def get_chest_regions(self):
"""Get the explicit list of chest regions in the data set.
Returns
-------
chest_regions : array, shape ( N )
Explicit list of the N chest regions in the data set
"""
conventions = ChestConventions()
tmp = []
for l in self.labels_:
tmp.append(conventions.GetChestRegionFromValue(l))
chest_regions = np.unique(np.array(tmp, dtype=int))
return chest_regions
def get_all_chest_regions(self):
"""Get all the chest regions in the data set, including those
implicitly present as a result of the region hierarchy.
Returns
-------
chest_regions : array, shape ( N )
All chest regions in the data set
"""
c = ChestConventions()
num_regions = c.GetNumberOfEnumeratedChestRegions()
tmp = []
for l in self.labels_:
r = c.GetChestRegionFromValue(l)
for sup in xrange(0, num_regions):
if c.CheckSubordinateSuperiorChestRegionRelationship(r, sup):
tmp.append(sup)
chest_regions = np.unique(np.array(tmp, dtype=int))
return chest_regions
def get_all_pairs(self):
"""Get all the region-type pairs, including implied pairs
Returns
-------
pairs : array, shape ( N, 2 )
All N chest-region chest-type pairs in the data set, including
those implied by the region hierarchy. The first column indicates
the chest region, and the second column represents the chest type.
"""
c = ChestConventions()
num_regions = c.GetNumberOfEnumeratedChestRegions()
tmp = []
for l in self.labels_:
t = c.GetChestTypeFromValue(l)
r = c.GetChestRegionFromValue(l)
for sup in xrange(0, num_regions):
if c.CheckSubordinateSuperiorChestRegionRelationship(r, sup):
if not (sup, t) in tmp:
tmp.append((sup, t))
pairs = np.array(tmp, dtype=int)
return pairs
def get_mask(self, chest_region=None, chest_type=None):
"""Get's boolean mask of all data indices that match the chest-region
chest-type query.
If only a chest region is specified, then all voxels in that region
will be included in the mask, regardless of the voxel's chest type
value (chest region hierarchy is honored). If only a type is specified,
then all voxels having that type will be included in the mask,
regardless of the voxel's chest region. If both a region and type are
speficied, then only those voxels matching both the region and type
will be included in the mask (the chest region hierarchy is honored).
Parameters
----------
chest_region : int
Integer value in the interval [0, 255] that indicates the chest
region
chest_type : int
Integer value in the interval [0, 255] that indicates the chest
type
Returns
-------
mask : array, shape ( X, Y, Z )
Boolean mask of all data indices that match the chest-region
chest-type query. The chest region hierarchy is honored.
"""
if chest_region is not None:
if type(chest_region) != int and type(chest_region) != np.int64:
raise ValueError(
'chest_region must be an int between 0 and 255 inclusive')
if chest_type is not None:
if type(chest_type) != int and type(chest_type) != np.int64:
raise ValueError(
'chest_type must be an int between 0 and 255 inclusive')
conventions = ChestConventions()
mask_labels = []
for l in self.labels_:
r = conventions.GetChestRegionFromValue(l)
t = conventions.GetChestTypeFromValue(l)
if chest_region is not None and chest_type is not None:
if t==chest_type and \
conventions.CheckSubordinateSuperiorChestRegionRelationship(\
r, chest_region):
mask_labels.append(l)
elif t == chest_type:
mask_labels.append(l)
elif chest_region is not None:
if conventions.\
CheckSubordinateSuperiorChestRegionRelationship(r, \
chest_region):
mask_labels.append(l)
mask = np.empty(self._data.shape, dtype=bool)
mask[:] = False
for ml in mask_labels:
mask = np.logical_or(mask, self._data == ml)
return mask