from sympy.core.containers import Tuple from sympy.core.numbers import oo from sympy.core.relational import (Gt, Lt) from sympy.core.symbol import (Dummy, Symbol) from sympy.functions.elementary.complexes import Abs from sympy.logic.boolalg import And from sympy.codegen.ast import ( Assignment, AddAugmentedAssignment, CodeBlock, Declaration, FunctionDefinition, Print, Return, Scope, While, Variable, Pointer, real ) """ This module collects functions for constructing ASTs representing algorithms. """ def newtons_method(expr, wrt, atol=1e-12, delta=None, debug=False, itermax=None, counter=None): """ Generates an AST for Newton-Raphson method (a root-finding algorithm). Explanation =========== Returns an abstract syntax tree (AST) based on ``sympy.codegen.ast`` for Netwon's method of root-finding. Parameters ========== expr : expression wrt : Symbol With respect to, i.e. what is the variable. atol : number or expr Absolute tolerance (stopping criterion) delta : Symbol Will be a ``Dummy`` if ``None``. debug : bool Whether to print convergence information during iterations itermax : number or expr Maximum number of iterations. counter : Symbol Will be a ``Dummy`` if ``None``. Examples ======== >>> from sympy import symbols, cos >>> from sympy.codegen.ast import Assignment >>> from sympy.codegen.algorithms import newtons_method >>> x, dx, atol = symbols('x dx atol') >>> expr = cos(x) - x**3 >>> algo = newtons_method(expr, x, atol, dx) >>> algo.has(Assignment(dx, -expr/expr.diff(x))) True References ========== .. [1] https://en.wikipedia.org/wiki/Newton%27s_method """ if delta is None: delta = Dummy() Wrapper = Scope name_d = 'delta' else: Wrapper = lambda x: x name_d = delta.name delta_expr = -expr/expr.diff(wrt) whl_bdy = [Assignment(delta, delta_expr), AddAugmentedAssignment(wrt, delta)] if debug: prnt = Print([wrt, delta], r"{}=%12.5g {}=%12.5g\n".format(wrt.name, name_d)) whl_bdy = [whl_bdy[0], prnt] + whl_bdy[1:] req = Gt(Abs(delta), atol) declars = [Declaration(Variable(delta, type=real, value=oo))] if itermax is not None: counter = counter or Dummy(integer=True) v_counter = Variable.deduced(counter, 0) declars.append(Declaration(v_counter)) whl_bdy.append(AddAugmentedAssignment(counter, 1)) req = And(req, Lt(counter, itermax)) whl = While(req, CodeBlock(*whl_bdy)) blck = declars + [whl] return Wrapper(CodeBlock(*blck)) def _symbol_of(arg): if isinstance(arg, Declaration): arg = arg.variable.symbol elif isinstance(arg, Variable): arg = arg.symbol return arg def newtons_method_function(expr, wrt, params=None, func_name="newton", attrs=Tuple(), *, delta=None, **kwargs): """ Generates an AST for a function implementing the Newton-Raphson method. Parameters ========== expr : expression wrt : Symbol With respect to, i.e. what is the variable params : iterable of symbols Symbols appearing in expr that are taken as constants during the iterations (these will be accepted as parameters to the generated function). func_name : str Name of the generated function. attrs : Tuple Attribute instances passed as ``attrs`` to ``FunctionDefinition``. \\*\\*kwargs : Keyword arguments passed to :func:`sympy.codegen.algorithms.newtons_method`. Examples ======== >>> from sympy import symbols, cos >>> from sympy.codegen.algorithms import newtons_method_function >>> from sympy.codegen.pyutils import render_as_module >>> x = symbols('x') >>> expr = cos(x) - x**3 >>> func = newtons_method_function(expr, x) >>> py_mod = render_as_module(func) # source code as string >>> namespace = {} >>> exec(py_mod, namespace, namespace) >>> res = eval('newton(0.5)', namespace) >>> abs(res - 0.865474033102) < 1e-12 True See Also ======== sympy.codegen.algorithms.newtons_method """ if params is None: params = (wrt,) pointer_subs = {p.symbol: Symbol('(*%s)' % p.symbol.name) for p in params if isinstance(p, Pointer)} if delta is None: delta = Symbol('d_' + wrt.name) if expr.has(delta): delta = None # will use Dummy algo = newtons_method(expr, wrt, delta=delta, **kwargs).xreplace(pointer_subs) if isinstance(algo, Scope): algo = algo.body not_in_params = expr.free_symbols.difference({_symbol_of(p) for p in params}) if not_in_params: raise ValueError("Missing symbols in params: %s" % ', '.join(map(str, not_in_params))) declars = tuple(Variable(p, real) for p in params) body = CodeBlock(algo, Return(wrt)) return FunctionDefinition(real, func_name, declars, body, attrs=attrs)