class_docstr: An Agent class for all optimization techniques.
class_docstr_tok: ["An","Agent","class","for","all","optimization","techniques","."]
docstr: Fills the agent's decision variables with a uniform distribution
  based on bounds limits.
docstr_tok: ["Fills","the","agent","'s","decision","variables","with","a","uniform","distribution","based","on","bounds","limits","."]
code: def fill_with_uniform(self) -> None:
      """Fills the agent's decision variables with a uniform distribution
      based on bounds limits.
  
      """
  
      for j, (lb, ub) in enumerate(zip(self.lb, self.ub)):
          self.position[j] = r.generate_uniform_random_number(
              lb, ub, self.n_dimensions
          )
  
imports: import time
  from typing import Dict, List, Optional, Union
  import numpy
  import opytimizer.math.random
  import opytimizer.utils.constant
  import opytimizer.utils.exception
  from opytimizer.utils import logging
label_desc: Use image node_id 22 for calling the Agent obj's underlying member method code with example usage: obj.fill_with_uniform() without return types