Julia Syntax: Comparison with Fortran

This is a simple cheatsheet and some performance comparison for scientific programmers who are interested in discover Julia. It is not an exhaustive list. This page is inspired from A Cheatsheet for Fortran 2008 Syntax: Comparison with Python 3.

	Fortran	Julia
Top-level constructs
the main program	program my_program ... end program	function my_program() ... end my_program() Not required but it is recommended to use a function for your main program
modules	module my_module ... end module my_module	module MyModule ... end
subroutines	subroutine my_subroutine ... end subroutine my_subroutine	function my_subroutine! ... end The bang in the function name is a convention if a function mutates one or more of its arguments. The convention is that the modified arguments should (if possible) come first.
functions	function f(x) result(res) res = ... end function f	function my_function(x) ... return res end
Generic interface	module cube_root_functions interface cube_root function s_cube_root(x) real :: s_cube_root real, intent(in) :: x end function s_cube_root function d_cube_root(x) double precision :: d_cube_root double precision, intent(in) :: x end function d_cube_root end interface end module cube_root_functions function s_cube_root(x) real :: s_cube_root real, intent(in) :: x s_cube_root = x ** (1.0/3.0) end function s_cube_root function d_cube_root(x) double precision :: d_cube_root double precision, intent(in) :: x d_cube_root = x ** (1.0d0/3.0d0) end function d_cube_root	cube_root( x :: Float32 ) :: Float32 = x^(1/3) cube_root( x :: Float64 ) :: Float64 = x^(1/3)
submodules	module main_module ... contains <submodule statements> end module main_module	module MainModule ... module SubModule ... end end
import statement	use my_module use my_module, only : fun1, var1	using MyModule import MyModule: fun1, var1
call subroutines and functions	call my_subroutine(args) my_function(args)	my_function(args)
abort a program	stop	exit()
inline comments	! This is a comment	# This is a comment
include external source files	include 'source_file_name'	include("source_file_name")
Control flow patterns
if construct	if <logical expr> then ... else if <logical expr> then ... else ... end if	if <logical expr> ... elseif <logical expr> ... else ... end
case construct	select case <expr> case <value> ... case <value> ... case default ... end select	Not supported. Possible alternative is to use the ternary ? : syntax: function case(x) x == 1 ? println(1) : x + 1 == 3 ? println(2) : x == 3 ? println(3) : println("greater than 3") end
do construct	do i = start_value, end_value, step ... end do	for i in start:step:end ... end
do while construct	do while <logical expr> ... end do	while <logical expr> ... end
break from a loop	exit	break
leave this iteration and continue to the next iteration	cycle	continue
Data types
declaration	integer(kind=8) :: n = 0 real(kind=8) :: x = 0.	n = 0 n :: Int64 = 0 x = 0. x :: Float64 = 0.
named constants	integer, parameter :: answer = 42 real(8), parameter :: pi = 4d0 * atan(1d0)	const answer = 42 pi is a named constant in Julia standard.
complex number	complex :: z = (1., -1.)	z = 1 - 1im z = complex(1, -1)
string	character(len=10) :: str_fixed_length character(len=:), allocatable :: str_var_length	string = "this is a string"
pointer	real, pointer :: p real, target :: r p => r	p = Ref(r)
boolean	.true. .false.	true false
logical operators	.not. .and. .or. .eqv. .neqv.	! && || Other logical operators do not have built-in support.
equal to	==, .eq.	==
not equal to	/=, .ne.	!==
greater than	>, .gt.	>
less than	<, .lt.	<
greater than or equal to	>=, .ge.	>=
less than or equal to	<=, .ge.	<=
array declaration	real(8), dimension(3) :: a = [1., 2., 3.]	a = [1., 2., 3.]
string array declaration	character(len=20), dimension(3, 4) :: char_arr	char_arr = String[] push!(char_arr, new_string) There is no easy way to preallocate space for strings.
elementwise array operations	a op b op can be +, -, *, /, **, =, ==, etc. This is supported since the Fortran 90 standard.	Supported by using the broadcast operator `.`and the `f.(x)` syntax
first element	a(1)	a[1] (or a[begin] for general indexing)
slicing	a(1:5) This slice includes a(5).	a[1:5] (or @view(a[1:5]) for non-allocating slicing) This slice includes a[5].
slicing with steps	a(1:100:2)	a[1:2:100]
size	size(a)	length(a)
shape	shape(a)	size(a)
shape along a dimension	size(a, dim)	size(a, dim)
Type conversion
to integer by truncation	int(x)	trunc(Int, x )
to integer by rounding	nint()	round()
integer to float	real(a[, kind])	float()
complex to real	real(z[, kind])	real()
to complex	cmplx(x [, y [, kind]])	complex()
to boolean	logical()	Bool()
Derived data types
definition	type Point real(8) :: x, y end type Point	struct Point x :: Float64 y :: Float64 end
instantiation	type(Point) :: point1 = Point(-1., 1.)	point1 = Point(-1., 1.)
get attributes	point1%x point1%y	point1.x point1.y
array of derived type	type(Point), dimension(:), allocatable :: point_arr	point_arr = Vector{Point}
type bound procedures (aka class method)	Assume that Circle has a type bound procedure (subroutine) print_area. type(Circle) :: c call c%print_area	Assume that Circle has a method print_area(c :: Circle). c = Circle() print_area(c)
Built-in mathematical functions
functions with the same names	abs(), cos(), cosh(), exp(), floor(), log(), log10(), max(), min(), sin(), sinh(), sqrt(), sum(), tan(), tanh(), acos(), asin(), atan()	Have the same name in Julia.
functions with different names	aimag() atan2(x, y) ceiling() conjg(z) modulo() call random_number()	imag() atan(x, y) ceil() conj() mod(), % Random.rand()
Built-in string functions
string length	len()	length()
string to ASCII code	iachar()	Int()
ASCII code to string	achar()	String()
string slicing	Same as 1D array slicing.	Same as 1D array slicing.
find the position of a substring	index(string, substring)	findfirst(substring, string)
string concatenation	"hello" // "world"	"hello" * "world" string("hello", "world")
Array constructs
where construct	where a > 0 b = 0 elsewhere b = 1 end where	b[a .> 0] .= 0 b[a .<= 0] .= 1 or (faster - does not allocate an intermediate array): for i in eachindex(a) a[i] > 0 ? b[i] = 0 : b[i] = 1 end
Comprehension	integer, parameter :: n = 20 integer, parameter :: m = n*(n+1)/2 integer :: i, j complex, dimension(m) :: a a = [ ( ( cmplx(i,j), i=j,n), j=1,n) ]	a = [ complex(i,j) for j=1:n for i=j:n]
forall construct	real, dimension(10, 10) :: a = 0 int :: i, j ... forall (i = 1:10, j = 1:10, i <= j) a(i, j) = i + j end forall	a = zeros(Float32, 10, 10) for i in 1:10, j in 1:10 if i <= j a[i, j] = i + j end end
CPU time	call cpu_time()	time = @elapsed begin ... end
command line arguments	call command_argument_count() call get_command() call get_command_argument()	For basic parsing, use ARGS
Input/output
print	print fmt, <output list>	println()
read from the command prompt	read fmt, <input list>	readline()
open a file	open(unit, file, ...)	f = open(file, 'r')
read from a file	read(unit, fmt, ...) <input list>	read(f) readlines(f)
write to a file	write(unit, fmt, ...) <output list>	write(f, ...)
close a file	close(unit, ...)	close(f)
file inquiry	inquire(unit, ...)	isfile("my_file.txt")
backspace in a file	backspace(unit, ...)	skip(f, -1)
end of file (EOF)	endfile(unit, ...)	seekend(f)
return to the start of a file	rewind(unit, ...)	seekstart(f)

Maxwell parallel solver in 2D

Here an example of a Fortran to Julia translation. We use the Yee numerical scheme FDTD: Finite-Difference Time-Domain method and MPI topology. You can find a serial version and a parallel version using MPI library.

Test your MPI.jl installation with

$ mpirun -np 4 julia --project hello_mpi.jl
Hello world, I am 0 of 4
Hello world, I am 3 of 4
Hello world, I am 1 of 4
Hello world, I am 2 of 4

Performances (without disk IO)

On small program like this in Julia is really fast.

Serial computation

1200 x 1200 and 1000 iterations.

• julia -O3 --check-bounds=no maxwell_serial.jl : 14 seconds
• make && time ./maxwell_serial_fortran : 31 seconds

1200 x 1200 on 9 processors and 1000 iterations

• make && time mpirun -np 9 ./maxwell_mpi_fortran : 7 seconds
• mpirun -np 9 julia --project -O3 --check-bounds=no : 5 seconds

Plot the magnetic field

Uncomment the plot_fields call in Julia programs or change idiag value in input_data for fortran.

gnuplot bz.gnu