Update docs, add test
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@@ -22,23 +22,19 @@ DataFrame of the candles that resulted in buy signals. Depending on how many buy
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makes, this file may get quite large, so periodically check your `user_data/backtest_results`
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folder to delete old exports.
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To analyze the buy tags, we need to use the `buy_reasons.py` script from
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[froggleston's repo](https://github.com/froggleston/freqtrade-buyreasons). Follow the instructions
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in their README to copy the script into your `freqtrade/scripts/` folder.
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Before running your next backtest, make sure you either delete your old backtest results or run
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backtesting with the `--cache none` option to make sure no cached results are used.
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If all goes well, you should now see a `backtest-result-{timestamp}_signals.pkl` file in the
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`user_data/backtest_results` folder.
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Now run the `buy_reasons.py` script, supplying a few options:
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To analyze the entry/exit tags, we now need to use the `freqtrade analysis` command:
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``` bash
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python3 scripts/buy_reasons.py -c <config.json> -s <strategy_name> -t <timerange> -g0,1,2,3,4
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freqtrade analysis -c <config.json> -s <strategy_name> --analysis_groups 0,1,2,3,4
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```
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The `-g` option is used to specify the various tabular outputs, ranging from the simplest (0)
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The `--analysis_groups` option is used to specify the various tabular outputs, ranging from the simplest (0)
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to the most detailed per pair, per buy and per sell tag (4). More options are available by
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running with the `-h` option.
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@@ -54,18 +50,18 @@ To show only certain buy and sell tags in the displayed output, use the followin
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For example:
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```bash
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python3 scripts/buy_reasons.py -c <config.json> -s <strategy_name> -t <timerange> -g0,1,2,3,4 --enter_reason_list "enter_tag_a,enter_tag_b" --exit_reason_list "roi,custom_exit_tag_a,stop_loss"
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freqtrade analysis -c <config.json> -s <strategy_name> --analysis_groups 0,1,2,3,4 --enter_reason_list "enter_tag_a,enter_tag_b" --exit_reason_list "roi,custom_exit_tag_a,stop_loss"
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```
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### Outputting signal candle indicators
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The real power of the buy_reasons.py script comes from the ability to print out the indicator
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The real power of `freqtrade analysis` comes from the ability to print out the indicator
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values present on signal candles to allow fine-grained investigation and tuning of buy signal
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indicators. To print out a column for a given set of indicators, use the `--indicator-list`
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option:
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```bash
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python3 scripts/buy_reasons.py -c <config.json> -s <strategy_name> -t <timerange> -g0,1,2,3,4 --enter_reason_list "enter_tag_a,enter_tag_b" --exit_reason_list "roi,custom_exit_tag_a,stop_loss" --indicator_list "rsi,rsi_1h,bb_lowerband,ema_9,macd,macdsignal"
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freqtrade analysis -c <config.json> -s <strategy_name> --analysis_groups 0,1,2,3,4 --enter_reason_list "enter_tag_a,enter_tag_b" --exit_reason_list "roi,custom_exit_tag_a,stop_loss" --indicator_list "rsi,rsi_1h,bb_lowerband,ema_9,macd,macdsignal"
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```
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The indicators have to be present in your strategy's main DataFrame (either for your main
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