How to Install and Uninstall python-nipy Package on Ubuntu 16.04 LTS (Xenial Xerus)

Last updated: June 03,2024

1. Install "python-nipy" package

Please follow the steps below to install python-nipy on Ubuntu 16.04 LTS (Xenial Xerus)


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                python-nipy
            
                    
    
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2. Uninstall "python-nipy" package

In this section, we are going to explain the necessary steps to uninstall python-nipy on Ubuntu 16.04 LTS (Xenial Xerus):


    
        
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                sudo apt remove
            
                        
                python-nipy
            
                    
    
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            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the python-nipy package on Ubuntu 16.04 LTS (Xenial Xerus)

Package: python-nipy
Priority: extra
Section: universe/python
Installed-Size: 3247
Maintainer: Ubuntu Developers
Original-Maintainer: NeuroDebian Team
Architecture: all
Source: nipy
Version: 0.3.0+git262-gbb838d7-1
Provides: python2.7-nipy
Depends: python-numpy (>= 1:1.2), python (>= 2.7), python (<< 2.8), python-scipy, python-nibabel, python-nipy-lib (>= 0.3.0+git262-gbb838d7-1)
Recommends: python-matplotlib, mayavi2, python-sympy
Suggests: python-mvpa
Filename: pool/universe/n/nipy/python-nipy_0.3.0+git262-gbb838d7-1_all.deb
Size: 721502
MD5sum: 64caa6ba5c9a8251765202a0e59e3365
SHA1: 96155052b586fd99ebf9203bf1c43ef4280261c6
SHA256: cdafc0b7e73f183ad4779801d4229f26128377eed83d8968877373cddfb50e57
Description-en: Analysis of structural and functional neuroimaging data
NiPy is a Python-based framework for the analysis of structural and
functional neuroimaging data. It provides functionality for
- General linear model (GLM) statistical analysis
- Combined slice time correction and motion correction
- General image registration routines with flexible cost functions,
optimizers and re-sampling schemes
- Image segmentation
- Basic visualization of results in 2D and 3D
- Basic time series diagnostics
- Clustering and activation pattern analysis across subjects
- Reproducibility analysis for group studies
Description-md5: 1b32129c672ebf51bd9d3ef07a7f5f16
Homepage: http://neuroimaging.scipy.org
Python-Version: 2.7
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Origin: Ubuntu