ds = ds[keep_idx]
_default_options = {
'estimator': [
[('clf1', cluster.KMeans())],
[('clf1', cluster.AgglomerativeClustering())],
],
'sample_slicer__runs':[[run] for run in np.unique(ds.sa.runs)],
'estimator__clf1__n_clusters': range(2, 10),
}
_default_config = {
'prepro': ['sample_slicer'],
'analysis': Clustering
}
errors = []
iterator = AnalysisIterator(_default_options, AnalysisConfigurator, config_kwargs=_default_config)
for conf in iterator:
kwargs = conf._get_kwargs()
a = AnalysisPipeline(conf, name="states+alessio").fit(ds, **kwargs)
a.save(path="/media/robbis/DATA/meg/hcp/")
###############################
