d_code | 2Photon Imaging and Electrophysiology Analysis code

by dattalab Jupyter Notebook Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions Vulnerabilities Install Support

kandi X-RAY | d_code Summary

d_code is a Jupyter Notebook library. d_code has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

There are 5 main packages:.

Support

Quality

Security

License

Reuse

Support

d_code has a low active ecosystem.

It has 14 star(s) with 8 fork(s). There are 13 watchers for this library.

It had no major release in the last 6 months.

There are 0 open issues and 1 have been closed. On average issues are closed in 960 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of d_code is current.

Quality

d_code has no bugs reported.

Security

d_code has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

d_code is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

d_code releases are not available. You will need to build from source code and install.

Installation instructions, examples and code snippets are available.

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d_code Key Features

No Key Features are available at this moment for d_code.

d_code Examples and Code Snippets

No Code Snippets are available at this moment for d_code.

Community Discussions

No Community Discussions are available at this moment for d_code.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install d_code

This package requires many core elements of the Python scientific stack, including Numpy and Scipy. The simplest way to get these is to install a Python distribution such as Anaconda (recommended) or Enthought. All of this code works on a Python 2.7.x codebase. Porting to Python 3 wouldn't be a bad idea, but right now it runs on 2.7.
Numpy
Scipy (interpolate, stats, ndimage, signal)
Matplotlib
Scikit-learn
IPython
Pyside
Sphinx (for documentation)
pymongo
mahotas
pymorph
image_registration
tifffile

Support

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 .

Find more information at: