nipy | Neuroimaging in Python FMRI analysis package

 by   nipy Python Version: 0.6.0 License: BSD-3-Clause

kandi X-RAY | nipy Summary

kandi X-RAY | nipy Summary

nipy is a Python library typically used in Data Science applications. nipy has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has high support. You can install using 'pip install nipy' or download it from GitHub, PyPI.

Neuroimaging in Python FMRI analysis package

            kandi-support Support

              nipy has a highly active ecosystem.
              It has 297 star(s) with 127 fork(s). There are 36 watchers for this library.
              There were 1 major release(s) in the last 6 months.
              There are 37 open issues and 110 have been closed. On average issues are closed in 121 days. There are 6 open pull requests and 0 closed requests.
              It has a positive sentiment in the developer community.
              The latest version of nipy is 0.6.0

            kandi-Quality Quality

              nipy has 0 bugs and 0 code smells.

            kandi-Security Security

              nipy has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              nipy code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              nipy is licensed under the BSD-3-Clause License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              nipy releases are not available. You will need to build from source code and install.
              Deployable package is available in PyPI.
              Build file is available. You can build the component from source.

            Top functions reviewed by kandi - BETA

            kandi has reviewed nipy and discovered the below as its top functions. This is intended to give you an instant insight into nipy implemented functionality, and help decide if they suit your requirements.
            • Plot a map
            • Load the anat data from a M1 brain
            • Plot the anat
            • Find the MNI template
            • Design the design matrix
            • Sets up the design matrix
            • Get parameters from an expression
            • Subtract terms from the term
            • Generate a time - realign of the input array
            • Estimate the model parameters
            • Create an XZ image from a 3D image
            • Calculate the group rejection metrics
            • Perform the clustering of the data
            • Design a block design matrix
            • Design a design matrix
            • Performs a clustering
            • Subtract a subset of terms
            • Create a 2D dataset for a 4D network
            • Worst down a graph
            • Generate a dmtx compressed time series
            • Create a 2D dataset
            • Format the format of the actions
            • Estimate the model
            • Convert euler to matrix
            • Generate a spectral decomposition using the spectral decomposition
            • Save an image to a file
            • Generate a ba image
            • Generate a xyz image
            • Write the comment to a file
            • Perform fixed parcellation using fixed parcellation
            • Removes the gradient of the PSM
            Get all kandi verified functions for this library.

            nipy Key Features

            No Key Features are available at this moment for nipy.

            nipy Examples and Code Snippets

            No Code Snippets are available at this moment for nipy.

            Community Discussions


            How to change pinned packages in mamba package manager
            Asked 2021-Jun-22 at 08:19

            When I try to install a python package in a minimamba distribution (mamba 0.14), there is no dependency solution for the python version installed (shown as pinned package below). How can I allow this package to be downgraded to allow a dependency solution?



            Answered 2021-Jun-22 at 08:10

            Did you try mamba install python=3.7 nipy? This should downgrade python package to the required version allowing you to install nipy and its dependencies.



            How to resolve versionConflict error in Flask (PyJWT and Flask-JWT-Extended)
            Asked 2021-May-29 at 14:41

            I want to run a very simple application using Flask framework. I have also run and developed flask app before. After a while I need to develop a new simple app using it.

            So I have created a virtual environment and activated it:



            Answered 2021-May-29 at 12:49

            It seems that the newest version of Flask (currently 2.0.1) has problem with dependencies.

            The problem was resolved after downgrading it to 1.1.2 via the following command:


            Community Discussions, Code Snippets contain sources that include Stack Exchange Network


            No vulnerabilities reported

            Install nipy

            You can install using 'pip install nipy' or download it from GitHub, PyPI.
            You can use nipy like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.


            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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            pip install nipy

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            gh repo clone nipy/nipy

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