Question about data and TCO algorithm

[Yccc0903]

Sorry, I'm poor in coding, and have some question.

1. What is the type of data (nyse_o, sp500, and so on.)? It dosen't looks like "raw stock price" or "price relatives".
2. About TCO1 algorithm, I want to know what are "p" and "history"?
3. And why it is "history.iloc[-2] / p" in reversal type?
   I study the paper, they use "1/xt" to predict next price relatives in TCO1.

Thanks for your help!

[TCO.py]

class TCO1(TCO):
def init(self, type="reversal", **kwargs):
self.type = type
super().init(min_history=1, **kwargs)

def predict(self, p, history):
    if self.type == "reversal":
        return history.iloc[-2] / p
    elif self.type == "trend":
        return p / history.iloc[-2]
    else:
        raise NotImplementedError()