From e7ceb45e242961e905d67afde6670d5de139add6 Mon Sep 17 00:00:00 2001
From: Paul McCarthy <pauld.mccarthy@gmail.com>
Date: Tue, 28 Jun 2016 16:13:56 +0100
Subject: [PATCH] Test case for collapseExpansions
---
test/test_imagewrapper.py | 100 ++++++++++++++++++++++++++++++++++++--
1 file changed, 95 insertions(+), 5 deletions(-)
diff --git a/test/test_imagewrapper.py b/test/test_imagewrapper.py
index 94aad7959..b2f5279e0 100644
--- a/test/test_imagewrapper.py
+++ b/test/test_imagewrapper.py
@@ -61,13 +61,17 @@ def random_coverage(shape, vol_limit=None):
def random_slices(coverage, shape, mode):
- ndims = len(shape) - 1
- nvols = shape[-1]
-
- slices = np.zeros((2, len(shape)))
-
+ shape = np.array(shape)
+ ndims = len(shape) - 1
+ nvols = shape[-1]
+ slices = np.zeros((2, len(shape)))
origMode = mode
+ if coverage is None:
+ coverage = np.zeros((2, ndims, nvols), dtype=np.float32)
+ coverage[0, :, :] = 0
+ coverage[1, :, :] = shape[:-1].reshape(ndims, 1).repeat(nvols, 1)
+
# If we're generating an 'out' slice (i.e.
# a slice which is not covered by the coverage),
# then only one dimension needs to be out. The
@@ -917,3 +921,89 @@ def test_ImageWrapper_write_different_volume(niters=150):
assert np.isclose(newLo, elo)
assert np.isclose(newHi, ehi)
+
+
+def test_collapseExpansions(niters=500):
+
+ def expEq(exp1, exp2):
+
+ if len(exp1) != len(exp2):
+ return False
+
+ for (e1lo, e1hi), (e2lo, e2hi) in zip(exp1, exp2):
+ if e1lo != e2lo: return False
+ if e1hi != e2hi: return False
+ return True
+
+ def rangesOverlapOrAdjacent(r1, r2):
+
+ r1lo, r1hi = r1
+ r2lo, r2hi = r2
+
+ return not ((r1lo > r2hi) or (r1hi < r2lo) or \
+ (r2lo > r1hi) or (r2hi < r1lo))
+
+ for i in range(niters):
+
+ # Generate a random coverage shape
+ ndims = random.choice((2, 3, 4)) - 1
+ nvols = np.random.randint(10, 40)
+ shape = np.random.randint(5, 60, size=ndims + 1)
+ shape[-1] = nvols
+
+ # Generate a bunch of random slices, and
+ # split each of them up by volume to
+ # turn them each into a set of expansions
+ exps = []
+ expected = []
+
+ for i in range(10):
+
+ # Generate a random slice with a volume
+ # range that doesn't overlap with, and
+ # is not adjacent to, any of the other
+ # generated random slices.
+ #
+ # The only reason I'm doing this is to
+ # overocme a chicken-and-egg problem -
+ # if I want to test overlapping/adjacent
+ # region, I basically have to
+ # re-implement the collapseExpansions
+ # function.
+ while True:
+ slices = random_slices(None, shape, 'in')
+ vlo, vhi = slices[-1]
+
+ for exp in expected:
+
+ if not expEq(exp[:-1], slices[:-1]):
+ continue
+
+ evlo, evhi = exp[-1]
+
+ # Overlap
+ if rangesOverlapOrAdjacent((vlo, vhi), (evlo, evhi)):
+ break
+ else:
+ break
+
+ expected.append(slices)
+
+ for vol in range(slices[-1][0], slices[-1][1]):
+
+ exp = tuple(list(slices[:-1]) + [(vol, vol + 1)])
+ exps.append(exp)
+
+ # Now shuffle them up randomly
+ np.random.shuffle(exps)
+
+ # And attempt to collapse them
+ collapsed = imagewrap.collapseExpansions(exps, ndims)
+
+ collapsed = sorted(collapsed)
+ expected = sorted(expected)
+
+ assert len(expected) == len(collapsed)
+
+ for exp, col in zip(expected, collapsed):
+ assert expEq(exp, col)
--
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