code: def samples_multidimensional_uniform(bounds, points_count):
      """
      Generates a multidimensional grid uniformly distributed.
      :param bounds: tuple defining the box constraints.
      :points_count: number of data points to generate.
      """
      dim = len(bounds)
      Z_rand = np.zeros(shape=(points_count, dim))
      for k in range(0, dim):
          Z_rand[:, k] = np.random.uniform(
              low=bounds[k][0], high=bounds[k][1], size=points_count
          )
      return Z_rand
  
file_path: GPyOpt/GPyOpt/experiment_design/random_design.py
imports: import numpy
  from .base import ExperimentDesign
  from ..core.task.variables import BanditVariable, DiscreteVariable, CategoricalVariable
label_desc: Use image node_id 1 for calling a global function with example usage: samples_multidimensional_uniform(bounds, points_count) and returns: Z_rand