nibabel problem

[michaelf500]

Hello

I'm running meica on a Windows 10 machine, with a bash shell under Windows Subsystem for Linux, with command meica.py -d MJF_180_ME_1.nii,MJF_180_ME_2.nii,MJF_180_ME_3.nii -e 14.8,37.98,61.16 --tpattern=seq-z --prefix MJF_180_multiecho

I get the following error message:

++ 3dZcat: AFNI version=AFNI_19.1.25 (Jun 25 2019) [64-bit] ++ output dataset: ./basestack.nii.gz -- T2* Map Component for ME-ICA v3.1 beta1 -- ++ Loading Data Traceback (most recent call last): File "/home/michael/meica/me-ica/meica.libs/t2smap.py", line 335, in catd = cat2echos(catim.get_data(),ne) File "/home/michael/meica/me-ica/meica.libs/nibabel/spatialimages.py", line 341, in get_data return np.asanyarray(self._data) File "/home/michael/.local/lib/python2.7/site-packages/numpy/core/numeric.py", line 591, in asanyarray return array(a, dtype, copy=False, order=order, subok=True) File "/home/michael/meica/me-ica/meica.libs/nibabel/arrayproxy.py", line 55, in array self._data = self._read_data() File "/home/michael/meica/me-ica/meica.libs/nibabel/arrayproxy.py", line 60, in _read_data data = self.header.data_from_fileobj(fileobj) File "/home/michael/meica/me-ica/meica.libs/nibabel/analyze.py", line 486, in data_from_fileobj data = self.raw_data_from_fileobj(fileobj) File "/home/michael/meica/me-ica/meica.libs/nibabel/analyze.py", line 458, in raw_data_from_fileobj return array_from_file(shape, dtype, fileobj, offset) File "/home/michael/meica/me-ica/meica.libs/nibabel/volumeutils.py", line 502, in array_from_file arr.flags.writeable = True ValueError: cannot set WRITEABLE flag to True of this array

Any suggestion appreciated.

Michael

[benoitberanger]

Hello Michael,

I just had the same problem not so long ago, and the answer was in the old MEICA repo on bitbucket. Try to downgrade Numpy into version 1.10, it worked for me. If you need help to install a specific version of python package : https://stackoverflow.com/questions/5226311/installing-specific-package-versions-with-pip

By the way, if you don't know what is tedana, you should take a look : https://github.com/ME-ICA/tedana. This repo is more "futur proof" for multi-echo denoising.

Best, Benoît

[michaelf500]

Hello Benoît

Thanks, going to numpy 1.10 solved the problem. Thanks also for the tip off about tedana, I'll have a look.

Best wishes

Michael