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PyMVPA: Python MultiVariate Pattern Analysis
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mvpa
:
MultiVariate Pattern Analysis
mvpa.algorithms
:
Import helper for PyMVPA algorithms.
mvpa.algorithms.cvtranserror
:
Cross-validate a classifier on a dataset
mvpa.base
:
Base functionality of PyMVPA
mvpa.base.dochelpers
mvpa.base.externals
:
Helper to verify presence of external libraries and modules
mvpa.clfs
:
Import helper for PyMVPA classifiers
mvpa.clfs._svmbase
:
Common to all SVM implementations functionality.
mvpa.clfs.base
:
Base classes for all classifiers.
mvpa.clfs.gpr
:
Gaussian Process Regression (GPR).
mvpa.clfs.kernel
:
Kernels for Gaussian Process Regression and Classification.
mvpa.clfs.knn
:
k-Nearest-Neighbour classifier.
mvpa.clfs.lars
:
Least angle regression (LARS) classifier.
mvpa.clfs.libsmlr
:
Wraper for the stepwise_regression function for SMLR.
mvpa.clfs.libsmlr.ctypes_helper
:
Helpers for wrapping C libraries with ctypes.
mvpa.clfs.libsvm
:
Classifiers provied by LibSVM library
mvpa.clfs.libsvm._svm
:
Python interface to the SWIG-wrapped libsvm
mvpa.clfs.libsvm.sens
:
Provide sensitivity measures for libsvm's SVM.
mvpa.clfs.libsvm.svm
:
Wrap the libsvm package into a very simple class interface.
mvpa.clfs.model_selector
:
Model selction.
mvpa.clfs.plr
:
Penalized logistic regression classifier.
mvpa.clfs.ridge
:
Ridge regression classifier.
mvpa.clfs.sg
:
Classifiers provied by shogun (sg) library
mvpa.clfs.sg.sens
:
Provide sensitivity measures for sg's SVM.
mvpa.clfs.sg.svm
:
Wrap the libsvm package into a very simple class interface.
mvpa.clfs.smlr
:
Sparse Multinomial Logistic Regression classifier.
mvpa.clfs.stats
:
Estimator for classifier error distributions.
mvpa.clfs.svm
:
Wrap the libsvm package into a very simple class interface.
mvpa.clfs.transerror
:
Utility class to compute the transfer error of classifiers.
mvpa.clfs.warehouse
:
Collection of classifiers to ease the exploration.
mvpa.datasets
:
PyMVPA datasets and helper classes such as mappers, splitters
mvpa.datasets.base
:
Dataset container
mvpa.datasets.mappeddataset
:
Mapped dataset
mvpa.datasets.maskeddataset
:
Dataset with applied mask
mvpa.datasets.metric
:
Classes and functions to provide sense of distances between sample points
mvpa.datasets.misc
:
Misc function performing operations on datasets.
mvpa.datasets.niftidataset
:
Dataset that gets its samples from a NIfTI file
mvpa.datasets.splitter
:
Collection of dataset splitters.
mvpa.featsel
mvpa.featsel.base
:
Feature selection base class and related stuff base classes and helpers.
mvpa.featsel.helpers
mvpa.featsel.ifs
:
Incremental feature search (IFS).
mvpa.featsel.rfe
:
Recursive feature elimination.
mvpa.mappers
:
PyMVPA mappers.
mvpa.mappers.base
:
Data mapper
mvpa.mappers.mask
:
Data mapper
mvpa.mappers.metric
:
Data mapper
mvpa.mappers.pca
:
Data mapper
mvpa.mappers.svd
:
Data mapper
mvpa.measures
mvpa.measures.anova
:
FeaturewiseDatasetMeasure performing a univariate ANOVA.
mvpa.measures.base
:
Base class for data measures: algorithms that quantify properties of datasets.
mvpa.measures.noiseperturbation
:
This is a
FeaturewiseDatasetMeasure
that uses a scalar
DatasetMeasure
and selective noise perturbation to compute a sensitivity map.
mvpa.measures.searchlight
:
Implementation of the Searchlight algorithm
mvpa.measures.splitmeasure
:
This is a
FeaturewiseDatasetMeasure
that uses another
FeaturewiseDatasetMeasure
and runs it multiple times on differents splits of a
Dataset
.
mvpa.misc
:
Import helper for PyMVPA misc modules
mvpa.misc.cmdline
:
Common functions and options definitions for command line
mvpa.misc.copy
:
Generic (shallow and deep) copying operations.
mvpa.misc.data_generators
:
Miscelaneous data generators for unittests and demos
mvpa.misc.errorfx
:
Error functions
mvpa.misc.exceptions
:
Exception classes which might get thrown
mvpa.misc.fsl
:
Import helper for FSL
mvpa.misc.fsl.flobs
:
Wrapper around FSLs halfcosbasis to generate HRF kernels
mvpa.misc.fsl.melodic
:
Wrapper around the output of MELODIC (part of FSL)
mvpa.misc.iohelpers
:
Some little helper for reading (and writing) common formats from and to disk.
mvpa.misc.param
:
Parameter representation
mvpa.misc.signal
:
Simple preprocessing utilities
mvpa.misc.state
:
Classes to control and store state information.
mvpa.misc.stats
:
Little statistics helper
mvpa.misc.support
:
Support function -- little helpers in everyday life
mvpa.misc.transformers
:
Simply functors that transform something.
mvpa.misc.verbosity
:
Verbose output and debugging facility
mvpa.misc.vproperty
:
C++-like virtual properties
mvpa.suite
:
MultiVariate Pattern Analysis -- load helper
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PyMVPA: Python MultiVariate Pattern Analysis
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