Skip to main content

QPrism

Overview

The QPrism Python package serves as a quality assessment toolbox for data collected using sensors in smartphones and wearables (eg. accelerometer, gyroscope, audio and video). The package leverages digital signal and image processing techniques along with machine learning algorithms to assess the quality of sensor data covering data availability, interpretability, noise contamination and consistency. QPrism is completely data-driven, requiring no a priori data assumptions or application-specific parameter tuning to generate a comprehensive data quality report.

Installation

The installation can be done with pip. Since pip does not resolve the dependencies' version efficiently, please install QPrism with the following steps.

$ python3 -m pip install --upgrade pip
$ pip install -r https://raw.githubusercontent.com/aid4mh/QPrism/main/requirements.txt
$ pip install --no-deps QPrism

Documentation

The full documentation for QPrism can be accessed here.

Examples:

We have provided throughout demo notebooks in Google Colab covered all functions.

The notebooks can be accessed here.

Note: In the sensor folder, it also contains notebooks that can validate each metric we have created, and a script demo that can be adopted by user with minor modifications.

Detailed explanation for the provided examples can be found in the documentation

Contributing to the project

We welcome and encourage project contributions! Please see the CONTRIBUTING.md for details.

Acknowledgments

The development of QPrism package is supported by Krembil Foundation.

The authors also like to acknowledge Aditi Surendra for designing the module function illustration.

Authors

License

MIT License

Metadata

Release files for QPrism 0.4.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for QPrism 0.4.0
File Size Uploaded
qprism-0.4.0.tar.gz 7.4 MB Details

Built distribution (wheel)

Table of built distributions (wheels) for QPrism 0.4.0
File Interpreter ABI Platform
qprism-0.4.0-py3-none-any.whl Python 3 none any Details

Total release size: 7.4 MB

Release files / qprism-0.4.0.tar.gz

Download URL qprism-0.4.0.tar.gz
Size 7.4 MB
Tags Source
SHA-256 checksum
How to use checksums
899cc681ea2247544ac5a5202e02e1243b394c529dc6244ee5cc5b6b8951909c
BLAKE2b-256 checksum
How to use checksums
1a64756dc061a7196a2c513b8f1da3757dd6435c092189098e950c877c2b8257
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.1 CPython/3.10.5

Release files / qprism-0.4.0-py3-none-any.whl

Download URL qprism-0.4.0-py3-none-any.whl
Size 32.7 kB
Tags Python 3
SHA-256 checksum
How to use checksums
b9f51d56fb3f2e01c38a0665ffb5308b9ef9599d6926d2d201c9b071f77d1185
BLAKE2b-256 checksum
How to use checksums
970b5b7d7d314d2790bda1f2b4374d90a15e491a2b62783d3a78786c9bbce031
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.1 CPython/3.10.5

Release history Release notifications | RSS feed

This release

0.4.0 This release

2 release files

0.3.9

2 release files

0.3.8

2 release files

0.3.7

2 release files

0.3.6

2 release files

0.3.5

2 release files

0.3.4

2 release files

0.3.3

2 release files

0.3.2

2 release files

0.3.1

2 release files

0.2.9

2 release files

0.2.8

1 release file

0.2.7

2 release files

0.2.6

2 release files

0.2.5

2 release files

0.2.4

2 release files

0.2.3

2 release files

0.2.2

2 release files

0.2.1

2 release files

0.1.9

2 release files

0.1.8

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page