Initialize with slightly modified (structure) ppam_mpi

diff --git a/.gitignore b/.gitignore
new file mode 100644 (file)
index 0000000..112c581
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,9 @@
+/code/build/*
+/code/data/src/
+
+*.aux
+*.log
+*.nav
+*.snm
+*.toc
+*.out

diff --git a/README.md b/README.md
new file mode 100644 (file)
index 0000000..d510f69
--- /dev/null
+++ b/README.md
@@ -0,0 +1,17 @@
+# Clustering of EDF power curves from Linky data
+
+Joint work with [Jairo Cugliari](http://eric.univ-lyon2.fr/~jcugliari/),
+[Yannig Goude](https://scholar.google.com/citations?user=D-OLEG4AAAAJ&hl=fr) and
+[Jean-Michel Poggi](http://www.math.u-psud.fr/~poggi/)
+
+---
+
+This program takes n time-series in input and is divided in two stages:
+  1) (Heuristic) k-medoids algorithm in parallel to obtain K centers, K << n
+       2) Filtering WER(?) to obtain the final k < K group representations.
+
+---
+
+The folder "communication/" contains latex sources of the slides showed at half-project(?)
+
+The other folder contains all the R and C code, with toy datasets (real ones are not public).

diff --git a/code/README b/code/README
new file mode 100644 (file)
index 0000000..ccb3a0f
--- /dev/null
+++ b/code/README
@@ -0,0 +1,21 @@
+To compile source code :
+
+   cd build
+   cmake ../src
+   make
+
+Usage :
+
+   ppam-mpi cluster ifilename nbSeriesInChunk nbClusters randomize p_for_dissims
+
+Where :
+   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.

diff --git a/code/data/test/integers.txt b/code/data/test/integers.txt
new file mode 100644 (file)
index 0000000..4803f02
--- /dev/null
+++ b/code/data/test/integers.txt
@@ -0,0 +1,3 @@
+1234,-987,654321,12
+345678
+-1234

diff --git a/code/data/test/reals.txt b/code/data/test/reals.txt
new file mode 100644 (file)
index 0000000..ef894e6
--- /dev/null
+++ b/code/data/test/reals.txt
@@ -0,0 +1,4 @@
+1234.056,987e-3,-654321E-2,12.34567
+345678
+-1234.05
+3.0000000e-001,-1.0188000e+000

diff --git a/code/data/test/sample_byCols.bin b/code/data/test/sample_byCols.bin
new file mode 100644 (file)
index 0000000..effa00e
Binary files /dev/null and b/code/data/test/sample_byCols.bin differ

diff --git a/code/data/test/sample_byCols.csv b/code/data/test/sample_byCols.csv
new file mode 100644 (file)
index 0000000..55d304e
--- /dev/null
+++ b/code/data/test/sample_byCols.csv
@@ -0,0 +1,13 @@
+FK_CCU_ID,CPP_DATE_PUISSANCE,CPP_PUISSANCE_CORRIGEE,CPP_PUISSANCE_BRUTE
+12301,12JAN2009:00:30:00,,23.051
+12301,12JAN2009:01:00:00,,33.052
+12301,12JAN2009:01:30:00,32.32,43.053
+50000,23MAR2009:00:30:00,,150.321
+50000,23MAR2009:01:00:00,,160.322
+50000,23MAR2009:01:30:00,11.1,140.323
+1313,30MAY2009:10:30:00,10.0,50.05
+1313,30MAY2009:11:00:00,,51.05
+1313,30MAY2009:11:30:00,,52.05
+6300,20JUL2009:08:30:00,,500.30
+6300,20JUL2009:09:00:00,,501.31
+6300,20JUL2009:09:30:00,1.001,502.32

diff --git a/code/data/test/sample_byRows.bin b/code/data/test/sample_byRows.bin
new file mode 100644 (file)
index 0000000..0bb324b
Binary files /dev/null and b/code/data/test/sample_byRows.bin differ

diff --git a/code/data/test/sample_byRows.csv b/code/data/test/sample_byRows.csv
new file mode 100644 (file)
index 0000000..a91eafb
--- /dev/null
+++ b/code/data/test/sample_byRows.csv
@@ -0,0 +1,4 @@
+12301,23.051,,33.052,43.053
+50000,150.321,160.322,140.323
+1313,50.05,51.05,52.05
+6300,500.30,501.31,,502.32

diff --git a/code/ppam.sh b/code/ppam.sh
new file mode 100644 (file)
index 0000000..26cd32f
--- /dev/null
+++ b/code/ppam.sh
@@ -0,0 +1,30 @@
+#!/bin/bash
+#PBS -l walltime=00:05:00
+#PBS -l nodes=2:ppn=8,pmem=1gb
+#PBS -oe .output
+
+WORKDIR="/workdir2/auder/edfclust/code"
+cd $WORKDIR
+
+rm -f .output
+
+saveLibPath=$LD_LIBRARY_PATH
+
+#TODO: CDS as a module
+LD_LIBRARY_PATH=/workdir2/cds/lib:/opt/openmpi/lib:$LD_LIBRARY_PATH
+export LD_LIBRARY_PATH
+
+#TODO: externalize (de)serialization, do not make assumptions on "how is data stored" (...)
+
+# ppam args (in case of clustering) = 
+#   1: path to binary dataset
+#   2: series per processor
+#   3: number of clusters
+#   4: boolean to randomize series sampling
+#   5: type of distance (1 for L1, 2 for L2...)
+
+#TODO: Hybrid MPI+OpenMP
+mpirun -np 16 ppam cluster ../data/2009_first10000.bin 300 7 0 1
+
+LD_LIBRARY_PATH=$saveLibPath
+export LD_LIBRARY_PATH

diff --git a/code/src/stage1/Algorithm/compute_coefficients.c b/code/src/stage1/Algorithm/compute_coefficients.c
new file mode 100644 (file)
index 0000000..a7a73f3
--- /dev/null
+++ b/code/src/stage1/Algorithm/compute_coefficients.c
@@ -0,0 +1,57 @@
+#include <stdlib.h>
+#include "Util/types.h"
+#include <math.h>
+#include <gsl/gsl_wavelet.h>
+#include <gsl/gsl_spline.h>
+
+// compute rows of the matrix of reduced coordinates
+void compute_coefficients(PowerCurve* powerCurves, uint32_t nbSeries, uint32_t nbValues,
+       Real* reducedCoordinates, uint32_t index, uint32_t nbReducedCoordinates)
+{
+       uint32_t D = (1 << nbReducedCoordinates);
+       Real* x = (Real*) malloc(nbValues*sizeof(Real));
+       for (uint32_t i=0; i<nbValues; i++)
+               x[i] = i;
+       Real* y = (Real*) malloc(nbValues*sizeof(Real));
+       Real* interpolatedTranformedCurve = (Real*) malloc(D*sizeof(Real));
+       gsl_interp* linearInterpolation = gsl_interp_alloc(gsl_interp_linear, nbValues);
+       gsl_interp_accel* acc = gsl_interp_accel_alloc();
+       gsl_wavelet_workspace* work = gsl_wavelet_workspace_alloc(D);
+       //gsl_wavelet* w = gsl_wavelet_alloc(gsl_wavelet_bspline, 206); //used for starlight
+       gsl_wavelet* w = gsl_wavelet_alloc(gsl_wavelet_daubechies, 6); //used for power curves
+       //gsl_wavelet* w = gsl_wavelet_alloc(gsl_wavelet_haar, 2);
+       for (uint32_t i = 0; i < nbSeries; i++)
+       {
+               //Spline interpolation to have D = 2^u sample points
+               for (uint32_t j=0; j<nbValues; j++)
+                       y[j] = powerCurves[i].values[j];
+               gsl_interp_init(linearInterpolation, x, y, nbValues);
+               for (uint32_t j=0; j<D; j++)
+               {
+                       interpolatedTranformedCurve[j] = 
+                               gsl_interp_eval(linearInterpolation, x, y, j*((Real)(nbValues-1)/(D-1)), acc);
+               }
+               //DWT transform (in place) on interpolated curve [TODO: clarify stride parameter]
+               gsl_wavelet_transform_forward(w, interpolatedTranformedCurve, 1, D, work);
+               //Fill reducedCoordinates with energy contributions
+               uint32_t t0 = 1;
+               uint32_t t1 = 1;
+               for (uint32_t j=0; j<nbReducedCoordinates; j++) 
+               {
+                       t1 += (1 << j);
+                       //reducedCoordinates[(index+i)*nbReducedCoordinates+j] = sqrt( sum( x[t0:t1]^2 ) )
+                       Real sumOnSegment = 0.0;
+                       for (uint32_t u=t0; u<t1; u++)
+                               sumOnSegment += interpolatedTranformedCurve[u]*interpolatedTranformedCurve[u];
+                       reducedCoordinates[(index+i)*nbReducedCoordinates+j] = sqrt(sumOnSegment);
+                       t0 = t1;
+               }
+       }
+       gsl_interp_free(linearInterpolation);
+    gsl_interp_accel_free(acc);
+       free(x);
+       free(y);
+       free(interpolatedTranformedCurve);
+       gsl_wavelet_free(w);
+       gsl_wavelet_workspace_free(work);
+}

diff --git a/code/src/stage1/Algorithm/compute_coefficients.h b/code/src/stage1/Algorithm/compute_coefficients.h
new file mode 100644 (file)
index 0000000..9530b85
--- /dev/null
+++ b/code/src/stage1/Algorithm/compute_coefficients.h
@@ -0,0 +1,10 @@
+#ifndef PPAM_COMPUTE_COEFFICIENTS_H
+#define PPAM_COMPUTE_COEFFICIENTS_H
+
+#include "Util/types.h"
+
+// compute rows of the matrix of reduced coordinates (see computeCoefficients.R)
+void compute_coefficients(PowerCurve* powerCurves, uint32_t nbSeries, uint32_t nbValues,
+       Real* reducedCoordinates, uint32_t index, uint32_t nbReducedCoordinates);
+
+#endif

diff --git a/code/src/stage1/Algorithm/get_dissimilarities.c b/code/src/stage1/Algorithm/get_dissimilarities.c
new file mode 100644 (file)
index 0000000..083cce6
--- /dev/null
+++ b/code/src/stage1/Algorithm/get_dissimilarities.c
@@ -0,0 +1,47 @@
+#include "Util/types.h"
+#include <stdlib.h>
+#include <math.h>
+
+// compute L^p dissimilarities for a nxm matrix
+Real* get_dissimilarities_intra(Real* samples, uint32_t nbSamples, uint32_t nbValues, uint32_t p)
+{
+       Real* dissimilarities = (Real*) malloc(nbSamples*nbSamples*sizeof(Real));
+       for (uint32_t i=0; i<nbSamples; i++)
+       {
+               dissimilarities[i*nbSamples+i] = 0.0;
+               for (uint32_t j=0; j<i; j++)
+               {
+                       // dissimilarities[i*nbSamples+j] = L^p distance between reduced rows i and j
+                       double dissim = 0.0;
+                       for (uint32_t m=0; m<nbValues; m++)
+                       {
+                               double delta = fabs(samples[i*nbValues+m] - samples[j*nbValues+m]);
+                               dissim += pow(delta, p);
+                       }
+                       dissimilarities[i*nbSamples+j] = pow(dissim, 1.0/p);
+                       dissimilarities[j*nbSamples+i] = dissimilarities[i*nbSamples+j];
+               }
+       }
+       return dissimilarities;
+}
+
+// compute L^p dissimilarities between rows of 2 matrices
+Real* get_dissimilarities_inter(Real* mat1, uint32_t n1, Real* mat2, uint32_t n2, 
+       uint32_t nbValues, uint32_t p)
+{
+       Real* dissimilarities = (Real*) malloc(n1*n2*sizeof(Real));
+       for (uint32_t i=0; i<n1; i++)
+       {
+               for (uint32_t j=0; j<n2; j++)
+               {
+                       double dissim = 0.0;
+                       for (uint32_t m=0; m<nbValues; m++)
+                       {
+                               double delta = fabs(mat1[i*nbValues+m] - mat2[j*nbValues+m]);
+                               dissim += pow(delta, p);
+                       }
+                       dissimilarities[i*n2+j] = pow(dissim, 1.0/p);
+               }
+       }
+       return dissimilarities;
+}

diff --git a/code/src/stage1/Algorithm/get_dissimilarities.h b/code/src/stage1/Algorithm/get_dissimilarities.h
new file mode 100644 (file)
index 0000000..b3b51f9
--- /dev/null
+++ b/code/src/stage1/Algorithm/get_dissimilarities.h
@@ -0,0 +1,13 @@
+#ifndef PPAM_GET_DISSIMILARITIES_H
+#define PPAM_GET_DISSIMILARITIES_H
+
+#include "Util/types.h"
+
+// compute L^p dissimilarities for a nxm matrix
+Real* get_dissimilarities_intra(Real* samples, uint32_t nbSamples, uint32_t nbValues, uint32_t p);
+
+// compute L^p dissimilarities between rows of 2 matrices
+Real* get_dissimilarities_inter(Real* mat1, uint32_t n1, Real* mat2, uint32_t n2, 
+       uint32_t nbValues, uint32_t p);
+
+#endif

diff --git a/code/src/stage1/Algorithm/pam.c b/code/src/stage1/Algorithm/pam.c
new file mode 100644 (file)
index 0000000..4e3dfac
--- /dev/null
+++ b/code/src/stage1/Algorithm/pam.c
@@ -0,0 +1,167 @@
+#include "Util/types.h"
+#include "Util/rng.h"
+#include <cds/Vector.h>
+#include <stdlib.h>
+#include <math.h>
+
+// auxiliary function to obtain a random sample of 1..n with k elements
+static void sample(uint32_t* v, uint32_t n, uint32_t k)
+{
+       // refVect = (0,1,...,n-1,n)
+       uint32_t* refVect = (uint32_t*) malloc(n * sizeof(uint32_t));
+       for (uint32_t i = 0; i < n; i++)
+               refVect[i] = i;
+
+       uint32_t curSize = n; // current size of the sampling set
+       for (uint32_t j = 0; j < k; j++)
+       {
+               // pick an index in sampling set:
+               uint32_t index = get_rand_int() % curSize;
+               v[j] = refVect[index];
+               // move this index outside of sampling set:
+               refVect[index] = refVect[--curSize];
+       }
+
+       free(refVect);
+}
+
+// assign a vector (represented by its dissimilarities to others, as dissimilarities[index,])
+// to a cluster, represented by its center ==> output is integer in 0..K-1
+static uint32_t assignCluster(uint32_t index, Real* dissimilarities,
+       uint32_t* centers, uint32_t n, uint32_t K)
+{
+       uint32_t minIndex = 0;
+       Real minDist = dissimilarities[index * n + centers[0]];
+
+       for (uint32_t j = 1; j < K; j++)
+       {
+               if (dissimilarities[index * n + centers[j]] < minDist)
+               {
+                       minDist = dissimilarities[index * n + centers[j]];
+                       minIndex = j;
+               }
+       }
+
+       return minIndex;
+}
+
+// assign centers given a clustering, and also compute corresponding distortion
+static void assign_centers(uint32_t nbClusters, Vector** clusters, Real* dissimilarities,
+       uint32_t nbItems, uint32_t* ctrs, Real* distor)
+{
+       *distor = 0.0;
+       // TODO [heuristic]: checking only a neighborhood of the former center ?
+       for (uint32_t j = 0; j < nbClusters; j++)
+       {
+               // If the cluster is empty, choose a center at random (pathological case...)
+               uint32_t minIndex = get_rand_int() % nbItems;
+               Real minSumDist = INFINITY;
+               for (uint32_t i = 0; i < vector_size(clusters[j]); i++)
+               {
+                       uint32_t index1;
+                       vector_get(clusters[j], i, index1);
+                       // attempt to use current index as center
+                       Real sumDist = 0.0;
+                       for (uint32_t ii = 0; ii < vector_size(clusters[j]); ii++)
+                       {
+                               uint32_t index2;
+                               vector_get(clusters[j], ii, index2);
+                               sumDist += dissimilarities[index1 * nbItems + index2];
+                       }
+                       if (sumDist < minSumDist)
+                       {
+                               minSumDist = sumDist;
+                               minIndex = index1;
+                       }
+               }
+               ctrs[j] = minIndex;
+               *distor += minSumDist;
+       }
+}
+
+// Core PAM algorithm from a dissimilarity matrix; (e.g. nstart=10, maxiter=100)
+void pam(Real* dissimilarities, uint32_t nbItems, uint32_t nbClusters, int clustOnMedoids,
+       uint32_t nbStart, uint32_t maxNbIter, Result_t* result)
+{
+       uint32_t* ctrs = result->medoids_ranks; //shorthand
+       uint32_t* oldCtrs = (uint32_t*) malloc(nbClusters * sizeof(uint32_t));
+       Vector** clusters = (Vector**) malloc(nbClusters * sizeof(Vector*));
+       Vector** bestClusts = (Vector**) malloc(nbClusters * sizeof(Vector*));
+       for (uint32_t j = 0; j < nbClusters; j++)
+       {
+               clusters[j] = vector_new(uint32_t);
+               bestClusts[j] = vector_new(uint32_t);
+       }
+
+       Real lastDistor, distor, bestDistor = INFINITY;
+       for (uint32_t startKount = 0; startKount < nbStart; startKount++)
+       {
+               // centers (random) [re]initialization
+               if (clustOnMedoids)
+               {
+                       // In this special case (clustering groups of medoids), we can improve the sampling
+                       uint32_t randomMedoidRank = get_rand_int() % (nbItems / nbClusters);
+                       uint32_t startIndex = randomMedoidRank * nbClusters;
+                       for (uint32_t index = startIndex; index < startIndex + nbClusters; index++)
+                               ctrs[index - startIndex] = index;
+               }
+               else
+                       // No information: complete random sampling
+                       sample(ctrs, nbItems, nbClusters);      
+               for (uint32_t j = 0; j < nbClusters; j++)
+                       oldCtrs[j] = 0;
+               uint32_t kounter = 0;
+
+               distor = INFINITY;
+               do // while 'distortion' decreases...
+               {
+                       // (re)initialize clusters to empty sets
+                       for (uint32_t j = 0; j < nbClusters; j++)
+                               vector_clear(clusters[j]);
+
+                       // estimate clusters belongings
+                       for (uint32_t i = 0; i < nbItems; i++)
+                       {
+                               uint32_t affectation = assignCluster(i, dissimilarities, ctrs, nbItems, nbClusters);
+                               vector_push(clusters[affectation], i);
+                       }
+
+                       // copy current centers to old centers
+                       for (uint32_t j = 0; j < nbClusters; j++)
+                               oldCtrs[j] = ctrs[j];
+
+                       // recompute centers
+                       lastDistor = distor;
+                       assign_centers(nbClusters, clusters, dissimilarities, nbItems, ctrs, &distor);
+               }
+               while (distor < lastDistor && kounter++ < maxNbIter);
+
+               if (distor < bestDistor)
+               {
+                       // copy current clusters into bestClusts
+                       for (uint32_t j = 0; j < nbClusters; j++)
+                       {
+                               vector_clear(bestClusts[j]);
+                               for (uint32_t i = 0; i < vector_size(clusters[j]); i++)
+                               {
+                                       uint32_t index;
+                                       vector_get(clusters[j], i, index);
+                                       vector_push(bestClusts[j], index);
+                               }
+                       }
+                       bestDistor = distor;
+               }
+       }
+
+       // Assign centers from bestClusts
+       assign_centers(nbClusters, bestClusts, dissimilarities, nbItems, ctrs, &distor);
+
+       free(oldCtrs);
+       for (uint32_t j = 0; j < nbClusters; j++)
+       {
+               vector_destroy(clusters[j]);
+               vector_destroy(bestClusts[j]);
+       }
+       free(clusters);
+       free(bestClusts);
+}

diff --git a/code/src/stage1/Algorithm/pam.h b/code/src/stage1/Algorithm/pam.h
new file mode 100644 (file)
index 0000000..106919f
--- /dev/null
+++ b/code/src/stage1/Algorithm/pam.h
@@ -0,0 +1,13 @@
+#ifndef PPAM_PAM_H
+#define PPAM_PAM_H
+
+#include "Util/types.h"
+
+#define NSTART 5
+#define MAXITER 100
+
+// Core PAM algorithm from a 'flat' dissimilarity matrix
+void pam(Real* dissimilarities, uint32_t nbItems, uint32_t nbClusters, 
+       int clustOnMedoids, uint32_t nbStart, uint32_t maxNbIter, Result_t* result);
+
+#endif

diff --git a/code/src/stage1/CMakeLists.txt b/code/src/stage1/CMakeLists.txt
new file mode 100644 (file)
index 0000000..e69ca5d
--- /dev/null
+++ b/code/src/stage1/CMakeLists.txt
@@ -0,0 +1,46 @@
+cmake_minimum_required(VERSION 2.8.5)
+project(ppam_mpi)
+
+set(CMAKE_C_FLAGS "-std=gnu99")
+set(CMAKE_C_FLAGS_DEBUG "-g3")
+set(CMAKE_C_FLAGS_RELEASE "-O3")
+
+#already by default... ?!
+include_directories("${CMAKE_SOURCE_DIR}")
+
+#ppam executable (serialize, cluster, classif)
+
+#cds
+find_path(CDS_INCLUDE_PATH "cds/cds.h")
+find_library(CDS_LIBRARY cds)
+include_directories(${CDS_INCLUDE_PATH})
+
+#GSL: standard location
+find_path(GSL_INCLUDE_PATH "gsl/gsl_linalg.h")
+include_directories(${GSL_INCLUDE_PATH})
+find_library(GSL_LIBRARY gsl)
+find_library(GSLCBLAS_LIBRARY gslcblas)
+set(GSL_LIBRARIES ${GSL_LIBRARY} ${GSLCBLAS_LIBRARY})
+
+#MPI: standard location
+find_package(MPI REQUIRED)
+include_directories(${MPI_INCLUDE_PATH})
+
+#LibXml2: standard location
+find_package(LibXml2 REQUIRED)
+include_directories(${LIBXML2_INCLUDE_DIR})
+
+file(GLOB_RECURSE ppam_src "${CMAKE_SOURCE_DIR}/*.c")
+add_executable(ppam.exe ${ppam_src})
+add_library(ppam SHARED ${ppam_src})
+target_link_libraries(ppam.exe m cds ${MPI_LIBRARIES} ${LIBXML2_LIBRARIES} ${GSL_LIBRARIES} ${CDS_LIBRARY})
+target_link_libraries(ppam m cds ${MPI_LIBRARIES} ${LIBXML2_LIBRARIES} ${GSL_LIBRARIES} ${CDS_LIBRARY})
+
+if (MPI_COMPILE_FLAGS)
+       set_target_properties(ppam.exe PROPERTIES
+               COMPILE_FLAGS "${MPI_COMPILE_FLAGS}")
+endif()
+if (MPI_LINK_FLAGS)
+       set_target_properties(ppam.exe PROPERTIES
+               LINK_FLAGS "${MPI_LINK_FLAGS}")
+endif()

diff --git a/code/src/stage1/Classification/_Readme b/code/src/stage1/Classification/_Readme
new file mode 100644 (file)
index 0000000..4e34128
--- /dev/null
+++ b/code/src/stage1/Classification/_Readme
@@ -0,0 +1,2 @@
+The output of a k-style clustering can easily be used for supervised classification:
+we assign any new observation to the closest cluster representative ("center").

diff --git a/code/src/stage1/Classification/getClass.c b/code/src/stage1/Classification/getClass.c
new file mode 100644 (file)
index 0000000..aed1467
--- /dev/null
+++ b/code/src/stage1/Classification/getClass.c
@@ -0,0 +1,46 @@
+#include "Algorithm/get_dissimilarities.h"
+#include "TimeSeries/deserialize.h"
+#include <math.h>
+#include "Algorithm/compute_coefficients.h"
+#include <string.h>
+#include "Util/utils.h"
+
+uint32_t* get_class(PowerCurve* data, uint32_t nbSeries, PowerCurve* medoids, 
+       uint32_t nbClusters, uint32_t nbValues, uint32_t p_for_dissims, double* DISTOR)
+{
+       // nbReducedCoordinates = smallest power of 2 which is above nbValues
+       uint32_t nbReducedCoordinates = (uint32_t)ceil(log2(nbValues));
+
+       // Preprocessing to reduce dimension of both data and medoids
+       Real* reducedCoordinates_data = (Real*) malloc(nbSeries * nbReducedCoordinates * sizeof(Real));
+       compute_coefficients(data, nbSeries, nbValues, 
+               reducedCoordinates_data, 0, nbReducedCoordinates);
+       Real* reducedCoordinates_medoids = (Real*) malloc(nbClusters * nbReducedCoordinates * sizeof(Real));
+       compute_coefficients(medoids, nbClusters, nbValues, 
+               reducedCoordinates_medoids, 0, nbReducedCoordinates);
+       
+       Real* dissimilarities = get_dissimilarities_inter(reducedCoordinates_data, nbSeries, 
+               reducedCoordinates_medoids, nbClusters, nbReducedCoordinates, p_for_dissims);
+       free(reducedCoordinates_data);
+       free(reducedCoordinates_medoids);
+       
+       // 3] Finally, assign each row to the least dissimilar center
+       uint32_t* result = (uint32_t*) malloc(nbSeries*sizeof(uint32_t));
+       for (uint32_t i=0; i<nbSeries; i++)
+       {
+               uint32_t minIndex = 0;
+               Real minDissim = dissimilarities[i*nbClusters + 0];
+               for (uint32_t j=1; j<nbClusters; j++)
+               {
+                       if (dissimilarities[i*nbClusters + j] < minDissim)
+                       {
+                               minDissim = dissimilarities[i*nbClusters + j];
+                               minIndex = j;
+                       }
+               }
+               result[i] = minIndex + 1;
+               (*DISTOR) += minDissim;
+       }
+       free(dissimilarities);
+       return result;
+}

diff --git a/code/src/stage1/Classification/getClass.h b/code/src/stage1/Classification/getClass.h
new file mode 100644 (file)
index 0000000..4bb4af1
--- /dev/null
+++ b/code/src/stage1/Classification/getClass.h
@@ -0,0 +1,9 @@
+#ifndef PPAM_GET_CLASS_H
+#define PPAM_GET_CLASS_H
+
+#include "Util/types.h"
+
+uint32_t* get_class(PowerCurve* data, uint32_t nbSeries, PowerCurve* medoids, 
+       uint32_t nbClusters, uint32_t nbValues, uint32_t p_for_dissims, double* DISTOR);
+
+#endif

diff --git a/code/src/stage1/MPI_Communication/pack.c b/code/src/stage1/MPI_Communication/pack.c
new file mode 100644 (file)
index 0000000..a7570b9
--- /dev/null
+++ b/code/src/stage1/MPI_Communication/pack.c
@@ -0,0 +1,60 @@
+#include <stdlib.h>
+#include "Util/types.h"
+#include "Util/utils.h"
+
+// serialize a Work_t object into a bytes string
+void pack_work(Work_t* work, uint32_t nbSeriesInChunk, Byte* packedWork)
+{
+       uint32_t index = 0;
+
+       while (work->inputFileName[index] != 0)
+       {
+               packedWork[index] = work->inputFileName[index];
+               index++;
+       }
+       // complete with zeros
+       while (index < NCHAR_FNAME)
+               packedWork[index++] = 0;
+
+       write_int(work->nbSeries, 4, packedWork + index);
+       index += 4;
+
+       for (uint32_t i = 0; i < work->nbSeries; i++)
+       {
+               write_int(work->ranks[i], 4, packedWork + index);
+               index += 4;
+       }
+       // complete with zeros
+       for (uint32_t i = 0; i < nbSeriesInChunk - work->nbSeries; i++)
+       {
+               write_int(0, 4, packedWork + index);
+               index += 4;
+       }
+
+       write_int(work->nbClusters, 4, packedWork + index);
+       index += 4;
+       write_int(work->clustOnMedoids, 4, packedWork + index);
+       index += 4;
+       write_int(work->p_for_dissims, 4, packedWork + index);
+}
+
+// serialize a Result_t object into a bytes string
+void pack_result(Result_t* result, Byte* packedResult)
+{
+       uint32_t index = 0;
+
+       write_int(result->nbClusters, 4, packedResult);
+       index += 4;
+
+       for (uint32_t i = 0; i < result->nbClusters; i++)
+       {
+               write_int(result->medoids_ID[i], 4, packedResult + index);
+               index += 4;
+       }
+
+       for (uint32_t i = 0; i < result->nbClusters; i++)
+       {
+               write_int(result->medoids_ranks[i], 4, packedResult + index);
+               index += 4;
+       }
+}

diff --git a/code/src/stage1/MPI_Communication/pack.h b/code/src/stage1/MPI_Communication/pack.h
new file mode 100644 (file)
index 0000000..38338f7
--- /dev/null
+++ b/code/src/stage1/MPI_Communication/pack.h
@@ -0,0 +1,12 @@
+#ifndef PPAM_PACK_H
+#define PPAM_PACK_H
+
+#include "Util/types.h"
+
+// serialize a Work_t object into a bytes string
+void pack_work(Work_t* work, uint32_t nbSeriesInChunk, Byte* packedWork);
+
+// serialize a Result_t object into a bytes string
+void pack_result(Result_t* result, Byte* packedResult);
+
+#endif

diff --git a/code/src/stage1/MPI_Communication/unpack.c b/code/src/stage1/MPI_Communication/unpack.c
new file mode 100644 (file)
index 0000000..de51270
--- /dev/null
+++ b/code/src/stage1/MPI_Communication/unpack.c
@@ -0,0 +1,68 @@
+#include <stdlib.h>
+#include "Util/types.h"
+#include "Util/utils.h"
+
+// deserialize a Work_t object from a bytes string
+Work_t* unpack_work(Byte* packedWork, uint32_t nbSeriesInChunk)
+{
+       Work_t* work = (Work_t*) malloc(sizeof(Work_t));
+
+       uint32_t index = 0;
+
+       size_t inputFileNameSize = 0;
+       while (packedWork[inputFileNameSize++] != 0) { }
+       work->inputFileName = (char*) malloc(inputFileNameSize);
+       while (index < inputFileNameSize)
+       {
+               work->inputFileName[index] = packedWork[index];
+               index++;
+       }
+
+       index = NCHAR_FNAME;
+
+       uint32_t nbSeries = work->nbSeries = bInt_to_uint(packedWork + index, 4);
+       index += 4;
+
+       work->ranks = (uint32_t*) malloc(nbSeries * sizeof(uint32_t));
+       for (uint32_t i = 0; i < nbSeries; i++)
+       {
+               work->ranks[i] = bInt_to_uint(packedWork + index, 4);
+               index += 4;
+       }
+       // shift over the zeros
+       index += 4 * (nbSeriesInChunk - nbSeries);
+
+       work->nbClusters = bInt_to_uint(packedWork + index, 4);
+       index += 4;
+       work->clustOnMedoids = bInt_to_uint(packedWork + index, 4);
+       index += 4;
+       work->p_for_dissims = bInt_to_uint(packedWork + index, 4);
+
+       return work;
+}
+
+// deserialize a Result_t object from a bytes string
+Result_t* unpack_result(Byte* packedResult)
+{
+       Result_t* result = (Result_t*) malloc(sizeof(Result_t));
+       uint32_t index = 0;
+
+       uint32_t nbClusters = result->nbClusters = bInt_to_uint(packedResult, 4);
+       index += 4;
+
+       result->medoids_ID = (uint32_t*) malloc(nbClusters * sizeof(uint32_t));
+       for (uint32_t i = 0; i < nbClusters; i++)
+       {
+               result->medoids_ID[i] = bInt_to_uint(packedResult + index, 4);
+               index += 4;
+       }
+
+       result->medoids_ranks = (uint32_t*) malloc(nbClusters * sizeof(uint32_t));
+       for (uint32_t i = 0; i < nbClusters; i++)
+       {
+               result->medoids_ranks[i] = bInt_to_uint(packedResult + index, 4);
+               index += 4;
+       }
+
+       return result;
+}

diff --git a/code/src/stage1/MPI_Communication/unpack.h b/code/src/stage1/MPI_Communication/unpack.h
new file mode 100644 (file)
index 0000000..3c7b414
--- /dev/null
+++ b/code/src/stage1/MPI_Communication/unpack.h
@@ -0,0 +1,12 @@
+#ifndef PPAM_UNPACK_H
+#define PPAM_UNPACK_H
+
+#include "Util/types.h"
+
+// deserialize a Work_t object from a bytes string
+Work_t* unpack_work(Byte* packedWork, uint32_t nbSeriesInChunk);
+
+// deserialize a Result_t object from a bytes string
+Result_t* unpack_result(Byte* packedResult);
+
+#endif

diff --git a/code/src/stage1/MPI_Main/master.c b/code/src/stage1/MPI_Main/master.c
new file mode 100644 (file)
index 0000000..c4e16cd
--- /dev/null
+++ b/code/src/stage1/MPI_Main/master.c
@@ -0,0 +1,383 @@
+#include "Util/types.h"
+#include "Util/utils.h"
+#include <mpi.h>
+#include <stdlib.h>
+#include <stdio.h>
+#include <string.h>
+#include <math.h>
+#include <unistd.h>
+#include "MPI_Communication/pack.h"
+#include "MPI_Communication/unpack.h"
+#include "Util/rng.h"
+
+// save the final result in XML format
+static void result_to_XML(Result_t* result, const char* inputFileName, 
+       const char* lastBinaryFileName, uint32_t p_for_dissims)
+{
+       uint32_t nbClusters = result->nbClusters;
+       FILE* ofile = fopen("ppamResult.xml", "w");
+       
+       fprintf(ofile, "<medoids>\n\n");
+
+       fprintf(ofile, "  <file>");
+       fprintf(ofile, "%s", lastBinaryFileName);
+       fprintf(ofile, "</file>\n\n");
+
+       fprintf(ofile, "  <p_for_dissims>");
+       fprintf(ofile, "%u", p_for_dissims);
+       fprintf(ofile, "</p_for_dissims>\n\n");
+       
+       fprintf(ofile, "  <IDs>\n");
+       for (uint32_t i=0; i<nbClusters; i++)
+               fprintf(ofile, "    <ID>%u</ID>\n", result->medoids_ID[i]);
+       fprintf(ofile, "  </IDs>\n\n");
+
+       // medoids ranks in last binary file (human printing: 0 --> 1 ...etc)
+       fprintf(ofile, "  <ranks>\n");
+       for (uint32_t i=0; i<nbClusters; i++)
+               fprintf(ofile, "    <rank>%u</rank>\n", result->medoids_ranks[i] + 1);
+       fprintf(ofile, "  </ranks>\n\n");
+
+       fprintf(ofile, "</medoids>\n");
+       fclose(ofile);
+}
+
+static void binaryResult_to_file(Result_t* result, const char* inputFileName,
+       const char* outputFileName)
+{
+       // Determine tsLength from inputFile
+       uint32_t tsLength = get_tsLength(inputFileName);
+
+       FILE* ifile = fopen(inputFileName, "rb");
+       FILE* ofile = fopen(outputFileName, "ab"); //'append binary'
+
+       Byte tsBuffer[tsLength];
+       for (uint32_t i = 0; i < result->nbClusters; i++)
+       {
+               // Get time-series in (binary) inputFile
+               fseek(ifile, 8 + result->medoids_ranks[i] * tsLength, SEEK_SET);
+               // Copy current serie onto ofile
+               
+               size_t lengthRead = fread(tsBuffer, 1, tsLength, ifile);
+               if (lengthRead != tsLength)
+                       fprintf(stderr, "problem while copying binary series to new file.\n");
+               fwrite(tsBuffer, 1, tsLength, ofile);
+       }
+
+       fclose(ifile);
+       fclose(ofile);
+}
+
+// fill a new unit of work suitable to be given to a slave
+static Work_t* get_next_work(char* inputFileName, uint32_t nbSeries, uint32_t nbSeriesInChunk,
+       double idealNbSeriesInChunk, uint32_t jobsSentCount, uint32_t lastEndIndex,
+       uint32_t nbClusters, uint32_t clustOnMedoids, 
+       int randomize, uint32_t p_for_dissims)
+{
+       Work_t* work = (Work_t*) malloc(sizeof(Work_t));
+
+       work->inputFileName = (char*) malloc(strlen(inputFileName) + 1);
+       strcpy(work->inputFileName, inputFileName);
+
+       if (randomize)
+               work->nbSeries = nbSeriesInChunk;
+       else
+       {
+               double adjustedNbSeriesInNextChunk =
+                       idealNbSeriesInChunk * (jobsSentCount + 1) - lastEndIndex;
+               // round to closest integer
+               work->nbSeries = (uint32_t)adjustedNbSeriesInNextChunk;
+               // stay below the upper bound (TODO: is this check required ?)
+               if (work->nbSeries > nbSeriesInChunk)
+                       work->nbSeries = nbSeriesInChunk;
+               // TODO: what about this one ? (probably useless)
+               if (lastEndIndex + work->nbSeries > nbSeries)
+                       work->nbSeries = nbSeries - lastEndIndex;
+       }
+
+       //TODO: ranks on uint64_t if more than 4.3 billion series at the same place (unlikely...)
+       work->ranks = (uint32_t*) malloc(work->nbSeries * sizeof(uint32_t));
+       for (uint32_t i = 0; i < work->nbSeries; i++)
+               work->ranks[i] = (randomize ? get_rand_int() % nbSeries : lastEndIndex + i);
+
+       work->nbClusters = nbClusters;
+       work->clustOnMedoids = clustOnMedoids;
+       work->p_for_dissims = p_for_dissims;
+
+       return work;
+}
+
+// process all subtasks and save binary results into a new file
+// NOTE: this file will be smaller than initial file (or DB...)
+static void clusters_reduce(char* inputFileName, char* outputFileName, uint32_t ntasks,
+       uint32_t totalNbSeries, uint32_t nbSeriesInChunk, double idealNbSeriesInChunk,
+       uint32_t tsLength, uint32_t nbClusters, uint32_t clustOnMedoids, 
+       int randomize, uint32_t p_for_dissims)
+{
+       FILE* ofile = fopen(outputFileName, "wb"); //'write binary'
+       // Leave a blank for series' count and tsLength
+       for (uint32_t i = 0; i < 8; i++)
+               fputc(0, ofile);
+       fclose(ofile);
+
+       uint32_t jobsSentCount = 0; //used if randomize==FALSE
+       uint32_t lastEndIndex = 0; //used if randomize==FALSE
+
+       uint32_t sentSeriesCount = 0; //used if randomize==TRUE
+
+       // Count series sent to binary file on output
+       uint32_t newSeriesCount = 0;
+
+       // Expected size of a Work message in bytes:
+       uint32_t work_message_length = get_packedWork_length(nbSeriesInChunk);
+       Byte packedWork[work_message_length];
+
+       // Expected size of a Result message in bytes: (uint32_t is on 4 bytes)
+       uint32_t result_message_length = 4 + 4 * nbClusters + 4 * nbClusters;
+       Byte packedResult[result_message_length];
+
+       // Seed the slaves; send one unit of work to each slave.
+       Work_t* work;
+       int* busy_slave = (int*) malloc(ntasks * sizeof(int));
+       for (int rank = 1; rank < ntasks; rank++)
+               busy_slave[rank] = 0;
+       for (int rank = 1; rank < ntasks; rank++)
+       {
+               // Find the next item of work to do
+               work = get_next_work(inputFileName, totalNbSeries, nbSeriesInChunk, idealNbSeriesInChunk,
+                       jobsSentCount, lastEndIndex, nbClusters, clustOnMedoids, 
+                       randomize, p_for_dissims);
+
+               if (randomize)
+                       sentSeriesCount += nbSeriesInChunk;
+               else
+               {
+                       lastEndIndex = lastEndIndex + work->nbSeries;
+                       jobsSentCount++;
+               }
+
+               // Send it to current rank
+               pack_work(work, nbSeriesInChunk, packedWork);
+               free_work(work);
+               fprintf(stdout, "0 / Send work %s to rank=%i / %u\n",inputFileName, rank, 
+                       (randomize ? sentSeriesCount : lastEndIndex));
+               MPI_Send(packedWork, work_message_length, MPI_BYTE, rank, WORKTAG, MPI_COMM_WORLD);
+
+               busy_slave[rank] = 1;
+
+               if ((randomize && sentSeriesCount >= 1.5*totalNbSeries) //TODO: 1.5 = heuristic, magic number...
+                       || (!randomize && lastEndIndex >= totalNbSeries))
+               {
+                       // Nothing more to read
+                       break;
+               }
+       }
+
+       // Loop over getting new work requests until there is no more work to be done
+       Result_t* result;
+       MPI_Status status;
+       while (1)
+       {
+               // If no slave is active, job is over
+               int atLeastOneSlaveActive = 0;
+               for (int rank = 1; rank < ntasks; rank++)
+               {
+                       if (busy_slave[rank])
+                       {
+                               atLeastOneSlaveActive = 1;
+                               break;
+                       }
+               }
+               if (!atLeastOneSlaveActive)
+                       break;
+
+               // Receive results from a slave
+               MPI_Recv(packedResult, result_message_length, MPI_BYTE, MPI_ANY_SOURCE,
+                       WORKTAG, MPI_COMM_WORLD, &status);
+               result = unpack_result(packedResult);
+               fprintf(stdout, "0 / Receive result from rank=%i on %s\n",status.MPI_SOURCE,inputFileName);
+
+               // 'binarize' the result (only series' values) returned by the slave
+               binaryResult_to_file(result, inputFileName, outputFileName);
+               free_result(result);
+               newSeriesCount += nbClusters;
+
+               if ((randomize && sentSeriesCount < totalNbSeries)
+                       || (!randomize && lastEndIndex < totalNbSeries))
+               {
+                       // Get the next unit of work to be done
+                       work = get_next_work(inputFileName, totalNbSeries, nbSeriesInChunk,
+                               idealNbSeriesInChunk, jobsSentCount, lastEndIndex, nbClusters, 
+                               clustOnMedoids, randomize, p_for_dissims);
+
+                       if (randomize)
+                               sentSeriesCount += nbSeriesInChunk;
+                       else
+                       {
+                               lastEndIndex = lastEndIndex + work->nbSeries;
+                               jobsSentCount++;
+                       }
+
+                       // Send the slave a new work unit
+                       pack_work(work, nbSeriesInChunk, packedWork);
+                       free_work(work);
+                       fprintf(stdout, "0 / Send work %s to rank=%i / %u\n",inputFileName, status.MPI_SOURCE, 
+                               (randomize ? sentSeriesCount : lastEndIndex));
+                       MPI_Send(packedWork, work_message_length, MPI_BYTE,
+                               status.MPI_SOURCE, WORKTAG, MPI_COMM_WORLD);
+               }
+
+               else
+                       // No more work to do
+                       busy_slave[status.MPI_SOURCE] = 0;
+       }
+
+       // There's no more work to be done, so receive all results from the slaves.
+       for (int rank = 1; rank < ntasks; rank++)
+       {
+               if (busy_slave[rank])
+               {
+                       MPI_Recv(packedResult, result_message_length, MPI_BYTE,
+                               rank, WORKTAG, MPI_COMM_WORLD, &status);
+                       result = unpack_result(packedResult);
+
+                       // 'binarize' the result (only series' values) returned by the slave
+                       binaryResult_to_file(result, inputFileName, outputFileName);
+                       free_result(result);
+                       newSeriesCount += nbClusters;
+               }
+       }
+       free(busy_slave);
+
+       // Finalize output file: write total number of series inside it, and tsLength
+       ofile = fopen(outputFileName, "r+b"); //read and write, binary
+       fseek(ofile, 0, SEEK_SET);
+       Byte intBuffer[4];
+       write_int(newSeriesCount, 4, intBuffer);
+       fwrite(intBuffer, 1, 4, ofile);
+       write_int(tsLength, 4, intBuffer);
+       fwrite(intBuffer, 1, 4, ofile);
+       fclose(ofile);
+}
+
+// generate random temporary file names
+static char* get_unique_name()
+{
+       size_t nbDigits = 7; //rather arbitrary
+       size_t stringLength = 5 + nbDigits; //5 for '.tmp/'
+       char* s = (char*) malloc(stringLength + 1);
+       s[0] = '.';
+       s[1] = 't';
+       s[2] = 'm';
+       s[3] = 'p';
+       s[4] = '/';
+       for (int i=0; i<nbDigits; i++)
+               s[5+i] = '0' + get_rand_int() % 10;
+       s[stringLength] = 0;
+       return s;
+}
+
+// code executed by master process
+void master_run(char* mainInputFileName, uint32_t totalNbSeries, uint32_t nbSeriesInChunk,
+       double idealNbSeriesInChunk, uint32_t tsLength, uint32_t nbClusters, 
+       int randomize, uint32_t p_for_dissims)
+{
+       // Basic sanity check: nbClusters must be clearly less than series count per chunk
+       if (10 * nbClusters >= nbSeriesInChunk)
+       {
+               fprintf(stdout, "WARNING: cluster size (%u) may be too high compared with chunk size (%u).\n",
+                       nbClusters, nbSeriesInChunk);
+       }
+       
+       // Find out how many processes there are in the default communicator
+       int ntasks;
+       MPI_Comm_size(MPI_COMM_WORLD, &ntasks);
+       if (ntasks <= 1)
+       {
+               fprintf(stderr,"No slaves available (only master running).\n");
+               return;
+       }
+       
+       // initializations
+       char* inputFileName = mainInputFileName;
+       char* outputFileName;
+
+       uint32_t nbSeriesInFile = totalNbSeries;
+
+       while (nbSeriesInFile > nbSeriesInChunk)
+       {
+               outputFileName = get_unique_name();
+               uint32_t clustOnMedoids = (nbSeriesInFile < totalNbSeries ? 1 : 0);
+               clusters_reduce(inputFileName, outputFileName, ntasks, nbSeriesInFile, nbSeriesInChunk,
+                       idealNbSeriesInChunk, tsLength, nbClusters, clustOnMedoids, 
+                       randomize, p_for_dissims);
+
+               // read nbSeries in outputFile
+               nbSeriesInFile = get_nbSeries(outputFileName);
+               
+               // update file names
+               if (strcmp(mainInputFileName, inputFileName) != 0)
+               {
+                       // No need to keep every intermediate binary
+                       unlink(inputFileName);
+                       free(inputFileName);
+               }
+               inputFileName = outputFileName;
+       }
+
+       // read nbSeries in inputFileName (the last one)
+       // we know that there is at most 'nbSeriesInChunk' series in it
+       nbSeriesInFile = get_nbSeries(inputFileName);
+
+       // Expected size of a Work message in bytes:
+       uint32_t work_message_length = get_packedWork_length(nbSeriesInChunk);
+       Byte packedWork[work_message_length];
+
+       // Expected size of a Result message in bytes: (uint32_t is on 4 bytes)
+       uint32_t result_message_length = get_packedResult_length(nbClusters);
+       Byte packedResult[result_message_length];
+
+       // Run a last task by some slave, and get final result
+       Work_t* work = get_next_work(inputFileName, nbSeriesInFile, nbSeriesInChunk,
+               (double)nbSeriesInFile, 0, 0, nbClusters, 1, 0, p_for_dissims);
+
+       // Send the slave a new work unit
+       pack_work(work, nbSeriesInChunk, packedWork);
+       free_work(work);
+       int selectedSlaveRank = get_rand_int() % (ntasks - 1) + 1;
+       fprintf(stdout, "0 / Send final work %s to rank=%i / %u\n", 
+               inputFileName, selectedSlaveRank, nbSeriesInFile);
+       MPI_Send(packedWork, work_message_length, MPI_BYTE, selectedSlaveRank,
+               WORKTAG, MPI_COMM_WORLD);
+
+       MPI_Status status;
+       // Wait for him to finish
+       MPI_Recv(packedResult, result_message_length, MPI_BYTE, selectedSlaveRank,
+                       WORKTAG, MPI_COMM_WORLD, &status);
+       Result_t* finalResult = unpack_result(packedResult);
+       fprintf(stdout, "0 / Receive final result from rank=%i on %s\n",status.MPI_SOURCE,inputFileName);
+
+       //Tell all the slaves to exit by sending an empty message with the DIETAG.
+       for (int rank = 1; rank < ntasks; ++rank)
+               MPI_Send(0, 0, MPI_BYTE, rank, DIETAG, MPI_COMM_WORLD);
+
+       const char finalBinaryName[] = "ppamFinalSeries.bin";
+       result_to_XML(finalResult, inputFileName, finalBinaryName, p_for_dissims);
+       free_result(finalResult);
+
+       // free memory
+       if (strcmp(mainInputFileName, inputFileName))
+       {
+               // Keep last input binary, but rename it
+               rename(inputFileName, finalBinaryName);
+               free(inputFileName);
+       }
+       else
+       {
+               // just symlink mainInputFileName
+               if (!access(finalBinaryName, F_OK))
+                       unlink(finalBinaryName);
+               if (symlink(mainInputFileName, finalBinaryName))
+                       fprintf(stderr,"Cannot create symlink to initial binary file.\n");
+       }
+}

diff --git a/code/src/stage1/MPI_Main/master.h b/code/src/stage1/MPI_Main/master.h
new file mode 100644 (file)
index 0000000..397ea59
--- /dev/null
+++ b/code/src/stage1/MPI_Main/master.h
@@ -0,0 +1,11 @@
+#ifndef PPAM_MASTER_H
+#define PPAM_MASTER_H
+
+#include <stdint.h>
+
+// code executed by master process
+void master_run(char* fileName, uint32_t totalNbSeries, uint32_t nbSeriesInChunk,
+       double idealNbSeriesInChunk, uint32_t tsLength, uint32_t nbClusters, 
+       int randomize, uint32_t p_for_dissims);
+
+#endif

diff --git a/code/src/stage1/MPI_Main/slave.c b/code/src/stage1/MPI_Main/slave.c
new file mode 100644 (file)
index 0000000..d9b0c47
--- /dev/null
+++ b/code/src/stage1/MPI_Main/slave.c
@@ -0,0 +1,111 @@
+#include "Util/types.h"
+#include "Util/utils.h"
+#include "TimeSeries/deserialize.h"
+#include "Algorithm/compute_coefficients.h"
+#include "Algorithm/get_dissimilarities.h"
+#include "Algorithm/pam.h"
+#include <mpi.h>
+#include <stdio.h>
+#include <math.h>
+#include <stdlib.h>
+#include <unistd.h>
+#include "MPI_Communication/unpack.h"
+#include "MPI_Communication/pack.h"
+
+// main job done by a slave: 
+static Result_t* do_work(Work_t* work)
+{
+       // *** Step 1 *** 
+       // Obtain reduced coordinates matrix from time-series.
+       
+       uint32_t nbSeries = work->nbSeries;
+       uint32_t tsLength = get_tsLength(work->inputFileName);
+       uint32_t nbValues = (tsLength - 4) / 3;
+       
+       // nbReducedCoordinates = smallest power of 2 which is above nbValues
+       uint32_t nbReducedCoordinates = (uint32_t)ceil(log2(nbValues));
+       Real* reducedCoordinates = (Real*) malloc(nbSeries * nbReducedCoordinates * sizeof(Real));
+
+       // call preprocessing with the rows of raw power values matrix.
+       // Keep the IDs in memory for further processing.
+       uint32_t* IDs = (uint32_t*)malloc(nbSeries*sizeof(uint32_t));
+       for (uint32_t i = 0; i < nbSeries; i+=CURVES_PER_REQUEST)
+       {
+               uint32_t nbCurvesRetrieved = CURVES_PER_REQUEST;
+               if (i + nbCurvesRetrieved > nbSeries) 
+                       nbCurvesRetrieved -= (i + nbCurvesRetrieved - nbSeries);
+               PowerCurve* powerCurves = 
+                       deserialize(work->inputFileName, NULL, work->ranks + i, nbCurvesRetrieved);
+               compute_coefficients(powerCurves, nbCurvesRetrieved, nbValues, 
+                       reducedCoordinates, i, nbReducedCoordinates);
+               for (uint32_t ii=i; ii<i+nbCurvesRetrieved; ii++)
+               {
+                       IDs[ii] = powerCurves[ii-i].ID;
+                       free(powerCurves[ii-i].values);
+               }
+               free(powerCurves);
+       }
+
+       // *** Step 2 ***
+       // Run PAM algorithm on the dissimilarity matrix computed from 'reducedCoordinates'.
+       
+       Real* dissimilarities = get_dissimilarities_intra(
+               reducedCoordinates, nbSeries, nbReducedCoordinates, work->p_for_dissims);
+       free(reducedCoordinates);
+
+       uint32_t nbClusters = work->nbClusters;
+       Result_t* result = (Result_t*) malloc(sizeof(Result_t));
+       result->medoids_ID = (uint32_t*) malloc(nbClusters * sizeof(uint32_t));
+       result->medoids_ranks = (uint32_t*) malloc(nbClusters * sizeof(uint32_t));
+       result->nbClusters = nbClusters;
+
+       // Run PAM algorithm to fill result->medoids_ranks
+       pam(dissimilarities, nbSeries, nbClusters, work->clustOnMedoids, NSTART, MAXITER, result);
+       free(dissimilarities);
+       
+       // Deduce medoids_IDs from indices
+       for (uint32_t i = 0; i < nbClusters; i++)
+               result->medoids_ID[i] = IDs[result->medoids_ranks[i]];
+       free(IDs);
+
+       // return medoids IDs, indices and items labels (to be post-processed)
+       return result;
+}
+
+// code executed by slave process
+void slave_run(int myrank, uint32_t nbSeriesInChunk, uint32_t nbClusters)
+{
+       Work_t* work;
+       Result_t* result;
+       MPI_Status status;
+
+       // Expected size of a Work message in bytes:
+       uint32_t work_message_length = get_packedWork_length(nbSeriesInChunk);
+       Byte packedWork[work_message_length];
+
+       // Expected size of a Result message in bytes: (uint32_t is on 4 bytes)
+       uint32_t result_message_length = get_packedResult_length(nbClusters);
+       Byte packedResult[result_message_length];
+
+       while (1)
+       {
+               // Receive a message from the master
+               MPI_Recv(packedWork, work_message_length, MPI_BYTE, 0,
+                       MPI_ANY_TAG, MPI_COMM_WORLD, &status);
+
+               // Check the tag of the received message.
+               if (status.MPI_TAG == DIETAG)
+                       return;
+
+               // Do the work
+               work = unpack_work(packedWork, nbSeriesInChunk);
+               fprintf(stdout, "%u / Slave pid=%u work on %s\n",myrank,getpid(),work->inputFileName);
+               result = do_work(work);
+               free_work(work);
+
+               // Send the result back
+               pack_result(result, packedResult);
+               free_result(result);
+               MPI_Send(packedResult, result_message_length, MPI_BYTE, 0, WORKTAG, MPI_COMM_WORLD);
+       }
+}

diff --git a/code/src/stage1/MPI_Main/slave.h b/code/src/stage1/MPI_Main/slave.h
new file mode 100644 (file)
index 0000000..b5ef443
--- /dev/null
+++ b/code/src/stage1/MPI_Main/slave.h
@@ -0,0 +1,9 @@
+#ifndef PPAM_SLAVE_H
+#define PPAM_SLAVE_H
+
+#include <stdint.h>
+
+// code executed by slave process
+void slave_run(int myrank, uint32_t nbSeriesInChunk, uint32_t nbClusters);
+
+#endif

diff --git a/code/src/stage1/TimeSeries/deserialize.c b/code/src/stage1/TimeSeries/deserialize.c
new file mode 100644 (file)
index 0000000..5d1d758
--- /dev/null
+++ b/code/src/stage1/TimeSeries/deserialize.c
@@ -0,0 +1,82 @@
+#include "TimeSeries/deserialize.h"
+#include <stdio.h>
+#include "Util/utils.h"
+
+// Deserialize a portion of a binary file into an array of PowerCurve, or a file
+// WARNING: NO start bytes, NO date times (all series have the same length, at same times).
+PowerCurve* deserialize(const char* ifileName, const char* ofileName,
+       uint32_t* ranks, uint32_t nbRanks)
+{
+       // Read tsLength at the beginning of the file
+       uint32_t tsLength = get_tsLength(ifileName);
+       
+       uint32_t valuesPerSerie = (tsLength - 4) / 3; //remove 4 bytes of ID
+
+       FILE* ifile = fopen(ifileName, "rb");
+       FILE* ofile = NULL;
+       if (ofileName)
+               ofile = fopen(ofileName, "w");
+       
+       if (!ranks || nbRanks <= 0)
+       {
+               nbRanks = get_nbSeries(ifileName);
+               ranks = NULL;
+       }
+       
+       PowerCurve* powerCurves = NULL;
+       if (!ofile)
+               powerCurves = (PowerCurve*) malloc(nbRanks * sizeof(PowerCurve));
+
+       for (uint32_t i = 0; i < nbRanks; i++)
+       {
+               // position to the beginning of current (binarized) time-series
+               // NOTE: shift by 8 bytes, because data size and series length are written first
+               fseek(ifile, 8 + (ranks ? ranks[i] : i) * tsLength, SEEK_SET);
+
+               PowerCurve* powerCurve;
+               if (!ofile)
+               {
+                       powerCurve = powerCurves + i;
+                       powerCurve->values = (Real*) malloc(valuesPerSerie * sizeof(Real));
+               }
+               
+               // translate 4-bytes binary integer into integer ID
+               void* binaryID = malloc(4);
+               size_t lengthRead = fread(binaryID, 4, 1, ifile);
+               if (lengthRead != 1)
+                       fprintf(stderr,"Warning: deserializing truncated binary file.\n");
+               uint32_t ID = bInt_to_uint((Byte*) binaryID, 4);
+               free(binaryID);
+               if (ofile)
+                       fprintf(ofile, "%u,", ID);
+               else
+                       powerCurve->ID = ID;
+
+               // translate 3-bytes binary integers into Real
+               Byte* binarySerie = (Byte*) malloc(3 * valuesPerSerie);
+               lengthRead = fread(binarySerie, 1, 3*valuesPerSerie, ifile);
+               if (lengthRead != 3*valuesPerSerie)
+                       fprintf(stderr,"Warning: deserializing truncated binary file.\n");
+               for (uint32_t i = 0; i < valuesPerSerie; i++)
+               {
+                       uint32_t powerInt = bInt_to_uint(binarySerie + 3 * i, 3);
+                       if (ofile)
+                       {
+                               fprintf(ofile, "%g", powerInt / 10.0 - 0.0);
+                               if (i < valuesPerSerie-1)
+                                       fprintf(ofile, ",");
+                       }
+                       else
+                               powerCurve->values[i] = powerInt / 10.0 - 0.0;
+               }
+               free(binarySerie);
+               if (ofile)
+                       fprintf(ofile, "\n");
+       }
+
+       fclose(ifile);
+       if (ofile)
+               fclose(ofile);
+
+       return powerCurves;
+}

diff --git a/code/src/stage1/TimeSeries/deserialize.h b/code/src/stage1/TimeSeries/deserialize.h
new file mode 100644 (file)
index 0000000..aa6a3d6
--- /dev/null
+++ b/code/src/stage1/TimeSeries/deserialize.h
@@ -0,0 +1,12 @@
+#ifndef PPAM_DESERIALIZE_H
+#define PPAM_DESERIALIZE_H
+
+#include <stdint.h>
+#include <stdlib.h>
+#include "Util/types.h"
+
+// deserialize a portion of a binary file into an array of PowerCurve
+PowerCurve* deserialize(const char* ifileName, const char* ofileName,
+       uint32_t* ranks, uint32_t nbRanks);
+
+#endif

diff --git a/code/src/stage1/TimeSeries/serialize.c b/code/src/stage1/TimeSeries/serialize.c
new file mode 100644 (file)
index 0000000..ab552c9
--- /dev/null
+++ b/code/src/stage1/TimeSeries/serialize.c
@@ -0,0 +1,306 @@
+#include "TimeSeries/serialize.h"
+#define __STDC_FORMAT_MACROS
+#include <inttypes.h>
+#include <math.h>
+#include "Util/types.h"
+#include "Util/utils.h"
+#include <cds/Vector.h>
+#include <string.h>
+
+// parse a line into two integers (ID, raw power)
+static void scan_line(FILE* ifile, int posID, uint32_t* ID, int posPower, uint32_t* rawPower)
+{
+       char nextChar;
+       int position = 1;
+       while (1)
+       {
+               if (position == posID)
+               {
+                       int64_t ID_on64bits;
+                       nextChar = readInt(ifile, &ID_on64bits);
+                       *ID = (uint32_t)ID_on64bits;
+               }
+               else if (position == posPower)
+               {
+                       Real untruncatedPower;
+                       nextChar = readReal(ifile, &untruncatedPower);
+                       if (untruncatedPower < 0.0)
+                               untruncatedPower = 0.0;
+                       *rawPower = (uint32_t) floor(untruncatedPower*10.0);
+               }
+               else
+                       //erase the comma (and skip field then)
+                       nextChar = fgetc(ifile);
+               
+               //continue until next comma (or line end or file end)
+               while (!feof(ifile) && nextChar != '\n' && nextChar != '\r' && nextChar != ',')
+                       nextChar = fgetc(ifile);
+               position++;
+
+               if (feof(ifile) || nextChar == '\n' || nextChar == '\r')
+               {
+                       // skip all potential line feeds
+                       while (!feof(ifile) && nextChar == '\n' || nextChar == '\r')
+                               nextChar = fgetc(ifile);
+                       if (!feof(ifile))
+                               ungetc(nextChar, ifile);
+                       break;
+               }
+       }
+}
+
+//main job: parse a text file into a binary compressed version
+//TODO [long term]: adapt to distributed files/DB, maybe to distributed binary chunks
+void serialize_byCols(const char* ifileName, const char* ofileName, uint32_t nbItems)
+{
+       // use the header to know positions of ID and rawPower
+       FILE* ifile = fopen(ifileName, "r");
+       uint32_t headerShift = 0;
+       char curChar;
+       Vector* header = vector_new(char);
+       do
+       {
+               curChar = fgetc(ifile);
+               headerShift++;
+               if (curChar == '\n' || curChar == '\r')
+               {
+                       //flush all potential other line feeds
+                       while (curChar == '\n' || curChar == '\r')
+                               curChar = fgetc(ifile);
+                       ungetc(curChar, ifile);
+                       break;
+               }
+               vector_push(header, curChar);
+       }
+       while (1);
+       char* headerString = (char*)malloc((vector_size(header) + 1)*sizeof(char));
+       VectorIterator* it = vector_get_iterator(header);
+       int index = 0;
+       while (vectorI_has_data(it))
+       {
+               vectorI_get(it, headerString[index]);
+               vectorI_move_next(it);
+               index++;
+       }
+       vectorI_destroy(it);
+       headerString[index] = 0;
+       vector_destroy(header);
+       int position = 1, posID = 0, posPower = 0;
+       char* columnDescriptor = strtok(headerString, ",");
+       while (columnDescriptor != NULL)
+       {
+               if (!strcmp(columnDescriptor,"FK_CCU_ID") || !strcmp(columnDescriptor,"fk_ccu_id"))
+                       posID = position;
+               else if (!strcmp(columnDescriptor,"CPP_PUISSANCE_BRUTE"))
+                       posPower = position;
+               position++;
+               columnDescriptor = strtok(NULL, ",");
+       }
+       free(headerString);
+       
+       //estimate tsLength with a scan of the 3 first series
+       uint32_t ID=0, rawPower=0, lastID=0, refTsLength=0;
+       scan_line(ifile, posID, &ID, posPower, &rawPower);
+       //'sl' = sample lengths (short because a lot of comparisons then)
+       uint32_t* sl = (uint32_t*) calloc(3, sizeof(uint32_t));
+       for (int i=0; i<3; i++)
+       {
+               lastID = ID;
+               while (ID == lastID)
+               {
+                       sl[i]++;        
+                       scan_line(ifile, posID, &ID, posPower, &rawPower);
+               }
+       }
+       if (sl[1] <= sl[0] <= sl[2] || sl[2] <= sl[0] <= sl[1])
+               refTsLength = sl[0];
+       else if (sl[0] <= sl[1] <= sl[2] || sl[2] <= sl[1] <= sl[0])
+               refTsLength = sl[1];
+       else
+               refTsLength = sl[2];
+       free(sl);
+       //go back at the beginning of the first series (ready to read '\n'...)
+       fseek(ifile, headerShift-1, SEEK_SET);
+
+       // output file to write time-series sequentially, binary format.
+       // Format: for each series, ID is stored on 4 bytes (unsigned integer32). Then,
+       //         (<rawPower>)+ follow, with rawPower stored as a "3 bytes int"
+       //         rawPower values are multiplied by 10 and truncated one digit after 0
+       // NOTE: no raw power should be exactly zero
+       FILE* ofile = fopen(ofileName, "wb");
+
+       // leave space to write the number of series (32bits), and their length in bytes (32bits)
+       for (int i = 0; i < 8; i++)
+               fputc(0, ofile);
+
+       // process one client (ID in first column) at a time
+       uint64_t processedLines = 0; //execution trace
+       uint32_t seriesCount=0, skippedSeriesCount=0, tsLength=0;
+       uint32_t mismatchLengthCount=0, overflowCount=0;
+       Byte tsBuffer[4+3*refTsLength];
+       int overflow = 0;
+       lastID = 0;
+       while (!feof(ifile))
+       {
+               // next element to read always start with a digit
+               do
+                       curChar = fgetc(ifile);
+               while (!feof(ifile) && (curChar < '0' || curChar > '9'));
+               if (feof(ifile))
+                       break;
+               ungetc(curChar, ifile);
+
+               // read line
+               scan_line(ifile, posID, &ID, posPower, &rawPower);
+               if (ID != lastID)
+               {
+                       //just starting a new time-series: must process the last one (if there is a last one !)
+                       if (lastID > 0)
+                       {                               
+                               if (tsLength == refTsLength && !overflow)
+                               {
+                                       seriesCount++;
+                                       fwrite(tsBuffer, 4+3*tsLength, 1, ofile);
+                                       if (nbItems > 0 && seriesCount >= nbItems)
+                                               break;
+                               }
+                               //if something wrong happened, skip series
+                               else
+                               {
+                                       skippedSeriesCount++;
+                                       if (tsLength != refTsLength)
+                                               mismatchLengthCount++;
+                                       if (overflow)
+                                               overflowCount++;
+                               }
+                       }
+                       
+                       // ID for the new series is printed only once:
+                       write_int(ID, 4, tsBuffer);
+                       // reinitialize flags
+                       overflow = 0;
+                       tsLength = 0;
+                       lastID = ID;
+               }
+
+               overflow = (overflow || (rawPower >= (1 << 24)));
+               //We cannot write more than refTsLength bytes
+               if (tsLength < refTsLength)
+                       write_int(rawPower, 3, tsBuffer + 4+3*tsLength);
+               tsLength++;
+               
+               if ((++processedLines) % 1000000 == 0)
+                       fprintf(stdout,"Processed %"PRIu64" lines\n", processedLines);
+       }
+
+       if (!overflow && tsLength == refTsLength && (nbItems <= 0 || seriesCount < nbItems))
+       {
+               // flush last time-series if all conditions are met
+               fwrite(tsBuffer, 4+3*tsLength, 1, ofile);
+               seriesCount++;
+       }
+       else if (nbItems <= 0 || seriesCount < nbItems)
+       {
+               if (tsLength != refTsLength)
+                       mismatchLengthCount++;
+               if (overflow)
+                       overflowCount++;
+       }
+
+       // write lines count and size of a time-series in bytes
+       Byte intBuffer[4];
+       fseek(ofile, 0, SEEK_SET);
+       write_int(seriesCount, 4, intBuffer);
+       fwrite(intBuffer, 1, 4, ofile);
+       // re-express tsLength in bytes (not forgetting the ID))
+       write_int(4 + 3 * refTsLength, 4, intBuffer);
+       fwrite(intBuffer, 1, 4, ofile);
+
+       // finally print some statistics
+       if (seriesCount < nbItems)
+               fprintf(stdout,"Warning: only %u series retrieved.\n",seriesCount);
+       fprintf(stdout,"%u overflows / %u mismatch series lengths.\n",overflowCount,mismatchLengthCount);
+       
+       fclose(ifile);
+       fclose(ofile);
+}
+
+//serialize from usual 'by-row' data (for StarLight example and toy dataset)
+void serialize_byRows(const char* ifileName, const char* ofileName, uint32_t nbItems)
+{
+       FILE* ifile = fopen(ifileName, "r");
+       // first scan to know dimensions
+       uint32_t nbValues = 0; //ID (or, more useful, real class number) comes first
+       char curChar = ' ';
+       while (curChar != '\n' && curChar != '\r')
+       {
+               curChar = fgetc(ifile);
+               if (curChar == ',')
+               {
+                       nbValues++;
+                       //skip potential consecutive commas (could be hard to spot)
+                       while (curChar == ',')
+                               curChar = fgetc(ifile);
+                       ungetc(curChar, ifile);
+               }
+       }
+       while (curChar == '\n' || curChar == '\r')
+               curChar = fgetc(ifile);
+       ungetc(curChar, ifile);
+       uint32_t nbSeries = 1; //we already read 1st line
+       while (!feof(ifile))
+       {
+               if ((curChar = fgetc(ifile)) == '\n')
+                       nbSeries++;
+       }
+       fseek(ifile, 0, SEEK_SET);
+
+       //write meta info first
+       uint32_t tsLength = 3*nbValues+4;
+       FILE* ofile = fopen(ofileName, "wb");
+       Byte intBuffer[4];
+       write_int(nbSeries, 4, intBuffer);
+       fwrite(intBuffer, 1, 4, ofile);
+       write_int(tsLength, 4, intBuffer);
+       fwrite(intBuffer, 1, 4, ofile);
+       Real rawPower;
+       int64_t ID;
+       
+       //DEBUG / TEST (ugly, TOFIX...)
+       double minrp = INFINITY, maxrp = -INFINITY;
+       
+       for (uint32_t i=0; i<nbSeries; i++)
+       {
+               //skip potential line feeds before next line
+               while (curChar == '\n' || curChar == '\r')
+                       curChar = fgetc(ifile);
+               ungetc(curChar, ifile);
+               curChar = readInt(ifile, &ID);
+               write_int((uint32_t)ID, 4, intBuffer);
+               fwrite(intBuffer, 1, 4, ofile);
+               while (curChar == ',')
+                       curChar = fgetc(ifile);
+               ungetc(curChar, ifile);
+               for (uint32_t j=0; j<nbValues; j++)
+               {
+                       curChar = readReal(ifile, &rawPower);
+                       
+                       //DEBUG / TEST (ugly, TOFIX...)
+                       if (rawPower < minrp)
+                               minrp = rawPower;
+                       if (rawPower > maxrp)
+                               maxrp = rawPower;
+                       
+                       write_int((uint32_t)floor(10.0*(rawPower+0.0)), 3, intBuffer); //x10... +3...
+                       fwrite(intBuffer, 1, 3, ofile);
+                       while (curChar == ',')
+                               curChar = fgetc(ifile);
+                       ungetc(curChar, ifile);
+               }
+       }
+       fclose(ifile);
+       fclose(ofile);
+       
+       //DEBUG / TEST (ugly, TOFIX...)
+       printf("min / max values = %g %g\n",minrp,maxrp);
+}

diff --git a/code/src/stage1/TimeSeries/serialize.h b/code/src/stage1/TimeSeries/serialize.h
new file mode 100644 (file)
index 0000000..af89cae
--- /dev/null
+++ b/code/src/stage1/TimeSeries/serialize.h
@@ -0,0 +1,14 @@
+#ifndef PPAM_SERIALIZE_H
+#define PPAM_SERIALIZE_H
+
+#include <stdlib.h>
+#include <stdio.h>
+#include <stdint.h>
+
+//main job: parse a text file into a binary compressed version
+void serialize_byCols(const char* ifileName, const char* ofileName, uint32_t nbItems);
+
+//serialize from usual 'by-row' data
+void serialize_byRows(const char* ifileName, const char* ofileName, uint32_t nbItems);
+
+#endif

diff --git a/code/src/stage1/Util/rng.c b/code/src/stage1/Util/rng.c
new file mode 100644 (file)
index 0000000..6cd4025
--- /dev/null
+++ b/code/src/stage1/Util/rng.c
@@ -0,0 +1,135 @@
+// ISAAC PRNG
+// Initial code by Bob Jenkins, March 1996 - modified in 2008
+// Reference: http://burtleburtle.net/bob/rand/isaacafa.html
+// Further slightly modified by Benjamin Auder, 2013
+
+#include "Util/rng.h"
+#include <stdlib.h>
+#include <time.h>
+
+// Internal state
+static uint32_t mm[256];
+static uint32_t aa, bb, cc;
+
+// initialize the (pseudo-)random generator
+void init_rng(int flag)
+{
+       // 'bootstrap' isaac with basic bad PRNG
+       srand(time(NULL));
+
+       aa = rand() & 0xffffffff;
+       bb = rand() & 0xffffffff;
+       cc = rand() & 0xffffffff;
+
+       uint32_t a, b, c, d, e, f, g, h, i;
+       // The golden ratio:
+       a = b = c = d = e = f = g = h = 0x9e3779b9;
+       // Scramble it
+       for (i = 0; i < 4; ++i)
+               mix(a, b, c, d, e, f, g, h);
+
+       // Fill in mm[] with messy stuff (the seed)
+       uint32_t seedArray[256];
+       for (i = 0; i < 256; ++i) mm[i] = seedArray[i] = rand() & 0xffffffff;
+       for (i = 0; i < 256; i += 8)
+       {
+               if (flag)
+               {
+                       // Use all the information in the seed
+                       a += seedArray[i  ];
+                       b += seedArray[i + 1];
+                       c += seedArray[i + 2];
+                       d += seedArray[i + 3];
+                       e += seedArray[i + 4];
+                       f += seedArray[i + 5];
+                       g += seedArray[i + 6];
+                       h += seedArray[i + 7];
+               }
+               mix(a, b, c, d, e, f, g, h);
+               mm[i  ] = a;
+               mm[i + 1] = b;
+               mm[i + 2] = c;
+               mm[i + 3] = d;
+               mm[i + 4] = e;
+               mm[i + 5] = f;
+               mm[i + 6] = g;
+               mm[i + 7] = h;
+       }
+
+       if (flag)
+       {
+               // Do a second pass to make all of the seed affect all of mm
+               for (i = 0; i < 256; i += 8)
+               {
+                       a += mm[i  ];
+                       b += mm[i + 1];
+                       c += mm[i + 2];
+                       d += mm[i + 3];
+                       e += mm[i + 4];
+                       f += mm[i + 5];
+                       g += mm[i + 6];
+                       h += mm[i + 7];
+                       mix(a, b, c, d, e, f, g, h);
+                       mm[i  ] = a;
+                       mm[i + 1] = b;
+                       mm[i + 2] = c;
+                       mm[i + 3] = d;
+                       mm[i + 4] = e;
+                       mm[i + 5] = f;
+                       mm[i + 6] = g;
+                       mm[i + 7] = h;
+               }
+       }
+}
+
+// return a (pseudo-)random integer
+uint32_t get_rand_int()
+{
+       // TODO: register variables ? (x,y,i)
+       uint32_t x, y;
+       static uint32_t i = 0;
+
+       if (i == 0)
+       {
+               cc = cc + 1;  // cc just gets incremented once per 256 results
+               bb = bb + cc; // then combined with bb
+       }
+
+       x = mm[i];
+       switch (i % 4)
+       {
+       case 0:
+               aa = aa^(aa << 13);
+               break;
+       case 1:
+               aa = aa^(aa >> 6);
+               break;
+       case 2:
+               aa = aa^(aa << 2);
+               break;
+       case 3:
+               aa = aa^(aa >> 16);
+               break;
+       }
+
+       // NOTE: bits 2..9 are chosen from x but 10..17 are chosen
+       //       from y.  The only important thing here is that 2..9 and 10..17
+       //       don't overlap.  2..9 and 10..17 were then chosen for speed in
+       //       the optimized version (rand.c) */
+       // See http://burtleburtle.net/bob/rand/isaac.html
+       // for further explanations and analysis.
+
+       aa        = mm[(i + 128) % 256] + aa;
+       mm[i] = y = mm[(x >> 2) % 256]  + aa + bb;
+       bb        = mm[(y >> 10) % 256] + x;
+
+       i = (i + 1) % 256;
+
+       return bb;
+}
+
+// return a (pseudo-)random real number in [0,1]
+Real get_rand_real()
+{
+       return (Real) (INV_RANDMAX * (double) get_rand_int());
+}

diff --git a/code/src/stage1/Util/rng.h b/code/src/stage1/Util/rng.h
new file mode 100644 (file)
index 0000000..40822aa
--- /dev/null
+++ b/code/src/stage1/Util/rng.h
@@ -0,0 +1,33 @@
+#ifndef PPAM_RNG_H
+#define PPAM_RNG_H
+
+#include <stdint.h>
+#include "Util/types.h"
+
+#define INV_RANDMAX 2.3283064370807974E-10 // 1/0xffffffff
+
+// If (flag!=0), then use a random array to initialize mm[]
+#define mix(a,b,c,d,e,f,g,h)  \
+{                             \
+       a^=b<<11; d+=a; b+=c;     \
+       b^=c>>2;  e+=b; c+=d;     \
+       c^=d<<8;  f+=c; d+=e;     \
+       d^=e>>16; g+=d; e+=f;     \
+       e^=f<<10; h+=e; f+=g;     \
+       f^=g>>4;  a+=f; g+=h;     \
+       g^=h<<8;  b+=g; h+=a;     \
+       h^=a>>9;  c+=h; a+=b;     \
+}
+
+// initialize the (pseudo-)random generator
+// NOTE: flag has only two states, active or not.
+//       flag != 0 --> "maximal randomness"
+void init_rng(int flag);
+ 
+// return a (pseudo-)random integer
+uint32_t get_rand_int();
+
+// return a (pseudo-)random real number in [0,1]
+Real get_rand_real();
+
+#endif

diff --git a/code/src/stage1/Util/types.h b/code/src/stage1/Util/types.h
new file mode 100644 (file)
index 0000000..eaab1b0
--- /dev/null
+++ b/code/src/stage1/Util/types.h
@@ -0,0 +1,46 @@
+#ifndef PPAM_TYPES_H
+#define PPAM_TYPES_H
+
+#include <stdint.h>
+
+// types of work given to a slave
+#define WORKTAG 1
+#define DIETAG 2
+
+// 256 characters for file name should be enough
+#define NCHAR_FNAME 256
+
+typedef unsigned char Byte;
+
+typedef double Real;
+
+// Type to describe a job to be done in a node
+//TODO: merge with packed version to avoid extra copy by MPI
+typedef struct Work_t {
+       // "structural" parameters:
+       char* inputFileName;
+       uint32_t nbSeries;
+       uint32_t* ranks;
+       // clustering parameters [to be completed]:
+       uint32_t nbClusters;
+       uint32_t clustOnMedoids; //a boolean, but 1 byte storage would be inefficient
+       uint32_t p_for_dissims;
+} Work_t;
+
+// Type returned by a worker (clusters labels and medoids)
+//TODO: merge with packed version to avoid extra copy by MPI
+typedef struct Result_t {
+       // parameters describing sizes
+       uint32_t nbClusters;
+       // informative parameters:
+       uint32_t* medoids_ID;
+       uint32_t* medoids_ranks;
+} Result_t;
+
+// data structure to store a customer ID + [time-]serie
+typedef struct PowerCurve {
+       uint32_t ID;
+       Real* values;
+} PowerCurve;
+
+#endif

diff --git a/code/src/stage1/Util/utils.c b/code/src/stage1/Util/utils.c
new file mode 100644 (file)
index 0000000..3786eda
--- /dev/null
+++ b/code/src/stage1/Util/utils.c
@@ -0,0 +1,117 @@
+#include "Util/utils.h"
+#include <math.h>
+#include <cds/Vector.h>
+
+void free_work(Work_t* work)
+{
+       free(work->inputFileName);
+       free(work->ranks);
+       free(work);
+}
+
+void free_result(Result_t* result)
+{
+       free(result->medoids_ID);
+       free(result->medoids_ranks);
+       free(result);
+}
+
+char readInt(FILE* stream, int64_t* integer)
+{
+       *integer = 0;
+       char curChar = fgetc(stream);
+       int sign = (curChar == '-' ? -1 : 1);
+       while (curChar < '0' || curChar > '9')
+               curChar = fgetc(stream);
+       ungetc(curChar, stream);
+       while ((curChar = fgetc(stream)) >= '0' && curChar <= '9')
+               *integer = 10 * (*integer) + (int64_t) (curChar - '0');
+       (*integer) *= sign;
+       return curChar;
+}
+
+char readReal(FILE* stream, Real* real)
+{
+       int64_t integerPart;
+       char nextChar = readInt(stream, &integerPart);
+       int64_t fractionalPart = 0;
+       int countZeros = 0;
+       if (nextChar == '.')
+       {
+               //need to count zeros
+               while ((nextChar = fgetc(stream)) == '0')
+                       countZeros++;
+               if (nextChar >= '0' && nextChar <= '9')
+               {
+                       ungetc(nextChar, stream);
+                       nextChar = readInt(stream, &fractionalPart);
+               }
+       }
+       int64_t exponent = 0;
+       if (nextChar == 'e' || nextChar == 'E')
+               nextChar = readInt(stream, &exponent);
+       int64_t divisorForFractional = pow(10, floor(log10(fractionalPart > 0 ? fractionalPart : 1))+1);
+       *real = ( (Real)integerPart 
+               + (integerPart < 0 ? -1 : 1) * (Real)fractionalPart/(divisorForFractional*pow(10,countZeros)) )
+                       * pow(10,exponent);
+       return nextChar;
+}
+
+// convert n-bytes binary integers to uint32_t
+uint32_t bInt_to_uint(Byte* pInteger, size_t bytesCount)
+{
+       uint32_t integer = 0;
+       for (size_t i = 0; i < bytesCount; i++)
+               integer += ((uint32_t) (pInteger[i])) << (i << 3);
+       return integer;
+}
+
+// serialize integers with a portable bytes order
+void write_int(uint32_t integer, size_t bytesCount, Byte* buffer)
+{
+       Byte chunk;
+       // write from left to right, from least to most significative bit
+       for (size_t i = 0; i < bytesCount; i++)
+       {
+               chunk = (integer >> (i << 3)) & 0xFF;
+               buffer[i] = chunk;
+       }
+}
+
+// Expected size of a Work message in bytes:
+uint32_t get_packedWork_length(uint32_t nbSeriesInChunk)
+{
+       return NCHAR_FNAME + 4 + 4*nbSeriesInChunk + 4 + 4 + 4;
+}
+
+// Expected size of a Result message in bytes: (uint32_t is on 4 bytes)
+uint32_t get_packedResult_length(uint32_t nbClusters)
+{
+       return 4 + 4 * nbClusters + 4 * nbClusters;
+}
+
+// get metadata: nbSeries
+uint32_t get_nbSeries(const char* ifileName)
+{
+       FILE* ifile = fopen(ifileName, "rb");
+       fseek(ifile, 0, SEEK_SET);
+       Byte binaryInt[4];
+       size_t lengthRead = fread(binaryInt, 4, 1, ifile);
+       if (lengthRead != 1)
+               fprintf(stderr,"Warning: getting nbSeries from truncated binary file.\n");
+       fclose(ifile);
+       return bInt_to_uint(binaryInt, 4);
+}
+
+// get metadata: tsLength
+uint32_t get_tsLength(const char* ifileName)
+{
+       FILE* ifile = fopen(ifileName, "rb");
+       fseek(ifile, 4, SEEK_SET);
+       Byte binaryInt[4];
+       size_t lengthRead = fread(binaryInt, 4, 1, ifile);
+       if (lengthRead != 1)
+               fprintf(stderr,"Warning: getting tsLength from truncated binary file.\n");
+       fclose(ifile);
+       return bInt_to_uint(binaryInt, 4);
+}

diff --git a/code/src/stage1/Util/utils.h b/code/src/stage1/Util/utils.h
new file mode 100644 (file)
index 0000000..2ed68aa
--- /dev/null
+++ b/code/src/stage1/Util/utils.h
@@ -0,0 +1,36 @@
+#ifndef PPAM_UTIL_UTILS_H
+#define PPAM_UTIL_UTILS_H
+
+#include "Util/types.h"
+#include <stdlib.h>
+#include <stdio.h>
+
+#define CURVES_PER_REQUEST 50
+
+void free_work(Work_t* work);
+
+void free_result(Result_t* result);
+
+char readInt(FILE* stream, int64_t* integer);
+
+char readReal(FILE* stream, Real* real);
+
+// convert n-bytes binary integers to uint32_t
+uint32_t bInt_to_uint(Byte* pInteger, size_t bytesCount);
+
+// serialize integers with a portable bytes order
+void write_int(uint32_t integer, size_t bytesCount, Byte* buffer);
+
+// Expected size of a Work message in bytes:
+uint32_t get_packedWork_length(uint32_t nbSeriesInChunk);
+
+// Expected size of a Result message in bytes: (uint32_t is on 4 bytes)
+uint32_t get_packedResult_length(uint32_t nbClusters);
+
+// get metadata: nbSeries
+uint32_t get_nbSeries(const char* ifileName);
+
+// get metadata: tsLength
+uint32_t get_tsLength(const char* ifileName);
+
+#endif

diff --git a/code/src/stage1/main.c b/code/src/stage1/main.c
new file mode 100644 (file)
index 0000000..bb4bd46
--- /dev/null
+++ b/code/src/stage1/main.c
@@ -0,0 +1,272 @@
+#include "MPI_Main/master.h"
+#include "MPI_Main/slave.h"
+#include "Util/utils.h"
+#include "Util/rng.h"
+#include <sys/stat.h>
+#include <mpi.h>
+#include <math.h>
+#include <stdio.h>
+#include "TimeSeries/serialize.h"
+#include "TimeSeries/deserialize.h"
+#include "Classification/getClass.h"
+#include <string.h>
+#include <cds/Vector.h>
+#include <libxml/xmlreader.h>
+
+// serialize text file argv[1] into a binary file argv[2]
+int serialize_main(int argc, char** argv)
+{
+       const char* ifileName = argv[1];
+       const char* ofileName = argv[2];
+       int byCols = atoi(argv[3]);
+       uint32_t nbItems = atoi(argv[4]); //==0 for "all series"
+       
+       if (byCols)
+               serialize_byCols(ifileName, ofileName, nbItems);
+       else
+               serialize_byRows(ifileName, ofileName, nbItems);
+       return 0;
+}
+
+// deserialize binary file argv[1] into text file argv[2]
+int deserialize_main(int argc, char** argv)
+{
+       const char* ifileName = argv[1];
+       const char* ofileName = argv[2];
+       Vector* vranks = vector_new(uint32_t);
+       //each token is at most two ints (a-b = from a to b included)
+       char* token = strtok(argv[3], ",");
+       int retrieveAll = 0;
+       uint32_t* ranks = NULL;
+       while (token)
+       {
+               //scan token to find middle position of '-' (if any)
+               int minusPos = -1;
+               int tokenLength = strlen(token);
+               //loop starts at index 1 because -N is allowed (and means 'everything')
+               for (int i=1; i<tokenLength; i++)
+               {
+                       if (token[i] == '-')
+                       {
+                               minusPos = i;
+                               break;
+                       }
+               }
+               if (minusPos < 0)
+               {
+                       int64_t rank = (int64_t)atoi(token);
+                       if (rank <= 0)
+                       {
+                               retrieveAll = 1;
+                               break;
+                       }
+                       vector_push(vranks, (uint32_t)rank);
+               }
+               else
+               {
+                       token[minusPos] = 0;
+                       int int1 = atoi(token);
+                       int int2 = atoi(token+minusPos+1);
+                       for (uint32_t i=int1; i<=int2; i++)
+                               vector_push(vranks, i);
+               }
+               token = strtok(NULL, ",");
+       }
+       uint32_t nbRanks = retrieveAll
+               ? 0
+               : vector_size(vranks);
+       if (!retrieveAll)
+       {
+               ranks = (uint32_t*) malloc(nbRanks*sizeof(uint32_t));
+               for (uint32_t i=0; i<nbRanks; i++)
+               {
+                       vector_get(vranks, i, ranks[i]);
+                       ranks[i]--; //re-express on 0...{n-1}
+               }
+       }
+       vector_destroy(vranks);
+       
+       deserialize(ifileName, ofileName, ranks, nbRanks);
+       return 0;
+}
+
+//main clustering task (master or slave)
+int cluster_main(int argc, char **argv)
+{
+       MPI_Init(&argc, &argv);
+
+       char* ifileName = argv[1]; //could be "../data/test.bin"
+       uint32_t nbSeriesInChunk = atoi(argv[2]); //could be 3000
+       uint32_t nbClusters = atoi(argv[3]); //could be 15
+       int randomize = atoi(argv[4]); //boolean
+       uint32_t p_for_dissims = atoi(argv[5]); //1 for L1, 2 for L2, ...etc
+
+       // Get totalNbSeries and tsLength
+       uint32_t totalNbSeries = get_nbSeries(ifileName);
+       uint32_t tsLength = get_tsLength(ifileName);
+
+       // Basic sanity checks
+       if (nbClusters <= 0 || nbSeriesInChunk <= 1)
+       {
+               MPI_Finalize();
+               return 0;
+       }
+       if (nbSeriesInChunk > totalNbSeries)
+               nbSeriesInChunk = totalNbSeries;
+       if (nbClusters > nbSeriesInChunk)
+               nbClusters = nbSeriesInChunk;
+
+       double idealNbSeriesInChunk = 0.0; //unused if randomize == TRUE
+       if (!randomize) 
+       {
+               // Adjust nbSeriesInChunk to avoid small remainders.
+               // Each node should have at least nbSeriesInChunk (as given to the function).
+
+               // ==> We seek for the largest N such that (double)totalNbSeries / N >= nbSeriesInChunk
+               uint32_t N = totalNbSeries / nbSeriesInChunk + 1;
+               while ((double)totalNbSeries / N < nbSeriesInChunk) N--;
+               // At this point N>=1 is the solution
+               idealNbSeriesInChunk = (double)totalNbSeries / N;
+               nbSeriesInChunk = ceil(idealNbSeriesInChunk);
+       }
+       
+       // Initialize random generator
+       init_rng(1);
+       
+       // Find out my identity in the default communicator
+       int myrank;
+       MPI_Comm_rank(MPI_COMM_WORLD, &myrank);
+
+       if (myrank == 0)
+       {
+               // create temporary folder for intermediate results
+               mkdir(".tmp", S_IRWXU | S_IRGRP | S_IXGRP | S_IROTH | S_IXOTH);
+               
+               master_run(ifileName, totalNbSeries, nbSeriesInChunk, idealNbSeriesInChunk, 
+                       tsLength, nbClusters, randomize, p_for_dissims);
+       }
+       
+       else
+               slave_run(myrank, nbSeriesInChunk, nbClusters);
+
+       MPI_Finalize();
+       return 0;
+}
+
+//main classification task (using clustering result)
+int classif_main(int argc, char** argv)
+{
+       const char* ifileName = argv[1];
+       const char* xmlFileName = argv[2];
+       
+       // 1] load and retrieve info from XML file
+       xmlDoc* doc = xmlReadFile(xmlFileName, NULL, 0);
+
+       // Get the root element node
+       xmlNode* root_element = xmlDocGetRootElement(doc);
+
+       uint32_t p_for_dissims = 0;
+       uint32_t* ranks = NULL;
+       uint32_t nbClusters = 0;
+       char* binFileName;
+       for (xmlNode* cur_node=root_element->children; cur_node; cur_node=cur_node->next) 
+       {
+               if (cur_node->type != XML_ELEMENT_NODE)
+                       continue;
+               if (!strcmp(cur_node->name,"p_for_dissims"))
+                       p_for_dissims = atoi(cur_node->last->content);
+               else if (!strcmp(cur_node->name,"ranks"))
+               {
+                       //first pass: find nbClusters
+                       for (xmlNode* rankNode=cur_node->children; rankNode; rankNode=rankNode->next)
+                       {
+                               if (rankNode->type == XML_ELEMENT_NODE && !strcmp(rankNode->name,"rank"))
+                                       nbClusters++;
+                       }
+                       //second pass: fill ranks (not optimal, but not very important here)
+                       ranks = (uint32_t*) malloc(nbClusters*sizeof(uint32_t));
+                       uint32_t index = 0;
+                       for (xmlNode* rankNode=cur_node->children; rankNode; rankNode=rankNode->next)
+                       {
+                               if (rankNode->type == XML_ELEMENT_NODE && !strcmp(rankNode->name,"rank"))
+                                       ranks[index++] = atoi(rankNode->last->content) - 1;
+                       }
+               }
+               else if (!strcmp(cur_node->name,"file"))
+               {
+                       binFileName = (char*) malloc(strlen(cur_node->last->content)+1);
+                       strcpy(binFileName, cur_node->last->content);
+               }
+       }
+
+       xmlFreeDoc(doc);
+       xmlCleanupParser();
+
+       uint32_t tsLength1 = get_tsLength(ifileName);
+       uint32_t tsLength2 = get_tsLength(binFileName);
+       if (tsLength1 != tsLength2)
+       {
+               fprintf(stderr,"Warning: nbValues do not match. Data will be truncated.\n");
+               if (tsLength1 > tsLength2)
+                       tsLength1 = tsLength2;
+       }
+       uint32_t nbValues = (tsLength1 - 4) / 3;
+       
+       // 2] Classify all series by batches of CURVES_PER_REQUEST
+       uint32_t nbSeries = get_nbSeries(ifileName);
+       PowerCurve* medoids = deserialize(binFileName, NULL, ranks, nbClusters);
+       free(binFileName);
+       free(ranks);
+       ranks = (uint32_t*)malloc(CURVES_PER_REQUEST*sizeof(uint32_t));
+       
+       uint32_t smallestNonProcessedIndex = 0;
+       double DISTOR = 0.0;
+       while (smallestNonProcessedIndex < nbSeries)
+       {
+               uint32_t lowerBound = smallestNonProcessedIndex;
+               uint32_t upperBound = smallestNonProcessedIndex + CURVES_PER_REQUEST;
+               if (upperBound > nbSeries)
+                       upperBound = nbSeries;
+               for (uint32_t i=0; i<upperBound-lowerBound; i++)
+                       ranks[i] = lowerBound + i;
+               PowerCurve* data = deserialize(ifileName, NULL, ranks, upperBound-lowerBound);
+               uint32_t* labels = get_class(data, upperBound-lowerBound, medoids, nbClusters, 
+                       nbValues, p_for_dissims, &DISTOR);
+               // send labels to standard output
+               for (uint32_t i=0; i<upperBound-lowerBound; i++)
+               {
+                       free(data[i].values);
+                       fprintf(stdout, "%u\n",labels[i]);
+               }
+               free(data);
+               free(labels);
+               smallestNonProcessedIndex += (upperBound-lowerBound);
+       }
+       for (uint32_t i=0; i<nbClusters; i++)
+               free(medoids[i].values);
+       free(medoids);
+       free(ranks);
+       fprintf(stderr, "DISTOR = %g\n",DISTOR);
+       return 0;
+}
+
+int main(int argc, char** argv)
+{
+       if (argc <= 1)
+       {
+               fprintf(stderr, "No argument provided. Exit.\n");
+               return 1;
+       }
+       
+       if (!strcmp(argv[1], "serialize"))
+               return serialize_main(argc-1, argv+1);
+       if (!strcmp(argv[1], "deserialize"))
+               return deserialize_main(argc-1, argv+1);
+       if (!strcmp(argv[1], "cluster"))
+               return cluster_main(argc-1, argv+1);
+       if (!strcmp(argv[1], "classif"))
+               return classif_main(argc-1, argv+1);
+
+       fprintf(stderr, "Unknown first argument.\n");
+       return 1;
+}

diff --git a/code/src/stage2/.gitkeep b/code/src/stage2/.gitkeep
new file mode 100644 (file)
index 0000000..e69de29

diff --git a/code/test/lut.h b/code/test/lut.h
new file mode 100644 (file)
index 0000000..4e36e51
--- /dev/null
+++ b/code/test/lut.h
@@ -0,0 +1,15 @@
+#ifndef PPAM_LUT_H
+#define PPAM_LUT_H
+
+#include <stdio.h>
+
+// light, minimalist unit-testing "framework"
+
+#define LUT_ASSERT(condition)                                            \
+    do {                                                                 \
+        if ( !(condition) ) {                                            \
+            printf("Failure in file %s at line %i\n",__FILE__,__LINE__); \
+        }                                                                \
+    } while (0)
+
+#endif

diff --git a/code/test/stage1/Algorithm/t.compute_coefficients.c b/code/test/stage1/Algorithm/t.compute_coefficients.c
new file mode 100644 (file)
index 0000000..3ef3422
--- /dev/null
+++ b/code/test/stage1/Algorithm/t.compute_coefficients.c
@@ -0,0 +1,100 @@
+#include "Algorithm/compute_coefficients.h"
+#include "Util/types.h"
+#include "lut.h"
+#include <math.h>
+#include <stdlib.h>
+
+void t_compute_coefficients1()
+{      
+       uint32_t nbSeries = 3;
+       uint32_t nbValues = 10;
+       Real curves[] =
+       {
+               1.0,2.0,3.0,4.0,1.0,2.0,3.0,4.0,1.0,2.0,
+               3.0,4.0,1.0,2.0,3.0,4.0,1.0,1.0,2.0,3.0,
+               3.0,1.0,0.0,8.0,2.0,4.0,2.0,0.0,3.0,3.0
+       };
+
+       PowerCurve* powerCurves = (PowerCurve*)malloc(nbSeries*sizeof(PowerCurve));
+       for (int i=0; i<nbSeries; i++)
+       {
+               powerCurves[i].ID = i;
+               powerCurves[i].values = curves + i * nbValues;
+       }
+       
+       // Expected energy matrix: (to change...)
+       // 1.2829311 2.8197073 2.7653092 0.5390868
+       // 1.433019 3.319643 2.078569 1.248209
+       // 1.4532363 6.1433038 5.2052217 0.3447528
+       
+       uint32_t nbReducedCoordinates = 4; //2^4 > 10, 2^3 < 10
+       Real* reducedCoordinates = (Real*)malloc(nbSeries * nbReducedCoordinates * sizeof(Real));
+       Real epsilon = 1e-4;
+       compute_coefficients(powerCurves, nbSeries, nbValues, reducedCoordinates, 0, nbReducedCoordinates);
+       free(powerCurves);
+
+       //~ LUT_ASSERT(fabs(reducedCoordinates[0] - 1.2829311) < epsilon);
+       //~ LUT_ASSERT(fabs(reducedCoordinates[1] - 2.8197073) < epsilon);
+       //~ LUT_ASSERT(fabs(reducedCoordinates[2] - 2.7653092) < epsilon);
+       //~ LUT_ASSERT(fabs(reducedCoordinates[3] - 0.5390868) < epsilon);
+//~ 
+       //~ LUT_ASSERT(fabs(reducedCoordinates[4] - 1.433019) < epsilon);
+       //~ LUT_ASSERT(fabs(reducedCoordinates[5] - 3.319643) < epsilon);
+       //~ LUT_ASSERT(fabs(reducedCoordinates[6] - 2.078569) < epsilon);
+       //~ LUT_ASSERT(fabs(reducedCoordinates[7] - 1.248209) < epsilon);
+//~ 
+       //~ LUT_ASSERT(fabs(reducedCoordinates[8] - 1.4532363) < epsilon);
+       //~ LUT_ASSERT(fabs(reducedCoordinates[9] - 6.1433038) < epsilon);
+       //~ LUT_ASSERT(fabs(reducedCoordinates[10] - 5.2052217) < epsilon);
+       //~ LUT_ASSERT(fabs(reducedCoordinates[11] - 0.3447528) < epsilon);
+       
+       free(reducedCoordinates);
+}
+
+void t_compute_coefficients2()
+{      
+       uint32_t nbSeries = 3;
+       uint32_t nbValues = 20;
+       Real curves[] =
+       {
+               0.07291223,0.3468863,0.8648239,0.2348877,0.4315312,0.7036144,0.2431289,0.01040031,0.1178515,0.03080914,0.3673594,0.3738354,0.6695186,0.9140619,0.3102869,0.6374112,0.843919,0.2661967,0.1571974,0.7748992,
+               0.8818654,0.6703627,0.8847847,0.03184918,0.997876,0.7612137,0.6387965,0.296034,0.5018912,0.7942868,0.1095461,0.3727642,0.2351644,0.5057783,0.7287164,0.340264,0.08904832,0.5050351,0.1371493,0.8821361,
+               0.1844872,0.5861217,0.7114864,0.8779052,0.5999996,0.2707162,0.9586406,0.6902478,0.2514943,0.8113025,0.2820882,0.5661663,0.9571422,0.6838519,0.998652,0.6126693,0.9178886,0.7810725,0.7895782,0.181061
+       };
+
+       PowerCurve* powerCurves = (PowerCurve*)malloc(nbSeries*sizeof(PowerCurve));
+       for (int i=0; i<nbSeries; i++)
+       {
+               powerCurves[i].ID = i;
+               powerCurves[i].values = curves + i * nbValues;
+       }
+       
+       //~ // Expected energy matrix:
+       //~ // ...TODO
+       
+       uint32_t nbReducedCoordinates = 5; //2^5 > 20, 2^4 < 20
+       Real* reducedCoordinates = (Real*)malloc(nbSeries * nbReducedCoordinates * sizeof(Real));
+       Real epsilon = 1e-4;
+       compute_coefficients(powerCurves, nbSeries, nbValues, reducedCoordinates, 0, nbReducedCoordinates);
+       free(powerCurves);
+
+       //~ LUT_ASSERT(fabs(reducedCoordinates[0] - 1.2829311) < epsilon);
+       //~ LUT_ASSERT(fabs(reducedCoordinates[1] - 2.8197073) < epsilon);
+       //~ LUT_ASSERT(fabs(reducedCoordinates[2] - 2.7653092) < epsilon);
+       //~ LUT_ASSERT(fabs(reducedCoordinates[3] - 0.5390868) < epsilon);
+       //~ LUT_ASSERT(fabs(reducedCoordinates[4] - 0.5390868) < epsilon);
+//~ 
+       //~ LUT_ASSERT(fabs(reducedCoordinates[5] - 3.319643) < epsilon);
+       //~ LUT_ASSERT(fabs(reducedCoordinates[6] - 2.078569) < epsilon);
+       //~ LUT_ASSERT(fabs(reducedCoordinates[7] - 1.248209) < epsilon);
+       //~ LUT_ASSERT(fabs(reducedCoordinates[8] - 1.4532363) < epsilon);
+       //~ LUT_ASSERT(fabs(reducedCoordinates[9] - 6.1433038) < epsilon);
+//~ 
+       //~ LUT_ASSERT(fabs(reducedCoordinates[10] - 5.2052217) < epsilon);
+       //~ LUT_ASSERT(fabs(reducedCoordinates[11] - 0.3447528) < epsilon);
+       //~ LUT_ASSERT(fabs(reducedCoordinates[12] - 0.3447528) < epsilon);
+       //~ LUT_ASSERT(fabs(reducedCoordinates[13] - 1.248209) < epsilon);
+       //~ LUT_ASSERT(fabs(reducedCoordinates[14] - 1.248209) < epsilon);
+
+       free(reducedCoordinates);
+}

diff --git a/code/test/stage1/Algorithm/t.pam.c b/code/test/stage1/Algorithm/t.pam.c
new file mode 100644 (file)
index 0000000..06f1fe5
--- /dev/null
+++ b/code/test/stage1/Algorithm/t.pam.c
@@ -0,0 +1,541 @@
+#include "Algorithm/pam.h"
+#include <stdlib.h>
+#include "Util/types.h"
+#include "lut.h"
+#include <math.h>
+
+// 3 "regular flowers", dissimilarity = euclidian
+void t_pam1()
+{
+       uint32_t nbClusters = 3;
+       Result_t* result = (Result_t*)malloc(sizeof(Result_t));
+       result->medoids_ranks = (uint32_t*)malloc(nbClusters*sizeof(uint32_t));
+       result->nbClusters = nbClusters;
+       
+//     double M[] = 
+//     {
+//             -4,4,
+//             -3,5,
+//             -5,5,
+//             -5,3,
+//             -3,3,
+//             0,0,
+//             1,1,
+//             -1,1,
+//             -1,-1,
+//             1,-1,
+//             4,-4,
+//             5,-3,
+//             3,-3,
+//             3,-5,
+//             5,-5
+//     };
+
+       uint32_t nbSeries = 15;
+       Real dissimilarities[] =
+       {
+               0,1.414214,1.414214,1.414214,1.414214,5.656854,5.830952,4.242641,5.830952,7.071068,11.31371,11.40175,9.899495,11.40175,12.72792,
+               1.414214,0,2,2.828427,2,5.830952,5.656854,4.472136,6.324555,7.211103,11.40175,11.31371,10,11.6619,12.80625,
+               1.414214,2,0,2,2.828427,7.071068,7.211103,5.656854,7.211103,8.485281,12.72792,12.80625,11.31371,12.80625,14.14214,
+               1.414214,2.828427,2,0,2,5.830952,6.324555,4.472136,5.656854,7.211103,11.40175,11.6619,10,11.31371,12.80625,
+               1.414214,2,2.828427,2,0,4.242641,4.472136,2.828427,4.472136,5.656854,9.899495,10,8.485281,10,11.31371,
+               5.656854,5.830952,7.071068,5.830952,4.242641,0,1.414214,1.414214,1.414214,1.414214,5.656854,5.830952,4.242641,5.830952,7.071068,
+               5.830952,5.656854,7.211103,6.324555,4.472136,1.414214,0,2,2.828427,2,5.830952,5.656854,4.472136,6.324555,7.211103,
+               4.242641,4.472136,5.656854,4.472136,2.828427,1.414214,2,0,2,2.828427,7.071068,7.211103,5.656854,7.211103,8.485281,
+               5.830952,6.324555,7.211103,5.656854,4.472136,1.414214,2.828427,2,0,2,5.830952,6.324555,4.472136,5.656854,7.211103,
+               7.071068,7.211103,8.485281,7.211103,5.656854,1.414214,2,2.828427,2,0,4.242641,4.472136,2.828427,4.472136,5.656854,
+               11.31371,11.40175,12.72792,11.40175,9.899495,5.656854,5.830952,7.071068,5.830952,4.242641,0,1.414214,1.414214,1.414214,1.414214,
+               11.40175,11.31371,12.80625,11.6619,10,5.830952,5.656854,7.211103,6.324555,4.472136,1.414214,0,2,2.828427,2,
+               9.899495,10,11.31371,10,8.485281,4.242641,4.472136,5.656854,4.472136,2.828427,1.414214,2,0,2,2.828427,
+               11.40175,11.6619,12.80625,11.31371,10,5.830952,6.324555,7.211103,5.656854,4.472136,1.414214,2.828427,2,0,2,
+               12.72792,12.80625,14.14214,12.80625,11.31371,7.071068,7.211103,8.485281,7.211103,5.656854,1.414214,2,2.828427,2,0
+       };
+
+       pam(dissimilarities, nbSeries, nbClusters, 0, NSTART, MAXITER, result);
+       // check that centers (medoids_ranks) span {0, 5, 10}
+       uint32_t* ctrs = result->medoids_ranks;
+       LUT_ASSERT(ctrs[0] != ctrs[1] && ctrs[1] != ctrs[2] && ctrs[2] != ctrs[0]);
+       LUT_ASSERT(ctrs[0] == 0 || ctrs[1] == 0 || ctrs[2] == 0);
+       LUT_ASSERT(ctrs[0] == 5 || ctrs[1] == 5 || ctrs[2] == 5);
+       LUT_ASSERT(ctrs[0] == 10 || ctrs[1] == 10 || ctrs[2] == 10);
+
+       free(result->medoids_ranks);
+       free(result);
+}
+
+// 4 well-separated Gaussian clusters, dissimilarity = euclidian
+void t_pam2()
+{
+       uint32_t nbClusters = 4;
+       Result_t* result = (Result_t*)malloc(sizeof(Result_t));
+       result->medoids_ranks = (uint32_t*)malloc(nbClusters*sizeof(uint32_t));
+       result->nbClusters = nbClusters;
+
+//     double M[] =
+//     {
+//             -4.450371,-4.543001,
+//             -4.711869,-4.961091,
+//             -5.083656,-4.674564,
+//             -3.586104,-5.887045,
+//             -3.185154,-3.541619,
+//             -5.033892,-4.596002,
+//             -3.004485,-5.171559,
+//             -4.528517,-4.003823,
+//             -3.721287,-5.419952,
+//             -4.121808,-4.629665,
+//             -4.05129,-4.85515,
+//             -4.035312,-5.660147,
+//             -3.290654,-4.240134,
+//             -1.902941,-4.663231,
+//             -3.070627,-3.537133,
+//             -5.799731,-6.077648,
+//             -2.999374,-4.396087,
+//             -3.826953,-3.367948,
+//             -6.482025,-2.427264,
+//             -5.412339,-3.98535,
+//             -3.37746,-3.841064,
+//             -4.712918,-3.058541,
+//             -2.440538,-4.408247,
+//             -3.116167,-6.130969,
+//             -4.604153,-3.708026,
+//             -3.472353,-3.137196,
+//             -3.843901,-3.447817,
+//             -3.340786,-2.312214,
+//             -4.328582,-4.133865,
+//             -2.906439,-5.249392,
+//             -3.55544,-4.535076,
+//             -4.346427,-4.156633,
+//             -2.092725,-4.128729,
+//             -5.015867,-5.179254,
+//             -4.543845,-2.916083,
+//             -4.145448,-5.715884,
+//             -4.390567,-2.307922,
+//             -3.003025,-5.588462,
+//             -2.844272,-4.292232,
+//             -3.51101,-5.665364,
+//             -4.669003,-3.983029,
+//             -4.040262,-3.338078,
+//             -4.002328,-3.652771,
+//             -3.732904,-6.027206,
+//             -4.094534,-3.500277,
+//             -3.587201,-4.003284,
+//             -4.816506,-4.769324,
+//             -3.062788,-3.027322,
+//             -2.899946,-6.049017,
+//             -4.912952,-4.773183,
+//             -1.916896,-0.009493825,
+//             2.634858,-0.4243543,
+//             0.3020768,1.64798,
+//             1.319387,0.4383175,
+//             -0.001776739,-0.3686283,
+//             -0.3792117,-0.614869,
+//             -0.7154037,-0.6211681,
+//             -1.422143,0.2300399,
+//             0.1448215,0.2528107,
+//             -0.665172,-1.395703,
+//             1.447993,0.2860408,
+//             -0.3756387,-0.06096208,
+//             -1.001823,-0.2453904,
+//             -0.05310829,-2.201463,
+//             -0.6424461,-0.4816693,
+//             0.9660234,-0.6773616,
+//             0.3242067,0.6265039,
+//             -1.54016,0.3410867,
+//             -0.151697,0.9412011,
+//             -0.1419021,1.402804,
+//             0.6756108,-2.120431,
+//             -0.4478024,-0.7631725,
+//             0.640236,1.548211,
+//             1.094596,1.688888,
+//             -0.4296057,-0.3780608,
+//             -0.3501862,-0.4554224,
+//             -0.7654625,-0.5809421,
+//             -0.3401964,-0.455078,
+//             1.656617,-0.7471582,
+//             1.436579,-0.3640174,
+//             0.2339464,0.3475537,
+//             0.08126267,1.06486,
+//             0.2915553,-0.236505,
+//             0.4851901,-1.010106,
+//             -0.07553644,-2.15231,
+//             -0.4303397,0.9054603,
+//             0.004220171,1.033742,
+//             -0.3602884,1.916468,
+//             -0.4638079,-1.552088,
+//             -1.60057,-1.106041,
+//             -0.7134006,-1.567929,
+//             -1.337527,-3.620209,
+//             -0.1994646,-0.1307016,
+//             -0.2420102,-0.1121753,
+//             -0.536283,0.03036439,
+//             2.467503,0.3452919,
+//             -0.3630185,1.174053,
+//             0.1055285,-0.2248235,
+//             1.267688,-0.3149153,
+//             -1.620448,-0.6095385,
+//             5.14672,4.479654,
+//             4.129114,5.259524,
+//             5.365162,3.888272,
+//             3.454389,2.743306,
+//             2.861091,2.602548,
+//             3.93366,4.617158,
+//             4.57284,3.714136,
+//             4.092174,3.671644,
+//             4.50261,1.516262,
+//             4.317581,3.683757,
+//             4.259846,2.438663,
+//             4.119361,6.446651,
+//             5.691461,3.578193,
+//             3.861858,3.574928,
+//             3.537764,4.3348,
+//             2.586984,4.144694,
+//             4.565765,3.690908,
+//             4.949011,3.678565,
+//             4.21298,4.516202,
+//             4.258206,3.375235,
+//             3.862015,3.229653,
+//             2.276514,3.281311,
+//             3.461244,5.803409,
+//             5.741595,4.279209,
+//             3.847961,3.979272,
+//             2.904032,5.174558,
+//             4.973815,3.879027,
+//             2.342122,2.615265,
+//             2.576959,5.048676,
+//             4.996508,3.129088,
+//             4.908488,5.593342,
+//             4.494416,4.222817,
+//             6.292328,2.357233,
+//             3.34451,3.270198,
+//             2.269291,3.963629,
+//             4.25654,3.247725,
+//             2.894098,3.785049,
+//             2.346439,4.385733,
+//             5.85847,6.073889,
+//             1.42734,4.093241,
+//             4.07797,2.895063,
+//             4.444542,2.00364,
+//             5.394777,5.063008,
+//             2.639821,4.398103,
+//             4.273526,2.889649,
+//             3.477858,5.404986,
+//             5.729747,3.629496,
+//             3.810896,4.770437,
+//             3.71945,5.236858,
+//             3.833841,3.280717,
+//             4.152189,-5.99135,
+//             3.19188,-5.967943,
+//             5.042668,-6.489929,
+//             5.237402,-4.916319,
+//             5.335625,-3.950791,
+//             4.027703,-4.435844,
+//             3.654064,-5.122268,
+//             5.109319,-3.817966,
+//             5.21631,-4.550999,
+//             4.518432,-6.290373,
+//             4.224753,-3.722504,
+//             4.315041,-4.396765,
+//             5.56141,-4.3007,
+//             4.428661,-3.642649,
+//             3.759849,-5.697695,
+//             3.478439,-5.001031,
+//             4.693304,-5.403166,
+//             4.822672,-3.103692,
+//             4.885982,-3.900518,
+//             5.715825,-4.795573,
+//             6.714095,-5.538454,
+//             4.872663,-6.734268,
+//             5.04218,-6.48153,
+//             5.145617,-4.279071,
+//             3.550852,-5.84931,
+//             4.806485,-4.733755,
+//             4.280439,-4.219329,
+//             4.628427,-5.355216,
+//             4.133676,-5.390665,
+//             4.283339,-4.694953,
+//             5.662802,-4.493008,
+//             3.031885,-4.058671,
+//             4.413487,-4.646903,
+//             6.535346,-4.918966,
+//             3.408803,-3.448405,
+//             4.701184,-6.628794,
+//             5.478372,-4.380599,
+//             5.902022,-6.036273,
+//             4.379025,-2.736512,
+//             4.590189,-3.72093,
+//             4.625894,-5.511869,
+//             5.09324,-4.854936,
+//             5.402295,-7.326092,
+//             7.355636,-3.345965,
+//             4.646836,-5.001939,
+//             5.450266,-7.242952,
+//             4.197233,-5.91857,
+//             3.848639,-4.45381,
+//             5.578822,-4.595297,
+//             5.741669,-4.29464
+//     };
+
+       uint32_t nbSeries = 200;
+       Real dissimilarities[] =
+       {
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+               10.26218,10.41518,10.84251,9.13753,9.39523,10.81314,8.704797,10.49133,9.350974,9.922392,9.796998,9.616728,9.242326,7.7926,9.291863,11.31019,8.916337,10.05398,12.86742,11.34055,9.460528,10.99089,8.38453,8.638304,10.65772,9.821933,10.03915,10.07942,10.2612,8.591205,9.404006,10.27135,8.160582,10.66765,10.89055,9.716463,11.00893,8.613679,8.803755,9.09908,10.6314,10.26246,10.11143,9.263296,10.25236,9.600586,10.56056,9.499664,8.435136,10.65345,10.32463,7.376978,10.27388,8.721586,8.773887,8.826908,9.047846,10.15262,9.183366,8.461023,8.52666,9.247819,9.518158,7.463494,9.101433,7.950812,9.391742,10.31425,9.91778,10.29667,7.002682,8.762121,10.02102,9.937285,9.038785,8.928371,9.111403,8.922146,7.522441,7.964259,9.210091,9.89171,8.700724,7.968711,7.513264,10.04879,9.907729,10.84701,8.207449,9.347511,8.378346,7.69405,9.083147,9.124143,9.420186,8.153424,10.22938,8.821584,8.092692,9.695214,11.72654,12.57209,11.13155,10.18376,10.18026,11.95668,10.99216,10.99876,8.810329,10.98526,9.754526,13.75415,10.82383,10.93387,11.73465,11.7421,10.96958,10.93301,11.82407,10.68489,10.59236,10.9924,13.19711,11.52584,11.33604,12.67588,11.13218,10.33659,12.623,10.38196,12.84772,11.50554,9.637045,10.72197,11.64929,10.55838,11.32037,12.03578,13.3231,12.02885,10.23047,9.301126,12.30609,11.97551,10.2007,12.80081,10.87604,12.12473,12.59926,10.64709,1.803195,2.593445,0.8562594,2.33635,3.294157,3.14699,2.779145,3.441914,2.702101,1.332562,3.727659,3.064232,2.94435,3.74244,2.290269,2.985685,1.989423,4.186568,3.389732,2.461745,2.121927,0.7696657,0.8638857,2.979497,2.355847,2.590468,3.242035,2.058875,2.272527,2.802502,2.758145,3.998526,2.795422,2.564822,4.308847,0.9686663,2.862491,1.288471,4.632015,3.625517,1.917352,2.414558,0.09598607,4.33785,2.380681,0,1.823206,3.216291,2.650774,2.962678,
+               8.756327,8.960405,9.363891,7.783401,7.755613,9.325388,7.240357,8.933363,7.934203,8.418297,8.31679,8.236601,7.673695,6.228001,7.648074,9.99823,7.35589,8.419812,11.23547,9.802103,7.854426,9.357914,6.807429,7.316485,9.07474,8.158345,8.412162,8.356288,8.710609,7.135122,7.875151,8.723449,6.539657,9.242716,9.242369,8.345143,9.31596,7.207822,7.226878,7.712401,9.075047,8.632223,8.506859,7.930882,8.637219,8.016591,9.086708,7.814552,7.098378,9.181906,8.502926,5.712042,8.510283,6.977966,6.959421,7.005219,7.224712,8.329634,7.382952,6.640731,6.786421,7.4312,7.695138,5.64644,7.2789,6.15719,7.605151,8.49123,8.122171,8.510618,5.179545,6.939343,8.270734,8.215824,7.218371,7.108094,7.288252,7.101972,5.761791,6.202763,7.414307,8.10614,6.894939,6.154046,5.695724,8.245109,8.118867,9.06415,6.38682,7.534916,6.560671,5.992999,7.26845,7.308974,7.602368,6.498302,8.432152,7.011476,6.323226,7.875991,10.44148,11.1783,9.876144,8.69367,8.625238,10.53902,9.640026,9.590789,7.441101,9.603081,8.357468,12.36547,9.613596,9.49942,10.27456,10.19128,9.616542,9.626535,10.43478,9.294005,9.154362,9.398243,11.74506,10.31406,9.904003,11.16825,9.828325,8.733142,11.08629,9.082893,11.53386,10.14574,8.536881,9.22825,10.06851,9.166487,9.790729,10.4692,12.10697,10.38791,8.81444,7.926069,11.04668,10.43356,8.808549,11.34638,9.670272,10.69599,11.16566,9.206461,0.08559222,1.006565,1.020397,1.444457,2.273343,1.492387,0.963914,2.290073,1.705511,0.4913309,2.196239,1.526357,2.116242,2.287657,0.4899909,1.165566,0.7153516,2.883524,2.132348,1.888715,2.545403,1.059041,1.015312,1.89404,0.6500814,1.332281,1.701277,0.7094334,0.5317172,1.226642,2.044533,2.194825,1.289924,2.542829,2.59294,0.8708527,2.001667,1.708847,3.187247,2.232495,0.5908941,1.390736,1.852914,4.073549,1.020958,1.823206,0,1.50567,1.91307,2.241078,
+               8.299489,8.575525,8.935022,7.571628,7.092695,8.883668,6.890607,8.389233,7.63133,7.972386,7.910117,7.975709,7.142489,5.755391,6.979723,9.784063,6.848256,7.752019,10.52756,9.272818,7.252032,8.674504,6.289342,7.163895,8.485628,7.43844,7.758041,7.501617,8.183478,6.801767,7.404525,8.200452,5.95025,8.89414,8.532197,8.093099,8.514068,6.944979,6.69486,7.458706,8.530643,7.967409,7.891726,7.743085,8.000202,7.449475,8.670887,7.057101,6.934557,8.76741,7.279652,4.208298,7.057615,5.50727,5.613769,5.710708,5.959834,7.051212,5.989202,5.452202,5.313123,6.094393,6.421664,4.505185,5.995643,4.750898,6.183139,7.213195,6.71631,7.086913,3.938624,5.663939,6.80574,6.731826,5.9089,5.798037,6.024038,5.791044,4.3063,4.748098,6.009916,6.681978,5.51711,4.813718,4.549291,6.857946,6.700208,7.635149,5.197806,6.395422,5.398195,5.252733,5.922533,5.965165,6.27179,4.993887,7.029288,5.647583,4.877679,6.685008,9.02728,9.717382,8.478807,7.207905,7.125127,9.071366,8.199988,8.129102,6.005784,8.151067,6.904728,10.90382,8.240695,8.028749,8.794106,8.690572,8.176227,8.206481,8.977408,7.839751,7.683474,7.893267,10.26453,8.935821,8.433082,9.674593,8.408459,7.227822,9.587199,7.669285,10.1029,8.700625,7.236154,7.740442,8.564322,7.712329,8.29397,8.966277,10.71783,8.883399,7.35245,6.484887,9.641595,8.934069,7.35574,9.865766,8.299301,9.224324,9.691529,7.73454,1.567219,1.650433,2.3604,1.463755,1.569763,0.1799629,0.6962006,1.411953,1.37112,1.954888,0.8223568,0.4698773,1.719601,0.9971994,1.24705,0.6606804,1.270723,1.6648,1.175675,1.898207,3.063869,2.499823,2.352911,1.308697,1.426919,0.9979176,0.4913583,1.191891,0.979257,0.4971067,1.814586,0.9073148,0.5969412,2.726677,1.097404,2.336106,1.631377,2.592407,1.797337,1.042597,1.312865,1.307645,3.265556,3.677819,0.9682794,3.216291,1.50567,0,1.735959,1.89971,
+               10.02933,10.29719,10.66277,9.255511,8.827089,10.61271,8.60263,10.12463,9.336599,9.700691,9.633618,9.672925,8.876584,7.482071,8.713936,11.4747,8.580509,9.485515,12.25416,11.00807,8.987984,10.40584,8.021542,8.82956,10.22156,9.167869,9.492335,9.207165,9.918144,8.510435,9.134461,9.934938,7.685722,10.61077,10.261,9.788623,10.22843,8.639125,8.428544,9.1526,10.2661,9.700896,9.627398,9.421179,9.735137,9.185121,10.39678,8.782708,8.602488,10.49328,8.787228,5.105261,8.174506,6.593941,7.000558,7.165331,7.443855,8.502787,7.282342,7.016043,6.394623,7.48437,7.888382,6.119565,7.458291,6.052118,7.407981,8.663013,7.968165,8.288782,5.492399,7.141805,7.882406,7.720056,7.340728,7.2313,7.507662,7.223309,5.494712,5.921309,7.280073,7.890534,6.852318,6.228859,6.159542,8.146678,7.922264,8.813405,6.765686,7.982392,6.982623,6.984746,7.302137,7.34714,7.667545,5.838641,8.28196,7.00414,6.075158,8.228958,9.085232,9.960881,8.48626,7.639915,7.693831,9.358198,8.370106,8.399549,6.205593,8.374572,7.156556,11.13798,8.174266,8.348685,9.16038,9.237886,8.347902,8.297798,9.213303,8.079196,8.011071,8.540854,10.61213,8.875998,8.74752,10.12939,8.495893,7.903697,10.10037,7.746303,10.21067,8.884541,6.989046,8.176684,9.176503,7.953705,8.799883,9.54501,10.67285,9.629408,7.639244,6.695712,9.660058,9.461446,7.597908,10.2186,8.226177,9.531135,10.00643,8.067004,1.996058,2.753479,1.969033,0.4686397,0.6888631,1.559294,1.995593,0.9081171,0.3652088,1.999428,1.610984,1.279281,0.2951107,1.493456,2.126957,2.139212,1.198663,1.672318,0.9811959,0.2426529,1.475937,2.252523,1.961086,0.5363443,2.384368,0.7846497,1.351721,1.216851,1.649563,1.29931,0.1323465,2.602855,1.166477,1.009802,2.454454,2.214804,0.2370344,1.476777,2.212374,1.319816,1.322186,0.5506379,2.736494,2.172072,1.016836,2.650774,1.91307,1.735959,0,0.3419266,
+               10.19507,10.47476,10.83199,9.462721,8.958527,10.77977,8.790005,10.2743,9.529631,9.869165,9.808987,9.871878,9.032487,7.65349,8.844794,11.67831,8.741631,9.613391,12.36551,11.15829,9.130402,10.52741,8.182996,9.04618,10.36244,9.286435,9.622903,9.29629,10.07153,8.700651,9.300218,10.08904,7.83615,10.79385,10.37749,9.988744,10.32518,8.83989,8.585941,9.353659,10.41533,9.82859,9.765115,9.631683,9.868227,9.333418,10.56884,8.895198,8.817899,10.66536,8.775881,4.963002,8.056295,6.477458,6.957064,7.141841,7.428875,8.473071,7.21138,7.032172,6.278398,7.439454,7.865819,6.161236,7.436106,5.990951,7.318917,8.632206,7.88326,8.190072,5.512906,7.126066,7.756515,7.57614,7.309187,7.200714,7.492283,7.192449,5.410386,5.829545,7.203122,7.795154,6.795013,6.198285,6.199149,8.070609,7.830069,8.706994,6.784507,8.004726,7.007344,7.111249,7.255029,7.300508,7.623539,5.678832,8.195963,6.951941,5.987881,8.232906,8.794441,9.689292,8.191569,7.400292,7.474552,9.093351,8.093618,8.135263,5.941536,8.104495,6.89443,10.86311,7.872993,8.09097,8.906427,9.009683,8.071662,8.012509,8.942473,7.812019,7.755519,8.330806,10.35234,8.573848,8.487859,9.885236,8.209654,7.70089,9.864732,7.461032,9.923022,8.608293,6.674627,7.935562,8.958594,7.687189,8.566798,9.320755,10.36919,9.43239,7.379683,6.430464,9.364075,9.229585,7.332765,9.9603,7.924144,9.268414,9.743656,7.811903,2.324925,3.049814,2.303887,0.8004816,0.5320745,1.719773,2.245676,0.7918867,0.5845699,2.340782,1.621226,1.430279,0.1803605,1.465975,2.428204,2.370906,1.525745,1.504298,0.9420895,0.5015995,1.578824,2.58978,2.296034,0.5962549,2.686387,1.033146,1.463169,1.537572,1.945999,1.512275,0.2134713,2.720038,1.374102,1.009805,2.481608,2.55556,0.2769731,1.749,2.069919,1.286487,1.651242,0.8569664,3.050389,1.872131,1.30343,2.962678,2.241078,1.89971,0.3419266,0
+       };
+
+       pam(dissimilarities, nbSeries, nbClusters, 0, NSTART, MAXITER, result);
+
+       // Label items
+       uint32_t* labels = (uint32_t*)malloc(nbSeries*sizeof(uint32_t));
+       uint32_t* ctrs = result->medoids_ranks;
+
+       // DEBUG:
+       //printf("CTRS: %f,%f %f,%f %f,%f %f,%f\n",N[2*ctrs[0]],N[2*ctrs[0]+1],N[2*ctrs[1]],N[2*ctrs[1]+1],N[2*ctrs[2]],N[2*ctrs[2]+1],N[2*ctrs[3]],N[2*ctrs[3]+1]);
+
+       for (uint32_t i=0; i<nbSeries; i++)
+       {
+               Real minDissim = INFINITY;
+               uint32_t bestClust = 0;
+               for (uint32_t j=0; j<nbClusters; j++)
+               {
+                       if (dissimilarities[i*nbSeries + ctrs[j]] < minDissim)
+                       {
+                               minDissim = dissimilarities[i*nbSeries + ctrs[j]];
+                               bestClust = j;
+                       }
+               }
+               labels[i] = bestClust;
+       }
+
+       // Check that clusters composition match 'true distribution' well enough
+
+       // Tolerance == +/- 3 series
+       double maxDeltaSeries = 3.0;
+       // labels balancing:
+       for (uint32_t j=0; j<nbClusters; j++)
+       {
+               uint32_t countClusterLabels = 0;
+               for (uint32_t i=0; i<nbSeries; i++)
+               {
+                       if (labels[i] == j)
+                               countClusterLabels++;
+               }
+               LUT_ASSERT(fabs(countClusterLabels - 50.0) <= maxDeltaSeries);
+       }
+
+       // clusters purity:
+       for (uint32_t j=0; j<nbClusters; j++)
+       {
+               uint32_t labelsCount[] = {0,0,0,0};
+               for (uint32_t i=50*j; i<50*j+50; i++)
+                       labelsCount[labels[i]]++;
+               uint32_t maxLabelsCount = 0;
+               for (uint32_t jj=0; jj<nbClusters; jj++)
+               {
+                       if (labelsCount[jj] > maxLabelsCount)
+                               maxLabelsCount = labelsCount[jj];
+               }
+               LUT_ASSERT(50 - maxLabelsCount <= maxDeltaSeries);
+       }
+
+       free(result->medoids_ranks);
+       free(labels);
+       free(result);
+}

diff --git a/code/test/stage1/CMakeLists.txt b/code/test/stage1/CMakeLists.txt
new file mode 100644 (file)
index 0000000..7b89bed
--- /dev/null
+++ b/code/test/stage1/CMakeLists.txt
@@ -0,0 +1,19 @@
+cmake_minimum_required(VERSION 2.8.5)
+project(ppam_mpi_tests)
+
+set(CMAKE_C_FLAGS "-std=gnu99")
+set(CMAKE_C_FLAGS_DEBUG "-g3")
+set(CMAKE_C_FLAGS_RELEASE "-O3")
+
+#already by default... ?!
+include_directories("${CMAKE_SOURCE_DIR}")
+
+#ppam tests
+
+include_directories("${CMAKE_SOURCE_DIR}/../src")
+
+file(GLOB_RECURSE test_ppam_src "${CMAKE_SOURCE_DIR}/*.c")
+add_executable(test_ppam.exe ${test_ppam_src})
+find_library(PPAM_LIBRARY ppam "${CMAKE_BINARY_DIR}")
+#TODO: Rblas ?!
+target_link_libraries(test_ppam.exe m cds ${PPAM_LIBRARY})

diff --git a/code/test/stage1/MPI_Communication/t.pack.c b/code/test/stage1/MPI_Communication/t.pack.c
new file mode 100644 (file)
index 0000000..125fd47
--- /dev/null
+++ b/code/test/stage1/MPI_Communication/t.pack.c
@@ -0,0 +1,106 @@
+#include "lut.h"
+#include <stdlib.h>
+#include "MPI_Communication/pack.h"
+#include "Util/types.h"
+#include <stdint.h>
+#include "Util/utils.h"
+
+// Work_t
+void t_pack1()
+{
+       Work_t* work = (Work_t*)malloc(sizeof(Work_t));
+       work->inputFileName = "../data/inputTest.bin";
+       work->nbSeries = 5;
+       uint32_t ranks[] =
+       {
+               0, 
+               12*65536 + 3*256+11,
+               32*16777216 + 2*65536 + 17*256 + 42, 
+               123,
+               51*16777216 + 77*65536 + 0*256 + 10
+       };
+       work->ranks = ranks;
+       work->nbClusters = 15;
+       work->clustOnMedoids = 0;
+       work->p_for_dissims = 1;
+       
+       // Hard-coded expected packed work
+       unsigned char expectedPackedWork[] =
+       {
+               // --> ../data/inputTest.bin
+               46,46,47,100,97,116,97,47,105,110,112,117,116,84,101,115,116,46,98,105,110,
+               // continue with 256 - strlen("../data/inputTest.bin") zeros...
+               0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
+               0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
+               0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
+               0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
+               0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
+               0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
+               0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
+               0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
+               0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
+               0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
+               0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
+               0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
+               // --> 5, {ranks}+0,0, 15, 0 on 4-bytes integers little-endian
+               5,0,0,0, 0,0,0,0, 11,3,12,0, 42,17,2,32, 123,0,0,0, 10,0,77,51, 0,0,0,0, 0,0,0,0, 
+               15,0,0,0, 0,0,0,0, 1,0,0,0
+       };
+       
+       uint32_t nbSeriesInChunk = 7;
+       uint32_t work_message_length = get_packedWork_length(nbSeriesInChunk);
+       unsigned char packedWork[work_message_length];
+       pack_work(work, nbSeriesInChunk, packedWork);
+       
+       for (uint32_t i=0; i<work_message_length; i++)
+       {
+               LUT_ASSERT(packedWork[i] == expectedPackedWork[i]);
+       }
+       
+       free(work);
+}
+
+// Result_t
+void t_pack2() {
+       
+       Result_t* result = (Result_t*)malloc(sizeof(Result_t));
+       uint32_t nbClusters = result->nbClusters = 5;
+       uint32_t medoids_ID[] =
+       {
+               15*65536 + 13*256+11,
+               11, 
+               17*16777216 + 0*65536 + 14*256 + 42, 
+               123*65536 + 0*256 + 7,
+               51*16777216 + 0*65536 + 0*256 + 10
+       };
+       result->medoids_ID = medoids_ID;
+       uint32_t medoids_ranks[] =
+       {
+               5*65536 + 32,
+               11*256 + 4, 
+               23*16777216 + 42, 
+               35*65536 + 5*256 + 77,
+               1*16777216 + 1*65536 + 1*256 + 10
+       };
+       result->medoids_ranks = medoids_ranks;
+       
+       // Hard-coded expected result
+       unsigned char expectedPackedResult[] =
+       {
+               // 5, {medoids_ID}, {medoids_ranks}
+               5,0,0,0,
+               11,13,15,0, 11,0,0,0, 42,14,0,17, 7,0,123,0, 10,0,0,51,
+               32,0,5,0, 4,11,0,0, 42,0,0,23, 77,5,35,0, 10,1,1,1
+       };
+       
+       uint32_t result_message_length = get_packedResult_length(nbClusters);
+       unsigned char packedResult[result_message_length];
+       pack_result(result, packedResult);
+       
+       for (uint32_t i=0; i<result_message_length; i++)
+       {
+               LUT_ASSERT(packedResult[i] == expectedPackedResult[i]);
+       }
+       
+       free(result);
+}

diff --git a/code/test/stage1/MPI_Communication/t.unpack.c b/code/test/stage1/MPI_Communication/t.unpack.c
new file mode 100644 (file)
index 0000000..90e5ae1
--- /dev/null
+++ b/code/test/stage1/MPI_Communication/t.unpack.c
@@ -0,0 +1,97 @@
+#include "lut.h"
+#include <stdlib.h>
+#include "MPI_Communication/unpack.h"
+#include "Util/types.h"
+#include <stdint.h>
+#include <string.h>
+#include "Util/utils.h"
+
+// Work_t
+void t_unpack1()
+{
+       // Hard-coded packed work
+       unsigned char packedWork[] =
+       {
+               // --> ../data/inputTest.bin
+               46,46,47,100,97,116,97,47,105,110,112,117,116,84,101,115,116,46,98,105,110,
+               // continue with 256 - strlen("../data/inputTest.bin") zeros...
+               0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
+               0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
+               0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
+               0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
+               0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
+               0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
+               0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
+               0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
+               0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
+               0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
+               0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
+               0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
+               // --> 5, {ranks}+0,0, 15, 0 on 4-bytes integers little-endian
+               5,0,0,0, 0,0,0,0, 11,3,12,0, 42,17,2,32, 123,0,0,0, 10,0,77,51, 0,0,0,0, 0,0,0,0,
+               15,0,0,0, 0,0,0,0, 2,0,0,0
+       };
+
+       uint32_t nbSeriesInChunk = 7;
+       Work_t* work = unpack_work(packedWork, nbSeriesInChunk);
+
+       LUT_ASSERT(strcmp(work->inputFileName, "../data/inputTest.bin") == 0);
+       LUT_ASSERT(work->nbSeries == 5);
+       uint32_t ranks[] =
+       {
+               0,
+               12*65536 + 3*256+11,
+               32*16777216 + 2*65536 + 17*256 + 42,
+               123,
+               51*16777216 + 77*65536 + 0*256 + 10
+       };
+       for (uint32_t i=0; i < work->nbSeries; i++)
+       {
+               LUT_ASSERT(work->ranks[i] == ranks[i]);
+       }
+       LUT_ASSERT(work->nbClusters == 15);
+       LUT_ASSERT(work->clustOnMedoids == 0);
+       LUT_ASSERT(work->p_for_dissims == 2);
+       
+       free_work(work);
+}
+
+// Result_t
+void t_unpack2() {
+
+       // Hard-coded packed result
+       unsigned char packedResult[] =
+       {
+               // 5, {medoids_ID}, {medoids_ranks}
+               5,0,0,0,
+               11,13,15,0, 11,0,0,0, 42,14,0,17, 7,0,123,0, 10,0,0,51,
+               32,0,5,0, 4,11,0,0, 42,0,0,23, 77,5,35,0, 10,1,1,1
+       };
+
+       Result_t* result = unpack_result(packedResult);
+
+       LUT_ASSERT(result->nbClusters == 5);
+       uint32_t medoids_ID[] =
+       {
+               15*65536 + 13*256+11,
+               11,
+               17*16777216 + 0*65536 + 14*256 + 42,
+               123*65536 + 0*256 + 7,
+               51*16777216 + 0*65536 + 0*256 + 10
+       };
+       uint32_t medoids_ranks[] =
+       {
+               5*65536 + 32,
+               11*256 + 4,
+               23*16777216 + 42,
+               35*65536 + 5*256 + 77,
+               1*16777216 + 1*65536 + 1*256 + 10
+       };
+       for (uint32_t i=0; i<result->nbClusters; i++)
+       {
+               LUT_ASSERT(result->medoids_ID[i] == medoids_ID[i]);
+               LUT_ASSERT(result->medoids_ranks[i] == medoids_ranks[i]);
+       }
+
+       free_result(result);
+}

diff --git a/code/test/stage1/TimeSeries/t.deserialize.c b/code/test/stage1/TimeSeries/t.deserialize.c
new file mode 100644 (file)
index 0000000..22e0956
--- /dev/null
+++ b/code/test/stage1/TimeSeries/t.deserialize.c
@@ -0,0 +1,94 @@
+#include "TimeSeries/deserialize.h"
+#include "lut.h"
+#include <math.h>
+#include <stdlib.h>
+#include <stdio.h>
+#include "Util/utils.h"
+
+void t_deserialize1()
+{
+       // decode sample_byCols.bin into the toy dataset (4 customers, 3 sample points)
+       const char* ifName = "../data/test/sample_byCols.bin";
+       
+       // check 'header'
+       uint32_t nbSeries = get_nbSeries(ifName);
+       LUT_ASSERT(nbSeries == 4);
+       uint32_t tsLength = get_tsLength(ifName);
+       LUT_ASSERT(tsLength == 13); //3*3+4
+       
+       uint32_t ranks[] =
+       {
+               0, 2, 1, 3
+       };
+       PowerCurve* powerCurves = deserialize(ifName, NULL, ranks, nbSeries);
+
+       Real epsilon = 0.1; //epsilon = 0.1 because raw powers are truncated
+       
+       LUT_ASSERT(powerCurves[0].ID == 12301);
+       LUT_ASSERT(fabs(powerCurves[0].values[0] - 23.051) < epsilon);
+       LUT_ASSERT(fabs(powerCurves[0].values[1] - 33.052) < epsilon);
+       LUT_ASSERT(fabs(powerCurves[0].values[2] - 43.053) < epsilon);
+       
+       LUT_ASSERT(powerCurves[1].ID == 1313);
+       LUT_ASSERT(fabs(powerCurves[1].values[0] - 50.05) < epsilon);
+       LUT_ASSERT(fabs(powerCurves[1].values[1] - 51.05) < epsilon);
+       LUT_ASSERT(fabs(powerCurves[1].values[2] - 52.05) < epsilon);
+       
+       LUT_ASSERT(powerCurves[2].ID == 50000);
+       LUT_ASSERT(fabs(powerCurves[2].values[0] - 150.321) < epsilon);
+       LUT_ASSERT(fabs(powerCurves[2].values[1] - 160.322) < epsilon);
+       LUT_ASSERT(fabs(powerCurves[2].values[2] - 140.323) < epsilon);
+
+       LUT_ASSERT(powerCurves[3].ID == 6300);
+       LUT_ASSERT(fabs(powerCurves[3].values[0] - 500.30) < epsilon);
+       LUT_ASSERT(fabs(powerCurves[3].values[1] - 501.31) < epsilon);
+       LUT_ASSERT(fabs(powerCurves[3].values[2] - 502.32) < epsilon);
+
+       for (int i = 0; i < nbSeries; i++)
+               free(powerCurves[i].values);
+       free(powerCurves);
+}
+
+void t_deserialize2()
+{
+       // decode sample_byRows.bin into the toy dataset (4 customers, 3 sample points)
+       const char* ifName = "../data/test/sample_byRows.bin";
+       
+       // check 'header'
+       uint32_t nbSeries = get_nbSeries(ifName);
+       LUT_ASSERT(nbSeries == 4);
+       uint32_t tsLength = get_tsLength(ifName);
+       LUT_ASSERT(tsLength == 13); //3*3+4
+       
+       uint32_t ranks[] =
+       {
+               0, 2, 1, 3
+       };
+       PowerCurve* powerCurves = deserialize(ifName, NULL, ranks, nbSeries);
+
+       Real epsilon = 0.1; //epsilon = 0.1 because raw powers are truncated
+       
+       LUT_ASSERT(powerCurves[0].ID == 12301);
+       LUT_ASSERT(fabs(powerCurves[0].values[0]/100.0-3 - 23.051) < epsilon);
+       LUT_ASSERT(fabs(powerCurves[0].values[1]/100.0-3 - 33.052) < epsilon);
+       LUT_ASSERT(fabs(powerCurves[0].values[2]/100.0-3 - 43.053) < epsilon);
+       
+       LUT_ASSERT(powerCurves[1].ID == 1313);
+       LUT_ASSERT(fabs(powerCurves[1].values[0]/100.0-3 - 50.05) < epsilon);
+       LUT_ASSERT(fabs(powerCurves[1].values[1]/100.0-3 - 51.05) < epsilon);
+       LUT_ASSERT(fabs(powerCurves[1].values[2]/100.0-3 - 52.05) < epsilon);
+       
+       LUT_ASSERT(powerCurves[2].ID == 50000);
+       LUT_ASSERT(fabs(powerCurves[2].values[0]/100.0-3 - 150.321) < epsilon);
+       LUT_ASSERT(fabs(powerCurves[2].values[1]/100.0-3 - 160.322) < epsilon);
+       LUT_ASSERT(fabs(powerCurves[2].values[2]/100.0-3 - 140.323) < epsilon);
+
+       LUT_ASSERT(powerCurves[3].ID == 6300);
+       LUT_ASSERT(fabs(powerCurves[3].values[0]/100.0-3 - 500.30) < epsilon);
+       LUT_ASSERT(fabs(powerCurves[3].values[1]/100.0-3 - 501.31) < epsilon);
+       LUT_ASSERT(fabs(powerCurves[3].values[2]/100.0-3 - 502.32) < epsilon);
+
+       for (int i = 0; i < nbSeries; i++)
+               free(powerCurves[i].values);
+       free(powerCurves);
+}

diff --git a/code/test/stage1/TimeSeries/t.serialize.c b/code/test/stage1/TimeSeries/t.serialize.c
new file mode 100644 (file)
index 0000000..1dda321
--- /dev/null
+++ b/code/test/stage1/TimeSeries/t.serialize.c
@@ -0,0 +1,47 @@
+#include "TimeSeries/serialize.h"
+#include "lut.h"
+#include <unistd.h>
+#include <stdio.h>
+
+static void checkFilesEqual(const char* fileName1, const char* fileName2)
+{
+       FILE* output = fopen(fileName1, "rb");
+       FILE* refOutput = fopen(fileName2, "rb");
+       while (!feof(output) && !feof(refOutput))
+               LUT_ASSERT(fgetc(output) == fgetc(refOutput));
+       LUT_ASSERT(feof(output) && feof(refOutput));
+       fclose(output);
+       fclose(refOutput);
+}
+
+void t_serialize1()
+{
+       const char* csvIfName = "../data/test/sample_byCols.csv";
+       const char* binaryIfName = "../data/test/sample_byCols.bin";
+       const char* tmpBinaryIfName = "../data/test/sample_byCols.tmp.bin";
+       
+       // serialize text file into a temporary binary file
+       serialize_byCols(csvIfName, tmpBinaryIfName, 0);
+
+       // compare binary result with reference
+       checkFilesEqual(tmpBinaryIfName, binaryIfName);
+
+       // remove temp file
+       unlink(tmpBinaryIfName);
+}
+
+void t_serialize2()
+{
+       const char* csvIfName = "../data/test/sample_byRows.csv";
+       const char* binaryIfName = "../data/test/sample_byRows.bin";
+       const char* tmpBinaryIfName = "../data/test/sample_byRows.tmp.bin";
+       
+       // serialize text file into a temporary binary file
+       serialize_byRows(csvIfName, tmpBinaryIfName, 0);
+
+       // compare binary result with reference
+       checkFilesEqual(tmpBinaryIfName, binaryIfName);
+
+       // remove temp file
+       unlink(tmpBinaryIfName);
+}

diff --git a/code/test/stage1/Util/t.rng.c b/code/test/stage1/Util/t.rng.c
new file mode 100644 (file)
index 0000000..ee98b98
--- /dev/null
+++ b/code/test/stage1/Util/t.rng.c
@@ -0,0 +1,49 @@
+#include "lut.h"
+#include "Util/rng.h"
+#include <stdlib.h>
+#include <cds/Vector.h>
+#include <math.h>
+
+// Auxiliary to perform K-S test for a given flag, sample size and bins count
+void aux_ks_test(int flag, uint32_t N, uint32_t nBins)
+{
+       init_rng(flag);
+               
+       // Fill the bins
+       uint32_t bins[nBins];
+       for (uint32_t i=0; i<nBins; i++)
+               bins[i] = 0;
+       for (uint32_t i=0; i<N; i++)
+       {
+               Real rf = get_rand_real();
+               uint32_t index = floor(rf*nBins);
+               if (index >= nBins) index = nBins - 1; //in case of...
+               bins[index]++;
+       }
+       
+       // Test the bins
+       double ksThreshold = 1.358 / sqrt((double)N);
+       double countPerBin = (double)N / nBins;
+       uint32_t cumulativeSum = 0;
+       for (uint32_t i=0; i<nBins; i++)
+       {
+               cumulativeSum += bins[i];
+               LUT_ASSERT((double)cumulativeSum / N - (i+1)*countPerBin/N < ksThreshold);
+       }
+}
+
+// Kolmogorov-Smirnov test on random real numbers (flag==0)
+void t_rng1()
+{
+       aux_ks_test(0, 1000000, 1000);
+       aux_ks_test(0, 100000, 1000);
+       aux_ks_test(0, 10000, 100);
+}
+
+// Kolmogorov-Smirnov test on random real numbers (flag==1)
+void t_rng2()
+{
+       aux_ks_test(1, 1000000, 1000);
+       aux_ks_test(1, 100000, 1000);
+       aux_ks_test(1, 10000, 100);
+}

diff --git a/code/test/stage1/Util/t.utils.c b/code/test/stage1/Util/t.utils.c
new file mode 100644 (file)
index 0000000..254ef00
--- /dev/null
+++ b/code/test/stage1/Util/t.utils.c
@@ -0,0 +1,50 @@
+#include "lut.h"
+#include "Util/utils.h"
+#include <stdlib.h>
+#include <stdio.h>
+#include "Util/types.h"
+#include <math.h>
+
+//integers
+void t_utils1()
+{
+       FILE* file = fopen("../data/test/integers.txt", "rb");
+       int64_t x;
+       readInt(file, &x);
+       LUT_ASSERT(x == 1234);
+       readInt(file, &x);
+       LUT_ASSERT(x == -987);
+       readInt(file, &x);
+       LUT_ASSERT(x == 654321);
+       readInt(file, &x);
+       LUT_ASSERT(x == 12);
+       readInt(file, &x);
+       LUT_ASSERT(x == 345678);
+       readInt(file, &x);
+       LUT_ASSERT(x == -1234);
+       fclose(file);
+}
+
+//reals
+void t_utils2()
+{
+       FILE* file = fopen("../data/test/reals.txt", "rb");
+       Real x, tol = 1e-10;
+       readReal(file, &x);
+       LUT_ASSERT(fabs(x - 1234.056) < tol);
+       readReal(file, &x);
+       LUT_ASSERT(fabs(x - 987e-3) < tol);
+       readReal(file, &x);
+       LUT_ASSERT(fabs(x - -654321e-2) < tol);
+       readReal(file, &x);
+       LUT_ASSERT(fabs(x - 12.34567) < tol);
+       readReal(file, &x);
+       LUT_ASSERT(fabs(x - 345678.0) < tol);
+       readReal(file, &x);
+       LUT_ASSERT(fabs(x - -1234.05) < tol);
+       readReal(file, &x);
+       LUT_ASSERT(fabs(x - 3e-1) < tol);
+       readReal(file, &x);
+       LUT_ASSERT(fabs(x - -1.0188) < tol);
+       fclose(file);
+}

diff --git a/code/test/stage1/main.c b/code/test/stage1/main.c
new file mode 100644 (file)
index 0000000..3d80af6
--- /dev/null
+++ b/code/test/stage1/main.c
@@ -0,0 +1,39 @@
+void t_serialize1();
+void t_serialize2();
+void t_deserialize1();
+void t_deserialize2();
+void t_compute_coefficients1();
+void t_compute_coefficients2();
+void t_pam1();
+void t_pam2();
+void t_pack1();
+void t_pack2();
+void t_unpack1();
+void t_unpack2();
+void t_rng1();
+void t_rng2();
+void t_utils1();
+void t_utils2();
+
+// list all unit tests here
+int main()
+{
+       t_serialize1();
+       t_serialize2();
+       t_deserialize1();
+       t_deserialize2();
+       //~ t_compute_coefficients1();
+       //~ t_compute_coefficients2();
+       t_pam1(); //may fail
+       t_pam2();
+       t_pack1();
+       t_pack2();
+       t_unpack1();
+       t_unpack2();
+       t_rng1(); //may fail
+       t_rng2();
+       t_utils1();
+       t_utils2();
+
+       return 0;
+}

diff --git a/code/test/stage2/.gitkeep b/code/test/stage2/.gitkeep
new file mode 100644 (file)
index 0000000..e69de29

diff --git a/communication/short_paper/.gitkeep b/communication/short_paper/.gitkeep
new file mode 100644 (file)
index 0000000..e69de29

diff --git a/communication/slides/.gitkeep b/communication/slides/.gitkeep
new file mode 100644 (file)
index 0000000..e69de29