fix pep 8 complaints

Author: mmcky

quantecon/__init__.py

@@ -7,7 +7,8 @@
 	import numba
 except:
 	raise ImportError(
-		"Cannot import numba from current anaconda distribution. Please run `conda install numba` to install the latest version.")
+		"Cannot import numba from current anaconda distribution. \
+			Please run `conda install numba` to install the latest version.")
 
 #-Modules-#
 from . import distributions
@@ -25,7 +26,8 @@
 # from .game_theory import <objects-here> 							#Place Holder if we wish to promote any general objects to the qe namespace.
 from .graph_tools import DiGraph, random_tournament_graph
 from .gridtools import cartesian, mlinspace, simplex_grid, simplex_index
-from .inequality import lorenz_curve, gini_coefficient, shorrocks_index, rank_size_plot
+from .inequality import lorenz_curve, gini_coefficient, shorrocks_index, \
+	rank_size_plot
 from .kalman import Kalman
 from .lae import LAE
 from .arma import ARMA
@@ -37,7 +39,8 @@
 from .quadsums import var_quadratic_sum, m_quadratic_sum
 #->Propose Delete From Top Level
 #Promote to keep current examples working
-from .markov import MarkovChain, random_markov_chain, random_stochastic_matrix, gth_solve, tauchen, rouwenhorst
+from .markov import MarkovChain, random_markov_chain, random_stochastic_matrix, \
+	gth_solve, tauchen, rouwenhorst
 #Imports that Should be Deprecated with markov package
 from .markov import mc_compute_stationary, mc_sample_path
 #<-

quantecon/inequality.py

@@ -122,10 +122,10 @@ def shorrocks_index(A):
 def rank_size_plot(data, ax, label=None, c=1.0):
     """
     Generate rank-size data corresponding to distribution data.
-    
+
     Examples
     --------
-    
+
     > import numpy as np
     > import matplotlib.pyplot as plt
     > y = np.exp(np.random.randn(1000))  # simulate data
@@ -135,13 +135,11 @@ def rank_size_plot(data, ax, label=None, c=1.0):
 
     Parameters
     ----------
-    
+
     data : array_like
         the set of observations
-        
     c : int or float
         restrict plot to top (c x 100)% of the distribution
-          
     ax : axis object
         for plotting on, has method ax.loglog
     """