drop support for scipy.fftpack

Author: Vahid Tavanashad

mkl_fft/__init__.py

@@ -39,7 +39,6 @@
     rfft2,
     rfftn,
 )
-from ._pydfti import irfftpack, rfftpack  # pylint: disable=no-name-in-module
 from ._version import __version__
 
 import mkl_fft.interfaces  # isort: skip
@@ -51,8 +50,6 @@
     "ifft2",
     "fftn",
     "ifftn",
-    "rfftpack",
-    "irfftpack",
     "rfft",
     "irfft",
     "rfft2",

mkl_fft/_pydfti.pyx

@@ -893,253 +893,3 @@ def _direct_fftnd(
             return out
         else:
             return f_arr
-
-
-# ========================= deprecated functions ==============================
-cdef object _rc_to_rr(cnp.ndarray rc_arr, int n, int axis, int xnd, int x_type):
-    cdef object res
-    inp = <object>rc_arr
-
-    slice_ = [slice(None, None, None)] * xnd
-    sl_0 = list(slice_)
-    sl_0[axis] = 0
-
-    sl_1 = list(slice_)
-    sl_1[axis] = 1
-    if (inp.flags["C"] and inp.strides[axis] == inp.itemsize):
-        res = inp
-        res = res.view(
-            dtype=np.single if x_type == cnp.NPY_FLOAT else np.double
-        )
-        res[tuple(sl_1)] = res[tuple(sl_0)]
-
-        slice_[axis] = slice(1, n + 1, None)
-
-        return res[tuple(slice_)]
-    else:
-        res_shape = list(inp.shape)
-        res_shape[axis] = n
-        res = np.empty(
-            tuple(res_shape),
-            dtype = np.single if x_type == cnp.NPY_FLOAT else np.double,
-        )
-
-        res[tuple(sl_0)] = inp[tuple(sl_0)].real
-        sl_dst_real = list(slice_)
-        sl_dst_real[axis] = slice(1, None, 2)
-        sl_src_real = list(slice_)
-        sl_src_real[axis] = slice(1, None, None)
-        res[tuple(sl_dst_real)] = inp[tuple(sl_src_real)].real
-        sl_dst_imag = list(slice_)
-        sl_dst_imag[axis] = slice(2, None, 2)
-        sl_src_imag = list(slice_)
-        sl_src_imag[axis] = slice(
-            1, inp.shape[axis] if (n & 1) else inp.shape[axis] - 1, None
-        )
-        res[tuple(sl_dst_imag)] = inp[tuple(sl_src_imag)].imag
-
-        return res[tuple(slice_)]
-
-
-cdef object _rr_to_rc(cnp.ndarray rr_arr, int n, int axis, int xnd, int x_type):
-
-    inp = <object> rr_arr
-
-    rc_shape = list(inp.shape)
-    rc_shape[axis] = (n // 2 + 1)
-    rc_shape = tuple(rc_shape)
-
-    rc_dtype = np.cdouble if x_type == cnp.NPY_DOUBLE else np.csingle
-    rc = np.empty(rc_shape, dtype=rc_dtype, order="C")
-
-    slice_ = [slice(None, None, None)] * xnd
-    sl_src_real = list(slice_)
-    sl_src_imag = list(slice_)
-    sl_src_real[axis] = slice(1, n, 2)
-    sl_src_imag[axis] = slice(2, n, 2)
-
-    sl_dest_real = list(slice_)
-    sl_dest_real[axis] = slice(1, None, None)
-    sl_dest_imag = list(slice_)
-    sl_dest_imag[axis] = slice(1, (n+1)//2, None)
-
-    sl_0 = list(slice_)
-    sl_0[axis] = 0
-
-    rc_real = rc.real
-    rc_imag = rc.imag
-
-    rc_real[tuple(sl_dest_real)] = inp[tuple(sl_src_real)]
-    rc_imag[tuple(sl_dest_imag)] = inp[tuple(sl_src_imag)]
-    rc_real[tuple(sl_0)] = inp[tuple(sl_0)]
-    rc_imag[tuple(sl_0)] = 0
-    if (n & 1 == 0):
-        sl_last = list(slice_)
-        sl_last[axis] = -1
-        rc_imag[tuple(sl_last)] = 0
-
-    return rc
-
-
-def _rr_fft1d_impl(x, n=None, axis=-1, overwrite_x=False, double fsc=1.0):
-    """
-    Uses MKL to perform real packed 1D FFT on the input array x
-    along the given axis.
-
-    This done by using rfft and post-processing the result.
-    Thus overwrite_x is effectively discarded.
-
-    Functionally equivalent to scipy.fftpack.rfft
-    """
-    cdef cnp.ndarray x_arr "x_arrayObject"
-    cdef cnp.ndarray f_arr "f_arrayObject"
-    cdef int xnd, in_place, dir_
-    cdef long n_, axis_
-    cdef int HALF_HARMONICS = 0  # give only positive index harmonics
-    cdef int x_type, status, f_type
-    cdef char * c_error_msg = NULL
-    cdef bytes py_error_msg
-    cdef DftiCache *_cache
-
-    x_arr = _process_arguments(x, n, axis, overwrite_x, <object>(+1),
-                               &axis_, &n_, &in_place, &xnd, &dir_, 1)
-
-    x_type = cnp.PyArray_TYPE(x_arr)
-
-    if x_type is cnp.NPY_FLOAT or x_type is cnp.NPY_DOUBLE:
-        in_place = 0
-    elif x_type is cnp.NPY_CFLOAT or x_type is cnp.NPY_CDOUBLE:
-        raise TypeError("1st argument must be a real sequence")
-    else:
-        try:
-            x_arr = <cnp.ndarray> cnp.PyArray_FROM_OTF(
-                x_arr, cnp.NPY_DOUBLE,
-                cnp.NPY_ARRAY_BEHAVED | cnp.NPY_ARRAY_ENSURECOPY
-            )
-        except:
-            raise TypeError("1st argument must be a real sequence")
-        x_type = cnp.PyArray_TYPE(x_arr)
-        in_place = 0
-
-    f_type = cnp.NPY_CFLOAT if x_type is cnp.NPY_FLOAT else cnp.NPY_CDOUBLE
-    f_arr = _allocate_result(x_arr, n_ // 2 + 1, axis_, f_type)
-
-    _cache_capsule = _tls_dfti_cache_capsule()
-    _cache = <DftiCache *>cpython.pycapsule.PyCapsule_GetPointer(
-        _cache_capsule, capsule_name
-    )
-    if x_type is cnp.NPY_DOUBLE:
-        status = double_cdouble_mkl_fft1d_out(
-            x_arr, n_, <int> axis_, f_arr, HALF_HARMONICS, fsc, _cache
-        )
-    else:
-        status = float_cfloat_mkl_fft1d_out(
-            x_arr, n_, <int> axis_, f_arr, HALF_HARMONICS, fsc, _cache
-        )
-
-    if (status):
-        c_error_msg = mkl_dfti_error(status)
-        py_error_msg = c_error_msg
-        raise ValueError("Internal error occurred: {}".format(py_error_msg))
-
-    # post-process and return
-    return _rc_to_rr(f_arr, n_, axis_, xnd, x_type)
-
-
-def _rr_ifft1d_impl(x, n=None, axis=-1, overwrite_x=False, double fsc=1.0):
-    """
-    Uses MKL to perform real packed 1D FFT on the input array x along
-    the given axis.
-
-    This done by using rfft and post-processing the result.
-    Thus overwrite_x is effectively discarded.
-
-    Functionally equivalent to scipy.fftpack.irfft
-    """
-    cdef cnp.ndarray x_arr "x_arrayObject"
-    cdef cnp.ndarray f_arr "f_arrayObject"
-    cdef int xnd, in_place, dir_
-    cdef long n_, axis_
-    cdef int x_type, rc_type, status
-    cdef char * c_error_msg = NULL
-    cdef bytes py_error_msg
-    cdef DftiCache *_cache
-
-    x_arr = _process_arguments(x, n, axis, overwrite_x, <object>(-1),
-                               &axis_, &n_, &in_place, &xnd, &dir_, 1)
-
-    x_type = cnp.PyArray_TYPE(x_arr)
-
-    if x_type is cnp.NPY_FLOAT or x_type is cnp.NPY_DOUBLE:
-        pass
-    else:
-        # we must cast the input and allocate the output,
-        # so we cast to complex double and operate in place
-        try:
-            x_arr = <cnp.ndarray> cnp.PyArray_FROM_OTF(
-                x_arr, cnp.NPY_DOUBLE,
-                cnp.NPY_ARRAY_BEHAVED | cnp.NPY_ARRAY_ENSURECOPY
-            )
-        except:
-            raise ValueError(
-                "First argument should be a real "
-                "or a complex sequence of single or double precision"
-            )
-        x_type = cnp.PyArray_TYPE(x_arr)
-        in_place = 1
-
-    # need to convert this into complex array
-    rc_obj = _rr_to_rc(x_arr, n_, axis_, xnd, x_type)
-    rc_arr = <cnp.ndarray> rc_obj
-
-    rc_type = cnp.NPY_CFLOAT if x_type is cnp.NPY_FLOAT else cnp.NPY_CDOUBLE
-    in_place = False
-    if in_place:
-        f_arr = x_arr
-    else:
-        f_arr = _allocate_result(x_arr, n_, axis_, x_type)
-
-    # call out-of-place FFT
-    if rc_type is cnp.NPY_CFLOAT:
-        _cache_capsule = _tls_dfti_cache_capsule()
-        _cache = <DftiCache *>cpython.pycapsule.PyCapsule_GetPointer(
-            _cache_capsule, capsule_name
-        )
-        status = cfloat_float_mkl_irfft_out(
-            rc_arr, n_, <int> axis_, f_arr, fsc, _cache
-        )
-    elif rc_type is cnp.NPY_CDOUBLE:
-        _cache_capsule = _tls_dfti_cache_capsule()
-        _cache = <DftiCache *>cpython.pycapsule.PyCapsule_GetPointer(
-            _cache_capsule, capsule_name
-        )
-        status = cdouble_double_mkl_irfft_out(
-            rc_arr, n_, <int> axis_, f_arr, fsc, _cache
-        )
-    else:
-        raise ValueError(
-            "Internal mkl_fft error occurred: Unrecognized rc_type"
-        )
-
-    if (status):
-        c_error_msg = mkl_dfti_error(status)
-        py_error_msg = c_error_msg
-        raise ValueError(
-            "Internal error occurred: {}".format(str(py_error_msg))
-        )
-
-    return f_arr
-
-
-def rfftpack(x, n=None, axis=-1, overwrite_x=False, fwd_scale=1.0):
-    """Packed real-valued harmonics of FFT of a real sequence x"""
-    return _rr_fft1d_impl(
-        x, n=n, axis=axis, overwrite_x=overwrite_x, fsc=fwd_scale
-    )
-
-
-def irfftpack(x, n=None, axis=-1, overwrite_x=False, fwd_scale=1.0):
-    """IFFT of a real sequence, takes packed real-valued harmonics of FFT"""
-    return _rr_ifft1d_impl(
-        x, n=n, axis=axis, overwrite_x=overwrite_x, fsc=fwd_scale
-    )

mkl_fft/interfaces/_scipy_fftpack.py

@@ -352,55 +352,6 @@ def test_array6(self):
         assert_allclose(y1, y2, atol=2e-15)
 
 
-class Test_mklfft_rfftpack(TestCase):
-    def setUp(self):
-        rnd.seed(1234567)
-        self.v1 = rnd.randn(16)
-        self.m2 = rnd.randn(5, 7)
-        self.t3 = rnd.randn(5, 7, 11)
-
-    def test1(self):
-        x = self.v1.copy()
-        f1 = mkl_fft.rfftpack(x)
-        f2 = mkl_fft.irfftpack(f1)
-        assert_allclose(f2, x)
-
-    def test2(self):
-        x = self.v1.copy()
-        f1 = mkl_fft.irfftpack(x)
-        f2 = mkl_fft.rfftpack(f1)
-        assert_allclose(f2, x)
-
-    def test3(self):
-        for a in range(0, 2):
-            for ovwr_x in [True, False]:
-                for dt, atol in zip([np.float32, np.float64], [2e-7, 2e-15]):
-                    x = self.m2.copy().astype(dt)
-                    f1 = mkl_fft.rfftpack(x, axis=a, overwrite_x=ovwr_x)
-                    f2 = mkl_fft.irfftpack(f1, axis=a, overwrite_x=ovwr_x)
-                    assert_allclose(
-                        f2, self.m2.astype(dt), atol=atol, err_msg=(a, ovwr_x)
-                    )
-
-    def test4(self):
-        for a in range(0, 2):
-            for ovwr_x in [True, False]:
-                for dt, atol in zip([np.float32, np.float64], [2e-7, 2e-15]):
-                    x = self.m2.copy().astype(dt)
-                    f1 = mkl_fft.irfftpack(x, axis=a, overwrite_x=ovwr_x)
-                    f2 = mkl_fft.rfftpack(f1, axis=a, overwrite_x=ovwr_x)
-                    assert_allclose(f2, self.m2.astype(dt), atol=atol)
-
-    def test5(self):
-        for a in range(0, 3):
-            for ovwr_x in [True, False]:
-                for dt, atol in zip([np.float32, np.float64], [4e-7, 4e-15]):
-                    x = self.t3.copy().astype(dt)
-                    f1 = mkl_fft.irfftpack(x, axis=a, overwrite_x=ovwr_x)
-                    f2 = mkl_fft.rfftpack(f1, axis=a, overwrite_x=ovwr_x)
-                    assert_allclose(f2, self.t3.astype(dt), atol=atol)
-
-
 @requires_numpy_2
 @pytest.mark.parametrize("axis", [0, 1, 2])
 @pytest.mark.parametrize("func", ["fft", "ifft"])