[pymvpa] Antwort: Re: Antwort: Re: Loading normalized data with 'get_model_bold_dataset' fails
lydia.hellrung at econ.uzh.ch
lydia.hellrung at econ.uzh.ch
Fri Jun 2 15:04:29 UTC 2017
No, they all have 195 volumes, but the geometry information is apparently
saved differently.
The output says:
./sub002/BOLD/task001_run001/bold_irbadvols.nii.gz float32 [112, 112,
27, 195] 1.96x1.96x4.06x2.00 #exts: 1 sform
./sub002/BOLD/task001_run001/bold_iwrbadvols.nii.gz float32 [105, 127,
105, 195] 1.50x1.50x1.50x0.00 #exts: 1
while the first file could be loaded, the second one not. Could that be an
issue? And in case, what would be needed?
If I check the headers, it says qform_code = 1 for first file and
qform_code = 4 for second one.
Thanks
Lydia
-----------------------------------------------------------------------------------------
Dr. rer. nat. Lydia Hellrung, Dipl.-Inf.
University of Zurich
Department of Economics
Blümlisaplstraße 10
8006 Zurich, Switzerland
phone: + 41 (0) 44 634 4838
e-mail: lydia.hellrung at econ.uzh.ch
-----------------------------------------------------------------------------------------
Von: Yaroslav Halchenko <debian at onerussian.com>
An: pkg-exppsy-pymvpa at lists.alioth.debian.org
Datum: 02/06/2017 16:42
Betreff: Re: [pymvpa] Antwort: Re: Loading normalized data with
'get_model_bold_dataset' fails
Gesendet von: "Pkg-ExpPsy-PyMVPA" <pkg-exppsy-pymvpa-bounces
+lydia.hellrung=econ.uzh.ch at lists.alioth.debian.org>
On Fri, 02 Jun 2017, lydia.hellrung at econ.uzh.ch wrote:
> Dear Yaroslav,
> there is the full traceback:
> /usr/lib/python2.7/dist-packages/nipy/modalities/fmri/hemodynamic_models.py:176:
> RuntimeWarning: divide by zero encountered in double_scalars
> min_onset) * oversampling) + 1
> Traceback (most recent call last):
> File "load.py2", line 31, in <module>
> time_attr='time_coords', condition_attr='condition')
> File
> "/usr/lib/python2.7/dist-packages/mvpa2/datasets/sources/openfmri.py",
> line 656, in get_model_bold_dataset
> 'mask', 'add_fa', 'add_sa')]))
> File
"/usr/lib/python2.7/dist-packages/mvpa2/datasets/eventrelated.py",
> line 574, in fit_event_hrf_model
> **design_kwargs)
> File
>
"/usr/lib/python2.7/dist-packages/nipy/modalities/fmri/design_matrix.py",
> line 433, in make_dmtx
> paradigm, hrf_model.lower(), frametimes, fir_delays, min_onset)
> File
>
"/usr/lib/python2.7/dist-packages/nipy/modalities/fmri/design_matrix.py",
> line 200, in _convolve_regressors
> min_onset=min_onset)
> File
>
"/usr/lib/python2.7/dist-packages/nipy/modalities/fmri/hemodynamic_models.py",
> line 360, in compute_regressor
> exp_condition, frametimes, oversampling, min_onset)
> File
>
"/usr/lib/python2.7/dist-packages/nipy/modalities/fmri/hemodynamic_models.py",
> line 180, in _sample_condition
> n_hr)
> File "/usr/lib/python2.7/dist-packages/numpy/core/function_base.py",
> line 76, in linspace
> num = int(num)
> OverflowError: cannot convert float infinity to integer
could it be that some "bold" volume in your dataset has only a single
volume?
That would make n =1 in
frametimes.max() * (1 + 1. / (n - 1))
thus inf ...
you can use smth like
find -iname *bold*nii.gz | xargs nib-ls
to quickly review all the bold volumes to have 4th dimension non-degenerate
--
Yaroslav O. Halchenko
Center for Open Neuroscience http://centerforopenneuroscience.org
Dartmouth College, 419 Moore Hall, Hinman Box 6207, Hanover, NH 03755
Phone: +1 (603) 646-9834 Fax: +1 (603) 646-1419
WWW: http://www.linkedin.com/in/yarik
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