Small fix and updated documentation from running on OSX (#1)

* Made code run on Unix systems.  Removed Windows-specific directory slash.

* Updated README.md for my experience installing on OSX

* Added file describing my install experience on OSX

README.md

@@ -6,6 +6,8 @@ All the yield curve data files (i.e A_Country_All_Data_Bloomberg.xlsm) for the r
 For initial reproduction of results, sample data files (i.e A_Country_All_Data_Bloomberg.xls) for the respective countries have been provided till November 2015.    
 
 Instructions for generating the results
-1.	Generation of Yield curve data: data_read.py script generates the spliced yield curve dataset (Govt. data spliced with the OIS data after a specific date) for a respective country (Line 61 in the code) in monthly, weekly and daily csv formats.
-2.	Generation of Shadow rate and other results: AAA_RUN_KANSM2_Est_LB.py script generates the results in a csv format as in the “Comparison of international monetary policy measures” for a respective country (Line 27) in the desired frequency (Line 28).
+0. Install pip   (E.g., on Unix run "sudo easy_install pip")
+1. Install libraries.  (E.g. run "pip install openpyxl")
+2.	Run "python data\_read.py"   This generates yield curve data.   The script generates the spliced yield curve dataset (Govt. data spliced with the OIS data after a specific date) for a respective country (Line 61 in the code) in monthly, weekly and daily csv formats.
+3.	Run "python AAA\_RUN\_KANSM2\_Est\_LB.py"  This generates the shadow rate and other results.  The script generates the results in a csv format as in the “Comparison of international monetary policy measures” for a respective country (Line 27) in the desired frequency (Line 28).
 Please Note: Currently the code uses given parameters (FinalNaturalParameters_Country.dat) but you have the option (Line 23) of estimating it from the whole dataset, although the code running time becomes slower and needs to be optimized further.

data_read.py

@@ -60,8 +60,8 @@ def filter_data(a,index,dim):
 
 Country='UK'# US, EA, JP, UK. 
 CurveType='OIS'
-PathName=os.getcwd()+'\\'
-ExcelName=PathName+'A_'+Country+'_All_Data_Bloomberg.xlsx'
+PathName=os.getcwd()
+ExcelName=os.path.join(PathName, 'A_'+Country+'_All_Data_Bloomberg.xlsx')
 if CurveType is 'OIS':
     ExcelSheetName='D. Live OIS data'
 if CurveType is 'Govt':
@@ -140,7 +140,7 @@ def filter_data(a,index,dim):
 
 #GOVT
 if Country is 'EA':
-    wbG=openpyxl.load_workbook(PathName+'A_GE_All_Data_Bloomberg.xlsx')
+    wbG=openpyxl.load_workbook(os.path.join(PathName, 'A_GE_All_Data_Bloomberg.xlsx'))
     sheet=wbG.get_sheet_by_name('D. Live Govt data')
     datenumG = [[] for i in range(len(datelist))]
     values_dataG=[[] for i in range(len(datelist))]
@@ -182,7 +182,7 @@ def filter_data(a,index,dim):
     post_euro_ge_index=filter_data(common_datenumG,index_to_del,1)
     post_euro_ge_vlues=filter_data(values_dataG,index_to_del,len(values_dataG))
 
-    wbF=openpyxl.load_workbook(PathName+'A_FR_All_Data_Bloomberg.xlsx')
+    wbF=openpyxl.load_workbook(os.path.join(PathName, 'A_FR_All_Data_Bloomberg.xlsx'))
     sheet=wbG.get_sheet_by_name('D. Live Govt data')
     datenumF = [[] for i in range(len(datelist))]
     values_dataF=[[] for i in range(len(datelist))]

install_log__OSX__2017_Jun_20.txt

@@ -0,0 +1,35 @@
+# This is the log of the commands run by Michael Nahas
+# when I installed on 2017 Jun 19.
+# on OSX 10.10.5 Yosemite
+
+# May need pip.  Installed in /usr/local/bin/pip
+# sudo easy_install pip
+
+# Tried to run this.  It hit an exception, so I skipped it.
+#pip install --upgrade pip
+
+# needed library
+# I added --user flag when I had permissions error.
+pip install openpyxl
+
+# Had to remove Windows-specific directory slash \\ so that it worked on Unix.
+python data_read.py
+
+# That command created these files:
+#   UK_Daily.csv
+#   UK_Monthly. csv
+#   UK_Weekly.csv
+
+python ./AAA_RUN_KANSM2_Est_LB.py
+
+# That command opened a number of graphs
+# It created files:
+#   EMS_Monthly.jpg
+#   ETZ_Monthly.jpg
+#   SSR_Monthly.jpg
+#   UK_GSW_Govt_rL_Est_30.000000_KANSM2_Monthly_IEKF_E-5.000000_Final_2017_06_19_15_59_39_final.csv
+#   plot.pdf
+
+# Seemed to only run the UK data, not all countries.
+#
+# Unfortunately, ran out of time to play with the code right now.  Leaving this here.