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import numpy as np def cooldown(signal, cooldown=60): # Convert the signal column to a NumPy array if it's not already signal_array = np.array(signal) cooldown_counter = 0 for i in range(len(signal_array)): if signal_array[i] == 1: # If a signal is found, set the cooldown counter to the cooldown period cooldown_counter = cooldown elif cooldown_counter > 0: # If we are within the cooldown period (but the current signal is not 1), # we decrement the cooldown counter and set the current signal to 1 signal_array[i] = 1 cooldown_counter -= 1 # If cooldown_counter is 0, do nothing (signal stays as is) return signal_array # Compute the signal signal = trainer.predict(X_test) signal= cooldown(signal,60)
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