# scipy.special.chebyt#

scipy.special.chebyt(n, monic=False)[source]#

Chebyshev polynomial of the first kind.

Defined to be the solution of

$(1 - x^2)\frac{d^2}{dx^2}T_n - x\frac{d}{dx}T_n + n^2T_n = 0;$

$$T_n$$ is a polynomial of degree $$n$$.

Parameters:
nint

Degree of the polynomial.

monicbool, optional

If True, scale the leading coefficient to be 1. Default is False.

Returns:
Torthopoly1d

Chebyshev polynomial of the first kind.

chebyu

Chebyshev polynomial of the second kind.

Notes

The polynomials $$T_n$$ are orthogonal over $$[-1, 1]$$ with weight function $$(1 - x^2)^{-1/2}$$.

References

[AS]

Milton Abramowitz and Irene A. Stegun, eds. Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables. New York: Dover, 1972.

Examples

Chebyshev polynomials of the first kind of order $$n$$ can be obtained as the determinant of specific $$n \times n$$ matrices. As an example we can check how the points obtained from the determinant of the following $$3 \times 3$$ matrix lay exacty on $$T_3$$:

>>> import numpy as np
>>> import matplotlib.pyplot as plt
>>> from scipy.linalg import det
>>> from scipy.special import chebyt
>>> x = np.arange(-1.0, 1.0, 0.01)
>>> fig, ax = plt.subplots()
>>> ax.set_ylim(-2.0, 2.0)
>>> ax.set_title(r'Chebyshev polynomial $T_3$')
>>> ax.plot(x, chebyt(3)(x), label=rf'$T_3$')
>>> for p in np.arange(-1.0, 1.0, 0.1):
...     ax.plot(p,
...             det(np.array([[p, 1, 0], [1, 2*p, 1], [0, 1, 2*p]])),
...             'rx')
>>> plt.legend(loc='best')
>>> plt.show()


They are also related to the Jacobi Polynomials $$P_n^{(-0.5, -0.5)}$$ through the relation:

$P_n^{(-0.5, -0.5)}(x) = \frac{1}{4^n} \binom{2n}{n} T_n(x)$

Let’s verify it for $$n = 3$$:

>>> from scipy.special import binom
>>> from scipy.special import jacobi
>>> x = np.arange(-1.0, 1.0, 0.01)
>>> np.allclose(jacobi(3, -0.5, -0.5)(x),
...             1/64 * binom(6, 3) * chebyt(3)(x))
True


We can plot the Chebyshev polynomials $$T_n$$ for some values of $$n$$:

>>> x = np.arange(-1.5, 1.5, 0.01)
>>> fig, ax = plt.subplots()
>>> ax.set_ylim(-4.0, 4.0)
>>> ax.set_title(r'Chebyshev polynomials $T_n$')
>>> for n in np.arange(2,5):
...     ax.plot(x, chebyt(n)(x), label=rf'$T_n={n}$')
>>> plt.legend(loc='best')
>>> plt.show()