Basics & Program Structure
Program Structure & Hello World
Every Fortran program starts with 'program NAME' and ends with 'end program NAME'. 'implicit none' is MANDATORY in modern Fortran — it forces explicit declaration of all variables (without it, Fortran uses implicit typing where variables starting with i-n are integer, others real, which is a major source of bugs). The 'contains' block separates executable code from internal procedures (subroutines/functions defined inside the program). Comments start with '!'. Free source form (Fortran 90+) uses .f90 extension; columns don't matter. Compile with gfortran/ifort.
program hello
! A complete Fortran program structure
implicit none
! declarations go here
integer :: status = 0
print *, "Hello, World!" ! list-directed output to stdout
! executable statements
call do_work(status)
print *, "Exit status: ", status
contains
subroutine do_work(st)
integer, intent(out) :: st
st = 0
print *, "Working..."
end subroutine do_work
end program hello
! Compile: gfortran hello.f90 -o hello
! Run: ./helloVariables & Intrinsic Types
Fortran has 5 intrinsic types: integer, real, complex, character, logical. 'kind' selects precision/size — use kind=8 for 64-bit (or better, use selected_real_kind/iso_fortran_env for portability). Real literals need a kind suffix: 3.14_8 (not just 3.14). Double precision is legacy syntax for real(kind=8). Complex literals use (real, imag) form. Logical values are .true. / .false. (with dots). Character strings have a fixed 'len' unless declared with len=: and allocatable (deferred-length, Fortran 2003+). Always initialize with the matching kind suffix to avoid silent precision loss.
program variables
implicit none
! Integer types
integer :: count = 0
integer(kind=8) :: big = 9223372036854775807_8 ! 64-bit
! Real types
real :: x = 3.14 ! default (often 32-bit)
real(kind=8) :: y = 2.718281828459045_8 ! double precision
double precision :: z = 1.0d0
! Complex
complex :: c = (1.0, 2.0) ! 1 + 2i
complex(kind=8) :: cw = (1.0_8, 2.0_8)
! Character
character(len=20) :: name = "Alice"
character(len=:), allocatable :: flexible ! deferred length
! Logical
logical :: flag = .true.
! Print all
print *, count, big
print *, x, y, z
print *, c, cw
print *, name, flag
end program variablesConstants & Parameters
Constants use the 'parameter' attribute and must be initialized at declaration. They cannot be modified — the compiler can optimize and inline them. Use SCREAMING_SNAKE_CASE by convention. character(*) means 'take the length from the initializer' (handy for string constants). Parameters are commonly used for array sizes, physical constants, and enum-like integer codes. Fortran 2003+ also has proper ENUM types but parameter integers remain the idiomatic choice. Parameters can be used in array dimension declarations and other constant-expression contexts.
program constants
implicit none
! Named constants via 'parameter' attribute
integer, parameter :: MAX_SIZE = 100
real, parameter :: PI = 3.14159265
real, parameter :: E = 2.718281828
character(*), parameter :: APP_NAME = "MyApp"
! Using parameters
real :: arr(MAX_SIZE)
arr = 0.0
print *, APP_NAME, " size=", MAX_SIZE
print *, "Circumference: ", 2.0 * PI * 5.0
! Enum-like via parameter
integer, parameter :: SUNDAY = 1, MONDAY = 2, TUESDAY = 3
integer :: day = MONDAY
print *, "Day code: ", day
end program constantsOperators & Expressions
Fortran operators: arithmetic (+ - * / **), with ** for exponentiation (unique to Fortran). Integer division truncates toward zero — use real(a)/b for true division. Two relational syntaxes: modern (< > == /= <= >=) and legacy (.lt. .gt. .eq. .ne. .le. .ge.). Logical: .and. .or. .not. .eqv. (equivalence) .neqv. (exclusive-or). String concatenation uses //; trim() removes trailing spaces (Fortran pads fixed-length strings with spaces). mod vs modulo: mod follows truncated division sign, modulo follows floored division — they differ for negative operands.
program operators
implicit none
integer :: a = 17, b = 5
real :: x = 2.0
! Arithmetic
print *, a + b, a - b, a * b ! 22 12 85
print *, a / b ! 3 (integer division!)
print *, real(a) / b ! 3.4 (cast to real)
print *, a ** 2 ! 289 (exponentiation)
print *, mod(a, b) ! 2 (modulo)
print *, modulo(a, b) ! 2 (differs for negatives)
! Relational (both forms work)
print *, a > b, a < b ! T F
print *, a .gt. b, a .lt. b ! T F (old form)
print *, a == b, a /= b ! F T
! Logical
print *, (a > 0) .and. (b > 0) ! T
print *, (a > 0) .or. (b < 0) ! T
print *, .not. (a > 0) ! F
print *, (a > 0) .eqv. (b > 0) ! T (equivalence)
! String concatenation
character(10) :: s1 = "Hello", s2 = "World"
print *, trim(s1) // " " // trim(s2) ! Hello World
end program operatorsIntrinsic Functions & Math
Fortran has a rich set of intrinsic (built-in) functions. Math: abs, sqrt, exp, log (natural), log10, sin/cos/tan/asin/acos/atan/atan2, sinh/cosh/tanh. Rounding: int (truncate), nint (nearest), floor, ceiling. Conversion: real(), int(), cmplx(). Inquiry: size, shape, huge (max value), tiny (min positive), kind. All trig functions take radians. atan2(y, x) returns the angle in the correct quadrant (unlike atan). Use huge/tiny to check range limits. Intrinsics are elemental — they work on arrays element-wise automatically.
program intrinsics
implicit none
real :: x = -3.7, y = 2.5
! Math functions
print *, abs(x) ! 3.7
print *, sqrt(2.0) ! 1.414...
print *, exp(1.0) ! 2.718... (e^x)
print *, log(2.0) ! 0.693... (natural log)
print *, log10(1000.0) ! 3.0
print *, sin(3.14159/2) ! 1.0
print *, cos(0.0) ! 1.0
print *, atan2(1.0,1.0) ! 0.785... (pi/4)
! Rounding
print *, int(x) ! -3 (truncate toward zero)
print *, nint(x) ! -4 (nearest integer)
print *, floor(x) ! -4 (toward -inf)
print *, ceiling(x) ! -3 (toward +inf)
print *, abs(x), max(x, y), min(x, y) ! 3.7 2.5 -3.7
! Type conversion
print *, real(5) ! 5.0
print *, int(3.9) ! 3
! Inquiry
real :: arr(10)
print *, size(arr) ! 10
print *, huge(1) ! 2147483647
print *, tiny(1.0) ! smallest positive real
end program intrinsicsControl Flow
If...Then...Else
Block IF: 'if (cond) then ... else if (cond) then ... else ... end if'. Each branch needs 'then' (except the final else). Logical IF is a one-liner: 'if (cond) statement' (no 'then'/'end if'). Conditions use relational operators (< > == /= <= >= or .lt. .gt. .eq. .ne. .le. .ge.) combined with .and. .or. .not. 'stop' terminates the program (optionally with a message/code). The arithmetic IF (if (x) label1, label2, label3) is deleted in Fortran 2018 — never use it. Always use 'implicit none' so undeclared variables are caught.
program if_demo
implicit none
integer :: score = 85
character(1) :: grade
! Multi-branch if/else if/else
if (score >= 90) then
grade = 'A'
else if (score >= 80) then
grade = 'B'
else if (score >= 70) then
grade = 'C'
else if (score >= 60) then
grade = 'D'
else
grade = 'F'
end if
print *, "Score ", score, " -> Grade ", grade
! Logical if (single statement, no 'then')
if (score < 0 .or. score > 100) stop "Invalid score"
! Arithmetic if (OBSOLETE - avoid)
! if (x) 10, 20, 30 ! jump to label based on sign
end program if_demoSelect Case (Switch)
select case is Fortran's switch statement. Cases can be single values (case (3)), lists (case (1, 3, 5)), or ranges (case (4:5) means 4 to 5 inclusive). case default is the fallback. Unlike C, there's NO fall-through — each branch is independent and only one runs. Works with integer, character, and logical types (NOT real). Character ranges use ASCII ordering ('A':'Z'). For floating-point comparisons, use if/else. select case is more efficient than long if/else if chains for integer/char dispatch (compiler may use jump tables).
program case_demo
implicit none
integer :: day = 3
character(1) :: ch = 'A'
character(10) :: day_name
! Integer select case
select case (day)
case (1)
day_name = "Monday"
case (2)
day_name = "Tuesday"
case (3)
day_name = "Wednesday"
case (4:5)
day_name = "Thu/Fri"
case (6:7)
day_name = "Weekend"
case default
day_name = "Invalid"
end select
print *, day_name
! Character select case (case-insensitive via pre-upper)
select case (ch)
case ('A':'Z')
print *, "Uppercase letter"
case ('a':'z')
print *, "Lowercase letter"
case ('0':'9')
print *, "Digit"
case default
print *, "Other"
end select
! Logical select case
select case (day > 5)
case (.true.)
print *, "Weekend!"
case (.false.)
print *, "Weekday"
end select
end program case_demoDo Loops (Counted)
Counted DO loop: 'do var = start, end, step' (step defaults to 1). The loop runs while var <= end (for positive step) or var >= end (for negative step). var is incremented AFTER each iteration. Implied-do constructs [(expr, var=start,end)] are powerful for array initialization and I/O lists. Named loops (outer: do ... end do outer) allow targeting cycle/exit to a specific nesting level. The loop variable is automatically defined; in Fortran it retains its final value after the loop. Avoid modifying the loop variable inside the loop body.
program do_loops
implicit none
integer :: i, j, total
! Basic counted loop: do var = start, end [, step]
do i = 1, 5
print *, i ! 1 2 3 4 5
end do
! With step
do i = 10, 1, -1 ! countdown
print *, i
end do
do i = 0, 100, 25 ! 0 25 50 75 100
print *, i
end do
! Implied-do (inline, for array init / I/O)
integer :: arr(5) = [(i**2, i=1,5)] ! 1 4 9 16 25
print *, arr
print *, (i, i=1,3) ! 1 2 3
! Nested loops with labels (for cycle/exit targeting)
total = 0
outer: do i = 1, 3
inner: do j = 1, 3
total = total + i*j
end do inner
end do outer
print *, "Total: ", total
end program do_loopsDo While & Infinite Loops
do while (cond) ... end do is a pre-test loop (checks condition before each iteration; may run zero times). For post-test behavior, use do ... if (cond) exit ... end do. The bare 'do ... end do' is an infinite loop — you MUST have an exit statement (otherwise infinite). 'exit' leaves the innermost loop (or a named loop). Named loops (factorial_loop:) let exit target an outer loop. Use do while when the iteration count is unknown and depends on a condition; use counted do when the count is known up front.
program while_demo
implicit none
integer :: n, count
real :: x, sum
! do while: pre-test loop
n = 1024
count = 0
do while (n > 1)
n = n / 2
count = count + 1
end do
print *, "log2(1024) = ", count ! 10
! Infinite loop with exit
sum = 0.0
do
read(*, *) x
if (x < 0) exit ! leave loop
sum = sum + x
end do
print *, "Sum: ", sum
! do ... end do with conditional exit
n = 1
factorial_loop: do
if (n > 10) exit factorial_loop
print *, n, factorial(n)
n = n + 1
end do factorial_loop
contains
recursive function factorial(n) result(f)
integer, intent(in) :: n
integer :: f
if (n <= 1) then
f = 1
else
f = n * factorial(n-1)
end if
end function factorial
end program while_demoCycle, Exit & Loop Control
cycle skips the rest of the current iteration and jumps to the next (like 'continue' in C/Python). exit breaks out of the loop entirely (like 'break'). Both target the innermost loop by default, but with named loops (search: do ... end do search) you can target an outer loop: 'exit search' or 'cycle search'. This is essential for breaking out of nested loops cleanly. Use cycle for filtering (skip unwanted iterations) and exit for early termination (search found, error detected). Named loops make nested control flow explicit and readable.
program loop_control
implicit none
integer :: i, j
! cycle: skip to next iteration (like 'continue' in C)
do i = 1, 10
if (mod(i, 2) == 0) cycle ! skip even numbers
print *, i ! 1 3 5 7 9
end do
! exit: break out of loop (like 'break' in C)
do i = 1, 100
if (i * i > 50) then
print *, "Stopped at i=", i
exit
end if
end do
! Named loops: cycle/exit can target outer loops
search: do i = 1, 5
do j = 1, 5
if (i + j == 7) then
print *, "Found: ", i, "+", j, "= 7"
exit search ! break out of OUTER loop
end if
end do
end do search
! Early exit from a search
integer :: arr(10) = [3, 1, 4, 1, 5, 9, 2, 6, 5, 3]
do i = 1, size(arr)
if (arr(i) == 9) then
print *, "Found 9 at index ", i
exit
end if
end do
end program loop_controlArrays & Vector Operations
Array Declaration & Initialization
Fortran arrays are 1-indexed by default (lower bound = 1), but you can specify a custom lower bound: a(0:4) has indices 0..4. Multi-dimensional arrays use (rows, cols) ordering — column-major storage (first index varies fastest in memory). Initialize with array constructors [1,2,3] or implied-do [(expr, i=start,end)]. reshape fills a multi-dim array from a 1D list. size() returns total elements; lbound/ubound return lower/upper bounds. shape() returns the shape as a 1D array. Arrays are 'whole-array' — you can assign and operate on them without explicit loops.
program array_decl
implicit none
! Declaration with dimension
integer :: a(5) ! 1D, indices 1..5
integer :: b(0:4) ! 1D, indices 0..4 (custom lower bound)
real :: c(3, 4) ! 2D, 3 rows x 4 cols
real, dimension(10) :: d ! using dimension attribute
! Initialization at declaration
integer :: x(5) = [1, 2, 3, 4, 5]
integer :: y(5) = [(i*2, i=1,5)] ! implied-do: 2 4 6 8 10
integer :: z(5) = 0 ! all zeros
real :: m(2,2) = reshape([1,2,3,4], [2,2])
! Allocation later
print *, size(x), lbound(x), ubound(x) ! 5 1 5
print *, size(c, dim=1) ! 3 (rows)
print *, size(c, dim=2) ! 4 (cols)
! Array of characters
character(10) :: names(3) = ["Alice", "Bob", "Carol"]
print *, names(2) ! Bob
end program array_declArray Sections & Vector Subscripts
Array sections (slicing) use a(start:end:stride) syntax — all parts optional. Stride can be negative (reverse). Vector subscripts allow gathering/scattering with an index array: a(idx) returns [a(idx(1)), a(idx(2)), ...]. Sections can be assigned to: a(2:4) = [99,98,97]. The 'where' construct is array-level conditional assignment (like numpy where). Fortran's array operations are vectorized — no explicit loops needed for element-wise ops. This is Fortran's killer feature for numerical code: clean, math-like syntax that compilers auto-vectorize.
program array_sections
implicit none
integer :: a(10) = [(i, i=1,10)]
integer :: b(5)
integer :: idx(3) = [2, 5, 7]
! Array sections (slicing): a(start:end[:stride])
print *, a(3:7) ! 3 4 5 6 7
print *, a(1:10:2) ! 1 3 5 7 9 (stride 2)
print *, a(:5) ! 1 2 3 4 5 (start defaults to 1)
print *, a(6:) ! 6 7 8 9 10 (end defaults to ubound)
print *, a(::3) ! 1 4 7 10
print *, a(10:1:-1) ! 10 9 8 ... 1 (reverse)
! Vector subscript (gather)
b = a(idx) ! b = [a(2), a(5), a(7)] = [2, 5, 7]
print *, b
! Assigning to a section
a(2:4) = [99, 98, 97]
print *, a(1:5) ! 1 99 98 97 5
! 2D sections
real :: m(4,4) = 0.0
m(2:3, 2:3) = 1.0 ! set 2x2 sub-block
print *, m(2,2), m(3,3) ! 1.0 1.0
! Where construct (masked array assignment)
where (a > 50) a = 0 ! set elements > 50 to 0
end program array_sectionsMultidimensional Arrays & Matrices
Fortran stores arrays column-major (first index varies fastest in memory) — opposite to C. reshape fills in column-major order, so reshape([1,2,3,4],[2,2]) gives [[1,3],[2,4]]. matmul(A,B) is true matrix multiplication (linear algebra); A*B is element-wise (Hadamard) — they are NOT the same! transpose(A) returns the transpose. Reductions: sum, product, maxval, minval, maxloc, minloc, count — all support dim= to reduce along one axis. For high performance, write loops in column-major order (innermost loop over the first index) to be cache-friendly.
program matrices
implicit none
real :: A(3,3), B(3,3), C(3,3)
integer :: i, j
! Initialize with implied-do
A = reshape([(real(i), i=1,9)], [3,3])
! A = 1 4 7
! 2 5 8
! 3 6 9 (column-major fill!)
! Identity matrix
B = 0.0
do i = 1, 3
B(i,i) = 1.0
end do
! Matrix multiplication (intrinsic)
C = matmul(A, B) ! A * I = A
print *, C(1,1), C(2,2) ! 1.0 5.0
! Transpose
print *, transpose(A)(1,:) ! 1 2 3 (first row of A^T)
! Element-wise operations
C = A + B ! element-wise add
C = A * 2.0 ! scalar multiply
C = A * B ! element-wise (NOT matmul!)
! Array reduction along a dimension
print *, sum(A, dim=1) ! column sums: 6 15 24
print *, sum(A, dim=2) ! row sums: 12 15 18
print *, maxval(A) ! 9.0
print *, maxloc(A) ! 3 3 (location of max)
! Reshape
integer :: flat(6) = [1,2,3,4,5,6]
integer :: mat(2,3)
mat = reshape(flat, [2,3])
end program matricesAllocatable Arrays (Dynamic)
allocatable arrays are the modern way to do dynamic memory in Fortran — safer than pointers (no memory leaks, automatic deallocation at scope exit). Declare with allocatable attribute and a deferred shape (:, (:,:), etc.). allocate() with stat= catches errors (always check!). deallocate() frees explicitly. Fortran 2003+ supports automatic reallocation on assignment: flex = [flex, 4] grows the array. allocated() checks if currently allocated. Allocatables are preferred over pointers for dynamic arrays because the compiler tracks and frees them automatically — no leaks, no dangling pointers.
program alloc_demo
implicit none
integer, allocatable :: arr(:), matrix(:,:)
integer :: n, m, i, stat
! Get size from user
print *, "Enter size:"
read(*, *) n
m = n * 2
! Allocate
allocate(arr(n), matrix(n, m), stat=stat)
if (stat /= 0) then
print *, "Allocation failed!"
stop 1
end if
! Use the arrays
arr = [(i, i=1, n)]
matrix = 0.0
do i = 1, n
matrix(i, :) = i
end do
print *, size(arr), size(matrix, dim=2)
print *, allocated(arr) ! T
! Deallocate (or let it auto-deallocate at scope exit)
deallocate(arr, matrix)
print *, allocated(arr) ! F
! Automatic reallocation on assignment (Fortran 2003)
integer, allocatable :: flex(:)
flex = [1, 2, 3] ! auto-allocates to size 3
flex = [flex, 4, 5] ! reallocates to size 5: 1 2 3 4 5
print *, flex
deallocate(flex)
end program alloc_demoArray Intrinsic Functions
Fortran's array intrinsics are its superpower. Reductions: sum, product, maxval, minval, maxloc (index of max), minloc, count (count of true), any (exists), all (every). All support mask= for conditional reduction. pack() gathers elements where mask is true (like numpy compress); unpack() scatters. cshift/eoshift rotate arrays (circular vs end-off). merge(a, b, mask) does element-wise selection. Note: Fortran has NO built-in sort — you must write one (or use a library). These intrinsics are elemental and vectorizable, making Fortran code both clean and fast.
program array_funcs
implicit none
integer :: a(5) = [3, 1, 4, 1, 5, 9, 2, 6]
! Wait, let's fix size
integer :: b(8) = [3, 1, 4, 1, 5, 9, 2, 6]
integer :: c(5) = [10, 20, 30, 40, 50]
logical :: mask(5) = [.true., .false., .true., .false., .true.]
! Inquiry
print *, size(b) ! 8
print *, shape(b) ! 8
print *, lbound(b), ubound(b) ! 1 8
! Reductions
print *, sum(b) ! 31
print *, product(c) ! 120000000
print *, maxval(b), minval(b) ! 9 1
print *, maxloc(b) ! 6 (index of max)
print *, minloc(b) ! 2 (index of min, first occurrence)
print *, count(b > 3) ! 5 (number of true elements)
print *, any(b > 8) ! T (at least one)
print *, all(b > 0) ! T (all of them)
! With mask
print *, sum(b, mask=b > 3) ! sum of elements > 3
print *, pack(b, b > 3) ! compact array of elements > 3
print *, unpack([1,2], mask, 0) ! spread values per mask
! Manipulation
print *, cshift(b, 2) ! circular shift left by 2
print *, eoshift(b, 2) ! end-off shift left by 2 (fills 0)
print *, merge(b, c, mask) ! element-wise: b where mask true, else c
! Sorting (Fortran 2003+)
integer :: sorted(8)
sorted = b
call sort_array(sorted) ! custom sort (no built-in sort)
end program array_funcsStrings & Character Handling
Character Declaration & Length
Fortran strings are FIXED-LENGTH by default — shorter strings are padded with spaces to fill the declared length. character(N) or character(len=N) declares length N. character(*) takes length from context (parameter initializer or dummy argument). character(:), allocatable enables deferred-length dynamic strings (Fortran 2003+) — the string reallocates on assignment. len() returns declared length; len_trim() returns length without trailing spaces. trim() returns the string without trailing spaces (but result is still fixed-length in context). For variable-length text processing, use allocatable deferred-length strings.
program char_decl
implicit none
! Fixed-length strings
character(10) :: s1 = "Hello"
character(len=20) :: s2 = "World"
character(20) :: s3 ! len= keyword optional
! Deferred-length (allocatable) - Fortran 2003+
character(:), allocatable :: flex
flex = "Dynamic" ! len=7
flex = "Now longer string" ! reallocates to len=18
print *, len(flex) ! 18
! Array of strings
character(15) :: names(3) = ["Alice", "Bob", "Carol"]
! Single character
character(1) :: ch = 'A'
character :: ch2 = 'B' ! len=1 default
print *, s1 ! "Hello " (padded to 10)
print *, trim(s1) ! "Hello" (no padding)
print *, len(s1), len_trim(s1) ! 10 5
print *, names(2) ! "Bob" (padded)
end program char_declString Concatenation & Operations
String concatenation uses // operator. repeat(s, n) repeats a string n times. Substrings use s(start:end) — 1-indexed, INCLUSIVE on both ends (unlike Python). s(8:) means from position 8 to end; s(:5) means from start to position 5. index(s, sub) returns the position of the first occurrence of sub (0 if not found, case-sensitive). scan(s, set) returns position of first character IN set; verify(s, set) returns first character NOT in set. adjustl/adjustr shift leading/trailing spaces. Fortran strings are NOT null-terminated like C — length is tracked separately.
program string_ops
implicit none
character(20) :: first = "John", last = "Doe"
character(50) :: full
! Concatenation with //
full = first // " " // last ! "John Doe"
print *, trim(full)
! Repeat
print *, repeat("-", 30) ! 30 dashes
! Substring (1-indexed, inclusive)
character(20) :: s = "Hello, World!"
print *, s(1:5) ! "Hello"
print *, s(8:12) ! "World"
print *, s(8:) ! "World!" (to end)
print *, s(:5) ! "Hello" (from start)
! Index (find substring)
print *, index(s, "World") ! 8 (position, 0 if not found)
print *, index(s, "world") ! 0 (case-sensitive)
print *, scan(s, "aeiou") ! 2 (first vowel position)
print *, verify(s, "abcdefg") ! 1 (first char NOT in set)
! Length
print *, len_trim(s) ! 13
print *, adjustl(s) ! left-justify
print *, adjustr(s) ! right-justify
end program string_opsIntrinsic String Functions
iachar(c) returns the ASCII code of a character; achar(i) is the inverse. (ichar/char are processor-dependent — prefer iachar/achar for portability.) Fortran has NO built-in case conversion — use iachar/achar manually (A-Z is 65-90, a-z is 97-122, difference is 32). Lexicographic comparison: lge/lgt/lle/llt (lexically greater/less than) handle strings of different lengths gracefully. Internal I/O (read/write to a string instead of a file) is the idiomatic way to convert between strings and numbers: read(str, *) num and write(str, fmt) num. I0 format gives minimal-width integers (no padding).
program string_funcs
implicit none
character(20) :: s = "Hello World"
integer :: i
character(1) :: ch
! Character code conversion
print *, iachar('A') ! 65 (ASCII code)
print *, achar(66) ! 'B' (from ASCII code)
print *, ichar('A') ! processor-dependent (use iachar for ASCII)
! Case conversion (manual - no built-in)
do i = 1, len_trim(s)
ch = s(i:i)
if (ch >= 'A' .and. ch <= 'Z') then
s(i:i) = achar(iachar(ch) + 32) ! to lowercase
end if
end do
print *, s ! "hello world"
! Comparison
print *, lge("apple", "banana") ! F (lexicographic >=)
print *, lgt("zebra", "apple") ! T
print *, lle("abc", "abcd") ! T (<=)
print *, llt("abc", "abd") ! T (<)
! String to number conversion (internal read)
character(20) :: num_str = "3.14159"
real :: pi_val
read(num_str, *) pi_val
print *, pi_val * 2 ! 6.28318
! Number to string (internal write)
character(20) :: out_str
integer :: n = 42
write(out_str, '(I0)') n ! I0 = minimal-width integer
print *, "Number: " // trim(out_str)
end program string_funcsString Formatting
Format specifications live in a string: '(I5, F8.2, A)'. I=integer, F=fixed-point real, E=exponential, ES=scientific (mantissa 1-10), A=character, X=space, /=newline. Width comes first (I5 = width 5), then optional .m for min digits (I5.3). I0 means minimal width (no padding). ES gives proper scientific notation (1.23E+6) vs E (0.12E+7). Repeats: 3I4 = three integers each width 4. String literals in format: '("text")'. Format can be a string variable, a * (list-directed, compiler chooses), or a label (statement number). For clean output, prefer I0 for integers and F or ES for reals.
program format_demo
implicit none
integer :: n = 42
real :: pi = 3.14159265
real :: big = 1234567.89
character(20) :: name = "Alice"
! Format specifiers
! Iw - integer, width w
! Iw.m - integer, width w, at least m digits
! Fw.d - fixed-point real, width w, d decimals
! Ew.d - exponential, width w, d decimals
! Aw - character, width w
! A - character, default width
! nX - n spaces
! / - newline
write(*, '(I5)') n ! " 42"
write(*, '(I5.3)') n ! " 042"
write(*, '(I0)') n ! "42" (minimal)
write(*, '(F10.4)') pi ! " 3.1416"
write(*, '(E12.4)') big ! " 0.1235E+07"
write(*, '(ES12.4)') big ! " 1.2346E+06" (scientific)
write(*, '(A10)') name ! " Alice"
write(*, '(A, I3)') "n=", n ! "n= 42"
! Multiple items
write(*, '(A, I3, A, F8.4)') "n=", n, " pi=", pi
! Repeated format: 3I4 = three integers width 4
write(*, '(3I4)') 1, 2, 3 ! " 1 2 3"
! Newline and spacing
write(*, '("Name: ", A, /, "Age: ", I3)') name, n
! List-directed (default format)
print *, name, n, pi
end program format_demoParsing & Tokenizing
Fortran has NO built-in split/tokenize — you must write it manually using index() and substrings. The pattern: find the delimiter with index, extract the token with substring, advance past the delimiter, repeat. For key=value pairs, find '=' with index and split into key (before) and value (after). trim() removes trailing spaces; adjustl() removes leading spaces. For robust parsing, also handle empty tokens and whitespace. Alternatively, use internal reads with format specifiers for structured data, or read from a string as if it were a file. Libraries like split() exist in some Fortran frameworks but aren't standard.
program parse_demo
implicit none
character(100) :: line = "name=Bob,age=30,city=NYC"
character(50) :: token
integer :: pos, start, end
! Split by comma
start = 1
do
end = index(line(start:), ",")
if (end == 0) then
! last token
token = line(start:)
call process(trim(token))
exit
end if
token = line(start:start+end-2)
call process(trim(token))
start = start + end
end do
contains
subroutine process(t)
character(*), intent(in) :: t
integer :: eq_pos
eq_pos = index(t, "=")
if (eq_pos > 0) then
print *, "Key: ", trim(t(:eq_pos-1)), &
" Value: ", trim(t(eq_pos+1:))
end if
end subroutine process
end program parse_demo
! Output:
! Key: name Value: Bob
! Key: age Value: 30
! Key: city Value: NYCProcedures: Functions & Subroutines
Functions
Functions return a value and are used in expressions (like math functions). Modern syntax: 'function name(args) result(var)' — the result variable is what gets returned. intent(in) marks read-only arguments (the compiler enforces this). Functions can return scalars OR arrays (use size() of input to size the output). Functions should be PURE (no side effects) — don't modify global state or do I/O in a function. Internal procedures (in 'contains' block) have access to the host's variables (host association). For external procedures, use an interface block to specify the signature.
program func_demo
implicit none
! Function declared in interface or as external
print *, add(3, 4) ! 7
print *, square(5) ! 25
print *, distance(0.0, 0.0, 3.0, 4.0) ! 5.0
contains
! Basic function with result clause
function add(a, b) result(c)
integer, intent(in) :: a, b
integer :: c
c = a + b
end function add
! Function with result named same as function (legacy)
function square(x) result(y)
integer, intent(in) :: x
integer :: y
y = x * x
end function square
! Real function
function distance(x1, y1, x2, y2) result(d)
real, intent(in) :: x1, y1, x2, y2
real :: d
d = sqrt((x2-x1)**2 + (y2-y1)**2)
end function distance
! Array-valued function
function reverse(arr) result(rev)
integer, intent(in) :: arr(:)
integer :: rev(size(arr))
integer :: i, n
n = size(arr)
do i = 1, n
rev(i) = arr(n-i+1)
end do
end function reverse
end program func_demoSubroutines & Intent
Subroutines are called with 'call' and don't return a value — they modify arguments in place. Use subroutines when: (1) you need to modify multiple arguments, (2) the operation is a 'command' not a 'computation', (3) returning an array-valued result is awkward. intent attributes document and enforce argument direction: intent(in) = read-only (compiler error if you assign to it), intent(out) = write-only (undefined on entry, must be set before return), intent(inout) = read-write. Always specify intent — it catches bugs and enables optimization. Subroutines can modify arrays passed to them (no copy made if they're contiguous).
program sub_demo
implicit none
integer :: x = 10, y = 20
real :: arr(5) = [1.0, 2.0, 3.0, 4.0, 5.0]
! Subroutines are called with 'call'
call swap(x, y)
print *, x, y ! 20 10
call scale_array(arr, 2.0)
print *, arr ! 2 4 6 8 10
call fill_zero(arr)
print *, arr ! 0 0 0 0 0
contains
subroutine swap(a, b)
integer, intent(inout) :: a, b ! read AND write
integer :: tmp
tmp = a
a = b
b = tmp
end subroutine swap
subroutine scale_array(a, factor)
real, intent(inout) :: a(:)
real, intent(in) :: factor
a = a * factor ! whole-array operation
end subroutine scale_array
subroutine fill_zero(a)
real, intent(out) :: a(:) ! write-only (output)
a = 0.0
end subroutine fill_zero
end program sub_demoPure & Elemental Functions
pure functions have NO side effects: no I/O, no global variable modification, no stop, can only call other pure procedures. They enable compiler optimization (parallelization, common subexpression elimination) and are required in some contexts (e.g., DO CONCURRENT). elemental functions are written for SCALARS but automatically work on arrays element-wise — write once, use for both. pure elemental combines both. Use pure for any function that's truly a math function (no side effects). Use elemental when the operation naturally applies element-wise to arrays (math functions, conversions). The compiler can auto-vectorize elemental calls on arrays.
program pure_demo
implicit none
real :: a(5) = [1.0, 2.0, 3.0, 4.0, 5.0]
real :: b(5)
integer :: i
! Pure function: no side effects, no I/O
b = square_arr(a)
print *, b ! 1 4 9 16 25
! Elemental function: works on scalars AND arrays automatically
b = cube(a) ! applies cube() element-wise
print *, b ! 1 8 27 64 125
print *, cube(2.0) ! also works on scalar: 8.0
contains
! Pure: no side effects, no I/O, no stop, only pure calls
pure function square_arr(x) result(y)
real, intent(in) :: x(:)
real :: y(size(x))
y = x * x
end function square_arr
! Elemental: scalar signature, but works on arrays too
elemental function cube(x) result(y)
real, intent(in) :: x
real :: y
y = x * x * x
end function cube
! Pure elemental: both
pure elemental double precision function sq(x) result(y)
double precision, intent(in) :: x
double precision :: y
y = x * x
end function sq
end program pure_demoOptional & Keyword Arguments
optional arguments let callers omit them. Use present(arg) inside the procedure to check if an argument was provided — accessing an absent optional is undefined behavior. Keyword arguments (name="value") allow passing arguments in any order and make calls self-documenting. Once you use a keyword, all subsequent arguments must also use keywords. Optional arguments must come after all required ones in the signature. Default values are implemented via present() checks (Fortran has no built-in default syntax). Keyword + optional together enable flexible APIs: callers specify only what they need.
program optional_demo
implicit none
! All arguments after the first optional must also be optional
print *, greet("Alice") ! Hello, Alice!
print *, greet("Bob", "Hi") ! Hi, Bob!
print *, greet("Carol", greeting="Hey") ! keyword argument
print *, greet(greeting="Welcome", name="Dave") ! all keywords
! With present() check
call log_msg("Starting up")
call log_msg("Error!", level=2)
call log_msg("Debug info", level=0, file="debug.log")
contains
function greet(name, greeting) result(msg)
character(*), intent(in) :: name
character(*), intent(in), optional :: greeting
character(50) :: msg
character(20) :: g
if (present(greeting)) then
g = greeting
else
g = "Hello"
end if
msg = trim(g) // ", " // name // "!"
end function greet
subroutine log_msg(message, level, file)
character(*), intent(in) :: message
integer, intent(in), optional :: level
character(*), intent(in), optional :: file
integer :: lvl
lvl = 1
if (present(level)) lvl = level
print *, "[L", lvl, "] ", trim(message)
end subroutine log_msg
end program optional_demoInternal & Recursive Procedures
Internal procedures (inside 'contains') have host association — they can read AND modify the host program's variables (like closures). Use them for helpers that need host state. recursive procedures must be declared with the 'recursive' prefix (Fortran 90/2003); Fortran 2018 makes recursion default. For mutual recursion, use an interface block to declare the forward reference. Recursion is elegant but can be slow (function call overhead) and risky (stack overflow for deep recursion). For factorial/fibonacci, iterative versions are faster and safer. Use recursion for naturally recursive problems (tree traversal, divide-and-conquer) with bounded depth.
program nested_demo
implicit none
integer :: counter = 0 ! host variable
! Internal procedures (in contains) access host variables
call increment
call increment
print *, counter ! 2
! Recursive function
print *, factorial(5) ! 120
print *, fib(10) ! 55
! Mutual recursion (needs forward declaration)
print *, is_even(4) ! T
contains
subroutine increment
counter = counter + 1 ! modifies host's counter
end subroutine increment
recursive function factorial(n) result(f)
integer, intent(in) :: n
integer :: f
if (n <= 1) then
f = 1
else
f = n * factorial(n-1)
end if
end function factorial
recursive function fib(n) result(f)
integer, intent(in) :: n
integer :: f
if (n < 2) then
f = n
else
f = fib(n-1) + fib(n-2)
end if
end function fib
! Mutual recursion with interface
recursive function is_even(n) result(r)
integer, intent(in) :: n
logical :: r
interface
recursive function is_odd(m) result(ro)
integer, intent(in) :: m
logical :: ro
end function is_odd
end interface
if (n == 0) then
r = .true.
else
r = is_odd(n-1)
end if
end function is_even
end program nested_demoModules & Encapsulation
Module Basics & Use
Modules are Fortran's primary encapsulation mechanism (replacing common blocks and external procedures). A module file contains: (1) declarations (constants, variables, derived types), (2) a 'contains' block with procedures. Use 'use module_name' to import; 'use module_name, only: x, y' imports only specific entities (recommended — avoids namespace pollution). Module variables are persistent (static) and shared across all procedures that use the module. Modules provide explicit interfaces (the compiler checks argument types), unlike external procedures. Always compile module files before files that use them. 'implicit none' in a module propagates to all its procedures.
! geometry.f90 - module file
module geometry
implicit none
private ! default: everything private
public :: circle_area, circle_perimeter, PI
! Module-level constants (persistent)
real, parameter :: PI = 3.14159265
contains
function circle_area(r) result(a)
real, intent(in) :: r
real :: a
a = PI * r * r
end function circle_area
function circle_perimeter(r) result(p)
real, intent(in) :: r
real :: p
p = 2.0 * PI * r
end function circle_perimeter
end module geometry
! main.f90 - using the module
program use_module
use geometry, only: circle_area, circle_perimeter, PI
implicit none
real :: r = 5.0
print *, "Area: ", circle_area(r) ! 78.5398
print *, "Perimeter: ", circle_perimeter(r) ! 31.4159
print *, "PI: ", PI
end program use_module
! Compile: gfortran geometry.f90 main.f90 -o mainAccess Control (Public/Private)
Access control: 'private' makes entities module-internal; 'public' exports them. Default can be set at module level ('private' then selectively 'public :: ...') — this is best practice (explicit interface). Derived type components can be private even if the type itself is public — callers can use the type but not access internals directly; they must go through procedures. 'save' makes module variables persistent (they retain values between calls) — module variables are saved by default. 'final' defines a destructor (called when the object goes out of scope). This encapsulation enables true OOP with invariants enforced through procedures.
module bank_account
implicit none
private ! default: everything private
! Explicitly export:
public :: account_t, deposit, withdraw, get_balance
! Derived type - can expose type but hide internals
type :: account_t
private ! components are private
real :: balance = 0.0
integer :: id = 0
contains
procedure :: balance => get_bal ! type-bound procedure
final :: cleanup ! destructor
end type account_t
! Module-level counter (private, not exported)
integer, save :: next_id = 1000
contains
! Constructor (factory function)
function create_account(initial) result(acc)
type(account_t) :: acc
real, intent(in) :: initial
acc%balance = initial
acc%id = next_id
next_id = next_id + 1
end function create_account
subroutine deposit(acc, amount)
type(account_t), intent(inout) :: acc
real, intent(in) :: amount
acc%balance = acc%balance + amount
end subroutine deposit
function get_bal(acc) result(b)
class(account_t), intent(in) :: acc
real :: b
b = acc%balance
end function get_bal
subroutine cleanup(acc)
type(account_t) :: acc
! cleanup code (e.g., log closure)
end subroutine cleanup
end module bank_accountDerived Types in Modules
Derived types defined in modules can have: type-bound procedures (procedure :: name => impl), constructors (via overloaded interface with the type name), and allocatable components. The 'class(keyword)' in type-bound procedures enables polymorphism (the actual type may be a subclass). Type-bound procedures are called as obj%method(args) — OOP syntax. Overloading the type name as an interface lets you have multiple constructors (vector_from_array, vector_from_size). Allocatable components are automatically allocated/deallocated. This is modern Fortran OOP: encapsulation, methods, constructors, and polymorphism, all within the module system.
module vector_mod
implicit none
private
public :: vector_t, vector_add, vector_scale
! Derived type with type parameters (Fortran 2003)
type :: vector_t
real, allocatable :: data(:)
integer :: length = 0
contains
procedure :: norm => vector_norm
procedure :: print => vector_print
end type vector_t
! Constructor interface (overloaded)
interface vector_t
procedure vector_from_array
procedure vector_from_size
end interface vector_t
contains
function vector_from_array(arr) result(v)
real, intent(in) :: arr(:)
type(vector_t) :: v
v%data = arr
v%length = size(arr)
end function
function vector_from_size(n, fill) result(v)
integer, intent(in) :: n
real, intent(in) :: fill
type(vector_t) :: v
allocate(v%data(n))
v%data = fill
v%length = n
end function
function vector_norm(self) result(n)
class(vector_t), intent(in) :: self
real :: n
n = sqrt(sum(self%data**2))
end function
subroutine vector_print(self)
class(vector_t), intent(in) :: self
print *, "Vector(len=", self%length, "): ", self%data
end subroutine
function vector_add(a, b) result(c)
type(vector_t), intent(in) :: a, b
type(vector_t) :: c
c%data = a%data + b%data
c%length = a%length
end function
function vector_scale(a, s) result(c)
type(vector_t), intent(in) :: a
real, intent(in) :: s
type(vector_t) :: c
c%data = a%data * s
c%length = a%length
end function
end module vector_modGeneric Procedures & Overloading
Generic interfaces provide ad-hoc polymorphism (overloading): one name dispatches to different specific procedures based on argument types. The 'interface name / module procedure proc1, proc2 / end interface' block lists all the specific procedures. The compiler picks the matching one by argument type/rank at compile time. All specific procedures in a generic must have DISTINCT signatures (distinguishable by argument types) — otherwise ambiguity. This is how Fortran does operator/function overloading without templates. Generic dispatch is resolved at compile time (no runtime overhead). Use generics to provide a uniform API across types.
module generics_mod
implicit none
private
public :: print_value, add
! Generic interface: one name, multiple specific procedures
interface print_value
module procedure print_int
module procedure print_real
module procedure print_str
module procedure print_int_array
end interface print_value
interface add
module procedure add_int
module procedure add_real
module procedure add_arrays
end interface add
contains
subroutine print_int(x)
integer, intent(in) :: x
print *, "Integer: ", x
end subroutine
subroutine print_real(x)
real, intent(in) :: x
print *, "Real: ", x
end subroutine
subroutine print_str(s)
character(*), intent(in) :: s
print *, "String: ", trim(s)
end subroutine
subroutine print_int_array(arr)
integer, intent(in) :: arr(:)
print *, "Array: ", arr
end subroutine
function add_int(a, b) result(c)
integer, intent(in) :: a, b
integer :: c
c = a + b
end function
function add_real(a, b) result(c)
real, intent(in) :: a, b
real :: c
c = a + b
end function
function add_arrays(a, b) result(c)
real, intent(in) :: a(:), b(:)
real :: c(size(a))
c = a + b
end function
end module generics_mod
program use_generics
use generics_mod
implicit none
call print_value(42) ! Integer: 42
call print_value(3.14) ! Real: 3.14
call print_value("Hello") ! String: Hello
call print_value([1,2,3]) ! Array: 1 2 3
print *, add(2, 3) ! 5
print *, add(2.5, 3.5) ! 6.0
end program use_genericsOperator Overloading
Operator overloading lets you define how +, -, *, /, ==, etc. work on your derived types. interface operator(+) / module procedure vec_add / end interface binds the + operator to a function. For binary operators, you can overload both orderings (vec*scalar and scalar*vec) with separate procedures. assignment(=) overloads the assignment operator (the procedure is a subroutine with intent(out) LHS and intent(in) RHS). This enables math-like syntax: c = a + b instead of c = vec_add(a, b). Use operator overloading for mathematical types (vectors, matrices, complex numbers) where it improves readability. Avoid overloading for non-obvious semantics. The structure constructor vec3(x,y,z) is built-in for derived types.
module vec_ops
implicit none
private
public :: vec3, operator(+), operator(*), assignment(=)
type :: vec3
real :: x, y, z
end type vec3
! Overload the + operator for vec3 + vec3
interface operator(+)
module procedure vec_add
end interface
! Overload * for vec3 * scalar and scalar * vec3
interface operator(*)
module procedure vec_scale_r
module procedure vec_scale_l
module procedure vec_dot
end interface
! Overload = for array-to-vec assignment
interface assignment(=)
module procedure arr_to_vec
end interface
contains
function vec_add(a, b) result(c)
type(vec3), intent(in) :: a, b
type(vec3) :: c
c = vec3(a%x+b%x, a%y+b%y, a%z+b%z)
end function
function vec_scale_r(v, s) result(r)
type(vec3), intent(in) :: v
real, intent(in) :: s
type(vec3) :: r
r = vec3(v%x*s, v%y*s, v%z*s)
end function
function vec_scale_l(s, v) result(r)
real, intent(in) :: s
type(vec3), intent(in) :: v
type(vec3) :: r
r = vec3(v%x*s, v%y*s, v%z*s)
end function
! vec3 * vec3 = dot product (scalar)
function vec_dot(a, b) result(d)
type(vec3), intent(in) :: a, b
real :: d
d = a%x*b%x + a%y*b%y + a%z*b%z
end function
subroutine arr_to_vec(v, arr)
type(vec3), intent(out) :: v
real, intent(in) :: arr(3)
v = vec3(arr(1), arr(2), arr(3))
end subroutine
end module vec_ops
program use_ops
use vec_ops
implicit none
type(vec3) :: a, b, c
a = vec3(1.0, 2.0, 3.0)
b = vec3(4.0, 5.0, 6.0)
c = a + b ! vec3 addition
print *, c%x, c%y, c%z ! 5 7 9
print *, a * 2.0 ! scale: 2 4 6
print *, 3.0 * b ! scale: 12 15 18
print *, a * b ! dot product: 32
end program use_opsDerived Types (Structs) & OOP
Defining Derived Types
Derived types are Fortran's structs (user-defined composite types). Define with 'type :: Name ... end type Name'. Components accessed with % (NOT . — that's for complex numbers). Structure constructor: Name(val1, val2) creates an instance. Components can have default values (= value in declaration). Whole-type assignment copies all components (deep copy for allocatable components). Arrays of derived types are supported. Derived types are the foundation for OOP in Fortran (with type-bound procedures, inheritance, polymorphism). Use % for component access: obj%field, obj%method(). The constructor syntax Name(args) is automatic unless you override it with an interface.
program derived_types
implicit none
! Basic derived type (struct)
type :: Point
real :: x, y
end type Point
! Type with default initialization
type :: Person
character(20) :: name = "Unknown"
integer :: age = 0
logical :: active = .true.
end type Person
! Declare and construct
type(Point) :: p1, p2
type(Person) :: alice, bob
! Structure constructor
p1 = Point(3.0, 4.0)
p2 = Point(0.0, 0.0)
alice = Person("Alice", 30, .true.)
bob = Person("Bob", 25) ! uses default for 'active'
! Access components with %
print *, p1%x, p1%y ! 3.0 4.0
print *, alice%name, alice%age ! Alice 30
print *, bob%active ! T (default)
! Modify components
p1%x = p1%x + 1.0
alice%age = 31
! Whole-type assignment (component-wise copy)
p2 = p1
print *, p2%x ! 4.0
! Array of derived types
type(Point) :: points(3)
points(1) = Point(1.0, 1.0)
points(2) = Point(2.0, 2.0)
points(3) = Point(3.0, 3.0)
print *, points(2)%y ! 2.0
end program derived_typesType Components & Constructors
Derived types can have: allocatable components (auto-managed memory), default-initialized components, type-bound procedures (methods), and finalizers (destructors). The 'interface TypeName / module procedure custom_init / end interface' overloads the structure constructor with a custom factory function. 'class(ClassName)' (vs 'type(ClassName)') in type-bound procedures enables polymorphism (the actual type may be a subclass). 'final' procedures run when an object goes out of scope (destructor) — use them to free resources. Allocatable components are automatically deallocated on finalization, but explicit finalizers are clearer for complex cleanup. block constructs allow declaring variables mid-code (Fortran 2008).
program type_components
implicit none
! Type with various component kinds
type :: Student
integer :: id
character(20) :: name
real, allocatable :: grades(:) ! allocatable component
integer :: num_grades = 0
contains
procedure :: add_grade
procedure :: average => student_avg
final :: student_finalize
end type Student
! Overloaded constructor
interface Student
module procedure student_init
end interface Student
type(Student) :: s
! Use custom constructor
s = Student(101, "Alice")
call s%add_grade(85.0)
call s%add_grade(92.0)
call s%add_grade(78.0)
print *, s%average() ! 85.0
contains
function student_init(id, name) result(s)
integer, intent(in) :: id
character(*), intent(in) :: name
type(Student) :: s
s%id = id
s%name = name
s%num_grades = 0
end function
subroutine add_grade(self, g)
class(Student), intent(inout) :: self
real, intent(in) :: g
integer :: n
n = self%num_grades
if (n == 0) then
allocate(self%grades(1))
else
! grow array
block
real, allocatable :: tmp(:)
tmp = self%grades
deallocate(self%grades)
allocate(self%grades(n+1))
self%grades(1:n) = tmp
end block
end if
self%num_grades = n + 1
self%grades(n+1) = g
end subroutine
function student_avg(self) result(avg)
class(Student), intent(in) :: self
real :: avg
if (self%num_grades > 0) then
avg = sum(self%grades) / self%num_grades
else
avg = 0.0
end if
end function
subroutine student_finalize(self)
type(Student) :: self
if (allocated(self%grades)) deallocate(self%grades)
end subroutine
end program type_componentsType-Bound Procedures (Methods)
Type-bound procedures are Fortran's methods: 'procedure :: method_name => implementation'. Call them as obj%method(args) — OOP syntax. The first argument is 'self' (the object), declared as 'class(TypeName)' (polymorphic) or 'type(TypeName)' (concrete). 'class' allows inheritance/polymorphism; 'type' is for non-extensible types. The '=> implementation' maps the method name to a specific procedure (allows renaming). final is the destructor. This example implements a dynamic stack with auto-growing array. Type-bound procedures give true OOP: encapsulation (data + methods together), message-passing syntax (obj%method), and polymorphism (via class). Always use class() for type-bound procedures to enable future inheritance.
module stack_mod
implicit none
private
public :: stack_t
type :: stack_t
integer, allocatable :: data(:)
integer :: top = 0
integer :: capacity = 0
contains
procedure :: push => stack_push
procedure :: pop => stack_pop
procedure :: peek => stack_peek
procedure :: is_empty => stack_is_empty
procedure :: size => stack_size
procedure :: clear => stack_clear
final :: stack_finalize
end type stack_t
interface stack_t
module procedure stack_init
end interface
contains
function stack_init(initial_cap) result(s)
integer, intent(in), optional :: initial_cap
type(stack_t) :: s
integer :: cap
cap = 16
if (present(initial_cap)) cap = initial_cap
allocate(s%data(cap))
s%capacity = cap
s%top = 0
end function
subroutine stack_push(self, val)
class(stack_t), intent(inout) :: self
integer, intent(in) :: val
if (self%top >= self%capacity) then
! grow
block
integer, allocatable :: tmp(:)
tmp = self%data
deallocate(self%data)
allocate(self%data(self%capacity * 2))
self%data(1:self%capacity) = tmp
self%capacity = self%capacity * 2
end block
end if
self%top = self%top + 1
self%data(self%top) = val
end subroutine
function stack_pop(self) result(val)
class(stack_t), intent(inout) :: self
integer :: val
if (self%top == 0) stop "Stack underflow"
val = self%data(self%top)
self%top = self%top - 1
end function
function stack_peek(self) result(val)
class(stack_t), intent(in) :: self
integer :: val
val = self%data(self%top)
end function
logical function stack_is_empty(self) result(r)
class(stack_t), intent(in) :: self
r = (self%top == 0)
end function
integer function stack_size(self) result(n)
class(stack_t), intent(in) :: self
n = self%top
end function
subroutine stack_clear(self)
class(stack_t), intent(inout) :: self
self%top = 0
end subroutine
subroutine stack_finalize(self)
type(stack_t) :: self
if (allocated(self%data)) deallocate(self%data)
end subroutine
end module stack_mod
program use_stack
use stack_mod
implicit none
type(stack_t) :: s
s = stack_t(8) ! initial capacity 8
call s%push(10)
call s%push(20)
call s%push(30)
print *, s%size() ! 3
print *, s%pop() ! 30
print *, s%pop() ! 20
print *, s%is_empty() ! F
end program use_stackInheritance & Polymorphism
Fortran OOP: 'type, extends(Parent) :: Child' creates a subclass (inheritance). 'type, abstract :: Name' with 'procedure(...), deferred :: method' defines an abstract base (like Java abstract class / C++ pure virtual). 'class(Base)' is polymorphic — can hold any subclass. Polymorphic dispatch: calling obj%method() invokes the subclass's override. 'select type (var => expr) / type is (ConcreteType) / end select' does runtime type checking (downcasting). Allocate with 'allocate(TypeName::var)' to create a polymorphic object of a specific concrete type. This is full OOP: inheritance, polymorphism, abstract types, and runtime dispatch — comparable to Java/C++.
module shapes
implicit none
private
public :: shape, circle, rectangle, shape_ptr
! Base type (abstract)
type, abstract :: shape
character(20) :: name
contains
procedure(area_if), deferred :: area
procedure(describe_if), deferred :: describe
procedure :: get_name => shape_get_name
end type shape
! Abstract interface (must be implemented by subclasses)
abstract interface
function area_if(self) result(a)
import :: shape
class(shape), intent(in) :: self
real :: a
end function area_if
subroutine describe_if(self)
import :: shape
class(shape), intent(in) :: self
end subroutine describe_if
end interface
! Derived type: circle extends shape
type, extends(shape) :: circle
real :: radius
contains
procedure :: area => circle_area
procedure :: describe => circle_describe
end type circle
! Derived type: rectangle extends shape
type, extends(shape) :: rectangle
real :: width, height
contains
procedure :: area => rect_area
procedure :: describe => rect_describe
end type rectangle
! Class pointer for polymorphism
type :: shape_ptr
class(shape), allocatable :: ptr
end type shape_ptr
contains
function shape_get_name(self) result(n)
class(shape), intent(in) :: self
character(20) :: n
n = self%name
end function
function circle_area(self) result(a)
class(circle), intent(in) :: self
real :: a
a = 3.14159265 * self%radius**2
end function
subroutine circle_describe(self)
class(circle), intent(in) :: self
print *, "Circle '", trim(self%name), "' r=", self%radius
end subroutine
function rect_area(self) result(a)
class(rectangle), intent(in) :: self
real :: a
a = self%width * self%height
end function
function rect_describe(self) result(s)
class(rectangle), intent(in) :: self
character(50) :: s
write(s, '("Rectangle ", F6.2, "x", F6.2)') self%width, self%height
end function
end module shapes
program use_polymorphism
use shapes
implicit none
type(shape_ptr) :: shapes_arr(2)
! Allocate concrete types into polymorphic container
allocate(circle::shapes_arr(1)%ptr)
select type(s => shapes_arr(1)%ptr)
type is (circle)
s%radius = 5.0
s%name = "C1"
end select
allocate(rectangle::shapes_arr(2)%ptr)
select type(s => shapes_arr(2)%ptr)
type is (rectangle)
s%width = 3.0
s%height = 4.0
s%name = "R1"
end select
! Polymorphic dispatch
block
integer :: i
do i = 1, 2
call shapes_arr(i)%ptr%describe
print *, "Area: ", shapes_arr(i)%ptr%area()
end do
end block
end program use_polymorphismNested Types & Arrays of Types
Derived types can be nested (composition): a type can have components of other derived types. Access nested components with chained %: emp%home%city. Structure constructors nest naturally: Employee(id, name, Address(...), salary). Arrays of derived types are supported: type(Employee) :: emps(N). You can extract an array of a single component: emps(:)%id gives an integer array. allocatable components allow dynamic-size collections (e.g., a department with a variable number of employees). This composition model is the foundation for building complex data structures (trees, graphs, lists) in Fortran. Use composition (has-a) over inheritance (is-a) when there's no clear subtype relationship.
program nested_types
implicit none
! Nested derived types
type :: Address
character(50) :: street
character(30) :: city
character(10) :: zip
end type Address
type :: Employee
integer :: id
character(30) :: name
type(Address) :: home ! nested type
real :: salary
end type Employee
type :: Department
character(30) :: name
type(Employee), allocatable :: employees(:) ! array of types
integer :: count = 0
end type Department
! Construct with nested structure constructor
type(Employee) :: emp
emp = Employee(101, "Alice", &
Address("123 Main St", "Springfield", "12345"), 75000.0)
! Access nested components
print *, emp%name ! Alice
print *, emp%home%city ! Springfield
print *, emp%home%zip ! 12345
! Department with array of employees
type(Department) :: dept
dept%name = "Engineering"
allocate(dept%employees(3))
dept%employees(1) = emp
dept%employees(2) = Employee(102, "Bob", &
Address("456 Oak Ave", "Shelbyville", "54321"), 68000.0)
dept%count = 2
! Iterate over array of types
block
integer :: i
do i = 1, dept%count
print *, dept%employees(i)%id, trim(dept%employees(i)%name), &
dept%employees(i)%home%city
end do
end block
! Array of derived type components
print *, dept%employees(1:2)%id ! array of id field
end program nested_typesFile I/O & Formatting
Opening & Closing Files
open() connects a file to a unit number. newunit=u lets the compiler pick a unique unit (avoids conflicts) — always prefer this over hard-coded unit numbers. status: 'old' (file must exist), 'new' (must not exist), 'replace' (delete + create), 'scratch' (temporary, auto-deleted on close). action: 'read', 'write', 'readwrite'. position: 'rewind' (start), 'append' (end), 'asis' (wherever). Always check iostat after open and read — non-zero means error (negative = EOF, positive = error). iomsg gives a descriptive error message. close() disconnects. For robust file handling, always check iostat and handle errors gracefully.
program file_open
implicit none
integer :: u, ios
character(100) :: msg
! newunit: compiler picks a unique unit number (Fortran 2008)
! status: 'old' (must exist), 'new' (must not exist),
! 'replace' (overwrite), 'scratch' (temporary)
! action: 'read', 'write', 'readwrite'
! position: 'rewind', 'append', 'asis'
open(newunit=u, file="data.txt", status="replace", &
action="write", iostat=ios, iomsg=msg)
if (ios /= 0) then
print *, "Open failed: ", trim(msg)
stop 1
end if
write(u, *) "First line"
write(u, *) "Second line"
close(u)
! Append to existing file
open(newunit=u, file="data.txt", status="old", &
action="write", position="append", iostat=ios)
if (ios == 0) then
write(u, *) "Appended line"
close(u)
end if
! Scratch file (auto-deleted on close)
open(newunit=u, status="scratch", action="readwrite")
write(u, *) "Temporary data"
rewind(u)
! read back...
close(u) ! file disappears
! Reading with end-of-file detection
open(newunit=u, file="data.txt", status="old", action="read")
do
read(u, '(A)', iostat=ios) msg
if (ios /= 0) exit ! EOF or error
print *, trim(msg)
end do
close(u)
end program file_openFormatted I/O
Format specifiers control I/O: '(A, I0, F8.2)'. A=character, I0=integer minimal width, F8.2=real width 8 with 2 decimals. write(unit, fmt) writes; read(unit, fmt) reads. unit=* means stdout/stdin. For files, use the unit from open(). List-directed I/O (*) is flexible: read(u, *) a, b, c reads comma/space-separated values automatically. For CSV, list-directed read works if values are comma-separated. Format strings can be reused: '(3I4)' applies I4 three times. Always match the format to the data type — mismatched formats cause runtime errors. For mixed text+numbers, read as a string then parse, or use explicit formats.
program formatted_io
implicit none
integer :: u, n = 42
real :: pi = 3.14159265
character(20) :: name = "Alice"
! Write formatted data to file
open(newunit=u, file="output.txt", status="replace")
write(u, '(A, I0)') "Count: ", n
write(u, '(A, F8.4)') "Pi: ", pi
write(u, '(A, A)') "Name: ", trim(name)
write(u, '(3(I0, 1X))') 1, 2, 3 ! "1 2 3 "
close(u)
! Read formatted data back
open(newunit=u, file="output.txt", status="old", action="read")
block
character(100) :: line
integer :: i
do i = 1, 5
read(u, '(A)') line
print *, trim(line)
end do
end block
close(u)
! Reading structured data
open(newunit=u, file="data.csv", status="replace")
write(u, '(I0, ",", I0, ",", I0)') 1, 10, 100
write(u, '(I0, ",", I0, ",", I0)') 2, 20, 200
close(u)
! Read back as numbers
open(newunit=u, file="data.csv", status="old", action="read")
block
integer :: a, b, c
! List-directed read handles commas as separators
read(u, *) a, b, c
print *, a, b, c ! 1 10 100
read(u, *) a, b, c
print *, a, b, c ! 2 20 200
end block
close(u)
end program formatted_ioUnformatted (Binary) I/O
Unformatted (binary) I/O is faster and more compact than formatted (text) I/O — no string conversion. form='unformatted' enables it. access='stream' (Fortran 2003) gives byte-stream access (like C file I/O, no record markers). access='sequential' (default) uses record markers (each write/read is a record with length prefixes) — portable within Fortran but not to other languages. For interoperability with C/Python, use stream access. Binary files are not human-readable but ideal for large numerical datasets. Always write metadata (array sizes, type info) before the data so you can read it back correctly. Unformatted I/O preserves full precision (no rounding from text conversion).
program binary_io
implicit none
integer :: u, i
real :: arr(5) = [1.0, 2.0, 3.0, 4.0, 5.0]
real :: arr_in(5)
integer :: n
! Write binary (unformatted) - faster, no format conversion
open(newunit=u, file="data.bin", status="replace", &
form="unformatted", access="stream")
write(u) size(arr) ! write the count first
write(u) arr ! write the whole array
close(u)
! Read binary back
open(newunit=u, file="data.bin", status="old", &
form="unformatted", access="stream", action="read")
read(u) n ! read the count
print *, "Count: ", n
read(u) arr_in ! read the array
print *, arr_in ! 1 2 3 4 5
close(u)
! Sequential unformatted (default) - with record markers
open(newunit=u, file="data_seq.bin", status="replace", &
form="unformatted") ! access defaults to "sequential"
do i = 1, 5
write(u) i, arr(i) ! each write is a "record"
end do
close(u)
! Read sequentially
open(newunit=u, file="data_seq.bin", status="old", &
form="unformatted", action="read")
do
read(u, iostat=i) n, arr_in(1)
if (i /= 0) exit
print *, n, arr_in(1)
end do
close(u)
end program binary_ioNamelist (Grouped I/O)
namelist groups variables for structured text I/O — like JSON/YAML but Fortran-native. Define with 'namelist /name/ var1, var2, ...'. write(u, nml=name) outputs in the format &NAME var=val, var=val, /. read(u, nml=name) parses it back. Namelist is perfect for configuration files: users edit a text file, the program reads it. Variables keep their declared values as defaults; only those in the file are overridden. The format is forgiving (whitespace-insensitive, optional commas). Namelist supports all intrinsic types and arrays. iostat catches parse errors. This is the easiest way to make a Fortran program configurable without writing a custom parser.
program namelist_demo
implicit none
! Namelist groups variables for easy I/O
integer :: max_iter = 100
real :: tolerance = 1.0e-6
logical :: verbose = .true.
character(20) :: method = "newton"
real :: params(3) = [0.1, 0.2, 0.3]
! Define a namelist group
namelist /config/ max_iter, tolerance, verbose, method, params
! Write namelist to file
block
integer :: u
open(newunit=u, file="config.nml", status="replace")
write(u, nml=config)
close(u)
end block
! The file looks like:
! &CONFIG
! MAX_ITER=100,
! TOLERANCE=1.0000000E-06,
! VERBOSE=T,
! METHOD="newton",
! PARAMS=0.100000, 0.200000, 0.300000,
! /
! Read namelist from file (overrides defaults)
block
integer :: u, ios
open(newunit=u, file="config.nml", status="old", action="read")
read(u, nml=config, iostat=ios)
close(u)
if (ios /= 0) then
print *, "Error reading config"
else
print *, "max_iter=", max_iter
print *, "tolerance=", tolerance
print *, "method=", trim(method)
print *, "params=", params
end if
end block
! User can edit config.nml in a text editor
! then re-run to pick up new values
end program namelist_demoInternal Files & Error Handling
Internal files let you read from / write to a character string instead of a file — Fortran's sprintf/sscanf. write(str, fmt) formats to a string; read(str, fmt) parses from a string. This is the standard way to convert between strings and numbers. Always use iostat for error handling: 0 = success, negative = EOF, positive = error. The legacy end= and err= labels work but iostat is cleaner (no goto). For robust parsing, check iostat after every read. Internal I/O is great for: building output strings, parsing user input, converting config file values. The string acts as an 'internal file' — same I/O statements, just a string destination.
program internal_io
implicit none
character(100) :: buffer
integer :: n = 42
real :: x = 3.14159
integer :: ios
! Internal write: format to a string (like sprintf)
write(buffer, '(A, I0, A, F8.4)') "n=", n, " x=", x
print *, trim(buffer) ! n=42 x= 3.1416
! Internal read: parse from a string (like sscanf)
character(50) :: input = "100 3.14 hello"
integer :: a
real :: b
character(20) :: c
read(input, *, iostat=ios) a, b, c
if (ios == 0) print *, a, b, trim(c) ! 100 3.14 hello
! Robust number parsing with error handling
character(20) :: num_str = "3.14abc"
real :: val
read(num_str, *, iostat=ios) val
if (ios /= 0) then
print *, "Parse error: '", trim(num_str), "' is not a number"
else
print *, "Value: ", val
end if
! End-of-file and error handling on file reads
block
integer :: u
character(100) :: line
open(newunit=u, file="data.txt", status="old", action="read")
do
read(u, '(A)', iostat=ios) line
if (ios < 0) then
print *, "End of file"
exit
else if (ios > 0) then
print *, "Read error at line"
exit
end if
print *, trim(line)
end do
close(u)
end block
! err= and end= labels (legacy style)
block
integer :: u, val
open(newunit=u, file="nums.txt", status="old", action="read")
do
read(u, *, end=100, err=200) val
print *, val
end do
100 print *, "Reached EOF"
close(u)
goto 300
200 print *, "Read error!"
close(u)
300 continue
end block
end program internal_ioNumerical Computing
Kind Parameters & Precision
Kind parameters control precision/size. Modern portable way: use iso_fortran_env (int32/int64, real32/real64/real128). Legacy: selected_real_kind(digits, exponent_range). real32 ≈ 7 significant digits, real64 ≈ 15 digits (double), real128 ≈ 33 digits (quad). CRITICAL: always append the kind suffix to literals (3.14_dp, not 3.14) — otherwise the literal is parsed as single precision THEN converted, losing digits. precision() returns significant digits; range() returns decimal exponent range. epsilon() gives the machine epsilon (smallest distinguishable increment). tiny/huge give min/max. For scientific computing, default to real64 (double precision).
program precision_demo
use iso_fortran_env, only: int32, int64, real32, real64, real128
implicit none
! Portable kind selection via iso_fortran_env
integer(kind=int32) :: i32 = 100
integer(kind=int64) :: i64 = 9223372036854775807_int64
real(kind=real32) :: r32 = 3.14159265_real32 ! single (~7 digits)
real(kind=real64) :: r64 = 3.14159265358979_real64 ! double (~15 digits)
real(kind=real128) :: r128 = 3.14159265358979_real128 ! quad (~33 digits)
! Legacy: selected_real_kind (still works)
integer, parameter :: dp = selected_real_kind(15, 307) ! double
integer, parameter :: sp = selected_real_kind(6, 37) ! single
real(kind=dp) :: pi = 3.14159265358979_dp
print *, "real32 precision: ", precision(r32), " range: ", range(r32)
print *, "real64 precision: ", precision(r64), " range: ", range(r64)
print *, "real128 precision: ", precision(r128)
! Epsilon and tiny
print *, "epsilon(r32): ", epsilon(r32) ! ~1.19e-7
print *, "epsilon(r64): ", epsilon(r64) ! ~2.22e-16
print *, "tiny(r64): ", tiny(r64) ! smallest positive
print *, "huge(i32): ", huge(i32) ! 2147483647
print *, "huge(i64): ", huge(i64)
! Always use _kind suffix on literals
! WRONG: real(kind=dp) :: x = 3.14 (loses precision!)
! RIGHT: real(kind=dp) :: x = 3.14_dp
end program precision_demoLinear Algebra (matmul, solve, BLAS)
Fortran has built-in linear algebra: matmul (matrix-matrix/matrix-vector multiply), dot_product, transpose. For solving linear systems (Ax=b), eigenvalues, SVD, etc., use LAPACK (the industry-standard Fortran library): dgesv solves Ax=b, dgesvd does SVD, dsyev does eigendecomposition. Link with -llapack -lblas. The example shows manual Gaussian elimination for a 3x3 system — for real work, use LAPACK (faster, more accurate with pivoting, handles any size). Fortran's column-major storage matches LAPACK's expectations natively (no transpose needed). matmul is optimized but for large matrices, BLAS dgemm is faster. Always check condition number for numerical stability.
program linalg
implicit none
real(8) :: A(3,3), B(3,3), C(3,3)
real(8) :: v(3), w(3), x(3)
real(8) :: det
integer :: i
! Initialize matrices
A = reshape([1,2,3, 4,5,6, 7,8,10], [3,3]) ! column-major fill
B = reshape([1,0,0, 0,1,0, 0,0,1], [3,3]) ! identity
! Matrix-matrix multiplication
C = matmul(A, B) ! A * I = A
print *, "A * I = A? ", all(abs(C - A) < 1e-10)
! Matrix-vector multiplication
v = [1.0, 2.0, 3.0]
w = matmul(A, v)
print *, "A * v = ", w ! 14 32 53
! Dot product
print *, "v . v = ", dot_product(v, v) ! 14
! Outer product
C = 0.0
do i = 1, 3
C(:,i) = v * v(i)
end do
! Transpose
C = transpose(A)
! Solve linear system Ax = b (need LAPACK or custom)
! Using LAPACK dgesv:
! call dgesv(n, nrhs, A, lda, ipiv, b, ldb, info)
! For demo, manual Gaussian elimination:
x = solve_3x3(A, v)
print *, "Solution: ", x
contains
function solve_3x3(A, b) result(x)
real(8), intent(inout) :: A(3,3)
real(8), intent(in) :: b(3)
real(8) :: x(3), M(3,4), factor
integer :: k, j
M(:,1:3) = A
M(:,4) = b
! Forward elimination
do k = 1, 2
do i = k+1, 3
factor = M(i,k) / M(k,k)
M(i,:) = M(i,:) - factor * M(k,:)
end do
end do
! Back substitution
x(3) = M(3,4) / M(3,3)
x(2) = (M(2,4) - M(2,3)*x(3)) / M(2,2)
x(1) = (M(1,4) - M(1,2)*x(2) - M(1,3)*x(3)) / M(1,1)
end function
end program linalgRandom Numbers
call random_number(x) fills x with uniform [0,1) reals — works on scalars or arrays. call random_seed(size=n) gets the seed size; random_seed(put=seed) sets the seed for reproducibility (essential for testing/debugging). For integers in [a,b]: a + int(r * (b-a+1)). For Gaussian (normal) random numbers, use the Box-Muller transform (shown) or the polar method. Fortran has no built-in normal distribution generator — implement it or use a library. For Monte Carlo simulations, set the seed for reproducibility, then run many trials. random_number is NOT cryptographically secure — use a crypto library for security. For parallel code, each image needs a distinct seed.
program random_demo
implicit none
real :: r
integer :: i, n = 10
real :: arr(10)
integer :: seed_size
integer, allocatable :: seed(:)
! Initialize random seed (Fortran 2003: random_seed with no args
! uses a processor-dependent seed; for reproducibility, set it)
call random_seed(size=seed_size)
allocate(seed(seed_size))
! Set a fixed seed for reproducibility
seed = [(12345 + i*6789, i=1, seed_size)]
call random_seed(put=seed)
! Generate uniform [0,1) random reals
call random_number(r)
print *, "Single: ", r
call random_number(arr) ! fills entire array
print *, "Array: ", arr
! Generate integers in [a, b]
block
integer :: a = 1, b = 6
integer :: dice
do i = 1, 5
call random_number(r)
dice = a + int(r * (b - a + 1)) ! [1, 6]
print *, "Dice roll: ", dice
end do
end block
! Normal (Gaussian) via Box-Muller transform
block
real :: u1, u2, z1, z2
integer :: j
do j = 1, 5
call random_number(u1)
call random_number(u2)
u1 = max(u1, 1e-10) ! avoid log(0)
z1 = sqrt(-2.0 * log(u1)) * cos(2.0 * 3.14159265 * u2)
z2 = sqrt(-2.0 * log(u1)) * sin(2.0 * 3.14159265 * u2)
print *, "Gaussian: ", z1, z2
end do
end block
! Monte Carlo: estimate pi
block
integer :: inside = 0, total = 100000
real :: x, y
do i = 1, total
call random_number(x)
call random_number(y)
if (x*x + y*y <= 1.0) inside = inside + 1
end do
print *, "Pi estimate: ", 4.0 * real(inside) / total
end block
end program random_demoNumerical Integration & Root Finding
Numerical integration: Simpson's rule is more accurate than the trapezoidal rule (O(h^4) error vs O(h^2)). Pass functions as arguments using an interface block. Root finding: bisection is robust (always converges if sign changes) but slow (linear convergence); Newton's method is fast (quadratic convergence) but needs the derivative and may diverge. For production work, use QUADPACK (integration) or MINPACK (root finding) — battle-tested Fortran libraries. The interface block is essential when passing functions as arguments — it tells the compiler the function's signature. Always set a max iteration count to avoid infinite loops. Check convergence with both function value and step size tolerances.
program numerical
implicit none
real(8) :: a, b, result
integer :: n
! Numerical integration: Simpson's rule
! Integrate f(x) = x^2 from 0 to 2 (exact: 8/3 ≈ 2.6667)
a = 0.0; b = 2.0; n = 1000
result = simpson(f_sq, a, b, n)
print *, "Integral of x^2 from 0 to 2: ", result ! ~2.6667
! Integrate sin(x) from 0 to pi (exact: 2.0)
result = simpson(f_sin, 0.0_8, 3.14159265358979_8, 1000)
print *, "Integral of sin(x) from 0 to pi: ", result ! ~2.0
! Root finding: bisection method
! Find root of f(x) = x^2 - 2 (i.e., sqrt(2) ≈ 1.4142)
result = bisection(f_x2_minus_2, 0.0_8, 2.0_8, 1e-12_8)
print *, "sqrt(2) = ", result ! ~1.41421356
! Newton's method (needs derivative)
result = newton(f_x2_minus_2, fp_x2_minus_2, 1.0_8, 1e-12_8)
print *, "sqrt(2) via Newton: ", result
contains
! Function to integrate: x^2
function f_sq(x) result(y)
real(8), intent(in) :: x
real(8) :: y
y = x * x
end function
function f_sin(x) result(y)
real(8), intent(in) :: x
real(8) :: y
y = sin(x)
end function
! Simpson's rule: integral of f from a to b with n intervals
function simpson(f, a, b, n) result(integral)
interface
function f(x) result(y)
import
real(8), intent(in) :: x
real(8) :: y
end function
end interface
real(8), intent(in) :: a, b
integer, intent(in) :: n
real(8) :: integral, h, x
integer :: i
h = (b - a) / n
integral = f(a) + f(b)
do i = 1, n-1
x = a + i * h
if (mod(i, 2) == 0) then
integral = integral + 2.0 * f(x)
else
integral = integral + 4.0 * f(x)
end if
end do
integral = integral * h / 3.0
end function
function f_x2_minus_2(x) result(y)
real(8), intent(in) :: x
real(8) :: y
y = x*x - 2.0
end function
function fp_x2_minus_2(x) result(y)
real(8), intent(in) :: x
real(8) :: y
y = 2.0 * x
end function
! Bisection: find root in [a, b] (f(a) and f(b) must have opposite signs)
function bisection(f, a, b, tol) result(root)
interface
function f(x) result(y)
import
real(8), intent(in) :: x
real(8) :: y
end function
end interface
real(8), intent(in) :: a, b, tol
real(8) :: root, fa, fb, mid, fmid
integer :: iter, maxiter = 100
fa = f(a); fb = f(b)
if (fa * fb > 0) stop "No sign change in interval"
do iter = 1, maxiter
mid = (a + b) / 2.0
fmid = f(mid)
if (abs(fmid) < tol .or. (b - a)/2.0 < tol) then
root = mid
return
end if
if (fa * fmid < 0) then
b = mid; fb = fmid
else
a = mid; fa = fmid
end if
end do
root = (a + b) / 2.0
end function
! Newton's method: x_{n+1} = x_n - f(x)/f'(x)
function newton(f, fp, x0, tol) result(root)
interface
function f(x) result(y)
import
real(8), intent(in) :: x
real(8) :: y
end function
function fp(x) result(y)
import
real(8), intent(in) :: x
real(8) :: y
end function
end interface
real(8), intent(in) :: x0, tol
real(8) :: root, x, fx, fpx
integer :: iter, maxiter = 100
x = x0
do iter = 1, maxiter
fx = f(x); fpx = fp(x)
if (abs(fx) < tol) then
root = x
return
end if
x = x - fx / fpx
end do
root = x
end function
end program numericalIEEE Arithmetic & Exceptions
ieee_arithmetic module (Fortran 2003) provides IEEE 754 support: Infinity, NaN (Not a Number), signaling/quiet NaN, exception flags, and rounding modes. NaN is NEVER equal to anything (including itself) — use ieee_is_nan() to test. Infinity results from overflow or division by zero. Exception flags (ieee_divide_by_zero, ieee_overflow, ieee_underflow, ieee_inexact, ieee_invalid) track if exceptions occurred — check with ieee_get_flag, clear with ieee_set_flag. ieee_set_halting_mode controls whether an exception halts the program. Rounding modes affect floating-point operations. Use this for robust numerical code: detect NaN/Inf, handle exceptions gracefully, and control precision. Note: -ffast-math in gfortran breaks IEEE compliance (don't use it for code relying on these features).
program ieee_demo
use ieee_arithmetic
implicit none
real :: a, b, c
logical :: flag
! IEEE special values
a = ieee_value(a, ieee_positive_inf) ! +Infinity
b = ieee_value(b, ieee_negative_inf) ! -Infinity
c = ieee_value(c, ieee_quiet_nan) ! NaN
print *, "Infinity: ", a ! Infinity
print *, "NaN: ", c ! NaN
print *, "Inf > 1e30: ", a > 1e30 ! T
print *, "NaN == NaN: ", c == c ! F (NaN is never equal!)
! Check for special values
print *, "is_nan(c): ", ieee_is_nan(c) ! T
print *, "is_finite(1.0): ", ieee_is_finite(1.0) ! T
print *, "is_inf(a): ", ieee_is_finite(a) ! F
! Operations producing special values
print *, "1.0/0.0: ", 1.0/0.0 ! Infinity (if -ffast-math off)
print *, "0.0/0.0: ", 0.0/0.0 ! NaN
print *, "sqrt(-1.0): ", sqrt(-1.0) ! NaN
! IEEE exception flags
call ieee_set_halting_mode(ieee_divide_by_zero, .false.) ! don't halt
b = 1.0 / 0.0 ! sets divide_by_zero flag, returns Inf
call ieee_get_flag(ieee_divide_by_zero, flag)
print *, "Divide by zero occurred: ", flag ! T
! Check and clear flags
call ieee_set_flag(ieee_all, .false.) ! clear all flags
b = 1.0 / 0.0
call ieee_get_flag(ieee_divide_by_zero, flag)
print *, "Flag after division: ", flag ! T
call ieee_set_flag(ieee_all, .false.) ! clear
! Rounding modes
call ieee_set_rounding_mode(ieee_nearest) ! default
call ieee_set_rounding_mode(ieee_down) ! round toward -inf
call ieee_set_rounding_mode(ieee_up) ! round toward +inf
call ieee_set_rounding_mode(ieee_to_zero) ! truncate
! Comparing NaN-safe
if (ieee_unordered(c, 1.0)) print *, "c is unordered (NaN)"
end program ieee_demoCoarrays & Parallel
Basic coarray declaration
Coarrays are Fortran's built-in parallel model (F2008). Each 'image' is a parallel process. Declare with [*] suffix. this_image() returns the rank; num_images() the count. Access remote with x[k]. sync all is a barrier. Compilers: gfortran (with -fcoarray=lib), ifort, Cray.
program coarray_hello
use iso_fortran_env, only: real64
implicit none
real(real64) :: x[*] ! coarray — one copy per image
integer :: me
me = this_image()
x = real(me, real64) ! local assignment
call co_sum(x, result_image=1) ! reduce sum to image 1
if (me == 1) print *, 'Sum =', x
sync all ! barrier
end programRemote access and sync
Access remote coarray with [k] suffix — one-sided communication. Reads and writes are non-blocking until sync. sync all is global barrier; sync images([1,2]) waits for specific images. Critical sections: lock/unlock with critical...end critical. Avoid deadlock by ordering syncs consistently.
program remote_access
implicit none
integer :: val[*], neighbor
integer :: me, n
me = this_image()
n = num_images()
val = me * 10
sync all ! ensure all writes complete
! read from neighbor (circular)
neighbor = merge(1, me + 1, me == n)
print *, 'Image', me, 'sees neighbor', neighbor, 'value', val[neighbor]
! write to image 1 from all
if (me /= 1) val[1] = val[me]
sync all
if (me == 1) print *, 'Image 1 received:', val
end programCollective operations
Collectives: co_sum, co_min, co_max, co_broadcast. They operate on coarrays and reduce/broadcast across images. result_image specifies who gets the answer (default: all). source_image for broadcast. Always sync before reading collective results on other images. Faster than manual loops with syncs.
program collectives
use iso_fortran_env, only: real64
implicit none
real(real64) :: local_sum, global_sum[*]
integer :: i
local_sum = 0.0_real64
do i = 1, 100
local_sum = local_sum + real(i * this_image(), real64)
end do
global_sum = local_sum
call co_sum(global_sum, result_image=1)
if (this_image() == 1) print *, 'Total:', global_sum
! other collectives: co_min, co_max, co_broadcast
call co_broadcast(global_sum, source_image=1)
end programCoarray derived types
Derived types can be coarrays — every component is replicated per image. Access remote components with p[k]%field. Allocatable components in coarrays require Fortran 2018+ (some compilers may not support). For arrays of particles, use type(particle), allocatable :: particles(:)[:].
program coarray_types
implicit none
type :: particle
real :: x, y, z
real :: mass
end type
type(particle) :: p[*]
integer :: me
me = this_image()
p%mass = real(me)
p%x = real(me) * 0.5
sync all
! access component of remote coarray
if (me == 1) print *, 'Image 2 mass:', p[2]%mass
end programAllocatable coarrays and teams
Allocatable coarrays are allocated on all images simultaneously with [*] suffix. Teams (F2018) split images into independent groups — each has its own this_image/num_images. form team creates teams; change team enters scope. Useful for hierarchical parallelism. Compiler support varies (ifort, gfortran 9+).
program alloc_coarrays
use iso_fortran_env, only: team_type
implicit none
integer, allocatable :: data(:)[:]
type(team_type) :: odd_team, even_team
integer :: me
me = this_image()
allocate(data(100)[*]) ! allocate on all images
! F2018 teams — split images into groups
form team(merge(1, 2, mod(me, 2) == 1), odd_team, even_team)
if (mod(me, 2) == 1) then
change team(odd_team)
! this_image() and num_images() now refer to team
data(this_image()) = me
end team
end if
deallocate(data)
end programInteroperability with C
ISO_C_BINDING basics
iso_c_binding provides C-compatible kinds (c_int, c_double, c_char, etc.). bind(C, name='...') exposes Fortran to C with a specific symbol name. C strings need c_null_char terminator. The interface block declares the C function signature. Compile C and Fortran separately, link together.
program c_interop
use iso_c_binding, only: c_int, c_double, c_char, c_null_char
implicit none
interface
subroutine c_print(msg) bind(C, name='c_print')
import :: c_char
character(kind=c_char), dimension(*) :: msg
end subroutine
end interface
call c_print('Hello from Fortran' // c_null_char)
end program
! Corresponding C:
! void c_print(const char* msg) { printf("%s\n", msg); }Passing arrays to C
Pass arrays via c_loc (get C pointer) and c_ptr type. Use 'value' attribute for scalar C arguments (passed by value, not reference). Fortran arrays are column-major; C is row-major — transpose 2D arrays or document the convention. c_f_pointer converts C pointers back to Fortran pointers.
program array_interop
use iso_c_binding, only: c_double, c_int, c_loc, c_f_pointer
implicit none
real(c_double), target :: arr(10)
integer(c_int) :: n
type(c_ptr) :: ptr
arr = [(real(i), i=1,10)]
ptr = c_loc(arr(1)) ! get C pointer
! call C function: void process(double* arr, int n);
call process_c(ptr, size(arr, kind=c_int))
interface
subroutine process_c(arr, n) bind(C, name='process')
import :: c_double, c_int, c_ptr
type(c_ptr), value :: arr
integer(c_int), value :: n
end subroutine
end interface
end programC-interoperable types
Types with bind(C) have C-compatible memory layout — required for passing structs to C. Only C-compatible kinds allowed (no default real/integer). No allocatable/pointer components. Fixed-length char arrays emulate C strings. Order matters — Fortran may reorder components without bind(C).
module data_types
use iso_c_binding, only: c_double, c_int, c_char
implicit none
type, bind(C) :: point
real(c_double) :: x, y
integer(c_int) :: id
end type
type, bind(C) :: string_holder
character(kind=c_char, len=1) :: name(64)
end type
end module
! C equivalent:
! struct point { double x, y; int id; };
! struct string_holder { char name[64]; };Calling Fortran from C
Subroutines with bind(C, name='...') are callable from C by that name. Use 'value' for scalars C passes by value; arrays are passed by reference (no value). Function results must be C-compatible scalars. Use C-binding names to avoid compiler name mangling (underscores, case changes).
! Fortran:
module fmod
use iso_c_binding, only: c_double
implicit none
contains
subroutine square_array(arr, n) bind(C, name='square_array')
integer, value :: n
real(c_double), intent(inout) :: arr(n)
arr = arr ** 2
end subroutine
end module
! C caller:
! extern void square_array(double* arr, int n);
! double data[5] = {1, 2, 3, 4, 5};
! square_array(data, 5);C function pointers and callbacks
abstract interface declares a C function signature. procedure(iface) accepts a matching function as argument. Pass C function pointers directly. c_funloc gets the C address of a Fortran procedure; c_f_procpointer converts a c_funptr back to a Fortran procedure. Useful for qsort-style callbacks.
module callbacks
use iso_c_binding, only: c_funloc, c_funptr, c_int
implicit none
abstract interface
function comparator(a, b) bind(C)
import :: c_int
integer(c_int), value :: a, b
integer(c_int) :: comparator
end function
end interface
contains
subroutine sort_with_c(arr, n, cmp) bind(C)
integer(c_int), value :: n
integer(c_int), intent(inout) :: arr(n)
procedure(comparator) :: cmp
! ... use cmp(a, b) to compare ...
end subroutine
end module
! C side:
! int descending(int a, int b) { return b - a; }
! sort_with_c(arr, n, descending);Object-Oriented (extends/final)
Type extension (inheritance)
Type extension = inheritance. 'extends(parent)' declares a subclass. 'class(T)' is polymorphic (accepts T or any extension); 'type(T)' is exact. 'abstract' + 'deferred' = abstract method (must be overridden). 'contains' introduces type-bound procedures. Override by re-declaring the procedure with the same name.
module shapes
implicit none
type, abstract :: shape
real :: x = 0, y = 0
contains
procedure(area_iface), deferred :: area
procedure :: move => shape_move
end type
abstract interface
function area_iface(this) result(a)
import :: shape
class(shape), intent(in) :: this
real :: a
end function
end interface
type, extends(shape) :: circle
real :: radius
contains
procedure :: area => circle_area
end type
contains
subroutine shape_move(this, dx, dy)
class(shape), intent(inout) :: this
real, intent(in) :: dx, dy
this%x = this%x + dx
this%y = this%y + dy
end subroutine
function circle_area(this) result(a)
class(circle), intent(in) :: this
real :: a
a = 3.14159 * this%radius ** 2
end function
end modulePolymorphism and SELECT TYPE
select type does runtime type discrimination on polymorphic variables. 'type is (T)' matches exact type; 'class is (T)' matches T and extensions. Inside the block, the variable is treated as the matched type (accesses specific components). Polymorphic arrays hold mixed types via class(shape) — but allocation must be per-element.
module polymorph
use shapes, only: shape, circle, rectangle
implicit none
contains
subroutine describe(s)
class(shape), intent(in) :: s
select type(s)
type is (circle)
print *, 'Circle radius:', s%radius
type is (rectangle)
print *, 'Rectangle:', s%width, 'x', s%height
class is (shape)
print *, 'Some shape at:', s%x, s%y
class default
print *, 'Unknown type'
end select
end subroutine
subroutine process_all(shapes)
class(shape), intent(in) :: shapes(:)
integer :: i
do i = 1, size(shapes)
call describe(shapes(i))
print *, 'Area:', shapes(i)%area()
end do
end subroutine
end moduleFinalizers and destructors
final procedures run automatically when a variable goes out of scope — like C++ destructors. Define with 'final :: name'. Must be a subroutine taking TYPE (not class) — no polymorphism. One type can have multiple finalizers (overloaded by rank). Use for closing files, freeing memory, releasing resources. Cannot fail/raise.
module resources
implicit none
type :: file_handle
integer :: unit = -1
contains
final :: close_file
procedure :: open
end type
contains
subroutine open(this, filename)
class(file_handle), intent(inout) :: this
character(*), intent(in) :: filename
open(newunit=this%unit, file=filename, status='old')
end subroutine
subroutine close_file(this)
type(file_handle), intent(inout) :: this
if (this%unit /= -1) then
close(this%unit)
this%unit = -1
end if
end subroutine
end module
program demo
use resources
type(file_handle) :: f
call f%open('data.txt')
! ... use file ...
end program ! f goes out of scope -> close_file called automaticallyConstructors and allocation
Generic interface with the type name acts as a custom constructor — overloads the default structure constructor. Multiple procedures allow different argument sets. The default constructor (point(x=..., y=...)) is still available unless overridden. Polymorphic allocation: allocate(circle :: shape_var) creates a circle in a class(shape) variable.
module points
implicit none
type :: point
real :: x, y
contains
procedure :: norm
end type
interface point
procedure new_point
procedure new_point_polar
end interface
contains
function new_point(x, y) result(p)
real, intent(in) :: x, y
type(point) :: p
p%x = x
p%y = y
end function
function new_point_polar(r, theta) result(p)
real, intent(in) :: r, theta
type(point) :: p
p%x = r * cos(theta)
p%y = r * sin(theta)
end function
function norm(this) result(n)
class(point), intent(in) :: this
real :: n
n = sqrt(this%x**2 + this%y**2)
end function
end module
program use_points
use points
type(point) :: a, b
a = point(1.0, 2.0) ! cartesian
b = point(3.0, 0.5) ! polar (same name, different args)
print *, a%norm(), b%norm()
end programAbstract types and templates
Abstract types can't be instantiated — only extended. Deferred procedures must be overridden in concrete subclasses. class(*) is unlimited polymorphic — holds any type (use select type to recover). This pattern implements abstract base classes and interfaces. Concrete containers (list, stack, queue) extend and implement the deferred procedures.
module container
implicit none
type, abstract :: container
contains
procedure(add_iface), deferred :: add
procedure(size_iface), deferred :: size
procedure :: is_empty => container_is_empty
end type
abstract interface
subroutine add_iface(this, item)
import :: container
class(container), intent(inout) :: this
class(*), intent(in) :: item
end subroutine
function size_iface(this) result(n)
import :: container
class(container), intent(in) :: this
integer :: n
end function
end interface
contains
function container_is_empty(this) result(e)
class(container), intent(in) :: this
logical :: e
e = (this%size() == 0)
end function
end module
! Concrete subclass implements add/size
! class(*) allows storing any type (unlimited polymorphic)Parameterized Derived Types
Basic PDT declaration
Parameterized Derived Types (PDTs, F2003) are like C++ templates. 'kind' params are compile-time (fixed per instance); 'len' params are runtime (can be deferred with ':'). Allocate deferred-length types with allocate(type(params) :: var). PDTs enable type-safe generic containers without preprocessor tricks.
module pdt_types
implicit none
type :: matrix(k, n, m)
integer, kind :: k = kind(1.0)
integer, len :: n, m
real(k) :: data(n, m)
end type
! kind parameters: compile-time (like template params)
! len parameters: runtime (like allocatable dimensions)
end module
program use_pdt
use pdt_types
implicit none
type(matrix(kind(1.0), 3, 3)) :: small ! fixed 3x3
type(matrix(kind(1.d0), :, :)), allocatable :: big ! deferred
small%data = 0.0
allocate(matrix(kind(1.d0), 100, 100) :: big)
big%data = 0.d0
deallocate(big)
end programPDT with kind parameter
Kind-parameterized types let you write one type that works for multiple precisions. The function return type uses this%k to match. Note the syntax class(array_t(k=*)) for the procedure — required for kind-param types. Compiler support: gfortran 9+, ifort. Useful for libraries supporting single/double/quad precision.
module typed_array
implicit none
type :: array_t(k)
integer, kind :: k = kind(1.0)
real(k), allocatable :: data(:)
contains
procedure :: sum_values
end type
contains
function sum_values(this) result(s)
class(array_t(k=*)), intent(in) :: this
real(this%k) :: s
s = sum(this%data)
end function
end module
program test
use typed_array
type(array_t(kind(1.0))) :: float_arr
type(array_t(kind(1.d0))) :: double_arr
allocate(float_arr%data(10))
allocate(double_arr%data(10))
float_arr%data = 1.0
double_arr%data = 1.d0
print *, float_arr%sum_values()
print *, double_arr%sum_values()
end programPDT with length parameter
Length-parameterized types carry size as a type parameter. fstr(5) and fstr(6) are different types. Procedures use fstr(*) to accept any length. The result type can depend on input lengths (c has length a%n + b%n). Useful for fixed-size buffers, statically-sized arrays. Limited compiler support — test thoroughly.
module fixed_string
implicit none
type :: fstr(n)
integer, len :: n
character(len=n) :: str
end type
contains
function concat(a, b) result(c)
type(fstr(*)), intent(in) :: a, b
type(fstr(a%n + b%n)) :: c
c%str = a%str // b%str
end function
end module
program test
use fixed_string
type(fstr(5)) :: a = fstr(5)('Hello')
type(fstr(6)) :: b = fstr(6)(' World')
type(fstr(11)) :: c
c = concat(a, b)
print *, c%str
end programPDT allocatable arrays
PDTs can contain allocatable components. The kind parameter propagates to component types (real(this%k)). move_alloc efficiently transfers allocation (no copy). Use class(stack(k=*)) in procedures to accept any kind. PDTs with allocatable components combine generic typing with dynamic sizing.
module stack_t
implicit none
type :: stack(k)
integer, kind :: k = kind(1.0)
real(k), allocatable :: data(:)
integer :: top = 0
contains
procedure :: push
procedure :: pop
procedure :: is_empty
end type
contains
subroutine push(this, val)
class(stack(k=*)), intent(inout) :: this
real(this%k), intent(in) :: val
if (this%top == size(this%data)) then
block
real(this%k), allocatable :: tmp(:)
tmp = [this%data, val]
call move_alloc(tmp, this%data)
end block
else
this%top = this%top + 1
this%data(this%top) = val
end if
end subroutine
end modulePDT limitations and workarounds
PDT support varies — kind parameters are widely supported; length parameters less so. For runtime sizing, prefer allocatable components over len parameters. PDT arrays (type(matrix(4,4)) :: arr(10)) may not work on all compilers. Test on your target compiler. For maximum portability, use preprocessor (#define) or generic interfaces.
! Limitations of PDTs:
! - Not all compilers fully support len parameters
! - I/O of PDTs may not work as expected
! - Some F2003 features (e.g., PDT arrays) have spotty support
! Workaround: use allocatable components instead of len params
module alt_matrix
implicit none
type :: matrix_alt(k)
integer, kind :: k = kind(1.0)
real(k), allocatable :: data(:,:)
end type
contains
function make_matrix(k_, n, m) result(mat)
integer, intent(in) :: n, m
! kind must be compile-time constant — can't pass dynamically
! workaround: separate constructors per kind
end function
end module
! Best practice: use kind params (well-supported), avoid len params
! Use allocatable components for runtime sizing insteadSubmodules
Basic submodule structure
Submodules (F2008) separate interface from implementation. The module declares the interface; the submodule provides the body. Changes to the submodule body don't trigger recompilation of dependents — only interface changes do. Use 'module procedure' to implement. Great for large libraries with expensive compilation.
! parent_module.f90
module math_lib
implicit none
interface
module function integrate(f, a, b, n) result(s)
abstract interface
real function func_t(x)
real, intent(in) :: x
end function
end interface
procedure(func_t) :: f
real, intent(in) :: a, b
integer, intent(in) :: n
real :: s
end function
end interface
end module
! sub_math.f90
submodule(math_lib) math_impl
implicit none
contains
module procedure integrate
integer :: i
real :: dx, x
dx = (b - a) / n
s = 0.5 * (f(a) + f(b))
do i = 1, n-1
x = a + i * dx
s = s + f(x)
end do
s = s * dx
end procedure
end submoduleMultiple submodules per module
A module can have multiple submodules — split implementations across files. Each submodule starts with 'submodule(parent) name'. Procedures in the same parent module can call each other. This enables incremental compilation: edit one submodule, recompile only it and link. Useful for very large modules.
! big_lib.f90
module big_lib
implicit none
interface
module subroutine sort(arr)
real, intent(inout) :: arr(:)
end subroutine
module function mean(arr) result(m)
real, intent(in) :: arr(:)
real :: m
end function
module function stddev(arr) result(s)
real, intent(in) :: arr(:)
real :: s
end function
end interface
end module
! sub_sort.f90 — one submodule
submodule(big_lib) sort_impl
contains
module procedure sort
! quicksort implementation
end procedure
end submodule
! sub_stats.f90 — another submodule
submodule(big_lib) stats_impl
contains
module procedure mean
m = sum(arr) / size(arr)
end procedure
module procedure stddev
block
real :: mu
mu = mean(arr) ! can call sibling module procedures
s = sqrt(sum((arr - mu)**2) / (size(arr) - 1))
end block
end procedure
end submoduleSubmodule-only internal procedures
Submodules can contain private helper procedures not visible through the parent module's interface. This hides implementation details while keeping them co-located. Only 'module procedure' implementations are accessible via the parent. Helpers stay internal — better encapsulation than putting everything in the module's contains block.
module sparse_ops
implicit none
interface
module function sparse_multiply(a, b) result(c)
! ... sparse matrix types ...
real, allocatable :: c(:,:)
end function
end interface
end module
submodule(sparse_ops) sparse_impl
implicit none
contains
module procedure sparse_multiply
! call helper — invisible to module users
call validate_dimensions(a, b)
c = multiply_kernel(a, b)
end procedure
! private helper — not exposed via parent module
subroutine validate_dimensions(a, b)
! ...
end subroutine
function multiply_kernel(a, b) result(c)
! ...
end function
end submoduleInheriting module variables
Submodules have access to the parent module's variables and types via host association. They can read and modify module-level state. This is useful for configuration that affects implementation behavior. Changes to module variables still require recompiling the submodule (and dependents).
module config
implicit none
integer :: verbosity = 0
interface
module subroutine log_message(msg)
character(*), intent(in) :: msg
end subroutine
end interface
end module
submodule(config) config_impl
implicit none
! submodule can access parent module's variables
contains
module procedure log_message
if (verbosity > 0) then
print *, '[LOG]', msg
end if
end procedure
end submodule
! Usage:
! use config
! verbosity = 1
! call log_message('Starting up')Submodule compilation benefits
The key benefit: implementation changes in a submodule don't trigger recompilation of code that only 'use's the parent module. Only the submodule itself recompiles. This dramatically speeds up incremental builds for large Fortran projects. Restructure hot-changing implementations into submodules; keep stable interfaces in the parent.
! Without submodules:
! module big_mod
! ... 5000 lines of implementation ...
! end module
! ! Any change -> recompile big_mod + all users
! With submodules:
! module big_mod
! ! just interfaces (~200 lines)
! end module
! submodule(big_mod) impl
! ! 5000 lines of implementation
! end submodule
! ! Change impl body -> recompile only submodule
! ! Change interface -> recompile everything (unavoidable)
! Build system example (Makefile):
! big_mod.o: big_mod.f90
! impl.o: impl.f90 big_mod.o
! user.o: user.f90 big_mod.o ! NOT impl.o
! app: user.o impl.o big_mod.o
! $(FC) -o app user.o impl.o big_mod.oIEEE Floating Point
IEEE exceptions and flags
ieee_exceptions provides access to IEEE exception flags (overflow, underflow, divide_by_zero, invalid, inexact). ieee_get_flag reads; ieee_set_flag clears. ieee_set_halting_mode controls whether exceptions halt the program. ieee_arithmetic provides ieee_is_nan, ieee_is_finite, ieee_is_negative, etc. Always check flags after critical computations.
program ieee_exceptions
use ieee_exceptions
use ieee_arithmetic, only: ieee_is_nan, ieee_is_finite
implicit none
real :: x, y
logical :: overflow_flag
call ieee_set_halting_mode(ieee_overflow, .false.)
x = huge(x) * 10 ! overflow -> Inf, no halt
call ieee_get_flag(ieee_overflow, overflow_flag)
print *, 'Overflow occurred:', overflow_flag
y = 0.0 / 0.0 ! NaN
print *, 'x is finite:', ieee_is_finite(x)
print *, 'y is NaN:', ieee_is_nan(y)
call ieee_set_flag(ieee_all, .false.) ! clear all flags
end programNaN and Inf handling
Inf and NaN are IEEE special values. NaN != NaN (use ieee_is_nan to test). Inf propagates through arithmetic. Operations that produce NaN: 0/0, Inf-Inf, 0*Inf, sqrt(-1). Compile with -ffpe-trap=invalid,zero,overflow to halt on these (debugging). Production code should check for NaN after risky operations.
program nan_inf
use ieee_arithmetic, only: ieee_value, ieee_nan, &
ieee_positive_inf, ieee_negative_inf
implicit none
real :: pos_inf, neg_inf, nan_val
pos_inf = ieee_value(0.0, ieee_positive_inf)
neg_inf = ieee_value(0.0, ieee_negative_inf)
nan_val = ieee_value(0.0, ieee_nan)
print *, 'Inf - Inf =', pos_inf - pos_inf ! NaN
print *, '0 * Inf =', 0.0 * pos_inf ! NaN
print *, 'Inf > 1e30:', pos_inf > 1e30 ! T
print *, 'NaN == NaN:', nan_val == nan_val ! F (always!)
! generate via arithmetic
pos_inf = 1.0 / 0.0 ! may halt without -fno-trapping-math
end programRounding modes
IEEE supports 4 rounding modes: nearest (default), down, up, to zero. ieee_set_rounding_mode changes it at runtime. Useful for interval arithmetic (compute upper/lower bounds by rounding up/down). Affects all subsequent FP operations until changed. Restore to nearest when done. Some compilers optimize assuming nearest — use with care.
program rounding_modes
use ieee_arithmetic, only: ieee_set_rounding_mode, &
ieee_nearest, ieee_down, ieee_up, ieee_to_zero
implicit none
real :: x, y, result
x = 1.0 / 3.0
print *, 'Nearest:', x
call ieee_set_rounding_mode(ieee_down)
result = 1.0 / 3.0
print *, 'Down:', result
call ieee_set_rounding_mode(ieee_up)
result = 1.0 / 3.0
print *, 'Up:', result
call ieee_set_rounding_mode(ieee_to_zero)
result = 1.0 / 3.0
print *, 'To zero:', result
call ieee_set_rounding_mode(ieee_nearest) ! restore default
end programIEEE features inquiry
ieee_features and ieee_arithmetic inquiry functions let you check what IEEE features the compiler/platform supports. ieee_support_nan, ieee_support_inf, ieee_support_rounding, ieee_support_datatype, etc. Useful for portable code — degrade gracefully on non-IEEE systems. Most modern systems support all features.
program ieee_inquiry
use ieee_features
use ieee_arithmetic, only: ieee_support_nan, ieee_support_inf, &
ieee_support_rounding, ieee_nearest
implicit none
if (ieee_support_nan(1.0)) print *, 'NaN supported'
if (ieee_support_inf(1.0)) print *, 'Inf supported'
if (ieee_support_rounding(ieee_nearest, 1.0)) &
print *, 'Nearest rounding supported'
! Check halting mode
block
use ieee_exceptions
logical :: halting
call ieee_get_halting_mode(ieee_overflow, halting)
print *, 'Overflow halts:', halting
end block
end programControlling FP environment
Control FP behavior per section: disable halting for risky code, check flags after, restore. ieee_all matches all exceptions. Pattern: clear flags, run computation, check flags, handle errors. For production, prefer explicit checks (ieee_is_nan) over flag-based detection — flags can be set by unrelated code.
program fp_env
use ieee_arithmetic
use ieee_exceptions
implicit none
real :: a, b, c
! Save/restore FP state
block
use iso_fortran_env, only: real32
real(real32) :: saved_state
! (no portable save/restore in standard — use compiler intrinsics)
end block
! Disable halting for a risky section
call ieee_set_halting_mode(ieee_all, .false.)
call ieee_set_flag(ieee_all, .false.)
a = sqrt(-1.0) ! NaN, no halt
b = 1.0 / 0.0 ! Inf, no halt
if (ieee_is_nan(a)) then
print *, 'Got NaN, using fallback'
a = 0.0
end if
! Re-enable halting
call ieee_set_halting_mode(ieee_divide_by_zero, .true.)
call ieee_set_halting_mode(ieee_invalid, .true.)
end programPerformance & Optimization
Array ordering and contiguity
Fortran arrays are column-major: a(i,j) and a(i+1,j) are adjacent in memory. Loop order matters: innermost loop should iterate the first index. Wrong order causes cache misses — 10x+ slowdown. Array syntax (sum, matmul) lets the compiler optimize. Use contiguous arrays (not pointers) for best performance.
program array_perf
implicit none
real, allocatable :: a(:,:), b(:,:)
integer :: i, j, n
real :: s
n = 1000
allocate(a(n,n), b(n,n))
! GOOD: column-major access (Fortran is column-major)
do j = 1, n
do i = 1, n
s = s + a(i,j)
end do
end do
! BAD: row-major access (cache misses)
do i = 1, n
do j = 1, n
s = s + a(i,j)
end do
end do
! BEST: array syntax (compiler optimizes)
s = sum(a)
end programPure and elemental procedures
pure procedures have no side effects — compiler can optimize, parallelize, and reorder calls. elemental procedures work on both scalars and arrays (auto-vectorized). pure elemental combines both. Use these for math functions. Restrictions: no I/O, no global modification, intent(in) for all inputs. Enables better optimization than regular procedures.
module math_ops
implicit none
contains
! pure: no side effects, enables optimization
pure function square(x) result(y)
real, intent(in) :: x
real :: y
y = x * x
end function
! elemental: works on scalars and arrays element-wise
pure elemental function clamp(x, lo, hi) result(y)
real, intent(in) :: x, lo, hi
real :: y
y = max(lo, min(x, hi))
end function
end module
program use_math
use math_ops
implicit none
real :: arr(100), scalar
arr = clamp(arr, 0.0, 1.0) ! applies to each element
scalar = clamp(1.5, 0.0, 1.0) ! also works on scalar
arr = square(arr) ! elemental too (if declared)
end programCompiler optimization flags
Start with -O2 -march=native for production. -O3 can help or hurt — benchmark. -Ofast breaks IEEE compliance (don't use if NaN/Inf matter). -flto enables cross-file inlining (slower compile, faster run). Use -fcheck=all and -ffpe-trap in debug builds to catch errors. Profile-guided optimization (-fprofile-use) gives 5-15% speedup.
! gfortran optimization flags:
! -O0 no optimization (debug)
! -O1 basic optimization
! -O2 standard optimization (recommended)
! -O3 aggressive (may increase code size)
! -Ofast -O3 + -ffast-math (breaks IEEE compliance)
! -march=native use CPU's full instruction set
! -flto link-time optimization (cross-file inlining)
! -fopenmp enable OpenMP pragmas
! -fprofile-generate/use profile-guided optimization
! Example Makefile:
! FC = gfortran
! FFLAGS = -O2 -march=native -Wall -fcheck=all
! FFLAGS_RELEASE = -O3 -march=native -flto -fno-trapping-math
! FFLAGS_DEBUG = -O0 -g -fcheck=all -fbacktrace -ffpe-trap=invalid,zero
! ifort equivalents:
! -O2, -O3, -xHost (= -march=native), -ipo (= -flto)OpenMP parallelism
OpenMP adds parallelism via directives (!$omp). 'parallel do' parallelizes the next loop. 'reduction(+:s)' handles sums safely. Compile with -fopenmp (gfortran) or -qopenmp (ifort). Set thread count via OMP_NUM_THREADS env var. Best for CPU-bound loops with independent iterations. Beware false sharing and load imbalance.
program openmp_demo
use omp_lib
implicit none
real, allocatable :: a(:), b(:), c(:)
integer :: i, n, nthreads
n = 10000000
allocate(a(n), b(n), c(n))
a = 1.0; b = 2.0
!$omp parallel
if (omp_get_thread_num() == 0) then
nthreads = omp_get_num_threads()
print *, 'Threads:', nthreads
end if
!$omp end parallel
!$omp parallel do
do i = 1, n
c(i) = a(i) + b(i)
end do
!$omp end parallel do
! reduction
block
real :: s
s = 0.0
!$omp parallel do reduction(+:s)
do i = 1, n
s = s + c(i)
end do
!$omp end parallel do
print *, 'Sum:', s
end block
end programProfiling and hotspot detection
system_clock gives portable timing. For serious profiling, use gprof (compile with -pg), perf (Linux), or Intel VTune. Profile before optimizing — surprises are common. Focus on hotspots (the 20% of code taking 80% of time). Optimize the innermost loops first. Always benchmark before/after changes — intuition is often wrong.
! Compile with profiling:
! gfortran -pg -O2 prog.f90 -o prog
! ./prog (generates gmon.out)
! gprof prog gmon.out > profile.txt
! Or use perf (Linux):
! perf record ./prog
! perf report
! Or gprofng (modern):
! gprofng collect app ./prog
! gprofng analyze
! Manual timing:
program timing
use iso_fortran_env, only: real64, int64
implicit none
integer(int64) :: start, finish, rate
real(real64) :: elapsed
real, allocatable :: a(:)
integer :: i
allocate(a(10000000))
call system_clock(start, rate)
do i = 1, 100
a = a + 1.0
end do
call system_clock(finish)
elapsed = real(finish - start, real64) / real(rate, real64)
print *, 'Elapsed:', elapsed, 'sec'
end programMixed Language Programming
Fortran calling C library
Wrap C library functions in a Fortran interface module. Use bind(C, name='...') to link to the exact C symbol. Pass pointers as c_ptr with 'value'. For function-pointer arguments (like qsort's comparator), use an abstract interface. This lets you call any C function — including libc, BLAS, system calls.
module c_glue
use iso_c_binding
implicit none
interface
function c_malloc(size) bind(C, name='malloc')
import :: c_ptr, c_size_t
integer(c_size_t), value :: size
type(c_ptr) :: c_malloc
end function
subroutine c_free(ptr) bind(C, name='free')
import :: c_ptr
type(c_ptr), value :: ptr
end subroutine
subroutine c_qsort(base, nmemb, size, compar) bind(C, name='qsort')
import :: c_ptr, c_size_t, c_int
type(c_ptr), value :: base
integer(c_size_t), value :: nmemb, size
abstract interface
function compar_fn(a, b) bind(C)
import :: c_ptr
type(c_ptr), value :: a, b
integer(c_int) :: compar_fn
end function
end interface
procedure(compar_fn) :: compar
end subroutine
end interface
end moduleC++ interop via extern C
C++ name-mangles symbols, so wrap C++ functions in extern "C" blocks. The Fortran interface then binds to the unmangled name. Link with -lstdc++ (gfortran) or use a C++ linker. This lets you use C++ libraries (STL, Boost, Qt) from Fortran. For C++ classes, write a flat C API wrapper, then call from Fortran.
! C++ side (wrapper.cpp):
! extern "C" {
! void cpp_process(double* data, int n) {
! std::vector<double> v(data, data+n);
! std::sort(v.begin(), v.end());
! std::copy(v.begin(), v.end(), data);
! }
! }
! Fortran side:
module cpp_glue
use iso_c_binding
implicit none
interface
subroutine cpp_process(data, n) bind(C, name='cpp_process')
import :: c_double, c_int
real(c_double), intent(inout) :: data(*)
integer(c_int), value :: n
end subroutine
end interface
end module
program use_cpp
use cpp_glue
implicit none
real(c_double) :: arr(10) = [5.d0, 3.d0, 8.d0, 1.d0, 9.d0, &
2.d0, 7.d0, 4.d0, 6.d0, 0.d0]
call cpp_process(arr, size(arr, kind=c_int))
print *, arr
end program
! Build: gfortran use_cpp.f90 wrapper.cpp -lstdc++ -o appPython interop via f2py
f2py (part of numpy) auto-generates Python bindings for Fortran. It reads intent attributes and creates proper Python/numpy interfaces. intent(out) becomes a return value. Arrays map to numpy arrays (zero-copy when contiguous). Great for performance-critical numerical code called from Python. Limited support for F2003+ features.
! Fortran module (myfuncs.f90):
module myfuncs
implicit none
contains
subroutine compute(arr, n, result)
integer, intent(in) :: n
real(8), intent(in) :: arr(n)
real(8), intent(out) :: result
result = sum(arr**2)
end subroutine
function fast_sin(x) result(y)
real(8), intent(in) :: x
real(8) :: y
y = sin(x)
end function
end module
! Build Python extension:
! f2py -c myfuncs.f90 -m myfuncs
! (creates myfuncs.cpython-*.so)
! Python usage:
! import numpy as np
! import myfuncs
! arr = np.array([1.0, 2.0, 3.0])
! result = myfuncs.myfuncs.compute(arr)
! y = myfuncs.myfuncs.fast_sin(1.5)Shared library and dynamic loading
Use dlopen/dlsym (POSIX) or LoadLibrary/GetProcAddress (Windows) for runtime-loaded plugins. Wrap in iso_c_binding interfaces. Convert c_ptr to procedure pointer with c_f_procpointer. This enables plugin architectures — load different implementations at runtime. Cross-platform: use #ifdef for OS-specific loaders.
module dynamic_loader
use iso_c_binding
implicit none
interface
function dlopen(filename, flag) bind(C, name='dlopen')
import :: c_ptr, c_char, c_int
character(kind=c_char), dimension(*) :: filename
integer(c_int), value :: flag
type(c_ptr) :: dlopen
end function
function dlsym(handle, name) bind(C, name='dlsym')
import :: c_ptr, c_char
type(c_ptr), value :: handle
character(kind=c_char), dimension(*) :: name
type(c_ptr) :: dlsym
end function
function dlclose(handle) bind(C, name='dlclose')
import :: c_ptr, c_int
type(c_ptr), value :: handle
integer(c_int) :: dlclose
end function
end interface
end module
program plugin
use dynamic_loader
implicit none
type(c_ptr) :: lib, sym
integer, parameter :: RTLD_NOW = 2
lib = dlopen('./plugin.so' // c_null_char, RTLD_NOW)
if (.not. c_associated(lib)) then
print *, 'Failed to load library'
stop 1
end if
sym = dlsym(lib, 'init' // c_null_char)
! call init via c_f_procpointer...
print *, dlclose(lib)
end programBuild system integration
CMake handles mixed-language builds well. Declare all languages in project(). Set per-language flags. Link libraries in dependency order. CMake tracks Fortran module dependencies automatically (no manual .mod ordering). For C++ standard library linking, use the right flag per platform. Use Fortran as the main linker if Fortran runtime is needed.
# CMakeLists.txt for mixed Fortran/C/C++ project:
cmake_minimum_required(VERSION 3.18)
project(mixed LANGUAGES Fortran C CXX)
set(CMAKE_Fortran_FLAGS "-O2 -fopenmp")
set(CMAKE_C_FLAGS "-O2")
set(CMAKE_CXX_FLAGS "-O2 -std=c++17")
add_library(fortran_lib STATIC mymod.f90)
add_library(c_lib STATIC helper.c)
add_library(cpp_lib STATIC wrapper.cpp)
# Mixed-language executable
add_executable(app main.f90)
target_link_libraries(app fortran_lib c_lib cpp_lib)
# Fortran needs C runtime
if(APPLE)
target_link_libraries(app "-lc++")
else()
target_link_libraries(app stdc++)
endif()
# Module dependency tracking (CMake handles automatically)
# fortran_lib depends on its own .mod files
# app depends on fortran_lib's .mod filesModern I/O
Newunit and safe file handling
newunit= avoids unit number collisions — the compiler picks a free number. Always check iostat after open/read/write — non-zero means error. iomsg gives a human-readable error message. action= ('read', 'write', 'readwrite') prevents accidental misuse. status= ('old', 'new', 'replace', 'scratch', 'unknown') controls file creation.
program safe_io
implicit none
integer :: u, ios
character(256) :: msg
! newunit: compiler picks an unused unit number
open(newunit=u, file='data.txt', status='old', action='read', &
iostat=ios, iomsg=msg)
if (ios /= 0) then
print *, 'Open failed:', trim(msg)
stop 1
end if
! read with error handling
read(u, *, iostat=ios, iomsg=msg) some_value
if (ios /= 0) then
print *, 'Read failed:', trim(msg)
end if
close(u)
contains
integer function some_value()
some_value = 0
end function
end programStream I/O (binary)
Stream access (F2003) gives byte-oriented I/O like C — no record markers. access='stream' enables it. pos= reads/writes at a specific byte offset. form='unformatted' for binary. Great for interoperable binary files (read Fortran-written files from C/Python). Default sequential access uses record markers (non-portable).
program stream_io
implicit none
integer :: u, i
real, allocatable :: data(:)
! stream access = byte-oriented (like C fread/fwrite)
open(newunit=u, file='data.bin', access='stream', &
form='unformatted', status='replace')
data = [(real(i), i=1,100)]
write(u) data ! binary, no record markers
close(u)
! read back
allocate(data(100))
open(newunit=u, file='data.bin', access='stream', &
form='unformatted', status='old', action='read')
read(u) data
close(u)
! position-based access
open(newunit=u, file='data.bin', access='stream', &
form='unformatted', status='old')
read(u, pos=21) data(1) ! read 5th real (4 bytes each)
close(u)
end programDerived type I/O
User-Defined Derived Type I/O (F2003) lets you control how types are read/written. Define a subroutine with the specific signature and bind it via 'generic :: write(formatted)'. The DT format code triggers it. Enables custom serialization (CSV, JSON-like, binary). iotype is 'LISTDIRECTED', 'NAMELIST', or 'DT' for formatted I/O.
module person_type
implicit none
type :: person
character(20) :: name
integer :: age
real :: height
end type
contains
! custom formatted I/O via DT format
subroutine write_person(dtv, unit, iotype, v_list, iostat, iomsg)
class(person), intent(in) :: dtv
integer, intent(in) :: unit
character(*), intent(in) :: iotype
integer, intent(in) :: v_list(:)
integer, intent(out) :: iostat
character(*), intent(inout) :: iomsg
write(unit, '(a,",",i0,",",f0.2)', iostat=iostat) &
trim(dtv%name), dtv%age, dtv%height
end subroutine
end module
program use_dtv
use person_type
implicit none
type(person) :: p = person('Alice', 30, 5.7)
! DT format triggers custom writer
print "(DT)", p ! calls write_person
end programNamelist I/O
Namelist provides human-readable, name-based I/O for groups of variables. Format: &group_name var=value, ... /. Reading only updates variables present in the file — others keep their values. Great for config files — users edit text, no parser needed. Limitations: no comments in some compilers, limited type support.
program namelist_demo
implicit none
integer :: n_iterations = 100
real :: tolerance = 1.0e-6
character(50) :: output_file = 'results.txt'
logical :: verbose = .true.
namelist /config/ n_iterations, tolerance, output_file, verbose
! write namelist
open(newunit=u, file='config.nml', status='replace')
write(u, nml=config)
close(u)
! read namelist (only specified vars are updated)
open(newunit=u, file='config.nml', status='old', action='read')
read(u, nml=config)
close(u)
print *, 'Iterations:', n_iterations
end program
! config.nml format:
! &config
! n_iterations = 500
! tolerance = 1.0e-8
! verbose = .false.
! /Asynchronous I/O
Asynchronous I/O (F2003) overlaps I/O with computation. write(..., asynchronous='yes') starts a non-blocking operation. wait(unit) blocks until it completes. Useful for large datasets — start writing while computing next chunk. Compiler support varies. Use inquire(unit=u, pending=...) to check status. Pair with double-buffering for pipelines.
program async_io
implicit none
integer :: u1, u2, ios
real, allocatable :: a(:), b(:)
allocate(a(1000000), b(1000000))
a = 1.0; b = 2.0
open(newunit=u1, file='a.bin', access='stream', form='unformatted', &
asynchronous='yes')
open(newunit=u2, file='b.bin', access='stream', form='unformatted', &
asynchronous='yes')
! non-blocking writes
write(u1, asynchronous='yes') a
write(u2, asynchronous='yes') b
! do other work while I/O proceeds...
! wait for completion
wait(u1)
wait(u2)
close(u1); close(u2)
end programDebugging & Profiling
Compile-time debugging flags
Use -fcheck=all for bounds checking (catches off-by-one errors). -ffpe-trap halts on NaN/Inf/overflow — invaluable for numerical code. -finit-real=nan makes uninitialized variables visible (they propagate as NaN). -fbacktrace prints a stack trace on crash. Always debug with these flags; remove for production builds (they slow code).
! gfortran debug build:
! gfortran -O0 -g -fcheck=all -fbacktrace -ffpe-trap=invalid,zero,overflow \
! -Wall -Wextra -Wpedantic -finit-real=nan prog.f90
! Flag explanations:
! -O0 no optimization (easier debugging)
! -g debug symbols (for gdb)
! -fcheck=all bounds, pointer, recursion checks
! -fbacktrace print stack trace on error
! -ffpe-trap halt on FP exceptions (invalid, zero, overflow)
! -finit-real=nan initialize reals to NaN (catch uninitialized)
! -finit-integer=-9999 initialize integers to sentinel
! -Wall -Wextra more warnings
! Runtime error message:
! At line 42 of file prog.f90
! Fortran runtime error: Array bound out of bounds for dimension 1Error handling with iostat
iostat: negative = EOF, zero = success, positive = error. iomsg gives details. Read into a string first, then parse — separates I/O errors from parse errors. Track line numbers for helpful error messages. Always handle errors explicitly — silent failures are hard to debug. Use stop with a non-zero code to signal failure to scripts.
program robust_io
implicit none
integer :: u, ios, line_num
character(256) :: msg, line
real :: value
open(newunit=u, file='data.txt', status='old', action='read', &
iostat=ios, iomsg=msg)
if (ios /= 0) call error_exit('Open: ' // trim(msg))
line_num = 0
do
line_num = line_num + 1
read(u, '(a)', iostat=ios) line
if (ios < 0) exit ! EOF
if (ios > 0) then
print *, 'Read error at line', line_num
cycle
end if
read(line, *, iostat=ios, iomsg=msg) value
if (ios /= 0) then
print *, 'Parse error at line', line_num, ':', trim(msg)
cycle
end if
! process value
end do
close(u)
contains
subroutine error_exit(m)
character(*), intent(in) :: m
print *, 'ERROR:', m
stop 1
end subroutine
end programGDB for Fortran
GDB supports Fortran: array slices, derived type components, module procedures (name format: modname__procname). Use -g -O0 for best debugging experience. 'display' auto-prints variables on each stop — useful for loop watching. 'info locals' shows all locals. For module variables, use 'print modname::varname'.
! Compile: gfortran -g -O0 prog.f90 -o prog
! Start: gdb ./prog
! Common GDB commands for Fortran:
! (gdb) break main break at main
! (gdb) break prog.f90:42 break at line 42
! (gdb) break mymod__my_sub break at subroutine (note double underscore)
! (gdb) run start program
! (gdb) next step over
! (gdb) step step into
! (gdb) print arr(5) print array element
! (gdb) print arr(1:10) print array slice
! (gdb) print mat(2,3) print 2D array element
! (gdb) print p%name print derived type component
! (gdb) display x watch variable (auto-print on stop)
! (gdb) backtrace show call stack
! (gdb) info locals show all local variables
! (gdb) continue resume executiongprof profiling
gprof samples the program counter during execution. Compile ALL source files with -pg for complete profiles. The flat profile shows where time is spent; the call graph shows the call hierarchy. Focus on functions with high 'self' time — that's where optimization helps. Note: -pg changes timing — profile-like code may behave differently in production.
! Compile with profiling:
! gfortran -pg -O2 prog.f90 -o prog
! Run:
! ./prog
! (creates gmon.out)
! Analyze:
! gprof prog gmon.out > profile.txt
! gprof prog gmon.out | less
! profile.txt sections:
! - Flat profile: time per function (self + cumulative)
! - Call graph: who called whom, how many times
! - Index: function cross-references
! Key columns:
! %time percentage of total time
! cumulative running total
! self seconds in function (excluding children)
! calls number of calls
! self/call average time per call (self)
! For multi-threaded: use gprofng (modern) or perfPerformance benchmarking
Benchmark properly: warmup first (cache effects), run multiple iterations, take the minimum (least noise). system_clock with count_rate gives wall time. Report throughput (elements/sec) for array ops. Compare implementations on the same machine with the same flags. Beware: compiler may optimize away 'unused' results — use the result (e.g., print sum) to prevent this.
program benchmark
use iso_fortran_env, only: real64, int64
implicit none
integer, parameter :: n = 1000000
integer, parameter :: niter = 100
real(real64), allocatable :: a(:), b(:), c(:)
integer(int64) :: start, finish, rate
real(real64) :: t_start, t_end, min_time
integer :: i, iter
allocate(a(n), b(n), c(n))
a = 1.0_real64; b = 2.0_real64
! warmup (cache, JIT-like effects)
do i = 1, n
c(i) = a(i) + b(i)
end do
min_time = huge(min_time)
call system_clock(count_rate=rate)
do iter = 1, niter
call system_clock(start)
do i = 1, n
c(i) = a(i) + b(i)
end do
call system_clock(finish)
t_start = real(start, real64) / rate
t_end = real(finish, real64) / rate
min_time = min(min_time, t_end - t_start)
end do
print *, 'Best time:', min_time * 1e6, 'us'
print *, 'Throughput:', real(n) / min_time / 1e9, 'G elem/s'
end programModern Fortran
Free Form
Modern Fortran (90+) uses free form: no column restrictions. Comments start with !. Statements can span multiple lines with &. Implicit none is mandatory for type safety. Much more readable than fixed-form Fortran 77.
program modern
implicit none
integer :: i
do i = 1, 10
print *, "Value:", i
end do
end program modern
! Free form: no column restrictions
! Comments start with !Modules
Modules group related procedures and data. use imports a module. contains separates module-level declarations from procedures. Modules provide explicit interfaces, enabling type checking. Prefer modules over external procedures.
module math_utils
implicit none
contains
function square(x) result(y)
real, intent(in) :: x
real :: y
y = x * x
end function square
end module math_utils
program test
use math_utils
print *, square(3.0) ! 9.0
end program testDerived Types
Derived types are user-defined data structures (structs). % accesses components. Type-bound procedures enable OOP. Constructors create instances. Derived types can have default values and extend other types (inheritance). Use for complex data modeling.
type :: Point
real :: x, y
end type Point
type(Point) :: p
p = Point(1.0, 2.0) ! Constructor
p%x = 3.0 ! Component access
print *, p%x, p%y
! Type-bound procedures (OOP)
type :: Circle
real :: radius
contains
procedure :: area => circle_area
end typeIntent Attributes
intent(in) parameters are read-only (cannot be modified). intent(out) is write-only (set by the procedure). intent(inout) is read-write. The compiler checks intent violations. Improves code clarity and enables optimizations. Always specify intent.
subroutine process(input, output, inout)
integer, intent(in) :: input ! Read-only
integer, intent(out) :: output ! Write-only
integer, intent(inout) :: inout ! Read-write
output = input * 2
inout = inout + 1
end subroutinePure & Elemental
pure functions have no side effects (no I/O, no mutable state). The compiler can optimize them. elemental functions work on both scalars and arrays automatically. They are pure by default. Ideal for mathematical operations. Enables parallel execution.
pure function square(x) result(y)
real, intent(in) :: x
real :: y
y = x * x
end function
! Elemental: works on scalars and arrays
elemental function double_it(x) result(y)
real, intent(in) :: x
real :: y
y = 2.0 * x
end function
! double_it([1,2,3]) returns [2,4,6]Arrays
Array Declaration
Fortran arrays are 1-indexed by default. Custom lower bounds with (0:). Column-major order (first index varies fastest). allocatable arrays are heap-allocated and must be deallocated. Array constants use [ ]. Fortran arrays are more efficient than C arrays due to descriptors.
! Static arrays
real :: a(10) ! 1D, indices 1-10
real :: b(0:9) ! 1D, indices 0-9
real :: c(3, 4) ! 2D, 3 rows x 4 cols
! Allocatable (dynamic)
real, allocatable :: d(:)
allocate(d(100)) ! Allocate
deallocate(d) ! Free
! Array constants
integer :: nums(5) = [1, 2, 3, 4, 5]Array Operations
Fortran supports whole-array operations: +, -, *, /, **. No loops needed for element-wise math. Intrinsic functions: sum, product, maxval, minval, any, all, count. Much faster than loops due to vectorization. This is Fortrans strength for numerical computing.
real :: a(5) = [1, 2, 3, 4, 5]
real :: b(5)
b = a * 2 ! Element-wise: [2,4,6,8,10]
b = a + 1 ! [2,3,4,5,6]
print *, sum(a) ! 15
print *, maxval(a) ! 5
print *, any(a > 3) ! .true.
print *, count(a > 2) ! 3Array Sections
Array sections use (start:end:stride) syntax. :: means default (1 to end, stride 1). Negative strides reverse. Multi-dimensional sections work on any dimension. Sections can be passed to procedures. Very powerful for slicing without copying.
real :: a(10) = [(i, i=1,10)]
print *, a(3:7) ! Elements 3 to 7
print *, a(::2) ! Every other: [1,3,5,7,9]
print *, a(2:8:2) ! Stride 2: [2,4,6,8]
real :: m(3,3)
m(:, 2) ! Second column
m(1, :) ! First rowwhere Construct
where is array-level conditional assignment. Like a vectorized if. Elsewhere handles the false case. More efficient than loops because it can be vectorized. Use for element-wise conditional operations on arrays.
real :: a(5) = [1, -2, 3, -4, 5]
where (a > 0)
a = a * 2 ! Double positives
elsewhere
a = 0 ! Zero negatives
end where
! Result: [2, 0, 6, 0, 10]
! Equivalent to a loop with ifDynamic Allocation
allocatable arrays are dynamically sized. allocate creates, deallocate frees. Fortran 2003+ auto-deallocates at end of scope. Check allocation status with allocated(). Allocatable arrays are automatically reallocated on assignment (Fortran 2003+). Much safer than C malloc/free.
real, allocatable :: matrix(:,:)
integer :: n
n = 100
allocate(matrix(n, n))
matrix = 0.0 ! Initialize all to 0
! ... use matrix ...
deallocate(matrix)
! Automatic deallocation at end of scope
! (Fortran 2003+)I/O Operations
Formatted Output
Format strings control output. I5 = integer width 5. F8.3 = float width 8, 3 decimals. I0 = minimal width. A = string. X = space. / = newline. write(*,...) is same as print but more flexible. Use format strings for aligned output.
integer :: i = 42
real :: x = 3.14159
print "(I5, F8.3)", i, x ! " 42 3.142"
print "(A, I0)", "Count=", i ! "Count=42"
write(*, "(3F6.2)") 1.0, 2.0, 3.0
! Format specifiers:
! I: integer, F: float, E: exponential
! A: string, X: space, /: newlineFile I/O
open connects a file to a unit. newunit assigns a free unit number. status: old (must exist), new (must not exist), replace. iostat returns non-zero on error or EOF. Always check iostat to avoid crashes. close disconnects the file.
integer :: unit, ios
open(newunit=unit, file="data.txt", status="old", action="read")
do
read(unit, *, iostat=ios) value
if (ios /= 0) exit
print *, value
end do
close(unit)
! status: old, new, replace, scratch
! action: read, write, readwriteNamelist
namelist groups variables for I/O. The file format is &config n=10, x=3.14 /. Useful for configuration files. Variables can be in any order. Only listed variables are read/written. Much easier than parsing custom formats.
integer :: n = 10
real :: x = 3.14
namelist /config/ n, x
! Write namelist
open(1, file="config.nml")
write(1, nml=config)
close(1)
! Read namelist
open(1, file="config.nml")
read(1, nml=config)
close(1)Internal Files
Internal files use character strings as I/O units. write to a string converts values to text. read from a string parses text. Useful for type conversion and formatting. trim removes trailing spaces. Much simpler than C sprintf/sscanf.
character(20) :: str
integer :: num = 42
! Integer to string
write(str, "(I0)") num
print *, trim(str) ! "42"
! String to integer
read(str, *) num
! Internal files use character variables as unitsBinary I/O
Unformatted I/O writes raw binary data. Faster and more compact than text. access="stream" for byte-level access (Fortran 2008). Not portable between architectures (endianness). Use for large scientific datasets. Formatted I/O is for human-readable data.
! Unformatted (binary) I/O
open(1, file="data.bin", form="unformatted", &
access="stream")
write(1) array ! No format, raw bytes
read(1) array2
close(1)
! Faster than formatted I/O
! Smaller file size
! Not portable across architecturesParallel Programming
OpenMP
OpenMP parallelizes loops with directives. !$omp parallel do distributes iterations across threads. private: each thread has its own copy. reduction: combines results. Compile with -fopenmp. Easy way to parallelize numerical code.
!$omp parallel do private(i) reduction(+:sum)
do i = 1, n
sum = sum + a(i) * b(i)
end do
!$omp end parallel do
! Compile: gfortran -fopenmp program.f90
! Environment: OMP_NUM_THREADS=4Coarrays
Coarrays (Fortran 2008) are built-in parallel arrays. Each image (process) has its own copy. [N] accesses another images data. sync all is a barrier. this_image() returns the image number. Built into the language, no library needed.
program coarray_example
implicit none
integer :: me[*] ! Coarray: one per image
me = this_image()
sync all ! Barrier
if (this_image() == 1) then
print *, "Image 2 has:", me[2] ! Remote access
end if
end program
! Compile: gfortran -fcoarray=single program.f90MPI Basics
MPI (Message Passing Interface) is the standard for distributed parallelism. mpi_init/finalize start and end. comm_rank gives the process ID. comm_size gives total processes. Send/recv for communication. Scales to thousands of cores. Use for clusters.
program mpi_example
use mpi
integer :: rank, size, ierr
call mpi_init(ierr)
call mpi_comm_rank(MPI_COMM_WORLD, rank, ierr)
call mpi_comm_size(MPI_COMM_WORLD, size, ierr)
print *, "I am rank", rank, "of", size
call mpi_finalize(ierr)
end program
! Compile: mpifort program.f90do concurrent
do concurrent (Fortran 2008) indicates loop iterations are independent. The compiler can parallelize automatically. local declares private variables. Safer than OpenMP: the compiler verifies independence. Use for embarrassingly parallel loops.
do concurrent (i = 1:n) local(tmp)
tmp = expensive_compute(a(i))
b(i) = tmp * 2
end do
! Tells compiler iterations are independent
! Can be parallelized automatically
! local: private variable per iterationReduction Pattern
Reductions combine partial results from each thread. Common: sum, product, max, min. Each thread computes a local partial result. The runtime combines them at the end. Avoids data races. Essential for parallel numerical algorithms.
!$omp parallel do reduction(+:total)
do i = 1, n
total = total + a(i)
end do
!$omp end parallel do
! Common reductions: +, *, max, min, .and., .or.
! Each thread has a private copy
! Combined at the endNumerical Methods
Linear Algebra
Fortran has built-in matrix operations. matmul multiplies matrices. dot_product computes dot product. transpose transposes. These are highly optimized (BLAS-level). For production, use LAPACK. Fortran is the language of choice for high-performance numerical computing.
! Matrix multiplication
do i = 1, n
do j = 1, n
c(i,j) = sum(a(i,:) * b(:,j))
end do
end do
! Or use matmul intrinsic
c = matmul(a, b)
! Dot product
dot = dot_product(a, b)
! Transpose
at = transpose(a)Solving ODEs
Euler method is the simplest ODE solver: y(n+1) = y(n) + dt*f(t,y). For accuracy, use Runge-Kutta (RK4). The interface block passes functions as arguments. Fortran is ideal for scientific computing due to array operations and performance.
! Euler method: dy/dt = f(t, y)
subroutine euler(f, t0, y0, dt, n, t, y)
interface
real function f(t, y)
real, intent(in) :: t, y
end function
end interface
real, intent(in) :: t0, y0, dt
integer, intent(in) :: n
real, intent(out) :: t(n+1), y(n+1)
integer :: i
t(1) = t0; y(1) = y0
do i = 1, n
t(i+1) = t(i) + dt
y(i+1) = y(i) + dt * f(t(i), y(i))
end do
end subroutineRandom Numbers
random_number generates uniform [0,1) reals. random_seed initializes the generator. For integers, scale and convert. Box-Muller transforms uniform to normal distribution. For serious work, use a library (e.g., Mersenne Twister). Always seed for reproducibility.
call random_seed() ! Seed from system
call random_number(x) ! x in [0, 1)
! Array of randoms
real :: arr(100)
call random_number(arr)
! Integer in range [1, 6]
integer :: dice
call random_number(r)
dice = int(r * 6) + 1
! Normal distribution (Box-Muller)
call random_number(u1)
call random_number(u2)
z = sqrt(-2*log(u1)) * cos(2*PI*u2)Interpolation
Linear interpolation estimates values between known points. Find the interval, then interpolate. For smoother results, use cubic spline interpolation. Fortrans array operations make this concise. Always check bounds to avoid extrapolation errors.
function interp(x, xs, ys) result(y)
real, intent(in) :: x, xs(:), ys(:)
real :: y
integer :: i
! Find interval
i = 1
do while (i < size(xs) .and. x > xs(i+1))
i = i + 1
end do
! Linear interpolation
y = ys(i) + (ys(i+1) - ys(i)) * &
(x - xs(i)) / (xs(i+1) - xs(i))
end functionNumerical Integration
Trapezoidal rule approximates integrals: sum of trapezoids. More accurate: Simpsons rule. For higher dimensions, use Gaussian quadrature. Fortran excels at numerical integration due to performance. Always validate with known analytical solutions.
! Trapezoidal rule
function trapezoid(f, a, b, n) result(integral)
interface
real function f(x)
real, intent(in) :: x
end function
end interface
real, intent(in) :: a, b
integer, intent(in) :: n
real :: integral, h
integer :: i
h = (b - a) / n
integral = (f(a) + f(b)) / 2
do i = 1, n-1
integral = integral + f(a + i*h)
end do
integral = integral * h
end functionCommon Pitfalls
1-based Indexing
Fortran arrays are 1-indexed by default, unlike C/Python (0-indexed). This causes off-by-one errors when porting code. Custom lower bounds (0:9) are allowed. Be consistent within a project. Check array bounds with -fcheck=bounds compiler flag.
! Fortran arrays are 1-based by default
real :: a(10) ! Indices 1 to 10
! a(0) = 1.0 ! Error: out of bounds
a(1) = 1.0 ! OK
! Custom bounds
real :: b(0:9) ! Indices 0 to 9
b(0) = 1.0 ! OKImplicit Typing
Without implicit none, variables starting with i-n are integer, others real. This causes subtle bugs (typo creates a new variable). Always use implicit none. Modern Fortran (2018+) can set it globally with -fimplicit-none. This is the most important Fortran best practice.
! BAD: implicit typing (Fortran 77 style)
program bad
! i-n start with integer by default
i = 1 ! integer (implicit)
x = 3.14 ! real (implicit)
end program
! GOOD: explicit typing
program good
implicit none ! Force explicit declaration
integer :: i
real :: x
end programColumn-Major Order
Fortran stores arrays column-major: m(1,1), m(2,1), m(3,1), m(1,2), ... Accessing column-by-column is cache-friendly. Wrong loop order causes cache misses and slows down by 10x+. Always match loop order to memory layout. Opposite of C (row-major).
! Fortran is column-major (first index varies fastest)
real :: m(3, 3)
! Efficient: iterate over first index in inner loop
do j = 1, 3
do i = 1, 3
m(i, j) = 0.0 ! Cache-friendly
end do
end do
! Inefficient: row-major access
do i = 1, 3
do j = 1, 3
m(i, j) = 0.0 ! Cache misses
end do
end doPass by Reference
Fortran passes arguments by reference (like C pointers). Subroutines can modify caller variables unless intent(in) is specified. Without intent, accidental modifications cause bugs. Always specify intent. intent(out) signals the procedure will set the value.
subroutine modify(x)
integer, intent(inout) :: x
x = 99 ! Modifies the caller variable
end subroutine
! Fortran passes by reference by default
! intent(in) prevents modification
! Without intent, modification is allowed (dangerous)Floating Point Precision
Default real is single precision (~7 digits), often insufficient. Use double precision for scientific computing. kind(1.0d0) or selected_real_kind(15) defines double. Always suffix literals: 3.14_dp. Mixing precisions causes silent truncation. Use iso_fortran_env for portable kinds.
! Single precision (default)
real :: x = 3.14159 ! ~7 digits
! Double precision
real(kind=8) :: y = 3.14159d0 ! ~15 digits
! Or use kind parameter
integer, parameter :: dp = kind(1.0d0)
real(dp) :: z = 3.14159_dp
! Always use _dp or d0 for double literalsRelated Fortran snippets
Copy-paste ready code for common tasks.
Arrays and Vector Operations
Create and operate on arrays in modern Fortran.
Subroutines and Functions
Define reusable procedures in Fortran.
Modules and Derived Types
Organize code with modules and OOP-style types.
File I/O and Formatting
Read/write files with formatted output.
OpenMP Parallelism
Parallelize loops with OpenMP directives.
Numerical: Linear Algebra (BLAS/LAPACK)
Call BLAS/LAPACK for matrix operations.
Derived Types and Pointers
Custom types with allocatable components and pointers.
Pointers and Allocatables
Dynamic memory allocation in Fortran.
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