numpy.polynomial.polynomial.polyvalfromroots

polynomial.polynomial.polyvalfromroots(x, r, tensor=True)[源代码]

在点x处计算由其根指定的多项式。

如果 r 长度 N ,此函数返回值

System Message: WARNING/2 (p(x)=\prod n=1 ^ n(x-r_n))

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参数 x 只有当数组是元组或列表时才转换为数组,否则将被视为标量。在任何一种情况下,要么 x 或者它的元素必须支持自身和元素的乘法和加法。 r .

如果 r 是一维数组,然后 p(x) 将具有与相同的形状 x . 如果 r 是多维的,则结果的形状取决于 tensor .如果 tensor is ` ` true``形状将为r.shape [1:] +x.shape;也就是说,每个多项式的每个值都是 `x .如果 tensorFalse ,形状为R。 [1:] ;也就是说,每个多项式只针对 x . 请注意,标量具有形状(,)。

1.12 新版功能.

参数
x类似数组的兼容对象

如果 x 是一个列表或元组,它被转换为一个ndarray,否则它将保持不变并被视为一个标量。在任何一种情况下, x 或者其元素必须支持与自身和元素的加法和乘法 r .

rarray_like

根数组。如果 r 是多维的,第一个索引是根索引,而其余的索引枚举多个多项式。例如,在二维情况下,每个多项式的根可以被认为是存储在 r .

tensor布尔值,可选

如果为真,则根数组的形状将用右边的形状扩展,每个维度的形状都扩展一个。 x . 此操作的标量的维度为0。结果是每列系数 r 对的每个元素进行了评估 x . 如果是假的, x 是通过以下列广播的 r 用于评估。当 r 是多维的。默认值为true。

返回
valuesndarray,兼容对象

上面描述了返回数组的形状。

实例

>>> from numpy.polynomial.polynomial import polyvalfromroots
>>> polyvalfromroots(1, [1,2,3])
0.0
>>> a = np.arange(4).reshape(2,2)
>>> a
array([[0, 1],
       [2, 3]])
>>> polyvalfromroots(a, [-1, 0, 1])
array([[-0.,   0.],
       [ 6.,  24.]])
>>> r = np.arange(-2, 2).reshape(2,2) # multidimensional coefficients
>>> r # each column of r defines one polynomial
array([[-2, -1],
       [ 0,  1]])
>>> b = [-2, 1]
>>> polyvalfromroots(b, r, tensor=True)
array([[-0.,  3.],
       [ 3., 0.]])
>>> polyvalfromroots(b, r, tensor=False)
array([-0.,  0.])