def test_fwdwnn_kpoints_group():
"""Test FwdWNN with group of k same points provided : all request should return
point of the dataset."""
result = True
size = 30
for i in range(20):
n = random.randint(1, size)
m = random.randint(1, size)
k = random.randint(1, size)
sigma = random.uniform(0.1, 10)
model = WeightedNNForwardModel(n, m, sigma=sigma, k=k)
ygroup = set()
for i in range(random.randint(1, size)):
x = np.random.rand(n)
y = np.random.rand(m)
ygroup.add(tuple(y))
for i in range(k):
model.add_xy(x, y)
for i in range(10):
x = np.random.rand(n)
yp = model.predict_y(x)
check = min([tools.dist(yp, y) for y in ygroup]) < 1e-10
if not check:
print('Error:', n, m, k,
min([tools.dist(yp, y) for y in ygroup]), yp)
result = result and check
return result
def test_fwdwnn_kpoints_group():
"""Test FwdWNN with group of k same points provided : all request should return
point of the dataset."""
result = True
size = 30
for i in range(20):
n = random.randint(1, size)
m = random.randint(1, size)
k = random.randint(1, size)
sigma = random.uniform(0.1, 10)
model = WeightedNNForwardModel(n, m, sigma = sigma, k = k)
ygroup = set()
for i in range(random.randint(1, size)):
x = np.random.rand(n)
y = np.random.rand(m)
ygroup.add(tuple(y))
for i in range(k):
model.add_xy(x, y)
for i in range(10):
x = np.random.rand(n)
yp = model.predict_y(x)
check = min([tools.dist(yp, y) for y in ygroup]) < 1e-10
if not check:
print('Error:', n, m, k, min([tools.dist(yp, y) for y in ygroup]), yp)
result = result and check
return result
def test_invwnn_kpoints_group():
"""Test InvWNN with group of k same points provided : all request should return
point of the dataset."""
result = True
for i in range(25):
n = random.randint(1, 20)
m = random.randint(1, 20)
k = random.randint(1, 20)
sigma = random.uniform(0.1, 10)
model = WeightedNNInverseModel(n, m, sigma, k)
xgroup = set()
for i in range(random.randint(1, 20)):
x = np.random.rand(n)
y = np.random.rand(m)
xgroup.add(tuple(x))
for i in range(k):
model.add_xy(x, y)
for i in range(10):
y = np.random.rand(m)
xp = model.infer_x(y)[0]
check = min([tools.dist(xp, x) for x in xgroup]) < 1e-10
if not check:
print('Error:', n, m, y, xe, xp)
result = result and check
return result
def test_fwdavgnn_kpoints_group():
"""Test FwdAvgNN with group of k same points provided : all request should return
point of the dataset."""
result = True
for i in range(25):
n = random.randint(1, 20)
m = random.randint(1, 20)
k = random.randint(1, 20)
model = AverageNNForwardModel(n, m, k = k)
ygroup = set()
for i in range(random.randint(1, 20)):
x = np.random.rand(n)
y = np.random.rand(m)
ygroup.add(tuple(y))
for i in range(k):
model.add_xy(x, y)
for i in range(10):
x = np.random.rand(n)
yp = model.predict_y(x)
check = min([tools.dist(yp, y) for y in ygroup]) < 1e-10
if not check:
print('Error:', x, yp)
result = result and check
return result
def test_invavgnn_kpoints_group():
"""Test InvAvgNN with group of k same points provided : all request should return
point of the dataset."""
result = True
for i in range(20):
n = random.randint(1, 20)
m = random.randint(1, 20)
k = random.randint(1, 20)
model = AverageNNInverseModel(n, m, k)
xgroup = set()
for i in range(random.randint(1, 20)):
x = np.random.rand(n)
y = np.random.rand(m)
xgroup.add(tuple(x))
for i in range(k):
model.add_xy(x, y)
for i in range(10):
y = np.random.rand(m)
xp = model.infer_x(y)[0]
check = min([tools.dist(xp, x) for x in xgroup]) < 1e-10
if not check:
print('Error:', n, m, y, xe, xp)
result = result and check
return result
def test_fwdavgnn_kpoints_group():
"""Test FwdAvgNN with group of k same points provided : all request should return
point of the dataset."""
result = True
for i in range(25):
n = random.randint(1, 20)
m = random.randint(1, 20)
k = random.randint(1, 20)
model = AverageNNForwardModel(n, m, k=k)
ygroup = set()
for i in range(random.randint(1, 20)):
x = np.random.rand(n)
y = np.random.rand(m)
ygroup.add(tuple(y))
for i in range(k):
model.add_xy(x, y)
for i in range(10):
x = np.random.rand(n)
yp = model.predict_y(x)
check = min([tools.dist(yp, y) for y in ygroup]) < 1e-10
if not check:
print('Error:', x, yp)
result = result and check
return result
