original_docstring: 
      Generates a multidimensional grid uniformly distributed.
      :param bounds: tuple defining the box constraints.
      :num_data: number of data points to generate.
  
      
docstring: Generates a multidimensional grid uniformly distributed.
docstring_tokens: Generates a multidimensional grid uniformly distributed .
code: def samples_multidimensional_uniform(bounds,num_data):
      '''
      Generates a multidimensional grid uniformly distributed.
      :param bounds: tuple defining the box constraints.
      :num_data: number of data points to generate.
  
      '''
      dim = len(bounds)
      Z_rand = np.zeros(shape=(num_data,dim))
      for k in range(0,dim): Z_rand[:,k] = np.random.uniform(low=bounds[k][0],high=bounds[k][1],size=num_data)
      return Z_rand
code_tokens: def samples_multidimensional_uniform ( bounds , num_data ) : dim = len ( bounds ) Z_rand = np . zeros ( shape = ( num_data , dim ) ) for k in range ( 0 , dim ) : Z_rand [ : , k ] = np . random . uniform ( low = bounds [ k ] [ 0 ] , high = bounds [ k ] [ 1 ] , size = num_data ) return Z_rand
short_docstring: Generates a multidimensional grid uniformly distributed.
short_docstring_tokens: Generates a multidimensional grid uniformly distributed .
comment: '''
      Generates a multidimensional grid uniformly distributed.
      :param bounds: tuple defining the box constraints.
      :num_data: number of data points to generate.
  
      '''