并重置一个画布
"""
fig.gca().cla()
fig.gca().set_title('Wireless Sensor Networks')
fig.gca().set_xlabel('x')
fig.gca().set_ylabel('y')
fig.set_size_inches(8, 6)
ax.set_position((0.1, 0.11, 0.6, 0.8))
legend_elements = (
pyplot.Line2D(xdata=[],
ydata=[],
marker='.',
linewidth=0,
color='red',
label='source'),
pyplot.Line2D(xdata=[],
ydata=[],
marker='.',
linewidth=0,
color='green',
label='alive'),
pyplot.Line2D(xdata=[],
ydata=[],
marker='.',
linewidth=0,
color='orange',
label='received'),
pyplot.Line2D(xdata=[],
ydata=[],
marker='.',
linewidth=0,
color='yellow',
label='replied'),
pyplot.Line2D(xdata=[],
ydata=[],
marker='.',
linewidth=0,
color='blue',
label='sending'),
pyplot.Line2D(xdata=[],
ydata=[],
marker='.',
linewidth=0,
color='black',
label='dead'),
pyplot.Circle(xy=(0, 0),
radius=0,
alpha=0.4,
color='red',
label='range of signal\n(source node)'),
pyplot.Circle(xy=(0, 0),
radius=0,
alpha=0.4,
color='green',
label='range of signal\n(alive node)'),
pyplot.Circle(xy=(0, 0),
radius=0,
alpha=0.4,
color='orange',
label='range of signal\n(received node)'),
pyplot.Circle(xy=(0, 0),
radius=0,
alpha=0.4,
color='yellow',
label='range of signal\n(replied node)'),
pyplot.Circle(xy=(0, 0),
radius=0,
alpha=0.4,
color='blue',
label='range of signal\n(sending node)'),
)
ax.legend(handles=legend_elements,
loc='upper left',
bbox_to_anchor=(1.02, 1),
borderaxespad=0)
