def render_spline(ctrl_pts, rows, cols):
ctrl_pts = ctrl_pts.reshape(-1, 3).detach().cpu().numpy().tolist()
pts_h = rows
pts_v = cols
surf = BSpline.Surface()
surf.degree_u = 3
surf.degree_v = 3
surf.set_ctrlpts(ctrl_pts, pts_h, pts_v)
surf.knotvector_u = knotvector.generate(3, pts_h, clamped=True)
surf.knotvector_v = knotvector.generate(3, pts_v, clamped=True)
surf.delta = 0.025
surf.evaluate()
surf.vis = VisPlotly.VisSurface()
surf.render(colormap=cm.cool)
surf.degree_u = 3
surf.degree_v = 3
# Get the control points from the generated grid
surf.ctrlpts2d = surfgrid.grid()
# Set knot vectors
surf.knotvector_u = utilities.generate_knot_vector(surf.degree_u,
surf.ctrlpts_size_u)
surf.knotvector_v = utilities.generate_knot_vector(surf.degree_v,
surf.ctrlpts_size_v)
# Split the surface at v = 0.35
split_surf = surf.split_v(0.35)
# Set sample size of the split surface
split_surf.sample_size = 25
# Generate the visualization component and its configuration
vis_config = VisPlotly.VisConfig(ctrlpts=False, legend=False)
vis_comp = VisPlotly.VisSurface(vis_config)
# Set visualization component of the split surface
split_surf.vis = vis_comp
# Plot the split surface
split_surf.render()
# Good to have something here to put a breakpoint
pass
os.chdir(os.path.dirname(os.path.realpath(__file__)))
# Create a BSpline surface instance
surf = BSpline.Surface()
# Set degrees
surf.degree_u = 3
surf.degree_v = 3
# Set control points
surf.set_ctrlpts(
*exchange.import_txt("ex_surface01.cpt", two_dimensional=True))
# Set knot vectors
surf.knotvector_u = [0.0, 0.0, 0.0, 0.0, 1.0, 2.0, 3.0, 3.0, 3.0, 3.0]
surf.knotvector_v = [0.0, 0.0, 0.0, 0.0, 1.0, 2.0, 3.0, 3.0, 3.0, 3.0]
# Set evaluation delta
surf.delta = 0.025
# Evaluate surface points
surf.evaluate()
# Plot the control point grid and the evaluated surface
vis_comp = VisPlotly.VisSurface()
surf.vis = vis_comp
surf.render()
# Good to have something here to put a breakpoint
pass
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Examples for the NURBS-Python Package
Released under MIT License
Developed by Onur Rauf Bingol (c) 2018
"""
import os
from geomdl import exchange
from geomdl.visualization import VisPlotly as vis
# Fix file path
os.chdir(os.path.dirname(os.path.realpath(__file__)))
# Read a directory containing smesh files
multi_smesh = exchange.import_smesh('data')
multi_smesh.sample_size = 5
# Draw the control point grid and the evaluated surface
vis_config = vis.VisConfig(ctrlpts=False, legend=False)
vis_comp = vis.VisSurface(vis_config)
multi_smesh.vis = vis_comp
multi_smesh.render()
# Save MultiSurface as a .obj file
exchange.export_obj(multi_smesh, "multisurface01.obj")
# Good to have something here to put a breakpoint
pass
[surface0, surface1] = geomdl.operations.split_surface_u(surface_full, 0.4)
[surface, surface2] = geomdl.operations.split_surface_u(surface1, 0.5555)
# save surface to a pickle file
pickle_filename = output_pickle_filename
print("Write pickle file \"{}\"".format(pickle_filename))
with open(pickle_filename,"wb") as f:
pickle.dump(surface,f)
# here we have the surface, either loaded from an existing pickle file or newly created
# triangulate the surface for output
for surf in [surface]:
surf.sample_size = 100
surf.evaluate()
# plot the result
if False:
surface_full.vis = VisPlotly.VisSurface()
surface_full.render()
surface.vis = VisPlotly.VisSurface()
#surface.vis = VisMPL.VisSurfWireframe()
surface.render()
# export as STL file
print("write stl file \"{}\"".format(output_stl_filename))
geomdl.exchange.export_stl(surface, output_stl_filename)
print("File \"{}\" written.".format(output_stl_filename))
drdt_es.append(cylinder_es.partial_theta()) drdz_es.append(cylinder_es.partial_z()) # print(len(drdt_ed)) pts_ed = r_ed size_u = 20 size_v = 20 degree_u = 3 degree_v = 3 # Do global surface approximation surf_ed = fitting.approximate_surface(pts_ed, size_u, size_v, degree_u, degree_v) surf_ed = convert.bspline_to_nurbs(surf_ed) surf_ed.delta = 0.025 surf_ed.vis = vis.VisSurface() evalpts_ed = np.array(surf_ed.evalpts) pts_es = r_es # Do global surface approximation surf_es = fitting.approximate_surface(pts_es, size_u, size_v, degree_u, degree_v) surf_es = convert.bspline_to_nurbs(surf_es) surf_es.delta = 0.025 surf_es.vis = vis.VisSurface() evalpts_es = np.array(surf_es.evalpts) # exchange.export_obj(surf_ed,"clyinder_ed.obj") # exchange.export_obj(surf_es,"clyinder_es.obj")
ax = plt.axes(projection='3d')
ax.scatter(r[:, 0], r[:, 1], r[:, 2], s=50, color='r')
pts = r
size_u = 20
size_v = 20
degree_u = 3
degree_v = 3
# Do global surface approximation
surf = fitting.approximate_surface(pts, size_u, size_v, degree_u, degree_v)
surf = convert.bspline_to_nurbs(surf)
surf.delta = 0.025
surf.vis = vis.VisSurface()
evalpts = np.array(surf.evalpts)
ax.scatter(evalpts[:, 0], evalpts[:, 1], evalpts[:, 2], color='b')
# plt.show()
surf_curves = construct.extract_curves(surf)
plot_extras = [
dict(points=surf_curves['u'][0].evalpts, name="u", color="red", size=5),
dict(points=surf_curves['v'][0].evalpts, name="v", color="black", size=5)
]
# surf.render(extras = plot_extras)
exchange.export_obj(surf, "clyinder_ed.obj")
# compute analytical metric tensor
a_E = []
a_F = []
a_G = []