DOC: WIP fix tutorial

docs/source/beginner-tutorial.rst

@@ -429,6 +429,10 @@ and allows us to plot the price of bitcoin. For example, we could easily
 examine now how our portfolio value changed over time compared to the
 bitcoin price.
 
+.. code-block:: python
+
+    %load_ext catalyst
+
 .. code-block:: python
 
     %pylab inline
@@ -484,7 +488,8 @@ a function we use in the ``handle_data()`` section:
 
 .. code-block:: python
 
-    %%catalyst --start 2016-1-1 --end 2017-9-30 -x bitfinex -o dma.pickle
+    %%catalyst --start 2016-4-1 --end 2017-9-30 -x bitfinex
+
     from catalyst.api import order, record, symbol, order_target
 
     def initialize(context):
@@ -492,16 +497,16 @@ a function we use in the ``handle_data()`` section:
        context.asset = symbol('btc_usd')
 
     def handle_data(context, data):
-       # Skip first 300 days to get full windows
+       # Skip first 150 days to get full windows
        context.i += 1
-       if context.i < 300:
+       if context.i < 150:
            return
 
        # Compute averages
        # data.history() has to be called with the same params
        # from above and returns a pandas dataframe.
-       short_mavg = data.history(context.asset, 'price', bar_count=100, frequency="1d").mean()
-       long_mavg = data.history(context.asset, 'price', bar_count=300, frequency="1d").mean()
+       short_mavg = data.history(context.asset, 'price', bar_count=50, frequency="1d").mean()
+       long_mavg = data.history(context.asset, 'price', bar_count=150, frequency="1d").mean()
 
        # Trading logic
        if short_mavg > long_mavg:
@@ -518,7 +523,7 @@ a function we use in the ``handle_data()`` section:
 
     def analyze(context, perf):
        import matplotlib.pyplot as plt
-       fig = plt.figure()
+       fig = plt.figure(figsize=(12,12))
        ax1 = fig.add_subplot(211)
        perf.portfolio_value.plot(ax=ax1)
        ax1.set_ylabel('portfolio value in $')