GamAnalyzer

mazarsju edited this page Mar 11, 2016 · 3 revisions

Using GAMAnalyzer

Install

Go to Git View -> Click on Import Projects Add the dependencies in ummisco.gama.feature.dependencies

GamAnalyzer is a tool to monitor several multi-agents simulation

The "agent_group_follower" goal is to monitor and analyze a group of agent during several simulation. This group of agent can be chosen by the user according to criteria chosen by the user. The monitoring process and analysis of these agents involves the extraction, processing and visualization of their data at every step of the simulation. The data for each simulation are pooled and treated commonly for their graphic representation or clusters.

Built-in Variable

  • varmap: All variable that can be analyzed or displayed in a graph.

  • numvarmap: Numerical variable (on this variable all the aggregator numeric are computed).

  • qualivarmap: All non numerical variable. Could be used for BDI to analyze beliefs.

  • metadatahistory: See updateMetaDataHistory. This matrice store all the metadata like getSimulationScope(), getClock().getCycle(), getUniqueSimName(scope), rule, scope.getAgentScope().getName(), this.getName(), this.agentsCourants.copy(scope), this.agentsCourants.size(), this.getGeometry().

  • lastdetailedvarvalues: store all the value (in varmap) for all the followed agent for the last iteration.

  • averagehistory: Average value for each of the numvar

  • stdevhistory: Std deviation value for each of the numvar

  • minhistory: Min deviation value for each of the numvar

  • maxhistory: Max deviation value for each of the numvar

  • distribhistoryparams: Gives the interval of the distribution described in distribhistory

  • distribhistory: Distribution of numvarmap

  • multi_metadatahistory: Aggregate each metadatahistory for each experiment

Example

This example is based on a toy model which is only composed of wandering people. In this example we will use GamAnalyzer to follow the agent people.

agent_group_follower peoplefollower;
create agentfollower 
{
  do analyse_cluster species_to_analyse:"people";
  peoplefollower<-self;
}

expGlobalNone

No clustering only the current agent follower is displayed

aspect base {
  display_mode <-"global";
  clustering_mode <-"none";
  draw shape color: #red;
}

expSimGlobalNone

The agent_group_follower corresponding to the current iteration and all the already launch experiments are displayed.

aspect simglobal{
  display_mode <-"simglobal";
  clustering_mode <-"none";
  draw shape color: #red;
  int curColor <-0;
  loop geom over: allSimShape{
    draw geom color:SequentialColors[curColor] at:{location.x,location.y,curColor*10};
    curColor <- curColor+1;
  }
}

expCluster

The agent group follower is divided in cluster computed thanks to a dbscan algorithm. Only the current agent_group_follower is displayed

aspect cluster {
  display_mode <-"global";
  clustering_mode <-"dbscan";
  draw shape color: #red;
}

expClusterSimGlobal

The agent_group_follower (made of different cluster) corresponding to the current iteration and all the already launch experiments are displayed.

aspect clusterSimGlobal {
  display_mode <-"simglobal";
  clustering_mode <-"dbscan";
  draw shape color: #red;
  int curColor <-0;
  loop geom over: allSimShape{
    draw geom color:SequentialColors[curColor] at:{location.x,location.y,curColor*10};
    curColor <- curColor+1;
  } 
}

Home

Introduction

Changes from 1.6.1 to 1.8

Platform

  1. Installation and Launching
  2. Installation
  3. Launching GAMA
  4. Headless Mode
  5. Updating GAMA
  6. Installing Plugins
  7. Troubleshooting
  8. Workspace, Projects and Models
  9. Navigating in the Workspace
  10. Changing Workspace
  11. Importing Models
  12. Editing Models
  13. GAML Editor (Generalities)
  14. GAML Editor Toolbar
  15. Validation of Models
  16. Running Experiments
  17. Launching Experiments
  18. Experiments User interface
  19. Menus and commands
  20. Parameters view
  21. Inspectors and monitors
  22. Displays
  23. Batch Specific UI
  24. Errors View
  25. Preferences

Learn GAML step by step

  1. Introduction
  2. Start with GAML
  3. Organization of a Model
  4. Basic programming concepts in GAML
  5. Manipulate basic Species
  6. Global Species
  7. Regular Species
  8. Defining Actions and Behaviors
  9. Interaction between Agents
  10. Attaching Skills
  11. Inheritance
  12. Defining Advanced Species
  13. Grid Species
  14. Graph Species
  15. Mirror Species
  16. Multi-Level Architecture
  17. Defining GUI Experiment
  18. Defining Parameters
  19. Defining Displays Generalities
  20. Defining Charts
  21. Defining 3D Displays
  22. Defining Monitors and Inspectors
  23. Defining Export files
  24. Defining User Interaction
  25. Exploring Models
  26. Run Several Simulations
  27. Batch Experiments
  28. Exploration Methods
  29. Optimizing Model Section
  30. Runtime Concepts
  31. Optimizing Models
  32. Multi-Paradigm Modeling
  33. Control Architecture
  34. Defining Equations

Recipes

  1. Manipulate OSM Datas
  2. Diffusion
  3. Using Database
  4. Calling R
  5. Using FIPA ACL
  6. Using GamAnalyzer
  7. Using BDI
  8. Using Driving Skill
  9. Manipulate dates
  10. Manipulate lights
  11. Using comodel
  12. Save and restore Simulations
  13. Using network
  14. Headless mode
  15. FAQ
  16. Known Issues

GAML References

  1. Built-in Species
  2. Agent Built-in
  3. Model Built-in
  4. Experiment Built-in
  5. Built-in Skills
  6. Built-in Architecture
  7. Statements
  8. Data Type
  9. File Type
  10. Expressions
  11. Literals
  12. Units and Constants
  13. Pseudo Variables
  14. Variables And Attributes
  15. Operators [A-A]
  16. Operators [B-C]
  17. Operators [D-H]
  18. Operators [I-M]
  19. Operators [N-R]
  20. Operators [S-Z]
  21. Index

Tutorials

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

Pedagogical materials

Developing Extensions

  1. Installing the GIT version
  2. Architecture of GAMA
  3. Developing a Plugin
  4. Developing a Skill
  5. Developing a Statement
  6. Developing an Operator
  7. Developing a Type
  8. Developing a Species
  9. Developing a Control Architecture
  10. Index of annotations
  11. IScope
  12. Creating a release of GAMA
  13. Documentation generation
  14. Website generation

Scientific References

Projects using GAMA

Training Session

Events

Older versions

Coding Camp

Clone this wiki locally
You can’t perform that action at this time.
You signed in with another tab or window. Reload to refresh your session. You signed out in another tab or window. Reload to refresh your session.
Press h to open a hovercard with more details.