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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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