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Fix Codacy Warnings (#477)

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Co-authored-by: Dario Coscia <dariocos99@gmail.com>
This commit is contained in:
Filippo Olivo
2025-03-10 15:38:45 +01:00
committed by Nicola Demo
parent e3790e049a
commit 4177bfbb50
157 changed files with 3473 additions and 3839 deletions
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35
tests/test_model/test_spline.py
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@@ -9,54 +9,61 @@ output_vars = 4
valid_args = [
{
'knots': torch.tensor([0., 0., 0., 1., 2., 3., 3., 3.]),
'control_points': torch.tensor([0., 0., 1., 0., 0.]),
'order': 3
"knots": torch.tensor([0.0, 0.0, 0.0, 1.0, 2.0, 3.0, 3.0, 3.0]),
"control_points": torch.tensor([0.0, 0.0, 1.0, 0.0, 0.0]),
"order": 3,
},
{
'knots': torch.tensor([-2., -2., -2., -2., -1., 0., 1., 2., 2., 2., 2.]),
'control_points': torch.tensor([0., 0., 0., 6., 0., 0., 0.]),
'order': 4
"knots": torch.tensor(
[-2.0, -2.0, -2.0, -2.0, -1.0, 0.0, 1.0, 2.0, 2.0, 2.0, 2.0]
),
"control_points": torch.tensor([0.0, 0.0, 0.0, 6.0, 0.0, 0.0, 0.0]),
"order": 4,
},
# {'control_points': {'n': 5, 'dim': 1}, 'order': 2},
# {'control_points': {'n': 7, 'dim': 1}, 'order': 3}
]
def scipy_check(model, x, y):
from scipy.interpolate._bsplines import BSpline
import numpy as np
spline = BSpline(
t=model.knots.detach().numpy(),
c=model.control_points.detach().numpy(),
k=model.order-1
k=model.order - 1,
)
y_scipy = spline(x).flatten()
y = y.detach().numpy()
np.testing.assert_allclose(y, y_scipy, atol=1e-5)
@pytest.mark.parametrize("args", valid_args)
def test_constructor(args):
Spline(**args)
def test_constructor_wrong():
with pytest.raises(ValueError):
Spline()
@pytest.mark.parametrize("args", valid_args)
def test_forward(args):
min_x = args['knots'][0]
max_x = args['knots'][-1]
min_x = args["knots"][0]
max_x = args["knots"][-1]
xi = torch.linspace(min_x, max_x, 1000)
model = Spline(**args)
yi = model(xi).squeeze()
scipy_check(model, xi, yi)
return
return
@pytest.mark.parametrize("args", valid_args)
def test_backward(args):
min_x = args['knots'][0]
max_x = args['knots'][-1]
min_x = args["knots"][0]
max_x = args["knots"][-1]
xi = torch.linspace(min_x, max_x, 100)
model = Spline(**args)
yi = model(xi)