Repository: scipy/scipy
File: scipy/signal/tests/test_waveforms.py (Python)

Code before:
    def test_unique(self, xp):
        t = xp.linspace(0, 2*np.pi, 1000)
        y = square(t)
        assert y.shape == t.shape
        unique = np.unique(_xp_copy_to_numpy(y))
        assert set(unique).issubset({-1.0, 1.0})

    def test_dtype(self, xp):
        waveform = square(xp.asarray(1, dtype=xp.float32),
                                    duty=xp.asarray(0.5, dtype=xp.float32))
        assert waveform.dtype == xp.float64

        waveform = square(xp.asarray(1, dtype=xp.float64))
        assert waveform.dtype == xp.float64

    @pytest.mark.parametrize("duty", [0.1, 0.25, 0.5, 0.75])
    def test_duty_cycle_fraction(self, duty, xp):
        t = xp.linspace(0, 2*xp.pi, 10_000, endpoint=False, dtype=xp.float64)
        y = square(t, duty=duty)

        fraction_high = xp.mean(xp.asarray(y == 1.0, dtype=xp.float64))
        xp_assert_close(fraction_high, xp.asarray(duty, dtype=xp.float64)[()],
                        rtol=1e-8)
        xp_assert_close(xp.mean(y), xp.asarray(2*duty - 1, dtype=xp.float64)[()])

    @pytest.mark.parametrize("duty,expected", [(1, 1), (0, -1)])
    def test_duty_edge_cases(self, duty, expected, xp):
        t = xp.linspace(0, 2*xp.pi, 100)
        y = square(t, duty=duty)
        xp_assert_equal(y, xp.full_like(t, expected, dtype=xp.float64))

    def test_periodic(self, xp):
        t = xp.linspace(0, 2*xp.pi, 10, endpoint=False, dtype=xp.float64)
        y1 = square(t, duty=0.4)
        y2 = square(t + 2*xp.pi, duty=0.4)

        xp_assert_equal(y1, y2)

    @pytest.mark.parametrize("duty", [-0.1, 1.1, 2.0])
    def test_invalid_duty(self, duty, xp):
        t = xp.linspace(0, 2*np.pi, 10)
        y = square(t, duty=duty)

        assert xp.all(xp.isnan(y))


Review comment (suggestion):
```suggestion
    @pytest.mark.parametrize("duty,expected", [(1., 1), (0., -1)])
```

Code after:
    def test_unique(self, xp):
        t = xp.linspace(0, 2*np.pi, 1000)
        y = square(t)
        assert y.shape == t.shape
        unique = np.unique(_xp_copy_to_numpy(y))
        assert set(unique).issubset({-1.0, 1.0})

    @pytest.mark.xfail_xp_backends("cupy", reason="cupy/cupy/issues/9541")
    @pytest.mark.parametrize("t_dtype", ["float32", "float64"])
    @pytest.mark.parametrize("duty_dtype", ["float32", "float64"])
    def test_dtype(self, t_dtype, duty_dtype, xp):
        t_dtype = getattr(xp, t_dtype)
        duty_dtype = getattr(xp, duty_dtype)
        waveform = square(xp.asarray(1, dtype=t_dtype),
                          duty=xp.asarray(0.5, dtype=duty_dtype))
        assert waveform.dtype == xp.result_type(t_dtype, duty_dtype)

    @pytest.mark.xfail_xp_backends("cupy", reason="cupy/cupy/issues/9541")
    @pytest.mark.parametrize("dtype", [None, "float32", "float64"])
    @pytest.mark.parametrize("duty", [0.1, 0.25, 0.5, 0.75])
    def test_duty_cycle_fraction(self, dtype, duty, xp):
        dtype = dtype if dtype is None else getattr(xp, dtype)  # duty is Python float
        # imperfect arithmetic w/ JAX `float32` causes trouble with duty=0.5
        # t = xp.linspace(0, 2*xp.pi, 10000, endpoint=False, dtype=dtype)
        t = xp.arange(10000., dtype=dtype) / 10000 * 2*xp.pi
        y = square(t, duty=duty)

        dtype = xp_default_dtype(xp) if dtype is None else dtype
        fraction_high = xp.mean(xp.asarray(y == 1.0, dtype=dtype))
        xp_assert_close(fraction_high, xp.asarray(duty, dtype=dtype)[()])
        xp_assert_close(xp.mean(y), xp.asarray(2*duty - 1, dtype=dtype)[()])

    @pytest.mark.parametrize("duty, expected", [(1., 1.), (0., -1.)])
    def test_duty_edge_cases(self, duty, expected, xp):
        t = xp.linspace(0, 2*xp.pi, 100)
        y = square(t, duty=duty)
        xp_assert_equal(y, xp.full(t.shape, expected))

    def test_periodic(self, xp):
        t = xp.linspace(0, 2*xp.pi, 10, endpoint=False, dtype=xp.float64)
        y1 = square(t, duty=0.4)
        y2 = square(t + 2*xp.pi, duty=0.4)

        xp_assert_equal(y1, y2)

    @pytest.mark.parametrize("duty", [-0.1, 1.1, 2.0])
    def test_invalid_duty(self, duty, xp):
        t = xp.linspace(0, 2*np.pi, 10)
        y = square(t, duty=duty)

        assert xp.all(xp.isnan(y))