Alignment - Fourier filters: fixed rfft filter shape

The filter shape is computed according to scipy.fft.rfftn recommendations

Signed-off-by: Nicola VIGANÒ <nicola.vigano@esrf.fr>

nabu/misc/fourier_filters.py

@@ -83,8 +83,8 @@ def get_lowpass_filter(img_shape, cutoff_par=None, use_rfft=False, data_type=np.
     res = res.astype(data_type)
 
     if use_rfft:
-        slicelist = tuple(slice(0, (N + 1) // 2) for N in res.shape)
-        return res[slicelist]
+        slicelist = [slice(None)] * (len(res.shape) - 1) + [slice(0, res.shape[-1] // 2 + 1)]
+        return res[tuple(slicelist)]
     else:
         return res
 

nabu/preproc/alignment.py

@@ -374,8 +374,8 @@ class AlignmentBase(object):
 
     def _compute_correlation_fft(self, img_1, img_2, padding_mode, axes=(-2, -1), low_pass=None, high_pass=None):
         do_circular_conv = padding_mode is None or padding_mode == "wrap"
+        img_shape = img_2.shape
         if not do_circular_conv:
-            img_shape = img_2.shape
             pad_size = np.ceil(np.array(img_shape) / 2).astype(np.int)
             pad_array = [(0,)] * len(img_shape)
             for a in axes:
@@ -392,7 +392,7 @@ class AlignmentBase(object):
 
         if low_pass is not None or high_pass is not None:
             filt = fourier_filters.get_bandpass_filter(
-                img_prod.shape[-2:],
+                img_shape[-2:],
                 cutoff_lowpass=low_pass,
                 cutoff_highpass=high_pass,
                 use_rfft=__have_scipy__,