The calibration example fits a logistic regression and plots its predicted probabilities. A reliability curve compares predicted probability with observed frequency, so the previous hand-written score misstated the calibration it was meant to demonstrate.
The seasonal example carries trend and noise. Its series was a noiseless sine, so all ten cycles coincided exactly and the figure showed a single curve behind a ten-entry legend.
calibration_plot gained the Parameters and Returns sections it lacked, including a note that y_score must hold fitted probabilities.