Zipflaw / data /zipf.c
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// Copyright 2003-2009 Bill Manaris, Dana Hughes, J.R. Armstrong, Thomas Zalonis, Luca Pellicoro,
// Chris Wagner, Chuck McCormick
//
// This program is free software: you can redistribute it and/or modify
// it under the terms of the GNU General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
// (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU General Public License
// along with this program. If not, see <http://www.gnu.org/licenses/>.
//
/* zipf.c Version 1.5 24-Dec-2009
*
* This module encapsulates functions that may be used to calculate
* the slope and r2 (fit) of a trendline
* of a Zipf distribution (byRank or bySize).
*
* The byRank distribution plots the values (y-axis)
* against the ranks of the values from largest to smallest
* (x-axis) in log-log scale. The ranks are generated automatically.
*
* The bySize distribution plots the values (y-axis)
* against the supplised keys (x-axis) in log-log scale.
*
* Usage: Call bySize(int *ranks, int numRanks, double *counts, int numCounts) and.or
* byRank(double *counts, int numCounts) functions.
*
* Output: slope and R2
*
* WARNING: If an error occurs the current code will NOT raise an exception;
* it will only print an error message (for ShedSkin compatibility).
* This may cause problems, if the error messages go undetected
* (e.g., this code is run in batch mode).
*
* Authors: Chris Wagner and Bill Manaris (based on VB code by Chuck McCormick and Bill Manaris)
*
* Thomas Zalonis - translate to C.
*
* version 1.5 (December 24, 2008) J.R. Armstrong and Bill Manaris
* - Now we are differentiating between monotonous and random phenomena (vertical vs. horizontal trendlines).
* In the first case, we return slope = 0 and r2 = 0.
* In the second case, we return slope = 0 and r2 = 1.
* Also, some variable names have been updated.
*
* version 1.4 (October 1, 2008) Bill Manaris
* - Added more unit-testing code (i.e., if __name__=='__main__') for Shed Skin Python-to-C++ conversion to work.
* - Updated some variable names for usability/readability
*
* version 1.3 (March 23, 2007) Thomas Zalonis
* - Added code to the getSlopeR2() function that calculates the y-intercept for the trendline.
* - getSlopeR2() now returns 3 values, slope, r2 and the trendline y-intercept
*
* version 1.2 (Feb 03, 2007) Luca Pellicoro
* -Translation from Java to Python
* -Raise exceptions with erroneous user inputs (such as zero keys or values)
*
* version 1.1 (July 30, 2005)
*
* version 1.0 (May 10, 2003)
*
*
* Calculates slope and R^2 values of a collection of numbers.
*
* Libraries needed:
* -----------------
* stdlib for qsort
*
*/
#include <stdlib.h>
#include <math.h>
#include <unistd.h>
#include <sys/stat.h>
#include <sys/types.h>
#include <sys/mman.h>
#include <fcntl.h>
#include <string.h>
#define FALSE 0
#define TRUE 1
//*****************************************************************************
// This struct is used to return multiple values from byRank()
// ****************************************************************************
struct ZipfValues
{
float slope;
float r2;
float yint;
};
// zipf related
struct ZipfValues *getSlopeR2(int *, int, double *, int);
int checkRanksAndCounts(int *, int, double *, int);
struct ZipfValues *bySize(int *, int, double *, int);
int compare(const void *, const void *);
struct ZipfValues *byRank(double *, int);
//*****************************************************************************
// The byRank distribution plots the values (y-axis)
// against the ranks of the values from largest to smallest
// (x-axis) in log-log scale. The ranks are generated automatically.
//*****************************************************************************
struct ZipfValues *byRank(double *counts, int numCounts)
{
double *newCounts = (double *)malloc(sizeof(double) * numCounts);
int *newRanks = (int *)malloc(sizeof(int) * numCounts);
int index;
for(index=0;index<numCounts;index++)
{
newCounts[index] = counts[index];
newRanks[index] = numCounts - index;
}
qsort((void *)newCounts, numCounts, sizeof(double), compare);
checkRanksAndCounts(newRanks, numCounts, newCounts, numCounts);
return getSlopeR2(newRanks, numCounts, newCounts, numCounts);
}
//*****************************************************************************
// 'Double' comparison function needed for sorting. This function
// is passed in as a parameter to qsort() in the byRank() function.
//*****************************************************************************
int compare(const void *a, const void *b)
{
double d = *( (double *) a) - *( (double *) b );
if(d > 0.0)
{
return 1;
}
else if (d < 0.0)
{
return -1;
}
else
{
return 0;
}
}
//*****************************************************************************
// The bySize distribution plots the values (y-axis)
// against the supplised keys (x-axis) in log-log scale.
//*****************************************************************************
struct ZipfValues *bySize(int *sizes, int numSizes, double *counts, int numCounts)
{
checkRanksAndCounts(sizes, numSizes, counts, numCounts);
return getSlopeR2(sizes, numSizes, counts, numCounts);
}
//*****************************************************************************
// Supporting function for bySize() and byRank(). Checks the passed values
// for correctness.
//*****************************************************************************
int checkRanksAndCounts(int *ranks, int numRanks, double *counts, int numCounts)
{
if(numCounts == 0)
{
fprintf(stderr, "Counts should contain at least one element.\n");
exit(0);
}
if(numRanks == 0)
{
fprintf(stderr, "Ranks should contain at least one element.\n");
exit(0);
}
if(numRanks != numCounts)
{
fprintf(stderr, "Ranks (%d) and counts (%d) should have the same size.\n", numRanks, numCounts);
exit(0);
}
int i;
for(i=0;i<numRanks;i++)
{
if(ranks[i] <= 0.0)
{
fprintf(stderr, "Ranks should be strictly positive.\n");
exit(0);
}
if(counts[i] <= 0.0)
{
fprintf(stderr, "Counts and values should be strictly positive.\n");
exit(0);
}
}
return 0;
}
//*****************************************************************************
// Supporting function for byRank() and bySize(). The actual zipf values
// (slope, R2 and yint) are calculated in this function and returned
// as a struct.
//*****************************************************************************
struct ZipfValues *getSlopeR2(int *ranks, int numRanks, double *counts, int numCounts)
{
struct ZipfValues *results = (struct ZipfValues *)malloc(sizeof(struct ZipfValues));
double sumX, sumY, sumXY, sumX2, sumY2,slope, r2, yint;
int index;
sumX = sumY = sumXY = sumX2 = sumY2 = 0.0;
// one exterme case:
// if the phenomenon is monotonous (only one type of event, e.g., ['a', 'a', 'a']),
// then the slope is negative infinity (cannot draw a line with only one data point),
// so indicate this with slope = 0 AND r2 = 0
if(numRanks == 1)
{
slope = 0.0;
r2 = 0.0;
}
else
{
//the other extreme case:
//if the phenomenon is uniformly distributed (several types of events,
//but all having the same number of instances, e.g., ['a', 'b', 'a', 'b', 'a', 'b']),
//then the slope = 0 and r2 = 1 (a horizontal line).
//check if all counts are equal
int allCountsEqual = 1;
for(index=0;(index < numRanks - 1) && allCountsEqual;index++)
{
if(counts[index] != counts[index + 1])
allCountsEqual = 0;
}
if(allCountsEqual)
{
slope = 0.0;
r2 = 1.0;
}
else // general case, so calculate actual slope and r2 values
{
double tmp1,tmp2;
for(index=0;index<numRanks;index++)
{
// only calculating the follow log()s once for efficiency
tmp1 = log10(ranks[index]);
tmp2 = log10(counts[index]);
sumX += tmp1;
sumY += tmp2;
sumXY += tmp1 * tmp2;
sumX2 += pow(tmp1, 2);
sumY2 += pow(tmp2, 2);
}
// calculate slope
if((numRanks*sumX2 - sumX*sumX) == 0.0)
slope = 0.0;
else
slope = ((numRanks*sumXY - sumX*sumY) / (numRanks*sumX2 - sumX*sumX));
// calculate r2
if(sqrt((numRanks*sumX2 - sumX*sumX) * (numRanks*sumY2 - sumY*sumY)) == 0.0)
{
r2 = 0.0;
}
else
{
r2 = (numRanks*sumXY - sumX*sumY)/(sqrt(numRanks*sumX2 - sumX*sumX)*sqrt(numRanks*sumY2 - sumY*sumY));
r2 = r2 * r2;
}
}
}
// calculate y-intercept
yint = (sumY - slope * sumX) / numRanks;
// packing slope, r2 and yint into a ZipfValues struct
// so that all three can be returned at once.
results->slope = slope;
results->r2 = r2;
results->yint = yint;
return results;
}