symbolic.py 文件源码

def grad(f, basis, for_numerical=True):
    """
    Compute the symbolic gradient of a vector-valued function with respect to a
    basis.

    Parameters
    ----------
    f : 1D array_like of sympy Expressions
        The vector-valued function to compute the gradient of.
    basis : 1D array_like of sympy symbols
        The basis symbols to compute the gradient with respect to.
    for_numerical : bool, optional
        A placeholder for the option of numerically computing the gradient.

    Returns
    -------
    grad : 2D array_like of sympy Expressions
        The symbolic gradient.
    """
    if hasattr(f, '__len__'):  # as of version 1.1.1, Array isn't supported
        f = sp.Matrix(f)

    return f.__class__([
        [
            sp.diff(f[x], basis[y])
            if not for_numerical or not f[x].has(sp.sign(basis[y])) else 0
            for y in range(len(basis))
        ] for x in range(len(f))
    ])