pre_train_all_indicator

The "GodStra_All_Indicator" strategy is a backtesting strategy that calculates various indicators in different time periods to optimize the strategy. However, it only calculates specific indicators in specific time periods inside the "buy" and "sell" strategy populator methods if needed. The purpose of the "populate_indicators" method is to calculate default values of hyperoptable parameters, but it doesn't provide significant benefits compared to calculating usable things inside the "buy" and "sell" trend populators.

The "populate_buy_trend" method is responsible for populating the conditions for generating buy signals.

It retrieves the values of multiple indicators, crossed indicators, operators, and real numbers from the strategy's parameters.

Then, it uses a "condition_generator" function to generate conditions based on these parameters and the input dataframe. The generated conditions are appended to a list. If any conditions exist in the list, they are applied to the dataframe, marking the corresponding rows as a buy signal. Similarly, the "populate_sell_trend" method populates the conditions for generating sell signals. It retrieves the values of sell indicators, crossed indicators, operators, and real numbers from the strategy's parameters and uses the "condition_generator" function to generate conditions. The generated conditions are appended to a list, and if any conditions exist, they are applied to the dataframe, marking the corresponding rows as a sell signal. Overall, this strategy calculates indicators and generates buy and sell signals based on the specified conditions.