[epclust.git] / code / README

To compile source code :

   mkdir -p build/stage1/src
   cd build/stage1/src
   cmake ../../../stage1/src
   make
   #repeat previous lines for stage 2

Usage (stage 1) :

   mpirun -np nbProcess ppam.exe cluster ifilename nbSeriesInChunk nbClusters randomize p_for_dissims

Where :
   nbProcess = number of simultaneous processes
   ifilename = path to serialized dataset (read below)
   nbSeriesInChunk = number of time-series to process sequentially
   nbClusters = number of clusters
   randomize = 1 to dispatch time-series at random. 0 to process them in order
   p_for_dissims = the 'p' of L_p distance used to compute dissimilarities

Note : custom [de]serialization. Consider writing your own 
in src/TimeSeries/ folder if you plan to test the package.

See also src/main.c for the details.
Commit	Line	Data
	1	To compile source code :
	2
	3	mkdir -p build/stage1/src
	4	cd build/stage1/src
	5	cmake ../../../stage1/src
	6	make
	7	#repeat previous lines for stage 2
	8
	9	Usage (stage 1) :
	10
	11	mpirun -np nbProcess ppam.exe cluster ifilename nbSeriesInChunk nbClusters randomize p_for_dissims
	12
	13	Where :
	14	nbProcess = number of simultaneous processes
	15	ifilename = path to serialized dataset (read below)
	16	nbSeriesInChunk = number of time-series to process sequentially
	17	nbClusters = number of clusters
	18	randomize = 1 to dispatch time-series at random. 0 to process them in order
	19	p_for_dissims = the 'p' of L_p distance used to compute dissimilarities
	20
	21	Note : custom [de]serialization. Consider writing your own
	22	in src/TimeSeries/ folder if you plan to test the package.
	23
	24	See also src/main.c for the details.