unit tests for optimize.hyperopt

freqtrade/optimize/hyperopt.py

@@ -25,12 +25,10 @@ logging.getLogger('hyperopt.tpe').setLevel(logging.WARNING)
 
 logger = logging.getLogger(__name__)
 
-
 # set TARGET_TRADES to suit your number concurrent trades so its realistic to 20days of data
 TARGET_TRADES = 1100
 TOTAL_TRIES = None
 _CURRENT_TRIES = 0
-
 CURRENT_BEST_LOSS = 100
 
 # this is expexted avg profit * expected trade count
@@ -111,6 +109,13 @@ def log_results(results):
         sys.stdout.flush()
 
 
+def calculate_loss(total_profit: float, trade_count: int):
+    """ objective function, returns smaller number for more optimal results """
+    trade_loss = 1 - 0.35 * exp(-(trade_count - TARGET_TRADES) ** 2 / 10 ** 5.2)
+    profit_loss = max(0, 1 - total_profit / EXPECTED_MAX_PROFIT)
+    return trade_loss + profit_loss
+
+
 def optimizer(params):
     global _CURRENT_TRIES
 
@@ -129,9 +134,8 @@ def optimizer(params):
             'loss': float('inf')
         }
 
-    trade_loss = 1 - 0.35 * exp(-(trade_count - TARGET_TRADES) ** 2 / 10 ** 5.2)
+    loss = calculate_loss(total_profit, trade_count)
-    profit_loss = max(0, 1 - total_profit / EXPECTED_MAX_PROFIT)
+
-    loss = trade_loss + profit_loss
     _CURRENT_TRIES += 1
 
     log_results({

freqtrade/tests/optimize/test_hyperopt.py

@@ -1,6 +1,79 @@
-# pragma pylint: disable=missing-docstring,W0212
+# pragma pylint: disable=missing-docstring,W0212,C0103
+
+from freqtrade.optimize.hyperopt import calculate_loss, TARGET_TRADES, EXPECTED_MAX_PROFIT, start, \
+    log_results
 
 
-def test_optimizer(default_conf, mocker):
+def test_loss_calculation_prefer_correct_trade_count():
-    # TODO: implement test
+    correct = calculate_loss(1, TARGET_TRADES)
-    pass
+    over = calculate_loss(1, TARGET_TRADES + 100)
+    under = calculate_loss(1, TARGET_TRADES - 100)
+    assert over > correct
+    assert under > correct
+
+
+def test_loss_calculation_has_limited_profit():
+    correct = calculate_loss(EXPECTED_MAX_PROFIT, TARGET_TRADES)
+    over = calculate_loss(EXPECTED_MAX_PROFIT * 2, TARGET_TRADES)
+    under = calculate_loss(EXPECTED_MAX_PROFIT / 2, TARGET_TRADES)
+    assert over == correct
+    assert under > correct
+
+
+def create_trials(mocker):
+    return mocker.Mock(
+        results=[{
+            'loss': 1,
+            'result': 'foo'
+        }]
+    )
+
+
+def test_start_calls_fmin(mocker):
+    mocker.patch('freqtrade.optimize.hyperopt.Trials', return_value=create_trials(mocker))
+    mocker.patch('freqtrade.optimize.preprocess')
+    mocker.patch('freqtrade.optimize.load_data')
+    mock_fmin = mocker.patch('freqtrade.optimize.hyperopt.fmin', return_value={})
+
+    args = mocker.Mock(epochs=1, config='config.json.example', mongodb=False)
+    start(args)
+
+    mock_fmin.assert_called_once()
+
+
+def test_start_uses_mongotrials(mocker):
+    mock_mongotrials = mocker.patch('freqtrade.optimize.hyperopt.MongoTrials',
+                                    return_value=create_trials(mocker))
+    mocker.patch('freqtrade.optimize.preprocess')
+    mocker.patch('freqtrade.optimize.load_data')
+    mocker.patch('freqtrade.optimize.hyperopt.fmin', return_value={})
+
+    args = mocker.Mock(epochs=1, config='config.json.example', mongodb=True)
+    start(args)
+
+    mock_mongotrials.assert_called_once()
+
+
+def test_log_results_if_loss_improves(mocker):
+    logger = mocker.patch('freqtrade.optimize.hyperopt.logger.info')
+    global CURRENT_BEST_LOSS
+    CURRENT_BEST_LOSS = 2
+    log_results({
+        'loss': 1,
+        'current_tries': 1,
+        'total_tries': 2,
+        'result': 'foo'
+    })
+
+    logger.assert_called_once()
+
+
+def test_no_log_if_loss_does_not_improve(mocker):
+    logger = mocker.patch('freqtrade.optimize.hyperopt.logger.info')
+    global CURRENT_BEST_LOSS
+    CURRENT_BEST_LOSS = 2
+    log_results({
+        'loss': 3,
+    })
+
+    assert not logger.called