Skip to content

Launching

RoiArthurB edited this page Feb 22, 2024 · 1 revision

Launching GAMA

Running GAMA for the first time requires that you launch the application (Gama.app on MacOS X, Gama.exe on Windows, Gama on Linux, located in the folder called GAMA_VERSION.NUMBER_YOUR_OS_NAME once you have unzipped the downloaded archive). In case you are unable to launch the application, or if error messages appear, please refer to the installation or troubleshooting instructions.

Table of contents

Launching the Application

The extraction of the downloaded archive provides:

  • on Mac OS X: a single file named Gama.app
  • on Windows and Linux: a folder named GAMA_1.8_YOUR_OS_NAME containing, among many other files and folders, the Gama.exe file (for Windows) and Gama (for Linux).

Running GAMA requires that you launch the application file (Gama.app on Mac OS X, Gama.exe on Windows, Gama on Linux) by double-clicking on them or from a terminal.

Launching the Application from the command line

Note that GAMA can also be launched in two different other ways:

  1. In a so-called headless mode (i.e. without a user interface, from the command line, in order to conduct experiments or to be run remotely). Please refer to the corresponding instructions.
  2. From the terminal, using a path to a model file and the name or number of an experiment, in order to allow running this experiment directly (note that the two arguments are optional: if the second is omitted, the file is imported in the workspace if not already present and opened in an editor; if both are omitted, GAMA is launched as usual):
  • Gama.app/Contents/MacOS/Gama path_to_a_model_file#experiment_name_or_number on Mac OS X
  • Gama path_to_a_model_file#experiment_name_or_number on Linux
  • Gama.exe path_to_a_model_file#experiment_name_or_number on Windows

Choosing a Workspace

Past the splash screen, GAMA will ask you to choose a workspace in which to store your models and their associated data and settings. The workspace can be any folder in your filesystem on which you have read/write privileges. If you want GAMA to remember your choice next time you run it (it can be handy if you run Gama from the command line), simply check the corresponding option. If this dialog does not show up when launching GAMA, it probably means that you inherit from an older workspace used with a previous GAMA version (and still "remembered"). In that case, a warning will be produced to indicate that the model library is out of date, offering you the possibility to create a new workspace.

Window to choose the workspace.

You can enter its address or browse your filesystem using the appropriate button. If the folder already exists, it will be reused (after a warning if it is not already a workspace). If not, it will be created. It is always a good idea, when you launch a new version of GAMA for the first time, to create a new workspace. You will then, later, be able to import your existing models into it. Failing to do so might lead to odd errors in the various validation processes.

When you try to choose a workspace used with a previous of GAMA, the following pop-up will appear.

Pop-up that appears when the user chooses a folder used as a workspace in a previous version of GAMA.

The following pop-up appears when the user wants to create a new workspace in a folder that does not exist. Click on OK to create the folder and set this new folder as the GAMA workspace.

Pop-up that appears when the user wants to create a new workspace. Click on OK.

Welcome Page

As soon as the workspace is created, GAMA will open and you will be presented with its first window. GAMA is based on Eclipse and reuses most of its visual metaphors for organizing the work of the modeler. The main window is then composed of several parts, which can be views or editors, and are organized in a perspective. GAMA proposes 2 main perspectives: Modeling, dedicated to the creation of models, and Simulation, dedicated to their execution and exploration. Other perspectives are available if you use shared models.

The default perspective in which GAMA opens is Modeling. It is composed of a central area where GAML editors are displayed, which is surrounded by a Navigator view on the left-hand side of the window, an Outline view (linked with the open editor), the Problems view, which indicates errors and warnings present in the models stored in the workspace and an interactive console, which allows the modeler to try some expressions and get an immediate result.

GAMA after the first launch.

In the absence of previously open models, GAMA will display a Welcome page (actually a web page), from which you can find links to the website, current documentation, tutorials, etc. This page can be kept open (for instance if you want to display the documentation when editing models) but it can also be safely closed (and reopened later from the "Help" menu).

Menu to open new views.

From this point, you are now able to edit a new model, navigate in the model library, or import an existing model.

  1. What's new (Changelog)
  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
  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 Models
    1. Runtime Concepts
    2. Analyzing code performance
    3. Optimizing Models
  8. Multi-Paradigm Modeling
    1. Control Architecture
    2. Defining Differential Equations
  1. Manipulate OSM Data
  2. Cleaning OSM Data
  3. Diffusion
  4. Using Database
  5. Using FIPA ACL
  6. Using BDI with BEN
  7. Using Driving Skill
  8. Manipulate dates
  9. Manipulate lights
  10. Using comodel
  11. Save and restore Simulations
  12. Using network
  13. Headless mode
  14. Using Headless
  15. Writing Unit Tests
  16. Ensure model's reproducibility
  17. Going further with extensions
    1. Calling R
    2. Using Graphical Editor
    3. Using Git from GAMA
  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
  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

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

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

Resources

  1. Videos
  2. Conferences
  3. Code Examples
  4. Pedagogical materials
Clone this wiki locally