def test_nn_xy(self):
nnset = NNSet()
for x_i in range(10):
nnset.add([x_i, x_i], [x_i * 2])
for x_i in range(10):
dists, idxs = nnset.nn_y([2 * x_i + 0.1], k=1)
nn_y = list(nnset.ys[idxs[0]])
self.assertEqual(nn_y, [2 * x_i])
def test_nn_x(self):
nnset = NNSet()
for x_i in range(10):
nnset.add([x_i, x_i])
for x_i in range(10):
dists, idxs = nnset.nn_x([x_i, x_i + 0.5], k=1)
nn_x = list(nnset.xs[idxs[0]])
self.assertEqual(nn_x, [x_i, x_i])
def test_nn_xy(self):
nnset = NNSet()
for x_i in range(10):
nnset.add([x_i, x_i], [x_i*2])
for x_i in range(10):
dists, idxs = nnset.nn_y([2*x_i+0.1], k=1)
nn_y = list(nnset.ys[idxs[0]])
self.assertEqual(nn_y, [2*x_i])
def test_nn_x(self):
nnset = NNSet()
for x_i in range(10):
nnset.add([x_i, x_i])
for x_i in range(10):
dists, idxs = nnset.nn_x([x_i, x_i+0.5], k=1)
nn_x = list(nnset.xs[idxs[0]])
self.assertEqual(nn_x, [x_i, x_i])
def test_incrementalnn(self):
for _ in range(10):
implementations = [
BruteForceNNSet(),
BatchNNSet(),
NNSet(poolsize=7)
]
n = random.randint(2, 5)
m = random.randint(2, 5)
for j in range(100):
x, y = [random.random() for _ in range(n)
], [random.random() for _ in range(m)]
for imp in implementations:
imp.add(x, y)
for _ in range(10):
k = min(random.randint(1, 10), j + 1)
x, y = [random.random() for _ in range(n)
], [random.random() for _ in range(m)]
indexes = []
for imp in implementations:
dists, idxes = imp.nn_x(x, k=k)
indexes.append(idxes)
self.assertEqual(*indexes)
K = 1
DYN_FREQ = 1
DYN_QUERIES = 1
END_QUERIES = 50
def testrun(nnset):
random.seed(0)
for i in range(N):
x = [random.random() for _ in range(DIM)]
nnset.add(x, [random.random()])
if i % DYN_FREQ == 0:
for i in range(DYN_QUERIES):
x = [random.random() for _ in range(DIM)]
nnset.nn_x(x, k=1)
for i in range(END_QUERIES):
x = [random.random() for _ in range(DIM)]
nnset.nn_x(x, k=1)
if __name__ == '__main__':
print('Running benchmark... this may take a few minutes.')
for nnset in [NNSet(), BatchNNSet(), BruteForceNNSet()]:
start = time.time()
testrun(nnset)
print('{}: {:4.2f}s'.format(nnset.__class__.__name__,
time.time() - start))
