code: def make_random_dense_gaussian_matrix(
      n_rows, n_columns, mu=0, sigma=0.01
  ):
      """
      Make some random data with Gaussian distributed values
      """
      np.random.seed(142352345)
      res = np.random.normal(mu, sigma, n_rows * n_columns)
      return np.reshape(res, (n_rows, n_columns))
  
file_path: catboost/contrib/python/scipy/py2/scipy/linalg/tests/test_sketches.py
imports: from __future__ import division, print_function, absolute_import
  import numpy
  from scipy.linalg import clarkson_woodruff_transform
  from numpy.testing import assert_
label_desc: Use image node_id 1 for calling a global function with example usage: make_random_dense_gaussian_matrix(n_rows, n_columns, mu, sigma) and returns: np