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* :class:`LabelAxis`: each row/column has a unique name and label table (with optional meta-data)
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* :class:`SeriesAxis`: each row/column is a timepoint, which increases monotonically
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- All of these classes are derived from the :class:` Axis` class.
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+ All of these classes are derived from the Axis class.
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After loading a CIFTI-2 file a tuple of axes describing the rows and columns can be obtained
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from the :meth:`.cifti2.Cifti2Header.get_axis` method on the header object
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(e.g. ``nibabel.load(<filename>).header.get_axis()``). Inversely, a new
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- :class:`.cifti2.Cifti2Header` object can be created from existing :class:` Axis` objects
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+ :class:`.cifti2.Cifti2Header` object can be created from existing Axis objects
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using the :meth:`.cifti2.Cifti2Header.from_axes` factory method.
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- CIFTI-2 :class:` Axis` objects of the same type can be concatenated using the '+'-operator.
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+ CIFTI-2 Axis objects of the same type can be concatenated using the '+'-operator.
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Numpy indexing also works on axes
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(except for SeriesAxis objects, which have to remain monotonically increasing or decreasing).
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Creating new CIFTI-2 axes
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-----------------------
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- New :class:` Axis` objects can be constructed by providing a description for what is contained
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- in each row/column of the described tensor. For each :class:` Axis` sub-class this descriptor is:
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+ New Axis objects can be constructed by providing a description for what is contained
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+ in each row/column of the described tensor. For each Axis sub-class this descriptor is:
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* :class:`BrainModelAxis`: a CIFTI-2 structure name and a voxel or vertex index
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* :class:`ParcelsAxis`: a name and a sequence of voxel and vertex indices
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