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tutorial validation (#185)

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Co-authored-by: Ben Volokh <89551265+benv123@users.noreply.github.com>
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Nicola Demo
2023-10-17 10:54:31 +02:00
parent 2e2fe93458
commit 32ff5de1f4
38 changed files with 1072 additions and 1006 deletions
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185
tutorials/tutorial2/tutorial.ipynb vendored
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17
tutorials/tutorial2/tutorial.py vendored
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@@ -98,7 +98,7 @@ trainer = Trainer(pinn, max_epochs=1000, callbacks=[MetricTracker()])
trainer.train()
# Now the *Plotter* class is used to plot the results.
# Now the `Plotter` class is used to plot the results.
# The solution predicted by the neural network is plotted on the left, the exact one is represented at the center and on the right the error between the exact and the predicted solutions is showed.
# In[4]:
@@ -238,18 +238,3 @@ trainer_learn.train()
plotter.plot(trainer_learn)
# In[10]:
import matplotlib.pyplot as plt
plt.figure(figsize=(16, 6))
plotter.plot_loss(trainer, label='Standard')
plotter.plot_loss(trainer_feat, label='Static Features')
plotter.plot_loss(trainer_learn, label='Learnable Features')
plt.grid()
plt.legend()
plt.show()