MAINT: add perf attrib to full tearsheet, refactoring

Author: vikram-narayan

pyfolio/perf_attrib.py

@@ -19,7 +19,7 @@
 
 import matplotlib.pyplot as plt
 from pyfolio.pos import get_percent_alloc
-from pyfolio.utils import print_table, set_legend_location, COLORS
+from pyfolio.utils import print_table, set_legend_location
 
 
 def perf_attrib(returns, positions, factor_returns, factor_loadings,
@@ -161,7 +161,7 @@ def show_perf_attrib_stats(returns, positions, factor_returns,
         positions,
         factor_returns,
         factor_loadings,
-        pos_in_dollars=pos_in_dollars
+        pos_in_dollars=pos_in_dollars,
     )
 
     perf_attrib_stats = create_perf_attrib_stats(perf_attrib_data)
@@ -270,8 +270,8 @@ def plot_factor_contribution_to_perf(perf_attrib_data, ax=None):
     factors_and_specific = perf_attrib_data.drop(
         ['total_returns', 'common_returns'], axis='columns')
 
-    for s in factors_and_specific:
-        ax.plot(factors_and_specific[s])
+    for col in factors_and_specific:
+        ax.plot(factors_and_specific[col])
 
     ax.axhline(0, color='k')
     set_legend_location(ax)
@@ -304,8 +304,8 @@ def plot_risk_exposures(exposures, ax=None):
     if ax is None:
         ax = plt.gca()
 
-    for s in exposures:
-        ax.plot(exposures[s])
+    for col in exposures:
+        ax.plot(exposures[col])
 
     set_legend_location(ax)
     ax.set_ylabel('Factor exposures')

pyfolio/tears.py

@@ -77,7 +77,11 @@ def create_full_tear_sheet(returns,
                            volumes=None,
                            percentile=None,
                            turnover_denom='AGB',
-                           set_context=True):
+                           set_context=True,
+                           factor_returns=None,
+                           factor_loadings=None,
+                           pos_in_dollars=True,
+                           return_fig=False):
     """
     Generate a number of tear sheets that are useful
     for analyzing a strategy's performance.
@@ -160,6 +164,13 @@ def create_full_tear_sheet(returns,
     set_context : boolean, optional
         If True, set default plotting style context.
          - See plotting.context().
+    factor_returns : pd.Dataframe, optional
+        Returns by factor, with date as index and factors as columns
+    factor_loadings : pd.Dataframe, optional
+        Factor loadings for all days in the date range, with date and
+        ticker as index, and factors as columns.
+    pos_in_dollars : boolean, optional
+        indicates whether positions is in dollars
     """
 
     if benchmark_rets is None:
@@ -219,6 +230,11 @@ def create_full_tear_sheet(returns,
             create_risk_tear_sheet(positions, style_factor_panel, sectors,
                                    caps, shares_held, volumes, percentile)
 
+        if factor_returns is not None and factor_loadings is not None:
+            create_perf_attrib_tearsheet(returns, positions, factor_returns,
+                                         factor_loadings,
+                                         pos_in_dollars=pos_in_dollars)
+
     if bayesian:
         create_bayesian_tear_sheet(returns,
                                    live_start_date=live_start_date,

pyfolio/utils.py

@@ -623,5 +623,7 @@ def set_legend_location(ax, autofmt_xdate=True):
     ax.legend(frameon=True, framealpha=0.5, loc='upper left',
               bbox_to_anchor=(1.05, 1))
 
+    ax.set_prop_cycle('color', COLORS)
+
     if autofmt_xdate:
         ax.figure.autofmt_xdate()