Eelbrain

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* Tools for generating colors for categories (see :ref:`ref-plotting`).
* Plots now all largely respect matplotlib rc-parameters (see
`Customizing Matplotlib <http://matplotlib.org/users/customizing.html>`_).
* Fixed an issue in the :mod:`testnd` module that could affect permutation based
p-values when multiprocessing was used.

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* :class:`Factor` API change: The ``rep`` argument was renamed to ``repeat``.
* T-values for regression coefficients through :meth:`NDVar.ols_t`.
* :class:`pipeline.MneExperiment`: subject name patterns and eog_sns are
now handled automatically.
* :class:`~plot.uts.UTSStat` and :class:`~plot.uv.Barplot` plots can use pooled
error for variability estimates (on by default for related measures designs,
can be turned off using the ``pool_error`` argument).

- API: for consistency, the argument to specify the kind of error to plot
changed to ``error`` in both plots.

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* A new GUI application controls plots as well as the epoch selection GUI (see
notes in the reference sections on :ref:`ref-plotting` and :ref:`ref-guis`).
* Randomization/Monte Carlo tests now seed the random state to make results replicable.

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* New recipes (outdated).

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* The :mod:`eelbrain.lab` and :mod:`eelbrain.eellab` modules are deprecated.
Everything can now me imported from :mod:`eelbrain` directly.

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* Optimized ANOVA evaluation, support for unbalanced fixed effects models.
* `rpy2 <http://rpy.sourceforge.net>`_ interaction: :meth:`Dataset.from_r` to
create a :class:`Dataset` from an R Data Frame, and :meth:`Dataset.to_r` to
cerate an R Data Frame from a :class:`Dataset`.