def get_norms(surf, timestep_limit):
# create a 2D bezier curve
curve = BSpline.Curve()
curve.degree = 3
ctrl_points = [[np.random.uniform(0, 0.2), np.random.uniform(0, 0.2)],
[np.random.uniform(0, 0.5), np.random.uniform(0, 0.5)],
[np.random.uniform(0.25, 0.75), np.random.uniform(0.25, 0.75)],
[np.random.uniform(0.5, 0.75), np.random.uniform(0.5, 0.75)],
[np.random.uniform(0.8, 1), np.random.uniform(0.8, 1.0)]]
curve.set_ctrlpts(ctrl_points)
curve.knotvector = utilities.generate_knot_vector(curve.degree, len(curve.ctrlpts))
curve.sample_size = timestep_limit
curve.evaluate()
points_c = curve.evalpts
norms = normal(surf, points_c)
angles = [] # pitch, yaw
traj = [] # x,y,z
for i in range(len(norms)):
nu = np.array(norms[i][1])
yaw = 180.0*np.arctan2(np.abs(nu[1]), np.abs(nu[0]))/np.pi
ca = np.linalg.norm(nu[0:2])
pitch = 180.0*np.arctan2(nu[2], ca)/np.pi
angles.append([pitch, yaw])
point = np.array(norms[i][0])
traj.append(np.array([point[0], point[1], point[2], pitch, yaw]))
return traj, norms, curve
def normal_array(self, us, vs):
if geomdl is not None:
uv_coords = list(zip(list(us), list(vs)))
spline_normals = np.array(
operations.normal(self.surface, uv_coords))[:, 1, :]
return spline_normals
surf.knotvector_v = utilities.generate_knot_vector(surf.degree_v, 6)
# Set evaluation delta
surf.delta = 0.05
# Evaluate surface
surf.evaluate()
# Evaluate surface tangent and normal vectors
uv_vals = [[0.1, 0.1], [0.65, 0.25], [0.9, 0.7], [0.2, 0.9]]
surftans = [[] for _ in range(len(uv_vals))]
surfnorms = [[] for _ in range(len(uv_vals))]
for idx, uv in enumerate(uv_vals):
surftans[idx] = operations.tangent(surf, uv, normalize=True)
surfnorms[idx] = operations.normal(surf, uv, normalize=True)
# Prepare points for plotting
surfpts = np.array(surf.evalpts)
tangent_vectors = np.array(surftans)
normal_vectors = np.array(surfnorms)
# Start plotting of the surface and the control points grid
fig = plt.figure(figsize=(10.67, 8), dpi=96)
ax = Axes3D(fig)
# Plot surface points
ax.plot_trisurf(surfpts[:, 0],
surfpts[:, 1],
surfpts[:, 2],
color='xkcd:gold',
# Set degrees
surf.degree_u = 3
surf.degree_v = 3
# Set control points
surf.set_ctrlpts(
*exchange.import_txt("ex_surface02.cpt", two_dimensional=True))
# Set knot vectors
surf.knotvector_u = utilities.generate_knot_vector(surf.degree_u, 6)
surf.knotvector_v = utilities.generate_knot_vector(surf.degree_v, 6)
# Set evaluation delta
surf.delta = 0.025
# Evaluate surface
surf.evaluate()
# Plot the control point grid and the evaluated surface
vis_comp = VisPlotly.VisSurface()
surf.vis = vis_comp
surf.render()
# Evaluate surface tangent and normal at the given u and v
uv = [0.2, 0.9]
surf_tangent = operations.tangent(surf, uv)
surf_normal = operations.normal(surf, uv)
# Good to have something here to put a breakpoint
pass
curve.evaluate()
#
# Multiple vector evaluation after v3.0.7
#
# List of parametric coordinates to be evaluated
u_list = (0.0175, 0.075, 0.375, 0.535, 0.65, 0.85, 0.975)
# Evaluate tangents, normals and binormals, respectively
curvetans = [[] for _ in range(len(u_list))]
curvenorms = [[] for _ in range(len(u_list))]
curvebinorms = [[] for _ in range(len(u_list))]
for idx, u in enumerate(u_list):
curvetans[idx] = operations.tangent(curve, u, normalize=True)
curvenorms[idx] = operations.normal(curve, u, normalize=True)
curvebinorms[idx] = operations.binormal(curve, u, normalize=True)
#
# Control Points, Curve and Tangent Vector Plotting using Matplotlib
#
# Arrange control points and evaluated curve points for plotting
ctrlpts = np.array(curve.ctrlpts)
curvepts = np.array(curve.evalpts)
# Convert tangent, normal and binormal vector lists into NumPy arrays
ctarr = np.array(curvetans)
cnarr = np.array(curvenorms)
cbnarr = np.array(curvebinorms)
