def test_update(self):
x = np.array([(0,1,2),
(2,5,6),
(3,2,1)],
dtype=[('a', np.float),
('b', np.float),
('c', np.float)])
y = {'y':np.array([1,1,0])}
results = (x,y)
prim_obj = prim.setup_prim(results, 'y', threshold=0.8)
box = PrimBox(prim_obj, prim_obj.box_init, prim_obj.yi)
new_box_lim = np.array([(0,1,1),
(2,5,6)],
dtype=[('a', np.float),
('b', np.float),
('c', np.float)])
indices = np.array([0,1], dtype=np.int)
box.update(new_box_lim, indices)
self.assertEqual(box.peeling_trajectory['mean'][1], 1)
self.assertEqual(box.peeling_trajectory['coverage'][1], 1)
self.assertEqual(box.peeling_trajectory['density'][1], 1)
self.assertEqual(box.peeling_trajectory['res dim'][1], 1)
self.assertEqual(box.peeling_trajectory['mass'][1], 2/3)
def test_drop_restriction(self):
x = pd.DataFrame([(0,1,2),
(2,5,6),
(3,2,1)],
columns=['a', 'b', 'c'])
y = {'y':np.array([1,1,0])}
results = (x,y)
prim_obj = prim.setup_prim(results, 'y', threshold=0.8)
box = PrimBox(prim_obj, prim_obj.box_init, prim_obj.yi)
new_box_lim = pd.DataFrame([(0,1,1),
(2,2,6)],
columns=['a', 'b', 'c'])
indices = np.array([0,1], dtype=np.int)
box.update(new_box_lim, indices)
box.drop_restriction('b')
correct_box_lims = pd.DataFrame([(0,1,1),
(2,5,6)],
columns=['a', 'b', 'c'])
box_lims = box.box_lims[-1]
names = box_lims.columns
for entry in names:
lim_correct = correct_box_lims[entry]
lim_box = box_lims[entry]
for i in range(len(lim_correct)):
self.assertEqual(lim_correct[i], lim_box[i])
self.assertEqual(box.peeling_trajectory['mean'][2], 1)
self.assertEqual(box.peeling_trajectory['coverage'][2], 1)
self.assertEqual(box.peeling_trajectory['density'][2], 1)
self.assertEqual(box.peeling_trajectory['res_dim'][2], 1)
self.assertEqual(box.peeling_trajectory['mass'][2], 2/3)
def test_show_ppt(self):
x = pd.DataFrame([(0, 1, 2), (2, 5, 6), (3, 2, 1)],
columns=['a', 'b', 'c'])
y = np.array([1, 1, 0])
prim_obj = prim.Prim(x, y, threshold=0.8)
box = PrimBox(prim_obj, prim_obj.box_init, prim_obj.yi)
cols = ['mean', 'mass', 'coverage', 'density', 'res_dim']
data = np.zeros((100, 5))
data[:, 0:4] = np.random.rand(100, 4)
data[:, 4] = np.random.randint(0, 5, size=(100, ))
box.peeling_trajectory = pd.DataFrame(data, columns=cols)
box.show_ppt()
def test_show_tradeoff(self):
x = pd.DataFrame([(0,1,2),
(2,5,6),
(3,2,1)],
columns=['a', 'b', 'c'])
y = np.array([1,1,0])
prim_obj = prim.Prim(x, y, threshold=0.8)
box = PrimBox(prim_obj, prim_obj.box_init, prim_obj.yi)
cols = ['mean', 'mass', 'coverage', 'density', 'res_dim']
data = np.zeros((100, 5))
data[:, 0:4] = np.random.rand(100, 4)
data[:, 4] = np.random.randint(0, 5, size=(100, ))
box.peeling_trajectory = pd.DataFrame(data, columns=cols)
box.show_tradeoff()
def test_init(self):
x = np.array([(0, 1, 2), (2, 5, 6), (3, 2, 1)],
dtype=[('a', np.float), ('b', np.float), ('c', np.float)])
y = {'y': np.array([0, 1, 2])}
results = (x, y)
prim_obj = prim.setup_prim(results, 'y', threshold=0.8)
box = PrimBox(prim_obj, prim_obj.box_init, prim_obj.yi)
self.assertEqual(box.peeling_trajectory.shape, (1, 5))
def test_select(self):
x = pd.DataFrame([(0,1,2),
(2,5,6),
(3,2,1)],
columns=['a', 'b', 'c'])
y = {'y':np.array([1,1,0])}
results = (x,y)
prim_obj = prim.setup_prim(results, 'y', threshold=0.8)
box = PrimBox(prim_obj, prim_obj.box_init, prim_obj.yi)
new_box_lim = pd.DataFrame([(0,1,1),
(2,5,6)],
columns=['a', 'b', 'c'])
indices = np.array([0,1], dtype=np.int)
box.update(new_box_lim, indices)
box.select(0)
self.assertTrue(np.all(box.yi==prim_obj.yi))
def test_init(self):
x = pd.DataFrame([(0, 1, 2), (2, 5, 6), (3, 2, 1)],
columns=['a', 'b', 'c'])
y = {'y': np.array([0, 1, 2])}
results = (x, y)
prim_obj = prim.setup_prim(results, 'y', threshold=0.8)
box = PrimBox(prim_obj, prim_obj.box_init, prim_obj.yi)
self.assertEqual(box.peeling_trajectory.shape, (1, 6))
def test_drop_restriction(self):
x = np.array([(0, 1, 2), (2, 5, 6), (3, 2, 1)],
dtype=[('a', np.float), ('b', np.float), ('c', np.float)])
y = {'y': np.array([1, 1, 0])}
results = (x, y)
prim_obj = prim.setup_prim(results, 'y', threshold=0.8)
box = PrimBox(prim_obj, prim_obj.box_init, prim_obj.yi)
new_box_lim = np.array([(0, 1, 1), (2, 2, 6)],
dtype=[('a', np.float), ('b', np.float),
('c', np.float)])
indices = np.array([0, 1], dtype=np.int)
box.update(new_box_lim, indices)
box.drop_restriction('b')
correct_box_lims = np.array([(0, 1, 1), (2, 5, 6)],
dtype=[('a', np.float), ('b', np.float),
('c', np.float)])
box_lims = box.box_lims[-1]
names = recfunctions.get_names(correct_box_lims.dtype)
for entry in names:
lim_correct = correct_box_lims[entry]
lim_box = box_lims[entry]
for i in range(len(lim_correct)):
self.assertEqual(lim_correct[i], lim_box[i])
self.assertEqual(box.peeling_trajectory['mean'][2], 1)
self.assertEqual(box.peeling_trajectory['coverage'][2], 1)
self.assertEqual(box.peeling_trajectory['density'][2], 1)
self.assertEqual(box.peeling_trajectory['res dim'][2], 1)
self.assertEqual(box.peeling_trajectory['mass'][2], 2 / 3)
def test_inspect(self):
x = np.array([(0,1,2),
(2,5,6),
(3,2,1)],
dtype=[('a', np.float),
('b', np.float),
('c', np.float)])
y = {'y':np.array([1,1,0])}
results = (x,y)
prim_obj = prim.setup_prim(results, 'y', threshold=0.8)
box = PrimBox(prim_obj, prim_obj.box_init, prim_obj.yi)
new_box_lim = np.array([(0,1,1),
(2,5,6)],
dtype=[('a', np.float),
('b', np.float),
('c', np.float)])
indices = np.array([0,1], dtype=np.int)
box.update(new_box_lim, indices)
box.inspect(1)
def test_inspect(self):
x = np.array([(0, 1, 2), (2, 5, 6), (3, 2, 1)],
dtype=[('a', np.float), ('b', np.float), ('c', np.float)])
y = {'y': np.array([1, 1, 0])}
results = (x, y)
prim_obj = prim.setup_prim(results, 'y', threshold=0.8)
box = PrimBox(prim_obj, prim_obj.box_init, prim_obj.yi)
new_box_lim = np.array([(0, 1, 1), (2, 5, 6)],
dtype=[('a', np.float), ('b', np.float),
('c', np.float)])
indices = np.array([0, 1], dtype=np.int)
box.update(new_box_lim, indices)
box.inspect(1)
def test_select(self):
x = pd.DataFrame([(0, 1, 2), (2, 5, 6), (3, 2, 1)],
columns=['a', 'b', 'c'])
y = {'y': np.array([1, 1, 0])}
results = (x, y)
prim_obj = prim.setup_prim(results, 'y', threshold=0.8)
box = PrimBox(prim_obj, prim_obj.box_init, prim_obj.yi)
new_box_lim = pd.DataFrame([(0, 1, 1), (2, 5, 6)],
columns=['a', 'b', 'c'])
indices = np.array([0, 1], dtype=np.int)
box.update(new_box_lim, indices)
box.select(0)
self.assertTrue(np.all(box.yi == prim_obj.yi))
def test_inspect(self):
x = pd.DataFrame([(0,1,2),
(2,5,6),
(3,2,1)],
columns=['a', 'b', 'c'])
y = np.array([1,1,0])
prim_obj = prim.Prim(x, y, threshold=0.8)
box = PrimBox(prim_obj, prim_obj.box_init, prim_obj.yi)
new_box_lim = pd.DataFrame([(0,1,1),
(2,5,6)],
columns=['a', 'b', 'c'])
indices = np.array([0,1], dtype=np.int)
box.update(new_box_lim, indices)
box.inspect(1)
def test_inspect(self):
x = pd.DataFrame([(0,1,2),
(2,5,6),
(3,2,1)],
columns=['a', 'b', 'c'])
y = np.array([1,1,0])
prim_obj = prim.Prim(x, y, threshold=0.8)
box = PrimBox(prim_obj, prim_obj.box_init, prim_obj.yi)
new_box_lim = pd.DataFrame([(0,1,1),
(2,5,6)],
columns=['a', 'b', 'c'])
indices = np.array([0,1], dtype=np.int)
box.update(new_box_lim, indices)
box.inspect(1)
box.inspect()
box.inspect(style='graph')
with self.assertRaises(ValueError):
box.inspect(style='some unknown style')
def test_inspect(self):
x = pd.DataFrame([(0, 1, 2), (2, 5, 6), (3, 2, 1)],
columns=['a', 'b', 'c'])
y = np.array([1, 1, 0])
prim_obj = prim.Prim(x, y, threshold=0.8)
box = PrimBox(prim_obj, prim_obj.box_init, prim_obj.yi)
new_box_lim = pd.DataFrame([(0, 1, 1), (2, 5, 6)],
columns=['a', 'b', 'c'])
indices = np.array([0, 1], dtype=np.int)
box.update(new_box_lim, indices)
box.inspect(1)
box.inspect()
box.inspect(style='graph')
with self.assertRaises(ValueError):
box.inspect(style='some unknown style')
