mask_en = 0;
vq_search = "gain"; % defaul to gain search method as it's our favourite atm
nvq = 0; % number of vector quantisers
- vq_start = vq_filename = [];
+ vq_start = [];
rate_K_sample_freqs_kHz = [0.1:0.1:4];
K = length(rate_K_sample_freqs_kHz);
% parse command line options
- % set vq search algorithm, e.g. mse, gain, mag, slope. We've settle don "gain" for now
+ % set vq search algorithm, e.g. mse, gain, mag, slope. We've settled on "gain" for now
% as slope required extra bits to quantise higher order parameters that offset advantages
+ weight_en = arg_exists(varargin, "weight");
+
ind = arg_exists(varargin, "vq_search");
if ind
vq_search = varargin{ind+1};
nvq++;
vq_start = [vq_start varargin{ind+1}];
avq_filename = varargin{ind+2};
- vq_filename = [vq_filename; avq_filename];
- printf("nvq %d vq_start: %d vq_filename: %s\n", nvq, vq_start(nvq), avq_filename);
+ if nvq < 2
+ vq_filename = avq_filename;
+ else
+ vq_filename = [vqfilname; avq_filename];
+ end
+ printf("nvq %d vq_start: %d vq_filename: %s weight_en: %d\n", nvq, vq_start(nvq), avq_filename, weight_en > 0);
anind = arg_exists(varargin(ind+1:length(varargin)), "vq");
if anind
ind += anind;
vq_st = vq_start(i); vq_en = vq_st + vq_cols - 1;
printf("split VQ: %d vq_filename: %s vq_st: %d vq_en: %d nVec: %d\n", i, avq_filename, vq_st, vq_en, vq_rows);
+ weights = ones(frames, vq_en - vq_st + 1);
+ if weight_en
+
+ % generate weighting. if min is 20dB and max 40dB, weight at min
+ % is 1 and max 2, same for -10 to 10. So gradient = 0.05, we only
+ % have to calculate y intercept
+
+ for f=1:frames
+ target = rate_K_surface_no_mean(f,vq_st:vq_en);
+ gradient = 0.05; yint = 1 - gradient*min(target);
+ weights(f,:) = gradient*target + yint;
+ end
+ end
+
if strcmp(vq_search, "mse")
[idx contrib errors test_ g mg sl] = vq_search_mse(vq, rate_K_surface_no_mean(:,vq_st:vq_en));
end
if strcmp(vq_search, "gain")
- [idx contrib errors test_ g mg sl] = vq_search_gain(vq, rate_K_surface_no_mean(:,vq_st:vq_en));
+ [idx contrib errors test_ g mg sl] = vq_search_gain(vq, rate_K_surface_no_mean(:,vq_st:vq_en), weights);
end
if strcmp(vq_search, "sg")
- [idx contrib errors test_ g mg sl] = vq_search_gain(vq, rate_K_surface_no_mean(:,vq_st:vq_en));
+ [idx contrib errors test_ g mg sl] = vq_search_sg(vq, rate_K_surface_no_mean(:,vq_st:vq_en));
end
if strcmp(vq_search, "slope")
- [idx contrib errors test_ g mg sl] = vq_search_slope(vq, rate_K_surface_no_mean(:,vq_st:vq_en));
+ [idx contrib errors test_ g mg sl] = vq_search_slope(vq, rate_K_surface_no_mean(:,vq_st:vq_en), weights);
+ end
+
+ if strcmp(vq_search, "para")
+ [idx contrib errors test_ g mg sl] = vq_search_para(vq, rate_K_surface_no_mean(:,vq_st:vq_en), weights);
end
rate_K_surface_no_mean_(:, vq_st:vq_en) = contrib;
hmg(f) = mg(f, idx(f));
hsl(f) = sl(f, idx(f));
end
- figure(fg++); clf; hist(hmg, 30);
- figure(fg++); clf; hist(hsl, 30);
+ figure(fg++); clf; hist(hmg, 30); title('mag')
+ figure(fg++); clf; hist(hsl, 30); title('slope')
end
sd_per_frame = std(res(:,vq_st:vq_en)');
melvq;
Fs = 8000; rate_K_sample_freqs_kHz = [0.1:0.1:4]; K = length(rate_K_sample_freqs_kHz);
- quant_en = 0; vq_search = "mse";
+ quant_en = 0; vq_search = "gain";
+ mask_en = 0;
+ nvec = 0;
+ weight_en = 0;
- % optional full band VQ
+ % optional VQ
ind = arg_exists(varargin, "vq");
if ind
- quant_en = 1;
- vq_filename = varargin{ind+1};
+ nvec++;
+ vq_filename = varargin{ind+2};
x = load(vq_filename); vq = x.vq;
- [vq_rows vq_cols] = size(vq); vq_st = 1; vq_en = vq_cols;
+ [vq_rows vq_cols] = size(vq); vq_st = varargin{ind+1}; vq_en = vq_st + vq_cols - 1;
end
- % optional split VQ low freq quantiser
-
- ind = arg_exists(varargin, "vql");
- if ind
- quant_en = 1;
- vq_filename = varargin{ind+1};
- x = load(vq_filename); vq = x.vq;
- [vq_rows vq_cols] = size(vq); vq_st = 1; vq_en = vq_st + vq_cols - 1;
- end
-
- % optional split VQ high freq quantiser
-
- ind = arg_exists(varargin, "vqh");
- if ind
- quant_en = 1;
- vq_filename = varargin{ind+1};
- x = load(vq_filename); vq = x.vq;
- [vq_rows vq_cols] = size(vq); vq_st = 11; vq_en = K;
- end
-
% different vq search algorithms
ind = arg_exists(varargin, "vq_search");
hold on;
plot(rate_K_sample_freqs_kHz*1000, rate_K_vec, ";rate K;b+-");
- if quant_en
+ if mask_en
+ % experimental masking stuff that I can't seem to get to work
+ maskdB = determine_mask(rate_K_vec, rate_K_sample_freqs_kHz, rate_K_sample_freqs_kHz, bark_model=1);
+ plot(rate_K_sample_freqs_kHz*1000, maskdB, ";mask dB;c+-");
+ end
+
+ if mask_en
+ target = rate_K_vec;
+ mask_thresh = 3;
+ ind = find (maskdB - target > mask_thresh);
+ target(ind) = maskdB(ind) - mask_thresh;
+ plot(rate_K_sample_freqs_kHz*1000, target, ";target;m+-");
+ target = target(vq_st:vq_en) - b;
+ else
target = rate_K_vec_fit(vq_st:vq_en);
+ end
+
+ weights = ones(1, vq_en - vq_st + 1);
+ if weight_en
+
+ % generate weighting. if min is 20dB and max 40dB, weight at min
+ % is 1 and max 2, same for -10 to 10. So gradient = 0.05, we only
+ % haveto calculate y intercept
+
+ gradient = 0.05; yint = 1 - gradient*min(target);
+ weights = gradient*target + yint;
+ end
+
+ if nvec
if strcmp(vq_search, "mse")
[idx contrib errors test_ g mg sl] = vq_search_mse(vq, target);
rate_K_surface_fit_(f, vq_st:vq_en) = contrib;
end
+ if strcmp(vq_search, "gain")
+ [idx contrib errors test_ g mg sl] = vq_search_gain(vq, target, weights);
+ end
+
if strcmp(vq_search, "slope")
- [idx contrib errors test_ g mg sl] = vq_search_slope(vq, target);
+ [idx contrib errors test_ g mg sl] = vq_search_slope1(vq, target, weights);
rate_K_surface_fit_(f, vq_st:vq_en) = contrib;
+ % printf("g: %3.2f mg: %3.2f sl: %3.2f\n", g(idx), mg(idx), sl(idx));
+ end
+
+ if strcmp(vq_search, "para")
+ printf("\n");
+ [idx contrib errors test_ g mg sl] = vq_search_para(vq, target, weights);
+ rate_K_surface_fit_(f, vq_st:vq_en) = contrib;
+ % printf("g: %3.2f mg: %3.2f sl: %3.2f\n", g(idx), mg(idx), sl(idx));
end
rate_K_vec_ = rate_K_vec_fit; rate_K_vec_(vq_st:vq_en) = contrib;
AmdB_ = AmdB_(1:L);
sdL = std(AmdB - AmdB_);
- %printf("f: %d mn_ind: %d g: %3.2f sdK: %3.2f sdL: %3.2f\n",
- % f, mn_ind, g(mn_ind), error(mn_ind), sdL);
-
- plot(rate_K_sample_freqs_kHz(vq_st:vq_en)*1000, target - contrib, ";diff;k+-");
+ plot(rate_K_sample_freqs_kHz(vq_st:vq_en)*1000, contrib, 'm+-');
+ l = sprintf(";diff sd = %3.2f;k+-", sdL);
+ plot(rate_K_sample_freqs_kHz(vq_st:vq_en)*1000, target - contrib, l);
plot((1:L)*Wo*4000/pi, AmdB_,";AmdB bar;r+-");
hold off;
+ end
+ if weight_en
+ figure(3); clf;
+ subplot(211);
+ plot((1:L)*Wo*4000/pi, AmdB,";AmdB;g+-");
+ axis([1 4000 -20 80]);
+ hold on;
+ plot(rate_K_sample_freqs_kHz*1000, rate_K_vec, ";rate K;b+-");
+ hold off;
+ subplot(212);
+ plot(rate_K_sample_freqs_kHz(vq_st:vq_en)*1000, weights);
+ axis([1 4000 0 8]);
end
% interactive menu ------------------------------------------
- printf("\rframe: %d menu: n-next b-back q-quit m-show_quant[%d]", f, quant_en);
+ printf("\rframe: %d menu: n-next b-back q-quit w-weight[%d]", f, weight_en);
fflush(stdout);
k = kbhit();
- if k == 'm'
- quant_en++;
- if quant_en == 2
- quant_en = 0;
+ if k == 'w'
+ weight_en++;
+ if weight_en == 2
+ weight_en = 0;
end
endif
if k == 'n'
--- /dev/null
+%----------------------------------------------------------------------
+% abs() search with a linear, ampl scaling, and slope term
+
+function [idx contrib errors test_ g mg sl] = vq_search_para(vq, data)
+ [nVec nCols] = size(vq);
+ nRows = rows(data);
+
+ g = mg = sl = zeros(nRows, nVec);
+ diff = zeros(nVec, nCols);
+ idx = errors = zeros(1, nRows);
+ error = zeros(1, nVec);
+ contrib = zeros(nRows, nCols);
+ test_ = zeros(nVec, nCols);
+
+ weights = ones(1,nCols);
+
+ A = zeros(4,4,nVec);
+ K = nCols; k=(1:K); k2 = k.^2;
+
+
+ b_log = zeros(nVec, 4);
+
+ for i=1:nVec
+ v = vq(i,:);
+
+ A(:,:,i) = [v*v' k2*v' k*v' sum(v); ...
+ k2*v' k2*k2' k*k2' k*k'; ...
+ k*v' k*k2' k*k' sum(k); ...
+ sum(v) k*k' sum(k) K ];
+ end
+
+ for f=1:nRows
+ t = data(f,:);
+
+ for i=1:nVec
+ v = vq(i,:);
+ c = [t*v' t*k2' t*k' sum(t)]';
+ b = inv(A(:,:,i))*c;
+ diff(i,:) = t - (b(1)*v + b(2)*k2 + b(3)*k + b(4));
+ b_log(i,:) = b;
+ error(i) = diff(i,:) * diff(i,:)';
+
+ %printf("f: %d i: %d e: %f b(1): %f b(2): %f b(3): %f b(4): %f\n", f, i, error(i), b(1), b(2), b(3), b(4));
+ end
+
+ [mn min_ind] = min(error);
+ errors(f) = mn;
+ idx(f) = min_ind(1);
+ b = b_log(min_ind,:);
+ v = vq(min_ind,:);
+
+ printf("f: %d i: %d b(1): %f b(2): %f b(3): %f b(4): %f\n", f, idx(f), b(1), b(2), b(3), b(4));
+ contrib(f,:) = test_(f,:) = b(1)*v + b(2)*k2 + b(3)*k + b(4);
+ end
+
+endfunction
projects / freetel-svn-tracking.git / commitdiff