gait-analysis-dataset | Raw dataset from Signal Processing

by lucabergamini Python Version: Current License: GPL-3.0

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

kandi X-RAY | gait-analysis-dataset Summary

gait-analysis-dataset is a Python library. gait-analysis-dataset has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has low support. However gait-analysis-dataset build file is not available. You can download it from GitHub.

Diplegia is one of the most common forms of a broad family of motion disorders named cerebral palsy (CP) affecting the voluntary muscular system. In recent years, various classification criteria have been proposed for CP, to assist in diagnosis, clinical decision-making and communication.

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Quality

Security

License

Reuse

Support

gait-analysis-dataset has a low active ecosystem.

It has 4 star(s) with 0 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

gait-analysis-dataset has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of gait-analysis-dataset is current.

Quality

gait-analysis-dataset has no bugs reported.

Security

gait-analysis-dataset has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

gait-analysis-dataset is licensed under the GPL-3.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

gait-analysis-dataset releases are not available. You will need to build from source code and install.

gait-analysis-dataset has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are not available. Examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed gait-analysis-dataset and discovered the below as its top functions. This is intended to give you an instant insight into gait-analysis-dataset implemented functionality, and help decide if they suit your requirements.

Read frames from the stream
The last frame in the header
Return the value of a group
Return the first frame in the frame
Write binary data to a file
Returns the number of bytes in bytes
Update the mesh
Move mesh to a point
Get the analog rate
Return the value of a given key
Return the value of a key
Return the value as a float
Return the value as a uint32
Return the value as a uint16
Returns the int16 value of the given key
Convert to integer 16 - bit integer
Return the value as a numpy array
Return the value as an integer
Get the value of a given key
Return the uint32 value of the key
Return a numpy array of integers
Return the value as a uint8 value
Returns the current analog pin
Return the first frame in the header
The last frame of the last frame
Returns the value of an integer key

Get all kandi verified functions for this library.

gait-analysis-dataset Key Features

No Key Features are available at this moment for gait-analysis-dataset.

gait-analysis-dataset Examples and Code Snippets

No Code Snippets are available at this moment for gait-analysis-dataset.

Community Discussions

No Community Discussions are available at this moment for gait-analysis-dataset.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install gait-analysis-dataset

You can download it from GitHub.
You can use gait-analysis-dataset 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.

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 .

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