Merge pull request #465 from grlee77/backport_pr462

Backport gh-462 (iswtn axis fix)

Author: grlee77

pywt/_swt.py

@@ -516,16 +516,19 @@ def iswtn(coeffs, wavelet, axes=None):
             [dt, ] + [v.dtype for v in details.values()]))
         if output.dtype != common_dtype:
             output = output.astype(common_dtype)
+
         # We assume all coefficient arrays are of equal size
         shapes = [v.shape for k, v in details.items()]
-        dshape = shapes[0]
         if len(set(shapes)) != 1:
             raise RuntimeError(
                 "Mismatch in shape of intermediate coefficient arrays")
 
+        # shape of a single coefficient array, excluding non-transformed axes
+        coeff_trans_shape = tuple([shapes[0][ax] for ax in axes])
+
         # nested loop over all combinations of axis offsets at this level
         for firsts in product(*([range(last_index), ]*ndim_transform)):
-            for first, sh, ax in zip(firsts, dshape, axes):
+            for first, sh, ax in zip(firsts, coeff_trans_shape, axes):
                 indices[ax] = slice(first, sh, step_size)
                 even_indices[ax] = slice(first, sh, 2*step_size)
                 odd_indices[ax] = slice(first+step_size, sh, 2*step_size)

pywt/tests/test_swt.py

@@ -4,15 +4,14 @@
 
 import warnings
 from copy import deepcopy
-from itertools import combinations
+from itertools import combinations, permutations
 import numpy as np
 from numpy.testing import (run_module_suite, dec, assert_allclose, assert_,
                            assert_equal, assert_raises, assert_array_equal,
                            assert_warns)
 
 import pywt
 from pywt._extensions._swt import swt_axis
-from pywt._extensions._pywt import _check_dtype
 
 # Check that float32 and complex64 are preserved.  Other real types get
 # converted to float64.
@@ -387,6 +386,21 @@ def test_iswtn_errors():
     assert_raises(RuntimeError, pywt.iswtn, coeffs, w, axes=axes)
 
 
+def test_swtn_iswtn_unique_shape_per_axis():
+    # test case for gh-460
+    _shape = (1, 48, 32)  # unique shape per axis
+    wav = 'sym2'
+    max_level = 3
+    rstate = np.random.RandomState(0)
+    for shape in permutations(_shape):
+        # transform only along the non-singleton axes
+        axes = [ax for ax, s in enumerate(shape) if s != 1]
+        x = rstate.standard_normal(shape)
+        c = pywt.swtn(x, wav, max_level, axes=axes)
+        r = pywt.iswtn(c, wav, axes=axes)
+        assert_allclose(x, r, rtol=1e-10, atol=1e-10)
+
+
 def test_per_axis_wavelets():
     # tests seperate wavelet for each axis.
     rstate = np.random.RandomState(1234)