def _train(self, dataset):
"""Determine the projection matrix onto the components from
a 2D samples x feature data matrix.
"""
white_param = {}
# more features than samples? -> rank deficiancy
# if not tranposing the data, MDP has to do SVD prior to ICA
if dataset.samples.shape[1] > dataset.samples.shape[0] \
and not self._transpose:
white_param['svd'] = True
if self._algorithm == 'fastica':
node = FastICANode(white_parm=white_param,
dtype=dataset.samples.dtype)
elif self._algorithm == 'cubica':
node = CuBICANode(white_parm=white_param,
dtype=dataset.samples.dtype)
else:
raise NotImplementedError
# node.train(dataset.samples.T)
# self._proj = dataset.samples.T * N.asmatrix(node.get_projmatrix())
# print self._proj.shape
# else:
node.train(dataset.samples)
self._proj = N.asmatrix(node.get_projmatrix())
self._recon = N.asmatrix(node.get_recmatrix())
