6a539afe37f422a70ebd0953ecc4675860a52219
[epclust.git] / code / README
1 0) Download & compile Benjamin's specific library
2
3 git clone git@auder.net:cgds
4 cd cgds
5 bash makeMakefile.sh src
6 make src
7 sudo make install
8
9 Make sure that the install destination is on the LD_LIBRARY_PATH environment variable.
10
11 1) Compile source code for 1st stage clustering
12
13 mkdir -p build/stage1/src
14 cd build/stage1/src
15 cmake ../../../stage1/src
16 make
17
18 2) #repeat previous lines for stage 2 ???
19
20
21 NOTA: Need to have openmpi, mpich (compiler for mpi) libxml, and libgsl installed.
22
23
24 Usage (stage 1) :
25
26 Serialize input data using
27
28 ppam.exe serialize inputfile_edf outputfile_edf 1 0
29
30 # 1 indicates data is by column
31 # 0 means process all the rows
32
33 mpirun -np nbProcess ppam.exe cluster ifilename nbSeriesInChunk nbClusters randomize p_for_dissims
34
35 ## ex. > mpirun -np 4 ./ppam.exe cluster ~/tmp/2009.bin 5000 200 1 2
36
37 Where :
38 nbProcess = number of simultaneous processes
39 ifilename = path to serialized dataset (read below)
40 nbSeriesInChunk = number of time-series to process sequentially
41 nbClusters = number of clusters
42 randomize = 1 to dispatch time-series at random. 0 to process them in order
43 p_for_dissims = the 'p' of L_p distance used to compute dissimilarities
44
45
46 The results are stored in ppamResult.xml (curves ids and ranks) while ppamFinalSeries.bin
47 are the curves used in the last clustering step. The ranks in ppamResult.xml refer to the
48 curves in ppamFinalSeries.bin
49
50
51 Note : custom [de]serialization. Consider writing your own
52 in src/TimeSeries/ folder if you plan to test the package.
53
54 See also src/main.c for the details.