Merge pull request #262 from quantopian/refactor_timeseries.py

Refactor timeseries.py

Author: twiecki

pyfolio/plotting.py

@@ -13,6 +13,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 from __future__ import division
+from collections import OrderedDict
 
 import pandas as pd
 import numpy as np
@@ -510,13 +511,13 @@ def show_perf_stats(returns, factor_returns, live_start_date=None):
     perf_stats = np.round(timeseries.perf_stats(
         returns_backtest,
         factor_returns=factor_returns), 2)
-    perf_stats.columns = ['Backtest']
 
     if live_start_date is not None:
-        perf_stats = perf_stats.join(perf_stats_live,
-                                     how='inner')
-        perf_stats = perf_stats.join(perf_stats_all,
-                                     how='inner')
+        perf_stats = pd.DataFrame(OrderedDict([
+            ('Backtest', perf_stats),
+            ('Out of sample', perf_stats_live),
+            ('All history', perf_stats_all),
+        ]))
 
     print(perf_stats)
 

pyfolio/tears.py

@@ -263,11 +263,6 @@ def create_returns_tear_sheet(returns, live_start_date=None,
     ax_monthly_dist = plt.subplot(gs[8, 2])
     ax_return_quantiles = plt.subplot(gs[9, :])
 
-    if live_start_date is not None:
-        ax_daily_similarity_scale = plt.subplot(gs[10, 0])
-        ax_daily_similarity_no_var = plt.subplot(gs[10, 1])
-        ax_daily_similarity_no_var_no_mean = plt.subplot(gs[10, 2])
-
     plotting.plot_rolling_returns(
         returns,
         factor_returns=benchmark_rets,
@@ -322,29 +317,6 @@ def create_returns_tear_sheet(returns, live_start_date=None,
         df_monthly,
         ax=ax_return_quantiles)
 
-    if live_start_date is not None:
-        returns_backtest = returns[returns.index < live_start_date]
-        returns_live = returns[returns.index > live_start_date]
-
-        plotting.plot_daily_returns_similarity(
-            returns_backtest,
-            returns_live,
-            title='Daily Returns Similarity',
-            ax=ax_daily_similarity_scale)
-        plotting.plot_daily_returns_similarity(
-            returns_backtest,
-            returns_live,
-            scale_kws={'with_std': False},
-            title='Similarity without\nvariance normalization',
-            ax=ax_daily_similarity_no_var)
-        plotting.plot_daily_returns_similarity(
-            returns_backtest,
-            returns_live,
-            scale_kws={'with_std': False,
-                       'with_mean': False},
-            title='Similarity without variance\nand mean normalization',
-            ax=ax_daily_similarity_no_var_no_mean)
-
     for ax in fig.axes:
         plt.setp(ax.get_xticklabels(), visible=True)
 

pyfolio/tests/test_timeseries.py

@@ -289,7 +289,7 @@ def test_sharpe_2(self, returns, rolling_sharpe_window, expected):
             returns, rolling_sharpe_window).values.tolist()), expected)
 
     @parameterized.expand([
-        (simple_rets, 0.010766923838471554)
+        (simple_rets, 0.10376378866671222)
     ])
     def test_stability_of_timeseries(self, returns, expected):
         self.assertAlmostEqual(