def test_hermite(self):
v = orth.eval_hermite(70, 1.0)
a = -1.457076485701412e60
assert_allclose(v,a)
def test_hermite_nan(n, x):
# Regression test for gh-11369.
assert np.isnan(orth.eval_hermite(n, x)) == np.any(np.isnan([n, x]))
assert np.isnan(orth.eval_hermitenorm(n, x)) == np.any(np.isnan([n, x]))
def gauss_hermite(u, sigma=1., m=0):
gaus_herm = gaussian(u, sigma) * spo.eval_hermite(m, u)
return gaus_herm
def test_hermite_domain():
# Regression test for gh-11091.
assert np.isnan(orth.eval_hermite(-1, 1.0))
assert np.isnan(orth.eval_hermitenorm(-1, 1.0))
from scipy.special import gamma
from scipy.special.orthogonal import eval_hermite, eval_hermitenorm
import matplotlib.pyplot as plt
import numpy as np
#psi = lambda n,x: 1.0/np.sqrt((2**n*gamma(n+1)*np.sqrt(np.pi))) * np.exp(-x**2/2.0) * eval_hermitenorm(n, x)
psi = lambda n,x: 1.0/np.sqrt((2**n*gamma(n+1)*np.sqrt(np.pi))) * np.exp(-x**2/2.0) * eval_hermite(n, x)
x = np.linspace(-5, 5, 500)
for n in xrange(6):
plt.plot(x, psi(n,x), label=r"$\psi_"+str(n)+r"(x)$")
plt.grid(True)
plt.xlim(-5,5)
#plt.ylim(-5,5)
plt.xlabel(r"$x$")
plt.ylabel(r"$\psi_n(x)$")
plt.legend(loc="lower right")
plt.title(r"Hermite functions $\psi_n$")
#plt.show()
plt.savefig('hermite.pdf')
