PDF version of the PyMVPA ManualΒΆ
The PDF version of the manual is available for download.
- Introduction
- Installation
- Getting Started
- Tutorial Introduction to PyMVPA
- Tutorial Prerequisites
- Dataset basics and concepts
- Getting data in shape
- Classifiers – All Alike, Yet Different
- Looking here and there – Searchlights
- Classifiers that do more – Meta Classifiers
- Classification Model Parameters – Sensitivity Analysis
- Event-related Data Analysis
- Multi-dimensional Searchlights
- Working with OpenFMRI.org data
- WiP: The Earth Is Round – Significance Testing
- Miscellaneous
- Example Analyses and Scripts
- Preprocessing
- Analysis strategies and Background
- A simple start
- Separating hyperplane tutorial
- Minimal Searchlight Example
- Searchlight on fMRI data
- Surface-based searchlight on fMRI data
- Representational similarity analysis (RSA) on fMRI data
- 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 of eye movement patterns
- Visualization
- Integrate with 3rd-party software
- Special interest and Miscellaneous
- Frequently Asked Questions
- General
- I’m a Matlab user. How hard is learning Python and PyMVPA for me?
- It is sloooooow. What can I do?
- I am tired of writing these endless import blocks. Any alternative?
- I feel like I want to contribute something, do you mind?
- I want to develop a new feature for PyMVPA. How can I do it efficiently?
- The manual is quite insufficient. When will you improve it?
- Data import, export and storage
- Data preprocessing
- Data analysis
- General
- Glossary
- References
- License
- Development Changelog
