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Julien Mazars edited this page Apr 15, 2016 · 23 revisions

Luneray's flu

This tutorial has for goal to introduce how to build a model with GAMA and to use GIS data and graphs. In particular, this tutorial shows how to write a simple GAMA model (the structure of a model, the notion of species...) load gis data, to agentify them and to use a network of polylines to constraint the movement of agents. The pdf of the presentation corresponding to this tutorial is available [here](https://github.com/gama-platform/gama/wiki/images/Tutorials/Luneray's flu/Luneray's flu.pdf). All the files related to this tutorial (shapefiles and models) are available [here](https://github.com/gama-platform/gama/wiki/images/Tutorials/Luneray's flu/Luneray's flu.zip).

The importation of models is described [here] (https://github.com/gama-platform/gama/wiki/G__ImportingModels)

Model Overview

The model built in this tutorial concerns the spreading of a flu in the city of Luneray (Normandie, France).

images/Luneray.jpg

Two layers of GIS data are used: a road layer (polylines) and a building layer (polygons). In this model, people agents are moving from building to building using the road network. Each infected people can infect the neighbor people.

Some data collected concerning Luneray and the disease:

  • Number of inhabitants: 2147 (source : wikipedia)
  • Mean speed of the inhabitants (while moving on the road) : 2-5 km/h
  • The disease - non lethal - is spreading (by air) from people to people
  • Time to cure the disease: more than 100 days
  • Infection distance: 10 meters
  • Infection probability (when two people are at infection distance) : 0.05/minute

From the data collected, we made some modeling choice:

  • Simulation step: 1 minute
  • People are moving on the roads from building to building
  • Most of time people are moving to meet their friend then go back home
  • People use the shortest path to move between buildings
  • All people move at constant speed
  • Each time, people arrived at a building they are staying a certain time : they are staying longer in their home than in their friend houses
  • Infected people are never cured

images/Luneray.jpg

Step List

This tutorial is composed of 5 steps corresponding to 5 models. For each step we present its purpose, an explicit formulation and the corresponding GAML code.

  1. Creation of a first basic disease spreading model
  2. Definition of monitors and chart outputs
  3. Importation of GIS data
  4. Use of a graph to constraint the movements of people
  5. Definition of 3D displays

Home

  1. What's new (Changelog)

Platform

  1. Installation and Launching
    1. Installation
    2. Launching GAMA
    3. Updating GAMA
    4. Installing Plugins
  2. Workspace, Projects and Models
    1. Navigating in the Workspace
    2. Changing Workspace
    3. Importing Models
  3. Editing Models
    1. GAML Editor (Generalities)
    2. GAML Editor Tools
    3. Validation of Models
  4. Running Experiments
    1. Launching Experiments
    2. Experiments User interface
    3. Controls of experiments
    4. Parameters view
    5. Inspectors and monitors
    6. Displays
    7. Batch Specific UI
    8. Errors View
  5. Running Headless
    1. Headless Batch
    2. Headless Server
    3. Headless Legacy
  6. Preferences
  7. Troubleshooting

Learn GAML step by step

  1. Introduction
    1. Start with GAML
    2. Organization of a Model
    3. Basic programming concepts in GAML
  2. Manipulate basic Species
  3. Global Species
    1. Regular Species
    2. Defining Actions and Behaviors
    3. Interaction between Agents
    4. Attaching Skills
    5. Inheritance
  4. Defining Advanced Species
    1. Grid Species
    2. Graph Species
    3. Mirror Species
    4. Multi-Level Architecture
  5. Defining GUI Experiment
    1. Defining Parameters
    2. Defining Displays Generalities
    3. Defining 3D Displays
    4. Defining Charts
    5. Defining Monitors and Inspectors
    6. Defining Export files
    7. Defining User Interaction
  6. Exploring Models
    1. Run Several Simulations
    2. Batch Experiments
    3. Exploration Methods
  7. Optimizing Model Section
    1. Runtime Concepts
    2. Optimizing Models
  8. Multi-Paradigm Modeling
    1. Control Architecture
    2. Defining Differential Equations

Recipes

  1. Manipulate OSM Data
  2. Diffusion
  3. Using Database
  4. Using FIPA ACL
  5. Using BDI with BEN
  6. Using Driving Skill
  7. Manipulate dates
  8. Manipulate lights
  9. Using comodel
  10. Save and restore Simulations
  11. Using network
  12. Headless mode
  13. Using Headless
  14. Writing Unit Tests
  15. Ensure model's reproducibility
  16. Going further with extensions
    1. Calling R
    2. Using Graphical Editor
    3. Using Git from GAMA

GAML References

  1. Built-in Species
  2. Built-in Skills
  3. Built-in Architecture
  4. Statements
  5. Data Type
  6. File Type
  7. Expressions
    1. Literals
    2. Units and Constants
    3. Pseudo Variables
    4. Variables And Attributes
    5. Operators [A-A]
    6. Operators [B-C]
    7. Operators [D-H]
    8. Operators [I-M]
    9. Operators [N-R]
    10. Operators [S-Z]
  8. Exhaustive list of GAMA Keywords

Developing GAMA

  1. Installing the GIT version
  2. Developing Extensions
    1. Developing Plugins
    2. Developing Skills
    3. Developing Statements
    4. Developing Operators
    5. Developing Types
    6. Developing Species
    7. Developing Control Architectures
    8. Index of annotations
  3. Introduction to GAMA Java API
    1. Architecture of GAMA
    2. IScope
  4. Using GAMA flags
  5. Creating a release of GAMA
  6. Documentation generation

Tutorials

  1. Predator Prey
  2. Road Traffic
  3. 3D Tutorial
  4. Incremental Model
  5. Luneray's flu
  6. BDI Agents

Community

  1. Team
  2. Projects using GAMA
  3. Scientific References
  4. Training Sessions

Versions of GAMA

Resources

  1. Videos
  2. Conferences
  3. Code Examples
  4. Pedagogical materials
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