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+#/*##########################################################################
+# Copyright (c) 2004-2016 European Synchrotron Radiation Facility
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+#
+#############################################################################*/
+#include <math.h>
+#include <stdlib.h>
+#include <stdio.h>
+#include "peaks.h"
+
+
+#define MIN(x, y) (((x) < (y)) ? (x) : (y))
+#define MAX(x, y) (((x) > (y)) ? (x) : (y))
+
+/* Peak search function, adapted from PyMca SpecFitFuns
+
+ This uses a convolution with the second-derivative of a gaussian curve, to
+ smooth the data.
+
+ Arguments:
+
+ - begin_index: First index of the region of interest in the input data
+ array
+ - end_index: Last index of the region of interest in the input data
+ array
+ - nsamples: Number of samples in the input array
+ - fwhm: Full width at half maximum for the gaussian used for smoothing.
+ - sensitivity:
+ - debug_info: If different from 0, print debugging messages
+ - data: input array of 1D data
+ - peaks: pointer to output array of peak indices
+ - relevances: pointer to output array of peak relevances
+*/
+long seek(long begin_index,
+ long end_index,
+ long nsamples,
+ double fwhm,
+ double sensitivity,
+ double debug_info,
+ double *data,
+ double **peaks,
+ double **relevances)
+{
+ /* local variables */
+ double *peaks0, *relevances0;
+ double *realloc_peaks, *realloc_relevances;
+ double sigma, sigma2, sigma4;
+ long max_gfactor = 100;
+ double gfactor[100];
+ long nr_factor;
+ double lowthreshold;
+ double data2[2];
+ double nom;
+ double den2;
+ long channel1;
+ long lld;
+ long cch;
+ long cfac, cfac2, max_cfac;
+ long ihelp1, ihelp2;
+ long i;
+ long max_npeaks = 100;
+ long n_peaks = 0;
+ double peakstarted = 0;
+
+ peaks0 = malloc(100 * sizeof(double));
+ relevances0 = malloc(100 * sizeof(double));
+ if (peaks0 == NULL || relevances0 == NULL) {
+ printf("Error: failed to allocate memory for peaks array.");
+ return(-123456);
+ }
+ /* Make sure the peaks matrix is filled with zeros */
+ for (i=0;i<100;i++){
+ peaks0[i] = 0.0;
+ relevances0[i] = 0.0;
+ }
+ /* Output pointers */
+ *peaks = peaks0;
+ *relevances = relevances0;
+
+ /* prepare the calculation of the Gaussian scaling factors */
+
+ sigma = fwhm / 2.35482;
+ sigma2 = sigma * sigma;
+ sigma4 = sigma2 * sigma2;
+ lowthreshold = 0.01 / sigma2;
+
+ /* calculate the factors until lower threshold reached */
+ nr_factor = 0;
+ max_cfac = MIN(max_gfactor, ((end_index - begin_index - 2) / 2) - 1);
+ for (cfac=0; cfac < max_cfac; cfac++) {
+ nr_factor++;
+ cfac2 = (cfac+1) * (cfac+1);
+ gfactor[cfac] = (sigma2 - cfac2) * exp(-cfac2/(sigma2*2.0)) / sigma4;
+
+ if ((gfactor[cfac] < lowthreshold)
+ && (gfactor[cfac] > (-lowthreshold))){
+ break;
+ }
+ }
+
+ /* What comes now is specific to MCA spectra ... */
+ lld = 0;
+ while (data[lld] == 0) {
+ lld++;
+ }
+ lld = lld + (int) (0.5 * fwhm);
+
+ channel1 = begin_index - nr_factor - 1;
+ channel1 = MAX (channel1, lld);
+ if(debug_info){
+ printf("nrfactor = %ld\n", nr_factor);
+ }
+ /* calculates smoothed value and variance at begincalc */
+ cch = MAX(begin_index, 0);
+ nom = data[cch] / sigma2;
+ den2 = data[cch] / sigma4;
+ for (cfac = 0; cfac < nr_factor; cfac++){
+ ihelp1 = cch-cfac;
+ if (ihelp1 < 0){
+ ihelp1 = 0;
+ }
+ ihelp2 = cch+cfac;
+ if (ihelp2 >= nsamples){
+ ihelp2 = nsamples-1;
+ }
+ nom += gfactor[cfac] * (data[ihelp2] + data[ihelp1]);
+ den2 += gfactor[cfac] * gfactor[cfac] *
+ (data[ihelp2] + data[ihelp1]);
+ }
+
+ /* now normalize the smoothed value to the standard deviation */
+ if (den2 <= 0.0) {
+ data2[1] = 0.0;
+ }else{
+ data2[1] = nom / sqrt(den2);
+ }
+ data[0] = data[1];
+
+ while (cch <= MIN(end_index,nsamples-2)){
+ /* calculate gaussian smoothed values */
+ data2[0] = data2[1];
+ cch++;
+ nom = data[cch]/sigma2;
+ den2 = data[cch] / sigma4;
+ for (cfac = 1; cfac < nr_factor; cfac++){
+ ihelp1 = cch-cfac;
+ if (ihelp1 < 0){
+ ihelp1 = 0;
+ }
+ ihelp2 = cch+cfac;
+ if (ihelp2 >= nsamples){
+ ihelp2 = nsamples-1;
+ }
+ nom += gfactor[cfac-1] * (data[ihelp2] + data[ihelp1]);
+ den2 += gfactor[cfac-1] * gfactor[cfac-1] *
+ (data[ihelp2] + data[ihelp1]);
+ }
+ /* now normalize the smoothed value to the standard deviation */
+ if (den2 <= 0) {
+ data2[1] = 0;
+ }else{
+ data2[1] = nom / sqrt(den2);
+ }
+ /* look if the current point falls in a peak */
+ if (data2[1] > sensitivity) {
+ if(peakstarted == 0){
+ if (data2[1] > data2[0]){
+ /* this second test is to prevent a peak from outside
+ the region from being detected at the beginning of the search */
+ peakstarted=1;
+ }
+ }
+ /* there is a peak */
+ if (debug_info){
+ printf("At cch = %ld y[cch] = %g\n", cch, data[cch]);
+ printf("data2[0] = %g\n", data2[0]);
+ printf("data2[1] = %g\n", data2[1]);
+ printf("sensitivity = %g\n", sensitivity);
+ }
+ if(peakstarted == 1){
+ /* look for the top of the peak */
+ if (data2[1] < data2[0]) {
+ /* we are close to the top of the peak */
+ if (debug_info){
+ printf("we are close to the top of the peak\n");
+ }
+ if (n_peaks == max_npeaks) {
+ max_npeaks = max_npeaks + 100;
+ realloc_peaks = realloc(peaks0, max_npeaks * sizeof(double));
+ realloc_relevances = realloc(relevances0, max_npeaks * sizeof(double));
+ if (realloc_peaks == NULL || realloc_relevances == NULL) {
+ printf("Error: failed to extend memory for peaks array.");
+ *peaks = peaks0;
+ *relevances = relevances0;
+ return(-n_peaks);
+ }
+ else {
+ peaks0 = realloc_peaks;
+ relevances0 = realloc_relevances;
+ }
+ }
+ peaks0[n_peaks] = cch-1;
+ relevances0[n_peaks] = data2[0];
+ n_peaks++;
+ peakstarted=2;
+ }
+ }
+ /* Doublet case */
+ if(peakstarted == 2){
+ if ((cch-peaks0[n_peaks-1]) > 0.6 * fwhm) {
+ if (data2[1] > data2[0]){
+ if(debug_info){
+ printf("We may have a doublet\n");
+ }
+ peakstarted=1;
+ }
+ }
+ }
+ }else{
+ if (peakstarted==1){
+ /* We were on a peak but we did not find the top */
+ if(debug_info){
+ printf("We were on a peak but we did not find the top\n");
+ }
+ }
+ peakstarted=0;
+ }
+ }
+ if(debug_info){
+ for (i=0;i< n_peaks;i++){
+ printf("Peak %ld found at ",i+1);
+ printf("index %g with y = %g\n", peaks0[i],data[(long ) peaks0[i]]);
+ }
+ }
+ *peaks = peaks0;
+ *relevances = relevances0;
+ return (n_peaks);
+}
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