def test_multi_class():
estimator = linear_model.LogisticRegression()
estimator.coef_ = np.array([[1, 2], [3, 4], [5, 6]])
estimator.intercept_ = np.array([7, 8, 9])
assembler = assemblers.LinearModelAssembler(estimator)
actual = assembler.assemble()
expected = ast.VectorVal([
ast.SubroutineExpr(
ast.BinNumExpr(
ast.BinNumExpr(
ast.NumVal(7),
ast.BinNumExpr(
ast.FeatureRef(0),
ast.NumVal(1),
ast.BinNumOpType.MUL),
ast.BinNumOpType.ADD),
ast.BinNumExpr(
ast.FeatureRef(1),
ast.NumVal(2),
ast.BinNumOpType.MUL),
ast.BinNumOpType.ADD)),
ast.SubroutineExpr(
ast.BinNumExpr(
ast.BinNumExpr(
ast.NumVal(8),
ast.BinNumExpr(
ast.FeatureRef(0),
ast.NumVal(3),
ast.BinNumOpType.MUL),
ast.BinNumOpType.ADD),
ast.BinNumExpr(
ast.FeatureRef(1),
ast.NumVal(4),
ast.BinNumOpType.MUL),
ast.BinNumOpType.ADD)),
ast.SubroutineExpr(
ast.BinNumExpr(
ast.BinNumExpr(
ast.NumVal(9),
ast.BinNumExpr(
ast.FeatureRef(0),
ast.NumVal(5),
ast.BinNumOpType.MUL),
ast.BinNumOpType.ADD),
ast.BinNumExpr(
ast.FeatureRef(1),
ast.NumVal(6),
ast.BinNumOpType.MUL),
ast.BinNumOpType.ADD))])
assert utils.cmp_exprs(actual, expected)
def test_single_feature():
estimator = linear_model.LinearRegression()
estimator.coef_ = [1]
estimator.intercept_ = 3
assembler = assemblers.LinearModelAssembler(estimator)
actual = assembler.assemble()
expected = ast.BinNumExpr(
ast.NumVal(3),
ast.BinNumExpr(ast.FeatureRef(0), ast.NumVal(1), ast.BinNumOpType.MUL),
ast.BinNumOpType.ADD)
assert utils.cmp_exprs(actual, expected)
def test_binary_class():
estimator = linear_model.LogisticRegression()
estimator.coef_ = np.array([[1, 2]])
estimator.intercept_ = np.array([3])
assembler = assemblers.LinearModelAssembler(estimator)
actual = assembler.assemble()
expected = ast.BinNumExpr(
ast.BinNumExpr(
ast.NumVal(3),
ast.BinNumExpr(ast.FeatureRef(0), ast.NumVal(1),
ast.BinNumOpType.MUL), ast.BinNumOpType.ADD),
ast.BinNumExpr(ast.FeatureRef(1), ast.NumVal(2), ast.BinNumOpType.MUL),
ast.BinNumOpType.ADD)
assert utils.cmp_exprs(actual, expected)
