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/*
** array.c Functions to manipulate/analyze 1-D double precision and
** single precision arrays.
**
** Part of willus.com general purpose C code library.
**
** Copyright (C) 2023 http://willus.com
**
** This program is free software: you can redistribute it and/or modify
** it under the terms of the GNU Affero General Public License as
** published by the Free Software Foundation, either version 3 of the
** License, or (at your option) any later version.
**
** This program is distributed in the hope that it will be useful,
** but WITHOUT ANY WARRANTY; without even the implied warranty of
** MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
** GNU Affero General Public License for more details.
**
** You should have received a copy of the GNU Affero General Public License
** along with this program. If not, see <http://www.gnu.org/licenses/>.
**
*/
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <time.h>
#include <math.h>
#include "willus.h"
static double findminfitd1(double *x,double *y,int n,double x0,double dx,
double *rmserr,int *npfit,double *ymin);
static int array_recfft(double *xr,double *xi,int length);
static int arrayf_recfft(float *xr,float *xi,int length);
static double digit_reverse(int x,int base);
/*
** mean/stdev of y[] from x1 to x2
**
** x[] must be sorted
*/
int array_mean_xy(double *x,double *y,int n,double x1,double x2,double *mean,double *stdev)
{
int i1,i2;
if (mean!=NULL)
(*mean)=0.;
if (stdev!=NULL)
(*stdev)=0.;
for (i1=0;i1<n;i1++)
if (x[i1] >= x1)
break;
if (i1>=n)
return(0);
for (i2=n-1;i2>=0;i2--)
if (x[i2] <= x2)
break;
if (i2<i1)
return(0);
array_mean(&y[i1],i2-i1+1,mean,stdev);
return(i2-i1+1);
}
/*
**
** Compute mean and standard deviation
**
*/
double array_mean(double *a,int n,double *mean,double *stddev)
{
int i;
double sum,avg,sum_sq;
if (n<1)
return(0.);
for (sum=sum_sq=i=0;i<n;i++)
sum += a[i];
avg = sum/n;
if (mean!=NULL)
(*mean) = avg;
if (stddev!=NULL)
{
double sum_sq;
for (sum_sq=i=0;i<n;i++)
sum_sq += (a[i]-avg)*(a[i]-avg);
(*stddev) = sqrt(sum_sq/n);
}
return(avg);
}
double arrayi_mean(int *a,int n,double *mean,double *stddev)
{
int i;
double sum,avg,sum_sq;
if (n<1)
return(0.);
for (sum=sum_sq=i=0;i<n;i++)
sum += a[i];
avg = sum/n;
if (mean!=NULL)
(*mean) = avg;
if (stddev!=NULL)
{
double sum_sq;
for (sum_sq=i=0;i<n;i++)
sum_sq += (a[i]-avg)*(a[i]-avg);
(*stddev) = sqrt(sum_sq/n);
}
return(avg);
}
double array_weighted_mean(double *a,double *w,int n)
{
int i;
double sum,wsum;
if (n<=0)
return(0.);
for (wsum=sum=0.,i=0;i<n;i++)
{
wsum += w[i];
sum += a[i]*w[i];
}
return(wsum==0. ? 0. : sum/wsum);
}
double array_weighted_stddev(double *a,double *w,int n)
{
int i;
double sumsq,sum,wsum,mean,meansq;
if (n<=0)
return(0.);
for (sumsq=wsum=sum=0.,i=0;i<n;i++)
{
wsum += w[i];
sum += a[i]*w[i];
sumsq += a[i]*a[i]*w[i];
}
if (wsum==0.)
return(0.);
mean = sum/wsum;
meansq = sumsq/wsum;
return(sqrt(fabs(meansq-mean*mean)));
}
void array_force_weighted_stddev(double *a,double *w,int n,double newstddev)
{
double mean,oldstddev,f;
int i;
mean=array_weighted_mean(a,w,n);
oldstddev=array_weighted_stddev(a,w,n);
f=newstddev/oldstddev;
for (i=0;i<n;i++)
a[i] = mean + (a[i]-mean)*f;
}
void array_copy(double *dst,double *src,int n)
{
memcpy((void *)dst,(void *)src,n*sizeof(double));
}
void array_fabs(double *a,int n)
{
int i;
for (i=0;i<n;i++)
a[i]=fabs(a[i]);
}
void array_set(double *a,int n,double value)
{
int i;
for (i=0;i<n;i++)
a[i]=value;
}
void array_scale(double *a,int n,double scale_factor,double offset)
{
int i;
for (i=0;i<n;a[i]=a[i]*scale_factor+offset,i++);
}
void array_center(double *a,int n)
{
double min,max,delta;
min=array_min(a,n);
max=array_max(a,n);
delta=(min+(1-max))/2.-min;
array_scale(a,n,1.0,delta);
}
double array_rms(double *a,int n)
{
int i;
double sum;
for (sum=i=0;i<n;i++)
sum += a[i]*a[i];
return(sqrt(sum/n));
}
double array_max(double *a,int n)
{
double max;
int i;
for (max=a[0],i=1;i<n;i++)
if (max<a[i])
max=a[i];
return(max);
}
double array_min(double *a,int n)
{
double min;
int i;
for (min=a[0],i=1;i<n;i++)
if (min>a[i])
min=a[i];
return(min);
}
void array_sort(double *a,int n)
{
sortd(a,(long)n);
}
void array_flipi(int *x,int n)
{
int n2;
int i;
if (n<2)
return;
n2=n/2;
for (i=0;i<n2;i++)
{
int t;
t=x[i];
x[i]=x[n-1-i];
x[n-1-i]=t;
}
}
/*
** n must be >= sw.
** The array is shifted so that a_new[n] = a_old[n+hw],
** where hw = (int)((sw-1)/2)
** e.g. if the sliding window width is 3, then hw = 1.
** The size of the array is reduced by sw-1.
*/
int array_sliding_window(double *a,int n,int sw)
{
double sum;
int i,j;
/* hw=(sw-1)/2; */
for (sum=0.,i=0;i<sw && i<n;i++)
sum += a[i];
if (i>n)
return(0);
for (j=0;i<=n;i++,j++)
{
double t;
t=sum/sw;
if (i<n)
sum+=a[i]-a[i-sw];
a[j]=t;
}
return(j);
}
/*
**
** Loads an n-element array (0..n-1) uniformly with a Hammersley's
** sequence.
**
** If load_type=="all_one", the array is zeroed.
**
** If load_type=="random", the array is loaded entirely randomly with values
** x, such that 0 <= x < 1, using the rand() function.
**
** If load_type=="uniform", the array is loaded uniformly from array[0]=0/n to
** array[n-1]=(n-1)/n.
**
** If load_type=="hbase_n", the arrays is loaded with Hammersley sequence
** n. E.g. load_type=="hbase_3".
**
** Explanation of Hammersley sequence of base 3 (see also digit_reverse):
** -----------------------------------------------------------------------
** Let m be the smallest integer such that 3^m >= n.
** Let M = 3^m.
** Then for each element i, convert i to base 3, reverse the m
** least significant base 3 digits, and divide by M. Assign that
** value to that element.
**
** The best number of array elements to use for a Hammersley's
** sequence is base^n, where n is an integer.
**
*/
void array_load(double *array,int n,char *loadtype)
{
static char *err= "array_load: ";
int i,base;
static int randomized=0;
if (!strcmp(loadtype,"all_one"))
{
array_set(array,n,0.);
return;
}
if (!strcmp(loadtype,"random"))
{
if (!randomized)
{
srand((unsigned)time(NULL)); /* seed the random number generator */
rand();
randomized=1;
}
for (i=0;i<n;i++)
array[i]=(double)rand()/((double)RAND_MAX+1.);
return;
}
if (!strcmp(loadtype,"uniform"))
{
for (i=0;i<n;i++)
array[i]=(double)i/n;
return;
}
if (strncmp(loadtype,"hbase",5))
{
fprintf(stderr,"%sUnknown load type %s.\n",err,loadtype);
return;
}
base = atoi(loadtype[5]=='_' ? &loadtype[6] : &loadtype[5]);
if (base<2)
{
fprintf(stderr,"%sBad Hammersley base %d.\n",err,base);
return;
}
for (i=0;i<n;i++)
{
// The (i+base-1)%n part seems to keep multiple arrays from
// having a correlated 0 index, otherwise all values at index 0
// are the smallest in the distribution.
array[i]=digit_reverse((i+base-1)%n,base);
#ifdef _CRAY
if (array[i]<0 || array[i]>1)
printf("array[%ld]=%g! Bad Hammersley loading!\n",i,array[i]);
#endif
}
}
/*
**
** digit_reverse(long x,int base)
**
** Treats x as base "base" and flips the digits about the decimal
** point. These values, when computed for a consecutive sequence
** of integers for a given base, are known as Hammersley's sequence
** for that base.
**
** Examples: If x==1234 and base==10, then the returned value is
** 0.4321.
**
** If x==34 (base 10) and base==3, then x base 3 is 1021,
** so the returned value is 0.1201 base 3 = 1/3+2/9+1/81 base 10.
**
*/
static double digit_reverse(int x,int base)
{
double result;
int inverse_multiplier;
result=0.;
inverse_multiplier=base;
while (x)
{
result += (double)(x%base)/(double)inverse_multiplier;
inverse_multiplier *= base;
x /= base;
}
return(result);
}
/*
** Find the x-position minimum of an (x,y) curve by fitting a parabola
** about the minimum point in the array. If the parabolic fit does
** not work well, then the x[] array value corresponding to the minimum
** y[] point is returned.
** dxmax is the maximum x-range that will be fitted over.
** errmax is the maximum allowable normalized rms error for the fit.
** If this error is exceeded, the minimum point will be returned
** without using any fitting.
**
** If err is not NULL, it gets the normalized rms error of the fit.
** If npf is not NULL, it gets the number of points fitted.
** If ymin is not NULL, it gets ymin (according to parabolic fit).
** NOTE: The arrays do NOT need to be sorted in x or y.
**
*/
double array_findminfitd(double *x,double *y,int n,double dxmax,double errmax,
double *err,int *npf,double *ymin)
{
int i,ipos,i0,i1,ib1,ib2,imin,npfbest,npf3;
double xb1,xb2,dxmean,xpos,xmin0,ymin0,dy;
double *xd,*yd;
double xmin,confbest,conf3,xmin3,ymin3,yminbest;
static char *funcname="array_findminfitd";
/*
printf("@array_findminfitd...\n");
printf(" n=%d\n",n);
printf(" x[0]=%g, y[0]=%g\n",x[0],y[0]);
printf(" x[%d]=%g, y[%d]=%g\n",n/2,x[n/2],n/2,y[n/2]);
printf(" x[%d]=%g, y[%d]=%g\n",n-1,x[n-1],n-1,y[n-1]);
*/
if (n<1)
return(0.);
imin=array_findminindexd(y,n);
xmin0 = x[imin];
ymin0 = y[imin];
/*
printf(" imin = %d, xmin0 = %g\n",imin,xmin0);
*/
if (n<4)
{
if (ymin!=NULL)
(*ymin) = ymin0;
return(xmin0);
}
if (!willus_mem_alloc(&xd,sizeof(double)*2*n,funcname))
{
fprintf(stderr,"willuslib %s willus_mem_alloc fails (%d elements)\n",
funcname,2*n);
exit(10);
}
yd = &xd[n];
for (i=0;i<n;i++)
{
xd[i]=x[i];
yd[i]=y[i];
}
sortxyd(xd,yd,n);
imin = array_findminindexd(yd,n);
/* Get slightly better initial guess of xmin0 */
ib1=ib2=imin;
for (;ib1>=0 && yd[ib1]==yd[imin];ib1--);
ib1++;
for (;ib2<=n-1 && yd[ib2]==yd[imin];ib2++);
ib2--;
if (ib1<=0 || ib2>=n-1)
{
willus_mem_free(&xd,funcname);
if (ymin!=NULL)
(*ymin) = ymin0;
return(xmin0);
}
i0 = ib1-1;
i1 = ib2+1;
dy = yd[i0]-yd[imin] > yd[i1]-yd[imin] ? yd[i0]-yd[imin] : yd[i1]-yd[imin];
if (yd[i0]-yd[imin] < 0.2*dy)
ib1--;
else if (yd[i1]-yd[imin] < 0.2*dy)
ib2++;
i0=ib1;
i1=ib2;
/* Recompute xmin0 */
for (xmin0=ymin0=0,i=i0;i<=i1;i++)
{
xmin0 += xd[i];
ymin0 += yd[i];
}
xmin0 /= (i1-i0+1);
ymin0 /= (i1-i0+1);
/*
printf(" xmin0 = %g\n",xmin0);
*/
ib1 = i0>2 ? i0-3 : 0;
ib2 = i1<n-3 ? i1+3 : n-1;
if (ib1==ib2)
{
willus_mem_free(&xd,funcname);
if (ymin!=NULL)
(*ymin)=ymin0;
return(xmin0);
}
xb1 = xd[ib1];
xb2 = xd[ib2];
dxmean = (xb2-xb1)/(ib2-ib1);
if (dxmean<=0.)
{
willus_mem_free(&xd,funcname);
if (ymin!=NULL)
(*ymin)=ymin0;
return(xmin0);
}
confbest=conf3= -1;
npfbest=npf3=0;
xmin = xmin3 = xmin0;
yminbest = ymin3 = ymin0;
/* Try some different parabolic fits around the minimum point */
/* and choose the best one. */
/*
{
double dxbest,dxbest3;
*/
for (ipos=-2;ipos<=2;ipos++)
{
int i0;
xpos = xmin0+ipos*dxmean;
i0 = fabs((double)ipos)+1.1;
for (i=i0;dxmean*i*2.<=dxmax;i++)
{
double x1,conf,rmserr,ymin1;
int npfit;
npfit=0; /* Avoid compiler warning. */
ymin1=rmserr=0.; /* Avoid compiler warning. */
x1 = findminfitd1(xd,yd,n,xpos,dxmean*(i+.6),&rmserr,&npfit,&ymin1);
if (x1<x[0] || x1<xpos-dxmean*i || x1>xpos+dxmean*i)
continue;
conf = rmserr; /* / (npfit-1); */
/*
printf("xpos = %g, dx=%g, np=%d, rmserr=%g, conf=%g\n",
xpos,dxmean*i,npfit,rmserr,conf);
printf("%g %g %d\n",x1,conf,npfit);
*/
if (npfit>3 && conf<errmax && (confbest < 0 || conf < confbest))
{
/*
dxbest = dxmean*(i+.6);
*/
confbest = conf;
xmin = x1;
npfbest = npfit;
yminbest = ymin1;
}
else if (npfit==3 && conf<errmax && (conf3 <0 || conf < conf3))
{
/*
dxbest3 = dxmean*(i+.6);
*/
conf3 = conf;
xmin3 = x1;
npf3 = npfit;
ymin3 = ymin1;
}
}
}
willus_mem_free(&xd,funcname);
if (confbest<0 && conf3>=0.)
{
xmin = xmin3;
confbest = conf3;
npfbest = npf3;
yminbest = ymin3;
/*
dxbest = dxbest3;
*/
}
/*
printf("dxbest = %g\n",dxbest);
}
*/
if (err!=NULL)
(*err) = confbest;
if (npf!=NULL)
(*npf) = npfbest;
if (ymin!=NULL)
(*ymin) = yminbest;
/*
printf("confbest = %g, conf3 = %g, xmin = %g\n",confbest,conf3,xmin);
*/
return(xmin);
}
int array_findminindexd(double *y,int n)
{
int i,imin;
for (imin=0,i=1;i<n;i++)
if (y[i] < y[imin])
imin=i;
return(imin);
}
/*
** Finds minimum of (x,y) curve (in y) by fitting parabola about
** points near x0.
** The fit range is determined +/-dx.
** The x[] array must be sorted (monotonically increasing from 0 to n-1).
** (*rmserr) gets the normalized rms error of the fit.
** [The normalization is to divide it by dy, the total range in y]
** (*npfit) gets the number of points fitted.
** The routine will fail if it cannot
** find at least 3 (in which case the rms error will be zero).
*/
static double findminfitd1(double *x,double *y,int n,double x0,double dx,
double *rmserr,int *npfit,double *ymin)
{
double c[3];
int i,i1,i2;
double errval,dy;
errval = x[0] - (x[n-1]-x[0]) - 1.0;
for (i=0;i<n;i++)
if (x[i] >= x0-dx)
break;
i1=i;
for (;i<n;i++)
if (x[i] > x0+dx)
break;
i2=i-1;
if (i2-i1+1 < 3)
return(errval);
if (npfit!=NULL)
(*npfit) = (i2-i1+1);
dy = array_max(&y[i1],i2-i1+1) - array_min(&y[i1],i2-i1+1);
if (dy<=0.)
return(errval);
wpolyfitd(&x[i1],&y[i1],i2-i1+1,2,c);
if (fabs(c[2])<1e-10)
return(errval);
if (rmserr!=NULL)
{
double err;
err=0;
for (i=i1;i<=i2;i++)
{
double yf;
yf = x[i]*x[i]*c[2] + x[i]*c[1] + c[0];
err += (yf-y[i])*(yf-y[i]);
}
(*rmserr) = sqrt(err/(i2-i1+1))/dy;
}
if (ymin!=NULL)
(*ymin) = c[0] - c[1]*c[1]/(4*c[2]);
return(-c[1]/(2.*c[2]));
}
/*
** Returns 1 for success, 0 if memory allocation error
**
** NOTE: if the input is totally real (all xi[] values are zero),
** then the FFT will have an even real part and an odd imaginary part.
*/
int array_fft(double *xr,double *xi,int n)
{
return(array_recfft(xr,xi,n));
}
/*
** Returns 1 for success, 0 if memory allocation error
*/
int array_ifft(double *xr,double *xi,int n)
{
int i;
for (i=0;i<n;i++)
xi[i]=-xi[i];
if (!array_fft(xr,xi,n))
return(0);
for (i=0;i<n;i++)
{
xr[i]/=n;
xi[i]/=-n;
}
return(1);
}
/*
**
** RECFFT Recursive FFT function used to calculate the FFT of a
** sequence. The sequence can be ANY length, however, if
** the length doesn't factor well, the calculations will
** approach normal DFT speeds.
**
** willus.com, July 20, 1989
**
**
*/
static int array_recfft(double *xr,double *xi,int length)
{
static int len=0;
static double *wr,*wi,*txr,*txi;
static int j,i1,i2,index;
int i,step,f1,f2;
static char *funcname="array_recfft";
if (length==1)
return(1);
if (length<=0)
return(0);
/*
** Initialization code, first pass of the function
*/
if (len==0)
{
if (!willus_mem_alloc(&wr,4L*sizeof(double)*length,funcname))
return(0);
wi=&wr[length];
txr=&wi[length];
txi=&txr[length];
for (i=0;i<length;i++)
{
wi[i]=sin(2*PI*(double)i/(double)length);
wr[i]=cos(2*PI*(double)i/(double)length);
wi[i]=-wi[i];
}
len=length;
}
/*
** Factor the length into two smaller multiples
*/
if (length%2==0)
f1=2;
else
if (length%3==0)
f1=3;
else
{
j=sqrt((double)length)+1;
for (i=5;i<=j;i+=4)
{
if (length%i==0)
break;
i+=2;
if (i>j)
break;
if (length%i==0)
break;
}
f1=(i>j)?length:i;
}
f2=length/f1;
/*
** Now do the FFT's of the factors, calling this function recursively.
*/
step=len/length;
if (f2>1)
for (i=0;i<f1;i++)
array_recfft(&xr[i*step],&xi[i*step],f2);
/*
** Recombine the FFT's of the factors to get the final result.
*/
for (i=0;i<length;i++)
{
txr[i]=0;
txi[i]=0;
index=i%f2*step*f1;
for (j=0;j<f1;j++)
{
i1=index+j*step;
i2=i*j%length*step;
txr[i] += xr[i1]*wr[i2] - xi[i1]*wi[i2];
txi[i] += xr[i1]*wi[i2] + xi[i1]*wr[i2];
}
}
for (i=0,j=0;i<length;i++,j+=step)
{
xr[j]=txr[i];
xi[j]=txi[i];
}
/*
** Clean up
*/
if (length==len)
{
willus_mem_free(&wr,funcname);
len=0;
}
return(1);
}
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/* SINGLE PRECISION STARTS HERE */
/* ==================================================================== */
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int arrayf_find_max_point(float *x0,float *y0,float *x,float *y,int n)
{
double c[3];
double *tx,*ty;
double xoff,yoff;
int i;
willus_mem_alloc_warn((void **)&tx,sizeof(double)*2*n,"arrayf_find_max_point",10);
ty = &tx[n];
for (xoff=yoff=0.,i=0;i<n;i++)
{
xoff += x[i];
yoff += y[i];
}
xoff /= n;
yoff /= n;
for (i=0;i<n;i++)
{
tx[i] = x[i]-xoff;
ty[i] = y[i]-yoff;
}
wpolyfitd(tx,ty,n,2,c);
willus_mem_free((double **)&tx,"array_find_max_point");
if (c[2]==0)
return(-1);
(*x0)= (float)(-c[1]/(2.*c[2]));
(*y0)= (float)(c[2]*(*x0)*(*x0) + c[1]*(*x0) + c[0] + yoff);
(*x0) = (*x0) + xoff;
return(0);
}
/*
// Find y = m*x + b equation for line fit
*/
void arrayf_get_lsq_slope(float *m,float *b,float *x,float *y,int n)
{
double c[2];
double *tx,*ty;
double xoff,yoff;
int i;
willus_mem_alloc_warn((void **)&tx,sizeof(double)*2*n,"arrayf_get_lsq_slope",10);
ty = &tx[n];
for (xoff=yoff=0.,i=0;i<n;i++)
{
xoff += x[i];
yoff += y[i];
}
xoff /= n;
yoff /= n;
for (i=0;i<n;i++)
{
tx[i] = x[i]-xoff;
ty[i] = y[i]-yoff;
}
wpolyfitd(tx,ty,n,1,c);
willus_mem_free((double **)&tx,"arrayf_get_lsq_slope");
(*m)=(float)c[1];
(*b)=(float)(c[0]+yoff);
}
int arrayf_is_linear(float *x,int n)
{
int i;
float xp,x0,x1,xav;
if (n<3)
return(1);
x0=x[0];
x1=x[n-1];
xav=(x0+x1)/2.;
if (xav==0)
xav=(x1-x0);
if (xav==0)
xav=1;
for (i=1;i<n-1;i++)
{
xp=x0+(x1-x0)*i/(n-1);
if (fabs((xp-x[i])/xav)>1e-5)
return(0);
}
return(1);
}
/*
** Linearize
*/
int arrayf_linearize_xyz(float *x,float *y,float *z,int n,int newn)
{
float *x0,*y0,*z0;
int i;
float xx;
if (!willus_mem_alloc((double **)&x0,sizeof(float)*3*newn,"arrayf_linearize_xyz"))
return(1);
y0=&x0[newn];
z0=&y0[newn];
for (i=0;i<newn;i++)
{
xx = x[0] + (x[n-1]-x[0])*(double)i/(newn-1);
x0[i]=xx;
y0[i]=interpxy(xx,x,y,n);
z0[i]=interpxy(xx,x,z,n);
}
for (i=0;i<newn;i++)
{
x[i]=x0[i];
y[i]=y0[i];
z[i]=z0[i];
}
willus_mem_free((double **)&x0,"arrayf_linearize_xyz");
return(0);
}
int arrayf_max_index(float *x,int n)
{
int i,imax;
for (imax=0,i=1;i<n;i++)
if (x[imax]<x[i])
imax=i;
return(imax);
}
float arrayf_maxdev(float *x,int n)
{
return(arrayf_max(x,n)-arrayf_min(x,n));
}
/*
**
** Compute mean and standard deviation
**
*/
void arrayf_mean(float *a,int n,double *mean,double *stddev)
{
int i;
double sum,avg,sum_sq;
if (n<1)
return;
for (sum=sum_sq=i=0;i<n;i++)
sum += a[i];
avg = sum/n;
if (mean!=NULL)
(*mean) = avg;
if (stddev!=NULL)
{
float sum_sq;
for (sum_sq=i=0;i<n;i++)
sum_sq += (a[i]-avg)*(a[i]-avg);
(*stddev) = sqrt(sum_sq/n);
}
}
double arrayf_rms(float *a,int n)
{
int i;
double sum;
for (sum=i=0;i<n;i++)
sum += a[i]*a[i];
return(sqrt(sum/n));
}
float arrayf_max(float *a,int n)
{
float max;
int i;
for (max=a[0],i=1;i<n;i++)
if (max<a[i])
max=a[i];
return(max);
}
float arrayf_min(float *a,int n)
{
float min;
int i;
for (min=a[0],i=1;i<n;i++)
if (min>a[i])
min=a[i];
return(min);
}
void arrayf_sort(float *a,int n)
{
sort(a,(long)n);
}
/*
** Returns 1 for success, 0 if memory allocation error
*/
int arrayf_fft(float *xr,float *xi,int n)
{
return(arrayf_recfft(xr,xi,n));
}
/*
** Returns 1 for success, 0 if memory allocation error
*/
int arrayf_ifft(float *xr,float *xi,int n)
{
int i;
for (i=0;i<n;i++)
xi[i]=-xi[i];
if (!arrayf_fft(xr,xi,n))
return(0);
for (i=0;i<n;i++)
{
xr[i]/=n;
xi[i]/=-n;
}
return(1);
}
/*
**
** RECFFT Recursive FFT function used to calculate the FFT of a
** sequence. The sequence can be ANY length, however, if
** the length doesn't factor well, the calculations will
** approach normal DFT speeds.
**
** willus.com, July 20, 1989
**
**
*/
static int arrayf_recfft(float *xr,float *xi,int length)
{
static int len=0;
static float *wr,*wi,*txr,*txi;
static int j,i1,i2,index;
int i,step,f1,f2;
static char *funcname="arrayf_recfft";
if (length==1)
return(1);
if (length<=0)
return(0);
/*
** Initialization code, first pass of the function
*/
if (len==0)
{
if (!willus_mem_alloc((double **)&wr,sizeof(float)*4L*length,funcname))
return(0);
wi=&wr[length];
txr=&wi[length];
txi=&txr[length];
for (i=0;i<length;i++)
{
double s,c;
s=sin(2.*PI*i/length);
c=cos(2.*PI*i/length);
wr[i]=(float)c;
wi[i]=-(float)s;
}
len=length;
}
/*
** Factor the length into two smaller multiples
*/
if (length%2==0)
f1=2;
else
if (length%3==0)
f1=3;
else
{
j=sqrt((float)length)+1;
for (i=5;i<=j;i+=4)
{
if (length%i==0)
break;
i+=2;
if (i>j)
break;
if (length%i==0)
break;
}
f1=(i>j)?length:i;
}
f2=length/f1;
/*
** Now do the FFT's of the factors, calling this function recursively.
*/
step=len/length;
if (f2>1)
for (i=0;i<f1;i++)
arrayf_recfft(&xr[i*step],&xi[i*step],f2);
/*
** Recombine the FFT's of the factors to get the final result.
*/
for (i=0;i<length;i++)
{
txr[i]=0;
txi[i]=0;
index=i%f2*step*f1;
for (j=0;j<f1;j++)
{
i1=index+j*step;
i2=i*j%length*step;
txr[i] += xr[i1]*wr[i2] - xi[i1]*wi[i2];
txi[i] += xr[i1]*wi[i2] + xi[i1]*wr[i2];
}
}
for (i=0,j=0;i<length;i++,j+=step)
{
xr[j]=txr[i];
xi[j]=txi[i];
}
/*
** Clean up
*/
if (length==len)
{
willus_mem_free((double **)&wr,funcname);
len=0;
}
return(1);
}
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