Exercise 4 for the course "Parallel and distributed systems" of THMMY in AUTH university.
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#ifndef SERIAL_GS_PAGERANK_FUNCTIONS_H /* Include guard */
#define SERIAL_GS_PAGERANK_FUNCTIONS_H
/* ===== INCLUDES ===== */
#include <stdbool.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <math.h>
#include "coo_sparse_matrix.h"
#include "lil_sparse_matrix.h"
/* ===== DEFINITIONS ===== */
//Colors used for better console output formating.
#define ANSI_COLOR_RED "\x1B[31m"
#define ANSI_COLOR_GREEN "\x1B[32m"
#define ANSI_COLOR_YELLOW "\x1B[33m"
#define ANSI_COLOR_BLUE "\x1B[34m"
#define ANSI_COLOR_CYAN "\x1B[36m"
#define ANSI_COLOR_RESET "\x1B[0m"
/* ===== CONSTANTS DEFINITION ===== */
// Constant strings that store the command line options available.
extern const char *ARGUMENT_CONVERGENCE_TOLERANCE;
extern const char *ARGUMENT_MAX_ITERATIONS;
extern const char *ARGUMENT_DAMPING_FACTOR;
extern const char *ARGUMENT_VERBAL_OUTPUT;
extern const char *ARGUMENT_OUTPUT_HISTORY;
extern const char *ARGUMENT_OUTPUT_FILENAME;
// The numerical base used when parsing numerical command line arguments.
extern const int NUMERICAL_BASE;
// Default filename used for the output.
extern char *DEFAULT_OUTPUT_FILENAME;
// The size of the buffer used for reading the graph input file.
extern const int FILE_READ_BUFFER_SIZE;
/* ===== STRUCTURES ===== */
// A data structure to conveniently hold the algorithm's parameters.
typedef struct parameters {
int numberOfPages, maxIterations;
double convergenceCriterion, dampingFactor;
bool verbose, history;
char *outputFilename, *graphFilename;
} Parameters;
/* ===== FUNCTION DEFINITIONS ===== */
// Function validUsage outputs the correct way to use the program with command
// line arguments.
void validUsage(char *programName);
// Function checkIncrement is a helper function used in parseArguments (see
// bellow).
int checkIncrement(int previousIndex, int maxIndex, char *programName);
// Function parseArguments parses command line arguments.
void parseArguments(int argumentCount, char **argumentVector,
Parameters *parameters);
// Function generateNormalizedTransitionMatrixFromFile reads through the entries
// of the file specified in the arguments (parameters->graphFilename), using
// them to populate the sparse array (transitionMatrix). The entries of the file
// represent the edges of the web transition graph. The entries are then
// modified to become the rows of the transition matrix.
void generateNormalizedTransitionMatrixFromFile(CooSparseMatrix *transitionMatrix,
Parameters *parameters);
// Function savePagerankToFile appends or overwrites the pagerank vector
// "pagerankVector" to the file with the filename supplied in the arguments.
void savePagerankToFile(char *filename, bool append, double *pagerankVector,
int vectorSize);
// Function initialize allocates memory for the pagerank vector, reads the
// dataset from the file and creates the transition probability distribution
// matrix.
void initialize(CooSparseMatrix *transitionMatrix, double **pagerankVector,
Parameters *parameters);
// Function vectorNorm calculates the first norm of a vector.
double vectorNorm(double *vector, int vectorSize);
// Function calculateNextPagerank calculates the next pagerank vector.
void calculateNextPagerank(CooSparseMatrix *transitionMatrix,
double *previousPagerankVector, double **pagerankVector,
double *linksFromConvergedPagesPagerankVector,
double *convergedPagerankVector, int vectorSize, double dampingFactor);
// Function pagerank iteratively calculates the pagerank of each page until
// either the convergence criterion is met or the maximum number of iterations
// is reached.
int pagerank(CooSparseMatrix *transitionMatrix, double **pagerankVector,
bool *convergenceStatus, Parameters parameters);
#endif // SERIAL_GS_PAGERANK_FUNCTIONS_H