INNER CODE UNIT · Python

ind

RichardS0268/CNN-for-Trading · dataset.py:39

            ind = indicators[i*2].NAME
            ind_names.append(ind)
            params = str(indicators[i*2+1].PARAM).split(' ')
            tabular_df[ind] = cal_indicators(tabular_df, ind, params)
    
    dataset = []
    valid_dates = []
    lookback = image_size[1]//3
    for d in range(lookback-1, len(tabular_df)):
        # random skip some trading dates
        if np.random.rand(1) > sample_rate:
            continue
        # skip dates before start_date
        if tabular_df.iloc[d]['date'] < start_date:
            continue
        
        price_slice = tabular_df[d-(lookback-1):d+1][['open', 'high', 'low', 'close']+ind_names].reset_index(drop=True)
        volume_slice = tabular_df[d-(lookback-1):d+1][['volume']].reset_index(drop=True)

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