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add legend in loss curves #8

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add legend in loss curves #8

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36 changes: 31 additions & 5 deletions src/callbacks.py
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Original file line number Diff line number Diff line change
Expand Up @@ -181,19 +181,45 @@ def save_fig_manifold(idx, b, deconvolver, dataloader, device, results_folder, l


def save_losses_fig(losses, results_folder):
steps = np.arange(len(losses))
arr = np.asarray(losses)
series = []
labels = []
if arr.ndim == 2 and arr.shape[1] >= 3:
total, drift, denoiser = arr[:, 0], arr[:, 1], arr[:, 2]
is_ode = np.allclose(denoiser, 0.0, atol=1e-12) and np.allclose(total, drift, atol=1e-12)
if is_ode:
series = [drift]
labels = ['drift_loss']
else:
series = [total, drift, denoiser]
labels = ['total_loss', 'drift_loss', 'denoiser_loss']
else:
# 1D (or anything else): treat as drift-only
series = [arr.squeeze()]
labels = ['drift_loss']

steps = np.arange(len(series[0]))
fig, axs = plt.subplots(1, 2, figsize=(12, 4))
axs[0].semilogy(steps, losses, marker='.', linestyle='-', markersize=4, alpha=0.7)
# semilogy
for y, lab in zip(series, labels):
axs[0].semilogy(steps, y, marker='.', linestyle='-', markersize=4, alpha=0.7, label=lab)
axs[0].set_xlabel("Steps")
axs[0].set_ylabel("Loss (log scale)")
axs[0].set_title("Loss Curve (Semi-Log Y Scale)")
axs[0].grid(True, which="both", ls="--", alpha=0.5)
axs[1].loglog(steps, losses, marker='.', linestyle='-', markersize=4, alpha=0.7, color='orangered')
axs[0].legend(loc='best', fontsize='small')

# loglog
for y in series:
axs[1].loglog(steps, y, marker='.', linestyle='-', markersize=4, alpha=0.7)
axs[1].set_xlabel("Steps (log scale)")
axs[1].set_ylabel("Loss (log scale)")
axs[1].set_title("Loss Curve (Log-Log Scale)")
axs[1].grid(True, which="both", ls="--", alpha=0.5)
axs[1].legend(labels, loc='best', fontsize='small')

plt.tight_layout()
print(os.path.join(results_folder, 'losses.png'))
plt.savefig(os.path.join(results_folder, 'losses.png'), dpi=300, bbox_inches='tight')
outfile = os.path.join(results_folder, 'losses.png')
print(outfile)
plt.savefig(outfile, dpi=300, bbox_inches='tight')
plt.close()