Multivariate Pattern Analysis in Python

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# Example Analyses and Scripts

Each of the examples in this section is a stand-alone script containing all necessary code to run some analysis. All examples are shipped with PyMVPA and can be found in the `doc/examples/` directory in the source package. This directory might include some more special-interest examples which are not listed here.

Some examples need to access a sample dataset available in the `data/` directory within the root of the PyMVPA hierarchy, and thus have to be invoked directly from PyMVPA root (e.g. `doc/examples/searchlight.py`). Alternatively, one can download a full example dataset, which is explained in the next section.

## Preprocessing

- Visualization of Data Projection Methods
- Simple Data-Exploration

## Analysis

- Separating hyperplane tutorial
- Tiny Example of a Full Cross-Validation
- Compare SMLR to Linear SVM Classifier
- Classifier Sweep
- The effect of different hyperparameters in GPR
- Simple model selection: grid search for GPR
- Efficient cross-validation using a cached kernel
- Minimal Searchlight Example
- Searchlight on fMRI data
- A searchlight computing a dissimilarity matrix measure
- Sensitivity Measure
- Classification of SVD-mapped Datasets
- Monte-Carlo testing of Classifier-based Analyses
- Nested Cross-Validation
- Determine the Distribution of some Variable
- Spatio-temporal Analysis of event-related fMRI data
- Hyperalignment for between-subject analysis
  - Analysis setup
  - Within-subject classification
  - Between-subject classification using anatomically aligned data
  - Between-subject classification with Hyperalignment(TM)
  - Comparing the results
    - Performance
    - Similarity structures
  - Regularized Hyperalignment
- Classifying the MNIST handwritten digits with MDP
  - MDP-style classification
  - Doing it the PyMVPA way
  - Visualizing data and results
- Analysis of eye movement patterns
  - Plotting the results

## Visualization

- ERP/ERF-Plots
- kNN – Model Flexibility in Pictures
- Simple Plotting of Classifier Behavior
- Generating Topography plots
- Self-organizing Maps
- Basic (f)MRI plotting

## Miscellaneous

- Kernel-Demo
- Curve-Fitting
  - BOLD-Response parameters
  - Searchlight accuracy distributions

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