code: def build_toy_dataset(N, V):
      """A simulator mimicking the data set from 2015-2016 NBA season with
      308 NBA players and ~150,000 shots."""
      L = np.tril(np.random.normal(2.5, 0.1, size=[V, V]))
      K = np.matmul(L, L.T)
      x = np.zeros([N, V])
      for n in range(N):
          f_n = multivariate_normal.rvs(cov=K, size=1)
          for v in range(V):
              x[n, v] = poisson.rvs(mu=np.exp(f_n[v]), size=1)
  
      return x
  
file_path: edward/examples/cox_process.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import edward
  import numpy
  import tensorflow
  from edward.models import MultivariateNormalTriL, Normal, Poisson
  from edward.util import rbf
  from scipy.stats import multivariate_normal, poisson
label_desc: Use image node_id 1 for calling a global function with example usage: build_toy_dataset(N, V) and returns: x