66 lines
2.0 KiB
Python
66 lines
2.0 KiB
Python
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import glob
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import pandas as pd
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from plotting import BacktestChart, plot
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DATE = 'Period'
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PROFIT = 'Cum. net profit'
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TOTAL_PROFIT = 'Total Cum. net profit'
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backtest_results_path = ''
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backtest_result_plot_title = ''
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all_start_dates = []
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all_end_dates = []
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# Find the earliest start date and the latest end date among all backtests.
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for file in glob.glob(backtest_results_path):
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backtest = pd.read_csv(file, sep = ',', usecols = [DATE])
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backtest[DATE] = pd.to_datetime(backtest[DATE])
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all_start_dates.append(backtest[DATE].min())
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all_end_dates.append(backtest[DATE].max())
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start_date = min(all_start_dates)
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end_date = max(all_end_dates)
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all_dates = pd.date_range(start = start_date, end = end_date, freq = 'D')
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backtests = []
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def parse_profit(profit):
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profit = profit.replace('$', '').replace(',', '').strip()
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# Negative values are enclosed in parentheses.
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if profit.startswith('(') and profit.endswith(')'):
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profit = profit.strip('()')
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return -float(profit)
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else:
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return float(profit)
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for file in glob.glob(backtest_results_path):
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backtest = pd.read_csv(file, sep = ',')
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backtest[DATE] = pd.to_datetime(backtest[DATE])
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backtest.set_index(DATE, inplace = True)
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backtest[PROFIT] = backtest[PROFIT].apply(parse_profit)
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backtest = backtest[[PROFIT]]
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backtest = backtest.reindex(all_dates)
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backtests.append(backtest)
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combined_backtests = pd.concat(backtests, axis = 1)
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combined_backtests.dropna(axis = 0, how = 'all', inplace = True)
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combined_backtests.fillna(method = 'ffill', inplace = True)
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combined_backtests.fillna(0, inplace = True)
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combined_backtests[TOTAL_PROFIT] = combined_backtests.sum(axis = 1)
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combined_backtests = combined_backtests[[TOTAL_PROFIT]]
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combined_backtests.reset_index(inplace = True)
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combined_backtests.rename(columns={'index': 'Date'}, inplace = True)
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plot(BacktestChart(
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dates = combined_backtests['Date'],
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profit = combined_backtests[TOTAL_PROFIT],
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title = backtest_result_plot_title
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))
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