GeriLife is a comprehensive toolkit designed to empower caregivers in elder-care communities, promoting wellness and ensuring equitable engagement in life-enriching activities. This project, rooted in real-world insights and collaborative innovation, aims to transform elder care by making quality-of-life activities visible and coordinated.
European Union Public License 1.2
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Create Mock Data Generator for Resident Activities #61
Add a mock data generator for activities, aiming to create a realistic data set for development and testing purposes.
Detailed Description
The generator will produce a random number of activities per resident, ranging from 10 to 30.
All activities will be backdated within the past 30 days to simulate a typical month.
Randomization will apply to all activity properties, including:
duration_m: Randomly set to 15, 30, 45, or 60 minutes.
caregiver_role: Randomly selected from the predefined caregiver roles.
activity_type: Randomly chosen from the available activity types.
The generated data should have a natural variance to mimic real-world scenarios.
Use Case
Facilitates UI testing by providing a diverse data set.
Assists in demonstrations to stakeholders and potential clients.
Enhances the development process with a rich, local testing environment.
Technical Considerations
Implement a script or management command within the Django framework for ease of use.
Utilize a probability distribution to ensure organic data variety, leveraging libraries such as numpy, scipy, or statsmodels which are already included in the project.
The generator should create a realistic spread of activity durations and types, using the probability distribution functions available in these libraries to select values.
Ensure the generator script is idempotent, allowing it to be run multiple times without duplicating data.
Generate a diverse set of data reflecting various resident activity levels, though perfect distribution across levels is not a requirement for the initial iteration.
Additional Context
While achieving a spread across different activity levels is ideal, the initial version need not strictly enforce this distribution.
Add a mock data generator for activities, aiming to create a realistic data set for development and testing purposes.
Detailed Description
duration_m
: Randomly set to 15, 30, 45, or 60 minutes.caregiver_role
: Randomly selected from the predefined caregiver roles.activity_type
: Randomly chosen from the available activity types.Use Case
Technical Considerations
numpy
,scipy
, orstatsmodels
which are already included in the project.Additional Context