It's fine to call it. The next version of SymPy will use an LRU cache that
should limit the memory growth of the cache.

Aaron Meurer

On Wed, Nov 5, 2014 at 7:10 AM, nanaya tachibana <[email protected]>
wrote:

> Hello,
> Yestday I found an memory issue in my experiment program.
> I used sympy to generate legendre polynomials in my program and finally I
> found this part of code cause the problem that the memory which used by
> sympy cache cannot be released.
> I'm new to sympy. Is it a good manner to call clear_cache() manually?Or
> is there any problem in my code?
> Thanks.
>
>
> def generate_legendre_polynomials(max_degree):
>     """
>     Create a list of legendre polynomials from degree of zero to degree of
> max_degree.
>     """
>     x, n = symbols('x n')
>     legendre_polynomial_list = [1, x]
>
>     def nth_order_legendre(nth):
>         """
>         Create nth legendre polynomials iteratively
>         according to Bonnet’s recursion formula.
>         """
>         if nth <= 1:
>             return legendre_polynomial_list[nth]
>
>         for i in range(2, nth + 1):
>             g = legendre_polynomial_list[i - 1]
>             h = legendre_polynomial_list[i - 2]
>             p = 1/n * ((2 * n - 1) * x * g -  (n - 1) * h)
>             legendre_polynomial_list.append(expand(p.subs(n, i - 1)))
>
>     nth_order_legendre(max_degree)
>     return legendre_polynomial_list
>
> legendre_polynomial_list = generate_legendre_polynomials(100)  # legendre
> polynomial table
> def generate_target_function(degree, legendre_polynomial_list=None):
>     """
>     Generate a target function randomly
>     according to the target function formula.
>     """
>     x = symbols('x')
>     if legendre_polynomial_list is None or len(legendre_polynomial_list) -
> 1 < degree:
>         legendre_polynomials = generate_legendre_polynomials(degree)
>     else:
>         legendre_polynomials = legendre_polynomial_list[:degree + 1]
>     alphas = [np.random.standard_normal() for i in range(degree + 1)]
>
>     f = np.dot(alphas, legendre_polynomials)  # sum of a_i * L_i
>     Z = integrate(f**2, (x, -1, 1)) / 2  # integrate f**2 from -1 to 1
>     f = f / sqrt(Z)  # normalized f
>     return f
>
> # memory usege goes up after each iteration
> for i in range(1000):
>     generate_target_function(20, legendre_polynomial_list)
>
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