Update 3a_likelihood_ratio.ipynb
from 10k to 1k in sampling.random_morphing_points
],
"source": [
"x, theta0, theta1, y, r_xz, t_xz, n_effective = sampler.sample_train_ratio(\n",
- " theta0=sampling.random_morphing_points(10000, [('gaussian', 0., 0.5), ('gaussian', 0., 0.5)]),\n",
+ " theta0=sampling.random_morphing_points(1000, [('gaussian', 0., 0.5), ('gaussian', 0., 0.5)]),\n",
" theta1=sampling.benchmark('sm'),\n",
" n_samples=500000,\n",
" folder='./data/samples',\n",
