Dear PyMVPA experts,
I successfully ran through the following code using Python 2.6.2+PyMVPA
2.2.0:
from mvpa2.tutorial_suite import *
ds=get_raw_haxby2001_data(roi='vt')
part=NFoldPartitioner()
sl=sphere_gnbsearchlight(GNB(),part,postproc=mean_sample())
map=sl(ds)
However, the same code with a new partitioner led to errors:
part=ChainNode([NFoldPartitioner(),
Balancer(limit='partitions',apply_selection=True)],
space='partitions')
The error messages were:
Traceback (most recent call last):
File "debug.py", line 9, in <module>
map=sl(ds)
File "/usr/local/lib/python2.6/dist-packages/mvpa2/base/learner.py", line
239, in __call__
return super(Learner, self).__call__(ds)
File "/usr/local/lib/python2.6/dist-packages/mvpa2/base/node.py", line
96, in __call__
result = self._call(ds)
File
"/usr/local/lib/python2.6/dist-packages/mvpa2/measures/searchlight.py",
line 141, in _call
results = self._sl_call(dataset, roi_ids, nproc)
File
"/usr/local/lib/python2.6/dist-packages/mvpa2/measures/adhocsearchlightbase.py",
line 354, in _sl_call
if not (np.all(p.sa[targets_sa_name].value == labels)):
ValueError: shape mismatch: objects cannot be broadcast to a single shape
Any ideas about what's wrong here?
Thanks!
Tren
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