def test_add(self):
result = self.container + (1, 2, 3)
expected = FrozenList(self.lst + [1, 2, 3])
self.check_result(result, expected)
result = (1, 2, 3) + self.container
expected = FrozenList([1, 2, 3] + self.lst)
self.check_result(result, expected)
class TestFrozenList(CheckImmutable, CheckStringMixin, tm.TestCase):
mutable_methods = ('extend', 'pop', 'remove', 'insert')
unicode_container = FrozenList([u("\u05d0"), u("\u05d1"), "c"])
def setUp(self):
self.lst = [1, 2, 3, 4, 5]
self.container = FrozenList(self.lst)
self.klass = FrozenList
def test_add(self):
result = self.container + (1, 2, 3)
expected = FrozenList(self.lst + [1, 2, 3])
self.check_result(result, expected)
result = (1, 2, 3) + self.container
expected = FrozenList([1, 2, 3] + self.lst)
self.check_result(result, expected)
def test_inplace(self):
q = r = self.container
q += [5]
self.check_result(q, self.lst + [5])
# other shouldn't be mutated
self.check_result(r, self.lst)
def setUp(self):
self.lst = [1, 2, 3, 4, 5]
self.container = FrozenList(self.lst)
self.klass = FrozenList
def parse_coords_definition(coords=None):
''' Validate coords to test for cyclic graph '''
if coords == None:
return None, None, None
if isinstance(coords, string_types):
return OrderedDict([(coords, None)]), FrozenList([coords]), {
coords: set([coords])
}
elif not has_iterkeys(coords):
if isinstance(coords, Coordinates):
coords = coords._coords
coords = OrderedDict(
list(zip(list(coords), [None for _ in range(len(coords))])))
return coords, FrozenList(
coords.keys()), {c: set([c])
for c in coords.keys()}
base_coords = []
dependencies = OrderedDict([])
base_deps = {}
visited = set()
def find_coord_dependencies(coord):
if coord in visited:
if coord not in dependencies:
raise GraphIsCyclicError
return
deps = coords.pop(coord)
if deps is None:
base_coords.append(coord)
dependencies[coord] = None
base_deps[coord] = set([coord])
visited.add(coord)
elif isinstance(deps, string_types):
visited.add(coord)
find_coord_dependencies(deps)
dependencies[coord] = set([deps])
base_deps[coord] = base_deps[deps]
else:
visited.add(coord)
dependencies[coord] = set()
base_deps[coord] = set()
for ele in deps:
find_coord_dependencies(ele)
dependencies[coord].add(ele)
base_deps[coord] |= base_deps[ele]
while len(coords) > 0:
find_coord_dependencies(next(iterkeys(coords)))
# Convert from sets to lists
for k, v in dependencies.items():
if v is not None:
dependencies[k] = list(v)
return dependencies, FrozenList(base_coords), base_deps
from sklearn.metrics.pairwise import pairwise_distances
from tqdm import tqdm
from config import ROOT_DIR
class LionClasses:
ADULT_MALES = 0
SUBADULT_MALES = 1
ADULT_FEMALES = 2
JUVENILES = 3
PUPS = 4
NUM_CLASSES = 5
CLASS_NAMES = FrozenList(['adult_males', 'subadult_males', 'adult_females', 'juveniles', 'pups'])
def coords_df_to_dict(coords_df_):
images_info = defaultdict(list)
for row in coords_df_.itertuples():
item = dict(cls=row.cls, row=row.row, col=row.col)
images_info[row.tid].append(item)
return images_info
def hardcode_coords(coords_df_):
coords_df_ = coords_df_.copy()
coords_df_.loc[(coords_df_['tid'] == 691) & (coords_df_['cls'] == 0), 'row'] = 105
coords_df_.loc[(coords_df_['tid'] == 691) & (coords_df_['cls'] == 0), 'col'] = 1550
return coords_df_