/usr/share/doc/libsuperlu-dev/tests/MATGEN/zlarnd.c is in libsuperlu3-dev 3.0+20070106-3.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 | /* -- translated by f2c (version 19940927).
You must link the resulting object file with the libraries:
-lf2c -lm (in that order)
*/
#include "f2c.h"
/* Double Complex */ VOID zlarnd_(doublecomplex * ret_val, integer *idist,
integer *iseed)
{
/* System generated locals */
doublereal d__1, d__2;
doublecomplex z__1, z__2, z__3;
/* Builtin functions */
double log(doublereal), sqrt(doublereal);
void z_exp(doublecomplex *, doublecomplex *);
/* Local variables */
static doublereal t1, t2;
extern doublereal dlaran_(integer *);
/* -- LAPACK auxiliary routine (version 2.0) --
Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd.,
Courant Institute, Argonne National Lab, and Rice University
September 30, 1994
Purpose
=======
ZLARND returns a random complex number from a uniform or normal
distribution.
Arguments
=========
IDIST (input) INTEGER
Specifies the distribution of the random numbers:
= 1: real and imaginary parts each uniform (0,1)
= 2: real and imaginary parts each uniform (-1,1)
= 3: real and imaginary parts each normal (0,1)
= 4: uniformly distributed on the disc abs(z) <= 1
= 5: uniformly distributed on the circle abs(z) = 1
ISEED (input/output) INTEGER array, dimension (4)
On entry, the seed of the random number generator; the array
elements must be between 0 and 4095, and ISEED(4) must be
odd.
On exit, the seed is updated.
Further Details
===============
This routine calls the auxiliary routine DLARAN to generate a random
real number from a uniform (0,1) distribution. The Box-Muller method
is used to transform numbers from a uniform to a normal distribution.
=====================================================================
Generate a pair of real random numbers from a uniform (0,1)
distribution
Parameter adjustments */
--iseed;
/* Function Body */
t1 = dlaran_(&iseed[1]);
t2 = dlaran_(&iseed[1]);
if (*idist == 1) {
/* real and imaginary parts each uniform (0,1) */
z__1.r = t1, z__1.i = t2;
ret_val->r = z__1.r, ret_val->i = z__1.i;
} else if (*idist == 2) {
/* real and imaginary parts each uniform (-1,1) */
d__1 = t1 * 2. - 1.;
d__2 = t2 * 2. - 1.;
z__1.r = d__1, z__1.i = d__2;
ret_val->r = z__1.r, ret_val->i = z__1.i;
} else if (*idist == 3) {
/* real and imaginary parts each normal (0,1) */
d__1 = sqrt(log(t1) * -2.);
d__2 = t2 * 6.2831853071795864769252867663;
z__3.r = 0., z__3.i = d__2;
z_exp(&z__2, &z__3);
z__1.r = d__1 * z__2.r, z__1.i = d__1 * z__2.i;
ret_val->r = z__1.r, ret_val->i = z__1.i;
} else if (*idist == 4) {
/* uniform distribution on the unit disc abs(z) <= 1 */
d__1 = sqrt(t1);
d__2 = t2 * 6.2831853071795864769252867663;
z__3.r = 0., z__3.i = d__2;
z_exp(&z__2, &z__3);
z__1.r = d__1 * z__2.r, z__1.i = d__1 * z__2.i;
ret_val->r = z__1.r, ret_val->i = z__1.i;
} else if (*idist == 5) {
/* uniform distribution on the unit circle abs(z) = 1 */
d__1 = t2 * 6.2831853071795864769252867663;
z__2.r = 0., z__2.i = d__1;
z_exp(&z__1, &z__2);
ret_val->r = z__1.r, ret_val->i = z__1.i;
}
return ;
/* End of ZLARND */
} /* zlarnd_ */
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