658 lines
18 KiB
Python
658 lines
18 KiB
Python
"""
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AST nodes specific to Fortran.
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The functions defined in this module allows the user to express functions such as ``dsign``
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as a SymPy function for symbolic manipulation.
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"""
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from sympy.codegen.ast import (
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Attribute, CodeBlock, FunctionCall, Node, none, String,
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Token, _mk_Tuple, Variable
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)
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from sympy.core.basic import Basic
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from sympy.core.containers import Tuple
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from sympy.core.expr import Expr
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from sympy.core.function import Function
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from sympy.core.numbers import Float, Integer
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from sympy.core.symbol import Str
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from sympy.core.sympify import sympify
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from sympy.logic import true, false
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from sympy.utilities.iterables import iterable
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pure = Attribute('pure')
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elemental = Attribute('elemental') # (all elemental procedures are also pure)
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intent_in = Attribute('intent_in')
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intent_out = Attribute('intent_out')
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intent_inout = Attribute('intent_inout')
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allocatable = Attribute('allocatable')
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class Program(Token):
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""" Represents a 'program' block in Fortran.
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Examples
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========
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>>> from sympy.codegen.ast import Print
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>>> from sympy.codegen.fnodes import Program
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>>> prog = Program('myprogram', [Print([42])])
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>>> from sympy import fcode
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>>> print(fcode(prog, source_format='free'))
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program myprogram
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print *, 42
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end program
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"""
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__slots__ = _fields = ('name', 'body')
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_construct_name = String
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_construct_body = staticmethod(lambda body: CodeBlock(*body))
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class use_rename(Token):
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""" Represents a renaming in a use statement in Fortran.
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Examples
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========
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>>> from sympy.codegen.fnodes import use_rename, use
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>>> from sympy import fcode
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>>> ren = use_rename("thingy", "convolution2d")
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>>> print(fcode(ren, source_format='free'))
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thingy => convolution2d
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>>> full = use('signallib', only=['snr', ren])
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>>> print(fcode(full, source_format='free'))
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use signallib, only: snr, thingy => convolution2d
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"""
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__slots__ = _fields = ('local', 'original')
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_construct_local = String
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_construct_original = String
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def _name(arg):
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if hasattr(arg, 'name'):
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return arg.name
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else:
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return String(arg)
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class use(Token):
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""" Represents a use statement in Fortran.
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Examples
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========
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>>> from sympy.codegen.fnodes import use
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>>> from sympy import fcode
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>>> fcode(use('signallib'), source_format='free')
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'use signallib'
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>>> fcode(use('signallib', [('metric', 'snr')]), source_format='free')
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'use signallib, metric => snr'
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>>> fcode(use('signallib', only=['snr', 'convolution2d']), source_format='free')
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'use signallib, only: snr, convolution2d'
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"""
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__slots__ = _fields = ('namespace', 'rename', 'only')
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defaults = {'rename': none, 'only': none}
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_construct_namespace = staticmethod(_name)
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_construct_rename = staticmethod(lambda args: Tuple(*[arg if isinstance(arg, use_rename) else use_rename(*arg) for arg in args]))
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_construct_only = staticmethod(lambda args: Tuple(*[arg if isinstance(arg, use_rename) else _name(arg) for arg in args]))
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class Module(Token):
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""" Represents a module in Fortran.
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Examples
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========
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>>> from sympy.codegen.fnodes import Module
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>>> from sympy import fcode
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>>> print(fcode(Module('signallib', ['implicit none'], []), source_format='free'))
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module signallib
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implicit none
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<BLANKLINE>
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contains
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<BLANKLINE>
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<BLANKLINE>
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end module
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"""
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__slots__ = _fields = ('name', 'declarations', 'definitions')
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defaults = {'declarations': Tuple()}
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_construct_name = String
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@classmethod
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def _construct_declarations(cls, args):
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args = [Str(arg) if isinstance(arg, str) else arg for arg in args]
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return CodeBlock(*args)
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_construct_definitions = staticmethod(lambda arg: CodeBlock(*arg))
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class Subroutine(Node):
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""" Represents a subroutine in Fortran.
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Examples
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========
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>>> from sympy import fcode, symbols
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>>> from sympy.codegen.ast import Print
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>>> from sympy.codegen.fnodes import Subroutine
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>>> x, y = symbols('x y', real=True)
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>>> sub = Subroutine('mysub', [x, y], [Print([x**2 + y**2, x*y])])
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>>> print(fcode(sub, source_format='free', standard=2003))
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subroutine mysub(x, y)
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real*8 :: x
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real*8 :: y
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print *, x**2 + y**2, x*y
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end subroutine
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"""
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__slots__ = ('name', 'parameters', 'body')
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_fields = __slots__ + Node._fields
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_construct_name = String
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_construct_parameters = staticmethod(lambda params: Tuple(*map(Variable.deduced, params)))
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@classmethod
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def _construct_body(cls, itr):
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if isinstance(itr, CodeBlock):
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return itr
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else:
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return CodeBlock(*itr)
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class SubroutineCall(Token):
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""" Represents a call to a subroutine in Fortran.
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Examples
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========
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>>> from sympy.codegen.fnodes import SubroutineCall
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>>> from sympy import fcode
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>>> fcode(SubroutineCall('mysub', 'x y'.split()))
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' call mysub(x, y)'
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"""
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__slots__ = _fields = ('name', 'subroutine_args')
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_construct_name = staticmethod(_name)
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_construct_subroutine_args = staticmethod(_mk_Tuple)
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class Do(Token):
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""" Represents a Do loop in in Fortran.
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Examples
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========
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>>> from sympy import fcode, symbols
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>>> from sympy.codegen.ast import aug_assign, Print
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>>> from sympy.codegen.fnodes import Do
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>>> i, n = symbols('i n', integer=True)
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>>> r = symbols('r', real=True)
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>>> body = [aug_assign(r, '+', 1/i), Print([i, r])]
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>>> do1 = Do(body, i, 1, n)
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>>> print(fcode(do1, source_format='free'))
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do i = 1, n
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r = r + 1d0/i
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print *, i, r
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end do
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>>> do2 = Do(body, i, 1, n, 2)
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>>> print(fcode(do2, source_format='free'))
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do i = 1, n, 2
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r = r + 1d0/i
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print *, i, r
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end do
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"""
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__slots__ = _fields = ('body', 'counter', 'first', 'last', 'step', 'concurrent')
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defaults = {'step': Integer(1), 'concurrent': false}
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_construct_body = staticmethod(lambda body: CodeBlock(*body))
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_construct_counter = staticmethod(sympify)
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_construct_first = staticmethod(sympify)
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_construct_last = staticmethod(sympify)
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_construct_step = staticmethod(sympify)
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_construct_concurrent = staticmethod(lambda arg: true if arg else false)
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class ArrayConstructor(Token):
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""" Represents an array constructor.
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Examples
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========
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>>> from sympy import fcode
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>>> from sympy.codegen.fnodes import ArrayConstructor
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>>> ac = ArrayConstructor([1, 2, 3])
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>>> fcode(ac, standard=95, source_format='free')
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'(/1, 2, 3/)'
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>>> fcode(ac, standard=2003, source_format='free')
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'[1, 2, 3]'
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"""
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__slots__ = _fields = ('elements',)
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_construct_elements = staticmethod(_mk_Tuple)
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class ImpliedDoLoop(Token):
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""" Represents an implied do loop in Fortran.
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Examples
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========
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>>> from sympy import Symbol, fcode
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>>> from sympy.codegen.fnodes import ImpliedDoLoop, ArrayConstructor
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>>> i = Symbol('i', integer=True)
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>>> idl = ImpliedDoLoop(i**3, i, -3, 3, 2) # -27, -1, 1, 27
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>>> ac = ArrayConstructor([-28, idl, 28]) # -28, -27, -1, 1, 27, 28
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>>> fcode(ac, standard=2003, source_format='free')
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'[-28, (i**3, i = -3, 3, 2), 28]'
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"""
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__slots__ = _fields = ('expr', 'counter', 'first', 'last', 'step')
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defaults = {'step': Integer(1)}
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_construct_expr = staticmethod(sympify)
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_construct_counter = staticmethod(sympify)
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_construct_first = staticmethod(sympify)
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_construct_last = staticmethod(sympify)
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_construct_step = staticmethod(sympify)
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class Extent(Basic):
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""" Represents a dimension extent.
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Examples
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========
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>>> from sympy.codegen.fnodes import Extent
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>>> e = Extent(-3, 3) # -3, -2, -1, 0, 1, 2, 3
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>>> from sympy import fcode
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>>> fcode(e, source_format='free')
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'-3:3'
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>>> from sympy.codegen.ast import Variable, real
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>>> from sympy.codegen.fnodes import dimension, intent_out
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>>> dim = dimension(e, e)
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>>> arr = Variable('x', real, attrs=[dim, intent_out])
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>>> fcode(arr.as_Declaration(), source_format='free', standard=2003)
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'real*8, dimension(-3:3, -3:3), intent(out) :: x'
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"""
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def __new__(cls, *args):
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if len(args) == 2:
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low, high = args
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return Basic.__new__(cls, sympify(low), sympify(high))
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elif len(args) == 0 or (len(args) == 1 and args[0] in (':', None)):
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return Basic.__new__(cls) # assumed shape
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else:
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raise ValueError("Expected 0 or 2 args (or one argument == None or ':')")
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def _sympystr(self, printer):
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if len(self.args) == 0:
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return ':'
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return ":".join(str(arg) for arg in self.args)
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assumed_extent = Extent() # or Extent(':'), Extent(None)
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def dimension(*args):
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""" Creates a 'dimension' Attribute with (up to 7) extents.
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Examples
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========
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>>> from sympy import fcode
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>>> from sympy.codegen.fnodes import dimension, intent_in
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>>> dim = dimension('2', ':') # 2 rows, runtime determined number of columns
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>>> from sympy.codegen.ast import Variable, integer
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>>> arr = Variable('a', integer, attrs=[dim, intent_in])
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>>> fcode(arr.as_Declaration(), source_format='free', standard=2003)
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'integer*4, dimension(2, :), intent(in) :: a'
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"""
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if len(args) > 7:
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raise ValueError("Fortran only supports up to 7 dimensional arrays")
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parameters = []
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for arg in args:
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if isinstance(arg, Extent):
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parameters.append(arg)
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elif isinstance(arg, str):
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if arg == ':':
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parameters.append(Extent())
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else:
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parameters.append(String(arg))
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elif iterable(arg):
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parameters.append(Extent(*arg))
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else:
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parameters.append(sympify(arg))
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if len(args) == 0:
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raise ValueError("Need at least one dimension")
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return Attribute('dimension', parameters)
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assumed_size = dimension('*')
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def array(symbol, dim, intent=None, *, attrs=(), value=None, type=None):
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""" Convenience function for creating a Variable instance for a Fortran array.
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Parameters
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==========
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symbol : symbol
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dim : Attribute or iterable
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If dim is an ``Attribute`` it need to have the name 'dimension'. If it is
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not an ``Attribute``, then it is passed to :func:`dimension` as ``*dim``
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intent : str
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One of: 'in', 'out', 'inout' or None
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\\*\\*kwargs:
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Keyword arguments for ``Variable`` ('type' & 'value')
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Examples
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========
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>>> from sympy import fcode
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>>> from sympy.codegen.ast import integer, real
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>>> from sympy.codegen.fnodes import array
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>>> arr = array('a', '*', 'in', type=integer)
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>>> print(fcode(arr.as_Declaration(), source_format='free', standard=2003))
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integer*4, dimension(*), intent(in) :: a
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>>> x = array('x', [3, ':', ':'], intent='out', type=real)
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>>> print(fcode(x.as_Declaration(value=1), source_format='free', standard=2003))
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real*8, dimension(3, :, :), intent(out) :: x = 1
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"""
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if isinstance(dim, Attribute):
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if str(dim.name) != 'dimension':
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raise ValueError("Got an unexpected Attribute argument as dim: %s" % str(dim))
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else:
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dim = dimension(*dim)
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attrs = list(attrs) + [dim]
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if intent is not None:
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if intent not in (intent_in, intent_out, intent_inout):
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intent = {'in': intent_in, 'out': intent_out, 'inout': intent_inout}[intent]
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attrs.append(intent)
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if type is None:
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return Variable.deduced(symbol, value=value, attrs=attrs)
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else:
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return Variable(symbol, type, value=value, attrs=attrs)
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def _printable(arg):
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return String(arg) if isinstance(arg, str) else sympify(arg)
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def allocated(array):
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""" Creates an AST node for a function call to Fortran's "allocated(...)"
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Examples
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========
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>>> from sympy import fcode
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>>> from sympy.codegen.fnodes import allocated
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>>> alloc = allocated('x')
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>>> fcode(alloc, source_format='free')
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'allocated(x)'
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"""
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return FunctionCall('allocated', [_printable(array)])
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def lbound(array, dim=None, kind=None):
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""" Creates an AST node for a function call to Fortran's "lbound(...)"
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Parameters
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==========
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array : Symbol or String
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dim : expr
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kind : expr
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Examples
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========
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>>> from sympy import fcode
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>>> from sympy.codegen.fnodes import lbound
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>>> lb = lbound('arr', dim=2)
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>>> fcode(lb, source_format='free')
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'lbound(arr, 2)'
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"""
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return FunctionCall(
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'lbound',
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[_printable(array)] +
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([_printable(dim)] if dim else []) +
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([_printable(kind)] if kind else [])
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)
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def ubound(array, dim=None, kind=None):
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return FunctionCall(
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'ubound',
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[_printable(array)] +
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([_printable(dim)] if dim else []) +
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([_printable(kind)] if kind else [])
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)
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def shape(source, kind=None):
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""" Creates an AST node for a function call to Fortran's "shape(...)"
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Parameters
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==========
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source : Symbol or String
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kind : expr
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Examples
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========
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>>> from sympy import fcode
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>>> from sympy.codegen.fnodes import shape
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>>> shp = shape('x')
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>>> fcode(shp, source_format='free')
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'shape(x)'
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"""
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return FunctionCall(
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'shape',
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[_printable(source)] +
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([_printable(kind)] if kind else [])
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)
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def size(array, dim=None, kind=None):
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""" Creates an AST node for a function call to Fortran's "size(...)"
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Examples
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========
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>>> from sympy import fcode, Symbol
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>>> from sympy.codegen.ast import FunctionDefinition, real, Return
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>>> from sympy.codegen.fnodes import array, sum_, size
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>>> a = Symbol('a', real=True)
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>>> body = [Return((sum_(a**2)/size(a))**.5)]
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>>> arr = array(a, dim=[':'], intent='in')
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>>> fd = FunctionDefinition(real, 'rms', [arr], body)
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>>> print(fcode(fd, source_format='free', standard=2003))
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real*8 function rms(a)
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real*8, dimension(:), intent(in) :: a
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rms = sqrt(sum(a**2)*1d0/size(a))
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end function
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"""
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return FunctionCall(
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'size',
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[_printable(array)] +
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([_printable(dim)] if dim else []) +
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([_printable(kind)] if kind else [])
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)
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def reshape(source, shape, pad=None, order=None):
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""" Creates an AST node for a function call to Fortran's "reshape(...)"
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Parameters
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==========
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source : Symbol or String
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shape : ArrayExpr
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"""
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return FunctionCall(
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'reshape',
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[_printable(source), _printable(shape)] +
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([_printable(pad)] if pad else []) +
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([_printable(order)] if pad else [])
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)
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def bind_C(name=None):
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""" Creates an Attribute ``bind_C`` with a name.
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Parameters
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==========
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name : str
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Examples
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========
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>>> from sympy import fcode, Symbol
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>>> from sympy.codegen.ast import FunctionDefinition, real, Return
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>>> from sympy.codegen.fnodes import array, sum_, bind_C
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>>> a = Symbol('a', real=True)
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>>> s = Symbol('s', integer=True)
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>>> arr = array(a, dim=[s], intent='in')
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>>> body = [Return((sum_(a**2)/s)**.5)]
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>>> fd = FunctionDefinition(real, 'rms', [arr, s], body, attrs=[bind_C('rms')])
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>>> print(fcode(fd, source_format='free', standard=2003))
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real*8 function rms(a, s) bind(C, name="rms")
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real*8, dimension(s), intent(in) :: a
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integer*4 :: s
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rms = sqrt(sum(a**2)/s)
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end function
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"""
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return Attribute('bind_C', [String(name)] if name else [])
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class GoTo(Token):
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""" Represents a goto statement in Fortran
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Examples
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========
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>>> from sympy.codegen.fnodes import GoTo
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>>> go = GoTo([10, 20, 30], 'i')
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>>> from sympy import fcode
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>>> fcode(go, source_format='free')
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'go to (10, 20, 30), i'
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"""
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__slots__ = _fields = ('labels', 'expr')
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defaults = {'expr': none}
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_construct_labels = staticmethod(_mk_Tuple)
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_construct_expr = staticmethod(sympify)
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class FortranReturn(Token):
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""" AST node explicitly mapped to a fortran "return".
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Explanation
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===========
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Because a return statement in fortran is different from C, and
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in order to aid reuse of our codegen ASTs the ordinary
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``.codegen.ast.Return`` is interpreted as assignment to
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the result variable of the function. If one for some reason needs
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to generate a fortran RETURN statement, this node should be used.
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Examples
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========
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>>> from sympy.codegen.fnodes import FortranReturn
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>>> from sympy import fcode
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>>> fcode(FortranReturn('x'))
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' return x'
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"""
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__slots__ = _fields = ('return_value',)
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defaults = {'return_value': none}
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_construct_return_value = staticmethod(sympify)
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class FFunction(Function):
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_required_standard = 77
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def _fcode(self, printer):
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name = self.__class__.__name__
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if printer._settings['standard'] < self._required_standard:
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raise NotImplementedError("%s requires Fortran %d or newer" %
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(name, self._required_standard))
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return '{}({})'.format(name, ', '.join(map(printer._print, self.args)))
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class F95Function(FFunction):
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_required_standard = 95
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class isign(FFunction):
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""" Fortran sign intrinsic for integer arguments. """
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nargs = 2
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class dsign(FFunction):
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""" Fortran sign intrinsic for double precision arguments. """
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nargs = 2
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class cmplx(FFunction):
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""" Fortran complex conversion function. """
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nargs = 2 # may be extended to (2, 3) at a later point
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class kind(FFunction):
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""" Fortran kind function. """
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nargs = 1
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class merge(F95Function):
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""" Fortran merge function """
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nargs = 3
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class _literal(Float):
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_token = None # type: str
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_decimals = None # type: int
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def _fcode(self, printer, *args, **kwargs):
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mantissa, sgnd_ex = ('%.{}e'.format(self._decimals) % self).split('e')
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mantissa = mantissa.strip('0').rstrip('.')
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ex_sgn, ex_num = sgnd_ex[0], sgnd_ex[1:].lstrip('0')
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ex_sgn = '' if ex_sgn == '+' else ex_sgn
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return (mantissa or '0') + self._token + ex_sgn + (ex_num or '0')
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class literal_sp(_literal):
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""" Fortran single precision real literal """
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_token = 'e'
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_decimals = 9
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class literal_dp(_literal):
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""" Fortran double precision real literal """
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_token = 'd'
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_decimals = 17
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class sum_(Token, Expr):
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__slots__ = _fields = ('array', 'dim', 'mask')
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defaults = {'dim': none, 'mask': none}
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_construct_array = staticmethod(sympify)
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_construct_dim = staticmethod(sympify)
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class product_(Token, Expr):
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__slots__ = _fields = ('array', 'dim', 'mask')
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defaults = {'dim': none, 'mask': none}
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_construct_array = staticmethod(sympify)
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_construct_dim = staticmethod(sympify)
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