From: Benjamin Auder Date: Fri, 7 Oct 2016 15:36:44 +0000 (+0200) Subject: Initialize with slightly modified (structure) ppam_mpi X-Git-Url: https://git.auder.net/doc/html/%7B%7B%20asset%28%27mixstore/css/static/home.css%27%29%20%7D%7D?a=commitdiff_plain;h=ab4a34efe7e9c82020a0e842a48d6bde1241d8a3;p=epclust.git Initialize with slightly modified (structure) ppam_mpi --- ab4a34efe7e9c82020a0e842a48d6bde1241d8a3 diff --git a/.gitignore b/.gitignore new file mode 100644 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 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 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 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 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 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 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 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 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 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 index 0000000..a7a73f3 --- /dev/null +++ b/code/src/stage1/Algorithm/compute_coefficients.c @@ -0,0 +1,57 @@ +#include +#include "Util/types.h" +#include +#include +#include + +// 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 +#include + +// 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 +#include +#include + +// 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 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 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 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 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 +#include "Algorithm/compute_coefficients.h" +#include +#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 +#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 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 index 0000000..de51270 --- /dev/null +++ b/code/src/stage1/MPI_Communication/unpack.c @@ -0,0 +1,68 @@ +#include +#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 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 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 +#include +#include +#include +#include +#include +#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, "\n\n"); + + fprintf(ofile, " "); + fprintf(ofile, "%s", lastBinaryFileName); + fprintf(ofile, "\n\n"); + + fprintf(ofile, " "); + fprintf(ofile, "%u", p_for_dissims); + fprintf(ofile, "\n\n"); + + fprintf(ofile, " \n"); + for (uint32_t i=0; i%u\n", result->medoids_ID[i]); + fprintf(ofile, " \n\n"); + + // medoids ranks in last binary file (human printing: 0 --> 1 ...etc) + fprintf(ofile, " \n"); + for (uint32_t i=0; i%u\n", result->medoids_ranks[i] + 1); + fprintf(ofile, " \n\n"); + + fprintf(ofile, "\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= 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 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 + +// 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 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 +#include +#include +#include +#include +#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; iip_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 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 + +// 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 index 0000000..5d1d758 --- /dev/null +++ b/code/src/stage1/TimeSeries/deserialize.c @@ -0,0 +1,82 @@ +#include "TimeSeries/deserialize.h" +#include +#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 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 +#include +#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 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 +#include +#include "Util/types.h" +#include "Util/utils.h" +#include +#include + +// 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, + // ()+ 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 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 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 +#include +#include + +//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 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 +#include + +// 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 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 +#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 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 + +// 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 index 0000000..3786eda --- /dev/null +++ b/code/src/stage1/Util/utils.c @@ -0,0 +1,117 @@ +#include "Util/utils.h" +#include +#include + +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 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 +#include + +#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 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 +#include +#include +#include +#include "TimeSeries/serialize.h" +#include "TimeSeries/deserialize.h" +#include "Classification/getClass.h" +#include +#include +#include + +// 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 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 + +// 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 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 +#include + +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 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 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 index 0000000..06f1fe5 --- /dev/null +++ b/code/test/stage1/Algorithm/t.pam.c @@ -0,0 +1,541 @@ +#include "Algorithm/pam.h" +#include +#include "Util/types.h" +#include "lut.h" +#include + +// 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[] = + { + 0,0.4931329,0.6468061,1.59794,1.61355,0.5859224,1.576601,0.5448115,1.140442,0.3398006,0.5066584,1.191759,1.198613,2.550266,1.707473,2.043505,1.458416,1.330188,2.933251,1.111916,1.282129,1.507499,2.014345,2.074064,0.8490186,1.712545,1.251893,2.491503,0.4268785,1.697855,0.8949661,0.4001053,2.393766,0.8512363,1.629601,1.211871,2.235879,1.785441,1.625559,1.463591,0.6011401,1.272803,0.9966205,1.648521,1.101768,1.018016,0.4304379,2.054914,2.161458,0.5166866,5.193379,8.195347,7.804742,7.622575,6.100441,5.657257,5.415788,5.652618,6.641958,4.922725,7.623015,6.057402,5.510167,4.981839,5.567289,6.654359,7.037072,5.685389,6.968147,7.342718,5.669615,5.505239,7.938334,8.341648,5.789066,5.78963,5.410773,5.796952,7.190531,7.219424,6.772028,7.20998,6.405605,6.069688,4.985437,6.770996,7.137468,7.64549,4.983799,4.464758,4.77661,3.246744,6.126875,6.110853,6.019614,8.470679,7.027884,6.277171,7.111463,4.845678,13.17241,13.02678,12.93952,10.7506,10.22332,12.41775,12.23105,11.85139,10.81067,12.02317,11.16295,13.93602,12.99271,11.61869,11.9426,11.18036,12.21016,12.4877,12.53486,11.77021,11.38024,10.31847,13.02466,13.47989,11.89502,12.1868,12.63906,9.868066,11.89049,12.16982,13.79615,12.52393,12.76788,11.03659,10.84051,11.68357,11.10395,11.22136,14.79833,10.44663,11.31625,11.04436,13.75508,11.41114,11.46083,12.72082,13.05467,12.44944,12.7433,11.39468,8.723632,7.773961,9.690631,9.694963,9.803899,8.478751,8.125111,9.587145,9.666684,9.137436,8.71384,8.766631,10.01471,8.924564,8.291021,7.942029,9.184045,9.384079,9.358433,10.16933,11.20876,9.577088,9.688468,9.599617,8.107158,9.258822,8.736808,9.115057,8.625799,8.735032,10.1133,7.497916,8.864467,10.99215,7.935033,9.38624,9.930072,10.45954,9.012305,9.077859,9.127831,9.548708,10.23819,11.86654,9.108776,10.26218,8.756327,8.299489,10.02933,10.19507, + 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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 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 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 index 0000000..125fd47 --- /dev/null +++ b/code/test/stage1/MPI_Communication/t.pack.c @@ -0,0 +1,106 @@ +#include "lut.h" +#include +#include "MPI_Communication/pack.h" +#include "Util/types.h" +#include +#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; inbClusters = 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 +#include "MPI_Communication/unpack.h" +#include "Util/types.h" +#include +#include +#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; inbClusters; 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 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 +#include +#include +#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 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 +#include + +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 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 +#include +#include + +// 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) 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 +#include +#include "Util/types.h" +#include + +//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 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 index 0000000..e69de29 diff --git a/communication/short_paper/.gitkeep b/communication/short_paper/.gitkeep new file mode 100644 index 0000000..e69de29 diff --git a/communication/slides/.gitkeep b/communication/slides/.gitkeep new file mode 100644 index 0000000..e69de29