1 files changed, 49 insertions, 3 deletions
diff --git a/python/mark_backtest_underpar.py b/python/mark_backtest_underpar.py
index 863af8c7..28f8f059 100644
--- a/python/mark_backtest_underpar.py
+++ b/python/mark_backtest_underpar.py
@@ -19,13 +19,59 @@ df_trades = pd.read_sql_query("select trade_date, identifier, principal_payment,
                               parse_dates=['trade_date'])
 df_trades = df_trades.sort_values('trade_date')
 df_wide = pd.merge_asof(df_trades, df_wide, left_on='trade_date', right_on='date', by='identifier')
-df_long = pd.merge_asof(df_trades, df, left_on='trade_date', right_on='date', by='identifier')
+d = {}
+for source, g in df.groupby('source'):
+    d[source] = pd.merge_asof(df_trades, g, left_on='trade_date', right_on='date', by='identifier')
+df_long = pd.concat(d, join='inner')
+df_long = df_long.reset_index()
+df_long = df_long.dropna(subset=['price','mark'])
+
+#filtering
+#filter = 2
+begindate = '2013-01-01'
+enddate = '2017-01-01'
+df_long = df_long[df_long.identifier.str.len()==9]
+df_long = df_long[(df_long['trade_date']>begindate) & (df_long['trade_date']<enddate)]
+#difference= df_long[df_long['<filter].groupby('level_0').[.mean(), columns=['Average'])
+#difference['Std Dev'] = df_long[df_long<filter].std()
 
 #pretty plot
-sns.lmplot(x='mark', y='price', hue = 'source', data=df_long, fit_reg=False)
+#dotsize = pd.Series.tolist(df_long['level_0'].apply(lambda x: 400 if x == 'MANAGER' else 20))
+#df_long['dotsize'] = df_long['level_0'].apply(lambda x: 400 if x == 'MANAGER' else 20)
+df_long['dotsize'] = df_long['level_0'].apply(lambda x: 400 if x == 'MANAGER' else 20)
+plt.switch_backend('Agg')
+sb.set_style("whitegrid")
+sb.set_context("notebook")
+regplot = sb.lmplot(x='mark', y='price', hue = 'source', data=df_long, fit_reg=False, legend_out=True, aspect = 2.1, size = 4, scatter_kws={"s": df_long['dotsize']})
+regplot.set(ylim=(0, 105), xlim=(0, 105))
+#plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)
+regplot.fig.savefig("/home/serenitas/edwin/fig1.png")
+
 
+#plt.switch_backend('Qt4Agg')
+order = ['MANAGER','BROKER','BVAL','IDC','MARKIT','PB','PRICESERVE','PRICINGDIRECT','REUTERS','S&P']
+sb.set_palette(sb.hls_palette(10, l=.4, s=.8))
+g = sb.FacetGrid(df_long, hue='source', hue_kws={'s':[50] + [20]*9, 'marker': ["o"]+["s"]*9, 'alpha': [1]+[.4]*9}, legend_out=True, aspect = 2.1, size = 4, hue_order = order)
+g.set(ylim=(0, 105), xlim=(0, 105))
+ax = g.map(plt.scatter, 'mark', 'price').add_legend()
+ax.fig.savefig("/home/serenitas/edwin/fig2.png")
 
 #fit all the models at once
 params = (df_long.
           groupby('source').
-          apply(lambda df: gls('price~mark', df).fit().params)
+          apply(lambda df: gls('price~mark', df).fit().params))
+
+
+def f(a, b, c):
+    return a+b+c
+
+f(1, 2, 3)
+
+l=[1, 2, 3]
+f(*l)
+
+def g(a, b, **kwargs):
+    if 'edwin' in kwargs:
+        print(kwargs[edwin])
+
+g(1, 2, edwin='hello')
+\ No newline at end of file