code: def test_glm_cloglog_link_func():
      estimator = utils.StatsmodelsSklearnLikeWrapper(
          sm.GLM,
          dict(
              init=dict(
                  family=sm.families.Binomial(
                      sm.families.links.cloglog()
                  )
              ),
              fit=dict(maxiter=1),
          ),
      )
      estimator = estimator.fit([[1], [2]], [0.1, 0.2])
  
      assembler = assemblers.StatsmodelsModelAssemblerSelector(
          estimator
      )
      actual = assembler.assemble()
  
      expected = ast.BinNumExpr(
          ast.NumVal(1.0),
          ast.ExpExpr(
              ast.BinNumExpr(
                  ast.NumVal(0.0),
                  ast.ExpExpr(
                      ast.BinNumExpr(
                          ast.NumVal(0.0),
                          ast.BinNumExpr(
                              ast.FeatureRef(0),
                              ast.NumVal(-0.8914468745),
                              ast.BinNumOpType.MUL,
                          ),
                          ast.BinNumOpType.ADD,
                      )
                  ),
                  ast.BinNumOpType.SUB,
              )
          ),
          ast.BinNumOpType.SUB,
      )
  
      assert utils.cmp_exprs(actual, expected)
  
imports: import numpy
  import pytest
  import statsmodels.api
  from statsmodels.regression.process_regression import ProcessMLE
  from m2cgen import assemblers, ast
  from tests import utils
label_desc: Use image node_id 15 for calling a global function with example usage: test_glm_cloglog_link_func() without return types