davide
b8301a4329
- pytest.ini: configura testpaths, marker slow, output verboso - tests/conftest.py: fixture condivise (device, small_data, pinn_model) - tests/test_config.py: sanità parametri fisici e numerici, CFL, _pde_scale - tests/test_model.py: HeatPINN.forward e heat_pinn_loss (shape, finiti, zero-weight analytici per IC e BC, scaling dei pesi) - tests/test_engine_data.py: set_seed, _get_device, prepare_data (shape, bounds, device consistency, determinismo) - tests/test_integration_pinn.py: pipeline dati→modello→loss→backward - tests/test_e2e.py: FDM completo, visualizer FDM/PINN con tmp_path, training breve (2 test @slow) - requirements.txt: aggiunge pytest>=7.0.0 Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
74 lines
1.9 KiB
Python
74 lines
1.9 KiB
Python
import sys
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import os
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sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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import math
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import config
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def test_x_src_within_domain():
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assert 0.0 <= config.X_SRC <= config.L
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def test_t_step_before_t_end():
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assert 0.0 < config.T_STEP < config.T_END
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def test_gauss_sigma_positive():
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assert config.GAUSS_SIGMA > 0.0
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def test_physics_positive():
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assert config.ALPHA > 0.0
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assert config.K > 0.0
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assert config.H_CONV > 0.0
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assert config.L > 0.0
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assert config.T_END > 0.0
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def test_training_hyperparameters_positive():
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assert config.PATIENCE > 0
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assert config.EPOCHS > 0
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assert config.LR_ADAM > 0.0
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assert config.SCHED_MIN_LR > 0.0
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assert config.SCHED_FACTOR > 0.0
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assert config.SCHED_PATIENCE > 0
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def test_lr_ordering():
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"""Min LR deve essere inferiore all'LR iniziale."""
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assert config.SCHED_MIN_LR < config.LR_ADAM
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def test_sched_patience_lt_patience():
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"""Lo scheduler deve poter agire prima che scatti l'early stopping."""
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assert config.SCHED_PATIENCE < config.PATIENCE
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def test_cfl_stability():
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"""La griglia FDM deve soddisfare la condizione CFL (r ≤ 0.5)."""
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dx = config.L / (config.NX - 1)
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dt = config.T_END / (config.NT - 1)
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r = config.ALPHA * dt / dx ** 2
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assert r <= 0.5, f"CFL violata: r={r:.4f} > 0.5"
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def test_grid_dimensions():
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assert config.NX >= 2
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assert config.NT >= 2
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assert config.N_F >= 1
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assert config.N_IC >= 1
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assert config.N_BC >= 1
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def test_pde_scale_covers_source_peak():
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"""_pde_scale in model.py deve coprire il picco gaussiano della sorgente."""
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from model import _pde_scale
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src_peak = config.ALPHA * config.Q_VAL / (
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config.K * config.GAUSS_SIGMA * math.sqrt(2 * math.pi)
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)
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assert _pde_scale >= src_peak ** 2 - 1e-6, (
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f"_pde_scale={_pde_scale:.1f} < src_peak²={src_peak**2:.1f}: "
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"la loss PDE non è normalizzata correttamente"
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)
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