Dear all,
I'm very happy to announce new release of nipype - the pipelining
framework that allows you to combine FSL, SPM, FreeSurfer, Nipy and
other neuroimaging packages. Among other changes (see the full list
below) this release brings support for MCR-based SPM, Analyze to Nifti
conversion and SPM thresholding procedures.
You can get the newest version of nipype from
https://github.com/nipy/nipype/zipball/0.3.4 and soon from NeuroDebian
repository ( http://http://neuro.debian.net/ ). Full documentation
with examples can be found at
http://nipy.sourceforge.net/nipype/documentation.html
Changes since 0.3.3:
* API: hash values for float use a string conversion up to the 10th
decimal place.
* API: Iterables in output path will always be generated as
_var1_val1_var2_val2 pairs
* ENH: Added support to nipy: GLM fit, contrast estimation and
calculating mask from EPI
* ENH: Added support for manipulating surface files in Freesurfer:
- projecting volume images onto the surface
- smoothing along the surface
- transforming a surface image from one subject to another
- using tksurfer to save pictures of the surface
* ENH: Added support for flash processing using FreeSurfer
* ENH: Added support for flirt matrix in BBRegister
* ENH: Added support for FSL convert_xfm
* ENH: hashes can be updated again without rerunning all nodes.
* ENH: Added multiple regression design for FSL
* ENH: Added SPM based Analyze to Nifti converter
* ENH: Added increased support for PyXNAT
* ENH: Added support for MCR-based binary version of SPM
* ENH: Added SPM node for calculating various threshold statistics
* ENH: Added distance and dissimilarity measurements
* BF: Diffusion toolkit gets installed
* BF: Changed FNIRT interface to accept flexible lists (rather than 4-tuples)
on all options specific to different subsampling levels
On behalf of the nipype team,
Chris Gorgolewski
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