def update(chset):
mlab.get_engine().scenes[0].children[-1].remove()
new = numpy.array([estimate[chset['new']]])
pnew = vis.plot_prism_mesh(new, style='surface', xy2ne=True)
neighbors = numpy.array([setden(e, chset['dens']) for e in [estimate[n] for n in chset['nn']]])
pnn = vis.plot_prism_mesh(neighbors, style='wireframe', xy2ne=True)
pnn.actor.property.color = neighborcolor
pnn.actor.property.line_width = 1
pos = 0
scale = 800
Z = numpy.reshape(data['value'] - chset['res'], dshape)
ct = mlab.contour_surf(X, Y, Z, contours=10, colormap='jet')
ct.contour.filled_contours = True
ct.actor.actor.position = (0,0,pos)
ct.actor.actor.scale = (1,1,scale)
def __init__(self, objects, objectsOverlay, objectInputOverlay, outputdir):
self.objects = objects
self.objectsOverlay = objectsOverlay
self.objectsInputOverlay = objectInputOverlay
self.outputdir = outputdir
self.counter = 0
self.max_spread_x = 0
self.max_spread_y = 0
self.max_spread_z = 0
for iobj in self.objects.values():
spread_x = max(iobj[0])-min(iobj[0])
if self.max_spread_x < spread_x:
self.max_spread_x = spread_x
spread_y = max(iobj[1])-min(iobj[1])
if self.max_spread_y < spread_y:
self.max_spread_y = spread_y
spread_z = max(iobj[2])-min(iobj[2])
if self.max_spread_z < spread_z:
self.max_spread_z = spread_z
self.max_spread_x = self.max_spread_x/2+10
self.max_spread_y = self.max_spread_y/2+10
self.max_spread_z = self.max_spread_z/2
from enthought.mayavi import mlab
# Returns the current scene.
self.scene = mlab.figure(size = (2*self.max_spread_x, 2*self.max_spread_y), bgcolor = (1., 1., 1.))
self.engine = mlab.get_engine()
def __init__(self, objects, objectsOverlay, objectInputOverlay, outputdir):
self.objects = objects
self.objectsOverlay = objectsOverlay
self.objectsInputOverlay = objectInputOverlay
self.outputdir = outputdir
self.counter = 0
self.max_spread_x = 0
self.max_spread_y = 0
self.max_spread_z = 0
for iobj in self.objects.values():
spread_x = max(iobj[0]) - min(iobj[0])
if self.max_spread_x < spread_x:
self.max_spread_x = spread_x
spread_y = max(iobj[1]) - min(iobj[1])
if self.max_spread_y < spread_y:
self.max_spread_y = spread_y
spread_z = max(iobj[2]) - min(iobj[2])
if self.max_spread_z < spread_z:
self.max_spread_z = spread_z
self.max_spread_x = self.max_spread_x / 2 + 10
self.max_spread_y = self.max_spread_y / 2 + 10
self.max_spread_z = self.max_spread_z / 2
from enthought.mayavi import mlab
# Returns the current scene.
self.scene = mlab.figure(size=(2 * self.max_spread_x,
2 * self.max_spread_y),
bgcolor=(1., 1., 1.))
self.engine = mlab.get_engine()
def generate_file_rst(fname, target_dir, src_dir, plot_gallery):
""" Generate the rst file for a given example.
"""
image_name = fname[:-2] + 'png'
global rst_template, plot_rst_template
this_template = rst_template
last_dir = os.path.split(src_dir)[-1]
# to avoid leading . in file names
if last_dir == '.': last_dir = ''
else: last_dir += '_'
short_fname = last_dir + fname
src_file = os.path.join(src_dir, fname)
example_file = os.path.join(target_dir, fname)
shutil.copyfile(src_file, example_file)
if plot_gallery and fname.startswith('plot'):
# generate the plot as png image if file name
# starts with plot and if it is more recent than an
# existing image.
if not os.path.exists(os.path.join(target_dir, 'images')):
os.makedirs(os.path.join(target_dir, 'images'))
image_file = os.path.join(target_dir, 'images', image_name)
if (not os.path.exists(image_file) or
os.stat(image_file).st_mtime <= os.stat(src_file).st_mtime):
print 'plotting %s' % fname
import matplotlib.pyplot as plt
plt.close('all')
try:
from enthought.mayavi import mlab
mlab.close(all=True)
except:
pass
try:
execfile(example_file, {'pl' : plt})
facecolor = plt.gcf().get_facecolor() # hack to keep black bg
if facecolor == (0.0, 0.0, 0.0, 1.0):
plt.savefig(image_file, facecolor='black')
else:
plt.savefig(image_file)
try:
from enthought.mayavi import mlab
e = mlab.get_engine()
if len(e.scenes) > 0:
mlab.savefig(image_file)
except:
pass
except:
print 80*'_'
print '%s is not compiling:' % fname
traceback.print_exc()
print 80*'_'
this_template = plot_rst_template
docstring, short_desc, end_row = extract_docstring(example_file)
f = open(os.path.join(target_dir, fname[:-2] + 'rst'), 'w')
f.write(this_template % locals())
f.flush()
def test_figure(self):
""" Various tests for mlab.figure().
"""
# Test when specifying figure instances
f1 = mlab.figure()
e = mlab.get_engine()
self.assert_(e.current_scene is f1)
f2 = mlab.figure()
self.assert_(e.current_scene is f2)
mlab.figure(f1)
self.assert_(e.current_scene is f1)
# Test when specifying figure numbers
f1 = mlab.figure(3)
self.assert_(e.current_scene is f1)
f2 = mlab.figure(4)
self.assert_(e.current_scene is f2)
mlab.figure(3)
self.assert_(e.current_scene is f1)
# Test when specifying figure names
f1 = mlab.figure('Test 1')
self.assert_(e.current_scene is f1)
f2 = mlab.figure('Test 2')
self.assert_(e.current_scene is f2)
mlab.figure('Test 1')
self.assert_(e.current_scene is f1)
def plotsln(mesh, z=None, sln=None, colorbar=False, view=(0,0),
filename="a.png"):
"""
Plot a solution for the mesh editor in the online lab.
"""
x = [n[0] for n in mesh.nodes]
y = [n[1] for n in mesh.nodes]
if z == None:
try:
z = [n[2] for n in mesh.nodes]
except IndexError:
z = [0]*len(y)
from enthought.mayavi import mlab
mlab.options.offscreen = True
mlab.clf()
#mlab.options.show_scalar_bar = False
mlab.triangular_mesh(x, y, z, mesh.elems, scalars=sln)
engine = mlab.get_engine()
image = engine.current_scene
image.scene.background = (1.0, 1.0, 1.0)
image.scene.foreground = (0.0, 0.0, 0.0)
if colorbar:
mlab.colorbar(orientation="vertical")
if view:
mlab.view(view[0], view[1])
mlab.savefig(filename)
def test_figure(self):
""" Various tests for mlab.figure().
"""
# Test when specifying figure instances
f1 = mlab.figure()
e = mlab.get_engine()
self.assert_(e.current_scene is f1)
f2 = mlab.figure()
self.assert_(e.current_scene is f2)
mlab.figure(f1)
self.assert_(e.current_scene is f1)
# Test when specifying figure numbers
f1 = mlab.figure(3)
self.assert_(e.current_scene is f1)
f2 = mlab.figure(4)
self.assert_(e.current_scene is f2)
mlab.figure(3)
self.assert_(e.current_scene is f1)
# Test when specifying figure names
f1 = mlab.figure('Test 1')
self.assert_(e.current_scene is f1)
f2 = mlab.figure('Test 2')
self.assert_(e.current_scene is f2)
mlab.figure('Test 1')
self.assert_(e.current_scene is f1)
def plot_sln_mayavi(x, y, mesh, sln_values, colorbar=False):
"""
Plot a solution using mayavi.
Example:
>>> from numpy import array
>>> from femhub.plot import plot_sln_mayavi
>>> f = plot_sln_mayavi([0, 1, 1], [0, 0, 1], [1, 2, 3])
>>> f.savefig("a.png")
"""
from enthought.mayavi import mlab
#mlab.options.offscreen = True
mlab.clf()
#mlab.options.show_scalar_bar = False
z = [0] * len(x)
mlab.triangular_mesh(x, y, z, mesh, scalars=sln_values)
engine = mlab.get_engine()
image = engine.current_scene
image.scene.background = (1.0, 1.0, 1.0)
image.scene.foreground = (0.0, 0.0, 0.0)
if colorbar:
mlab.colorbar(orientation="vertical")
mlab.view(0, 0)
return mlab
def show(self, sln, show=True, lib="mayavi", notebook=None,
filename="scalar.png", **options):
"""
Shows the solution.
show ... should it actually plot the window? Set to False in tests.
lib .... which library to use for the plotting? either "mpl" or "mayavi"
notebook ... are we running inside Sage notebook? If True, just save
the image to a.png
filename ... the name of the filename if we are saving the image (e.g.
notebook == False)
Example:
>>> 1 + 1
2
>>> 1 + 2
3
"""
if notebook is None:
try:
from sagenb.misc.support import EMBEDDED_MODE
except ImportError:
EMBEDDED_MODE = False
notebook = EMBEDDED_MODE
self._lib = lib
self._notebook = notebook
if lib == "glut":
if self._glut_view is None:
from _hermes2d import ScalarView
self._glut_view = ScalarView(self._name)
self._glut_view.show(sln)
elif lib == "mpl":
plot_sln_mpl(sln, **options)
import pylab
if show:
if notebook:
pylab.savefig(filename)
else:
pylab.ion()
pylab.draw()
pylab.ioff()
elif lib == "mayavi":
plot_sln_mayavi(sln, notebook=notebook)
from enthought.mayavi import mlab
if show:
engine = mlab.get_engine()
image = engine.current_scene
image.scene.background = (1.0, 1.0, 1.0)
image.scene.foreground = (0.0, 0.0, 0.0)
#mlab.colorbar(orientation="vertical")
if notebook:
mlab.savefig(filename)
else:
mlab.show()
else:
raise NotImplementedError("Unknown library '%s'" % lib)
def tearDown(self):
# Check that the NullEngine is still the mlab engine
if not mlab.get_engine() is self.e:
raise AssertionError, \
"The NullEngine has been overridden"
engine_manager.current_engine = None
# Unregistering the engine, to avoid side-effects between tests
self.e.stop()
registry.unregister_engine(self.e)
def serve_udp(engine=None, port=9007, logto=sys.stdout):
"""Serve the `M2UDP` protocol using the given `engine` on the
specified `port` logging messages to given `logto` which is a
file-like object. This function will block till the service is
closed. There is no need to call `mlab.show()` after or before
this. The Mayavi UI will be fully responsive.
**Parameters**
:engine: Mayavi engine to use. If this is `None`,
`mlab.get_engine()` is used to find an appropriate engine.
:port: int: port to serve on.
:logto: file : File like object to log messages to. If this is
`None` it disables logging.
**Examples**
Here is a very simple example::
from enthought.mayavi import mlab
from enthought.mayavi.tools import server
mlab.test_plot3d()
server.serve_udp()
Test it like so::
import socket
s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
s.bind(('', 9008))
s.sendto('camera.azimuth(10)', ('', 9007))
**Warning**
Data sent is exec'd so this is a security hole.
"""
from enthought.mayavi import mlab
e = engine or mlab.get_engine()
# Setup the protocol with the right attributes.
proto = M2UDP()
proto.engine = e
proto.scene = e.current_scene.scene
proto.mlab = mlab
if logto is not None:
log.startLogging(logto)
log.msg('Serving Mayavi2 UDP server on port', port)
log.msg('Using Engine', e)
# Register the running wxApp.
reactor.registerWxApp(wx.GetApp())
# Listen on port 9007 using above protocol.
reactor.listenUDP(port, proto)
# Run the server + app. This will block.
reactor.run()
def serve_udp(engine=None, port=9007, logto=sys.stdout):
"""Serve the `M2UDP` protocol using the given `engine` on the
specified `port` logging messages to given `logto` which is a
file-like object. This function will block till the service is
closed. There is no need to call `mlab.show()` after or before
this. The Mayavi UI will be fully responsive.
**Parameters**
:engine: Mayavi engine to use. If this is `None`,
`mlab.get_engine()` is used to find an appropriate engine.
:port: int: port to serve on.
:logto: file : File like object to log messages to. If this is
`None` it disables logging.
**Examples**
Here is a very simple example::
from enthought.mayavi import mlab
from enthought.mayavi.tools import server
mlab.test_plot3d()
server.serve_udp()
Test it like so::
import socket
s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
s.bind(('', 9008))
s.sendto('camera.azimuth(10)', ('', 9007))
**Warning**
Data sent is exec'd so this is a security hole.
"""
from enthought.mayavi import mlab
e = engine or mlab.get_engine()
# Setup the protocol with the right attributes.
proto = M2UDP()
proto.engine = e
proto.scene = e.current_scene.scene
proto.mlab = mlab
if logto is not None:
log.startLogging(logto)
log.msg('Serving Mayavi2 UDP server on port', port)
log.msg('Using Engine', e)
# Register the running wxApp.
reactor.registerWxApp(wx.GetApp())
# Listen on port 9007 using above protocol.
reactor.listenUDP(port, proto)
# Run the server + app. This will block.
reactor.run()
def tearDown(self):
# Check that the NullEngine is still the mlab engine
if not mlab.get_engine() is self.e:
raise AssertionError, \
"The NullEngine has been overridden"
engine_manager.current_engine = None
# Unregistering the engine, to avoid side-effects between tests
self.e.stop()
registry.unregister_engine(self.e)
def tearDown(self):
# Check that the NullEngine was not set as the default mlab engine.
if not mlab.get_engine() is self._non_null_engine:
raise AssertionError, \
"The NullEngine has overridden the default one"
engine_manager.current_engine = None
# Unregistering all unused engines.
registry.unregister_engine(self._non_null_engine)
for engine in registry.engines.keys():
registry.unregister_engine(engine)
def view(src):
""" Open up a mayavi scene and display the dataset in it.
"""
from enthought.mayavi import mlab
mayavi = mlab.get_engine()
fig = mlab.figure(bgcolor=(1, 1, 1), fgcolor=(0, 0, 0),)
mayavi.add_source(src)
mlab.pipeline.surface(src, opacity=0.1)
mlab.pipeline.surface(mlab.pipeline.extract_edges(src),
color=(0, 0, 0), )
def close_scenes(self):
""" Closes all scenes for this render manager """
from enthought.mayavi import mlab
eng = mlab.get_engine()
try:
# Uncomment to activate again
#eng.close_scene(self.scene2d)
eng.close_scene(self.scene3d)
except Exception:
pass
def run_mlab_file(filename, image_file):
## XXX: Monkey-patch mlab.show, so that we keep control of the
## the mainloop
old_show = mlab.show
def my_show(func=None):
pass
mlab.show = my_show
mlab.clf()
e = mlab.get_engine()
e.close_scene(mlab.gcf())
execfile(filename, {'__name__': '__main__'})
mlab.savefig(image_file)
size = mlab.gcf().scene.get_size()
for scene in e.scenes:
e.close_scene(scene)
mlab.show = old_show
def view(src):
""" Open up a mayavi scene and display the dataset in it.
"""
from enthought.mayavi import mlab
mayavi = mlab.get_engine()
fig = mlab.figure(
bgcolor=(1, 1, 1),
fgcolor=(0, 0, 0),
)
mayavi.add_source(src)
mlab.pipeline.surface(src, opacity=0.1)
mlab.pipeline.surface(
mlab.pipeline.extract_edges(src),
color=(0, 0, 0),
)
def init(changes, ns):
for chset in changes[0:ns]:
seed = numpy.array([estimate[chset['new']]])
pnew = vis.plot_prism_mesh(seed, style='surface', xy2ne=True)
mlab.get_engine().scenes[0].children[-1].children[0].children[0].children[0].scalar_lut_manager.data_range = [0,1000]
neighbors = numpy.array([setden(e, chset['dens']) for e in [estimate[n] for n in chset['nn']]])
pnn = vis.plot_prism_mesh(neighbors, style='wireframe', xy2ne=True)
pnn.actor.property.color = neighborcolor
pnn.actor.property.line_width = 1
pos = 0
scale = 800
Z = numpy.reshape(data['value'] - changes[ns-1]['res'], dshape)
ct = mlab.contour_surf(X, Y, Z, contours=10, colormap='jet')
ct.contour.filled_contours = True
ct.actor.actor.position = (0,0,pos)
ct.actor.actor.scale = (1,1,scale)
def run_mlab_file(filename, image_file):
## XXX: Monkey-patch mlab.show, so that we keep control of the
## the mainloop
old_show = mlab.show
def my_show(func=None):
pass
mlab.show = my_show
mlab.clf()
e = mlab.get_engine()
e.close_scene(mlab.gcf())
execfile(filename, {'__name__': '__main__'})
mlab.savefig(image_file)
size = mlab.gcf().scene.get_size()
for scene in e.scenes:
e.close_scene(scene)
mlab.show = old_show
def show(self, sln, show=True, lib="mpl", notebook=False, filename="a.png",
**options):
"""
Shows the solution.
show ... should it actually plot the window? Set to False in tests.
lib .... which library to use for the plotting? either "mpl" or "mayavi"
notebook ... are we running inside Sage notebook? If True, just save
the image to a.png
filename ... the name of the filename if we are saving the image (e.g.
notebook == False)
"""
self._lib = lib
self._notebook = notebook
if lib == "mpl":
plot_sln_mpl(sln, **options)
import pylab
if show:
if notebook:
pylab.savefig(filename)
else:
pylab.ion()
pylab.draw()
pylab.ioff()
elif lib == "mayavi":
plot_sln_mayavi(sln, notebook=notebook)
from enthought.mayavi import mlab
if show:
engine = mlab.get_engine()
image = engine.current_scene
image.scene.background = (1.0, 1.0, 1.0)
image.scene.foreground = (0.0, 0.0, 0.0)
c = mlab.colorbar(orientation="vertical")
c.position = (0.000, 0.035)
if notebook:
mlab.savefig(filename)
else:
mlab.show()
else:
raise NotImplementedError("Unknown library '%s'" % lib)
def __init__(self, network, **traits):
super(RenderManager, self).__init__(**traits)
from enthought.mayavi import mlab
logger.info('Initalize RenderManager...')
# set the datasource manager
self.datasourcemanager = network.datasourcemanager
# getting mlab engine
self.engine = mlab.get_engine()
# store reference to managed network
self.network = network
# create the scene instances
self._create_scenes()
# use nice trackball camera interactor
# self.scene3d.scene.interactor.interactor_style = tvtk.InteractorStyleTrackballCamera()
# otherwise just use tvtk.InteractorStyleSwitch()
# create my node picker inclusive the NodePickHandler
self.nodepicker = NodePicker(renwin=self.scene3d.scene)
# add custom picker for the scene3d
self.scene3d.scene.picker = self.nodepicker
# adding observers to capture key events
self.scene3d.scene.interactor.add_observer('KeyPressEvent', self.nodepicker.key_pressed)
# add the callback function after a pick event
self.scene3d.scene.picker.pointpicker.add_observer('EndPickEvent', self._nodepicked_callback)
# initialize node_labels
self.node_labels = {}
logger.info('RenderManager created.')
def doit():
global s
global iter
if iter == 0:
print "plotting the triangular mesh..."
s = mlab.triangular_mesh(x, y, z, triangles, scalars=t)
print " done."
print "adjusting view..."
mlab.view(0, 0)
print " done."
else:
print "changing the source..."
# This doesn't work due to a bug in mayavi/VTK:
# http://github.com/certik/mhd-hermes/issues#issue/1
#s.mlab_source.reset(x=x, y=y, z=z, triangles=triangles, scalars=t)
# so until this is fixed, let's call triangular_mesh and delete the
# old mesh (this is slow but works):
scene = mlab.gcf().scene
scene.disable_render = True
s = mlab.triangular_mesh(x, y, z, triangles, scalars=t)
mlab.get_engine().scenes[0].children[:1] = []
scene.disable_render = False
print " done."
iter += 1
def doit():
global s
global iter
if iter == 0:
print "plotting the triangular mesh..."
s = mlab.triangular_mesh(x, y, z, triangles, scalars=t)
print " done."
print "adjusting view..."
mlab.view(0, 0)
print " done."
else:
print "changing the source..."
# This doesn't work due to a bug in mayavi/VTK:
# http://github.com/certik/mhd-hermes/issues#issue/1
#s.mlab_source.reset(x=x, y=y, z=z, triangles=triangles, scalars=t)
# so until this is fixed, let's call triangular_mesh and delete the
# old mesh (this is slow but works):
scene = mlab.gcf().scene
scene.disable_render = True
s = mlab.triangular_mesh(x, y, z, triangles, scalars=t)
mlab.get_engine().scenes[0].children[:1] = []
scene.disable_render = False
print " done."
iter += 1
def make_plots(plots,argd=None,figs=None,save=False,overwrite=True,showfigs=True):
"""
Generate plots and maybe save them.
:param plots: A comma-seperated string of plots to show
:param argd:
The dictionary to use to find the arguments of the plot function. If
None, global variables will be used.
:param figs:
A list of figure numbers to use for each of the figures in `plots`. If
None, the current figure will be used as the starting point.
:param str save:
A directory in which to save the plots. If False, they will not be
saved, if True, the current directory will be used.
:param bool overwrite:
If True and plots are being saved, any existing plot will be
overwritten. Otherwise, the figure will not be saved.
:parm bool showfigs:
If True, the figures will be shown (in whatever GUI is the correct one
for the type).
"""
import os,shutil,inspect,subprocess
if save is True:
save='.'
if isinstance(save,basestring) and not save.endswith(os.sep):
save+=os.sep
if plots is None:
plots = _plotreg.keys()
elif isinstance(plots,basestring):
if '*' in plots:
import re
plots = plots.replace('*','.*')
regex = re.compile(plots)
plots = [p for p in plot_names()[0] if regex.match(p)]
else:
plots = plots.split(',')
if figs is None:
figs = arange(len(plots))+1
if len(figs) != len(plots):
raise ValueError("plots don't match figs")
if argd is None:
argd = globals()
plotd={}
for p,fnum in zip(plots,figs):
if p not in _plotreg:
raise KeyError('plotname %s not found'%p)
plotd[p] = (_plotreg[p][0],fnum,_plotreg[p][1],_plotreg[p][2],_plotreg[p][3])
isinter = plt.isinteractive()
plt.ioff()
anympl = False
try:
for fname,(figf,fignum,figsize,ftype,tweakbbox) in plotd.iteritems():
print 'figure',fname
if 'mpl' in ftype:
anympl = True
if isinter:
plt.ion()
plt.close(fignum)
plt.figure(fignum,figsize=figsize)
plt.ioff()
elif 'mayavi' in ftype:
from enthought.mayavi import mlab as M
if len(M.get_engine().scenes) > 0:
M.gcf().parent.close_scene(M.gcf())
f=M.figure(fignum,size=figsize)
#this is buggy
#f.scene.set_size(figsize)
#M.clf()
else:
raise ValueError('unrecognized figtype')
argsp = inspect.getargspec(figf)
if argsp[2] is not None:
figf(**argd)
else:
args=[]
for arg in argsp[0]:
args.append(argd[arg])
figf(*args)
if save:
epsconv = False
if ftype=='mpltoeps':
epsconv = 'png'
savefunc = plt.savefig
saveexts = ['png']
elif ftype.startswith('mpl'):
savefunc = plt.savefig
saveexts = ftype[3:].strip()
if saveexts=='':
saveexts = ['eps','pdf']
else:
saveexts = saveexts.split(',')
elif ftype.startswith('mayavi'):
savefunc = M.savefig
saveexts = ftype[6:].strip()
if saveexts=='':
saveexts = ['png']
else:
saveexts = saveexts.split(',')
if 'eps' in saveexts:
saveexts.remove('eps')
if 'png' not in saveexts:
saveexts.append('png')
epsconv = 'png'
else:
raise ValueError('unrecognized figtype')
for saveext in saveexts:
fn = '%s%s.%s'%(save,fname,saveext)
epsfns = None
if not overwrite and os.path.exists(fn):
print fn,'exists, skipping (use -o at command line to overwrite)'
else:
print 'saving',fn
savefunc(fn)
if saveext == epsconv:
epsfns = (fn,'%s%s.%s'%(save,fname,'eps'))
if epsfns is not None:
from os import system
fn,epsfn = epsfns
print 'converting',fn,'to',epsfn
retcode = subprocess.call('convert %s %s'%(fn,epsfn),shell=True)
if retcode is not 0:
raise ValueError('convert failed to convert %s to %s'%(fn,epsfn))
if tweakbbox is not None:
print 'updating eps bounding box on',epsfn,'to',tweakbbox
with open(epsfn+'.tmpwrite','w') as fw:
with open(epsfn,'r') as fr:
for l in fr:
if 'BoundingBox' in l and 'Page' not in l:
newline = l.split(':')[0]+(': %s %s %s %s\n'%tweakbbox)
fw.write(newline)
else:
fw.write(l)
shutil.move(epsfn+'.tmpwrite',epsfn)
finally:
if isinter:
plt.ion()
if showfigs and anympl:
plt.draw()
def serve_tcp(engine=None, port=8007, logto=sys.stdout, max_connect=1):
"""Serve the `M2TCP` protocol using the given `engine` on the
specified `port` logging messages to given `logto` which is a
file-like object. This function will block till the service is
closed. There is no need to call `mlab.show()` after or before
this. The Mayavi UI will be fully responsive.
**Parameters**
:engine: Mayavi engine to use. If this is `None`,
`mlab.get_engine()` is used to find an appropriate engine.
:port: int: port to serve on.
:logto: file: File like object to log messages to. If this is
`None` it disables logging.
:max_connect: int: Maximum number of simultaneous connections to
support.
**Examples**
Here is a very simple example::
from enthought.mayavi import mlab
from enthought.mayavi.tools import server
mlab.test_plot3d()
server.serve_tcp()
The TCP server will listen on port 8007 by default in the above.
Any data sent to the server is simply exec'd, meaning you can do
pretty much anything you want. The `engine`, `scene`, `camera` and
`mlab` are all available and can be used. For example after running
the above you can do this::
$ telnet localhost 8007
Trying 127.0.0.1...
Connected to localhost.
Escape character is '^]'.
scene.camera.azimuth(45)
mlab.clf()
mlab.test_contour3d()
scene.camera.zoom(1.5)
**Warning**
Data sent is exec'd so this is a security hole.
"""
from enthought.mayavi import mlab
e = engine or mlab.get_engine()
# Setup the factory with the right attributes.
factory = Factory()
factory.protocol = M2TCP
factory.maxConnect = max_connect
factory.numConnect = 0
factory.engine = e
factory.scene = e.current_scene.scene
factory.mlab = mlab
if logto is not None:
log.startLogging(logto)
log.msg('Serving Mayavi2 TCP server on port', port)
log.msg('Using Engine', e)
# Register the running wxApp.
reactor.registerWxApp(wx.GetApp())
# Listen on port 9007 using above protocol.
reactor.listenTCP(port, factory)
# Run the server + app. This will block.
reactor.run()
height = 0
for area in sorted(regions.keys()):
pulses = regions[area]
if len(pulses) == 0 or area < 280 or area > 300:
continue
values = [crh.get_value(p) for p in pulses]
height_diff = max(values) - min(values)
value_maxes.append(height_diff)
centre = height + height_diff / 2.0
pulse_values = np.zeros_like(img)
for p in pulses:
crh.set_array(pulse_values, p, crh.get_value(p))
y, x = np.where(pulse_values)
s = pulse_values[y, x]
mlab.barchart(x,
y, [height + centre] * len(s),
s,
opacity=1.0,
scale_factor=1.5)
height += height_diff + 0.5
scene = mlab.get_engine().scenes[0]
scene.scene.parallel_projection = True
mlab.show()
def close():
"""Close the scene."""
f = mlab.gcf()
e = mlab.get_engine()
v = e.get_viewer(f)
v.close()
def close():
"""Close the scene."""
f = mlab.gcf()
e = mlab.get_engine()
e.window.close()
def serve_tcp(engine=None, port=8007, logto=sys.stdout, max_connect=1):
"""Serve the `M2TCP` protocol using the given `engine` on the
specified `port` logging messages to given `logto` which is a
file-like object. This function will block till the service is
closed. There is no need to call `mlab.show()` after or before
this. The Mayavi UI will be fully responsive.
**Parameters**
:engine: Mayavi engine to use. If this is `None`,
`mlab.get_engine()` is used to find an appropriate engine.
:port: int: port to serve on.
:logto: file: File like object to log messages to. If this is
`None` it disables logging.
:max_connect: int: Maximum number of simultaneous connections to
support.
**Examples**
Here is a very simple example::
from enthought.mayavi import mlab
from enthought.mayavi.tools import server
mlab.test_plot3d()
server.serve_tcp()
The TCP server will listen on port 8007 by default in the above.
Any data sent to the server is simply exec'd, meaning you can do
pretty much anything you want. The `engine`, `scene`, `camera` and
`mlab` are all available and can be used. For example after running
the above you can do this::
$ telnet localhost 8007
Trying 127.0.0.1...
Connected to localhost.
Escape character is '^]'.
scene.camera.azimuth(45)
mlab.clf()
mlab.test_contour3d()
scene.camera.zoom(1.5)
**Warning**
Data sent is exec'd so this is a security hole.
"""
from enthought.mayavi import mlab
e = engine or mlab.get_engine()
# Setup the factory with the right attributes.
factory = Factory()
factory.protocol = M2TCP
factory.maxConnect = max_connect
factory.numConnect = 0
factory.engine = e
factory.scene = e.current_scene.scene
factory.mlab = mlab
if logto is not None:
log.startLogging(logto)
log.msg('Serving Mayavi2 TCP server on port', port)
log.msg('Using Engine', e)
# Register the running wxApp.
reactor.registerWxApp(wx.GetApp())
# Listen on port 9007 using above protocol.
reactor.listenTCP(port, factory)
# Run the server + app. This will block.
reactor.run()
def close():
"""Close the scene."""
f = mlab.gcf()
e = mlab.get_engine()
v = e.get_viewer(f)
v.close()
with open("res.pickle") as f:
res = pickle.load(f)
with open("seeds.pickle") as f:
seeds = pickle.load(f)
with open("model.pickle") as f:
model = pickle.load(f)
extent = view.extent
ranges = view.ranges
scene = mlab.figure(size=view.size)
scene.scene.background = (1, 1, 1)
p = vis.plot_prism_mesh(res, style='surface', xy2ne=True)
p.actor.property.line_width = 2
mlab.get_engine().scenes[0].children[-1].children[0].children[0].children[0].scalar_lut_manager.data_range = [0,1200]
p = vis.plot_prism_mesh(seeds, style='surface', xy2ne=True)
p.actor.property.line_width = 2
mlab.get_engine().scenes[0].children[-1].children[0].children[0].children[0].scalar_lut_manager.data_range = [0,1200]
p = vis.plot_prism_mesh(model, style='surface', xy2ne=True)
p.actor.property.line_width = 2
p = vis.plot_prism_mesh(mesh.vfilter(model,1100,1201), style='wireframe', xy2ne=True)
p.actor.property.color = (0,0,0)
p.actor.property.line_width = 3
mlab.outline(color=(0,0,0), extent=extent)
a = mlab.axes(p, nb_labels=5, extent=extent, ranges=ranges, color=(0,0,0))
from gpaw import * basename = 'CO' # load nc binary file and get calculator atoms, calc = restart(basename + '.gpw') # write atomic positions to xyz-file write(basename + '.xyz', atoms) # loop over all wfs and write their cube files nbands = calc.get_number_of_bands() wf = calc.get_pseudo_wave_function(band=0) from enthought.mayavi import mlab #mlab.figure(1, bgcolor=(0, 0, 0), size=(350, 350)) mlab.clf() data = wf source = mlab.pipeline.scalar_field(data) mlab.view(132, 54, 45, [21, 20, 21.5]) engine = mlab.get_engine() from enthought.mayavi.modules.scalar_cut_plane import ScalarCutPlane scalar_cut_plane = ScalarCutPlane() engine.add_module(scalar_cut_plane, obj=None) scene = engine.scenes[0] scene.scene.render() mlab.show()
def _engine_default(self):
return m2_mlab.get_engine()
def _engine_default(self):
return m2_mlab.get_engine()
def chcolor():
mlab.get_engine().scenes[0].children[-3].children[0].children[0].children[0].scalar_lut_manager.data_range = [0,1000]
points[:, 2],
faces,
color=(1, 1, 0),
opacity=0.3)
# show one cortical surface
mlab.triangular_mesh(lh_points[:, 0],
lh_points[:, 1],
lh_points[:, 2],
lh_faces,
color=(0.7, ) * 3)
# show dipole as small cones
dipoles = mlab.quiver3d(pos[:, 0],
pos[:, 1],
pos[:, 2],
ori[:, 0],
ori[:, 1],
ori[:, 2],
opacity=1.,
scale_factor=4e-4,
scalars=time,
mode='cone',
colormap='RdBu')
# revert colormap
dipoles.module_manager.scalar_lut_manager.reverse_lut = True
mlab.colorbar(dipoles, title='Dipole fit time (ms)')
# proper 3D orientation
mlab.get_engine().scenes[0].scene.x_plus_view()
def plot_map(map, affine, cut_coords=None, anat=None, anat_affine=None,
figure=None, axes=None, title=None, threshold=None,
annotate=True, draw_cross=True,
do3d=False, threshold_3d=None,
view_3d=(38.5, 70.5, 300, (-2.7, -12, 9.1)),
black_bg=False,
**kwargs):
""" Plot three cuts of a given activation map (Frontal, Axial, and Lateral)
Parameters
----------
map : 3D ndarray
The activation map, as a 3D image.
affine : 4x4 ndarray
The affine matrix going from image voxel space to MNI space.
cut_coords: 3-tuple of floats or None
The MNI coordinates of the point where the cut is performed, in
MNI coordinates and order.
If None is given, the cut point is calculated automaticaly.
anat : 3D ndarray or False, optional
The anatomical image to be used as a background. If None, the
MNI152 T1 1mm template is used. If False, no anat is displayed.
anat_affine : 4x4 ndarray, optional
The affine matrix going from the anatomical image voxel space to
MNI space. This parameter is not used when the default
anatomical is used, but it is compulsory when using an
explicite anatomical image.
figure : integer or matplotlib figure, optional
Matplotlib figure used or its number. If None is given, a
new figure is created.
axes : matplotlib axes or 4 tuple of float: (xmin, xmax, ymin, ymin), optional
The axes, or the coordinates, in matplotlib figure space,
of the axes used to display the plot. If None, the complete
figure is used.
title : string, optional
The title dispayed on the figure.
threshold : a number, None, or 'auto'
If None is given, the maps are not thresholded.
If a number is given, it is used to threshold the maps:
values below the threshold are plotted as transparent. If
auto is given, the threshold is determined magically by
analysis of the map.
annotate: boolean, optional
If annotate is True, positions and left/right annotation
are added to the plot.
draw_cross: boolean, optional
If draw_cross is True, a cross is drawn on the plot to
indicate the cut plosition.
do3d: {True, False or 'interactive'}, optional
If True, Mayavi is used to plot a 3D view of the
map in addition to the slicing. If 'interactive', the
3D visualization is displayed in an additional interactive
window.
threshold_3d:
The threshold to use for the 3D view (if any). Defaults to
the same threshold as that used for the 2D view.
view_3d: tuple,
The view used to take the screenshot: azimuth, elevation,
distance and focalpoint, see the docstring of mlab.view.
black_bg: boolean, optional
If True, the background of the image is set to be black. If
you whish to save figures with a black background, you
will need to pass "facecolor='k', edgecolor='k'" to pylab's
savefig.
kwargs: extra keyword arguments, optional
Extra keyword arguments passed to pylab.imshow
Notes
-----
Arrays should be passed in numpy convention: (x, y, z)
ordered.
Use masked arrays to create transparency:
import numpy as np
map = np.ma.masked_less(map, 0.5)
plot_map(map, affine)
"""
map, affine = _xyz_order(map, affine)
nan_mask = np.isnan(np.asarray(map))
if np.any(nan_mask):
map = map.copy()
map[nan_mask] = 0
# Deal with automatic settings of plot parameters
if threshold == 'auto':
# Threshold epsilon above a percentile value, to be sure that some
# voxels are indeed threshold
threshold = _fast_abs_percentile(map) + 1e-5
if cut_coords is None:
x_map, y_map, z_map = find_cut_coords(map,
activation_threshold=threshold)
cut_coords = coord_transform(x_map, y_map, z_map, affine)
if do3d:
try:
from enthought.mayavi import version
if not int(version.version[0]) > 2:
raise ImportError
except ImportError:
warnings.warn('Mayavi > 3.x not installed, plotting only 2D')
do3d = False
# Make sure that we have a figure
if not isinstance(figure, Figure):
if do3d:
size = (10, 2.6)
else:
size = (6.6, 2.6)
facecolor = 'k' if black_bg else 'w'
figure = pl.figure(figure, figsize=size, facecolor=facecolor)
else:
if isinstance(axes, Axes):
assert axes.figure is figure, ("The axes passed are not "
"in the figure")
# Use Mayavi for the 3D plotting
if do3d:
from .maps_3d import plot_map_3d, m2screenshot
from enthought.tvtk.api import tvtk
version = tvtk.Version()
offscreen = True
if (version.vtk_major_version, version.vtk_minor_version) < (5, 2):
offscreen = False
if do3d == 'interactive':
offscreen = False
cmap = kwargs.get('cmap', pl.cm.cmap_d[pl.rcParams['image.cmap']])
# Computing vmin and vmax is costly in time, and is needed
# later, so we compute them now, and store them for future
# use
vmin = kwargs.get('vmin', map.min())
kwargs['vmin'] = vmin
vmax = kwargs.get('vmax', map.max())
kwargs['vmax'] = vmax
from enthought.mayavi import mlab
if threshold_3d is None:
threshold_3d = threshold
plot_map_3d(np.asarray(map), affine, cut_coords=cut_coords,
anat=anat, anat_affine=anat_affine,
offscreen=offscreen, cmap=cmap,
threshold=threshold_3d,
view=view_3d,
vmin=vmin, vmax=vmax)
ax = figure.add_axes((0.001, 0, 0.29, 1))
ax.axis('off')
m2screenshot(mpl_axes=ax)
axes = (0.3, 0, .7, 1.)
if offscreen:
# Clean up, so that the offscreen engine doesn't become the
# default
mlab.clf()
engine = mlab.get_engine()
from enthought.mayavi.core.registry import registry
for key, value in registry.engines.iteritems():
if value is engine:
registry.engines.pop(key)
break
if threshold:
map = np.ma.masked_inside(map, -threshold, threshold, copy=False)
ortho_slicer = plot_anat(anat, anat_affine, cut_coords=cut_coords,
figure=figure, axes=axes, title=title,
annotate=annotate, draw_cross=draw_cross,
black_bg=black_bg)
ortho_slicer.plot_map(map, affine, **kwargs)
return ortho_slicer
"""Example of how to generate 3D ellipsoids in mayavi, using glyphs.
Adapted from Gael Varoquaux"""
from enthought.tvtk.api import tvtk
from enthought.mayavi import mlab
#from enthought.mayavi.sources.vtk_data_source import VTKDataSource
import numpy as np
point = np.array([0, 0, 0])
tensor = np.array([20, 0, 0, 0, 20, 0, 0, 0, 20])
engine = mlab.get_engine()
engine.start()
scene = engine.new_scene()
scene.scene.disable_render = True # for speed
glyphs = []
for i in range(10):
data = tvtk.PolyData(points=[point])
data.point_data.tensors = [tensor]
data.point_data.tensors.name = 'some_name'
data.point_data.scalars = [i]
#data.point_data.scalars.name = 'some_other_name'
#mlab.clf()
#src = VTKDataSource(data=data)
#e = mlab.get_engine()
#e.add_source(src)
glyph = mlab.pipeline.tensor_glyph(data)
regions = lulu.decompose(img)
value_maxes = []
height = 0
for area in sorted(regions.keys()):
pulses = regions[area]
if len(pulses) == 0 or area < 280 or area > 300:
continue
values = [crh.get_value(p) for p in pulses]
height_diff = max(values) - min(values)
value_maxes.append(height_diff)
centre = height + height_diff / 2.0
pulse_values = np.zeros_like(img)
for p in pulses:
crh.set_array(pulse_values, p, crh.get_value(p))
y, x = np.where(pulse_values)
s = pulse_values[y, x]
mlab.barchart(x, y, [height + centre] * len(s), s,
opacity=1.0, scale_factor=1.5)
height += height_diff + 0.5
scene = mlab.get_engine().scenes[0]
scene.scene.parallel_projection = True
mlab.show()
try:
from enthought.mayavi import mlab
except:
from mayavi import mlab
lh_points = src[0]['rr']
lh_faces = src[0]['use_tris']
mlab.figure(size=(600, 600), bgcolor=(1, 1, 1), fgcolor=(0, 0, 0))
# show brain surface after proper coordinate system transformation
points = brain_surface['rr']
faces = brain_surface['tris']
coord_trans = fwd['mri_head_t']['trans']
points = np.dot(coord_trans[:3,:3], points.T).T + coord_trans[:3,-1]
mlab.triangular_mesh(points[:, 0], points[:, 1], points[:, 2],
faces, color=(1, 1, 0), opacity=0.3)
# show one cortical surface
mlab.triangular_mesh(lh_points[:, 0], lh_points[:, 1], lh_points[:, 2],
lh_faces, color=(0.7, ) * 3)
# show dipole as small cones
dipoles = mlab.quiver3d(pos[:,0], pos[:,1], pos[:,2],
ori[:,0], ori[:,1], ori[:,2],
opacity=1., scale_factor=4e-4, scalars=time,
mode='cone')
mlab.colorbar(dipoles, title='Dipole fit time (ms)')
# proper 3D orientation
mlab.get_engine().scenes[0].scene.x_plus_view()
from fatiando import mesh, vis, utils
with open("mesh.pickle") as f:
res = pickle.load(f)
x1, x2 = 0, 3000
y1, y2 = 0, 3000
z1, z2 = 0, 3000
extent = [x1, x2, y1, y2, -z2, -z1]
# Plot the adjusted model plus the skeleton of the synthetic model
fig = mlab.figure(size=(600, 730))
fig.scene.background = (1, 1, 1)
p = vis.plot_prism_mesh(res, style='surface')
mlab.get_engine().scenes[0].children[-1].children[0].children[0].children[
0].scalar_lut_manager.lut_mode = "Greys"
scene = fig
scene.scene.camera.position = [
5617.6246210610589, 9378.6744914189112, 1832.0425527256102
]
scene.scene.camera.focal_point = [
1435.8921050117997, 1598.1461572098237, -1715.9026272606379
]
scene.scene.camera.view_angle = 30.0
scene.scene.camera.view_up = [
-0.18883236854009863, -0.3216128720649955, 0.92785101019163696
]
scene.scene.camera.clipping_range = [4531.9434654515926, 15755.396726380868]
scene.scene.camera.compute_view_plane_normal()
scene.scene.render()
from fatiando import mesh, vis, utils
with open("mesh.pickle") as f:
res = pickle.load(f)
x1, x2 = 0, 3000
y1, y2 = 0, 3000
z1, z2 = 0, 3000
extent = [x1, x2, y1, y2, -z2, -z1]
# Plot the adjusted model plus the skeleton of the synthetic model
fig = mlab.figure(size=(600,730))
fig.scene.background = (1, 1, 1)
p = vis.plot_prism_mesh(mesh.vfilter(res,900,2001), style='surface', opacity=1)
mlab.get_engine().scenes[0].children[-1].children[0].children[0].children[0].scalar_lut_manager.data_range = [0,2000]
#a = mlab.axes(p, nb_labels=0, extent=extent, color=(0,0,0))
#a.label_text_property.color = (0,0,0)
#a.title_text_property.color = (0,0,0)
#a.axes.label_format = ""
#a.axes.x_label, a.axes.y_label, a.axes.z_label = "", "", ""
#a.property.line_width = 1
mlab.outline(p, extent=extent, color=(0,0,0))
scene = fig
scene.scene.camera.position = [5617.6246210610589, 9378.6744914189112, 1832.0425527256102]
scene.scene.camera.focal_point = [1435.8921050117997, 1598.1461572098237, -1715.9026272606379]
scene.scene.camera.view_angle = 30.0
scene.scene.camera.view_up = [-0.18883236854009863, -0.3216128720649955, 0.92785101019163696]
import cPickle as pickle
from enthought.mayavi import mlab
from fatiando import mesh, vis, utils
with open("mesh.pickle") as f:
res = pickle.load(f)
x1, x2 = 0, 3000
y1, y2 = 0, 3000
z1, z2 = 0, 3000
extent = [x1, x2, y1, y2, -z2, -z1]
# Plot the adjusted model plus the skeleton of the synthetic model
fig = mlab.figure(size=(600,730))
fig.scene.background = (1, 1, 1)
p = vis.plot_prism_mesh(res, style='surface')
mlab.get_engine().scenes[0].children[-1].children[0].children[0].children[0].scalar_lut_manager.lut_mode = "Greys"
scene = fig
scene.scene.camera.position = [5617.6246210610589, 9378.6744914189112, 1832.0425527256102]
scene.scene.camera.focal_point = [1435.8921050117997, 1598.1461572098237, -1715.9026272606379]
scene.scene.camera.view_angle = 30.0
scene.scene.camera.view_up = [-0.18883236854009863, -0.3216128720649955, 0.92785101019163696]
scene.scene.camera.clipping_range = [4531.9434654515926, 15755.396726380868]
scene.scene.camera.compute_view_plane_normal()
scene.scene.render()
mlab.show()
