From e2356c856d24e955f9eae419042417ad0e3eca54 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Sat, 2 Oct 2021 15:23:09 +0200
Subject: [PATCH] Improve outstanding balance

---
 freqtrade/data/btanalysis.py        |  6 ++---
 tests/optimize/test_hyperoptloss.py | 34 ++++++++++++++++++++---------
 2 files changed, 27 insertions(+), 13 deletions(-)

diff --git a/freqtrade/data/btanalysis.py b/freqtrade/data/btanalysis.py
index 79b0c2801..8ba61aeed 100644
--- a/freqtrade/data/btanalysis.py
+++ b/freqtrade/data/btanalysis.py
@@ -446,13 +446,13 @@ def calculate_outstanding_balance(results: pd.DataFrame, timeframe: str,
 
     from freqtrade.exchange import timeframe_to_minutes
     timeframe_min = timeframe_to_minutes(timeframe)
-    df3 = expand_trades_over_period(results, timeframe, timeframe_min)
+    trades_over_period = expand_trades_over_period(results, timeframe, timeframe_min)
 
     values = {}
     # Iterate over every pair
     for pair in hloc:
         ohlc = hloc[pair].set_index('date')
-        df_pair = df3.loc[df3['pair'] == pair]
+        df_pair = trades_over_period.loc[trades_over_period['pair'] == pair]
         # filter on pair and convert dateindex to utc
         # * Temporary workaround
         df_pair.index = pd.to_datetime(df_pair.index, utc=True)
@@ -466,6 +466,6 @@ def calculate_outstanding_balance(results: pd.DataFrame, timeframe: str,
         values[pair] = df4
 
     balance = pd.concat([df[['value']] for k, df in values.items()])
-    # TODO: Does this resample make sense ... ?
+    # Combine multi-pair balances
     balance = balance.resample(f"{timeframe_min}min").agg({"value": sum})
     return balance
diff --git a/tests/optimize/test_hyperoptloss.py b/tests/optimize/test_hyperoptloss.py
index 923e3fc32..d35b45e12 100644
--- a/tests/optimize/test_hyperoptloss.py
+++ b/tests/optimize/test_hyperoptloss.py
@@ -6,6 +6,7 @@ import pytest
 from freqtrade.exceptions import OperationalException
 from freqtrade.optimize.hyperopt_loss_short_trade_dur import ShortTradeDurHyperOptLoss
 from freqtrade.resolvers.hyperopt_resolver import HyperOptLossResolver
+from tests.strategy.test_strategy_helpers import generate_test_data
 
 
 def test_hyperoptlossresolver_noname(default_conf):
@@ -78,14 +79,16 @@ def test_loss_calculation_has_limited_profit(hyperopt_conf, hyperopt_results) ->
     assert under > correct
 
 
-@pytest.mark.parametrize('lossfunction', [
-    "OnlyProfitHyperOptLoss",
-    "SortinoHyperOptLoss",
-    "SortinoHyperOptLossDaily",
-    "SharpeHyperOptLoss",
-    "SharpeHyperOptLossDaily",
+@pytest.mark.parametrize('lossfunction, needsdata', [
+    ("OnlyProfitHyperOptLoss", False),
+    ("SortinoHyperOptLoss", False),
+    ("SortinoHyperOptLossDaily", False),
+    ("SharpeHyperOptLoss", False),
+    ("SharpeHyperOptLossDaily", False),
+    ("SortinoLossBalance", True),
 ])
-def test_loss_functions_better_profits(default_conf, hyperopt_results, lossfunction) -> None:
+def test_loss_functions_better_profits(default_conf, hyperopt_results,
+                                       lossfunction, needsdata) -> None:
     results_over = hyperopt_results.copy()
     results_over['profit_abs'] = hyperopt_results['profit_abs'] * 2
     results_over['profit_ratio'] = hyperopt_results['profit_ratio'] * 2
@@ -93,13 +96,24 @@ def test_loss_functions_better_profits(default_conf, hyperopt_results, lossfunct
     results_under['profit_abs'] = hyperopt_results['profit_abs'] / 2
     results_under['profit_ratio'] = hyperopt_results['profit_ratio'] / 2
 
+    if needsdata:
+        data = {'ETH/USDT': generate_test_data('5m', 1200, start='2019-01-01')}
+    else:
+        data = {}
+
     default_conf.update({'hyperopt_loss': lossfunction})
     hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
     correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
-                                        datetime(2019, 1, 1), datetime(2019, 5, 1))
+                                        datetime(2019, 1, 1), datetime(2019, 5, 1),
+                                        config=default_conf, processed=data,
+                                        )
     over = hl.hyperopt_loss_function(results_over, len(results_over),
-                                     datetime(2019, 1, 1), datetime(2019, 5, 1))
+                                     datetime(2019, 1, 1), datetime(2019, 5, 1),
+                                     config=default_conf, processed=data,
+                                     )
     under = hl.hyperopt_loss_function(results_under, len(results_under),
-                                      datetime(2019, 1, 1), datetime(2019, 5, 1))
+                                      datetime(2019, 1, 1), datetime(2019, 5, 1),
+                                      config=default_conf, processed=data,
+                                      )
     assert over < correct
     assert under > correct