def verify_derivatives(self,inf,cov,mean,lik,thr):
""" Compare numerical against analytical derivatives.
"""
n,D,X,y = self.n,self.D,self.X,self.y
post,nlZ,dnlZ = inf(cov,mean,lik,X,y,deriv=True)
h = 1e-5
hyp = cov.get_hyp(); dhyp = np.zeros_like(hyp) # covariance parameters
for i in range(len(hyp)):
hyp[i] += h; cov.set_hyp(hyp)
_,nlZh = inf(cov,mean,lik,X,y)
hyp[i] -= h; cov.set_hyp(hyp)
dhyp[i] = (nlZh-nlZ)/h
self.assertLessEqual(erel(dhyp,dnlZ.cov),thr)
hyp = mean.get_hyp(); dhyp = np.zeros_like(hyp) # mean parameters
for i in range(len(hyp)):
hyp[i] += h; mean.set_hyp(hyp)
_,nlZh = inf(cov,mean,lik,X,y)
hyp[i] -= h; mean.set_hyp(hyp)
dhyp[i] = (nlZh-nlZ)/h
self.assertLessEqual(erel(dhyp,dnlZ.mean),thr)
hyp = lik.get_hyp(); dhyp = np.zeros_like(hyp) # likelihood parameters
for i in range(len(hyp)):
hyp[i] += h; lik.set_hyp(hyp)
_,nlZh = inf(cov,mean,lik,X,y)
hyp[i] -= h; lik.set_hyp(hyp)
dhyp[i] = (nlZh-nlZ)/h
self.assertLessEqual(erel(dhyp,dnlZ.lik),thr)
from inf import *
a = inf(1, lambda x: x % 3 == 0)
print(a.take(10))
print(a.take(10))
print("\n")
b = inf(2, 2)
print(b.take(10))
print(b.take(10))
print("\n")
c = inf(2, 3)
print(c.take(10))
print(c.take(10))