added signal hypers notebooks

market_trade/notebooks/autogen/Signal hypers.py

@@ -0,0 +1,90 @@
+#!/usr/bin/env python
+# coding: utf-8
+
+# This notebook is designed for ray integrations for signals
+# 
+# lets load askbid candlesticks file.
+
+# In[20]:
+
+
+import market_trade.constants
+import market_trade.dataloader
+
+candlesticks_filepaths = [filepath for filepath in market_trade.constants.CANDLESTICK_DATASETS_PATH.iterdir()]
+candlesticks_filepath = candlesticks_filepaths[0]
+duka_interface = market_trade.dataloader.DukaMTInterface(candlesticks_filepath)
+duka_interface.bid_candlesticks
+
+
+# Let's test signal.
+
+# In[21]:
+
+
+import market_trade.signals.Signal1
+
+bid_candlesticks_df = duka_interface.bid_candlesticks[:10000]
+
+ind_params = {'MeanType': 'SMA', 'window': 5, 'valueType': 'low', 'kDev': 2}
+indEl1 = {
+    'df': bid_candlesticks_df,
+    'params': ind_params,
+    'needFig': False,
+    'showOnlyIndex': False,
+    'drawFig': True
+}
+signal_result = market_trade.signals.Signal1.SignalBollingerBands1({'BB': indEl1})
+signal_result.analiz
+
+
+# Now let's design ray trainable.
+
+# In[22]:
+
+
+def trainable(config):
+    ind_params = {'MeanType': 'SMA',
+                  'window': config['window'],
+                  'valueType': config['value_type'],
+                  'kDev': config['k_dev']}
+    indEl1 = {
+        'df': bid_candlesticks_df,
+        'params': ind_params,
+        'needFig': False,
+        'showOnlyIndex': False,
+        'drawFig': True
+    }
+    signal_result = market_trade.signals.Signal1.SignalBollingerBands1({'BB': indEl1})
+    tune.report(accuracy=signal_result.analiz["toch"])
+
+
+# Let's create config space.
+
+# In[23]:
+
+
+from ray import tune
+
+config = {
+    'window': tune.qrandint(5,100,5),
+    'value_type': tune.choice(['open', 'low', 'high', 'close']),
+    'k_dev': tune.uniform(1,4)
+}
+
+
+# Let's run ray tune
+
+# In[24]:
+
+
+analysis = tune.run(trainable, config=config, num_samples=100, mode='max', metric='accuracy')
+
+
+# Let's see who was the best
+
+# In[31]:
+
+
+analysis.best_config
+