diff --git a/test/test_imagewrapper.py b/test/test_imagewrapper.py
index 4c38ff2978c7a1006fdd12d2ba86b0c32fa6e5c6..f235e006cad346298c6f43d537700b40d621db27 100644
--- a/test/test_imagewrapper.py
+++ b/test/test_imagewrapper.py
@@ -74,6 +74,9 @@ def random_slices(coverage, shape, mode):
# Assuming that coverage is same for each volume
lowCover = coverage[0, dim, 0]
highCover = coverage[1, dim, 0]
+
+ if (np.isnan(lowCover) or np.isnan(highCover)) and mode in ('in', 'overlap'):
+ raise RuntimeError('Can\'t generate in/overlapping slices on an empty coverage')
# Generate some slices that will
# be contained within the coverage
@@ -94,9 +97,15 @@ def random_slices(coverage, shape, mode):
elif mode == 'out':
+ # No coverage, anything that
+ # we generate will be outside
+ if np.isnan(lowCover) or np.isnan(highCover):
+ lowSlice = np.random.randint(0, size)
+ highSlice = np.random.randint(lowSlice + 1, size + 1)
+
# The coverage is full, so we can't
- # generate an outside range
- if lowCover == 0 and highCover == size:
+ # generate an outside range
+ elif lowCover == 0 and highCover == size:
lowSlice = np.random.randint(lowCover, highCover)
highSlice = np.random.randint(lowSlice + 1, highCover + 1)
@@ -165,11 +174,14 @@ def test_adjustCoverage():
# TODO Randomise
+ n = np.nan
+
# Each test is a tuple of (coverage, expansion, expectedResult)
- tests = [([[3, 5], [2, 6]], [[6, 7], [8, 10]], [[3, 7], [2, 10]]),
- ([[0, 0], [0, 0]], [[1, 2], [3, 5]], [[0, 2], [0, 5]]),
- ([[2, 3], [0, 6]], [[1, 5], [4, 10]], [[1, 5], [0, 10]]),
- ([[0, 1], [0, 1]], [[0, 7], [19, 25], [0, 1]], [[0, 7], [0, 25]]),
+ tests = [([[3, 5], [2, 6]], [[6, 7], [8, 10]], [[3, 7], [2, 10]]),
+ ([[0, 0], [0, 0]], [[1, 2], [3, 5]], [[0, 2], [0, 5]]),
+ ([[2, 3], [0, 6]], [[1, 5], [4, 10]], [[1, 5], [0, 10]]),
+ ([[0, 1], [0, 1]], [[0, 7], [19, 25], [0, 1]], [[0, 7], [0, 25]]),
+ ([[n, n], [n, n]], [[0, 7], [19, 25], [0, 1]], [[0, 7], [19, 25]]),
]
for coverage, expansion, result in tests:
@@ -183,7 +195,7 @@ def test_adjustCoverage():
def test_sliceCovered():
# A bunch of random coverages
- for i in range(500):
+ for i in range(250):
# 2D, 3D or 4D?
# ndims is the number of dimensions
@@ -200,24 +212,23 @@ def test_sliceCovered():
# Generate some slices that should
# be contained within the coverage
- for j in range(500):
+ for j in range(250):
slices = random_slices(coverage, shape, 'in')
assert imagewrap.sliceCovered(slices, coverage, shape)
# Generate some slices that should
# overlap with the coverage
- for j in range(500):
+ for j in range(250):
slices = random_slices(coverage, shape, 'overlap')
assert not imagewrap.sliceCovered(slices, coverage, shape)
# Generate some slices that should
# be outside of the coverage
- for j in range(500):
+ for j in range(250):
slices = random_slices(coverage, shape, 'out')
assert not imagewrap.sliceCovered(slices, coverage, shape)
-
# The sum of the coverage ranges + the
# expansion ranges should be equal to
# the coverage, expanded to include the
@@ -232,66 +243,93 @@ def _test_expansion(coverage, slices, volumes, expansions):
print
print 'Slice: "{}"'.format(" ".join(["{:2d} {:2d}".format(l, h) for l, h in slices]))
+ # Figure out what the adjusted
+ # coverage should look like (assumes
+ # that adjustCoverage is working, and
+ # the coverage is the same on all
+ # volumes)
+ oldCoverage = coverage[..., 0]
+ newCoverage = imagewrap.adjustCoverage(oldCoverage, slices)
+
+ nc = newCoverage
+
+ # We're goint to test that every point
+ # in the expected (expanded) coverage
+ # is contained either in the original
+ # coverage, or in one of the expansions.
+ dimranges = []
+ for d in range(ndims):
+ dimranges.append(np.arange(nc[0, d], nc[1, d]))
+
+ points = it.product(*dimranges)
+
# Bin the expansions by volume
expsByVol = collections.defaultdict(list)
for vol, exp in zip(volumes, expansions):
print ' {:3d}: "{}"'.format(vol, " ".join(["{:2d} {:2d}".format(l, h) for l, h in exp]))
expsByVol[vol].append(exp)
-
- for vol, exps in expsByVol.items():
-
- # Figure out what the adjusted
- # coverage should look like (assumes
- # that adjustCoverage is working).
- oldCoverage = coverage[..., vol]
- newCoverage = imagewrap.adjustCoverage(oldCoverage, slices)
-
- nc = newCoverage
-
- dimranges = []
- for d in range(ndims):
- dimranges.append(np.arange(nc[0, d], nc[1, d]))
-
- points = it.product(*dimranges)
-
- for point in points:
-
- # Is this point in the old coverage?
- covered = True
- for dim in range(ndims):
- covLow, covHigh = oldCoverage[:, dim]
-
- if point[dim] < covLow or point[dim] > covHigh:
- covered = False
- break
-
- if covered:
+
+ for point in points:
+
+ # Is this point in the old coverage?
+ covered = True
+ for dim in range(ndims):
+ covLow, covHigh = oldCoverage[:, dim]
+
+ if np.isnan(covLow) or \
+ np.isnan(covHigh) or \
+ point[dim] < covLow or \
+ point[dim] > covHigh:
+ covered = False
break
+ if covered:
+ continue
+
+ for vol, exps in expsByVol.items():
+
# Is this point in any of the expansions
- covered = [False] * len(exps)
+ coveredInExp = [False] * len(exps)
for i, exp in enumerate(exps):
- covered[i] = True
+ coveredInExp[i] = True
for dim in range(ndims):
expLow, expHigh = exp[dim]
if point[dim] < expLow or point[dim] > expHigh:
- covered[i] = False
+ coveredInExp[i] = False
break
- if not any(covered):
- raise AssertionError(point)
+ if not (covered or any(coveredInExp)):
+ raise AssertionError(point)
-
-def test_calcSliceExpansion():
+
+def test_calcExpansionNoCoverage():
for i in range(500):
+ ndims = random.choice((2, 3, 4)) - 1
+ shape = np.random.randint(5, 100, size=ndims + 1)
+ shape[-1] = np.random.randint(1, 8)
+ coverage = np.zeros((2, ndims, shape[-1]))
+ coverage[:] = np.nan
- ndims = 3 # random.choice((2, 3, 4)) - 1
- shape = np.random.randint(5, 100, size=ndims + 1)
- coverage = random_coverage(shape)
+ print
+ print '-- Out --'
+ for j in range(250):
+ slices = random_slices(coverage, shape, 'out')
+ vols, exps = imagewrap.calcExpansion(slices, coverage)
+ _test_expansion(coverage, slices, vols, exps)
+
+
+def test_calcExpansion():
+
+ for i in range(250):
+
+ ndims = random.choice((2, 3, 4)) - 1
+ shape = np.random.randint(5, 60, size=ndims + 1)
+ shape[-1] = np.random.randint(1, 6)
+ coverage = random_coverage(shape)
cov = [(lo, hi) for lo, hi in coverage[:, :, 0].T]
@@ -303,7 +341,10 @@ def test_calcSliceExpansion():
for j in range(250):
slices = random_slices(coverage, shape, 'in')
vols, exps = imagewrap.calcExpansion(slices, coverage)
- _test_expansion(coverage, slices, vols, exps)
+
+ # There should be no expansions for a
+ # slice that's inside the coverage
+ assert len(vols) == 0 and len(exps) == 0
print
print '-- Overlap --'
@@ -318,3 +359,4 @@ def test_calcSliceExpansion():
slices = random_slices(coverage, shape, 'out')
vols, exps = imagewrap.calcExpansion(slices, coverage)
_test_expansion(coverage, slices, vols, exps)
+