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chebyt(n, monic=False)

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 $n$ .

Notes

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

Parameters

n : int

Degree of the polynomial.

monic : bool, optional

If :None:None:`True`, scale the leading coefficient to be 1. Default is :None:None:`False`.

Returns

T : orthopoly1d

Chebyshev polynomial of the first kind.

Chebyshev polynomial of the first kind.

See Also

chebyu

Chebyshev polynomial of the second kind.

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 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 chebyt
... 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 $n$ :

>>> import matplotlib.pyplot as plt
... from scipy.special import chebyt
... 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()
See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

scipy.special._orthogonal.chebyu scipy.special._orthogonal.chebyc scipy.special._orthogonal.chebyt

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GitHub : /scipy/special/_orthogonal.py#1634
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