Delineo Infection Simulator

This repository contains a simulation framework for modeling infection spread and profiling different scenarios across regions. It includes tools for simulation setup, data interface, profiling, and visualization.

Directory Structure

dmp/

Handles Disease Modelling Platform (DMP) functionality, including interfacing with APIs or structured data layers. DMP uses matrices to predict the infection trajectory of an individual.

profiles/

Contains profiling data (e.g., .prof, .txt) to analyze performance of key functions like run_main and initialize_dmp_api as well as app.py

profiling_results/

Stores simulation profiling outputs for various dataset sizes (100, 1000, 10000) to benchmark runtime performance.

simulator/

Main simulation logic and configuration files.

Subdirectories:

• api_testing/, api_testing_copy/: For testing API functionality, with different configurations.
• barnsdall/, hagerstown/: Regional datasets/configurations.

Key Files:

• config.py: Contains default simulation configuration settings.
• data_interface.py: Manages loading and formatting of external datasets (CSV, JSON, YAML).
• generate_pattern.py: Generates movement patterns used in simulations.
• infection_model.py: Based on Wells-Reilly model to predict infection probability.
• infectionmgr.py: Manages infection state across simulation steps.
• pap_places.json, pap_places.py: Contains predefined place-based datasets and associated logic.
• pattern_simple.json, patterns_alg.json: Pattern configuration files.
• population_info.yaml: Metadata about the population used in simulations.
• simulate.py: Main simulation logic
• test_loading_data.py: Unit test or utility to check data loading.
• visualize.ipynb: Jupyter Notebook for visualizing simulation outputs.
• cbg_populations.csv, clusters.csv, facility_data.json: Input datasets.

Root-Level Files

• app_3.py, app_profiling.py, app.py: Simulation applications with various configurations.
• dmp_functions.py: Functions supporting DMP operations.
• simulation_functions.py: Core functions used across simulation runs.
• simulator_results.txt, simulator_results_1.txt: Text-based output logs of simulation runs.
• user_input.py: Likely processes user configurations or interactive inputs.
• stream_debug.log: Debug log for streaming or runtime operations.
• README.md, README_v0.md: Documentation for project usage and structure.
• .gitignore, LICENSE: Standard project configuration files.

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Getting Started

Things you will need to install beforehand

Install Python and set up your IDE's Python environment

NO MODULE ERROR: If you receive an error message "ModuleNotFoundError: No module named [module name]" What you need to do is, in whatever environment you want to run the simulator, type "python -m pip install [module name]" into the terminal to install the module.

Modules you will probably have to install (if you receive any error messages, install what it says is missing) flask, flask_cors, numpy, pandas, pyyaml, requests

USE CELL DATA: Hopkins DNS is giving us issues at the moment, so we cannot use Hopkins WiFi to run the simulation. For this reason, please use cell data when running the simulation for the time being.

To run a simulation:

python app.py