Пример #1
0
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)
Пример #2
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 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()
Пример #3
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    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()
Пример #4
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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()
Пример #5
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    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)
Пример #6
0
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)
Пример #7
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    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)
Пример #8
0
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
Пример #9
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    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)
Пример #10
0
 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)
Пример #11
0
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()
Пример #12
0
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()
Пример #13
0
 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)
Пример #14
0
 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)
Пример #15
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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), )
Пример #16
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 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
Пример #17
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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
Пример #18
0
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),
    )
Пример #19
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)
Пример #20
0
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
Пример #21
0
    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)
Пример #22
0
    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.')
Пример #23
0
 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
Пример #24
0
 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
Пример #25
0
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()
Пример #26
0
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()
Пример #27
0
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()
Пример #28
0
def close():
    """Close the scene."""
    f = mlab.gcf()
    e = mlab.get_engine()
    v = e.get_viewer(f)
    v.close()
Пример #29
0
def close():
    """Close the scene."""
    f = mlab.gcf()
    e = mlab.get_engine()
    e.window.close()
Пример #30
0
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()
Пример #31
0
def close():
    """Close the scene."""
    f = mlab.gcf()
    e = mlab.get_engine()
    v = e.get_viewer(f)
    v.close()
Пример #32
0
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))
Пример #33
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()
Пример #34
0
 def _engine_default(self):
     return m2_mlab.get_engine()
Пример #35
0
 def _engine_default(self):
     return m2_mlab.get_engine()
Пример #36
0
def chcolor():    
    mlab.get_engine().scenes[0].children[-3].children[0].children[0].children[0].scalar_lut_manager.data_range = [0,1000]
Пример #37
0
                     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()
Пример #38
0
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
Пример #39
0
"""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)
Пример #40
0
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()
Пример #41
0
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()
Пример #42
0
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()
Пример #43
0
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]
Пример #44
0
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()