separate TODO and wrapper example

[epclust.git] / \e\e\e:q

\e[1mdiff --git a/TODO b/TODO\e[m
\e[1mindex 9fd325a..cd454f2 100644\e[m
\e[1m--- a/TODO\e[m
\e[1m+++ b/TODO\e[m
\e[36m@@ -18,25 +18,21 @@\e[m \e[mA faire:\e[m
  - finir les experiences (sur nb de classes, nb de curves / chunk, nb de procs)\e[m
    et sur d'autres architectures\e[m
 \e[m
\e[31m-\e[m
\e[31m-\e[m
\e[31m-\e[m
\e[31m-\e[m
 dans old_C_code/build :\e[m
 cmake ../stage1/src\e[m
 make\e[m
 \e[m
 dans data/, lancer R puis :\e[m
 source("../old_C_code/wrapper.R")\e[m
\e[31m-serialize("../old_C_code/build", "2009.csv","2009.bin")\e[m
\e[31m-\e[m
\e[31m-\e[m
\e[31m-\e[m
\e[31m-	 ppam_exe("build",np,"pathTo2010.bin","nbSeriesPerChunk nbClusters 1 2")\e[m
\e[31m-	 C = getMedoids("build", "ppamResult.xml", "ppamFinalSeries.bin")\e[m
\e[31m-	 quelques_series = deserialize("pathTo2010.bin", rangs...)\e[m
\e[31m-	 #plot C ... et quelques_series ...\e[m
\e[31m-	 getDistor("buid", "ppamResult.xml", "pathTo2010.bin")\e[m
\e[32m+\e[m\e[32mserialize("../old_C_code/build", "2009.csv","2009.bin",1)\e[m
\e[32m+\e[m\e[32mlibrary(parallel)\e[m
\e[32m+\e[m\e[32mnp = detectCores()\e[m
\e[32m+\e[m\e[32mnbSeriesPerChunk = 3000\e[m
\e[32m+\e[m\e[32mnbClusters = 20\e[m
\e[32m+\e[m\e[32mppam_exe("../old_C_code/build",np,"2009.bin",nbSeriesPerChunk,nbClusters)\e[m
\e[32m+\e[m\e[32mC = getMedoids("../old_C_code/build", "ppamResult.xml", "ppamFinalSeries.bin")\e[m
\e[32m+\e[m\e[32mfirst100series = deserialize("../old_C_code/build", "2009.bin", "2009.csv.part", "1-100")\e[m
\e[32m+\e[m\e[32mdistor = getDistor("../old_C_code/build", "ppamResult.xml", "2009.bin")\e[m
 \e[m
 - interface matrice -> binaire\e[m
 	 OK\e[m
\e[1mdiff --git a/old_C_code/wrapper.R b/old_C_code/wrapper.R\e[m
\e[1mindex ee15a79..d6d05e1 100644\e[m
\e[1m--- a/old_C_code/wrapper.R\e[m
\e[1m+++ b/old_C_code/wrapper.R\e[m
\e[36m@@ -1,3 +1,21 @@\e[m
\e[32m+\e[m\e[32m#Exemple :\e[m
\e[32m+\e[m\e[32m#\e[m
\e[32m+\e[m\e[32m#dans old_C_code/build :\e[m
\e[32m+\e[m\e[32m#cmake ../stage1/src\e[m
\e[32m+\e[m\e[32m#make\e[m
\e[32m+\e[m\e[32m#\e[m
\e[32m+\e[m\e[32m#dans data/, lancer R puis :\e[m
\e[32m+\e[m\e[32m#source("../old_C_code/wrapper.R")\e[m
\e[32m+\e[m\e[32m#serialize("../old_C_code/build", "2009.csv","2009.bin",1)\e[m
\e[32m+\e[m\e[32m#library(parallel)\e[m
\e[32m+\e[m\e[32m#np = detectCores()\e[m
\e[32m+\e[m\e[32m#nbSeriesPerChunk = 3000\e[m
\e[32m+\e[m\e[32m#nbClusters = 20\e[m
\e[32m+\e[m\e[32m#ppam_exe("../old_C_code/build",np,"2009.bin",nbSeriesPerChunk,nbClusters)\e[m
\e[32m+\e[m\e[32m#C = getMedoids("../old_C_code/build", "ppamResult.xml", "ppamFinalSeries.bin")\e[m
\e[32m+\e[m\e[32m#first100series = deserialize("../old_C_code/build", "2009.bin", "2009.csv.part", "1-100")\e[m
\e[32m+\e[m\e[32m#distor = getDistor("../old_C_code/build", "ppamResult.xml", "2009.bin")\e[m
\e[32m+\e[m
 ppam_exe = function(path=".", np=parallel::detectCores(), data=NULL,\e[m
 	nbSeriesPerChunk, nbClusters, randomize=1, p_dissims=2)\e[m
 {\e[m