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cmath2.c, cleanup

This commit is contained in:
h_vogt 2016-09-17 16:15:29 +02:00 committed by rlar
parent 2e35329678
commit 2ab3b82696
1 changed files with 28 additions and 27 deletions
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55
src/maths/cmaths/cmath2.c
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@ -118,12 +118,12 @@ cx_uminus(void *data, short int type, int length, int *newlength, short int *new
}
/* random integers drawn from a uniform distribution
*data in: integer numbers, their absolut values are used,
maximum is RAND_MAX (32767)
*data out: random integers in interval [0, data[i][
standard library function rand() is used
*/
/* random integers drawn from a uniform distribution
* data in: integer numbers, their absolut values are used,
* maximum is RAND_MAX (32767)
* data out: random integers in interval [0, data[i][
* standard library function rand() is used
*/
void *
cx_rnd(void *data, short int type, int length, int *newlength, short int *newtype)
{
@ -160,9 +160,9 @@ cx_rnd(void *data, short int type, int length, int *newlength, short int *newtyp
}
}
/* random numbers drawn from a uniform distribution
*data out: random numbers in interval [-1, 1[
*/
/* random numbers drawn from a uniform distribution
* data out: random numbers in interval [-1, 1[
*/
void *
cx_sunif(void *data, short int type, int length, int *newlength, short int *newtype)
{
@ -194,11 +194,11 @@ cx_sunif(void *data, short int type, int length, int *newlength, short int *newt
}
}
/* random numbers drawn from a poisson distribution
*data in: lambda
*data out: random integers according to poisson distribution,
with lambda given by each vector element
*/
/* random numbers drawn from a poisson distribution
* data in: lambda
* data out: random integers according to poisson distribution,
* with lambda given by each vector element
*/
void *
cx_poisson(void *data, short int type, int length, int *newlength, short int *newtype)
{
@ -232,11 +232,11 @@ cx_poisson(void *data, short int type, int length, int *newlength, short int *ne
}
}
/* random numbers drawn from an exponential distribution
*data in: Mean values
*data out: exponentially distributed random numbers,
with mean given by each vector element
*/
/* random numbers drawn from an exponential distribution
* data in: Mean values
* data out: exponentially distributed random numbers,
* with mean given by each vector element
*/
void *
cx_exponential(void *data, short int type, int length, int *newlength, short int *newtype)
{
@ -308,10 +308,11 @@ cx_sgauss(void *data, short int type, int length, int *newlength, short int *new
/* Compute the avg of a vector.
Created by A.M.Roldan 2005-05-21 */
* Created by A.M.Roldan 2005-05-21
*/
void
*cx_avg(void *data, short int type, int length, int *newlength, short int *newtype)
void *
cx_avg(void *data, short int type, int length, int *newlength, short int *newtype)
{
double sum_real = 0.0, sum_imag = 0.0;
int i;
@ -575,10 +576,10 @@ cx_times(void *data1, void *data2, short int datatype1, short int datatype2, int
} else {
c2 = cc2[i];
}
realpart(c[i]) = realpart(c1) * realpart(c2)
- imagpart(c1) * imagpart(c2);
imagpart(c[i]) = imagpart(c1) * realpart(c2)
+ realpart(c1) * imagpart(c2);
realpart(c[i]) =
realpart(c1) * realpart(c2) - imagpart(c1) * imagpart(c2);
imagpart(c[i]) =
imagpart(c1) * realpart(c2) + realpart(c1) * imagpart(c2);
}
return ((void *) c);
}
@ -764,7 +765,7 @@ cx_d(void *data, short int type, int length, int *newlength, short int *newtype)
imagpart(c[length-1])=imagpart(cc[length-1])-imagpart(cc[length-2]);
for (i = 1; i < (length-1); i++) {
for (i = 1; i < length - 1; i++) {
realpart(c[i])=realpart(cc[i+1])-realpart(cc[i-1]);
imagpart(c[i])=imagpart(cc[i+1])-imagpart(cc[i-1]);