def test_smooth_minmax_default_sense():
# Test that smooth_minmax defaults to maximise
assert smooth_minmax(
1,
2,
0,
) == 2
def test_smooth_minmax_expr(simple_model):
# Test that smooth_minmax works with Pyomo components
assert value(smooth_minmax(simple_model.a,
simple_model.b,
0,
sense='max')) == 4.0
assert value(smooth_minmax(simple_model.a,
simple_model.b,
0,
sense='min')) == -4.0
assert value(smooth_minmax(simple_model.a,
simple_model.b,
sense='max')) == pytest.approx(4.0, abs=1e-4)
assert value(smooth_minmax(simple_model.a,
simple_model.b,
sense='min')) == pytest.approx(-4.0, abs=1e-4)
assert value(smooth_minmax(simple_model.a,
simple_model.b,
simple_model.e,
sense='max')) == pytest.approx(4.0, abs=1e-4)
assert value(smooth_minmax(simple_model.a,
simple_model.b,
simple_model.e,
sense='min')) == pytest.approx(-4.0, abs=1e-4)
def test_smooth_minmax_maths():
# Test basic smooth_minmax functionality
assert smooth_minmax(1, 2, 0, sense='max') == 2
assert smooth_minmax(1, 2, 0, sense='min') == 1
assert smooth_minmax(5.0, 3, 0.0, sense='max') == 5
assert smooth_minmax(5.0, 3, 0.0, sense='min') == 3
assert (smooth_minmax(2.0, 12.0, 1e-4, 'max') ==
pytest.approx(12.0, abs=1e-4))
assert (smooth_minmax(2.0, 12.0, 1e-4, 'min') ==
pytest.approx(2.0, abs=1e-4))
assert (smooth_minmax(32.0, 12.0, sense='max') ==
pytest.approx(32.0, abs=1e-4))
assert (smooth_minmax(32.0, 12.0, sense='min') ==
pytest.approx(12.0, abs=1e-4))
def test_smooth_minmax_sense_errors():
# Test that smooth_abs returns meaningful errors when given invalid sense
with pytest.raises(ValueError):
smooth_minmax(1.0, 1.0, sense="foo")
with pytest.raises(ValueError):
smooth_minmax(1.0, 1.0, sense=1.0)
with pytest.raises(ValueError):
smooth_minmax(1.0, 1.0, sense=[1.0])
def test_smooth_minmax_eps_errors():
# Test that smooth_abs returns meaningful errors when given invalid eps
with pytest.raises(TypeError):
smooth_minmax(1.0, 1.0, "foo")
with pytest.raises(TypeError):
smooth_minmax(1.0, 1.0, [1, 2, 3])
