Changes between Version 472 and Version 473 of WikiStart

Timestamp:

03/23/22 13:34:12 (2 years ago)

Author:

wouter

Comment:

--

WikiStart

@@ -738 +738 @@
 
 == LogConverter
-The LogConverter tool adds outcome utilities to APP.json and APPLearn.json log files. These log files contain a section  "results". T
+The LogConverter tool adds outcome utilities to APP.json and APPLearn.json log files. These log files are just serialized NegoState objects. The converter picks up the results from these and adds utilities to them. Then it can write the results to stdout or a file, in either JSON or CSV format.
 
 You call the logconverter like this (download the logconverter from the artifactory, or download the sources):
 {{{
-java -jar target/logconverter-2.1.3-jar-with-dependencies.jar  src/test/resources/APP1646925947841.json 
-}}}
+java -jar target/logconverter-2.1.3-jar-with-dependencies.jar -s src/test/resources/APP1646925947841local.json -f CSV -o test.csv
+}}}
+
+You can also convert an entire directory, like this (make sure you create the output dir and that all files in the source dir are NegoState objects)
+{{{
+java -jar target/logconverter-2.1.3-jar-with-dependencies.jar -s src/test/resources/ -f CSV -o test
+}}}
+
+If your output is CSV format, you get a csv file with a header {{{session,party,profile,utility
+}}} and one row of data for each session result. 
+ 
+If your output is JSON format, each SessionResult from the Session is converted to a SessionResultWithUtils, and the list of these objects is written.
 
 The logconverter adds a section "utilities" to each of the results, containing a dict with the final utility for each party. The final utility was defined in [#SessionResult the SessionResult section]. 
 
-The logconverter outputs the converted json file to stdout. You may want to redirect this into a file for use in a statistical package like R.
+You can directly import the CSV for statistical postprocessing, for instance using R:
+
+{{{
+R
+data<-read.csv("test.csv")
+aggregate(x=data$utility, by=list(data$party), FUN=mean)
+}}}
+
+Of course you can also use any software that can read CSV to analyse the results, like Microsoft Excel, Python, Mathematica etc.
 
 = Example Parties