Add trade parallelism plot

closes #6142

docs/plotting.md

@@ -283,6 +283,7 @@ The `plot-profit` subcommand shows an interactive graph with three plots:
 * The summarized profit made by backtesting.
 Note that this is not the real-world profit, but more of an estimate.
 * Profit for each individual pair.
+* Parallelism of trades.
 
 The first graph is good to get a grip of how the overall market progresses.
 
@@ -292,6 +293,8 @@ This graph will also highlight the start (and end) of the Max drawdown period.
 
 The third graph can be useful to spot outliers, events in pairs that cause profit spikes.
 
+The forth graph can help you analyze trade parallelism, showing how often max_open_trades have been maxed out.
+
 Possible options for the `freqtrade plot-profit` subcommand:
 
 ```

freqtrade/plot/plotting.py

@@ -5,8 +5,9 @@ from typing import Any, Dict, List
 import pandas as pd
 
 from freqtrade.configuration import TimeRange
-from freqtrade.data.btanalysis import (calculate_max_drawdown, combine_dataframes_with_mean,
+from freqtrade.data.btanalysis import (analyze_trade_parallelism, calculate_max_drawdown,
-                                       create_cum_profit, extract_trades_of_period, load_trades)
+                                       combine_dataframes_with_mean, create_cum_profit,
+                                       extract_trades_of_period, load_trades)
 from freqtrade.data.converter import trim_dataframe
 from freqtrade.data.dataprovider import DataProvider
 from freqtrade.data.history import get_timerange, load_data
@@ -185,6 +186,24 @@ def add_max_drawdown(fig, row, trades: pd.DataFrame, df_comb: pd.DataFrame,
     return fig
 
 
+def add_parallelism(fig, row, trades: pd.DataFrame, timeframe: str) -> make_subplots:
+    """
+    Add Chart showing trade parallelism
+    """
+    try:
+        result = analyze_trade_parallelism(trades, timeframe)
+
+        drawdown = go.Bar(
+            x=result.index,
+            y=result['open_trades'],
+            name="Parallel trades",
+        )
+        fig.add_trace(drawdown, row, 1)
+    except ValueError:
+        logger.warning("No trades found - not plotting Parallelism.")
+    return fig
+
+
 def plot_trades(fig, trades: pd.DataFrame) -> make_subplots:
     """
     Add trades to "fig"
@@ -482,20 +501,27 @@ def generate_profit_graph(pairs: str, data: Dict[str, pd.DataFrame],
         name='Avg close price',
     )
 
-    fig = make_subplots(rows=3, cols=1, shared_xaxes=True,
+    fig = make_subplots(rows=4, cols=1, shared_xaxes=True,
-                        row_width=[1, 1, 1],
+                        row_width=[1, 1, 1, 1],
                         vertical_spacing=0.05,
-                        subplot_titles=["AVG Close Price", "Combined Profit", "Profit per pair"])
+                        subplot_titles=[
+                            "AVG Close Price",
+                            "Combined Profit",
+                            "Profit per pair",
+                            "Parallelism"
+                            ])
     fig['layout'].update(title="Freqtrade Profit plot")
     fig['layout']['yaxis1'].update(title='Price')
     fig['layout']['yaxis2'].update(title=f'Profit {stake_currency}')
     fig['layout']['yaxis3'].update(title=f'Profit {stake_currency}')
+    fig['layout']['yaxis4'].update(title='Trade count')
     fig['layout']['xaxis']['rangeslider'].update(visible=False)
     fig.update_layout(modebar_add=["v1hovermode", "toggleSpikeLines"])
 
     fig.add_trace(avgclose, 1, 1)
     fig = add_profit(fig, 2, df_comb, 'cum_profit', 'Profit')
     fig = add_max_drawdown(fig, 2, trades, df_comb, timeframe)
+    fig = add_parallelism(fig, 4, trades, timeframe)
 
     for pair in pairs:
         profit_col = f'cum_profit_{pair}'

tests/test_plotting.py

@@ -336,15 +336,17 @@ def test_generate_profit_graph(testdatadir):
     assert fig.layout.yaxis3.title.text == "Profit BTC"
 
     figure = fig.layout.figure
-    assert len(figure.data) == 5
+    assert len(figure.data) == 6
 
     avgclose = find_trace_in_fig_data(figure.data, "Avg close price")
     assert isinstance(avgclose, go.Scatter)
 
     profit = find_trace_in_fig_data(figure.data, "Profit")
     assert isinstance(profit, go.Scatter)
-    profit = find_trace_in_fig_data(figure.data, "Max drawdown 10.45%")
+    drawdown = find_trace_in_fig_data(figure.data, "Max drawdown 10.45%")
-    assert isinstance(profit, go.Scatter)
+    assert isinstance(drawdown, go.Scatter)
+    parallel = find_trace_in_fig_data(figure.data, "Parallel trades")
+    assert isinstance(parallel, go.Bar)
 
     for pair in pairs:
         profit_pair = find_trace_in_fig_data(figure.data, f"Profit {pair}")