some comments added

find_songs_from_hand_annotations.m

@@ -0,0 +1,100 @@
+function likelihoodModels = find_songs_from_hand_annotations(male_songs,female_songs,overlap_songs)
+%Inputs arrays of selected male, female, and overlap song and outputs
+%likelihood models
+%Inputs:
+%   male_songs -> N_male x length(frequencies) array of male song wavelet amplitudes
+%   female_songs -> N_female x length(frequencies) array of female song wavelet amplitudes
+%   overlap_songs -> N_overlap x length(frequencies) array of overlapping song amplitudes
+%
+%Output:
+%   likelihoodModels -> struct containing likelihood models needed to run
+%                       segmentVirilisSong.m
+%
+% (C) Gordon J. Berman, Jan Clemens, Kelly M. LaRue, and Mala Murthy, 2015
+%     Princeton University
+
+
+    %load parameters
+    segParams = params_virilis();
+
+    probModes = segParams.probModes;
+    maxNumPeaks = segParams.maxNumPeaks;
+    maxNumPeaks_firstMode = segParams.maxNumPeaks_firstMode;
+    frequencies = segParams.fc;
+    gmm_replicates = segParams.gmm_replicates;
+    maxNumGMM = segParams.maxNumGMM;
+
+    fprintf(1,'Finding Male Principal Components\n');
+    male_mean = mean(male_songs);
+    [coeffs_male,scores_male,latent_male] = princomp(male_songs);
+
+
+    fprintf(1,'Finding Female Principal Components\n');
+    female_mean = mean(female_songs);
+    [coeffs_female,scores_female,latent_female] = princomp(female_songs);
+
+
+    if nargin >= 3 && isempty(overlap_songs)
+        fprintf(1,'Finding Overlap Principal Components\n');
+        both_mean = mean(overlap_songs);
+        [coeffs_both,scores_both,latent_both] = princomp(overlap_songs);
+    end
+
+
+
+    fprintf(1,'Finding PDFs\n');
+
+    malePDFs = cell(probModes,1);
+    femalePDFs = cell(probModes,1);
+    if nargin >= 3 && isempty(overlap_songs)
+        bothPDFs = cell(probModes,1);
+    end
+    for i=1:probModes
+
+        fprintf(1,'\t #%2i of %2i\n',i,probModes);
+        if i == 1
+            q = maxNumPeaks_firstMode;
+        else
+            q = maxNumPeaks;
+        end
+
+        malePDFs{i} = findBestGMM_AIC(scores_male(:,i),q,gmm_replicates,maxNumGMM);
+        femalePDFs{i} = findBestGMM_AIC(scores_female(:,i),q,gmm_replicates,maxNumGMM);
+        if nargin >= 3 && isempty(overlap_songs)
+            bothPDFs{i} = findBestGMM_AIC(scores_both(:,i),q,gmm_replicates,maxNumGMM);
+        end
+    end
+
+
+    likelihoodModels.malePDFs = malePDFs;
+    likelihoodModels.femalePDFs = femalePDFs;
+    likelihoodModels.noisePDFs = noisePDFs;    
+
+    likelihoodModels.male_mean = male_mean;
+    likelihoodModels.female_mean = female_mean;
+    likelihoodModels.noise_mean = noise_mean;    
+
+    likelihoodModels.coeffs_male = coeffs_male;
+    likelihoodModels.coeffs_female = coeffs_female;
+    likelihoodModels.coeffs_noise = coeffs_noise;
+
+    likelihoodModels.latent_male = latent_male;
+    likelihoodModels.latent_female = latent_female;
+    likelihoodModels.latent_noise = latent_noise;
+
+    likelihoodModels.probModes = probModes;
+    likelihoodModels.frequencies = frequencies;
+
+    K = scal2frq(1,wav,segParams.dt);
+    scales = K ./ frequencies;
+    likelihoodModels.scales = scales;
+
+
+    if nargin >= 3 && isempty(overlap_songs)
+        likelihoodModels.bothPDFs = bothPDFs;
+        likelihoodModels.both_mean = both_mean;
+        likelihoodModels.coeffs_both = coeffs_both;
+        likelihoodModels.latent_both = latent_both;
+    end
+
+

find_songs_from_hand_annotations.m~

@@ -0,0 +1,84 @@
+function likelihoodModels = find_songs_from_hand_annotations(male_songs,female_songs,overlap_songs)
+%Inputs arrays of selected male, female, and overlap song, 
+
+    %load parameters
+    segParams = params_virilis();
+
+    probModes = segParams.probModes;
+    maxNumPeaks = segParams.maxNumPeaks;
+    maxNumPeaks_firstMode = segParams.maxNumPeaks_firstMode;
+    frequencies = segParams.fc;
+    gmm_replicates = segParams.gmm_replicates;
+    maxNumGMM = segParams.maxNumGMM;
+
+    fprintf(1,'Finding Male Principal Components\n');
+    male_mean = mean(male_songs);
+    [coeffs_male,scores_male,latent_male] = princomp(male_songs);
+
+
+    fprintf(1,'Finding Female Principal Components\n');
+    female_mean = mean(female_songs);
+    [coeffs_female,scores_female,latent_female] = princomp(female_songs);
+
+
+    if nargin >= 3 && isempty(overlap_songs)
+        fprintf(1,'Finding Overlap Principal Components\n');
+        both_mean = mean(overlap_songs);
+        [coeffs_both,scores_both,latent_both] = princomp(overlap_songs);
+    end
+
+
+
+    fprintf(1,'Finding PDFs\n');
+
+    malePDFs = cell(probModes,1);
+    femalePDFs = cell(probModes,1);
+    if nargin >= 3 && isempty(overlap_songs)
+        bothPDFs = cell(probModes,1);
+    end
+    for i=1:probModes
+
+        fprintf(1,'\t #%2i of %2i\n',i,probModes);
+        if i == 1
+            q = maxNumPeaks_firstMode;
+        else
+            q = maxNumPeaks;
+        end
+
+        malePDFs{i} = findBestGMM_AIC(scores_male(:,i),q,gmm_replicates,maxNumGMM);
+        femalePDFs{i} = findBestGMM_AIC(scores_female(:,i),q,gmm_replicates,maxNumGMM);
+        if nargin >= 3 && isempty(overlap_songs)
+            bothPDFs{i} = findBestGMM_AIC(scores_both(:,i),q,gmm_replicates,maxNumGMM);
+        end
+    end
+
+
+    likelihoodModels.malePDFs = malePDFs;
+    likelihoodModels.femalePDFs = femalePDFs;
+    likelihoodModels.noisePDFs = noisePDFs;    
+
+    likelihoodModels.male_mean = male_mean;
+    likelihoodModels.female_mean = female_mean;
+    likelihoodModels.noise_mean = noise_mean;    
+
+    likelihoodModels.coeffs_male = coeffs_male;
+    likelihoodModels.coeffs_female = coeffs_female;
+    likelihoodModels.coeffs_noise = coeffs_noise;
+
+    likelihoodModels.latent_male = latent_male;
+    likelihoodModels.latent_female = latent_female;
+    likelihoodModels.latent_noise = latent_noise;
+
+    likelihoodModels.probModes = probModes;
+    likelihoodModels.frequencies = frequencies;
+    likelihoodModels.scales = scales;
+
+
+    if nargin >= 3 && isempty(overlap_songs)
+        likelihoodModels.bothPDFs = bothPDFs;
+        likelihoodModels.both_mean = both_mean;
+        likelihoodModels.coeffs_both = coeffs_both;
+        likelihoodModels.latent_both = latent_both;
+    end
+
+