From ea0ffbae736950c585810ba9701c69d1dd967610 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Fri, 29 Jan 2021 19:06:46 +0100
Subject: [PATCH] use profit_ratio in calculate_cum_profit

---
 freqtrade/data/btanalysis.py  | 12 ++++++------
 tests/data/test_btanalysis.py |  2 +-
 tests/test_plotting.py        |  4 ++--
 3 files changed, 9 insertions(+), 9 deletions(-)

diff --git a/freqtrade/data/btanalysis.py b/freqtrade/data/btanalysis.py
index c004a4d23..b7c8529ac 100644
--- a/freqtrade/data/btanalysis.py
+++ b/freqtrade/data/btanalysis.py
@@ -337,7 +337,7 @@ def create_cum_profit(df: pd.DataFrame, trades: pd.DataFrame, col_name: str,
     """
     Adds a column `col_name` with the cumulative profit for the given trades array.
     :param df: DataFrame with date index
-    :param trades: DataFrame containing trades (requires columns close_date and profit_percent)
+    :param trades: DataFrame containing trades (requires columns close_date and profit_ratio)
     :param col_name: Column name that will be assigned the results
     :param timeframe: Timeframe used during the operations
     :return: Returns df with one additional column, col_name, containing the cumulative profit.
@@ -349,8 +349,8 @@ def create_cum_profit(df: pd.DataFrame, trades: pd.DataFrame, col_name: str,
     timeframe_minutes = timeframe_to_minutes(timeframe)
     # Resample to timeframe to make sure trades match candles
     _trades_sum = trades.resample(f'{timeframe_minutes}min', on='close_date'
-                                  )[['profit_percent']].sum()
-    df.loc[:, col_name] = _trades_sum['profit_percent'].cumsum()
+                                  )[['profit_ratio']].sum()
+    df.loc[:, col_name] = _trades_sum['profit_ratio'].cumsum()
     # Set first value to 0
     df.loc[df.iloc[0].name, col_name] = 0
     # FFill to get continuous
@@ -359,13 +359,13 @@ def create_cum_profit(df: pd.DataFrame, trades: pd.DataFrame, col_name: str,
 
 
 def calculate_max_drawdown(trades: pd.DataFrame, *, date_col: str = 'close_date',
-                           value_col: str = 'profit_percent'
+                           value_col: str = 'profit_ratio'
                            ) -> Tuple[float, pd.Timestamp, pd.Timestamp]:
     """
     Calculate max drawdown and the corresponding close dates
-    :param trades: DataFrame containing trades (requires columns close_date and profit_percent)
+    :param trades: DataFrame containing trades (requires columns close_date and profit_ratio)
     :param date_col: Column in DataFrame to use for dates (defaults to 'close_date')
-    :param value_col: Column in DataFrame to use for values (defaults to 'profit_percent')
+    :param value_col: Column in DataFrame to use for values (defaults to 'profit_ratio')
     :return: Tuple (float, highdate, lowdate) with absolute max drawdown, high and low time
     :raise: ValueError if trade-dataframe was found empty.
     """
diff --git a/tests/data/test_btanalysis.py b/tests/data/test_btanalysis.py
index a26ada3ba..96ac6f63c 100644
--- a/tests/data/test_btanalysis.py
+++ b/tests/data/test_btanalysis.py
@@ -142,7 +142,7 @@ def test_extract_trades_of_period(testdatadir):
 
     trades = DataFrame(
         {'pair': [pair, pair, pair, pair],
-         'profit_percent': [0.0, 0.1, -0.2, -0.5],
+         'profit_ratio': [0.0, 0.1, -0.2, -0.5],
          'profit_abs': [0.0, 1, -2, -5],
          'open_date': to_datetime([Arrow(2017, 11, 13, 15, 40, 0).datetime,
                                    Arrow(2017, 11, 14, 9, 41, 0).datetime,
diff --git a/tests/test_plotting.py b/tests/test_plotting.py
index 96c9868a9..4c8ac4816 100644
--- a/tests/test_plotting.py
+++ b/tests/test_plotting.py
@@ -179,7 +179,7 @@ def test_plot_trades(testdatadir, caplog):
     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.loc[trades['profit_percent'] > 0]) == len(trade_sell.x)
+    assert len(trades.loc[trades['profit_ratio'] > 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'
@@ -187,7 +187,7 @@ def test_plot_trades(testdatadir, caplog):
     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['profit_percent'] <= 0]) == len(trade_sell_loss.x)
+    assert len(trades.loc[trades['profit_ratio'] <= 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'