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DefiningGUIExperiment
When you execute your simulation, you will often need to display some information. For each simulation, you can define some inputs, outputs and behaviors:
- The inputs will be composed of parameters manipulated by the user for each simulation.
- The behaviors will be used to define behavior executed at each step of the experiment.
- The outputs will be composed of displays, monitors and inspectors. They will be defined inside the scope
output
. The definition of their layout can also be set with thelayout
statement.
A typical GUI experiment code follows this pattern:
experiment exp_name type: gui {
[input]
[behaviors]
output {
layout [layout_option]
[display statements]
[monitor statements]
}
}
You can define fours types of experiments (through the facet type
):
-
gui
experiments (the default type) are used to play an experiment and displays its outputs. It is also used when the user wants to interact with the simulation. -
batch
experiments are used to play an experiment several times (usually with other input values), used for model exploration. We will come back to this notion a bit further in the tutorial. -
test
experiments are used to write unit tests on a model (used to ensure its quality). -
memorize
experiments are GUI experiments in which the simulation state is kept in memory and the user can backtrack to any previous step.
Inside experiment scope, you can access to some built-in attributes which can be useful, such as minimum_cycle_duration
, to force the duration of one cycle.
experiment my_experiment type: gui {
float minimum_cycle_duration <- 2.0#minute;
}
In addition, the attribute simulations
contain the list of all the simulation agents that are running in the current experiment. Whereas the attribute simulation
represents a single simulation, the last element of the simulation list.
Finally, in the case of a GUI experiment, the facets autorun
and benchmark
can be used as follows:
experiment name type: gui autorun: true benchmark: true { }
When autorun
is set to true
the launch of the experiment will be followed automatically by its run. When benchmark
is set to true, GAMA records the number of invocations and running time of the statements and operators of the simulations launched in this experiment. The results are automatically saved in a csv file in a folder called 'benchmarks' when the experiment is closed.
Other built-ins are available, to learn more about, go to the page experiment built-in.
A layout
can be added to output
to specify the layout of the various displays defined below (e.g. #none
, #split
, #stack
, #vertical
or #horizontal
). It will also define which elements of the interface are displayed: parameters
, navigator
, editors
, consoles
, toolbars
, tray
, or tabs
facets (expecting a boolean value). You will find more detailed information in the statement's documentation
In this part, we will focus on the gui experiments. We will start with learning how to define input parameters, then we will study the outputs, such as displays, monitors and inspectors, and export files. We will finish this part with how to define user commands.
- Installation and Launching
- Workspace, Projects and Models
- Editing Models
- Running Experiments
- Running Headless
- Preferences
- Troubleshooting
- Introduction
- Manipulate basic Species
- Global Species
- Defining Advanced Species
- Defining GUI Experiment
- Exploring Models
- Optimizing Model Section
- Multi-Paradigm Modeling
- Manipulate OSM Data
- Diffusion
- Using Database
- Using FIPA ACL
- Using BDI with BEN
- Using Driving Skill
- Manipulate dates
- Manipulate lights
- Using comodel
- Save and restore Simulations
- Using network
- Headless mode
- Using Headless
- Writing Unit Tests
- Ensure model's reproducibility
- Going further with extensions
- Built-in Species
- Built-in Skills
- Built-in Architecture
- Statements
- Data Type
- File Type
- Expressions
- Exhaustive list of GAMA Keywords
- Installing the GIT version
- Developing Extensions
- Introduction to GAMA Java API
- Using GAMA flags
- Creating a release of GAMA
- Documentation generation