comparison src/vector.c @ 1:b8f2448f7207

Initial import

+/* libxtract feature extraction library
+ *  
+ * Copyright (C) 2006 Jamie Bullock
+ *
+ * This program is free software; you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation; either version 2 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 General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program; if not, write to the Free Software
+ * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301, 
+ * USA.
+ */
+
+
+/* xtract_vector.c: defines functions that extract a feature as a single value from an input vector */
+
+#include "xtract/libxtract.h"
+#include <math.h>
+#include <fftw3.h>
+
+int xtract_magnitude_spectrum(float *data, int N, void *argv, float *result){
+
+    float *temp;
+    int n , M = N >> 1;
+    fftwf_plan plan;
+
+    temp = (float *)fftwf_malloc(N * sizeof(float));
+
+    plan = fftwf_plan_r2r_1d(N, data, temp, FFTW_R2HC, FFTW_ESTIMATE);
+    
+    fftwf_execute(plan);
+    
+    for(n = 1; n < M; n++){
+        result[n] = sqrt(SQ(temp[n]) + SQ(temp[N - n])) / N;
+        result[N-n] = 0.0f;
+    }
+    
+    result[0] = fabs(temp[0]) / N;
+    result[M] = fabs(temp[M]) / N;
+    
+    fftwf_destroy_plan(plan);
+    fftwf_free(temp);
+    
+}
+
+int xtract_autocorrelation(float *data, int N, void *argv, float *result){
+
+    /* Naive time domain implementation  */
+    
+    int n = N, i;
+    
+    float corr;
+
+    while(n--){
+       corr = 0;
+        for(i = 0; i < N - n; i++){
+            corr += data[i] * data[i + n];
+        }
+        result[n] = corr / N;
+    }
+}
+
+int xtract_autocorrelation_fft(float *data, int N, void *argv, float *result){
+    
+    float *temp;
+    int n;
+    fftwf_plan plan;
+
+    temp = (float *)fftwf_malloc(N * sizeof(float));
+    plan = fftwf_plan_r2r_1d(N, data, temp, FFTW_HC2R, FFTW_ESTIMATE);
+
+    fftwf_execute(plan);
+    
+    for(n = 0; n < N - 1; n++)
+        result[n] = temp[n+1];
+    
+    fftwf_destroy_plan(plan);
+    fftwf_free(temp);
+}
+
+int xtract_amdf(float *data, int N, void *argv, float *result){
+
+    int n = N, i;
+    
+    float md;
+
+    while(n--){
+       md = 0;
+        for(i = 0; i < N - n; i++){
+            md += abs(data[i] - data[i + n]);
+        }
+        result[n] = md / N;
+    }
+}
+
+int xtract_asdf(float *data, int N, void *argv, float *result){
+    
+    int n = N, i;
+    
+    float sd;
+
+    while(n--){
+       sd = 0;
+        for(i = 0; i < N - n; i++){
+            sd = 1;
+            sd += SQ(data[i] - data[i + n]);
+        }
+        result[n] = sd / N;
+    }
+}
+
+int xtract_mfcc(float *data, int N, void *argv, float *result){
+
+    xtract_mel_filter *f;
+    int n, filter;
+    fftwf_plan plan;
+
+    f = (xtract_mel_filter *)argv;
+
+    for(filter = 0; filter < f->n_filters; filter++){
+        for(n = 0; n < N; n++){
+            result[filter] += data[n] * f->filters[filter][n];
+        }
+        if(result[filter] < LOG_LIMIT) result[filter] = LOG_LIMIT;
+        result[filter] = log(result[filter]);
+    }
+
+    for(n = filter + 1; n < N; n++) result[n] = 0; 
+    
+    xtract_dct(result, f->n_filters, NULL, result);
+
+}
+
+int xtract_dct(float *data, int N, void *argv, float *result){
+    
+    fftwf_plan plan;
+
+    plan = 
+        fftwf_plan_r2r_1d(N, data, result, FFTW_REDFT00, FFTW_ESTIMATE);
+    
+    fftwf_execute(plan);
+    fftwf_destroy_plan(plan);
+}
+
+int xtract_bark_coefficients(float *data, int N, void *argv, float *result){
+
+    int *limits, band, n;
+
+    limits = (int *)argv;
+    
+    for(band = 0; band < BARK_BANDS; band++){
+        for(n = limits[band]; n < limits[band + 1]; n++)
+            result[band] += data[n];
+    }
+}
+
+int xtract_peaks(float *data, int N, void *argv, float *result){
+
+    float thresh, max, y, y2, y3, p, width, sr; 
+    int n = N, M, return_code;
+    
+    if(argv != NULL){
+        thresh = ((float *)argv)[0];
+        sr = ((float *)argv)[1];
+        return_code = BAD_ARGV;
+    }
+    else{
+        thresh = 0;
+        sr = 44100;
+    }
+
+    M = N >> 1;
+    width = sr / N;
+    
+    y = y2 = y3 = p = max = 0;
+
+    if(thresh < 0 || thresh > 100){
+        thresh = 0;
+        return_code = BAD_ARGV;
+    }
+
+    if(!sr){
+        sr = 44100;
+        return_code = BAD_ARGV;
+    }
+
+    while(n--){
+        max = MAX(max, data[n]);
+        /* ensure we never take log10(0) */
+        /*data[n] = (data[n] < LOG_LIMIT ? LOG_LIMIT : data[n]);*/
+        if ((data[n] * 100000) <= 1)
+        /* We get a more stable peak this way */
+		    data[n] = 1;
+        
+    }
+    
+    thresh *= .01 * max;
+
+    result[0] = 0;
+    result[M] = 0;
+
+    for(n = 1; n < M; n++){
+        if(data[n] >= thresh){
+            if(data[n] > data[n - 1] && data[n] > data[n + 1]){
+                result[n] = width * (n + (p = .5 * (y = 20 * log10(data[n-1]) - (y3 = 20 * log10(data[n+1]))) / (20 * log10(data[n - 1]) - 2 * (y2 = 20 * log10(data[n])) + 20 * log10(data[n + 1]))));
+                result[M + n] = y2 - .25 * (y - y3) * p;
+            }
+            else{
+                result[n] = 0;
+                result[M + n] = 0;
+            }
+        }
+        else{
+            result[n] = 0;
+            result[M + n] = 0;
+        }
+    }	  
+   
+    return (return_code ? return_code : SUCCESS);
+}
+