Sorting¶
This chapter describes functions for sorting data, both directly and indirectly (using an index). All the functions use the heapsort algorithm. Heapsort is an algorithm which operates inplace and does not require any additional storage. It also provides consistent performance, the running time for its worstcase (ordered data) being not significantly longer than the average and best cases. Note that the heapsort algorithm does not preserve the relative ordering of equal elements—it is an unstable sort. However the resulting order of equal elements will be consistent across different platforms when using these functions.
Sorting objects¶
The following function provides a simple alternative to the standard
library function qsort()
. It is intended for systems lacking
qsort()
, not as a replacement for it. The function qsort()
should be used whenever possible, as it will be faster and can provide
stable ordering of equal elements. Documentation for qsort()
is
available in the GNU C Library Reference Manual.
The functions described in this section are defined in the header file
gsl_heapsort.h
.

void gsl_heapsort(void *array, size_t count, size_t size, gsl_comparison_fn_t compare)¶
This function sorts the
count
elements of the arrayarray
, each of sizesize
, into ascending order using the comparison functioncompare
. The type of the comparison function is defined by
type gsl_comparison_fn_t¶
int (*gsl_comparison_fn_t) (const void * a, const void * b)
A comparison function should return a negative integer if the first argument is less than the second argument,
0
if the two arguments are equal and a positive integer if the first argument is greater than the second argument.For example, the following function can be used to sort doubles into ascending numerical order.
int compare_doubles (const double * a, const double * b) { if (*a > *b) return 1; else if (*a < *b) return 1; else return 0; }
The appropriate function call to perform the sort is:
gsl_heapsort (array, count, sizeof(double), compare_doubles);
Note that unlike
qsort()
the heapsort algorithm cannot be made into a stable sort by pointer arithmetic. The trick of comparing pointers for equal elements in the comparison function does not work for the heapsort algorithm. The heapsort algorithm performs an internal rearrangement of the data which destroys its initial ordering.
type gsl_comparison_fn_t¶

int gsl_heapsort_index(size_t *p, const void *array, size_t count, size_t size, gsl_comparison_fn_t compare)¶
This function indirectly sorts the
count
elements of the arrayarray
, each of sizesize
, into ascending order using the comparison functioncompare
. The resulting permutation is stored inp
, an array of lengthn
. The elements ofp
give the index of the array element which would have been stored in that position if the array had been sorted in place. The first element ofp
gives the index of the least element inarray
, and the last element ofp
gives the index of the greatest element inarray
. The array itself is not changed.
Sorting vectors¶
The following functions will sort the elements of an array or vector,
either directly or indirectly. They are defined for all real and integer
types using the normal suffix rules. For example, the float
versions of the array functions are gsl_sort_float()
and
gsl_sort_float_index()
. The corresponding vector functions are
gsl_sort_vector_float()
and gsl_sort_vector_float_index()
. The
prototypes are available in the header files gsl_sort_float.h
gsl_sort_vector_float.h
. The complete set of prototypes can be
included using the header files gsl_sort.h
and
gsl_sort_vector.h
.
There are no functions for sorting complex arrays or vectors, since the ordering of complex numbers is not uniquely defined. To sort a complex vector by magnitude compute a real vector containing the magnitudes of the complex elements, and sort this vector indirectly. The resulting index gives the appropriate ordering of the original complex vector.

void gsl_sort(double *data, const size_t stride, size_t n)¶
This function sorts the
n
elements of the arraydata
with stridestride
into ascending numerical order.

void gsl_sort2(double *data1, const size_t stride1, double *data2, const size_t stride2, size_t n)¶
This function sorts the
n
elements of the arraydata1
with stridestride1
into ascending numerical order, while making the same rearrangement of the arraydata2
with stridestride2
, also of sizen
.

void gsl_sort_vector(gsl_vector *v)¶
This function sorts the elements of the vector
v
into ascending numerical order.

void gsl_sort_vector2(gsl_vector *v1, gsl_vector *v2)¶
This function sorts the elements of the vector
v1
into ascending numerical order, while making the same rearrangement of the vectorv2
.

void gsl_sort_index(size_t *p, const double *data, size_t stride, size_t n)¶
This function indirectly sorts the
n
elements of the arraydata
with stridestride
into ascending order, storing the resulting permutation inp
. The arrayp
must be allocated with a sufficient length to store then
elements of the permutation. The elements ofp
give the index of the array element which would have been stored in that position if the array had been sorted in place. The arraydata
is not changed.

int gsl_sort_vector_index(gsl_permutation *p, const gsl_vector *v)¶
This function indirectly sorts the elements of the vector
v
into ascending order, storing the resulting permutation inp
. The elements ofp
give the index of the vector element which would have been stored in that position if the vector had been sorted in place. The first element ofp
gives the index of the least element inv
, and the last element ofp
gives the index of the greatest element inv
. The vectorv
is not changed.
Selecting the k smallest or largest elements¶
The functions described in this section select the smallest or largest elements of a data set of size . The routines use an direct insertion algorithm which is suited to subsets that are small compared with the total size of the dataset. For example, the routines are useful for selecting the 10 largest values from one million data points, but not for selecting the largest 100,000 values. If the subset is a significant part of the total dataset it may be faster to sort all the elements of the dataset directly with an algorithm and obtain the smallest or largest values that way.

int gsl_sort_smallest(double *dest, size_t k, const double *src, size_t stride, size_t n)¶
This function copies the
k
smallest elements of the arraysrc
, of sizen
and stridestride
, in ascending numerical order into the arraydest
. The sizek
of the subset must be less than or equal ton
. The datasrc
is not modified by this operation.

int gsl_sort_largest(double *dest, size_t k, const double *src, size_t stride, size_t n)¶
This function copies the
k
largest elements of the arraysrc
, of sizen
and stridestride
, in descending numerical order into the arraydest
.k
must be less than or equal ton
. The datasrc
is not modified by this operation.

int gsl_sort_vector_smallest(double *dest, size_t k, const gsl_vector *v)¶

int gsl_sort_vector_largest(double *dest, size_t k, const gsl_vector *v)¶
These functions copy the
k
smallest or largest elements of the vectorv
into the arraydest
.k
must be less than or equal to the length of the vectorv
.
The following functions find the indices of the smallest or largest elements of a dataset.

int gsl_sort_smallest_index(size_t *p, size_t k, const double *src, size_t stride, size_t n)¶
This function stores the indices of the
k
smallest elements of the arraysrc
, of sizen
and stridestride
, in the arrayp
. The indices are chosen so that the corresponding data is in ascending numerical order.k
must be less than or equal ton
. The datasrc
is not modified by this operation.

int gsl_sort_largest_index(size_t *p, size_t k, const double *src, size_t stride, size_t n)¶
This function stores the indices of the
k
largest elements of the arraysrc
, of sizen
and stridestride
, in the arrayp
. The indices are chosen so that the corresponding data is in descending numerical order.k
must be less than or equal ton
. The datasrc
is not modified by this operation.

int gsl_sort_vector_smallest_index(size_t *p, size_t k, const gsl_vector *v)¶

int gsl_sort_vector_largest_index(size_t *p, size_t k, const gsl_vector *v)¶
These functions store the indices of the
k
smallest or largest elements of the vectorv
in the arrayp
.k
must be less than or equal to the length of the vectorv
.
Computing the rank¶
The rank of an element is its order in the sorted data. The rank is the inverse of the index permutation, . It can be computed using the following algorithm:
for (i = 0; i < p>size; i++)
{
size_t pi = p>data[i];
rank>data[pi] = i;
}
This can be computed directly from the function
gsl_permutation_inverse(rank,p)
.
The following function will print the rank of each element of the vector :
void
print_rank (gsl_vector * v)
{
size_t i;
size_t n = v>size;
gsl_permutation * perm = gsl_permutation_alloc(n);
gsl_permutation * rank = gsl_permutation_alloc(n);
gsl_sort_vector_index (perm, v);
gsl_permutation_inverse (rank, perm);
for (i = 0; i < n; i++)
{
double vi = gsl_vector_get(v, i);
printf ("element = %d, value = %g, rank = %d\n",
i, vi, rank>data[i]);
}
gsl_permutation_free (perm);
gsl_permutation_free (rank);
}
Examples¶
The following example shows how to use the permutation to print the elements of the vector in ascending order:
gsl_sort_vector_index (p, v);
for (i = 0; i < v>size; i++)
{
double vpi = gsl_vector_get (v, p>data[i]);
printf ("order = %d, value = %g\n", i, vpi);
}
The next example uses the function gsl_sort_smallest()
to select
the 5 smallest numbers from 100000 uniform random variates stored in an
array,
#include <gsl/gsl_rng.h>
#include <gsl/gsl_sort_double.h>
int
main (void)
{
const gsl_rng_type * T;
gsl_rng * r;
size_t i, k = 5, N = 100000;
double * x = malloc (N * sizeof(double));
double * small = malloc (k * sizeof(double));
gsl_rng_env_setup();
T = gsl_rng_default;
r = gsl_rng_alloc (T);
for (i = 0; i < N; i++)
{
x[i] = gsl_rng_uniform(r);
}
gsl_sort_smallest (small, k, x, 1, N);
printf ("%zu smallest values from %zu\n", k, N);
for (i = 0; i < k; i++)
{
printf ("%zu: %.18f\n", i, small[i]);
}
free (x);
free (small);
gsl_rng_free (r);
return 0;
}
The output lists the 5 smallest values, in ascending order,
5 smallest values from 100000
0: 0.000003489200025797
1: 0.000008199829608202
2: 0.000008953968062997
3: 0.000010712770745158
4: 0.000033531803637743
References and Further Reading¶
The subject of sorting is covered extensively in the following,
Donald E. Knuth, The Art of Computer Programming: Sorting and Searching (Vol 3, 3rd Ed, 1997), AddisonWesley, ISBN 0201896850.
The Heapsort algorithm is described in the following book,
Robert Sedgewick, Algorithms in C, AddisonWesley, ISBN 0201514257.