finished converter

market_trade/notebooks/autogen/Make unified candlesticks data import.py

@@ -3,7 +3,7 @@
 
 # Let's try to get filepath of any candlesticks file.
 
-# In[2]:
+# In[1]:
 
 
 import market_trade.constants
@@ -15,7 +15,7 @@ candlesticks_filepath
 
 # Let's import that file to pandas
 
-# In[18]:
+# In[2]:
 
 
 import pandas as pd
@@ -24,13 +24,22 @@ import pandas as pd
 candlesticks_df = pd.read_csv(candlesticks_filepath,index_col=0, header=[0,1], parse_dates=True)
 candlesticks_df['date'] = candlesticks_df.index 
 candlesticks_df.reset_index(inplace=True, drop=True)
-ask_candlesticks_df = candlesticks_df['ask']
+ask_candlesticks_df = candlesticks_df['ask'].copy()
 ask_candlesticks_df.head()
 
 
-# Everything imported beatifully.
+# Everything imported beatifully, let's attach the date to it 
 
-# In[17]:
+# In[3]:
+
+
+ask_candlesticks_df['date'] = candlesticks_df['date']
+ask_candlesticks_df.head()
+
+
+# Let's test it
+
+# In[4]:
 
 
 """
@@ -43,11 +52,115 @@ ind_params = {'MeanType': 'SMA', 'window': 5, 'valueType': 'low', 'kDev': 2}
 # df_candle[:3000],ind_params,True,False,True
 # window 5..100 (5) | valueType: 'open', 'low' | 'kdev' : 1..4 (0.1)
 indEl1 = {
-    'df': ask_candlesticks_df[:3000],
+    'df': ask_candlesticks_df,
     'params': ind_params,
     'needFig': False,
     'showOnlyIndex': False,
     'drawFig': True
 }
 a = market_trade.signals.Signal1.SignalBollingerBands1({'BB': indEl1})
+a.analiz
+
+
+# Let's test that i didn't broke the file. Let's import test file, and compare results.
+# 
+# Importing
+
+# In[5]:
+
+
+test_candlesticks = pd.read_csv(market_trade.constants.TEST_CANDLESTICKS_PATH)
+test_candlesticks['date'] = test_candlesticks['timestamp']
+test_candlesticks.drop(['timestamp'], axis=1, inplace=True)
+test_candlesticks.head()
+
+
+# Comparing results
+
+# In[6]:
+
+
+"""
+expected results
+{'chstota': 0.3555926544240401,
+ 'zeroNum %': 0.5963272120200334,
+ 't %': 0.37963272120200336,
+ 'f %': 0.024040066777963272,
+ 'toch': 0.9404466501240695}
+"""
+
+import market_trade.signals.Signal1
+
+
+ind_params = {'MeanType': 'SMA', 'window': 5, 'valueType': 'low', 'kDev': 2}
+# df_candle[:3000],ind_params,True,False,True
+# window 5..100 (5) | valueType: 'open', 'low' | 'kdev' : 1..4 (0.1)
+indEl1 = {
+    'df': test_candlesticks[:3000],
+    'params': ind_params,
+    'needFig': False,
+    'showOnlyIndex': False,
+    'drawFig': True
+}
+a = market_trade.signals.Signal1.SignalBollingerBands1({'BB': indEl1})
+a.analiz
+
+
+# Nice! And lets try full file
+
+# In[16]:
+
+
+ind_params = {'MeanType': 'SMA', 'window': 5, 'valueType': 'low', 'kDev': 2}
+# df_candle[:3000],ind_params,True,False,True
+# window 5..100 (5) | valueType: 'open', 'low' | 'kdev' : 1..4 (0.1)
+indEl1 = {
+    'df': test_candlesticks[:10000],
+    'params': ind_params,
+    'needFig': False,
+    'showOnlyIndex': False,
+    'drawFig': True
+}
+a = market_trade.signals.Signal1.SignalBollingerBands1({'BB': indEl1})
+a.analiz
+
+
+# Let's test our file loading
+
+# In[8]:
+
+
+candlesticks_filepaths
+
+
+# Let's choose EURUSD candletsicks
+
+# In[11]:
+
+
+candlesticks_filepath = candlesticks_filepaths[5]
+
+candlesticks_df = pd.read_csv(candlesticks_filepath,index_col=0, header=[0,1], parse_dates=True)
+candlesticks_df['date'] = candlesticks_df.index 
+candlesticks_df.reset_index(inplace=True, drop=True)
+ask_candlesticks_df = candlesticks_df['ask'].copy()
+ask_candlesticks_df['date'] = candlesticks_df['date']
+ask_candlesticks_df.head()
+
+
+# Let's test
+
+# In[15]:
+
+
+ind_params = {'MeanType': 'SMA', 'window': 5, 'valueType': 'low', 'kDev': 2}
+indEl1 = {
+    'df': ask_candlesticks_df[:10000],
+    'params': ind_params,
+    'needFig': False,
+    'showOnlyIndex': False,
+    'drawFig': True
+}
+a = market_trade.signals.Signal1.SignalBollingerBands1({'BB': indEl1})
+a.analiz