In this part, we will go back to the previous examples of this tutorial and see how to do the same with a python script. The data for the examples in this section are the same : ftp://ftp.cea.fr/pub/dsv/anatomist/data/demo_data.zip.
The following examples use the general API functions that are available in both direct and socket implementations.
To run the following examples, we will use an interactive python shell IPython. It is much more practical than the classic python shell because it offers useful features like automatic completion. This program is available in the BrainVISA package with all other executable programs in the bin directory of the BrainVISA package directory. IPython should be run with the option -q4thread, which runs a Qt event loop, needed for the graphical interface.
<brainvisa_installation_directory>/bin/ipython -q4thread
First of all, we need to import anatomist API module. Here, in a Python shell, the default implementation is the direct one (Python bindings).
Then we can create an instance of Anatomist class.
import anatomist.api as ana a=ana.Anatomist()
In this example, we will put the path to the data_for_anatomist directory in a variable named src. We will use this variable in all the next examples. We will also load a python module named os which has useful functions to handle files and paths.
import os src="<path to data_for_anatomist directory>" # Load an object t1mri=a.loadObject( os.path.join(src, "data_for_anatomist", "subject01", "subject01.nii") )
We open an axial window and add the volume loaded in the previous example in this window.
# view an object
axial=a.createWindow("Axial")
axial.addObjects(t1mri)
See the corresponding actions in the graphical interface.
When opening a new window, it is possible to change its initial position and size with the geometry parameter. This parameter is a list of 4 values (in pixels) : [x, y, width, height].
# customizing the position and size of a new window : the windows will be displayed at position (100, 150) with a size of (300, 300)
w=a.createWindow("Axial", geometry=[100,150, 300, 300 ])
We create 4 views in the same windows block and add the image in each views.
# view an object in a 4 views block
block=a.createWindowsBlock(2) # 2 columns
w1=a.createWindow("Axial", block=block)
w2=a.createWindow("Sagittal", block=block)
w3=a.createWindow("Coronal", block=block)
w4=a.createWindow("3D", block=block)
t1mri.addInWindows( [w1, w2, w3, w4] )
# show the cursor position print "\nCursor at : ", a.linkCursorLastClickedPosition() # move the linked cursor w1.moveLinkedCursor([150,100,60]) print "\nCursor at : ", a.linkCursorLastClickedPosition()
This method enables to change the camera parameters of a window. In this example, we change the zoom.
axial.camera(zoom=2)You can also change the rotation of the view by changing the view_quaternion parameters. The rotation is represented by a quaternion which is a vector with 4 parameters. As the interpretation of quaternions is not easy at first time, it is useful to look at the current value of the parameter in a window with the method getInfos().
axial.getInfos() axial.camera(view_quaternion=[0.9, -0.2, -0.2, 0.3])It is possible to change the orientation of the slice plan with the parameter slice_quaternion.
axial.camera(slice_quaternion=[0.3, 0.3, 0, 0.9])
# view header
browser=a.createWindow("Browser")
browser.addObjects(t1mri)
# color palette
palette=a.getPalette("Blue-Green-Red-Yellow")
t1mri.setPalette(palette)
# view meshes
lwhite=a.loadObject( os.path.join(src, "data_for_anatomist", "subject01", "subject01_Lwhite.mesh") )
rwhite=a.loadObject( os.path.join(src, "data_for_anatomist", "subject01", "subject01_Rwhite.mesh") )
w3d=a.createWindow("3D")
w3d.addObjects([lwhite, rwhite])
# superimposing a.addObjects(t1mri, w3d)
# mesh material head=a.loadObject(os.path.join(src, "data_for_anatomist", "subject01", "subject01_head.mesh")) head.addInWindows(w3d) material=a.Material(diffuse=[0.8, 0.6, 0.6, 0.5]) head.setMaterial(material)
brain_mask=a.loadObject(os.path.join(src, "data_for_anatomist", "subject01", "brain_subject01.nii"))
brain_mask.setPalette(a.getPalette("GREEN-ufusion"))
t1mri.setPalette("B-W LINEAR")
# fusion 2D
fusion2d=a.fusionObjects([brain_mask, t1mri], "Fusion2DMethod")
axial=a.createWindow("Axial")
axial.addObjects(fusion2d)
# params of the fusion : linear on non null
a.execute("Fusion2DParams", object=fusion2d, mode="linear_on_defined", rate=0.4)
It is possible to do different types of fusion using the same method fusionObjects and changing the list of objects and the type of fusion.
t1mri_s2=a.loadObject( os.path.join(src, "data_for_anatomist", "subject02", "sujet02.ima") )
t1mri_s2.setPalette("Blue-White")
fusion2d=a.fusionObjects([t1mri, t1mri_s2], "Fusion2DMethod")
r1=a.createReferential()
r2=a.createReferential()
cr=a.centralRef
t1mri.assignReferential(r1)
t1mri_s2.assignReferential(r2)
# load a transformation
a.loadTransformation( os.path.join(src, "data_for_anatomist", "subject01", "RawT1-subject01_default_acquisition_TO_Talairach-ACPC.trm"), r1, cr)
a.loadTransformation( os.path.join(src, "data_for_anatomist", "subject02", "RawT1-sujet02_200810_TO_Talairach-ACPC.trm"), r2, cr)
axial=a.createWindow("Axial")
axial.addObjects(fusion2d)
lwhite.assignReferential(r1) axial.addObjects(lwhite)
map=a.loadObject( os.path.join(src, "data_for_anatomist", "subject01", "Audio-Video_T_map.nii" ) )
map.setPalette("tvalues100-200-100")
t1mri.loadReferentialFromHeader()
map.loadReferentialFromHeader()
fusion_map=a.fusionObjects([map, t1mri], "Fusion2DMethod")
axial=a.createWindow("Axial")
axial.addObjects(fusion_map)
a.execute("Fusion2DParams", object=fusion_map, mode="linear_on_defined", rate=0.5)
graph=a.loadObject( os.path.join(src, "data_for_anatomist", "roi", "basal_ganglia.arg") ) w = a.createWindow( '3D' ) w.addObjects( graph, add_graph_nodes=True )
A lot of commands that can be processed by Anatomist are encapsulted in Anatomist class methods. But some commands, less commonly used are not available through specific methods. Nevertheless, they can be called through a generic method Anatomist.execute(< command name >, **parameters).
The list of available commands is listed in the following page : http://brainvisa.info/doc/anatomist/html/fr/programmation/commands.html.
In the previous examples, we use this method to call Fusion2DParams command which is not encapsulated in a specific method.
a.execute("Fusion2DParams", object=fusion_map, mode="linear_on_defined", rate=0.5)