Northeastern Productivity App

Week Planner

To use the week planner, run results.ipynb. First, you will need to select a set of tasks to use. You can either use one of the pre-existing task sets in sample_tasks or add your own set of tasks to that folder following the structure of existing task sets. Then, generate a random plan using the save_random_plan method. You do not need to do this if you are using an existing task set. Be sure to specify the task file you created in the previous step when running generating a random plan. Next, run the get_results method specifying your task file, random plan file (from the previous step), and home address. To run the algorithm once, set the n_runs parameter is to 1. Now you have generated an optimized week plan!

Snell Density

All the relevant files are loacted in backend/snell_density. The model training is in model.py. Change the model type parameter to run the different model types, such as "lr" for linear regression, "nn" for neural networks, "dt" for decision trees", and "rf" for random forests. The code to process the data file data.csv is located in DATE_PARSER.py and FILE_READER.py, while the featurizing of the data is in main.py.

Start Web App:

Backend:

• cd backend
• pip install flask if not installed already
• set FLASK_APP=app
• flask run

Frontend:

• Open a new terminal
• cd frontend
• npm install
• npm start