numpy.polynomial.polynomial.polyval

numpy.polynomial.polynomial.polyval(x, c, tensor=True) [source]

Вычислить значение многочлена в точках x.

Если c имеет длину n + 1, эта функция возвращает значение

<img alt="p(x) = c_0 + c_1 * x + ... + c_n * x^n" src="data:image/svg+xml;base64,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

Параметр x преобразуется в массив только в том случае, если это кортеж или список, в противном случае он обрабатывается как скаляр. В любом случае, x или его элементы должны поддерживать умножение и сложение как с самими собой, так и с элементами c.

Если c является одномерным массивом, то p(x) будет иметь такую же форму, как и x. Если c является многомерным, то форма результата зависит от значения tensor. Если tensor имеет значение true, форма будет c.shape[1:] + x.shape. Если tensor имеет значение false, форма будет c.shape[1:]. Обратите внимание, что скаляры имеют форму (,).

Конечные нули в коэффициентах будут использоваться в вычислениях, поэтому их следует избегать, если эффективность является проблемой.

Параметры:

x : array_like, compatible object Если x является списком или кортежем, он преобразуется в массив ndarray, в противном случае он остается неизменным и обрабатывается как скаляр. В любом случае, x или его элементы должны поддерживать сложение и умножение как с самими собой, так и с элементами c. c : array_like Массив коэффициентов, упорядоченных так, что коэффициенты для членов степени n содержатся в c[n]. Если c многомерный, оставшиеся индексы перечисляют несколько полиномов. В двумерном случае коэффициенты можно рассматривать как хранящиеся в столбцах c. tensor : boolean, optional Если True, форма массива коэффициентов расширяется единицами справа, по одному для каждой размерности x. Скаляры имеют размерность 0 для этого действия. В результате каждый столбец коэффициентов в c оценивается для каждого элемента x. Если False, x транслируется по столбцам c для вычисления. Этот ключевой параметр полезен, когда c многомерный. Значение по умолчанию — True. Новое в версии 1.7.0.

Возвращаемое значение:

values : ndarray, compatible object Форма возвращаемого массива описана выше.

См. также

polyval2d, polygrid2d, polyval3d, polygrid3d

Примечания

Вычисление выполняется по методу Хорнера.

Примеры

>>> from numpy.polynomial.polynomial import polyval
>>> polyval(1, [1,2,3])
6.0
>>> a = np.arange(4).reshape(2,2)
>>> a
array([[0, 1],
       [2, 3]])
>>> polyval(a, [1,2,3])
array([[  1.,   6.],
       [ 17.,  34.]])
>>> coef = np.arange(4).reshape(2,2) # multidimensional coefficients
>>> coef
array([[0, 1],
       [2, 3]])
>>> polyval([1,2], coef, tensor=True)
array([[ 2.,  4.],
       [ 4.,  7.]])
>>> polyval([1,2], coef, tensor=False)
array([ 2.,  7.])