aboutsummaryrefslogtreecommitdiff
path: root/src/scalar.c
diff options
context:
space:
mode:
Diffstat (limited to 'src/scalar.c')
-rw-r--r--src/scalar.c364
1 files changed, 182 insertions, 182 deletions
diff --git a/src/scalar.c b/src/scalar.c
index 8767621..d5d9837 100644
--- a/src/scalar.c
+++ b/src/scalar.c
@@ -26,104 +26,104 @@
#include <stdlib.h>
int xtract_mean(float *data, int N, void *argv, float *result){
-
+
int n = N;
while(n--)
- *result += *data++;
-
+ *result += *data++;
+
*result /= N;
}
int xtract_variance(float *data, int N, void *argv, float *result){
-
+
int n = N;
while(n--)
- *result += *data++ - *(float *)argv;
-
+ *result += *data++ - *(float *)argv;
+
*result = SQ(*result) / (N - 1);
}
int xtract_standard_deviation(float *data, int N, void *argv, float *result){
-
+
*result = sqrt(*(float *)argv);
-
+
}
int xtract_average_deviation(float *data, int N, void *argv, float *result){
-
+
int n = N;
while(n--)
- *result += fabs(*data++ - *(float *)argv);
-
+ *result += fabs(*data++ - *(float *)argv);
+
*result /= N;
}
int xtract_skewness(float *data, int N, void *argv, float *result){
-
+
int n = N;
while(n--)
- *result += (*data++ - ((float *)argv)[0]) / ((float *)argv)[1];
-
+ *result += (*data++ - ((float *)argv)[0]) / ((float *)argv)[1];
+
*result = pow(*result, 3) / N;
}
int xtract_kurtosis(float *data, int N, void *argv, float *result){
-
+
int n = N;
while(n--)
- *result += (*data++ - ((float *)argv)[0]) / ((float *)argv)[1];
-
+ *result += (*data++ - ((float *)argv)[0]) / ((float *)argv)[1];
+
*result = pow(*result, 4) / N - 3;
-
+
}
int xtract_centroid(float *data, int N, void *argv, float *result){
-
+
int n = N;
- float *freqs, *amps, FA, A;
+ float *freqs, *amps, FA, A;
+
+ freqs = data;
+ amps = data + (N >> 1);
- freqs = data;
- amps = data + (N >> 1);
-
while(n--){
- FA += freqs[n] * amps[n];
- A += amps[n];
- }
-
- *result = FA / A;
+ FA += freqs[n] * amps[n];
+ A += amps[n];
+ }
+
+ *result = FA / A;
}
int xtract_irregularity_k(float *data, int N, void *argv, float *result){
-
+
int n,
- M = M - 1;
+ M = M - 1;
for(n = 1; n < M; n++)
- *result += abs(data[n] - (data[n-1] + data[n] + data[n+1]) / 3);
+ *result += abs(data[n] - (data[n-1] + data[n] + data[n+1]) / 3);
}
int xtract_irregularity_j(float *data, int N, void *argv, float *result){
-
+
int n = N;
float num, den;
while(n--){
- num += data[n] - data[n+1];
- den += data[n] * data[n];
+ num += data[n] - data[n+1];
+ den += data[n] * data[n];
}
-
+
*result = num / den;
}
@@ -135,52 +135,52 @@ int xtract_tristimulus_1(float *data, int N, void *argv, float *result){
float den;
while(n--)
- den += data[n];
+ den += data[n];
*result = data[0] / den;
}
int xtract_tristimulus_2(float *data, int N, void *argv, float *result){
-
+
int n = N;
float den;
while(n--)
- den += data[n];
+ den += data[n];
*result = (data[1] + data[2] + data[3]) / den;
-
+
}
int xtract_tristimulus_3(float *data, int N, void *argv, float *result){
-
+
int n = N;
float den, num;
while(n--)
- den += data[n];
+ den += data[n];
num = den - data[0] + data[1] + data[2] + data[3];
-
+
*result = num / den;
-
+
}
int xtract_smoothness(float *data, int N, void *argv, float *result){
-
+
int n = N;
if (data[0] <= 0) data[0] = 1;
if (data[1] <= 0) data[1] = 1;
-
+
for(n = 2; n < N; n++){
- if(data[n] <= 0) data[n] = 1;
- *result += abs(20 * log(data[n-1]) - (20 * log(data[n-2]) +
- 20 * log(data[n-1]) + 20 * log(data[n])) / 3);
- }
+ if(data[n] <= 0) data[n] = 1;
+ *result += abs(20 * log(data[n-1]) - (20 * log(data[n-2]) +
+ 20 * log(data[n-1]) + 20 * log(data[n])) / 3);
+ }
}
int xtract_spread(float *data, int N, void *argv, float *result){
@@ -190,49 +190,49 @@ int xtract_spread(float *data, int N, void *argv, float *result){
float num, den, tmp;
while(n--){
- tmp = n - *(float *)argv;
- num += SQ(tmp) * data[n];
- den += data[n];
+ tmp = n - *(float *)argv;
+ num += SQ(tmp) * data[n];
+ den += data[n];
}
*result = sqrt(num / den);
-
+
}
int xtract_zcr(float *data, int N, void *argv, float *result){
int n = N;
-
+
for(n = 1; n < N; n++)
- if(data[n] * data[n-1] < 0) (*result)++;
-
+ if(data[n] * data[n-1] < 0) (*result)++;
+
*result /= N;
-
+
}
int xtract_rolloff(float *data, int N, void *argv, float *result){
int n = N;
float pivot, temp;
-
+
while(n--) pivot += data[n];
-
+
pivot *= *(float *)argv;
-
+
for(n = 0; temp < pivot; temp += data[n++]);
*result = n;
-
+
}
int xtract_loudness(float *data, int N, void *argv, float *result){
-
+
int n = BARK_BANDS;
-
+
/*if(n != N) return BAD_VECTOR_SIZE; */
while(n--)
- *result += pow(data[n], 0.23);
+ *result += pow(data[n], 0.23);
}
@@ -241,43 +241,43 @@ int xtract_flatness(float *data, int N, void *argv, float *result){
int n = N;
float num, den;
-
+
while(n--){
- if(data[n] !=0){
- num *= data[n];
- den += data[n];
- }
+ if(data[n] !=0){
+ num *= data[n];
+ den += data[n];
+ }
}
num = pow(num, 1 / N);
den /= N;
-
+
*result = 10 * log10(num / den);
-
+
}
int xtract_tonality(float *data, int N, void *argv, float *result){
-
+
float sfmdb, sfm;
-
+
sfm = *(float *)argv;
sfmdb = (sfm > 0 ? (10 * log10(sfm)) / -60 : 0);
-
+
*result = MIN(sfmdb, 1);
-
+
}
int xtract_crest(float *data, int N, void *argv, float *result){
-
- NOT_IMPLEMENTED;
-
+
+ NOT_IMPLEMENTED;
+
}
int xtract_noisiness(float *data, int N, void *argv, float *result){
-
- NOT_IMPLEMENTED;
-
+
+ NOT_IMPLEMENTED;
+
}
int xtract_rms_amplitude(float *data, int N, void *argv, float *result){
@@ -287,32 +287,32 @@ int xtract_rms_amplitude(float *data, int N, void *argv, float *result){
while(n--) *result += SQ(data[n]);
*result = sqrt(*result / N);
-
+
}
int xtract_inharmonicity(float *data, int N, void *argv, float *result){
int n = N;
float num, den,
- *fund, *freq;
+ *fund, *freq;
fund = *(float **)argv;
freq = fund+1;
-
+
while(n--){
- num += abs(freq[n] - n * *fund) * SQ(data[n]);
- den += SQ(data[n]);
+ num += abs(freq[n] - n * *fund) * SQ(data[n]);
+ den += SQ(data[n]);
}
*result = (2 * num) / (*fund * den);
-
+
}
int xtract_power(float *data, int N, void *argv, float *result){
- NOT_IMPLEMENTED;
-
+ NOT_IMPLEMENTED;
+
}
int xtract_odd_even_ratio(float *data, int N, void *argv, float *result){
@@ -322,161 +322,161 @@ int xtract_odd_even_ratio(float *data, int N, void *argv, float *result){
float num, den;
while(n--){
- j = n * 2;
- k = j - 1;
- num += data[k];
- den += data[j];
+ j = n * 2;
+ k = j - 1;
+ num += data[k];
+ den += data[j];
}
*result = num / den;
-
+
}
int xtract_sharpness(float *data, int N, void *argv, float *result){
NOT_IMPLEMENTED;
-
+
}
int xtract_slope(float *data, int N, void *argv, float *result){
NOT_IMPLEMENTED;
-
+
}
int xtract_lowest_match(float *data, int N, void *argv, float *result){
-
+
float lowest_match = SR_LIMIT;
int n = N;
while(n--) {
- if(data[n] > 0)
- lowest_match = MIN(lowest_match, data[n]);
+ if(data[n] > 0)
+ lowest_match = MIN(lowest_match, data[n]);
}
*result = (lowest_match == SR_LIMIT ? 0 : lowest_match);
-
+
}
int xtract_hps(float *data, int N, void *argv, float *result){
int n = N, M, m, l, peak_index, position1_lwr;
float *coeffs2, *coeffs3, *product, L,
- largest1_lwr, peak, ratio1, sr;
+ largest1_lwr, peak, ratio1, sr;
+
+ sr = *(float*)argv;
- sr = *(float*)argv;
-
coeffs2 = (float *)malloc(N * sizeof(float));
coeffs3 = (float *)malloc(N * sizeof(float));
product = (float *)malloc(N * sizeof(float));
-
+
while(n--) coeffs2[n] = coeffs3[n] = 1;
M = N >> 1;
L = N / 3;
while(M--){
- m = M << 1;
- coeffs2[M] = (data[m] + data[m+1]) * 0.5f;
+ m = M << 1;
+ coeffs2[M] = (data[m] + data[m+1]) * 0.5f;
- if(M < L){
- l = M * 3;
- coeffs3[M] = (data[l] + data[l+1] + data[l+2]) / 3;
- }
+ if(M < L){
+ l = M * 3;
+ coeffs3[M] = (data[l] + data[l+1] + data[l+2]) / 3;
+ }
}
-
+
peak_index = peak = 0;
-
+
for(n = 1; n < N; n++){
- product[n] = data[n] * coeffs2[n] * coeffs3[n];
- if(product[n] > peak){
- peak_index = n;
- peak = product[n];
- }
+ product[n] = data[n] * coeffs2[n] * coeffs3[n];
+ if(product[n] > peak){
+ peak_index = n;
+ peak = product[n];
+ }
}
largest1_lwr = position1_lwr = 0;
for(n = 0; n < N; n++){
- if(data[n] > largest1_lwr && n != peak_index){
- largest1_lwr = data[n];
- position1_lwr = n;
- }
+ if(data[n] > largest1_lwr && n != peak_index){
+ largest1_lwr = data[n];
+ position1_lwr = n;
+ }
}
ratio1 = data[position1_lwr] / data[peak_index];
if(position1_lwr > peak_index * 0.4 && position1_lwr <
- peak_index * 0.6 && ratio1 > 0.1)
- peak_index = position1_lwr;
+ peak_index * 0.6 && ratio1 > 0.1)
+ peak_index = position1_lwr;
*result = sr / (float)peak_index;
-
+
free(coeffs2);
free(coeffs3);
free(product);
-
+
}
int xtract_f0(float *data, int N, void *argv, float *result){
- int M, sr, tau, n;
- float f0, err_tau_1, err_tau_x, array_max, threshold_peak, threshold_centre;
-
- sr = *(float *)argv;
-/* threshold_peak = *((float *)argv+1);
- threshold_centre = *((float *)argv+2);
- printf("peak: %.2f\tcentre: %.2f\n", threshold_peak, threshold_centre);*/
- /* add temporary dynamic control over thresholds to test clipping effects */
-
-/* FIX: tweak and make into macros */
- threshold_peak = .8;
- threshold_centre = .3;
- M = N >> 1;
- err_tau_1 = 0;
- array_max = 0;
-
- /* Find the array max */
- for(n = 0; n < N; n++){
- if (data[n] > array_max)
- array_max = data[n];
- }
-
- threshold_peak *= array_max;
-
- /* peak clip */
- for(n = 0; n < N; n++){
- if(data[n] > threshold_peak)
- data[n] = threshold_peak;
- else if(data[n] < -threshold_peak)
- data[n] = -threshold_peak;
- }
-
- threshold_centre *= array_max;
-
- /* Centre clip */
- for(n = 0; n < N; n++){
- if (data[n] < threshold_centre)
- data[n] = 0;
- else
- data[n] -= threshold_centre;
- }
-
- /* Estimate fundamental freq */
- for (n = 1; n < M; n++)
- err_tau_1 = err_tau_1 + fabs(data[n] - data[n+1]);
- /* FIX: this doesn't pose too much load if it returns 'early', but if it can't find f0, load can be significant for larger block sizes M^2 iterations! */
- for (tau = 2; tau < M; tau++){
- err_tau_x = 0;
- for (n = 1; n < M; n++){
- err_tau_x = err_tau_x + fabs(data[n] - data[n+tau]);
+ int M, sr, tau, n;
+ float f0, err_tau_1, err_tau_x, array_max, threshold_peak, threshold_centre;
+
+ sr = *(float *)argv;
+ /* threshold_peak = *((float *)argv+1);
+ threshold_centre = *((float *)argv+2);
+ printf("peak: %.2f\tcentre: %.2f\n", threshold_peak, threshold_centre);*/
+ /* add temporary dynamic control over thresholds to test clipping effects */
+
+ /* FIX: tweak and make into macros */
+ threshold_peak = .8;
+ threshold_centre = .3;
+ M = N >> 1;
+ err_tau_1 = 0;
+ array_max = 0;
+
+ /* Find the array max */
+ for(n = 0; n < N; n++){
+ if (data[n] > array_max)
+ array_max = data[n];
+ }
+
+ threshold_peak *= array_max;
+
+ /* peak clip */
+ for(n = 0; n < N; n++){
+ if(data[n] > threshold_peak)
+ data[n] = threshold_peak;
+ else if(data[n] < -threshold_peak)
+ data[n] = -threshold_peak;
+ }
+
+ threshold_centre *= array_max;
+
+ /* Centre clip */
+ for(n = 0; n < N; n++){
+ if (data[n] < threshold_centre)
+ data[n] = 0;
+ else
+ data[n] -= threshold_centre;
+ }
+
+ /* Estimate fundamental freq */
+ for (n = 1; n < M; n++)
+ err_tau_1 = err_tau_1 + fabs(data[n] - data[n+1]);
+ /* FIX: this doesn't pose too much load if it returns 'early', but if it can't find f0, load can be significant for larger block sizes M^2 iterations! */
+ for (tau = 2; tau < M; tau++){
+ err_tau_x = 0;
+ for (n = 1; n < M; n++){
+ err_tau_x = err_tau_x + fabs(data[n] - data[n+tau]);
+ }
+ if (err_tau_x < err_tau_1) {
+ f0 = sr / (tau + (err_tau_x / err_tau_1));
+ *result = f0;
+ return SUCCESS;
+ }
}
- if (err_tau_x < err_tau_1) {
- f0 = sr / (tau + (err_tau_x / err_tau_1));
- *result = f0;
- return SUCCESS;
- }
- }
- return NO_RESULT;
+ return NO_RESULT;
}
generated by cgit v1.2.3 (git 2.25.1) at 2025-07-03 23:24:10 +0000