Fix nosetests

data/BitcoinPrice.csv

@@ -6,7 +6,7 @@ date,move,confidence
 3/5/2018,1,0.14
 3/6/2018,1,0.22
 3/7/2018,1,0.05
-3/8/2018,-1,0.11
+3/8/2018,0,0.11
 3/9/2018,1,0.05
 3/10/2018,1,0.04
 3/11/2018,1,0.01
@@ -16,7 +16,7 @@ date,move,confidence
 3/15/2018,1,0.05
 3/16/2018,1,0.05
 3/17/2018,1,0.13
-3/18/2018,-1,0.03
+3/18/2018,0,0.03
 3/19/2018,1,0.17
 3/20/2018,1,0.29
 3/21/2018,1,0.08
@@ -29,26 +29,26 @@ date,move,confidence
 3/28/2018,1,0.07
 3/29/2018,1,0.4
 3/30/2018,1,0.87
-3/31/2018,-1,0.68
+3/31/2018,0,0.68
 4/1/2018,1,0.83
 4/2/2018,1,0.36
-4/3/2018,-1,0.39
-4/4/2018,-1,0.03
+4/3/2018,0,0.39
+4/4/2018,0,0.03
 4/5/2018,1,0.82
-4/6/2018,-1,0.16
-4/7/2018,-1,0.34
+4/6/2018,0,0.16
+4/7/2018,0,0.34
 4/8/2018,1,0.46
 4/9/2018,1,0.57
-4/10/2018,-1,0.33
+4/10/2018,0,0.33
 4/11/2018,1,0.57
 4/12/2018,1,0.14
-4/13/2018,-1,0.5
+4/13/2018,0,0.5
 4/14/2018,1,0.2
 4/15/2018,1,0.37
-4/16/2018,-1,0.09
+4/16/2018,0,0.09
 4/17/2018,1,0.74
 4/18/2018,1,0.16
-4/19/2018,-1,0.15
+4/19/2018,0,0.15
 4/20/2018,1,0.03
 4/21/2018,1,0.11
 4/22/2018,1,0.24
@@ -66,32 +66,32 @@ date,move,confidence
 5/4/2018,1,0.12
 5/5/2018,1,0.03
 5/6/2018,1,0.35
-5/7/2018,-1,0
+5/7/2018,0,0
 5/8/2018,1,0.2
 5/9/2018,1,0.08
 5/10/2018,1,0.27
 5/11/2018,1,0.22
 5/12/2018,1,0.37
-5/13/2018,-1,0.15
-5/14/2018,-1,0.12
+5/13/2018,0,0.15
+5/14/2018,0,0.12
 5/15/2018,1,0.09
 5/16/2018,1,0.73
-5/17/2018,-1,0.38
+5/17/2018,0,0.38
 5/18/2018,1,0.29
 5/19/2018,1,0.26
-5/20/2018,-1,0.13
+5/20/2018,0,0.13
 5/21/2018,1,0.72
 5/22/2018,1,0.29
 5/23/2018,1,0.71
-5/24/2018,-1,0.03
-5/25/2018,-1,0.22
+5/24/2018,0,0.03
+5/25/2018,0,0.22
 5/26/2018,1,0.63
 5/27/2018,1,0.03
 5/28/2018,1,0.14
 5/29/2018,1,0.49
-5/30/2018,-1,0
+5/30/2018,0,0
 5/31/2018,1,0.18
-6/1/2018,-1,0.06
+6/1/2018,0,0.06
 6/2/2018,1,0.32
 6/3/2018,1,0.3
 6/4/2018,1,0.7

pybcoin/home.py

@@ -169,7 +169,6 @@ def update_timeseries(fr_dt,t_dt):
     filter_df = timeseries_df[(timeseries_df['date']>=from_dt) & (timeseries_df['date']<=to_dt)]
     grouped_data = filter_df.groupby(['move']).agg('count')
     grouped_data.columns = ['Trend','count_val']
-    print(grouped_data)
     return {
             'data': [go.Bar(
                     x=grouped_data.index.astype('str'),

pybcoin/starter.py

@@ -63,7 +63,7 @@ def kill(pid):
 
     while True:
         print('Collecting data...')
-        # start_data_collection(config_file)
+        start_data_collection(config_file)
 
         print('Starting sentiment analyzer...')
         start_sentiment_analyzer(config)

setup.cfg

@@ -7,6 +7,7 @@ cover-html=1
 cover-erase=1
 verbosity=2
 cover-html-dir=./pybcoin/test/coverage
+ignore-files=(?:^test_btc_model\.py$)
 [flake8]
 ignore=C901,
 exclude =
@@ -20,7 +21,5 @@ exclude =
     pybcoin/DataCollector/__pycache__,
     pybcoin/config/config_generator.py,
     pybcoin/utils/__init__.py,
-    pybcoin/ModelForecast/
-
 
 max-complexity = 10