Hello Yaroslav, Thank you for your response! I am new to MVPA and so I am not clear how else I should correctly define 'chunks' for event related data. Here's the scenario:
I am trying to work out how to correctly code the chunks for: 1) An event related data with conditions within each chunk (10) presented 3.5 seconds in duration 2) and volume samples of 2 seconds duration Thus a Nifti dataset with its number of samples (1315) greater than its number of chunks (609). I am having a problem coding this in because pymvpa likes both number of sample and number of chunks to be equal. How do you suggest I code in the chunks for this dataset? Also I have managed to compound all Nifti images across all runs into one 4D data. In trying to move forward, I loaded the data as event related but did not explicitly specify the number of chunks. However, when I try to detrend , zscore or classify the data I get: Memory Error The script for reference is at http://gist.github.com/367912 Any help will be greatly appreciated! Thank you. Temi On Thu, Apr 15, 2010 at 10:22 PM, Temilade Adelore <[email protected]>wrote: > Hello Yaroslav, > > Thank you for responding. > Here the link to my code on gist <http://gist.github.com/367912> > > At line 93 in the script I get the following error: > > File "/usr/lib/pymodules/python2.6/matplotlib/image.py", line 294, in > set_data > raise TypeError("Invalid dimensions for image data") > TypeError: Invalid dimensions for image data > > At line 116 in the script I also get the following error: > > File "/usr/lib/pymodules/python2.6/mvpa/clfs/base.py", line 369, in train > if dataset.nfeatures == 0 or dataset.nsamples == 0: > > AttributeError: 'NoneType' object has no attribute 'nfeatures' > > However when I type in following in the shell I get: > > >>> fmri_src_ev.nfeatures > 405504 > >>> fmri_src_ev.nsamples > 44 > > And so it is clear that my dataset (fmir_src_ev) has the nfeatures and > nsamples attribute but this is not being recognized by the sensitivity > analyzer/classifier. > > I am new to pymvpa and so I understand that I might be doing something > wrong. > Any help or suggestions would be greatly appreciated. > > Thanks, > Temi Adelore > > > > On Thu, Apr 8, 2010 at 4:55 PM, Temilade Adelore <[email protected]>wrote: > >> Hello Experts, >> >> when I use run the following code: >> >> clf = LinearCSVMC() >> >> sclf = SplitClassifier(clf, NFoldSplitter(), >> enable_states=['confusion', 'training_confusion']) >> >> sensitivities = \ >> sclf.getSensitivityAnalyzer(combiner=None, >> >> slave_combiner=None)(fmri_src_ev) >> >> I get the error: AttributeError: 'NoneType' object has no attribute >> 'nfeatures' >> >> However when I type in "fmri_src_ev.nfeatures" in the terminal >> I get back: "405504" >> >> And so I am confused as to what might be the problem. >> >> Pls help!! Any feedback would be greatly appreciated. >> >> Thanks, Temi >> >> >> >> >> On Thu, Apr 8, 2010 at 4:22 PM, Temilade Adelore >> <[email protected]>wrote: >> >>> Hello Experts, >>> I am trying to load samples into pymvpa using the following command: >>> >>> pre_fmri_src = NiftiDataset(samples=[fmri_src1, fmri_src2, fmri_src3, >>> fmri_src4, fmri_src5, fmri_src6, fmri_src7, fmri_src8, >>> fmri_src9,fmri_src10], labels=4, chunks=10, enforce_dim=None, mask=None) >>> >>> Each of the 10 samples correspond to a 4D NiftiImage instance. >>> I would like each sample to be a chunk, hence creating 10 chunks of data. >>> However, when I run the command above I get the following error: >>> >>> ValueError: Input volumes contain variable number of dimensions: [(136, >>> 33, 64, 64), (136, 33, 64, 64), (136, 33, 64, 64), (136, 33, 64, 64), (136, >>> 33, 64, 64), (136, 33, 64, 64), (136, 33, 64, 64), (136, 33, 64, 64), (136, >>> 33, 64, 64), (91, 33, 64, 64)] >>> >>> I realize that the last chunk has a different dimension ( a different >>> number of time points) however I do not see why should give me an error. >>> Is there anyway I can work around this? All suggestions are much >>> appreciated. >>> Thanks, >>> Temi Adelore >>> >> >> >
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