def toggle3d(state=True, nb_backend=None, **kwds):
"""
Switch on/off the mayavi backend.
**Parameters**
state: bool | True
on/off state of the mayavi backend
nb_backend: | None
type of rendering engine choose from 'x3d' (interactive) and 'png' (static).
**kwds: keyword arguments
additional arguments to be passed into ``mayavi.mlab.init_notebook()``.
"""
global PLOT3D
PLOT3D = state
if PLOT3D == True:
global mlab
from mayavi import mlab
if nb_backend:
mlab.init_notebook(nb_backend, **kwds)
else:
try:
mlab = None
except:
pass
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
if self._get_mode() == 0:
mlab.init_notebook()
size = (600, 400)
if self.size:
size = self.size
self._fig = mlab.figure(
size=size,
bgcolor=cfg["mayavi"]["bg_color"],
fgcolor=cfg["mayavi"]["fg_color"],
)
def show_fem(u, local=False, show_volume=True, show_plane=True):
global fem_counter
fem_counter = fem_counter + 1
mlab.init_notebook()
mlab.clf()
name_base = "./tmp_u_" + str(fem_counter)
dolfin.File(name_base + ".pvd") << u
time.sleep(1)
s = mlab.pipeline.open(name_base + '000000.vtu')
#mlab.pipeline.volume(s)
#mlab.contour3d(s)
if show_volume:
scp = mlab.pipeline.volume(s)
if show_plane:
scp = mlab.pipeline.scalar_cut_plane(s, view_controls=True)
return scp
def show_geom(g, local=False, step=0.6, show_surface=True):
if not local:
stl_file = getStl(g, step=step)
time.sleep(3)
print(stl_file)
mlab.init_notebook()
mlab.clf()
s = mlab.pipeline.open(stl_file)
if show_surface:
s = mlab.pipeline.surface(s)
return s
else:
result = DisplayShape(trans_box,
export_edges=True,
color=rnd_color,
transparency=random.random())
return display(result)
def postprocessing(self):
import mayavi, vtk, os
from mayavi import mlab
mlab.init_notebook()
from mayavi.sources.vtk_xml_file_reader import VTKXMLFileReader
from mayavi.sources.vrml_importer import VRMLImporter
from mayavi.modules.outline import Outline
from mayavi.modules.streamline import Streamline
from mayavi.modules.iso_surface import IsoSurface
from mayavi.sources.vtk_file_reader import VTKFileReader
print('Mayavi {}, {}, DISPLAY {}'.format(mayavi.__version__, vtk.vtkVersion.GetVTKSourceVersion(), os.environ['DISPLAY']))
# fetch the results
fname='Composition_00010000.vtk'
oc_proj_base = self.wJobPath.value.strip(' /')
oc=DavProxy()
oc.set_token()
oc.get(oc_proj_base + '/OP/VTK/'+fname, './' + fname)
# run mlab pipeline
mlab.clf() # clear figure
r = VTKFileReader()
r.initialize(fname)
r.point_scalars_name = 'TotalComposition_Li'
scp=mlab.pipeline.scalar_cut_plane(r, view_controls=False,plane_orientation='y_axes')
scpx=mlab.pipeline.scalar_cut_plane(r, view_controls=False,plane_orientation='x_axes')
mlab.pipeline.outline(r)
col_cp=mlab.scalarbar(scp, title='C(Li)', orientation='vertical')
return mlab.gcf() # plot
# <markdowncell>
# 
# 
# 
# <codecell>
# <markdowncell>
# Mayavi can also be used to plot grid function in Python. This approach
# relies on methods to extract `numpy` representations of the grid data
# structure and values of a given grid function.
#
# __Note__: mayavi is not installed in the Docker image and, therefore,
# this feature is not available the Docker container.
# <codecell>
level = 3
triangulation = f.grid.triangulation(level)
z = f.pointData(level)[:, 0]
try:
from mayavi import mlab
from mayavi.tools.notebook import display
mlab.init_notebook("png")
mlab.figure(bgcolor=(1, 1, 1))
s = mlab.triangular_mesh(triangulation.x, triangulation.y, z * 0.5,
triangulation.triangles)
display(s)
# mlab.savefig("mayavi.png", size=(400,300))
mlab.close(all=True)
except ImportError:
pass
import os
import sys
import re
import pickle # todo: current pickle file are using format 3 witch is not compatible with python2
from meshpy.obj_file import ObjFile
from meshpy.sdf_file import SdfFile
from dexnet.grasping import GraspableObject3D
import numpy as np
from dexnet.visualization.visualizer3d import DexNetVisualizer3D as Vis
from dexnet.grasping import RobotGripper
from autolab_core import YamlConfig
try:
from mayavi import mlab
mlab.init_notebook('x3d', 800, 800)
except ImportError:
print("can not import mayavi")
mlab = None
from dexnet.grasping import GpgGraspSampler # temporary way for show 3D gripper using mayavi
import pcl
import glob
from IPython.display import display
# In[2]:
# global configurations:
home_dir = os.environ['HOME']
yaml_config = YamlConfig(home_dir + "/code/grasp-pointnet/dex-net/test/config.yaml")
def init():
display = Xvfb(width=500, height=500)
display.start()
mlab.init_notebook()
def plot3d(uh,level):
x, triangles = uh.space.grid.tesselate(level)
mlab.init_notebook("png") # use x3d for interactive plotting in the notebook
mlab.figure(bgcolor = (1,1,1))
s = mlab.triangular_mesh(x[:,0],x[:,1],x[:,2],triangles)
display( s )
from mayavi import mlab
import numpy as np
mlab.init_notebook('x3d', 400, 200, local=False)
mlab.clf()
theta = np.linspace(0, 2 * np.pi, 100)
phi = np.linspace(0, 2 * np.pi, 100)
X = np.outer((20 + 4 * np.cos(phi)), np.cos(theta))
Y = np.outer((20 + 4 * np.cos(phi)), np.sin(theta))
Z = np.outer(np.sin(phi), 1.8 * np.ones(np.size(theta)))
#the position of the ball
x = np.array([2.5, 3.0, 3.0])
y = np.array([3.0, 2.5, 3.0])
z = np.array([3.0, 3.0, 2.5])
mlab.clf()
mlab.points3d(x[1:-1],
y[1:-1],
z[1:-1],
color=(1, 1, 1),
resolution=20,
scale_factor=3)
mlab.mesh(X, Y, Z, representation='wireframe')
mlab.title('3D Torus Billiard')
Find closest trajectories
=========================
Finds the probe insertions that are closest a a specified probe insertion of interest and plots
their location in a 3D image. Additionally prints out the information of closeby sessions
"""
# Author: Mayo Faulkner
# import modules
import numpy as np
import ibllib.pipes.histology as histology
import ibllib.atlas as atlas
from oneibl.one import ONE
from mayavi import mlab
from atlaselectrophysiology import rendering
mlab.init_notebook()
# Instantiate brain atlas and one
brain_atlas = atlas.AllenAtlas(25)
one = ONE()
# Find all trajectories with histology tracing
all_hist = one.alyx.rest('trajectories', 'list', provenance='Histology track')
# Some do not have tracing, exclude these ones
sess_with_hist = [sess for sess in all_hist if sess['x'] is not None]
traj_ids = [sess['id'] for sess in sess_with_hist]
# Compute trajectory objects for each of the trajectories
trajectories = [atlas.Insertion.from_dict(sess) for sess in sess_with_hist]
# Find the trajectory of the id that you want to find closeby probe insertions for
subject = 'SWC_023'
date = '2020-02-13'
label_title = Label(Mafenetre, text="Welcome to billiard game")
label_title.pack()
# Création d'un widget Canvas
Canevas = Canvas(Mafenetre, height=HAUTEUR, width=LARGEUR, bg='green')
Canevas.pack(padx=5, pady=5)
# Création d'un objet graphique
Balle = Canevas.create_oval(X - RAYON,
Y - RAYON,
X + RAYON,
Y + RAYON,
width=1,
fill='white')
#Bouton quitter
Bouton_Quitter = Button(Mafenetre, text='Quit', command=Mafenetre.destroy)
Bouton_Quitter.pack()
deplacement()
Mafenetre.mainloop()
from mayavi import mlab
mlab.init_notebook(backend='x3d', local=False)
theta = np.linspace(0, 2 * np.pi, 100)
phi = np.linspace(0, 2 * np.pi, 100)
X = np.outer((1 + 0.2 * np.cos(phi)), np.cos(theta))
Y = np.outer((1 + 0.2 * np.cos(phi)), np.sin(theta))
Z = np.outer(np.sin(phi), 0.09 * np.ones(np.size(theta)))
mlab.clf()
mlab.mesh(X, Y, Z, representation='wireframe')
# Linden Parkes, 2019 # [email protected] import os import numpy as np import nibabel as nib import mayavi as my from mayavi import mlab mlab.init_notebook(backend='png') import surfer import math from matplotlib.pyplot import get_cmap def roi_to_vtx(roi_data, parcel_names, parc_file): # roi_data = (num_nodes,) array vector of node-level data to plot onto surface # # # parcel_names = (num_nodes,) array vector of strings containg roi names # corresponding to roi_data # # parc_file = full path and file name to surface file # Note, I used fsaverage/fsaverage5 surfaces # Load freesurfer file labels, ctab, surf_names = nib.freesurfer.read_annot(parc_file) # convert FS surf_names to array of strings if type(surf_names[0]) != str: for i in np.arange(0, len(surf_names)):