Minor changes

.gitignore

@@ -14,7 +14,7 @@ __pycache__/
 env/
 build/
 develop-eggs/
-dist/
+dist*/
 downloads/
 eggs/
 .eggs/

finmarketpy/backtest/backtestengine.py

@@ -924,6 +924,7 @@ def signal(self):
 import abc
 import pandas
 import datetime
+import copy
 
 from chartpy import Chart, Style, ChartConstants
 
@@ -946,6 +947,7 @@ class TradingModel(object):
     DEFAULT_PLOT_ENGINE = ChartConstants().chartfactory_default_engine
     SCALE_FACTOR = ChartConstants().chartfactory_scale_factor
     CHART_SOURCE = ChartConstants().chartfactory_source
+    CHART_STYLE = Style()
 
     DUMP_CSV = ''
     DUMP_PATH = datetime.date.today().strftime("%Y%m%d") + ' '
@@ -1865,7 +1867,7 @@ def _strip_dataframe(self, data_frame, strip):
         return data_frame
 
     def _create_style(self, title, file_add, reduce_plot=True):
-        style = Style()
+        style = copy.deepcopy(self.CHART_STYLE)
 
         if self.SHOW_TITLES:
             style.title = self.FINAL_STRATEGY + " " + title

finmarketpy/economics/eventstudy.py

@@ -64,7 +64,7 @@ def get_economic_event_ret_over_custom_event_day(self, data_frame_in, event_date
 
     def get_intraday_moves_over_custom_event(self, data_frame_rets, ef_time_frame, vol=False,
                                              minute_start = 5, mins = 3 * 60, min_offset = 0 , create_index = False,
-                                             resample = False, freq = 'minutes'):
+                                             resample = False, freq = 'minutes', cumsum = True):
 
         filter = Filter()
 
@@ -126,7 +126,7 @@ def get_intraday_moves_over_custom_event(self, data_frame_rets, ef_time_frame, v
             if vol is True:
                 # annualise (if vol)
                 data_frame = data_frame.rolling(center=False,window=5).std() * math.sqrt(ann_factor)
-            else:
+            elif cumsum:
                 data_frame = data_frame.cumsum()
 
         return data_frame

finmarketpy_examples/tradingmodelfxtrend_example.py

@@ -26,6 +26,8 @@
 from finmarketpy.backtest import TradingModel, BacktestRequest
 from finmarketpy.economics import TechIndicator
 
+from chartpy import Style
+
 class TradingModelFXTrend_Example(TradingModel):
 
     def __init__(self):
@@ -37,6 +39,7 @@ def __init__(self):
         self.FINAL_STRATEGY = 'FX trend'
         self.SCALE_FACTOR = 1
         self.DEFAULT_PLOT_ENGINE = 'matplotlib'
+        # self.CHART_STYLE = Style(plotly_plot_mode='offline_jupyter')
 
         self.br = self.load_parameters()
         return
@@ -225,7 +228,7 @@ def construct_strategy_benchmark(self):
 
         # now examine sensitivity to different transaction costs
         tc = [0, 0.25, 0.5, 0.75, 1, 1.25, 1.5, 1.75, 2.0]
-        ta.run_tc_shock(strategy, tc = tc)
+        ta.run_tc_shock(strategy, tc=tc)
 
         # how does P&L change on day of month
         ta.run_day_of_month_analysis(strategy)

setup.py

@@ -1,11 +1,15 @@
 from setuptools import setup, find_packages
 
+long_description = """finmarketpy is a Python based library that enables you to analyze market data and also to backtest 
+trading strategies using a simple to use API, which has prebuilt templates for you to define backtest."""
+
 setup(name='finmarketpy',
-      version='0.11',
-      description='Trading Backtest library',
+      version='0.11.1',
+      description='finmarketpy is a Python based library for backtesting trading strategies',
       author='Saeed Amen',
       author_email='saeed@cuemacro.com',
       license='Apache 2.0',
+      long_description=long_description,
       keywords = ['trading', 'markets', 'currencies', 'pandas', 'data', 'Bloomberg', 'tick', 'stocks', 'equities'],
       url = 'https://github.com/cuemacro/finmarketpy',
       packages = find_packages(),