python sumpy.diff()関数(導関数またはバイアスを求める?)

from sympy/core/function.py

def diff(f, *symbols, **kwargs):
    """
    Differentiate f with respect to symbols.

    This is just a wrapper to unify .diff() and the Derivative class; its
    interface is similar to that of integrate().  You can use the same
    shortcuts for multiple variables as with Derivative.  For example,
    diff(f(x), x, x, x) and diff(f(x), x, 3) both return the third derivative
    of f(x).

    You can pass evaluate=False to get an unevaluated Derivative class.  Note
    that if there are 0 symbols (such as diff(f(x), x, 0), then the result will
    be the function (the zeroth derivative), even if evaluate=False.

 f     。

          .diff（） Derivative     ；        Integrated（）   。            “  ”       。   ，diff（f（x），x，x，x） diff（f（x），x，3）   f（x）     。

          validate = False          。    ，   0   （  diff（f（x），x，0）），      = False，        （   ）。
     
    Examples
    ========

    >>> from sympy import sin, cos, Function, diff
    >>> from sympy.abc import x, y
    >>> f = Function('f')

    >>> diff(sin(x), x)
    cos(x)
    >>> diff(f(x), x, x, x)
    Derivative(f(x), (x, 3))
    >>> diff(f(x), x, 3)
    Derivative(f(x), (x, 3))
    >>> diff(sin(x)*cos(y), x, 2, y, 2)
    sin(x)*cos(y)

    >>> type(diff(sin(x), x))
    cos
    >>> type(diff(sin(x), x, evaluate=False))
    
    >>> type(diff(sin(x), x, 0))
    sin
    >>> type(diff(sin(x), x, 0, evaluate=False))
    sin

    >>> diff(sin(x))
    cos(x)
    >>> diff(sin(x*y))
    Traceback (most recent call last):
    ...
    ValueError: specify differentiation variables to differentiate sin(x*y)

    Note that ``diff(sin(x))`` syntax is meant only for convenience
    in interactive sessions and should be avoided in library code.

    References
    ==========

    http://reference.wolfram.com/legacy/v5_2/Built-inFunctions/AlgebraicComputation/Calculus/D.html

    See Also
    ========

    Derivative
    idiff: computes the derivative implicitly

    """
    if hasattr(f, 'diff'):
        return f.diff(*symbols, **kwargs)
    kwargs.setdefault('evaluate', True)
    return Derivative(f, *symbols, **kwargs)