def update(viewer):
global V, F, T, W, slice_z, overlay
plane = igl.eigen.MatrixXd([
0, 0, 1,
-((1 - slice_z) * V.col(2).minCoeff() + slice_z * V.col(2).maxCoeff())
])
V_vis = igl.eigen.MatrixXd()
F_vis = igl.eigen.MatrixXi()
J = igl.eigen.MatrixXi()
bary = igl.eigen.SparseMatrixd()
igl.slice_tets(V, T, plane, V_vis, F_vis, J, bary)
W_vis = igl.eigen.MatrixXd()
igl.slice(W, J, W_vis)
C_vis = igl.eigen.MatrixXd()
igl.parula(W_vis, False, C_vis)
if overlay == 1: # OVERLAY_INPUT
append_mesh(C_vis, F_vis, V_vis, V, F,
igl.eigen.MatrixXd([[1., 0.894, 0.227]]))
elif overlay == 2: # OVERLAY_OUTPUT
append_mesh(C_vis, F_vis, V_vis, V, F,
igl.eigen.MatrixXd([[0.8, 0.8, 0.8]]))
viewer.data.clear()
viewer.data.set_mesh(V_vis, F_vis)
viewer.data.set_colors(C_vis)
viewer.data.set_face_based(True)
def update_visualization(viewer):
global V, F, T, tree, FN, VN, EN, E, EMAP, max_distance, slice_z, overlay
plane = igl.eigen.MatrixXd([
0.0, 0.0, 1.0,
-((1 - slice_z) * V.col(2).minCoeff() + slice_z * V.col(2).maxCoeff())
])
V_vis = igl.eigen.MatrixXd()
F_vis = igl.eigen.MatrixXi()
# Extract triangle mesh slice through volume mesh and subdivide nasty triangles
J = igl.eigen.MatrixXi()
bary = igl.eigen.SparseMatrixd()
igl.marching_tets(V, T, plane, V_vis, F_vis, J, bary)
max_l = 0.03
while True:
l = igl.eigen.MatrixXd()
igl.edge_lengths(V_vis, F_vis, l)
l /= (V_vis.colwiseMaxCoeff() - V_vis.colwiseMinCoeff()).norm()
if l.maxCoeff() < max_l:
break
bad = l.rowwiseMaxCoeff() > max_l
notbad = l.rowwiseMaxCoeff() <= max_l # TODO replace by ~ operator
F_vis_bad = igl.eigen.MatrixXi()
F_vis_good = igl.eigen.MatrixXi()
igl.slice_mask(F_vis, bad, 1, F_vis_bad)
igl.slice_mask(F_vis, notbad, 1, F_vis_good)
igl.upsample(V_vis, F_vis_bad)
F_vis = igl.cat(1, F_vis_bad, F_vis_good)
# Compute signed distance
S_vis = igl.eigen.MatrixXd()
I = igl.eigen.MatrixXi()
N = igl.eigen.MatrixXd()
C = igl.eigen.MatrixXd()
# Bunny is a watertight mesh so use pseudonormal for signing
igl.signed_distance_pseudonormal(V_vis, V, F, tree, FN, VN, EN, EMAP,
S_vis, I, C, N)
# push to [0,1] range
S_vis = 0.5 * (S_vis / max_distance) + 0.5
C_vis = igl.eigen.MatrixXd()
# color without normalizing
igl.parula(S_vis, False, C_vis)
if overlay:
append_mesh(C_vis, F_vis, V_vis, V, F,
igl.eigen.MatrixXd([[0.8, 0.8, 0.8]]))
viewer.data().clear()
viewer.data().set_mesh(V_vis, F_vis)
viewer.data().set_colors(C_vis)
viewer.core.lighting_factor = overlay
def update_visualization(viewer):
global V, F, T, tree, FN, VN, EN, E, EMAP, max_distance, slice_z, overlay
plane = igl.eigen.MatrixXd([0.0, 0.0, 1.0, -((1 - slice_z) * V.col(2).minCoeff() + slice_z * V.col(2).maxCoeff())])
V_vis = igl.eigen.MatrixXd()
F_vis = igl.eigen.MatrixXi()
# Extract triangle mesh slice through volume mesh and subdivide nasty triangles
J = igl.eigen.MatrixXi()
bary = igl.eigen.SparseMatrixd()
igl.slice_tets(V, T, plane, V_vis, F_vis, J, bary)
max_l = 0.03
while True:
l = igl.eigen.MatrixXd()
igl.edge_lengths(V_vis, F_vis, l)
l /= (V_vis.colwiseMaxCoeff() - V_vis.colwiseMinCoeff()).norm()
if l.maxCoeff() < max_l:
break
bad = l.rowwiseMaxCoeff() > max_l
notbad = l.rowwiseMaxCoeff() <= max_l # TODO replace by ~ operator
F_vis_bad = igl.eigen.MatrixXi()
F_vis_good = igl.eigen.MatrixXi()
igl.slice_mask(F_vis, bad, 1, F_vis_bad)
igl.slice_mask(F_vis, notbad, 1, F_vis_good)
igl.upsample(V_vis, F_vis_bad)
F_vis = igl.cat(1, F_vis_bad, F_vis_good)
# Compute signed distance
S_vis = igl.eigen.MatrixXd()
I = igl.eigen.MatrixXi()
N = igl.eigen.MatrixXd()
C = igl.eigen.MatrixXd()
# Bunny is a watertight mesh so use pseudonormal for signing
igl.signed_distance_pseudonormal(V_vis, V, F, tree, FN, VN, EN, EMAP, S_vis, I, C, N)
# push to [0,1] range
S_vis = 0.5 * (S_vis / max_distance) + 0.5
C_vis = igl.eigen.MatrixXd()
# color without normalizing
igl.parula(S_vis, False, C_vis)
if overlay:
append_mesh(C_vis, F_vis, V_vis, V, F, igl.eigen.MatrixXd([[0.8, 0.8, 0.8]]))
viewer.data.clear()
viewer.data.set_mesh(V_vis, F_vis)
viewer.data.set_colors(C_vis)
viewer.core.lighting_factor = overlay
def key_down(viewer, key, mod):
global U, c
if key == ord(' '):
U = U.rightCols(k)
# Rescale eigen vectors for visualization
Z = bbd * 0.5 * U.col(c)
C = igl.eigen.MatrixXd()
igl.parula(U.col(c), False, C)
c = (c + 1) % U.cols()
if twod:
V.setcol(2, Z)
viewer.data.set_mesh(V, F)
viewer.data.compute_normals()
viewer.data.set_colors(C)
return True
def key_down(viewer, key, mod):
global U, c
if key == ord(' '):
U = U.rightCols(k)
# Rescale eigen vectors for visualization
Z = bbd * 0.5 * U.col(c)
C = igl.eigen.MatrixXd()
igl.parula(U.col(c), False, C)
c = (c + 1) % U.cols()
if twod:
V.setcol(2, Z)
viewer.data.set_mesh(V, F)
viewer.data.compute_normals()
viewer.data.set_colors(C)
return True
def update(viewer):
global V, F, T, W, slice_z, overlay
plane = igl.eigen.MatrixXd([0, 0, 1, -((1 - slice_z) * V.col(2).minCoeff() + slice_z * V.col(2).maxCoeff())])
V_vis = igl.eigen.MatrixXd()
F_vis = igl.eigen.MatrixXi()
J = igl.eigen.MatrixXi()
bary = igl.eigen.SparseMatrixd()
igl.marching_tets(V, T, plane, V_vis, F_vis, J, bary)
W_vis = igl.eigen.MatrixXd()
igl.slice(W, J, W_vis)
C_vis = igl.eigen.MatrixXd()
igl.parula(W_vis, False, C_vis)
if overlay == 1: # OVERLAY_INPUT
append_mesh(C_vis, F_vis, V_vis, V, F, igl.eigen.MatrixXd([[1., 0.894, 0.227]]))
elif overlay == 2: # OVERLAY_OUTPUT
append_mesh(C_vis, F_vis, V_vis, V, F, igl.eigen.MatrixXd([[0.8, 0.8, 0.8]]))
viewer.data().clear()
viewer.data().set_mesh(V_vis, F_vis)
viewer.data().set_colors(C_vis)
viewer.data().set_face_based(True)
def pre_draw(viewer):
if not viewer.core.is_animating:
return False
global anim_t
global start_point
global end_point
igl.streamlines_next(V, F, data, state)
value = (anim_t % 100) / 100.0
if value > 0.5:
value = 1 - value
value /= 0.5
r, g, b = igl.parula(value)
viewer.data.add_edges(state.start_point, state.end_point, igl.eigen.MatrixXd([[r, g, b]]))
anim_t += anim_t_dir
return False
def pre_draw(viewer):
if not viewer.core().is_animating:
return False
global anim_t
global start_point
global end_point
igl.streamlines_next(V, F, data, state)
value = (anim_t % 100) / 100.0
if value > 0.5:
value = 1 - value
value /= 0.5
r, g, b = igl.parula(value)
viewer.data().add_edges(state.start_point, state.end_point, igl.eigen.MatrixXd([[r, g, b]]))
anim_t += anim_t_dir
return False
PD2 = igl.eigen.MatrixXd() PV1 = igl.eigen.MatrixXd() PV2 = igl.eigen.MatrixXd() igl.principal_curvature(V, F, PD1, PD2, PV1, PV2) # Mean curvature H = 0.5 * (PV1 + PV2) viewer = igl.glfw.Viewer() viewer.data().set_mesh(V, F) # Compute pseudocolor C = igl.eigen.MatrixXd() igl.parula(H, True, C) viewer.data().set_colors(C) # Average edge length for sizing avg = igl.avg_edge_length(V, F) # Draw a blue segment parallel to the minimal curvature direction red = igl.eigen.MatrixXd([[0.8, 0.2, 0.2]]) blue = igl.eigen.MatrixXd([[0.2, 0.2, 0.8]]) viewer.data().add_edges(V + PD1 * avg, V - PD1 * avg, blue) # Draw a red segment parallel to the maximal curvature direction viewer.data().add_edges(V + PD2 * avg, V - PD2 * avg, red)
PD2 = igl.eigen.MatrixXd() PV1 = igl.eigen.MatrixXd() PV2 = igl.eigen.MatrixXd() igl.principal_curvature(V, F, PD1, PD2, PV1, PV2) # Mean curvature H = 0.5 * (PV1 + PV2) viewer = igl.glfw.Viewer() viewer.data().set_mesh(V, F) # Compute pseudocolor C = igl.eigen.MatrixXd() igl.parula(H, True, C) viewer.data().set_colors(C) # Average edge length for sizing avg = igl.avg_edge_length(V, F) # Draw a blue segment parallel to the minimal curvature direction red = igl.eigen.MatrixXd([[0.8, 0.2, 0.2]]) blue = igl.eigen.MatrixXd([[0.2, 0.2, 0.8]]) viewer.data().add_edges(V + PD1 * avg, V - PD1 * avg, blue) # Draw a red segment parallel to the maximal curvature direction viewer.data().add_edges(V + PD2 * avg, V - PD2 * avg, red)
