コード例 #1
0
ファイル: randtest.py プロジェクト: devs1991/test_edx_docmode
def test_derivative_numerically(f, z, tol=1.0e-6, a=2, b=-1, c=3, d=1):
    """
    Test numerically that the symbolically computed derivative of f
    with respect to z is correct.

    Examples:
    >>> from sympy import sin, cos
    >>> from sympy.abc import x
    >>> from sympy.utilities.randtest import test_derivative_numerically as td
    >>> td(sin(x), x)
    True
    """
    from sympy.core.function import Derivative
    z0 = random_complex_number(a, b, c, d)
    f1 = f.diff(z).subs(z, z0)
    f2 = Derivative(f, z).doit_numerically(z0)
    return comp(f1.n(), f2.n(), tol)
コード例 #2
0
ファイル: randtest.py プロジェクト: Kimay/sympy
def test_derivative_numerically(f, z, tol=1.0e-6, a=2, b=-1, c=3, d=1):
    """
    Test numerically that the symbolically computed derivative of f
    with respect to z is correct.

    Examples
    ========
    >>> from sympy import sin, cos
    >>> from sympy.abc import x
    >>> from sympy.utilities.randtest import test_derivative_numerically as td
    >>> td(sin(x), x)
    True
    """
    from sympy.core.function import Derivative
    z0 = random_complex_number(a, b, c, d)
    f1 = f.diff(z).subs(z, z0)
    f2 = Derivative(f, z).doit_numerically(z0)
    return comp(f1.n(), f2.n(), tol)
コード例 #3
0
ファイル: randtest.py プロジェクト: dyao-vu/meta-core
def test_derivative_numerically(f, z, tol=1.0e-6, a=2, b=-1, c=3, d=1):
    """
    Test numerically that the symbolically computed derivative of f
    with respect to z is correct.

    This routine does not test whether there are Floats present with
    precision higher than 15 digits so if there are, your results may
    not be what you expect due to round-off errors.

    Examples
    ========

    >>> from sympy import sin, cos
    >>> from sympy.abc import x
    >>> from sympy.utilities.randtest import test_derivative_numerically as td
    >>> td(sin(x), x)
    True
    """
    from sympy.core.function import Derivative
    z0 = random_complex_number(a, b, c, d)
    f1 = f.diff(z).subs(z, z0)
    f2 = Derivative(f, z).doit_numerically(z0)
    return comp(f1.n(), f2.n(), tol)
コード例 #4
0
def test_derivative_numerically(f, z, tol=1.0e-6, a=2, b=-1, c=3, d=1):
    """
    Test numerically that the symbolically computed derivative of f
    with respect to z is correct.

    This routine does not test whether there are Floats present with
    precision higher than 15 digits so if there are, your results may
    not be what you expect due to round-off errors.

    Examples
    ========

    >>> from sympy import sin, cos
    >>> from sympy.abc import x
    >>> from sympy.utilities.randtest import test_derivative_numerically as td
    >>> td(sin(x), x)
    True
    """
    from sympy.core.function import Derivative
    z0 = random_complex_number(a, b, c, d)
    f1 = f.diff(z).subs(z, z0)
    f2 = Derivative(f, z).doit_numerically(z0)
    return comp(f1.n(), f2.n(), tol)