def testOrderTriangle(self):
# Additional tests to complement the doctests
self.assertRaises(ValueError, Utils.OrderTriangle, [0, 2], [1, 2, 3])
self.assertRaises(ValueError, Utils.OrderTriangle, [0, 2, 4], [1, 2])
self.assertEqual(Utils.OrderTriangle([1, 3, 1], [2, 3, 4]), ([1, 3, 1], [4, 3, 2]))
self.assertEqual(Utils.OrderTriangle([1, 3, 1], [4, 3, 2]), ([1, 3, 1], [4, 3, 2]))
# If all the features are the same, we want the distances in reverse order
for dist in itertools.permutations([1, 2, 3], 3):
self.assertEqual(Utils.OrderTriangle([1, 1, 1], dist), ([1, 1, 1], [3, 2, 1]))
def GetBitIdx(self, featIndices, dists, sortIndices=True):
""" returns the index for a pharmacophore described using a set of
feature indices and distances
**Arguments***
- featIndices: a sequence of feature indices
- dists: a sequence of distance between the features, only the
unique distances should be included, and they should be in the
order defined in Utils.
- sortIndices : sort the indices
**Returns**
the integer bit index
"""
nPoints = len(featIndices)
if nPoints > 3:
raise NotImplementedError('>3 points not supported')
if nPoints < self.minPointCount:
raise IndexError('bad number of points')
if nPoints > self.maxPointCount:
raise IndexError('bad number of points')
# this is the start of the nPoint-point pharmacophores
startIdx = self._starts[nPoints]
#
# now we need to map the pattern indices to an offset from startIdx
#
if sortIndices:
tmp = list(featIndices)
tmp.sort()
featIndices = tmp
if featIndices[0] < 0: raise IndexError('bad feature index')
if max(featIndices) >= self._nFeats:
raise IndexError('bad feature index')
if nPoints == 3:
featIndices, dists = Utils.OrderTriangle(featIndices, dists)
offset = Utils.CountUpTo(self._nFeats, nPoints, featIndices)
if _verbose:
print('offset for feature %s: %d' % (str(featIndices), offset))
offset *= len(self._scaffolds[len(dists)])
try:
if _verbose:
print('>>>>>>>>>>>>>>>>>>>>>>>')
print('\tScaffolds:', repr(self._scaffolds[len(dists)]),
type(self._scaffolds[len(dists)]))
print('\tDists:', repr(dists), type(dists))
print('\tbins:', repr(self._bins), type(self._bins))
bin = self._findBinIdx(dists, self._bins,
self._scaffolds[len(dists)])
except ValueError:
fams = self.GetFeatFamilies()
fams = [fams[x] for x in featIndices]
raise IndexError(
'distance bin not found: feats: %s; dists=%s; bins=%s; scaffolds: %s'
% (fams, dists, self._bins, self._scaffolds))
return startIdx + offset + bin