implement dpnp.fft.fftfreq and dpnp.fft.rfftfreq

dpnp/fft/dpnp_iface_fft.py

@@ -197,19 +197,113 @@ def fft2(x, s=None, axes=(-2, -1), norm=None):
     return call_origin(numpy.fft.fft2, x, s, axes, norm)
 
 
-def fftfreq(n=None, d=1.0):
+def fftfreq(n, d=1.0, device=None, usm_type=None, sycl_queue=None):
     """
-    Compute the one-dimensional discrete Fourier Transform sample frequencies.
+    Return the Discrete Fourier Transform sample frequencies.
+
+    The returned float array `f` contains the frequency bin centers in cycles
+    per unit of the sample spacing (with zero at the start). For instance, if
+    the sample spacing is in seconds, then the frequency unit is cycles/second.
+
+    Given a window length `n` and a sample spacing `d`::
+
+      f = [0, 1, ...,   n/2-1,     -n/2, ..., -1] / (d*n)   if n is even
+      f = [0, 1, ..., (n-1)/2, -(n-1)/2, ..., -1] / (d*n)   if n is odd
 
     For full documentation refer to :obj:`numpy.fft.fftfreq`.
 
-    Limitations
-    -----------
-    Parameter `d` is unsupported.
+    Parameters
+    ----------
+    n : int
+        Window length.
+    d : scalar, optional
+        Sample spacing (inverse of the sampling rate).
+        Default: ``1``.
+    device : {None, string, SyclDevice, SyclQueue}, optional
+        An array API concept of device where the output array is created.
+        The `device` can be ``None`` (the default), an OneAPI filter selector
+        string, an instance of :class:`dpctl.SyclDevice` corresponding to
+        a non-partitioned SYCL device, an instance of :class:`dpctl.SyclQueue`,
+        or a `Device` object returned by
+        :obj:`dpnp.dpnp_array.dpnp_array.device` property.
+    usm_type : {None, "device", "shared", "host"}, optional
+        The type of SYCL USM allocation for the output array.
+        Default: ``None``.
+    sycl_queue : {None, SyclQueue}, optional
+        A SYCL queue to use for output array allocation and copying.
+        Default: ``None``.
+
+    Returns
+    -------
+    f : dpnp.ndarray
+        Array of length `n` containing the sample frequencies.
+
+    See Also
+    --------
+    :obj:`dpnp.fft.rfftfreq` : Return the Discrete Fourier Transform sample
+                        frequencies (for usage with :obj:`dpnp.fft.rfft` and
+                        :obj:`dpnp.fft.irfft`).
+
+    Examples
+    --------
+    >>> import dpnp as np
+    >>> signal = np.array([-2, 8, 6, 4, 1, 0, 3, 5])
+    >>> fourier = np.fft.fft(signal)
+    >>> n = signal.size
+    >>> timestep = 0.1
+    >>> freq = np.fft.fftfreq(n, d=timestep)
+    >>> freq
+    array([ 0.  ,  1.25,  2.5 ,  3.75, -5.  , -3.75, -2.5 , -1.25])
+
+    Creating the output array on a different device or with a
+    specified usm_type:
+
+    >>> x = np.fft.fftfreq(n, d=timestep) # default case
+    >>> x.shape, x.device, x.usm_type
+    ((8, ), Device(level_zero:gpu:0), 'device')
+
+    >>> y = np.fft.fftfreq(n, d=timestep, device="cpu")
+    >>> y.shape, y.device, y.usm_type
+    ((8, ), Device(opencl:cpu:0), 'device')
+
+    >>> z = np.fft.fftfreq(n, d=timestep, usm_type="host")
+    >>> z.shape, z.device, z.usm_type
+    ((8, ), Device(level_zero:gpu:0), 'host')
 
     """
 
-    return call_origin(numpy.fft.fftfreq, n, d)
+    if not isinstance(n, int):
+        raise ValueError("`n` should be an integer")
+    if not dpnp.isscalar(d):
+        raise ValueError("`d` should be an scalar")
+    val = 1.0 / (n * d)
+    results = dpnp.empty(
+        n,
+        dtype=dpnp.intp,
+        device=device,
+        usm_type=usm_type,
+        sycl_queue=sycl_queue,
+    )
+    N = (n - 1) // 2 + 1
+    p1 = dpnp.arange(
+        0,
+        N,
+        dtype=dpnp.intp,
+        device=device,
+        usm_type=usm_type,
+        sycl_queue=sycl_queue,
+    )
+    results[:N] = p1
+    p2 = dpnp.arange(
+        -(n // 2),
+        0,
+        dtype=dpnp.intp,
+        device=device,
+        usm_type=usm_type,
+        sycl_queue=sycl_queue,
+    )
+    results[N:] = p2
+    return results * val
 
 
 def fftn(x, s=None, axes=None, norm=None):
@@ -870,19 +964,103 @@ def rfft2(x, s=None, axes=(-2, -1), norm=None):
     return call_origin(numpy.fft.rfft2, x, s, axes, norm)
 
 
-def rfftfreq(n=None, d=1.0):
+def rfftfreq(n, d=1.0, device=None, usm_type=None, sycl_queue=None):
     """
-    Compute the one-dimensional discrete Fourier Transform sample frequencies.
+    Return the Discrete Fourier Transform sample frequencies
+    (for usage with :obj:`dpnp.fft.rfft`, :obj:`dpnp.fft.irfft`).
+
+    The returned float array `f` contains the frequency bin centers in cycles
+    per unit of the sample spacing (with zero at the start). For instance, if
+    the sample spacing is in seconds, then the frequency unit is cycles/second.
+
+    Given a window length `n` and a sample spacing `d`::
+
+      f = [0, 1, ...,     n/2-1,     n/2] / (d*n)   if n is even
+      f = [0, 1, ..., (n-1)/2-1, (n-1)/2] / (d*n)   if n is odd
+
+    Unlike :obj:`dpnp.fft.fftfreq` the Nyquist frequency component is
+    considered to be positive.
 
     For full documentation refer to :obj:`numpy.fft.rfftfreq`.
 
-    Limitations
-    -----------
-    Parameter `d` is unsupported.
+    Parameters
+    ----------
+    n : int
+        Window length.
+    d : scalar, optional
+        Sample spacing (inverse of the sampling rate).
+        Default: ``1``.
+    device : {None, string, SyclDevice, SyclQueue}, optional
+        An array API concept of device where the output array is created.
+        The `device` can be ``None`` (the default), an OneAPI filter selector
+        string, an instance of :class:`dpctl.SyclDevice` corresponding to
+        a non-partitioned SYCL device, an instance of :class:`dpctl.SyclQueue`,
+        or a `Device` object returned by
+        :obj:`dpnp.dpnp_array.dpnp_array.device` property.
+    usm_type : {None, "device", "shared", "host"}, optional
+        The type of SYCL USM allocation for the output array.
+        Default: ``None``.
+    sycl_queue : {None, SyclQueue}, optional
+        A SYCL queue to use for output array allocation and copying.
+        Default: ``None``.
+
+    Returns
+    -------
+    f : dpnp.ndarray
+        Array of length `n` containing the sample frequencies.
+
+    See Also
+    --------
+    :obj:`dpnp.fft.fftfreq` : Return the Discrete Fourier Transform sample
+                        frequencies (for usage with :obj:`dpnp.fft.fft` and
+                        :obj:`dpnp.fft.ifft`).
+
+    Examples
+    --------
+    >>> import dpnp as np
+    >>> signal = np.array([-2, 8, 6, 4, 1, 0, 3, 5, -3, 4])
+    >>> fourier = np.fft.fft(signal)
+    >>> n = signal.size
+    >>> sample_rate = 100
+    >>> freq = np.fft.fftfreq(n, d=1./sample_rate)
+    >>> freq
+    array([  0.,  10.,  20.,  30.,  40., -50., -40., -30., -20., -10.])
+    >>> freq = np.fft.rfftfreq(n, d=1./sample_rate)
+    >>> freq
+    array([  0.,  10.,  20.,  30.,  40.,  50.])
+
+    Creating the output array on a different device or with a
+    specified usm_type:
+
+    >>> x = np.fft.rfftfreq(n, d=1./sample_rate) # default case
+    >>> x.shape, x.device, x.usm_type
+    ((6, ), Device(level_zero:gpu:0), 'device')
+
+    >>> y =np.fft.rfftfreq(n, d=1./sample_rate, device="cpu")
+    >>> y.shape, y.device, y.usm_type
+    ((6, ), Device(opencl:cpu:0), 'device')
+
+    >>> z = np.fft.rfftfreq(n, d=1./sample_rate, usm_type="host")
+    >>> z.shape, z.device, z.usm_type
+    ((6, ), Device(level_zero:gpu:0), 'host')
 
     """
 
-    return call_origin(numpy.fft.rfftfreq, n, d)
+    if not isinstance(n, int):
+        raise ValueError("`n` should be an integer")
+    if not dpnp.isscalar(d):
+        raise ValueError("`d` should be an scalar")
+    val = 1.0 / (n * d)
+    N = n // 2 + 1
+    results = dpnp.arange(
+        0,
+        N,
+        dtype=dpnp.intp,
+        device=device,
+        usm_type=usm_type,
+        sycl_queue=sycl_queue,
+    )
+    return results * val
 
 
 def rfftn(x, s=None, axes=None, norm=None):

tests/test_fft.py

@@ -354,3 +354,21 @@ def test_fft_invalid_dtype(self, func_name):
         dpnp_func = getattr(dpnp.fft, func_name)
         with pytest.raises(TypeError):
             dpnp_func(a)
+
+
+class TestFftfreq:
+    @pytest.mark.parametrize("func", ["fftfreq", "rfftfreq"])
+    @pytest.mark.parametrize("n", [10, 20])
+    @pytest.mark.parametrize("d", [0.5, 2])
+    def test_fftfreq(self, func, n, d):
+        expected = getattr(dpnp.fft, func)(n, d)
+        result = getattr(numpy.fft, func)(n, d)
+        assert_dtype_allclose(expected, result)
+
+    @pytest.mark.parametrize("func", ["fftfreq", "rfftfreq"])
+    def test_error(self, func):
+        # n should be an integer
+        assert_raises(ValueError, getattr(dpnp.fft, func), 10.0)
+
+        # d should be an scalar
+        assert_raises(ValueError, getattr(dpnp.fft, func), 10, (2,))

tests/test_sycl_queue.py

@@ -1260,6 +1260,20 @@ def test_fft_rfft(type, shape, device):
     assert_sycl_queue_equal(result_queue, expected_queue)
 
 
+@pytest.mark.parametrize("func", ["fftfreq", "rfftfreq"])
+@pytest.mark.parametrize(
+    "device",
+    valid_devices,
+    ids=[device.filter_string for device in valid_devices],
+)
+def test_fftfreq(func, device):
+    result = getattr(dpnp.fft, func)(10, 0.5, device=device)
+    expected = getattr(numpy.fft, func)(10, 0.5)
+
+    assert_dtype_allclose(result, expected)
+    assert result.sycl_device == device
+
+
 @pytest.mark.parametrize(
     "data, is_empty",
     [

tests/test_usm_type.py

@@ -931,6 +931,20 @@ def test_eigenvalue(func, shape, usm_type):
     assert a.usm_type == dp_val.usm_type
 
 
+@pytest.mark.parametrize("func", ["fftfreq", "rfftfreq"])
+@pytest.mark.parametrize("usm_type", list_of_usm_types + [None])
+def test_fftfreq(func, usm_type):
+    result = getattr(dp.fft, func)(10, 0.5, usm_type=usm_type)
+    expected = getattr(numpy.fft, func)(10, 0.5)
+
+    if usm_type is None:
+        # assert against default USM type
+        usm_type = "device"
+
+    assert_dtype_allclose(result, expected)
+    assert result.usm_type == usm_type
+
+
 @pytest.mark.parametrize("func", ["fft", "ifft"])
 @pytest.mark.parametrize("usm_type", list_of_usm_types, ids=list_of_usm_types)
 def test_fft(func, usm_type):

tests/third_party/cupy/fft_tests/test_fft.py

@@ -324,7 +324,6 @@ def test_ihfft(self, xp, dtype):
     {"n": 10, "d": 0.5},
     {"n": 100, "d": 2},
 )
-@pytest.mark.usefixtures("allow_fall_back_on_numpy")
 class TestFftfreq:
     @testing.for_all_dtypes()
     @testing.numpy_cupy_allclose(