def wronskian(functions, var, method='bareis'): """ Compute Wronskian for [] of functions :: | f1 f2 ... fn | | f1' f2' ... fn' | | . . . . | W(f1, ..., fn) = | . . . . | | . . . . | | (n) (n) (n) | | D (f1) D (f2) ... D (fn) | see: http://en.wikipedia.org/wiki/Wronskian See Also ======== sympy.matrices.mutable.Matrix.jacobian hessian """ from dense import Matrix for index in range(0, len(functions)): functions[index] = sympify(functions[index]) n = len(functions) if n == 0: return 1 W = Matrix(n, n, lambda i, j: functions[i].diff(var, j)) return W.det(method)