/* Calculate SPI assuming incomplete gamma distribution. */
void spi_empiric (int nrun, /* input - run length */
double *pp, /* input - prec array */
/* dimensioned [NYRS][MONTH_OR_WEEK] */
double *index) /* output - index values */
/* also dimensioned [NYRS][MONTH_OR_WEEK] */
{
int im, i, j, n, nsort[MONTH_OR_WEEK];
double *temparr, *sort[MONTH_OR_WEEK], *t_ptr;
temparr = (double *) malloc(sizeof(double)*((NYRS)+1));
for (j = 0; j < nrun-1; j++)
index[j] = MISSING;
for (j = nrun-1; j < NYRS*MONTH_OR_WEEK; j++)
{
index[j] = 0.0;
for (i = 0; i < nrun; i++)
{
if(pp[j - i] != MISSING)
index[j] += pp[j - i];
else
{
index[j] = MISSING;
break;
}
}
}
for (i = 0; i<MONTH_OR_WEEK; i++)
{
t_ptr = temparr;
n = 0;
for (j = nrun+i-1; j<NYRS*MONTH_OR_WEEK; j+=MONTH_OR_WEEK)
{
if(index[j] != MISSING)
{
*t_ptr = index[j];
t_ptr++;
n++;
}
}
im = (nrun + i - 1) % MONTH_OR_WEEK;
nsort[im] = n;
sort[im] = empiric_fit (n, temparr);
}
for (j = nrun-1; j < NYRS*MONTH_OR_WEEK; j++)
{
im = j%MONTH_OR_WEEK;
/*printf("%2d %6.2lf ", im, index[j]);*/
if(index[j] != MISSING)
{
index[j] = empiric_cdf(nsort[im], sort[im], index[j]);
/*printf("%6.2lf ", index[j]);*/
index[j] = inv_normal(index[j]);
/*printf("%6.2lf\n", index[j]);*/
}
}
free(temparr);
for(i=0; i<MONTH_OR_WEEK; i++) free(sort[i]);
}
/* Calculate indices assuming incomplete gamma distribution. */
void spi_gamma (int nrun, /* input - run length */
double *pp, /* input - prec array */
/* dimensioned [NYRS][12] */
double *beta, /* output - beta param */
double *gamm, /* output - gamma param */
double *pzero, /* output - prob of x = 0 */
double *index) /* output - index values */
/* also dimensioned [NYRS][12] */
{
int im, i, j, n;
double *temparr, *t_ptr, alpha;
/* Allocate temporary space */
temparr = (double *) malloc(sizeof(double)*((NYRS)+1));
/* The first nrun-1 index values will be missing. */
for (j = 0; j < nrun-1; j++)
index[j] = MISSING;
/* Sum nrun precip. values;
store them in the appropriate index location.
If any value is missing; set the sum to missing.*/
for (j = nrun-1; j < NYRS*12; j++)
{
index[j] = 0.0;
for (i = 0; i < nrun; i++)
{
if(pp[j - i] != MISSING)
index[j] += pp[j - i];
else
{
index[j] = MISSING;
break;
}
}
}
/* For nrun<12, the monthly distributions will be substantially
different. So we need to compute gamma parameters for
each month starting with the (nrun-1)th. */
for (i = 0; i<12; i++)
{
t_ptr = temparr;
for (j = nrun+i-1; j<NYRS*12; j+=12)
{
if(index[j] != MISSING)
{
*t_ptr = index[j];
t_ptr++;
}
}
n = t_ptr - temparr;
im = (nrun + i - 1) % 12; /* im is the calendar month; 0=jan...*/
/* Here's where we do the fitting. */
gamma_fit (temparr, n, &alpha, &beta[im], &gamm[im], &pzero[im]);
}
/* Replace precip. sums stored in index with SPI's */
for (j = nrun-1; j < NYRS*12; j++)
{
im = j%12;
if(index[j] != MISSING)
{
/* Get the probability */
index[j] = gamma_cdf(beta[im], gamm[im], pzero[im], index[j]);
/* Convert prob. to z value. */
index[j] = inv_normal(index[j]);
}
}
/* Free temp space and return */
free(temparr);
}
