Update of /cvsroot/pure-data/externals/cxc
In directory sc8-pr-cvs1.sourceforge.net:/tmp/cvs-serv4698
Added Files:
Tag: branch-v0-39-2-extended
mean~.c
Removed Files:
Tag: branch-v0-39-2-extended
mean.c
Log Message:
cleaned up cxc so that it passes the automated test in scripts/load_every_help.sh: renamed help files to standard name; made each file named after the class; removed non-functional aliases in flatspace
--- mean.c DELETED ---
--- NEW FILE: mean~.c ---
/*
jdl(a)xdv.org, 200203
calculate mean of buffer
standard deviation + histogram
*/
#include "m_pd.h"
#include <math.h>
//#include <stdlib.h>
/* cx.mean: calculate the mean from a table */
/* as defined by: add all samples together and divide by number of samples */
t_class *cxmean_class;
typedef struct _cxmean
{
t_object x_obj;
t_symbol *x_arrayname;
t_float x_mean;
float *x_vec;
t_float f;
int x_nsampsintab;
} t_cxmean;
void *cxmean_new(t_symbol *s)
{
t_cxmean *x = (t_cxmean *)pd_new(cxmean_class);
x->x_arrayname = s;
x->x_mean = 0;
outlet_new(&x->x_obj, &s_float);
return (x);
}
static void cxmean_set(t_cxmean *x, t_symbol *s)
{
t_garray *a;
x->x_arrayname = s;
if (!(a = (t_garray *)pd_findbyclass(x->x_arrayname, garray_class)))
{
if (*s->s_name) pd_error(x, "mean~: %s: no such array",
x->x_arrayname->s_name);
x->x_vec = 0;
}
else if (!garray_getfloatarray(a, &x->x_nsampsintab, &x->x_vec))
{
error("%s: bad template for mean~", x->x_arrayname->s_name);
x->x_vec = 0;
}
else garray_usedindsp(a);
}
void cxmean_bang(t_cxmean *x)
{
outlet_float(x->x_obj.ob_outlet,x->x_mean);
}
static void cxmean_mean(t_cxmean *x)
{
// t_float *bl;
t_garray *a;
int cnt;
t_float *fp;
t_float xz = 0.;
cnt = 0;
if(!(a = (t_garray *)pd_findbyclass(x->x_arrayname,garray_class))) {
pd_error(x, "%s: no such table", x->x_arrayname->s_name);
}
garray_getfloatarray(a,&x->x_nsampsintab,&x->x_vec);
fp = x->x_vec;
while(cnt < x->x_nsampsintab) {
//post("cxc/mean.c: %f",*fp++);
xz += *fp++;
cnt++;
}
#ifdef DEBUG
post("cxc/mean.c: sampsum: %f",xz);
#endif
x->x_mean = xz / x->x_nsampsintab;
outlet_float(x->x_obj.ob_outlet, x->x_mean);
}
void cxmean_setup(void)
{
cxmean_class = class_new(gensym("cxmean"),
(t_newmethod)cxmean_new,
0,
sizeof(t_cxmean),
CLASS_DEFAULT,
A_DEFSYM, 0);
class_addcreator((t_newmethod)cxmean_new,gensym("cx.mean"),A_DEFSYM, 0);
class_addmethod(cxmean_class, (t_method)cxmean_set,
gensym("set"), A_DEFSYM, 0);
class_addmethod(cxmean_class, (t_method)cxmean_mean,
gensym("mean"), A_DEFSYM, 0);
class_addbang(cxmean_class, cxmean_bang);
class_sethelpsymbol(cxmean_class, gensym("statistics.pd"));
}
/* cx.avgdev: calculate the average deviation of an array from
mean as input and array.
takes mean as input, sum of abs values of sample-val - mean
divided by number of samples
*/
t_class *cxavgdev_class;
typedef struct _cxavgdev
{
t_object x_obj;
t_symbol *x_arrayname;
t_float x_avgdev;
float *x_vec;
t_float f;
int x_nsampsintab;
} t_cxavgdev;
void *cxavgdev_new(t_symbol *s)
{
t_cxavgdev *x = (t_cxavgdev *)pd_new(cxavgdev_class);
x->x_arrayname = s;
x->x_avgdev = 0;
outlet_new(&x->x_obj, &s_float);
return (x);
}
static void cxavgdev_set(t_cxavgdev *x, t_symbol *s)
{
t_garray *a;
x->x_arrayname = s;
if (!(a = (t_garray *)pd_findbyclass(x->x_arrayname, garray_class)))
{
if (*s->s_name) pd_error(x, "mean~: %s: no such array",
x->x_arrayname->s_name);
x->x_vec = 0;
}
else if (!garray_getfloatarray(a, &x->x_nsampsintab, &x->x_vec))
{
error("%s: bad template for mean~", x->x_arrayname->s_name);
x->x_vec = 0;
}
else garray_usedindsp(a);
}
void cxavgdev_bang(t_cxavgdev *x)
{
outlet_float(x->x_obj.ob_outlet,x->x_avgdev);
}
static void cxavgdev_float(t_cxavgdev *x, t_float f)
{
// t_float *bl;
t_garray *a;
int cnt;
t_float *fp;
t_float xz = 0.;
t_float tz = 0.;
cnt = 0;
if(!(a = (t_garray *)pd_findbyclass(x->x_arrayname,garray_class))) {
pd_error(x, "%s: no such table", x->x_arrayname->s_name);
}
garray_getfloatarray(a,&x->x_nsampsintab,&x->x_vec);
fp = x->x_vec;
while(cnt < x->x_nsampsintab) {
tz = *fp++;
tz = fabs(tz - f);
xz += tz;
#ifdef DEBUG
//post("cxc/mean.c: sampdeviation: %f",tz);
#endif
cnt++;
}
#ifdef DEBUG
post("cxc/mean.c: avgsum: %f",xz);
#endif
x->x_avgdev = xz / x->x_nsampsintab;
outlet_float(x->x_obj.ob_outlet, x->x_avgdev);
}
void cxavgdev_setup(void)
{
cxavgdev_class = class_new(gensym("cxavgdev"),
(t_newmethod)cxavgdev_new,
0,
sizeof(t_cxavgdev),
CLASS_DEFAULT,
A_DEFSYM, 0);
class_addcreator((t_newmethod)cxavgdev_new,gensym("cx.avgdev"),A_DEFSYM, 0);
class_addmethod(cxavgdev_class, (t_method)cxavgdev_set,
gensym("set"), A_DEFSYM, 0);
/* class_addmethod(cxavgdev_class, (t_method)cxavgdev_mean, */
/* gensym("mean"), A_DEFSYM, 0); */
class_addfloat(cxavgdev_class, (t_method)cxavgdev_float);
class_addbang(cxavgdev_class, cxavgdev_bang);
class_sethelpsymbol(cxavgdev_class, gensym("statistics.pd"));
}
/* cx.stddev: calculate the standard deviation of an array from
mean as input and array.
square root of sum of power of sample - mean divided by num of
samps - 1
*/
t_class *cxstddev_class;
typedef struct _cxstddev
{
t_object x_obj;
t_symbol *x_arrayname;
t_float x_stddev;
float *x_vec;
t_float f;
int x_nsampsintab;
} t_cxstddev;
void *cxstddev_new(t_symbol *s)
{
t_cxstddev *x = (t_cxstddev *)pd_new(cxstddev_class);
x->x_arrayname = s;
x->x_stddev = 0;
outlet_new(&x->x_obj, &s_float);
return (x);
}
static void cxstddev_set(t_cxstddev *x, t_symbol *s)
{
t_garray *a;
x->x_arrayname = s;
if (!(a = (t_garray *)pd_findbyclass(x->x_arrayname, garray_class)))
{
if (*s->s_name) pd_error(x, "mean~: %s: no such array",
x->x_arrayname->s_name);
x->x_vec = 0;
}
else if (!garray_getfloatarray(a, &x->x_nsampsintab, &x->x_vec))
{
error("%s: bad template for mean~", x->x_arrayname->s_name);
x->x_vec = 0;
}
else garray_usedindsp(a);
}
void cxstddev_bang(t_cxstddev *x)
{
outlet_float(x->x_obj.ob_outlet,x->x_stddev);
}
static void cxstddev_float(t_cxstddev *x, t_float f)
{
// t_float *bl;
t_garray *a;
int cnt;
t_float *fp;
t_float xz = 0.;
t_float tz = 0.;
cnt = 0;
if(!(a = (t_garray *)pd_findbyclass(x->x_arrayname,garray_class))) {
pd_error(x, "%s: no such table", x->x_arrayname->s_name);
}
garray_getfloatarray(a,&x->x_nsampsintab,&x->x_vec);
fp = x->x_vec;
while(cnt < x->x_nsampsintab) {
tz = *fp++;
tz = pow(tz - f,2); // power of 2
xz += tz;
#ifdef DEBUG
//post("cxc/mean.c: sampdeviation: %f",tz);
#endif
cnt++;
}
#ifdef DEBUG
post("cxc/mean.c: avgsum: %f",xz);
#endif
x->x_stddev = sqrt(xz / (x->x_nsampsintab - 1));
outlet_float(x->x_obj.ob_outlet, x->x_stddev);
}
void cxstddev_setup(void)
{
cxstddev_class = class_new(gensym("cxstddev"),
(t_newmethod)cxstddev_new,
0,
sizeof(t_cxstddev),
CLASS_DEFAULT,
A_DEFSYM, 0);
class_addcreator((t_newmethod)cxstddev_new,gensym("cx.stddev"),A_DEFSYM, 0);
class_addmethod(cxstddev_class, (t_method)cxstddev_set,
gensym("set"), A_DEFSYM, 0);
/* class_addmethod(cxstddev_class, (t_method)cxstddev_mean, */
/* gensym("mean"), A_DEFSYM, 0); */
class_addfloat(cxstddev_class, (t_method)cxstddev_float);
class_addbang(cxstddev_class, cxstddev_bang);
class_sethelpsymbol(cxstddev_class, gensym("statistics.pd"));
}
/* ---------- mean~ ---------- */
/* output the mean as a signal */
t_class *mean_tilde_class;
typedef struct _mean_tilde
{
t_object x_obj;
t_symbol *x_arrayname;
t_float x_mean;
float *x_vec;
t_float f;
int x_nsampsintab;
} t_mean_tilde;
void *mean_tilde_new(t_symbol *s)
{
t_mean_tilde *x = (t_mean_tilde *)pd_new(mean_tilde_class);
x->x_arrayname = s;
x->x_mean = 0;
outlet_new(&x->x_obj, &s_float);
return (x);
}
static t_int *mean_tilde_perform(t_int *w)
{
t_mean_tilde *x = (t_mean_tilde *)(w[1]);
//t_float *out = (t_float *)(w[3]),
t_float *fp;
//// t_float *in = (t_float *)(w[2]);
//// *out = *in;
int n = (int)(w[2]);
t_float xz = 0.;
fp = x->x_vec;
while(n--) {
xz += abs(*fp++);
//post("cxc/mean.c: %d : %f : %f",n,xz,fp);
}
x->x_mean = (t_float)(xz / n);
//post("cxc/mean.c: %f",xz);
return (w+3);
//return 0;
}
static void mean_tilde_set(t_mean_tilde *x, t_symbol *s)
{
t_garray *a;
x->x_arrayname = s;
if (!(a = (t_garray *)pd_findbyclass(x->x_arrayname, garray_class)))
{
if (*s->s_name) pd_error(x, "mean~: %s: no such array",
x->x_arrayname->s_name);
x->x_vec = 0;
}
else if (!garray_getfloatarray(a, &x->x_nsampsintab, &x->x_vec))
{
error("%s: bad template for mean~", x->x_arrayname->s_name);
x->x_vec = 0;
}
else garray_usedindsp(a);
}
static void mean_tilde_dsp(t_mean_tilde *x, t_signal **sp)
{
mean_tilde_set(x, x->x_arrayname);
//dsp_add(mean_tilde_perform, 2, x, sp[0]->s_vec, sp[0]->s_n);
//dsp_add(mean_tilde_perform, 3, x, sp[0]->s_vec, sp[0]->s_n);
dsp_add(mean_tilde_perform, 2, x, sp[0]->s_n);
}
void mean_tilde_bang(t_mean_tilde *x)
{
outlet_float(x->x_obj.ob_outlet,x->x_mean);
}
static void mean_tilde_mean(t_mean_tilde *x)
{
// t_float *bl;
t_garray *a;
int cnt;
t_float *fp;
t_float xz = 0.;
cnt = 0;
if(!(a = (t_garray *)pd_findbyclass(x->x_arrayname,garray_class))) {
pd_error(x, "%s: no such table", x->x_arrayname->s_name);
}
garray_getfloatarray(a,&x->x_nsampsintab,&x->x_vec);
fp = x->x_vec;
while(cnt < x->x_nsampsintab) {
//post("cxc/mean.c: %f",*fp++);
xz += *fp++;
cnt++;
}
#ifdef DEBUG
post("cxc/mean.c: sampsum: %f",xz);
#endif
x->x_mean = xz / x->x_nsampsintab;
outlet_float(x->x_obj.ob_outlet, x->x_mean);
}
void mean_tilde_setup(void)
{
//post("mean~ setup");
mean_tilde_class = class_new(gensym("mean~"),
(t_newmethod)mean_tilde_new,
0,
sizeof(t_mean_tilde),
CLASS_DEFAULT,
A_DEFSYM, 0);
//CLASS_MAINSIGNALIN(mean_tilde_class, t_mean_tilde, f);
class_addmethod(mean_tilde_class, nullfn, gensym("signal"), 0);
class_addmethod(mean_tilde_class,
(t_method)mean_tilde_dsp,
gensym("dsp"), 0);
class_addmethod(mean_tilde_class, (t_method)mean_tilde_set,
gensym("set"), A_DEFSYM, 0);
class_addmethod(mean_tilde_class, (t_method)mean_tilde_mean,
gensym("mean"), A_DEFSYM, 0);
class_addbang(mean_tilde_class, mean_tilde_bang);
}