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BasicProgrammingConceptsInGAML
In this part, we will focus on the very basic structures in GAML, such as how to declare a variable, how to use loops, or how to manipulate lists. We will overfly quickly all those basic programming concepts, admitting that you already have some basics in coding.
- Variables
- Declare variables using facet
- Operators in GAMA
- Conditional structures
- Loop
- Manipulate containers
- Random values
Variables are declared very easily in GAML, starting with the keyword for the type, following by the name you want for your variable.
NB: The declaration has to be inside the global
, the experiment
, or the species
scope.
typeName myVariableName;
All the "basic" types are present in GAML:int
, float
, string
, bool
(see the data type page for information about all the available datatype).
The operator for the affectation in GAML is <-
(the operator =
is used to test the equality).
int integerVariable <- 3;
float floatVariable <- 2.5;
string stringVariable <- "test"; // you can also write simple ' : <- 'test'
bool booleanVariable <- true; // or false
To follow the behavior of a variable, we can write
their value in the console. Let's go back to our basic skeleton of a model, and let's create a reflex in the global scope (to be short, a reflex is a procedure that is executed in each step. We will come back to this concept later). The write
statement works very easily, simply writing down the keyword write
and the name of the variable we want to be displayed.
model firstModel
global {
int integerVariable <- 3;
float floatVariable <- 2.5;
string stringVariable <- "test"; // you can also write simple ' : <- 'test'
bool booleanVariable <- true; // or false
reflex writeDebug {
write integerVariable;
write floatVariable;
write stringVariable;
write booleanVariable;
}
}
experiment myExperiment {}
The statement write
is overloaded for each type of variable (even for the more complex type, such as containers).
Note that before being initialized, a variable has the value nil
.
reflex update {
string my_string;
write my_string; // this will write "nil".
int my_int;
write my_int; // this will write "0", which is the default value for int.
}
nil
is also a literal you can use to initialize your variables (you can learn more about the concept of literal in this page).
reflex update {
string my_string <- "a string";
my_string <- nil;
write my_string; // this will write "nil".
int my_int <- 6;
my_int <- nil;
write my_int; // this will write "0", which is the default value for int.
}
Another variable type you should know is the point
type. This type of variable is used to describe coordinates. It is in fact a complex variable, composed of two float variables (or three if you are working in 3D). To declare it, you have to use the curly bracket {
:
point p <- {0.2,2.4};
The first field is related to the x
value, and the second one to the y
value. You can easily get this value as follows:
point p <- {0.2,2.4};
write p.x; // the output will be 0.2
write p.y; // the output will be 2.4
You cannot modify directly the value. But if you want, you can do a simple operation to get what you want:
point p <- {0.2,2.4};
p <- p + {0.0,1.0};
write p.y; // the output will be 3.4
When manipulating float values, you can specify the dimension (also called unit) of your value. Dimensions are preceded by # or ° (exactly the same).
float a <- 5°m;
float b <- 4#cm;
float c <- a + b; // c is equal to 5.0399999 (it's not equal to 5.04 because it is a float value, not as precise as int)
Facets are used to describe the behavior of a variable during its declaration, by adding the keyword facet
just after the variable name, followed by the value you want for the facet (or also just after the initial value). See the page related to the variable declaration for all the facets.
type variableName <- initialValue facet1:valueForFacet1 facet2:valueForFacet2;
// or:
type variableName facet1:valueForFacet1 facet2:valueForFacet2;
variableName <- initialValue;
You can use the facet update
if you want the value of your variable to change at every simulation step. For example, to increment your integer variable each step, you can do as follow:
int integerVariable <- 3 min: 0 max: 10 update: integerVariable+1;
// nb: the operator "++" doesn't exist in gaml.
You can use the facets min
and max
to constraint the value in a specific range of values:
int integerVariable <- 3 min: 0 max: 10 update: integerVariable+1;
// the result will be 3 - 4 - 5 - 6 - 7 - 8 - 9 - 10 - 10 - 10 - ...
The facet among
can also be useful (that can be seen as an enum):
string fruits <- "banana" among: ["pear","apple","banana"];
In GAML language, you can use a lot of different operators. An operator is a function, i.e. a way to get the result of a computation. All of them are listed in this page, but here are the most useful ones:
The basic arithmetical operators, such as +
(add), -
(substract), *
(multiply), /
(divide), ^
(power) are used this way:
// FirstOperand BinaryOperator SecondOperand
// --> ex: 5 * 3; // return 15
int fif <- 5 * 3;
Some other operators, such as cos
(cosinus), sin
(sinus), tan
(tangent), sqrt
(square root), round
(rounding) etc... are used this way:
// UnaryOperator(Operand)
// --> ex: sqrt(49); // return 7.0
float sq <- sqrt(49);
Logical operators such as and
(and), or
(inclusive or) are used the same way as basic arithmetical operators. The operator !
(negation) has to be placed just before the operand. They return a boolean result.
// FirstOperand Operator SecondOperand
// --> ex: true or false; // return true
// NegationOperator Operand
// --> ex: !(true or false); // return false
The comparison operators !=
(different than), <
(smaller than), <=
(smaller of equal), =
(equal), >
(bigger than), >=
(bigger or equal) are used the same way as basic arithmetical operators:
// FirstOperand Operator SecondOperand
// --> ex: 5 < 3; // return false
bool cmp <- 5 < 3;
You can cast an operand to a special type using casting operator:
// Operator(Operand);
// --> ex: int(2.1); // return 2
int intTwo <- int(2.1);
A lot of other operators exist in GAML. The standard way to use those operators is as followed:
Operator(FirstOperand,SecondOperand,...) --> ex: rnd(1,8);
Some others are used in a more intuitive way:
FirstOperand Operator SecondOperand --> ex: 2[6,4,5] contains(5);
You can write conditionals with if/else in GAML:
if (integerVariable<0) {
write "my value is negative !! The exact value is " + integerVariable;
}
else if (integerVariable>0) {
write "my value is positive !! The exact value is " + integerVariable;
}
else if (integerVariable=0) {
write "my value is equal to 0 !!";
}
else {
write "hey... This is not possible, right ?";
}
GAML also accepts ternary operator:
stringVariable <- (booleanVariable) ? "booleanVariable = true" : "booleanVariable = false";
Loops in GAML are designed by the keyword loop
. As for variables, a loop have multiple facets to determine its behavior:
- The facet
times
, to repeat a fixed number of times a set of statements:
loop times: 2 {
write "helloWorld";
}
// the output will be helloWorld - helloWorld
- The facet
while
, to repeat a set of statements while a condition is true:
loop while: true {
}
// infinity loop
- The facet
from
/to
, to repeat a set of statements while an index iterates over a range of values with a fixed step of 1:
loop i from: 0 to: 5 {
write i;
}
// the output will be 0 - 1 - 2 - 3 - 4 - 5
- The facet
from
/to
combine with the facetstep
to choose the step:
loop i from: 0 to: 5 step: 2 {
write i;
}
// the output will be 0 - 2 - 4
- The facet
over
to browse containers, as we will see in the next part.
loop i over: [0, 2, 4] {
write i;
}
// the output will be 0 - 2 - 4
Nb: you can interrupt a loop at any time by using the break
statement.
We saw in the previous parts "simple" types of variable. You also have multiple containers types, such as list, matrix, map, pair... In this section, we will only focus on the container list
(you can learn the other by reading the section about datatypes).
How to declare a list?
To declare a list, you can either or not specify the type of the data of its elements:
list<int> listOfInt <- [5,4,9,8];
list listWithoutType <- [2,4.6,"oij",["hoh",0.0]];
How to know the number of elements of a list?
To know the number of elements of a list, you can use the operator length
that returns the number of elements (note that this operator also works with strings).
int numberOfElements <- length([12,13]); // will return 2
int numberOfElements <- length([]); // will return 0
int numberOfElements <- length("stuff"); // will return 5
There is another operator, empty
, that returns you a boolean telling you if the list is empty or not.
bool isEmpty <- empty([12,13]); // will return false
bool isEmpty <- empty([]); // will return true
bool isEmpty <- empty("stuff"); // will return false
How to get an element from a list?
To get an element from a list by its index, you have to use the operator at
(nb: it is indeed an operator and not a facet, so no ":" after the keyword).
int theFirstElementOfTheList <- [5,4,9,8] at 0; // this will return 5
int theThirdElementOfTheList <- [5,4,9,8] at 2; // this will return 9
How to know the index of an element of a list?
You can know the index of the first occurrence of a value in a list using the operator index_of
.
You can know the index of the last occurrence of a value in a list using the operator last_index_of
.
int result <- [4,2,3,4,5,4] last_index_of 4; // result equals 5
int result <- [4,2,3,4,5,4] index_of 4; // result equals 0
How to know if an element exists in a list?
You can use the operator contains
(return a boolean):
bool result <- [{1,2}, {3,4}, {5,6}] contains {3,4}; // result equals true
How to insert/remove an element to/from a list?
For those operation, you can use dedicated statements. The statements add
and put
are used to insert/modify an element, while the statement remove
is used to remove an element. Here are some examples of how to use those 3 statements with the most common facets:
list<int> list_int <- [1,5,7,6,7];
remove from:list_int index:1; // remove the 2nd element of the list
write list_int; // the output is : [1,7,6,7]
remove item:7 from:list_int; // remove the 1st occurrence of 7
write list_int; // the output is : [1,6,7]
add item:9 to: list_int at: 2; // add 9 in the 3rd position
write list_int; // the output is : [1,6,9,7]
add 0 to: list_int; // add 0 in the last position
write list_int; // the output is : [1,6,9,7,0]
put 3 in: list_int at: 0; // put 3 in the 1st position
write list_int; // the output is : [3,6,9,7,0]
put 2 in: list_int key: 2; // put 2 in the 3rd position
write list_int; // the output is : [3,6,2,7,0]
Note that the +
and -
operators can be used to add an element at the end of a list and to remove the last element of a list:
list<int> list_int <- [1,5,7,6,7];
list_int <- list_int + 8;
write list_int; // the output is : [1,5,7,6,7,8]
list_int <- list_int - 7;
write list_int; // the output is : [1,5,7,6,8]
How to add 2 lists?
You can add 2 lists by creating a third one and browsing the 2 first one, but you can do it much easily by using the operator +
:
list<int> list_int1 <- [1,5,7,6,7];
list<int> list_int2 <- [6,9];
list<int> list_int_result <- list_int1 + list_int2;
How to browse a list?
You can use the facet over
of a loop:
list<int> exampleOfList <- [4,2,3,4,5,4];
loop i over: exampleOfList {
write i;
}
// the output will be 4 - 2 - 3 - 4 - 5 - 4
How to filter a list?
If you want to get all the elements of a list that fulfill a particular condition, you need the operator where. In the condition, you can design all the elements of a particular list by using the pseudo-variable each
as followed:
list<int> exampleOfList <- [4,2,3,4,5,4] where (each <= 3);
// the list is now [2,3]
Other useful operators for the manipulation of lists:
Here are some other operators which can be useful to manipulate lists: sort
, sort_by
, shuffle
, reverse
, collect
, accumulate
, among
. Please read the GAML Reference if you want to know more about those operators.
When you will implement your model, you will have to manipulate some random values quite often.
To get a random value in a range of value, use the operator rnd
. You can use this operator in many ways:
int var0 <- rnd (2); // var0 equals 0, 1 or 2
float var1 <- rnd (1000) / 1000; // var1 equals a float between 0 and 1 with a precision of 0.001
float var2 <- rnd(3.4); // var4 equals a random float between 0.0 and 3.4
point var3 <- rnd ({2.0, 4.0}, {2.0, 5.0, 10.0}, 1); // var2 equals a point with x = 2.0, y equal to 2.0, 3.0 or 4.0 and z between 0.0 and 10.0 every 1.0
float var4 <- rnd (2.0, 4.0, 0.5); // var3 equals a float number between 2.0 and 4.0 every 0.5
int var5 <- rnd (2, 4); // var7 equals 2, 3 or 4
int var6 <- rnd (2, 12, 4); // var5 equals 2, 6 or 10
point var7 <- rnd ({2.5,3, 0.0}); // var6 equals {x,y} with x in [0.0,2.0], y in [0.0,3.0], z = 0.0
point var8 <- rnd ({2.0, 4.0}, {2.0, 5.0, 10.0}); // var8 equals a point with x = 2.0, y between 2.0 and 4.0 and z between 0.0 and 10.0
float var9 <- rnd (2.0, 4.0); // var9 equals a float number between 2.0 and 4.0
Use the operator flip
if you want to pick a boolean value with a certain probability:
bool result <- flip(0.2); // result will have 20% of chance to be true
You can use randomness in list, by using the operator shuffle
, or also by using the operator among
to pick randomly one (or several) element of your list:
list TwoRandomValuesFromTheList <- 2 among [5,4,9,8];
// the list will be for example [5,9].
You can use probabilistic laws, using operators such as gauss
, poisson
, binomial
, or truncated_gauss
(we invite you to read the documentation for those operators).
- 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