def plot(obj, *args, **kwargs):
if isinstance(obj, TimeSeries):
is_time_series = True
else:
is_time_series = False
if not is_time_series and isinstance(obj, OnlineFunction.Type()):
is_truth_solution = False
elif is_time_series and isinstance(obj[0], OnlineFunction.Type()):
assert all(isinstance(obj_, OnlineFunction.Type()) for obj_ in obj)
is_truth_solution = False
else:
is_truth_solution = True
if is_time_series:
if "every" in kwargs:
obj = obj[::kwargs["every"]]
del kwargs["every"]
if "interval" in kwargs:
anim_interval = kwargs["interval"]
del kwargs["interval"]
else:
anim_interval = None
if not is_truth_solution:
assert "reduced_problem" in kwargs, (
"Please use this method as plot(reduced_solution, reduced_problem=my_reduced_problem)"
+ " when plotting a reduced solution")
if not is_time_series:
N = obj.N
else:
N = obj[0].N
assert all(obj_.N == N for obj_ in obj)
reduced_problem = kwargs["reduced_problem"]
del kwargs["reduced_problem"]
basis_functions = reduced_problem.basis_functions[:N]
truth_problem = reduced_problem.truth_problem
if not is_time_series:
obj = basis_functions * obj
else:
obj = [basis_functions * obj_ for obj_ in obj]
elif "truth_problem" in kwargs:
truth_problem = kwargs["truth_problem"]
del kwargs["truth_problem"]
else:
truth_problem = None
if "component" in kwargs:
component = kwargs["component"]
del kwargs["component"]
if not is_time_series:
obj = obj.sub(component)
else:
obj = [obj_.sub(component) for obj_ in obj]
if truth_problem is not None and hasattr(truth_problem, "mesh_motion"):
truth_problem.mesh_motion.move_mesh()
if not is_time_series:
output = original_plot(obj, *args, **kwargs)
else:
def animate(i):
return original_plot(obj[i], *args, **kwargs).collections
fig = plt.figure()
output = matplotlib.animation.FuncAnimation(
fig, animate, frames=len(obj), interval=anim_interval, repeat=False)
try:
from IPython.display import HTML
except ImportError:
pass
else:
output = HTML(output.to_html5_video())
plt.close()
if truth_problem is not None and hasattr(truth_problem, "mesh_motion"):
truth_problem.mesh_motion.reset_reference()
return output
def animate_planar_quad(t,
x,
y,
θ,
title_string=None,
display_in_notebook=False):
"""Animate the planar quadrotor system from given position data.
All arguments are assumed to be 1-D NumPy arrays, where `x`, `y`, and `θ`
are the degrees of freedom of the planar quadrotor over time `t`.
Example usage:
import matplotlib.pyplot as plt
from animations import animate_planar_quad
fig, ani = animate_planar_quad(t, x, θ)
ani.save('planar_quad.mp4', writer='ffmpeg')
plt.show()
"""
# Geometry
rod_width = 2.
rod_height = 0.15
axle_height = 0.2
axle_width = 0.05
prop_width = 0.5 * rod_width
prop_height = 1.5 * rod_height
hub_width = 0.3 * rod_width
hub_height = 2.5 * rod_height
# Figure and axis
fig, ax = plt.subplots(dpi=100)
x_min, x_max = np.min(x), np.max(x)
x_pad = (rod_width + prop_width) / 2 + 0.1 * (x_max - x_min)
y_min, y_max = np.min(y), np.max(y)
y_pad = (rod_width + prop_width) / 2 + 0.1 * (y_max - y_min)
ax.set_xlim([x_min - x_pad, x_max + x_pad])
ax.set_ylim([y_min - y_pad, y_max + y_pad])
ax.set_aspect(1.)
if title_string is not None:
plt.title(title_string)
# Artists
rod = mpatches.Rectangle((-rod_width / 2, -rod_height / 2),
rod_width,
rod_height,
facecolor='tab:blue',
edgecolor='k')
hub = mpatches.FancyBboxPatch((-hub_width / 2, -hub_height / 2),
hub_width,
hub_height,
facecolor='tab:blue',
edgecolor='k',
boxstyle='Round,pad=0.,rounding_size=0.05')
axle_left = mpatches.Rectangle((-rod_width / 2, rod_height / 2),
axle_width,
axle_height,
facecolor='tab:blue',
edgecolor='k')
axle_right = mpatches.Rectangle(
(rod_width / 2 - axle_width, rod_height / 2),
axle_width,
axle_height,
facecolor='tab:blue',
edgecolor='k')
prop_left = mpatches.Ellipse(
((axle_width - rod_width) / 2, rod_height / 2 + axle_height),
prop_width,
prop_height,
facecolor='tab:gray',
edgecolor='k',
alpha=0.7)
prop_right = mpatches.Ellipse(
((rod_width - axle_width) / 2, rod_height / 2 + axle_height),
prop_width,
prop_height,
facecolor='tab:gray',
edgecolor='k',
alpha=0.7)
patches = (rod, hub, axle_left, axle_right, prop_left, prop_right)
for patch in patches:
ax.add_patch(patch)
trace = ax.plot([], [], '--', linewidth=2, color='tab:orange')[0]
timestamp = ax.text(0.1, 0.9, '', transform=ax.transAxes)
def animate(k, t, x, y, θ):
transform = mtransforms.Affine2D().rotate_around(0., 0., θ[k])
transform += mtransforms.Affine2D().translate(x[k], y[k])
transform += ax.transData
for patch in patches:
patch.set_transform(transform)
trace.set_data(x[:k + 1], y[:k + 1])
timestamp.set_text('t = {:.1f} s'.format(t[k]))
artists = patches + (trace, timestamp)
return artists
dt = t[1] - t[0]
step = max(int(np.floor((1 / 30) / dt)),
1) # max out at 30Hz for faster rendering
ani = animation.FuncAnimation(fig,
animate,
t[::step].size,
fargs=(t[::step], x[::step], y[::step],
θ[::step]),
interval=step * dt * 1000,
blit=True)
if display_in_notebook:
try:
get_ipython()
from IPython.display import HTML
ani = HTML(ani.to_html5_video())
except (NameError, ImportError):
raise RuntimeError(
"`display_in_notebook = True` requires this code to be run in jupyter/colab."
)
return fig, ani
