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_fwdavgnn_kpoints():
"""Test FwdAvgNN with k point provided : all request should get the same prediction."""
result = True
for i in range(50):
n = random.randint(1, 20)
m = random.randint(1, 20)
k = random.randint(1, 20)
model = AverageNNForwardModel(n, m, k = k)
for i in range(k):
x = np.random.rand(n)
y = np.random.rand(m)
model.add_xy(x, y)
x = np.random.rand(n)
ypg = model.predict_y(x)
for i in range(10):
x = np.random.rand(n)
ye = ypg
yp = model.predict_y(x)
check = np.allclose(ye, yp, rtol = 1e-10, atol = 1e-10)
if not check:
print('Error:', ye, yp)
result = result and check
return result
def test_fwdavgnn_samepoint():
"""Test FwdAvgNN with one point provided multiple times."""
result = True
for i in range(50):
n = random.randint(1, 20)
m = random.randint(1, 20)
k = random.randint(1, 20)
model = AverageNNForwardModel(n, m, k = k)
x = np.random.rand(n)
y = np.random.rand(m)
for i in range(random.randint(1, 20)):
model.add_xy(x, y)
for i in range(10):
x = np.random.rand(n)
ye = y
yp = model.predict_y(x)
check = np.allclose(ye, yp, rtol = 1e-10, atol = 1e-10)
if not check:
print('Error:', x, ye, yp)
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_fwdavgnn_samepoint():
"""Test FwdAvgNN with one point provided multiple times."""
result = True
for i in range(50):
n = random.randint(1, 20)
m = random.randint(1, 20)
k = random.randint(1, 20)
model = AverageNNForwardModel(n, m, k=k)
x = np.random.rand(n)
y = np.random.rand(m)
for i in range(random.randint(1, 20)):
model.add_xy(x, y)
for i in range(10):
x = np.random.rand(n)
ye = y
yp = model.predict_y(x)
check = np.allclose(ye, yp, rtol=1e-10, atol=1e-10)
if not check:
print('Error:', x, ye, yp)
result = result and check
return result
def test_fwdavgnn_kpoints():
"""Test FwdAvgNN with k point provided : all request should get the same prediction."""
result = True
for i in range(50):
n = random.randint(1, 20)
m = random.randint(1, 20)
k = random.randint(1, 20)
model = AverageNNForwardModel(n, m, k=k)
for i in range(k):
x = np.random.rand(n)
y = np.random.rand(m)
model.add_xy(x, y)
x = np.random.rand(n)
ypg = model.predict_y(x)
for i in range(10):
x = np.random.rand(n)
ye = ypg
yp = model.predict_y(x)
check = np.allclose(ye, yp, rtol=1e-10, atol=1e-10)
if not check:
print('Error:', ye, yp)
result = result and check
return result