Merge pull request #2752 from freqtrade/plotting/indicator_strategy
Allow enhanced plot-dataframe configuration
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Matthias
GitHub
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@ -120,16 +120,77 @@ To plot trades from a backtesting result, use `--export-filename <filename>`
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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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The sample plot configuration below specifies fixed colors for the indicators. Otherwise consecutive plots may produce different colorschemes 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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Sample configuration with inline comments explaining the process:
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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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},
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'subplots': {
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# Create subplot MACD
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"MACD": {
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'macd': {'color': 'blue'},
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'macdsignal': {'color': 'orange'},
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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`, `macd`, `macdsignal` and `rsi` are columns in the DataFrame created by the strategy.
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## Plot profit
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The `freqtrade plot-profit` subcommand shows an interactive graph with three plots:
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The `plot-profit` subcommand shows an interactive graph with three plots:
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1) Average closing price for all pairs
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2) The summarized profit made by backtesting.
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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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3) Profit for each individual pair
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* Profit for each individual pair.
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The first graph is good to get a grip of how the overall market progresses.
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@ -363,15 +363,13 @@ AVAILABLE_CLI_OPTIONS = {
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"indicators1": Arg(
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'--indicators1',
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help='Set indicators from your strategy you want in the first row of the graph. '
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'Space-separated list. Example: `ema3 ema5`. Default: `%(default)s`.',
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default=['sma', 'ema3', 'ema5'],
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"Space-separated list. Example: `ema3 ema5`. Default: `['sma', 'ema3', 'ema5']`.",
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nargs='+',
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),
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"indicators2": Arg(
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'--indicators2',
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help='Set indicators from your strategy you want in the third row of the graph. '
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'Space-separated list. Example: `fastd fastk`. Default: `%(default)s`.',
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default=['macd', 'macdsignal'],
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"Space-separated list. Example: `fastd fastk`. Default: `['macd', 'macdsignal']`.",
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nargs='+',
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),
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"plot_limit": Arg(
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@ -54,21 +54,27 @@ def init_plotscript(config):
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}
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def add_indicators(fig, row, indicators: List[str], data: pd.DataFrame) -> make_subplots:
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def add_indicators(fig, row, indicators: Dict[str, Dict], data: pd.DataFrame) -> make_subplots:
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"""
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Generator all the indicator selected by the user for a specific row
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Generate all the indicators selected by the user for a specific row, based on the configuration
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:param fig: Plot figure to append to
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:param row: row number for this plot
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:param indicators: List of indicators present in the dataframe
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:param indicators: Dict of Indicators with configuration options.
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Dict key must correspond to dataframe column.
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:param data: candlestick DataFrame
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"""
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for indicator in indicators:
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for indicator, conf in indicators.items():
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logger.debug(f"indicator {indicator} with config {conf}")
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if indicator in data:
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kwargs = {'x': data['date'],
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'y': data[indicator].values,
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'mode': 'lines',
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'name': indicator
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}
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if 'color' in conf:
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kwargs.update({'line': {'color': conf['color']}})
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scatter = go.Scatter(
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x=data['date'],
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y=data[indicator].values,
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mode='lines',
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name=indicator
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**kwargs
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)
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fig.add_trace(scatter, row, 1)
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else:
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@ -107,11 +113,31 @@ def plot_trades(fig, trades: pd.DataFrame) -> make_subplots:
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"""
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# Trades can be empty
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if trades is not None and len(trades) > 0:
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# Create description for sell summarizing the trade
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trades['desc'] = trades.apply(lambda row: f"{round(row['profitperc'] * 100, 1)}%, "
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f"{row['sell_reason']}, {row['duration']} min",
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axis=1)
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trade_buys = go.Scatter(
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x=trades["open_time"],
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y=trades["open_rate"],
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mode='markers',
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name='trade_buy',
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name='Trade buy',
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text=trades["desc"],
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marker=dict(
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symbol='circle-open',
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size=11,
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line=dict(width=2),
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color='cyan'
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)
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)
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trade_sells = go.Scatter(
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x=trades.loc[trades['profitperc'] > 0, "close_time"],
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y=trades.loc[trades['profitperc'] > 0, "close_rate"],
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text=trades.loc[trades['profitperc'] > 0, "desc"],
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mode='markers',
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name='Sell - Profit',
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marker=dict(
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symbol='square-open',
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size=11,
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@ -119,16 +145,12 @@ def plot_trades(fig, trades: pd.DataFrame) -> make_subplots:
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color='green'
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)
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)
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# Create description for sell summarizing the trade
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desc = trades.apply(lambda row: f"{round(row['profitperc'] * 100, 1)}%, "
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f"{row['sell_reason']}, {row['duration']} min",
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axis=1)
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trade_sells = go.Scatter(
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x=trades["close_time"],
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y=trades["close_rate"],
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text=desc,
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trade_sells_loss = go.Scatter(
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x=trades.loc[trades['profitperc'] <= 0, "close_time"],
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y=trades.loc[trades['profitperc'] <= 0, "close_rate"],
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text=trades.loc[trades['profitperc'] <= 0, "desc"],
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mode='markers',
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name='trade_sell',
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name='Sell - Loss',
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marker=dict(
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symbol='square-open',
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size=11,
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@ -138,14 +160,53 @@ def plot_trades(fig, trades: pd.DataFrame) -> make_subplots:
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)
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fig.add_trace(trade_buys, 1, 1)
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fig.add_trace(trade_sells, 1, 1)
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fig.add_trace(trade_sells_loss, 1, 1)
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else:
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logger.warning("No trades found.")
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return fig
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def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFrame = None,
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def create_plotconfig(indicators1: List[str], indicators2: List[str],
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plot_config: Dict[str, Dict]) -> Dict[str, Dict]:
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"""
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Combines indicators 1 and indicators 2 into plot_config if necessary
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:param indicators1: List containing Main plot indicators
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:param indicators2: List containing Sub plot indicators
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:param plot_config: Dict of Dicts containing advanced plot configuration
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:return: plot_config - eventually with indicators 1 and 2
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"""
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if plot_config:
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if indicators1:
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plot_config['main_plot'] = {ind: {} for ind in indicators1}
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if indicators2:
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plot_config['subplots'] = {'Other': {ind: {} for ind in indicators2}}
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if not plot_config:
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# If no indicators and no plot-config given, use defaults.
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if not indicators1:
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indicators1 = ['sma', 'ema3', 'ema5']
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if not indicators2:
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indicators2 = ['macd', 'macdsignal']
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# Create subplot configuration if plot_config is not available.
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plot_config = {
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'main_plot': {ind: {} for ind in indicators1},
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'subplots': {'Other': {ind: {} for ind in indicators2}},
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}
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if 'main_plot' not in plot_config:
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plot_config['main_plot'] = {}
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if 'subplots' not in plot_config:
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plot_config['subplots'] = {}
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return plot_config
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def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFrame = None, *,
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indicators1: List[str] = [],
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indicators2: List[str] = [],) -> go.Figure:
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indicators2: List[str] = [],
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plot_config: Dict[str, Dict] = {},
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) -> go.Figure:
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"""
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Generate the graph from the data generated by Backtesting or from DB
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Volume will always be ploted in row2, so Row 1 and 3 are to our disposal for custom indicators
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@ -154,21 +215,26 @@ def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFra
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:param trades: All trades created
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:param indicators1: List containing Main plot indicators
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:param indicators2: List containing Sub plot indicators
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:return: None
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:param plot_config: Dict of Dicts containing advanced plot configuration
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:return: Plotly figure
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"""
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plot_config = create_plotconfig(indicators1, indicators2, plot_config)
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rows = 2 + len(plot_config['subplots'])
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row_widths = [1 for _ in plot_config['subplots']]
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# Define the graph
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fig = make_subplots(
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rows=3,
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rows=rows,
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cols=1,
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shared_xaxes=True,
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row_width=[1, 1, 4],
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row_width=row_widths + [1, 4],
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vertical_spacing=0.0001,
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)
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fig['layout'].update(title=pair)
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fig['layout']['yaxis1'].update(title='Price')
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fig['layout']['yaxis2'].update(title='Volume')
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fig['layout']['yaxis3'].update(title='Other')
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for i, name in enumerate(plot_config['subplots']):
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fig['layout'][f'yaxis{3 + i}'].update(title=name)
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fig['layout']['xaxis']['rangeslider'].update(visible=False)
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# Common information
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@ -238,12 +304,13 @@ def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFra
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)
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fig.add_trace(bb_lower, 1, 1)
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fig.add_trace(bb_upper, 1, 1)
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if 'bb_upperband' in indicators1 and 'bb_lowerband' in indicators1:
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indicators1.remove('bb_upperband')
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indicators1.remove('bb_lowerband')
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if ('bb_upperband' in plot_config['main_plot']
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and 'bb_lowerband' in plot_config['main_plot']):
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del plot_config['main_plot']['bb_upperband']
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del plot_config['main_plot']['bb_lowerband']
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# Add indicators to main plot
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fig = add_indicators(fig=fig, row=1, indicators=indicators1, data=data)
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fig = add_indicators(fig=fig, row=1, indicators=plot_config['main_plot'], data=data)
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fig = plot_trades(fig, trades)
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@ -258,7 +325,10 @@ def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFra
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fig.add_trace(volume, 2, 1)
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# Add indicators to separate row
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fig = add_indicators(fig=fig, row=3, indicators=indicators2, data=data)
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for i, name in enumerate(plot_config['subplots']):
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fig = add_indicators(fig=fig, row=3 + i,
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indicators=plot_config['subplots'][name],
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data=data)
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return fig
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@ -359,8 +429,9 @@ def load_and_plot_trades(config: Dict[str, Any]):
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pair=pair,
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data=dataframe,
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trades=trades_pair,
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indicators1=config["indicators1"],
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indicators2=config["indicators2"],
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indicators1=config.get("indicators1", []),
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indicators2=config.get("indicators2", []),
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plot_config=strategy.plot_config if hasattr(strategy, 'plot_config') else {}
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)
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store_plot_file(fig, filename=generate_plot_filename(pair, config['ticker_interval']),
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@ -112,6 +112,9 @@ class IStrategy(ABC):
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dp: Optional[DataProvider] = None
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wallets: Optional[Wallets] = None
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# Definition of plot_config. See plotting documentation for more details.
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plot_config: Dict = {}
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def __init__(self, config: dict) -> None:
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self.config = config
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# Dict to determine if analysis is necessary
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@ -78,7 +78,7 @@ class {{ strategy }}(IStrategy):
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'buy': 'gtc',
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'sell': 'gtc'
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}
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{{ plot_config | indent(4) }}
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def informative_pairs(self):
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"""
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Define additional, informative pair/interval combinations to be cached from the exchange.
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@ -80,6 +80,22 @@ class SampleStrategy(IStrategy):
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'sell': 'gtc'
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}
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plot_config = {
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'main_plot': {
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'tema': {},
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'sar': {'color': 'white'},
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},
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'subplots': {
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"MACD": {
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'macd': {'color': 'blue'},
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'macdsignal': {'color': 'orange'},
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},
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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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def informative_pairs(self):
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"""
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Define additional, informative pair/interval combinations to be cached from the exchange.
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18
freqtrade/templates/subtemplates/plot_config_full.j2
Normal file
18
freqtrade/templates/subtemplates/plot_config_full.j2
Normal file
@ -0,0 +1,18 @@
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plot_config = {
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# Main plot indicators (Moving averages, ...)
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'main_plot': {
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'tema': {},
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'sar': {'color': 'white'},
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},
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'subplots': {
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# Subplots - each dict defines one additional plot
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"MACD": {
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'macd': {'color': 'blue'},
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'macdsignal': {'color': 'orange'},
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},
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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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@ -102,12 +102,14 @@ def deploy_new_strategy(strategy_name, strategy_path: Path, subtemplate: str):
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indicators = render_template(templatefile=f"subtemplates/indicators_{subtemplate}.j2",)
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buy_trend = render_template(templatefile=f"subtemplates/buy_trend_{subtemplate}.j2",)
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sell_trend = render_template(templatefile=f"subtemplates/sell_trend_{subtemplate}.j2",)
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plot_config = render_template(templatefile=f"subtemplates/plot_config_{subtemplate}.j2",)
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strategy_text = render_template(templatefile='base_strategy.py.j2',
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arguments={"strategy": strategy_name,
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"indicators": indicators,
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"buy_trend": buy_trend,
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"sell_trend": sell_trend,
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"plot_config": plot_config,
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})
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logger.info(f"Writing strategy to `{strategy_path}`.")
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@ -13,6 +13,7 @@ from freqtrade.data.btanalysis import create_cum_profit, load_backtest_data
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from freqtrade.exceptions import OperationalException
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from freqtrade.plot.plot_utils import start_plot_dataframe, start_plot_profit
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from freqtrade.plot.plotting import (add_indicators, add_profit,
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create_plotconfig,
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generate_candlestick_graph,
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generate_plot_filename,
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generate_profit_graph, init_plotscript,
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@ -66,8 +67,8 @@ def test_add_indicators(default_conf, testdatadir, caplog):
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data = history.load_pair_history(pair=pair, timeframe='1m',
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datadir=testdatadir, timerange=timerange)
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indicators1 = ["ema10"]
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indicators2 = ["macd"]
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indicators1 = {"ema10": {}}
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indicators2 = {"macd": {"color": "red"}}
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# Generate buy/sell signals and indicators
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strat = DefaultStrategy(default_conf)
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@ -86,9 +87,10 @@ def test_add_indicators(default_conf, testdatadir, caplog):
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macd = find_trace_in_fig_data(figure.data, "macd")
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assert isinstance(macd, go.Scatter)
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assert macd.yaxis == "y3"
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assert macd.line.color == "red"
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# No indicator found
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fig3 = add_indicators(fig=deepcopy(fig), row=3, indicators=['no_indicator'], data=data)
|
||||
fig3 = add_indicators(fig=deepcopy(fig), row=3, indicators={'no_indicator': {}}, data=data)
|
||||
assert fig == fig3
|
||||
assert log_has_re(r'Indicator "no_indicator" ignored\..*', caplog)
|
||||
|
||||
@ -108,18 +110,29 @@ def test_plot_trades(testdatadir, caplog):
|
||||
figure = fig1.layout.figure
|
||||
|
||||
# Check buys - color, should be in first graph, ...
|
||||
trade_buy = find_trace_in_fig_data(figure.data, "trade_buy")
|
||||
trade_buy = find_trace_in_fig_data(figure.data, 'Trade buy')
|
||||
assert isinstance(trade_buy, go.Scatter)
|
||||
assert trade_buy.yaxis == 'y'
|
||||
assert len(trades) == len(trade_buy.x)
|
||||
assert trade_buy.marker.color == 'green'
|
||||
assert trade_buy.marker.color == 'cyan'
|
||||
assert trade_buy.marker.symbol == 'circle-open'
|
||||
assert trade_buy.text[0] == '4.0%, roi, 15 min'
|
||||
|
||||
trade_sell = find_trace_in_fig_data(figure.data, "trade_sell")
|
||||
trade_sell = find_trace_in_fig_data(figure.data, 'Sell - Profit')
|
||||
assert isinstance(trade_sell, go.Scatter)
|
||||
assert trade_sell.yaxis == 'y'
|
||||
assert len(trades) == len(trade_sell.x)
|
||||
assert trade_sell.marker.color == 'red'
|
||||
assert trade_sell.text[0] == "4.0%, roi, 15 min"
|
||||
assert len(trades.loc[trades['profitperc'] > 0]) == len(trade_sell.x)
|
||||
assert trade_sell.marker.color == 'green'
|
||||
assert trade_sell.marker.symbol == 'square-open'
|
||||
assert trade_sell.text[0] == '4.0%, roi, 15 min'
|
||||
|
||||
trade_sell_loss = find_trace_in_fig_data(figure.data, 'Sell - Loss')
|
||||
assert isinstance(trade_sell_loss, go.Scatter)
|
||||
assert trade_sell_loss.yaxis == 'y'
|
||||
assert len(trades.loc[trades['profitperc'] <= 0]) == len(trade_sell_loss.x)
|
||||
assert trade_sell_loss.marker.color == 'red'
|
||||
assert trade_sell_loss.marker.symbol == 'square-open'
|
||||
assert trade_sell_loss.text[5] == '-10.4%, stop_loss, 720 min'
|
||||
|
||||
|
||||
def test_generate_candlestick_graph_no_signals_no_trades(default_conf, mocker, testdatadir, caplog):
|
||||
@ -371,3 +384,47 @@ def test_plot_profit(default_conf, mocker, testdatadir, caplog):
|
||||
|
||||
assert profit_mock.call_args_list[0][0][0] == default_conf['pairs']
|
||||
assert store_mock.call_args_list[0][1]['auto_open'] is True
|
||||
|
||||
|
||||
@pytest.mark.parametrize("ind1,ind2,plot_conf,exp", [
|
||||
# No indicators, use plot_conf
|
||||
([], [], {},
|
||||
{'main_plot': {'sma': {}, 'ema3': {}, 'ema5': {}},
|
||||
'subplots': {'Other': {'macd': {}, 'macdsignal': {}}}}),
|
||||
# use indicators
|
||||
(['sma', 'ema3'], ['macd'], {},
|
||||
{'main_plot': {'sma': {}, 'ema3': {}}, 'subplots': {'Other': {'macd': {}}}}),
|
||||
# only main_plot - adds empty subplots
|
||||
([], [], {'main_plot': {'sma': {}}},
|
||||
{'main_plot': {'sma': {}}, 'subplots': {}}),
|
||||
# Main and subplots
|
||||
([], [], {'main_plot': {'sma': {}}, 'subplots': {'RSI': {'rsi': {'color': 'red'}}}},
|
||||
{'main_plot': {'sma': {}}, 'subplots': {'RSI': {'rsi': {'color': 'red'}}}}),
|
||||
# no main_plot, adds empty main_plot
|
||||
([], [], {'subplots': {'RSI': {'rsi': {'color': 'red'}}}},
|
||||
{'main_plot': {}, 'subplots': {'RSI': {'rsi': {'color': 'red'}}}}),
|
||||
# indicator 1 / 2 should have prevelance
|
||||
(['sma', 'ema3'], ['macd'],
|
||||
{'main_plot': {'sma': {}}, 'subplots': {'RSI': {'rsi': {'color': 'red'}}}},
|
||||
{'main_plot': {'sma': {}, 'ema3': {}}, 'subplots': {'Other': {'macd': {}}}}
|
||||
),
|
||||
# indicator 1 - overrides plot_config main_plot
|
||||
(['sma', 'ema3'], [],
|
||||
{'main_plot': {'sma': {}}, 'subplots': {'RSI': {'rsi': {'color': 'red'}}}},
|
||||
{'main_plot': {'sma': {}, 'ema3': {}}, 'subplots': {'RSI': {'rsi': {'color': 'red'}}}}
|
||||
),
|
||||
# indicator 2 - overrides plot_config subplots
|
||||
([], ['macd', 'macd_signal'],
|
||||
{'main_plot': {'sma': {}}, 'subplots': {'RSI': {'rsi': {'color': 'red'}}}},
|
||||
{'main_plot': {'sma': {}}, 'subplots': {'Other': {'macd': {}, 'macd_signal': {}}}}
|
||||
),
|
||||
])
|
||||
def test_create_plotconfig(ind1, ind2, plot_conf, exp):
|
||||
|
||||
res = create_plotconfig(ind1, ind2, plot_conf)
|
||||
assert 'main_plot' in res
|
||||
assert 'subplots' in res
|
||||
assert isinstance(res['main_plot'], dict)
|
||||
assert isinstance(res['subplots'], dict)
|
||||
|
||||
assert res == exp
|
||||
|
||||
Loading…
Reference in New Issue
Block a user