from sage.all import * from sage.interfaces.maxima_lib import maxima_lib from sage.symbolic.expression import Expression def set_simplification_domain(d): """ Set Maxima's simplification domain. INPUT: - ``d`` -- The domain, either 'real' or 'complex'. TESTS: With the default 'complex' domain, we don't simplify this:: sage: (abs(x)^2).simplify() abs(x)^2 But in the 'real' domain, we do:: sage: set_simplification_domain('real') 'real' sage: (abs(x)^2).simplify() x^2 sage: set_simplification_domain('complex') 'complex' """ cmd = 'domain: %s;' % d result = maxima_lib._eval_line(cmd) return result def safe_simplify(expr): """ What should be a totally safe simplification operation that works a little better than the plain simplify(). Uses a top-level function because we can't monkey-patch Cython classes. """ expr = expr.simplify_factorial() expr = expr.simplify_log() return expr def matrix_subs_expr(m, *equations): """ Symbolic matrices have a `subs()` method, but no `subs_expr()`. This makes it diffucult to substitute in a list of solutions obtained with `solve()`. INPUT: - ``m`` -- A symbolic matrix. - ``equations`` - One or more symbolic equations, presumably for the entries of `m`. OUTPUT: The result of substituting each equation into `m`, one after another. EXAMPLES:: sage: w,x,y,z = SR.var('w,x,y,z') sage: A = matrix(SR, [[w,x],[y,z]]) sage: matrix_subs_expr(A, w == 1, x == 2, y == 3, z == 4) [1 2] [3 4] """ from sage.symbolic.expression import is_SymbolicEquation if not m.base_ring() == SR: raise TypeError, 'the matrix "m" must be symbolic' if isinstance(equations[0], dict): eq_dict = equations[0] equations = [ x == eq_dict[x] for x in eq_dict.keys() ] if not all([is_SymbolicEquation(eq) for eq in equations]): raise TypeError, "each expression must be an equation" d = dict([(eq.lhs(), eq.rhs()) for eq in equations]) return m.subs(d)