code: def log_gaussian_pdf(theta, sigma=1, mu=0, ndim=None):
      if ndim is None:
          try:
              ndim = len(theta)
          except TypeError:
              assert isinstance(theta, (float, int)), theta
              ndim = 1
      logl = -(np.sum((theta - mu) ** 2) / (2 * sigma**2))
      logl -= np.log(2 * np.pi * (sigma**2)) * ndim / 2.0
      return logl
  
imports: import copy
  import numpy
  from scipy.stats import multivariate_normal
  import scipy.special
label_desc: Use image node_id 1 for calling a global function with example usage: log_gaussian_pdf(theta, sigma, mu, ndim) and returns: logl