scale = 10 / 170.258 # New legnth [um] / old length [px]
folder = 'res/pipe00' #
iframes_raw = list(range(1, 18, 2)) + [18] + list(range(21, 42, 2))
shapes = []
for iframe_raw in iframes_raw:
xname = os.path.join(folder, 'x-{}.dat'.format(iframe_raw))
yname = os.path.join(folder, 'y-{}.dat'.format(iframe_raw))
zname = os.path.join(folder, 'z-{}.dat'.format(iframe_raw))
xx = scale * np.loadtxt(xname)
yy = scale * np.loadtxt(yname)
zz = scale * np.loadtxt(zname)
cc = colors[iframe_raw] # shapes are starting from 1
c = tuple(cc[:3]) # discard opacity
shape = vedo.Tube(list(zip(zz, xx, yy)), r=0.125, c=c)
shapes += [shape]
# ===== final =====
# + shift
folder = 'res/pipe_final' #
iframes_raw = list(range(20))
x = np.loadtxt(os.path.join(folder, 'x-data'))
y = np.loadtxt(os.path.join(folder, 'y-data'))
z = np.loadtxt(os.path.join(folder, 'z-data'))
# Add shapes
# Shift them and rescale for easier comparison
x0, y0 = 20, 0
for iframe_raw, xx, yy, zz in zip(iframes_raw, x, y, z):
def viz_observation_manifold(t3, tlim, size):
tmin = 0
tmax = 2 * tlim
# tlim line
vline1 = vp.Tube([[tmin, tlim, t3], [tmax, tlim, t3]], r=2.0)
vline1.color('g')
# t = 0 line
vline2 = vp.Tube([[tmin, tlim, t3], [tmin, tmax, t3]], r=2.0)
vline2.color((1, 1, 1))
# Manifold
verts = [[tmin, tlim, t3], [tmax, tlim, t3], [tmin, tmax, t3],
[tmax, tmax, t3]]
triangs = [[0, 1, 3], [0, 3, 2]]
vmesh1 = vp.Mesh([verts, triangs])
vmesh1.color((1, 1, 1))
# Inverse manifold
verts = [[tmin, tmin, t3], [tmax, tmin, t3], [tmin, tlim, t3],
[tmax, tlim, t3]]
triangs = [[0, 1, 3], [0, 3, 2]]
vmesh2 = vp.Mesh([verts, triangs])
vmesh2.color((0.9, 0.9, 0.9)).alpha(0.0)
# Invisible points to set the extent
vpoints = vp.Points([(tmin - 0.1, tmin - 0.1, tmin - 0.1),
(1.01 * tmax, 1.01 * tmax, 1.01 * tmax)]).alpha(0.0)
lpos = [(p, str(p)) for p in [0, 50, 100, 150]]
vplotter = vp.Plotter(offscreen=True,
size=size,
axes=dict(xyGrid=True,
yzGrid=True,
zxGrid=True,
xTitleSize=0,
yTitleSize=0,
zTitleSize=0,
xPositionsAndLabels=lpos,
yPositionsAndLabels=lpos,
zPositionsAndLabels=lpos[1:],
axesLineWidth=5,
tipSize=0.02,
gridLineWidth=2,
xLabelSize=0.05,
yLabelSize=0.05,
zLabelSize=0.05,
xLabelOffset=0.05,
yLabelOffset=0.05,
zLabelOffset=0.0,
zTitleRotation=225))
vlabels = [
vp.Text2D("H", (0.09 * size[0], 0.10 * size[1]), s=3, font='Arial'),
vp.Text2D("N", (0.87 * size[0], 0.16 * size[1]), s=3, font='Arial'),
vp.Text2D("S", (0.49 * size[0], 0.90 * size[1]), s=3, font='Arial')
]
vp.show([vline1, vline2, vmesh1, vpoints] + vlabels,
camera=dict(pos=(378, 324, 450),
focalPoint=(tlim, tlim, tlim + 27),
viewup=(0, 0, 1)))
img = vp.screenshot(None, scale=1, returnNumpy=True)
vp.clear()
vp.closePlotter()
return img
def viz_param_manifold(filename, size):
data = np.load(filename)
vline = vp.Tube(data['boundary_hns'], r=0.08)
vline.color('g')
# HNS manifold
vmesh_hns = vp.Mesh([data['verts_hns'], data['triangs_hns']])
k = 3
prior = (2 * np.pi)**(-k / 2) * (np.exp(
-0.5 * np.sum(vmesh_hns.points()**2, axis=1)))
vmesh_hns.pointColors(prior, cmap='Reds', vmin=0)
vmesh_hns.addScalarBar(horizontal=True,
nlabels=6,
c='k',
pos=(0.74, 0.01),
titleFontSize=44)
vmesh_hns.scalarbar.SetLabelFormat("%.2g")
vmesh_hns.scalarbar.SetBarRatio(1.0)
# Inverted HNS manifold
vmesh_hnsi = vp.Mesh([data['verts_hnsi'], data['triangs_hnsi']])
# vmesh_hnsi.color([0.68, 0.68, 0.68])
vmesh_hnsi.color([0.9, 0.9, 0.9]).alpha(0.0)
# Invisible points to set the extent
vpoints = vp.Points([(-5.01, -5.01, -5.01), (5.01, 5.01, 5.01)]).alpha(0.0)
vplotter = vp.Plotter(offscreen=True,
size=size,
axes=dict(xyGrid=True,
yzGrid=True,
zxGrid=True,
xTitleSize=0,
yTitleSize=0,
zTitleSize=0,
xHighlightZero=True,
yHighlightZero=True,
zHighlightZero=True,
xHighlightZeroColor='b',
yHighlightZeroColor='b',
zHighlightZeroColor='b',
numberOfDivisions=10,
axesLineWidth=5,
tipSize=0.02,
gridLineWidth=2,
xLabelSize=0.05,
yLabelSize=0.05,
zLabelSize=0.05,
xLabelOffset=0.05,
yLabelOffset=0.05,
zLabelOffset=0.0,
zTitleRotation=225))
vlabels = [
vp.Text2D("H", (0.09 * size[0], 0.10 * size[1]), s=3, font='Arial'),
vp.Text2D("N", (0.87 * size[0], 0.16 * size[1]), s=3, font='Arial'),
vp.Text2D("S", (0.49 * size[0], 0.90 * size[1]), s=3, font='Arial')
]
k = 2
vecs = np.array([[[0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0]],
[[k, -k, 0, 0, 0, 0], [0, 0, k, -k, 0, 0],
[0, 0, 0, 0, k, -k]]])
varrows = vp.Arrows(vecs[0].T, vecs[1].T, s=1.2, c='k')
vp.show([vline, vmesh_hns, vmesh_hnsi, vpoints, varrows] + vlabels,
camera=dict(pos=(16, 13, 20),
focalPoint=(0, 0, 1.5),
viewup=(0, 0, 1)))
img = vp.screenshot(None, scale=1, returnNumpy=True)
vp.clear()
vp.closePlotter()
return img
'''
if isinstance(cmap, str):
cmap = plt.get_cmap(cmap) #
return cmap(np.linspace(minval, maxval, num, endpoint=endpoint))
x = np.loadtxt(os.path.join(folder, 'x-data'))
y = np.loadtxt(os.path.join(folder, 'y-data'))
z = np.loadtxt(os.path.join(folder, 'z-data'))
colors = get_colors(len(iframes_raw), 'hsv')
shapes = []
for iframe_raw, xx, yy, zz in zip(iframes_raw, x, y, z):
cc = colors[iframe_raw] # shapes are starting from 1
c = tuple(cc[:3]) # discard opacity
shape = vedo.Tube(list(zip(xx, yy, zz)), r=0.125, c=c)
shapes += [shape]
size = 256 * np.array([4, 3]) # window size # 256
offscreen = False # Hide
interactive = False # should be false to execute the whole script
plotter = vedo.plotter.Plotter(pos=(100, 0),
interactive=interactive,
size=size,
offscreen=offscreen)
plane = vedo.Plane(pos=(0, 0, 0), normal=(0, 0, 1), sx=10).alpha(0.5)
shapes += [plane]
plotter.add(shapes, render=False)
plotter.show(interactive=True).close()
cmap = plt.get_cmap(cmap) #
return cmap(np.linspace(minval, maxval, num, endpoint=endpoint))
colors = get_colors(42, 'hsv')
shapes = []
for iframe_raw in iframes_raw:
xname = os.path.join(folder, 'x-{}.dat'.format(iframe_raw))
yname = os.path.join(folder, 'y-{}.dat'.format(iframe_raw))
zname = os.path.join(folder, 'z-{}.dat'.format(iframe_raw))
xx = np.loadtxt(xname)
yy = np.loadtxt(yname)
zz = np.loadtxt(zname)
cc = colors[iframe_raw] # shapes are starting from 1
c = tuple(cc[:3]) # discard opacity
shape = vedo.Tube(list(zip(zz, xx, yy)), r=1, c=c) # NB: Swapped axes!!
shapes += [shape]
size = 256 * np.array([4, 3]) # window size # 256
offscreen = False # Hide
interactive = False # should be false to execute the whole script
plotter = vedo.plotter.Plotter(pos=(100, 0), interactive=interactive,
size=size, offscreen=offscreen)
plane = vedo.Plane(pos=(0, 0, 0), normal=(0, 0, 1), sx=100).alpha(0.5)
shapes += [plane]
plotter.add(shapes, render=False)
plotter.show(interactive=True).close()
# Git repo at : https://morphomatics.github.io/tutorial_ssm/
# Install with:
# pip install git+https://github.com/morphomatics/morphomatics.git#egg=morphomatics
#
from morphomatics.geom import Surface
from morphomatics.stats import StatisticalShapeModel
from morphomatics.manifold import FundamentalCoords
import numpy as np
import vedo
ln1 = [[1, 1, x / 2] for x in np.arange(0, 15, 0.15)]
ln2 = [[np.sin(x), np.cos(x), x / 2] for x in np.arange(0, 15, 0.15)]
rads = [0.4 * (np.cos(6 * ir / len(ln2)))**2 + 0.1 for ir in range(len(ln2))]
vmesh1 = vedo.Tube(ln1, r=0.08, c="tomato").triangulate().clean()
vmesh2 = vedo.Tube(ln2, r=rads, c="tomato").triangulate().clean()
verts1 = vmesh1.points()
verts2 = vmesh2.points()
faces = np.array(vmesh1.faces())
# construct model
SSM = StatisticalShapeModel(lambda ref: FundamentalCoords(ref))
surfaces = [Surface(v, faces) for v in [verts1, verts2]]
SSM.construct(surfaces)
# sample trajectory along the main mode of variation
shapes = [vmesh1]
std = np.sqrt(SSM.variances[0])
for t in np.linspace(-1.0, 1.0, 20):
e = SSM.space.exp(SSM.mean_coords, t * std * SSM.modes[0])