class_docstr: Abstract class that defines various tests for high-level optimizers
  
  Whenever an optimizer implementation inherits from ABCTestOptimizer,
  you don't need to write down all tests anymore. Instead, you can just
  specify all required fixtures in the test suite.
class_docstr_tok: ["Abstract","class","that","defines","various","tests","for","high-level","optimizers","Whenever","an","optimizer","implementation","inherits","from","ABCTestOptimizer",",","you","do","n't","need","to","write","down","all","tests","anymore",".","Instead",",","you","can","just","specify","all","required","fixtures","in","the","test","suite","."]
docstr: Test if error is raised with incomplete kwargs
docstr_tok: ["Test","if","error","is","raised","with","incomplete","kwargs"]
code: def test_obj_missing_kwargs(self, obj_with_args, optimizer, options):
      """Test if error is raised with incomplete kwargs"""
      x_max = 10 * np.ones(2)
      x_min = -1 * x_max
      bounds = (x_min, x_max)
      opt = optimizer(100, 2, options=options, bounds=bounds)
      with pytest.raises(TypeError):
          # kwargs `b` is missing here
          cost, pos = opt.optimize(obj_with_args, 1000, a=1)
  
imports: import abc
  import numpy
  import pytest
  from pyswarms.utils.functions.single_obj import rosenbrock, sphere
label_desc: Use image node_id 13 for calling the ABCTestOptimizer obj's underlying member method code with example usage: obj.test_obj_missing_kwargs(obj_with_args, optimizer, options) without return types