[pymvpa] SL on an artificial dataset

[Matthias Ekman]

Thanks Michael,

I guess I am missing something very obvious here. With the following 
code I get the error below (it doesn't seem to be related to 'mycoord').

from sklearn.datasets import make_classification
from mvpa2.suite import *
X,y = make_classification(n_samples=50, n_features=630, n_classes=2)
ds = Dataset(X)
ds.targets = y
ds.chunks = np.arange(50)
cv = CrossValidation(LinearCSVMC(C=1), NFoldPartitioner())
# print cv(ds) # same error
ds.fa['mycoord'] = np.arange(ds.nfeatures)
sl = sphere_searchlight(cv, radius=2, space='mycoord',nproc=1)
sl_map = sl(ds)


In [3]: %run tmp.py
ERROR: An unexpected error occurred while tokenizing input
The following traceback may be corrupted or invalid
The error message is: ('EOF in multi-line statement', (100, 0))

ERROR: An unexpected error occurred while tokenizing input
The following traceback may be corrupted or invalid
The error message is: ('EOF in multi-line statement', (163, 0))

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)

/vol/biopsy/me/tmp.py in <module>()
      11 ds.fa['mycoord'] = np.arange(ds.nfeatures)
      12 sl = sphere_searchlight(cv, radius=2, space='mycoord',nproc=1)
---> 13 sl_map = sl(ds)
      14
      15

/vol/biopsy/me/apps/PyMVPA/mvpa2/base/learner.pyc in __call__(self, ds)
     235                                    "used and auto training is 
disabled."
     236                                    % str(self))
--> 237         return super(Learner, self).__call__(ds)
     238
     239

/vol/biopsy/me/apps/PyMVPA/mvpa2/base/node.pyc in __call__(self, ds)
      78
      79         self._precall(ds)
---> 80         result = self._call(ds)
      81         result = self._postcall(ds, result)
      82

/vol/biopsy/me/apps/PyMVPA/mvpa2/measures/searchlight.pyc in _call(self, 
dataset)
     123
     124         # pass to subclass

--> 125         results, roi_sizes = self._sl_call(dataset, roi_ids, nproc)
     126
     127         if not roi_sizes is None:

/vol/biopsy/me/apps/PyMVPA/mvpa2/measures/searchlight.pyc in 
_sl_call(self, dataset, roi_ids, nproc)
     239             # otherwise collect the results in a list

     240             results, roi_sizes = \
--> 241                     self._proc_block(roi_ids, dataset, 
self.__datameasure)
     242
     243         if __debug__ and 'SLC' in debug.active:

/vol/biopsy/me/apps/PyMVPA/mvpa2/measures/searchlight.pyc in 
_proc_block(self, block, ds, measure)
     291
     292             # compute the datameasure and store in results

--> 293             results.append(measure(roi))
     294
     295             # store the size of the roi dataset


/vol/biopsy/me/apps/PyMVPA/mvpa2/base/learner.pyc in __call__(self, ds)
     235                                    "used and auto training is 
disabled."
     236                                    % str(self))
--> 237         return super(Learner, self).__call__(ds)
     238
     239

/vol/biopsy/me/apps/PyMVPA/mvpa2/base/node.pyc in __call__(self, ds)
      78
      79         self._precall(ds)
---> 80         result = self._call(ds)
      81         result = self._postcall(ds, result)
      82

/vol/biopsy/me/apps/PyMVPA/mvpa2/measures/base.pyc in _call(self, ds)
     465         # always untrain to wipe out previous stats

     466         self.untrain()
--> 467         return super(CrossValidation, self)._call(ds)
     468
     469

/vol/biopsy/me/apps/PyMVPA/mvpa2/measures/base.pyc in _call(self, ds)
     290         # run the node an all generated datasets

     291         results = []
--> 292         for i, sds in enumerate(generator.generate(ds)):
     293             if __debug__:
     294                 debug('REPM', "%d-th iteration of %s on %s",

/vol/biopsy/me/apps/PyMVPA/mvpa2/generators/partition.pyc in 
generate(self, ds)
     111     def generate(self, ds):
     112         # for each split

--> 113         cfgs = self.get_partition_specs(ds)
     114         n_cfgs = len(cfgs)
     115

/vol/biopsy/me/apps/PyMVPA/mvpa2/generators/partition.pyc in 
get_partition_specs(self, ds)
     186         """
     187         # list (#splits) of lists (#partitions)

--> 188         cfgs = self._get_partition_specs(ds.sa[self.__attr].unique)
     189
     190         # Select just some splits if desired


KeyError: 'chunks'