Merge pull request #79 from IntelPython/hotfix/scipy-fft-rfft

Hotfix/scipy fft rfft

Author: oleksandr-pavlyk

conda-recipe/meta.yaml

@@ -1,4 +1,4 @@
-{% set version = "1.3.4" %}
+{% set version = "1.3.5" %}
 {% set buildnumber = 0 %}
 
 package:

mkl_fft/_scipy_fft_backend.py

@@ -151,7 +151,7 @@ def _workers_to_num_threads(w):
         return _workers_global_settings.get().workers
     _w = operator.index(w)
     if (_w == 0):
-        raise ValueError("Number of workers must be nonzero")
+        raise ValueError("Number of workers must not be zero")
     if (_w < 0):
         ub = _cpu_max_threads_count().get_cpu_count()
         _w += ub + 1
@@ -338,21 +338,22 @@ def irfft(a, n=None, axis=-1, norm=None, workers=None, plan=None):
         return NotImplemented
     if x is NotImplemented:
         return x
-    fsc = _compute_1d_forward_scale(norm, n, x.shape[axis])
+    nn = n if n else 2*(x.shape[axis]-1)
+    fsc = _compute_1d_forward_scale(norm, nn, x.shape[axis])
     _check_plan(plan)
     with Workers(workers):
         output = _pydfti.irfft_numpy(x, n=n, axis=axis, forward_scale=fsc)
     return output
 
 
-def _compute_nd_forward_scale_for_rfft(norm, s, axes, x):
+def _compute_nd_forward_scale_for_rfft(norm, s, axes, x, invreal=False):
     if norm in (None, "backward"):
         fsc = 1.0
     elif norm == "forward":
-        s, axes = _cook_nd_args(x, s, axes)
+        s, axes = _cook_nd_args(x, s, axes, invreal=invreal)
         fsc = _frwd_sc_nd(s, axes, x.shape)
     elif norm == "ortho":
-        s, axes = _cook_nd_args(x, s, axes)
+        s, axes = _cook_nd_args(x, s, axes, invreal=invreal)
         fsc = sqrt(_frwd_sc_nd(s, axes, x.shape))
     else:
         _check_norm(norm)
@@ -380,7 +381,7 @@ def irfft2(a, s=None, axes=(-2, -1), norm=None, workers=None, plan=None):
         return NotImplemented
     if x is NotImplemented:
         return x
-    s, axes, fsc = _compute_nd_forward_scale_for_rfft(norm, s, axes, x)
+    s, axes, fsc = _compute_nd_forward_scale_for_rfft(norm, s, axes, x, invreal=True)
     _check_plan(plan)
     with Workers(workers):
         output = _pydfti.irfftn_numpy(x, s, axes, forward_scale=fsc)
@@ -408,7 +409,7 @@ def irfftn(a, s=None, axes=None, norm=None, workers=None, plan=None):
         return NotImplemented
     if x is NotImplemented:
         return x
-    s, axes, fsc = _compute_nd_forward_scale_for_rfft(norm, s, axes, x)
+    s, axes, fsc = _compute_nd_forward_scale_for_rfft(norm, s, axes, x, invreal=True)
     _check_plan(plan)
     with Workers(workers):
         output = _pydfti.irfftn_numpy(x, s, axes, forward_scale=fsc)

mkl_fft/_version.py

@@ -1 +1 @@
-__version__ = '1.3.4'
+__version__ = '1.3.5'

mkl_fft/tests/test_interfaces.py

@@ -65,6 +65,12 @@ def test_scipy_rfft(norm, dtype):
     xx = mfi.scipy_fft.irfft(w, n=x.shape[0], norm=norm, workers=None, plan=None)
     tol = 64 * np.finfo(np.dtype(dtype)).eps
     assert np.allclose(x, xx, atol=tol, rtol=tol)
+    
+    x = np.ones(510, dtype=dtype)
+    w = mfi.scipy_fft.rfft(x, norm=norm, workers=None, plan=None)
+    xx = mfi.scipy_fft.irfft(w, norm=norm, workers=None, plan=None)
+    tol = 64 * np.finfo(np.dtype(dtype)).eps
+    assert np.allclose(x, xx, atol=tol, rtol=tol)
 
 
 @pytest.mark.parametrize('norm', [None, "forward", "backward", "ortho"])
@@ -99,20 +105,26 @@ def test_numpy_fftn(norm, dtype):
 
 @pytest.mark.parametrize('norm', [None, "forward", "backward", "ortho"])
 @pytest.mark.parametrize('dtype', [np.float32, np.float64])
-def test_scipy_rftn(norm, dtype):
+def test_scipy_rfftn(norm, dtype):
     x = np.ones((37, 83), dtype=dtype)
     w = mfi.scipy_fft.rfftn(x, norm=norm, workers=None, plan=None)
-    xx = mfi.scipy_fft.ifftn(w, s=x.shape, norm=norm, workers=None, plan=None)
+    xx = mfi.scipy_fft.irfftn(w, s=x.shape, norm=norm, workers=None, plan=None)
+    tol = 64 * np.finfo(np.dtype(dtype)).eps
+    assert np.allclose(x, xx, atol=tol, rtol=tol)
+
+    x = np.ones((36, 82), dtype=dtype)
+    w = mfi.scipy_fft.rfftn(x, norm=norm, workers=None, plan=None)
+    xx = mfi.scipy_fft.irfftn(w, norm=norm, workers=None, plan=None)
     tol = 64 * np.finfo(np.dtype(dtype)).eps
     assert np.allclose(x, xx, atol=tol, rtol=tol)
 
 
 @pytest.mark.parametrize('norm', [None, "forward", "backward", "ortho"])
 @pytest.mark.parametrize('dtype', [np.float32, np.float64])
-def test_numpy_rftn(norm, dtype):
+def test_numpy_rfftn(norm, dtype):
     x = np.ones((37, 83), dtype=dtype)
     w = mfi.numpy_fft.rfftn(x, norm=norm)
-    xx = mfi.numpy_fft.ifftn(w, s=x.shape, norm=norm)
+    xx = mfi.numpy_fft.irfftn(w, s=x.shape, norm=norm)
     tol = 64 * np.finfo(np.dtype(dtype)).eps
     assert np.allclose(x, xx, atol=tol, rtol=tol)