random_MT64_table_get
Retrieves the current table used in the 64-bit Mersenne Twister generator.
Synopsis
#include <imsls.h>
void imsls_random_MT64_table_get (unsigned long long **table, ..., 0)
Required Arguments
unsigned long long **table (Output)
Address of a pointer to an array of length 625 containing the table used in the 64-bit Mersenne Twister generator. Typically, unsigned long long *table is declared and &table is used as an argument.
Synopsis with Optional Arguments
#include <imsls.h>
void imsls_random_MT64_table_get (unsigned long long **table,
IMSLS_RETURN_USER, unsigned long long r[],
0)
Optional Arguments
IMSLS_RETURN_USER, unsigned long long r[] (Output)
User-supplied array of length 625 containing the table used in the 64-bit Mersenne Twister generator.
Description
The values in the
table contain the state of the 64-bit Mersenne Twister random number generator. The table can be used by
imsls_random_MT64_table_set to set the generator back to this state.
Example
In this example, four simulation streams are generated. The first series is generated with the seed used for initialization. The second series is generated using an array for initialization. The third series is obtained by resetting the generator back to the state it had at the beginning of the second stream. Therefore the second and third streams are identical. The fourth stream is obtained by resetting the generator back to its original, uninitialized state, and having it reinitialize using the seed. The fourth and first streams are therefore the same.
#include <imsls.h>
int main()
{
unsigned long long init[] = {0x123, 0x234, 0x345, 0x456};
float *r;
int iseed = 123457;
unsigned long long *itable;
int nr = 5;
/* Initialize 64-bit Mersenne Twister series with a seed */
imsls_random_option (9);
imsls_random_seed_set (iseed);
r = imsls_f_random_uniform (nr, 0);
imsls_f_write_matrix ("First stream output", 1, 5, r,
IMSLS_NO_COL_LABELS,
IMSLS_NO_ROW_LABELS,
0);
imsls_free(r);
/* Reinitialize Mersenne Twister series with an array */
imsls_random_option (9);
imsls_random_MT64_init(4, init);
/* Save the state of the series */
imsls_random_MT64_table_get(&itable, 0);
r = imsls_f_random_uniform (nr, 0);
imsls_f_write_matrix ("Second stream output", 1, 5, r,
IMSLS_NO_COL_LABELS,
IMSLS_NO_ROW_LABELS,
0);
imsls_free(r);
/* Restore the state of the series */
imsls_random_MT64_table_set(itable);
r = imsls_f_random_uniform (nr, 0);
imsls_f_write_matrix ("Third stream output", 1, 5, r,
IMSLS_NO_COL_LABELS,
IMSLS_NO_ROW_LABELS,
0);
imsls_free(r);
/* Reset the series - it will reinitialize from the seed */
itable[0] = 1000;
imsls_random_MT64_table_set(itable);
r = imsls_f_random_uniform (nr, 0);
imsls_f_write_matrix ("Fourth stream output", 1, 5, r,
IMSLS_NO_COL_LABELS,
IMSLS_NO_ROW_LABELS,
0);
imsls_free(r);
return 0;
}
Output
First stream output
0.5799 0.9401 0.7102 0.1640 0.5457
Second stream output
0.4894 0.7397 0.5725 0.0863 0.7588
Third stream output
0.4894 0.7397 0.5725 0.0863 0.7588
Fourth stream output
0.5799 0.9401 0.7102 0.1640 0.5457
