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tools/figures/log_snr.py

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+import numpy as np
+import matplotlib.pyplot as plt
+
+t = np.linspace(0.001, 0.999, 100)
+def snr(t):
+    return np.log((1-t)/t)
+def pds(t):
+    return np.clip(((1-t)/t)**2, a_max=0.5, a_min=0.0)
+print(pds(t))
+plt.figure(figsize=(16, 4))
+plt.plot(t, snr(t), color="#ff70a6", linewidth=3, marker="o")
+# plt.plot(t, pds(t), color="#ff9770", linewidth=3, marker="o")
+plt.ylabel("log-SNR", weight="bold")
+plt.xlabel("Timesteps", weight="bold")
+plt.xticks([1.0, 0.8, 0.6, 0.4, 0.2, 0.0])
+plt.gca().invert_xaxis()
+plt.show()
+# plt.savefig("output/logsnr.pdf", bbox_inches='tight')