How to Install and Uninstall python3-nibabel.noarch Package on Fedora 34

Last updated: October 05,2024

1. Install "python3-nibabel.noarch" package

This tutorial shows how to install python3-nibabel.noarch on Fedora 34


    
        
            $
        

        
            
                sudo dnf update
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo dnf install
            
                        
                python3-nibabel.noarch
            
                    
    
    Copied

2. Uninstall "python3-nibabel.noarch" package

This guide let you learn how to uninstall python3-nibabel.noarch on Fedora 34:


    
        
            $
        

        
            
                sudo dnf remove
            
                        
                python3-nibabel.noarch
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo dnf autoremove
            
                    
    
    Copied

3. Information about the python3-nibabel.noarch package on Fedora 34

Last metadata expiration check: 0:38:04 ago on Tue Sep 6 08:10:37 2022.
Available Packages
Name : python3-nibabel
Version : 3.2.2
Release : 1.fc34
Architecture : noarch
Size : 3.3 M
Source : python-nibabel-3.2.2-1.fc34.src.rpm
Repository : updates
Summary : Python package to access a cacophony of neuro-imaging file formats
URL : http://nipy.org/nibabel/
License : MIT and PDDL-1.0
Description : Read / write access to some common neuroimaging file formats
:
: This package provides read +/- write access to some common medical and
: neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2 and
: later), GIFTI, NIfTI1, NIfTI2, MINC1, MINC2, MGH and ECAT as well as Philips
: PAR/REC. We can read and write Freesurfer geometry, and read Freesurfer
: morphometry and annotation files. There is some very limited support for DICOM.
: NiBabel is the successor of PyNIfTI.
:
: The various image format classes give full or selective access to header (meta)
: information and access to the image data is made available via NumPy arrays.