replaced freesurfer mri_surf2surf command with nipype's SurfaceTransform #2

binarybottle · 2012-05-27T00:02:38Z

Before merging, for this to work, nipype need to include an --sval-annot argument for accepting a source annotation file (which should replace the "source_file") and --tval argument for accepting a target (output) annotation file.

…Transform

satra · 2012-05-27T02:18:10Z

will include sval-annot soon

binarybottle · 2012-05-29T13:42:04Z

i reinstalled nipype on my mac and on my linux box, and source_annot_file is available on the mac but not on linux. the only difference in setup i can discern is that the linux required me to do a sudo python setup.py install.

TraitError: Cannot set the undefined 'source_annot_file' attribute of a 'SurfaceTransformInputSpec' object.

satra · 2012-05-29T14:35:49Z

you'll have to find out which version of nipype you are using via nipype.version or nipype.get_info() and the location and contents of the utils.py file in freesurfer.

binarybottle · 2012-05-29T15:07:34Z

i'm using the newest version:

In [4]: nipype.version
Out[4]: '0.5.3'

In [3]: nipype.get_info()
Out[3]:
{'commit_hash': '8b8ba0e',
'commit_source': 'archive substitution',
'networkx_version': '1.6',
'nibabel_version': '1.1.0',
'numpy_version': '1.6.1',
'pkg_path': '/usr/lib/pymodules/python2.7/nipype',
'scipy_version': '0.9.0',
'sys_executable': '/usr/bin/python',
'sys_platform': 'linux2',
'sys_version': '2.7.3 (default, Apr 20 2012, 22:39:59) \n[GCC 4.6.3]',
'traits_version': '4.0.0'}

i have fs v5.1 installed, but i can't find a utils.py within
/usr/local/freesurfer/

On Tue, May 29, 2012 at 10:35 AM, Satrajit Ghosh <
reply@reply.github.com

wrote:

you'll have to find out which version of nipype you are using via
nipype.version or nipype.get_info() and the location and contents of
the utils.py file in freesurfer.

Reply to this email directly or view it on GitHub:
#2 (comment)

satra · 2012-05-29T15:26:19Z

that is not the latest version. if you are running of the latest master, then the following is the latest version.


In [1]: import nipype
Installed version: 0.6.0.g83c33ea-dev
Current stable version: 0.5.3
Current dev version: 0.6.0.g83c33ea-dev

In [2]: nipype.get_info()
Out[2]: 
{'commit_hash': '83c33ea',
 'commit_source': 'repository',
 'networkx_version': '1.6',
 'nibabel_version': '1.3.0dev',
 'numpy_version': '1.6.1',
 'pkg_path': '/software/nipy-repo/nipype/nipype',
 'scipy_version': '0.10.0',
 'sys_executable': '/software/virtualenvs.EPD/7.2/devpype/bin/python',
 'sys_platform': 'darwin',
 'sys_version': '2.7.2 |CUSTOM| (default, Sep  7 2011, 16:31:15) \n[GCC 4.0.1 (Apple Inc. build 5493)]',
 'traits_version': '4.1.0'}

In [3]: nipype.__version__
Out[3]: '0.6.0.g83c33ea-dev'

binarybottle · 2012-05-29T15:30:16Z

odd. should i be doing something other than?:

git clone git@github.com:nipy/nipype.git

cheers,
@rno

On Tue, May 29, 2012 at 11:26 AM, Satrajit Ghosh <
reply@reply.github.com

wrote:

that is not the latest version. if you are running of the latest master,
then the following is the latest version.


In [1]: import nipype
Installed version: 0.6.0.g83c33ea-dev
Current stable version: 0.5.3
Current dev version: 0.6.0.g83c33ea-dev

In [2]: nipype.get_info()
Out[2]:
{'commit_hash': '83c33ea',
 'commit_source': 'repository',
 'networkx_version': '1.6',
 'nibabel_version': '1.3.0dev',
 'numpy_version': '1.6.1',
 'pkg_path': '/software/nipy-repo/nipype/nipype',
 'scipy_version': '0.10.0',
 'sys_executable': '/software/virtualenvs.EPD/7.2/devpype/bin/python',
 'sys_platform': 'darwin',
 'sys_version': '2.7.2 |CUSTOM| (default, Sep  7 2011, 16:31:15) \n[GCC
4.0.1 (Apple Inc. build 5493)]',
 'traits_version': '4.1.0'}

In [3]: nipype.__version__
Out[3]: '0.6.0.g83c33ea-dev'

Reply to this email directly or view it on GitHub:
#2 (comment)

satra · 2012-05-29T15:37:36Z

a clone will give you the latest version. but perhaps your environment is setup in a way that is different between the user and the superuser?

just do:

sudo python -c "import nipype; print nipype.version"
and
python -c "import nipype; print nipype.version"

if they are different you know something is amiss. you might then want to check which python you are using!

cheers,

satra

binarybottle · 2012-05-29T15:39:25Z

they are both using 0.5.3

cheers,
@rno

On Tue, May 29, 2012 at 11:37 AM, Satrajit Ghosh <
reply@reply.github.com

wrote:

a clone will give you the latest version. but perhaps your environment is
setup in a way that is different between the user and the superuser?

just do:

sudo python -c "import nipype; print nipype.version"
and
python -c "import nipype; print nipype.version"

if they are different you know something is amiss. you might then want to
check which python you are using!

cheers,

satra

Reply to this email directly or view it on GitHub:
#2 (comment)

satra · 2012-05-29T15:44:58Z

then you don't have the latest version. check: nipype/nipype/info.py in your source

binarybottle · 2012-05-29T15:51:20Z

ha! i found out what my problem was. i tried running python setup.py
install first w/o, then w/ "sudo" -- now i've got 0.6.0...! thank you,
satra!

cheers,
@rno

binarybottle · 2012-05-29T15:55:22Z

but it depends on where i am:

arno@boggle:~/Software/nipype$ python -c "import nipype; print
nipype.version"

nipype/init.py:53: UserWarning: Running the tests from the install
directory may trigger some failures
warnings.warn('Running the tests from the install directory may '
0.6.0.g83c33ea-dev

arno@boggle:~/Documents/Projects/mindboggle/mindboggle$ python -c "import
nipype; print nipype.version"
0.5.3

should i set an explicit path in bash_profile?

cheers,
@rno

satra · 2012-05-29T15:57:47Z

that's still an incorrect installation then! or you are using two different python executables! or they have different sys.paths.

binarybottle · 2012-05-29T16:12:29Z

well, at least the python executables are the same (python --version -> Python 2.7.3)

Rather than run the connect_points() on the anchor points, extract_endpoints() from the resulting skeleton, and run connect_points() on the endpoints, implement a very fast approach: 1. threshold likelihood values in a fold/sulcus 2. skeletonize(), retaining anchor points 3. extract endpoints of skeleton that are also anchor points 4. run connect_points() on endpoints and skeletonize results Preliminary anchor point skeletons and endpoint skeletons are the same, but retaining #2 for the following reasons (from yrjo): 1. The likelihood function can have flat areas, so that it doesn't reduce to a single point when thresholding 2. The likelihood function can have areas of low values where the fundus is 'cut' 3. The likelihood function is about to change with the learning approach, and the endpoint selection has to be able to perform with different kinds of likelihood functions, even if they don't produce nice skeletons from thresholding.

Rather than run the connect_points() on the anchor points, extract_endpoints() from the resulting skeleton, and run connect_points() on the endpoints, implement a very fast approach: 1. threshold likelihood values in a fold/sulcus 2. skeletonize(), retaining anchor points 3. extract endpoints of skeleton that are also anchor points 4. run connect_points() on endpoints and skeletonize results Preliminary anchor point skeletons and endpoint skeletons are the same, but retaining #2 for the following reasons (from yrjo): 1. The likelihood function can have flat areas, so that it doesn't reduce to a single point when thresholding 2. The likelihood function can have areas of low values where the fundus is 'cut' 3. The likelihood function is about to change with the learning approach, and the endpoint selection has to be able to perform with different kinds of likelihood functions, even if they don't produce nice skeletons from thresholding. Former-commit-id: cf35a4c

Rather than run the connect_points() on the anchor points, extract_endpoints() from the resulting skeleton, and run connect_points() on the endpoints, implement a very fast approach: 1. threshold likelihood values in a fold/sulcus 2. skeletonize(), retaining anchor points 3. extract endpoints of skeleton that are also anchor points 4. run connect_points() on endpoints and skeletonize results Preliminary anchor point skeletons and endpoint skeletons are the same, but retaining #2 for the following reasons (from yrjo): 1. The likelihood function can have flat areas, so that it doesn't reduce to a single point when thresholding 2. The likelihood function can have areas of low values where the fundus is 'cut' 3. The likelihood function is about to change with the learning approach, and the endpoint selection has to be able to perform with different kinds of likelihood functions, even if they don't produce nice skeletons from thresholding. Former-commit-id: 977bf71

Rather than run the connect_points() on the anchor points, extract_endpoints() from the resulting skeleton, and run connect_points() on the endpoints, implement a very fast approach: 1. threshold likelihood values in a fold/sulcus 2. skeletonize(), retaining anchor points 3. extract endpoints of skeleton that are also anchor points 4. run connect_points() on endpoints and skeletonize results Preliminary anchor point skeletons and endpoint skeletons are the same, but retaining #2 for the following reasons (from yrjo): 1. The likelihood function can have flat areas, so that it doesn't reduce to a single point when thresholding 2. The likelihood function can have areas of low values where the fundus is 'cut' 3. The likelihood function is about to change with the learning approach, and the endpoint selection has to be able to perform with different kinds of likelihood functions, even if they don't produce nice skeletons from thresholding. Former-commit-id: ceaef26

Processed data

small fixes

replaced freesurfer mri_surf2surf command with nipype-wrapped Surface…

21ece6d

…Transform

binarybottle merged commit 21ece6d into master May 27, 2012

This was referenced May 12, 2013

Feature-based labeling #8

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Transform VTK coordinates to voxel index coordinates #13

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Data and doc string Examples #7

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binarybottle mentioned this pull request Sep 12, 2013

Zernike descriptors are HUGE #25

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binarybottle pushed a commit that referenced this pull request Mar 30, 2017

Merge pull request #2 from shnizzedy/cd_and_untar

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mgxd pushed a commit to mgxd/mindboggle that referenced this pull request Oct 29, 2018

Merge pull request nipy#2 from mgxd/enh/antsupdate

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replaced freesurfer mri_surf2surf command with nipype's SurfaceTransform #2

replaced freesurfer mri_surf2surf command with nipype's SurfaceTransform #2

binarybottle commented May 27, 2012

satra commented May 27, 2012

binarybottle commented May 29, 2012

satra commented May 29, 2012

binarybottle commented May 29, 2012

satra commented May 29, 2012

binarybottle commented May 29, 2012

satra commented May 29, 2012

binarybottle commented May 29, 2012

satra commented May 29, 2012

binarybottle commented May 29, 2012

binarybottle commented May 29, 2012

satra commented May 29, 2012

binarybottle commented May 29, 2012

replaced freesurfer mri_surf2surf command with nipype's SurfaceTransform #2

replaced freesurfer mri_surf2surf command with nipype's SurfaceTransform #2

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binarybottle commented May 27, 2012

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