code: def test_single_condition():
      estimator = DecisionTreeRegressor()
  
      estimator.fit([[1], [2]], [1, 2])
  
      assembler = TreeModelAssembler(estimator)
      actual = assembler.assemble()
  
      expected = ast.IfExpr(
          ast.CompExpr(
              ast.FeatureRef(0), ast.NumVal(1.5), ast.CompOpType.LTE
          ),
          ast.NumVal(1.0),
          ast.NumVal(2.0),
      )
  
      assert cmp_exprs(actual, expected)
  
imports: from sklearn.tree import DecisionTreeClassifier, DecisionTreeRegressor
  from m2cgen import ast
  from m2cgen.assemblers import TreeModelAssembler
  from tests.utils import cmp_exprs
label_desc: Use image node_id 1 for calling a global function with example usage: test_single_condition() without return types