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377 lines
15 KiB
Markdown
377 lines
15 KiB
Markdown
# Plotting
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This page explains how to plot prices, indicators and profits.
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## Installation / Setup
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Plotting modules use the Plotly library. You can install / upgrade this by running the following command:
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``` bash
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pip install -U -r requirements-plot.txt
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```
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## Plot price and indicators
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The `freqtrade plot-dataframe` subcommand shows an interactive graph with three subplots:
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* Main plot with candlesticks and indicators following price (sma/ema)
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* Volume bars
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* Additional indicators as specified by `--indicators2`
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Possible arguments:
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```
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usage: freqtrade plot-dataframe [-h] [-v] [--logfile FILE] [-V] [-c PATH]
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[-d PATH] [--userdir PATH] [-s NAME]
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[--strategy-path PATH] [-p PAIRS [PAIRS ...]]
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[--indicators1 INDICATORS1 [INDICATORS1 ...]]
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[--indicators2 INDICATORS2 [INDICATORS2 ...]]
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[--plot-limit INT] [--db-url PATH]
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[--trade-source {DB,file}] [--export EXPORT]
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[--export-filename PATH]
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[--timerange TIMERANGE] [-i TIMEFRAME]
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[--no-trades]
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optional arguments:
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-h, --help show this help message and exit
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-p PAIRS [PAIRS ...], --pairs PAIRS [PAIRS ...]
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Limit command to these pairs. Pairs are space-
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separated.
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--indicators1 INDICATORS1 [INDICATORS1 ...]
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Set indicators from your strategy you want in the
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first row of the graph. Space-separated list. Example:
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`ema3 ema5`. Default: `['sma', 'ema3', 'ema5']`.
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--indicators2 INDICATORS2 [INDICATORS2 ...]
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Set indicators from your strategy you want in the
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third row of the graph. Space-separated list. Example:
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`fastd fastk`. Default: `['macd', 'macdsignal']`.
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--plot-limit INT Specify tick limit for plotting. Notice: too high
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values cause huge files. Default: 750.
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--db-url PATH Override trades database URL, this is useful in custom
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deployments (default: `sqlite:///tradesv3.sqlite` for
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Live Run mode, `sqlite:///tradesv3.dryrun.sqlite` for
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Dry Run).
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--trade-source {DB,file}
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Specify the source for trades (Can be DB or file
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(backtest file)) Default: file
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--export EXPORT Export backtest results, argument are: trades.
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Example: `--export=trades`
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--export-filename PATH
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Save backtest results to the file with this filename.
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Requires `--export` to be set as well. Example:
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`--export-filename=user_data/backtest_results/backtest
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_today.json`
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--timerange TIMERANGE
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Specify what timerange of data to use.
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-i TIMEFRAME, --timeframe TIMEFRAME
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Specify timeframe (`1m`, `5m`, `30m`, `1h`, `1d`).
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--no-trades Skip using trades from backtesting file and DB.
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Common arguments:
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-v, --verbose Verbose mode (-vv for more, -vvv to get all messages).
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--logfile FILE Log to the file specified. Special values are:
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'syslog', 'journald'. See the documentation for more
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details.
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-V, --version show program's version number and exit
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-c PATH, --config PATH
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Specify configuration file (default:
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`userdir/config.json` or `config.json` whichever
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exists). Multiple --config options may be used. Can be
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set to `-` to read config from stdin.
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-d PATH, --datadir PATH
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Path to directory with historical backtesting data.
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--userdir PATH, --user-data-dir PATH
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Path to userdata directory.
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Strategy arguments:
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-s NAME, --strategy NAME
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Specify strategy class name which will be used by the
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bot.
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--strategy-path PATH Specify additional strategy lookup path.
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```
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Example:
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``` bash
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freqtrade plot-dataframe -p BTC/ETH --strategy AwesomeStrategy
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```
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The `-p/--pairs` argument can be used to specify pairs you would like to plot.
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!!! Note
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The `freqtrade plot-dataframe` subcommand generates one plot-file per pair.
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Specify custom indicators.
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Use `--indicators1` for the main plot and `--indicators2` for the subplot below (if values are in a different range than prices).
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``` bash
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freqtrade plot-dataframe --strategy AwesomeStrategy -p BTC/ETH --indicators1 sma ema --indicators2 macd
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```
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### Further usage examples
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To plot multiple pairs, separate them with a space:
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``` bash
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freqtrade plot-dataframe --strategy AwesomeStrategy -p BTC/ETH XRP/ETH
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```
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To plot a timerange (to zoom in)
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``` bash
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freqtrade plot-dataframe --strategy AwesomeStrategy -p BTC/ETH --timerange=20180801-20180805
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```
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To plot trades stored in a database use `--db-url` in combination with `--trade-source DB`:
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``` bash
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freqtrade plot-dataframe --strategy AwesomeStrategy --db-url sqlite:///tradesv3.dry_run.sqlite -p BTC/ETH --trade-source DB
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```
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To plot trades from a backtesting result, use `--export-filename <filename>`
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``` bash
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freqtrade plot-dataframe --strategy AwesomeStrategy --export-filename user_data/backtest_results/backtest-result.json -p BTC/ETH
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```
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### Plot dataframe basics
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The `plot-dataframe` subcommand requires backtesting data, a strategy and either a backtesting-results file or a database, containing trades corresponding to the strategy.
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The resulting plot will have the following elements:
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* Green triangles: Buy signals from the strategy. (Note: not every buy signal generates a trade, compare to cyan circles.)
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* Red triangles: Sell signals from the strategy. (Also, not every sell signal terminates a trade, compare to red and green squares.)
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* Cyan circles: Trade entry points.
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* Red squares: Trade exit points for trades with loss or 0% profit.
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* Green squares: Trade exit points for profitable trades.
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* Indicators with values corresponding to the candle scale (e.g. SMA/EMA), as specified with `--indicators1`.
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* Volume (bar chart at the bottom of the main chart).
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* Indicators with values in different scales (e.g. MACD, RSI) below the volume bars, as specified with `--indicators2`.
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!!! Note "Bollinger Bands"
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Bollinger bands are automatically added to the plot if the columns `bb_lowerband` and `bb_upperband` exist, and are painted as a light blue area spanning from the lower band to the upper band.
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#### Advanced plot configuration
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An advanced plot configuration can be specified in the strategy in the `plot_config` parameter.
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Additional features when using `plot_config` include:
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* Specify colors per indicator
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* Specify additional subplots
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* Specify indicator pairs to fill area in between
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The sample plot configuration below specifies fixed colors for the indicators. Otherwise, consecutive plots may produce different color schemes each time, making comparisons difficult.
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It also allows multiple subplots to display both MACD and RSI at the same time.
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Plot type can be configured using `type` key. Possible types are:
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* `scatter` corresponding to `plotly.graph_objects.Scatter` class (default).
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* `bar` corresponding to `plotly.graph_objects.Bar` class.
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Extra parameters to `plotly.graph_objects.*` constructor can be specified in `plotly` dict.
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Sample configuration with inline comments explaining the process:
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``` python
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@property
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def plot_config(self):
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"""
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There are a lot of solutions how to build the return dictionary.
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The only important point is the return value.
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Example:
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plot_config = {'main_plot': {}, 'subplots': {}}
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"""
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plot_config = {}
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plot_config['main_plot'] = {
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# Configuration for main plot indicators.
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# Assumes 2 parameters, emashort and emalong to be specified.
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f'ema_{self.emashort.value}': {'color': 'red'},
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f'ema_{self.emalong.value}': {'color': '#CCCCCC'},
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# By omitting color, a random color is selected.
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'sar': {},
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# fill area between senkou_a and senkou_b
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'senkou_a': {
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'color': 'green', #optional
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'fill_to': 'senkou_b',
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'fill_label': 'Ichimoku Cloud', #optional
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'fill_color': 'rgba(255,76,46,0.2)', #optional
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},
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# plot senkou_b, too. Not only the area to it.
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'senkou_b': {}
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}
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plot_config['subplots'] = {
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# Create subplot MACD
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"MACD": {
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'macd': {'color': 'blue', 'fill_to': 'macdhist'},
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'macdsignal': {'color': 'orange'},
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'macdhist': {'type': 'bar', 'plotly': {'opacity': 0.9}}
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},
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# Additional subplot RSI
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"RSI": {
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'rsi': {'color': 'red'}
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}
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}
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return plot_config
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```
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??? Note "As attribute (former method)"
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Assigning plot_config is also possible as Attribute (this used to be the default way).
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This has the disadvantage that strategy parameters are not available, preventing certain configurations from working.
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``` python
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plot_config = {
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'main_plot': {
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# Configuration for main plot indicators.
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# Specifies `ema10` to be red, and `ema50` to be a shade of gray
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'ema10': {'color': 'red'},
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'ema50': {'color': '#CCCCCC'},
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# By omitting color, a random color is selected.
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'sar': {},
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# fill area between senkou_a and senkou_b
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'senkou_a': {
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'color': 'green', #optional
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'fill_to': 'senkou_b',
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'fill_label': 'Ichimoku Cloud', #optional
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'fill_color': 'rgba(255,76,46,0.2)', #optional
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},
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# plot senkou_b, too. Not only the area to it.
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'senkou_b': {}
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},
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'subplots': {
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# Create subplot MACD
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"MACD": {
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'macd': {'color': 'blue', 'fill_to': 'macdhist'},
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'macdsignal': {'color': 'orange'},
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'macdhist': {'type': 'bar', 'plotly': {'opacity': 0.9}}
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},
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# Additional subplot RSI
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"RSI": {
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'rsi': {'color': 'red'}
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}
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}
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}
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```
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!!! Note
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The above configuration assumes that `ema10`, `ema50`, `senkou_a`, `senkou_b`,
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`macd`, `macdsignal`, `macdhist` and `rsi` are columns in the DataFrame created by the strategy.
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!!! Warning
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`plotly` arguments are only supported with plotly library and will not work with freq-ui.
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!!! Note "Trade position adjustments"
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If `position_adjustment_enable` / `adjust_trade_position()` is used, the trade initial buy price is averaged over multiple orders and the trade start price will most likely appear outside the candle range.
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## Plot profit
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The `plot-profit` subcommand shows an interactive graph with three plots:
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* Average closing price for all pairs.
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* The summarized profit made by backtesting.
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Note that this is not the real-world profit, but more of an estimate.
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* Profit for each individual pair.
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* Parallelism of trades.
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* Underwater (Periods of drawdown).
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The first graph is good to get a grip of how the overall market progresses.
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The second graph will show if your algorithm works or doesn't.
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Perhaps you want an algorithm that steadily makes small profits, or one that acts less often, but makes big swings.
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This graph will also highlight the start (and end) of the Max drawdown period.
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The third graph can be useful to spot outliers, events in pairs that cause profit spikes.
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The forth graph can help you analyze trade parallelism, showing how often max_open_trades have been maxed out.
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Possible options for the `freqtrade plot-profit` subcommand:
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```
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usage: freqtrade plot-profit [-h] [-v] [--logfile FILE] [-V] [-c PATH]
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[-d PATH] [--userdir PATH] [-s NAME]
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[--strategy-path PATH] [-p PAIRS [PAIRS ...]]
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[--timerange TIMERANGE] [--export EXPORT]
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[--export-filename PATH] [--db-url PATH]
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[--trade-source {DB,file}] [-i TIMEFRAME]
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optional arguments:
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-h, --help show this help message and exit
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-p PAIRS [PAIRS ...], --pairs PAIRS [PAIRS ...]
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Limit command to these pairs. Pairs are space-
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separated.
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--timerange TIMERANGE
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Specify what timerange of data to use.
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--export EXPORT Export backtest results, argument are: trades.
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Example: `--export=trades`
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--export-filename PATH, --backtest-filename PATH
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Use backtest results from this filename.
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Requires `--export` to be set as well. Example:
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`--export-filename=user_data/backtest_results/backtest
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_today.json`
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--db-url PATH Override trades database URL, this is useful in custom
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deployments (default: `sqlite:///tradesv3.sqlite` for
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Live Run mode, `sqlite:///tradesv3.dryrun.sqlite` for
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Dry Run).
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--trade-source {DB,file}
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Specify the source for trades (Can be DB or file
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(backtest file)) Default: file
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-i TIMEFRAME, --timeframe TIMEFRAME
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Specify timeframe (`1m`, `5m`, `30m`, `1h`, `1d`).
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--auto-open Automatically open generated plot.
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Common arguments:
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-v, --verbose Verbose mode (-vv for more, -vvv to get all messages).
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--logfile FILE Log to the file specified. Special values are:
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'syslog', 'journald'. See the documentation for more
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details.
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-V, --version show program's version number and exit
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-c PATH, --config PATH
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Specify configuration file (default:
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`userdir/config.json` or `config.json` whichever
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exists). Multiple --config options may be used. Can be
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set to `-` to read config from stdin.
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-d PATH, --datadir PATH
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Path to directory with historical backtesting data.
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--userdir PATH, --user-data-dir PATH
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Path to userdata directory.
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Strategy arguments:
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-s NAME, --strategy NAME
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Specify strategy class name which will be used by the
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bot.
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--strategy-path PATH Specify additional strategy lookup path.
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```
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The `-p/--pairs` argument, can be used to limit the pairs that are considered for this calculation.
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Examples:
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Use custom backtest-export file
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``` bash
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freqtrade plot-profit -p LTC/BTC --export-filename user_data/backtest_results/backtest-result.json
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```
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Use custom database
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``` bash
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freqtrade plot-profit -p LTC/BTC --db-url sqlite:///tradesv3.sqlite --trade-source DB
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```
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``` bash
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freqtrade --datadir user_data/data/binance_save/ plot-profit -p LTC/BTC
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```
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