Msmbuilder

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API Changes
~~~~~~~~~~~

New Features
~~~~~~~~~~~~
- Added functions to compute error bars for transition probabilities to account for
finite sampling, and sample transition matrices from these error distributions (i.e.
bootstrapping). Located in msmbuilder.msm.validation.transmat_errorbar.

Improvements
~~~~~~~~~~~~

---------------------

We're pleased to annoounce the release of MSMBuilder 3.8. This release
features updates and improvements to contact featurizers, kernel tICA, HMMs,
and preprocessing. There are also some bugfixes and API hygiene improements.
We recommend all users upgrade to MSMBuilder 3.8.

API Changes
~~~~~~~~~~~

New Features
~~~~~~~~~~~~

- ``ContactFeaturizer`` now lets you use a soft_min option for closest
contact distances.

Improvements
~~~~~~~~~~~~

- The ``stride`` parameter in ``KernelTICA`` now works as intended to
automatically generate a set of landmark points (gh-972).
- The ``contacts`` parameter in ``CommonContactFeaturizer`` now performs as the
contacts method in regular ``ContactFeaturizer`` albeit after validating all
the contacts.
- ``GaussianHMM`` and ``VonMisesHMM`` are now compatible with
``sklearn.pipeline.Pipeline`` workflows (gh-980).
- ``msmbuilder.preprocessing`` is now compatible with
``sklearn.pipeline.Pipeline`` workflows (gh-987).
- Fixed error in pickling HMMs (gh-996).

-----------------------

We're pleased to announce the release of MSMBuilder 3.7. This release
introduces several new featurizers that can handle multiple sequences or
multiple chains within a topology file. There are also some bugfixes and
API hygiene improvements. We recommend all users upgrade to MSMBuilder 3.7.

API Changes
~~~~~~~~~~~

- ``TrajFeatureUnion`` and ``SubsetFeatureUnion`` have been removed due to
incompatibilities with the ``scikit-learn`` API.

New Features
~~~~~~~~~~~~

- ``KSparseTICA`` lets you specify the number of non-zero entries, ``k``
rather than a regularization strength (gh-916).
- ``BootStrapMarkovStateModel`` optionally saves all the models that it
generates (gh-919).
- ``tICA`` supports commute mapping (see 10.1021/acs.jctc.6b00762)
(gh-925).
- ``CommonContactFeaturizer`` featurizes different trajectories with
different topologies using a common set of inter-residue contacts
(gh-876).
- ``msmbuilder.tpt.mfpt.mfpts`` can now compute distributions of MFPTs, accounting
for the model error due to finite sampling.
- Three new featurization schemes for protein-ligand trajectories are
now available: ``LigandContactFeaturizer``,
``BinaryLigandContactFeaturizer``, and ``LigandRMSDFeaturizer`` (gh-883).

Improvements
~~~~~~~~~~~~

- Compatibility with scikit-learn 0.18 (gh-915).
- ``FeatureSelector`` feature order is deterministic (gh-920).
- ``SASAFeaturizer`` supports the ``describe_features`` method (gh-913).
- All ``LandmarkAgglomerative`` clusterers now have ``cluster_centers_`` except
when ``metric = rmsd`` (gh-958)

-------------------------

We're pleased to announce the release of MSMBuilder 3.6. This release
introduces project templating and a whole host of new ``sklearn`` estimators.
There are also some bugfixes and API hygiene improvements. We recommend all
users upgrade to MSMBuilder 3.6.

API Changes
~~~~~~~~~~~

- ``version.short_version`` is now 3.y instead of 3.y.z (gh-829).
- ``weighted_transform`` is no longer supported in tICA methods (gh-807). Please
used ``kinetic_mapping``.
- The cached filenames and formats for DoubleWell, QuadWell,
and MullerPotential example datasets have changed. The API through
``msmbuilder.example_datasets`` is still the same, but the data may
be re-generated instead of using a cached version from a previous installation
of MSMBuilder (gh-854).
- The alias for Ward clustering has been removed. Modelers should now use
``LandmarkAgglomerative(linkage='ward')`` (gh-874). Ward clustering is also
available in ``AgglomerativeClustering``, but without a prediction algorithm.

New Features
~~~~~~~~~~~~

- ``Butterworth``, ``DoubleEWMA``, ``StandardScaler``, ``RobustScaler`` are
available via the command line (gh-895).
- ``BinaryContactFeaturizer`` featurizes a trajectory into a
boolean array corresponding to whether each residue-residue
distance is below a cutoff (gh-798).
- ``LogisticContactFeaturizer`` produces a logistic transform
of residue-residue distances about a center distance (798).
- ``FactorAnalysis``, ``FastICA``, and ``KernelPCA`` are available in the
``decomposition`` module (gh-807).
- ``Butterworth``, ``EWMA``, and ``DoubleEWMA`` are available in the
``preprocessing`` module (gh-818).
- We encourage users to download the ``msmb_data`` conda package to easily
install example data. The data can be loaded through existing methods
in ``msmbuilder.example_datasets`` (gh-854, gh-867).
- An example dataset ``MinimalFsPeptide`` is available. This is a strided
version of the existing ``FsPeptide`` dataset. We use it for testing,
when a fully-converged dataset is not required (gh-867).
- Project templates! Read the new tutorial or the :ref:`io` page for
details (gh-768).
- ``LandmarkAgglomerative`` clustering now features the ``ward`` linkage
option. An algorithm for predicting cluster assignments with the
``ward`` objective function has been developed and implemented (gh-874).

Improvements
~~~~~~~~~~~~

- Remove a unicode character from ``ktica.py`` (gh-833)
- ``msmbuilder.decomposition.KernelTICA`` now includes all parameters in its
``__init__``, making it compatible with Osprey (gh-823).
- ``msmbuilder.tpt`` methods can now handle ``BayesianMarkovStateModels`` as
input. Please note that we still do not recommend using this module with
``BootStrapMarkovStateModel``.

--------------------

We're pleased to announce the release of MSMBuilder 3.5. This release
wraps more relevant ``sklearn`` estimators and transformers. There are
also some bugfixes and API hygiene improvements. We recommend all users
upgrade to MSMBuilder 3.5.

API Changes
~~~~~~~~~~~

- ``msmbuilder.featurizer.FeatureUnion`` is now deprecated. Please use
``msmbuilder.feature_selection.FeatureSelector`` instead (799).
- ``msmbuilder.feature_extraction`` has been added to conform to the
``scikit-learn`` API. This is essentially an alias of
``msmbuilder.featurizer`` (799).

New Features
~~~~~~~~~~~~

- ``KernelTICA``, ``Nystroem``, and ``LandmarkNystroem`` are available in the
``decomposition`` module (807).

- ``FeatureSelector`` and ``VarianceThreshold`` are available in the
``feature_selection`` module (799).

- ``SparsePCA`` and ``MiniBatchSparsePCA`` are available in the
``decomposition`` module (791).

- ``Binarizer``, ``FunctionTransformer``, ``Imputer``, ``KernelCenterer``,
``LabelBinarizer``, ``MultiLabelBinarizer``, ``MinMaxScaler``,
``MaxAbsScaler``, ``Normalizer``, ``RobustScaler``, ``StandardScaler``,
and ``PolynomialFeatures`` are available in the ``preprocessing``
module (796).


Improvements
~~~~~~~~~~~~

- Fix a compilation error on gcc 5 (783)
- Fix pickle-ing of ``ContinuousTimeMSM``. The ``optimizer_state_``
parameter is not saved (822).

---------------------

We're pleased to announce MSMBuilder 3.4. It contains a plethora of new
features, bug fixes, and improvements.

API Changes
~~~~~~~~~~~

- Range-based slicing on dataset objects is no longer allowed. Keys in the
dataset object don't have to be continuous. The empty slice, e.g. ``ds[:]``
loads all trajectories in a list (610).
- Ward clustering has been renamed AgglomerativeClustering in scikit-learn.
Please use the new msmbuilder wrapper class AgglomerativeClustering. An
alias for Ward has been made available (685).
- ``PCCA.trimmed_microstates_to_macrostates`` has been removed. This
dictionary was actually keyed by *untrimmed* microstate labels.
``PCCA.transform`` would throw an exception when operating on a system
with trimming because it was using this misleading dictionary. Please use
``pcca.microstate_mapping_`` for this functionality (709).
- ``UnionDataset`` has been removed after deprecation in 3.3. Please use
``FeatureUnion`` instead (671).
- ``SubsetFeaturizer`` and ilk have been removed from the
``msmbuilder.featurizer`` namespace. Please import them from
``msmbuilder.featurizer.subset`` (738).
- ``FirstSlicer`` has been removed. Use ``Slicer(first=x)`` for the same
functionality (738).
- ``msmbuilder.featurizer.load`` has been removed. ``Featurizer.save``
has been removed. Please use ``utils.load``, ``utils.dump`` (738).


New Features
~~~~~~~~~~~~

- Dataset objects can call, ``fit_transform_with()`` to simplify the
common pattern of applying an estimator to a dataset object to produce a
new dataset object (610).
- ``kinetic_mapping`` is a new option to ``tICA``. It's similar to
``weighted_transform``, but based on a better theoretical framework.
``weighted_transform`` is deprecated (766).
- ``VonMisesFeaturizer`` uses soft bins around the unit-circle to give an
alternate representation of dihedral angles (744).
- ``MarkovStateModel`` has a ``partial_transform()`` method (707).
- ``KappaAngleFeaturizer`` is available via the command line (681).
- ``MarkovStateModel`` has a new attribute, ``percent_retained_``, for
ergodic trimming (689).
- ``AlphaAngleFeaturizer`` computes the dihedral angles between alpha
carbons (691).
- ``FunctionFeaturizer`` computes features based on an arbitrary Python
function or callable (717).
- Automatic State Partitioning (APM) uses kinetic information to cluster
conformations (748).


Improvements
~~~~~~~~~~~~

- Consistent counts setup and ergodic cutoff across various flavors of
Markov models (718, 729, 701, 705).
- Tests no longer depend on ``sklearn.hmm``, which has been removed (690).
- Improvements to ``RSMDFeaturizer`` (695, 764).
- ``SparseTICA`` is completely re-written with large performance
improvements when dealing with large numbers of features (704).
- Links for downloading example data are un-broken after figshare
changed URLs (751).