![]() Now look at the texture on the mesh (inflated or not) in Anatomist. write ( tex, 'subject01_Lwhite_semiinflated_texture.tex' ) read ( 'data_for_anatomist/subject01/subject01.nii' ) tex = aims. read ( 'subject01_Lwhite_semiinflated_sh' ) vol = aims. updateNormals ()įrom soma import aims import numpy as np mesh = aims. write ( mesh, 'saucer.gii' ) # automatically calculate normals mesh. vstack (( pol, pol2 ))) # write result aims. header () = 'a message in the header' vert = mesh. AimsTimeSurface ( 3 ) # a mesh has a header mesh. # build a flying saucer mesh from soma import aims import numpy mesh = aims. A cleaner alternative, especially if no write access is allowed on this data directory, is to make a symbolic link to the data_for_anatomist subdirectory To use the examples directly, users should go to the directory where this archive was uncompressed, and then run ipython from this directory. The data for the examples in this section can be downloaded here. There is obviously an overhead to call C++ from python, but once in the C++ layer, it is C++ execution speed.Ī few examples of how to use and manipulate the main data structures will be shown here. As pyaims is actually C++ code called from python, it is still fast to execute complex algorithms.It can be used interactively in a python interactive shell.Scripts are more flexible, can be modified on-the-fly, etc.Writing python scripts and programs is much easier and faster than C++: there is no fastidious and long compilation step. ![]() This has many advantages compared to pure C++: This means that the C++ classes and functions can be used from python. This tutorial should work with Python 2 (2.6 or higher), and is also compatible with Python 3 (if pyaims is compiled in python3 mode).ĪIMS is a C++ library, but has python language bindings: PyAIMS. PyAims tutorial : programming with AIMS in Python language ¶
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