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detEdit.m
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detEdit.m
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% detEdit.m
% 2/21/2016 modified for version 1.1
% For Kogia JAH 5/22/15
% Estimate the number of False Detections
% JAH 10-19-2014
% spec2 uses the LTSA for the click spectra
% spec3 uses the TPWS file for the click spectra JAH 9-26-14
% spcc4 used the TPWS2 file JAH 10-12-14
% 7-7-14 use Simone bouts and Sean Detector JAH
% includes brushing FD, MD in and out of files
% Brushing only works in MATLAB ver 2013b, not 2013a or 2012b
% modified for BW 140308 jah 140320 jah for small ici
% 140311 smw detection editor based on evalSessions.m
clearvars
% utSetDesktopTitle('detEdit');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Load user input. Has to happen first so you know species.
detEdit_settings_kelby
% define subfolder that fit specified iteration
% if itnum > 1
% for id = 2: str2num(itnum); % iternate id times according to itnum
% subfolder = ['TPWS',num2str(id)];
% sdir = (fullfile(sdir,subfolder));
% end
% end
%% Load Settings preferences
% Get parameter settings worked out between user preferences, defaults, and
% species-specific settings:
p = sp_setting_defaults('sp',sp,'srate',srate,'analysis','detEdit','spParamsUser',spParamsUser);
%% Check if TPWS file exists
% Concatenate parts of file name
if isempty(p.speName)
detfn = [filePrefix,'.*','TPWS',itnum,'.mat'];
else
detfn = [filePrefix,'.*',p.speName,'.*TPWS',itnum,'.mat'];
end
% Get a list of all the files in the start directory
fileList = cellstr(ls(sdir));
% Find the file name that matches the filePrefix
fileMatchIdx = find(~cellfun(@isempty,regexp(fileList,detfn))>0);
if isempty(fileMatchIdx)
% if no matches, throw error
error('No files matching filePrefix found!')
elseif length(fileMatchIdx)>1
% if more than one match, throw error
error('Multiple TPWS files match the filePrefix. Make the prefix more specific.')
end
matchingFile = fileList{fileMatchIdx};
fnTPWS = fullfile(sdir,matchingFile);
%% Handle Transfer Function
% add in transfer function if desired
if p.tfSelect > 0
if ~exist('tfName','var')% user interface to get TF file
disp('Load Transfer Function File');
[fname,pname] = uigetfile('I:\Harp_TF\*.tf','Load TF File');
tffn = fullfile(pname,fname);
else % or get it automatically from tf directory provided in settings
stndeploy = strsplit(filePrefix,'_'); % get only station and deployment
tffn = findTfFile(tfName,stndeploy); % get corresponding tf file
end
if strcmp(num2str(fname),'0')
disp('Cancelled TF File');
return
else %give feedback
disp(['TF File: ',tffn]);
end
fid = fopen(tffn);
[A,count] = fscanf(fid,'%f %f',[2,inf]);
tffreq = A(1,:);
tfuppc = A(2,:);
fclose(fid);
tf = interp1(tffreq,tfuppc,p.tfSelect,'linear','extrap');
disp(['TF @',num2str(p.tfSelect),' Hz =',num2str(tf)]);
else
tf = 0;
disp('No TF Applied');
end
%% Generate FD, TD, and ID files if needed
% Name and build false detection file
ffn = strrep(matchingFile,'TPWS','FD');
fnameFD = fullfile(sdir,ffn);
AFD = exist(fnameFD,'file');
if (AFD ~= 2) % if it doesn't exist, make it
zFD(1,1) = 1;
save(fnameFD,'zFD');
disp('Make new FD file');
end
% Name true detection file
tfn = strrep(matchingFile,'TPWS','TD');
fnameTD = fullfile(sdir,tfn);
% NOTE: TD file is made below because it depends on a later variable
% Name and build ID file
idfn = strrep(matchingFile,'TPWS','ID');
fnameID = fullfile(sdir,idfn);
AID = exist(fnameID,'file');
if (AID ~= 2)% if it doesn't exist, make it
zID = [];
save(fnameID,'zID');
disp('Make new ID file');
end
% Name and build ID file
mdfn = strrep(matchingFile,'TPWS','MD');
fnameMD = fullfile(sdir,mdfn);
AMD = exist(fnameMD,'file');
if (AMD ~= 2)% if it doesn't exist, make it
zMD = [];
save(fnameMD,'zMD');
disp('Make new MD file');
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Load detections and false detections
% MTT = time MPP = peak-peak % MSN = waveform %MSP = spectra
load(fnTPWS,'MTT','MPP')
% if you have more than "maxDetLoad" detections, don't load all spectra and
% time series into memory. You can access them from the disk instead.
% Note: Can't remove duplicates in that case, because matlab won't let you
% select non-contiguous sets from files stored on disk.
nDets = length(MTT);
if ~exist('maxDetLoad')
loadMSP = true;
elseif isempty(maxDetLoad)
loadMSP = true;
else
loadMSP = nDets <= maxDetLoad; % true/false, if you have more detections than
end
% the maximum load this becomes false.
ic1 = [];
if loadMSP
% remove duplicates from MTT (can't do this if too many detections to load into memory).
[uMTT,ia1,ic1] = unique(MTT);
if (length(uMTT) ~= length(MTT))
disp([' TimeLevel Data NOT UNIQUE - removed: ', ...
num2str(length(ic1) - length(ia1))]);
end
load(fnTPWS,'MSP','MSN')
else
ia1 = [1:length(MTT)]';
end
[r,c] = size(MTT); %get shape of array
if (r > c)
clickTimes = MTT(ia1);
clickLevels = MPP(ia1);
else
clickTimes = MTT(ia1)';
clickLevels = MPP(ia1)';
end
if specploton && loadMSP
% if specploton and there aren't too many detections, load spectra
csn = MSN(ia1,:);
csp = MSP(ia1,:);
else
disp('No Waveform or Spectra');
end
%% apply tf and remove low amplitude detections
clickLevels = clickLevels + tf;
ib1 = find(clickLevels >= p.threshRL);
if (size(ib1,1) ~= size(clickLevels,1)) && ~loadMSP % catch for case where enforcing
% min RL threshold on large dataset creates non-continuous indices.
error('detEdit:RL',['Error: Re-run makeTPWS to enforce your minimum peak to peak RL threshold.\n',...
'You cannot do it here because you have too many detections to load into memory.\n',...
sprintf('TPWS minimum RL = %d \ndetEdit minimum RL = %d',min(clickLevels),p.threshRL)])
end
if (size(ib1,1) == 0)
% min RL threshold excludes all detections
error('detEdit:RL',['Error: No detections meet the minimum peak to peak RL threshold.\n',...
sprintf('TPWS maximum RL = %d \ndetEdit minimum RL = %d',max(clickLevels),p.threshRL)])
end
% prune by RL only if spectra & waveforms have been loaded
if specploton && loadMSP
disp([' Removed too low:',num2str(length(ia1)-length(ib1))]);
clickTimes = clickTimes(ib1);
clickLevels = clickLevels(ib1);
keepers = ia1(ib1);
csn = csn(ib1,:);
csp = csp(ib1,:);
else
keepers = ia1;
end
%% Make FD file intersect with MTT
load(fnameFD) % false detection times zFD
jFD = []; ia = []; ic = [];
if (~isempty(zFD))
[jFD,ia,ic] = intersect(MTT,zFD);
rFD = length(zFD) - length(jFD);
disp([' Removed ',num2str(rFD),...
' FD detections that do not match detection times']);
if size(jFD,1)<size(jFD,2)
jFD = jFD';
end
zFD = jFD;
save(fnameFD,'zFD');
end
%% Make ID file intersect with MTT
load(fnameID) % identified detection times zID
if (~isempty(zID))
[jID,ia,ic] = intersect(MTT,zID(:,1));
rID = length(zID) - length(jID);
disp([' Removed ',num2str(rID),...
' ID detections that do not match detection times']);
if size(jID,1)<size(jID,2)
jID = jID';
end
zID = zID(ic,:);
save(fnameID,'zID');
end
%% Make MD file intersect with MTT
load(fnameMD) % identified detection times zMD
if (~isempty(zMD))
[jMD,ia,ic] = intersect(MTT,zMD(:,1));
rMD = length(zMD) - length(jMD);
disp([' Removed ',num2str(rMD),...
' MD detections that do not match detection times']);
if size(jMD,1)<size(jMD,2)
jMD = jMD';
end
zMD = zMD(ic,:);
save(fnameMD,'zMD');
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Calculate bout starts and ends
% TODO: this is calculated in mkLTSA, we should save it there instead of
% recalculating here but would create backward compatibility issues
% TODO: Should be a function
bFlag = 0;
% find edges (start and end times) of bouts or sessions
dt = diff(clickTimes)*24*60*60; % calculate time between detections in seconds
gt = gth*60*60; % gap time in sec
I = find(dt>gt); % find start of gaps
sb = [clickTimes(1);clickTimes(I+1)]; % start time of bout
eb = [clickTimes(I);clickTimes(end)]; % end time of bout
dd = clickTimes(end)-clickTimes(1); % deployment duration [d]
nb = length(sb); % number of bouts
bd = (eb - sb); % duration of bout in days
% find bouts longer than the minimum
if ~isempty(p.minBout)
bdI = find(bd > (p.minBout / (60*60*24)));
bd = bd(bdI);
sb = sb(bdI);
eb = eb(bdI);
nb = length(sb); % number of bouts
end
% limit the length of a bout
blim = p.ltsaMax/24; % 6 hr bout length limit in days
ib = 1;
while ib <= nb
bd = (eb - sb); %duration bout in days
if (bd(ib) > blim) % find long bouts
nadd = ceil(bd(ib)/blim) - 1; % number of bouts to add
for imove = nb : -1: (ib +1)
sb(imove+nadd)= sb(imove);
end
for iadd = 1 : 1: nadd
sb(ib+iadd) = sb(ib) + blim*iadd;
end
for imove = nb : -1 : ib
eb(imove+nadd) = eb(imove);
end
for iadd = 0 : 1 : (nadd - 1)
eb(ib+iadd) = sb(ib) + blim*(iadd+1);
end
nb = nb + nadd;
ib = ib + nadd;
end
ib = ib + 1;
end
disp(['Number Bouts : ',num2str(nb)])
%% Make LTSA session file
lsfn = strrep(matchingFile,'TPWS','LTSA');
fnameLTSA = fullfile(sdir,lsfn);
Altsa = exist(fnameLTSA,'file');
if Altsa ~= 2
disp(['Error: LTSA Sessions File Does Not Exist: ',fnameLTSA])
return
else
disp('Loading LTSA Sessions, please wait ...')
load(fnameLTSA) % LTSA sessions: pwr and pt structures
disp('Done Loading LTSA Sessions')
sltsa = size(pt);
if (sltsa(2) ~= nb)
disp(['Error: Number of LTSA sessions calculated here doesn''t match ',...
'input LTSA file. Check ltsaMax parameter.'])
return
end
end
%% Set up Tests for False Detections
% The false positive estimate tool picks every Nth click to test. If you
% have false positives in zFD, you can pick out only the true ones to
% determine which click indices to look at (that happens just below),
% but if the user then adds or removes anything from zFD, the indices won't
% adjust. Provide a warning to tell the user there might be an issue.
if ~isempty(zFD)
disp(strcat('WARNING: This dataset contains false-flagged detections. ', ...
' It is recommended that you remove them using modDet prior to ',...
'estimating false positive rate.'))
end
[~,trueClickIDx] = setdiff(clickTimes, zFD);
ixfd = (1: c4fd : length(trueClickIDx)); % selected to test for False Det
testClickIdx = trueClickIDx(ixfd);
A6 = exist(fnameTD,'file');
if (A6 ~= 2)
zTD = -1.*ones(nb,4);
save(fnameTD,'zTD'); % create new TD
disp(' Make new TD file');
else
load(fnameTD)
if (length(zTD(:,1)) ~= nb)
disp([' Problem with TD file:',fnameTD]);
return
end
end
%% Compute Spectra Plot Parameters
% max and min for LTSA frequency
fiminLTSA = 0;% TODO: make this configurable
fimaxLTSA = srate/2 ; % in kHz 100 or 160 kHz
% set ltsa step size
iPwr = 1;
while isempty(pwr{1,iPwr}) && iPwr<length(pwr)
iPwr = iPwr+1;
end
% ToDo: Seems like LTSA parameters (step size and frequency bins) could
% be calculated from LTSA directly, especially because there are
% inconsistent step sizes in some LTSAs.
if any(strcmp('dfManual',fieldnames(p)))&& ~isempty(p.dfManual)
% allow non-standard ltsa step sizes
df = p.dfManual;
else
df = 1000*fimaxLTSA/(size(pwr{1,iPwr},1)-1);
end
% for LTSA PLOT
f = 1000*fiminLTSA:df:1000*fimaxLTSA;
if p.tfSelect > 0 % tfParams isn't being used...
tfLTSA = interp1(tffreq,tfuppc,f,'linear','extrap')'; % add to LTSA vector
else
tfLTSA = zeros(size(f))';
end
if specploton
% check length of MSP
inFileMat = matfile(fnTPWS);
if ~loadMSP
MSP = inFileMat.MSP(1,:);
end
smsp2 = size(MSP,2);% 2nd element is num fft points
ift = 1:smsp2;
% make frequency vector that matches spectral bins
if any(strcmp('f',fieldnames(inFileMat)))
fmsp = inFileMat.f;
else
fmsp = [];
end
if isempty(fmsp)
fmsp = ((srate/2)/(smsp2-1))*ift - (srate/2)/(smsp2-1);
fprintf('No freq vector in TPWS file. Using approximation based on sample rate.\n')
end
% find the indices that are in the range of interest
fi = find(fmsp > p.fLow &...
fmsp <= p.fHi);
fimint = fi(1); fimaxt = fi(end);
ft = fmsp(fi);
% for the PP vs RMS plot
if (p.tfSelect > 0)
Ptfpp = interp1(tffreq,tfuppc,fmsp*1000,'linear','extrap');
else
Ptfpp = zeros(1,smsp2);
end
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
kstart = input('Starting Session: ');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
pause on
disp('Press ''b'' key to go backward ')
disp('Press any other key to go forward')
cc = ' '; % avoids crash when first bout too short
k = kstart;
yell = [];
blag = 0;
if (size(zTD,2) == 2) % this seems to patch on extra columns
% to old zTD matrices that maybe only had the first two. Probably
% only needed for backward compatibility
zTD = [zTD,-1.*ones(length(zTD),2)];
save(fnameTD,'zTD');
end
%% Main Loop
% loop over the number of bouts (sessions)
%onerun = 1; % What does this do?
while (k <= nb)
disp([' BEGIN SESSION: ',num2str(k)]);
% load in FD, MD and TD each session in case these have been modified
load(fnameFD); % brings in zFD
load(fnameID); % brings in zID
load(fnameMD); % brings in zMD
load(fnameTD); % brings in zTD
% If all time series are loaded:
% Make PP versus RMS plot for all clicks, if all time series are loaded
figure(51); clf; set(51,'name',sprintf('RL pp vs. RL rms (left shift by %d)',p.threshRL))
h51 = gca;
% Make RMS versus frequency plot for all clicks
figure(53); clf; set(53,'name',sprintf('RL rms vs. Peak freq. (left shift by %d)',p.threshRL))
h53 = gca;
if p.threshHiFreq ~=0 %any(strcmp('threshHiFreq',fieldnames(p)))
ymax = p.threshHiFreq + 1;
else
ymax = fmsp(end); % yaxis max of plot 53 (Default)
end
if specploton && loadMSP
xmsp0All = csp + repmat(Ptfpp,size(csp,1),1);
[xmspAll,im] = max(xmsp0All(:,fimint:fimaxt),[],2); % maximum between flow-100kHz
% calculate peak-to-peak amplitude including transfer function
if isrow(clickLevels)
xmppAll = clickLevels-tf+ Ptfpp(im + fimint-1); % vectorized version
else
xmppAll = clickLevels'-tf+ Ptfpp(im + fimint-1); % vectorized version
end
% turn diagonal to vertical (easier way to find thresholds)
if isrow(xmspAll)
pxmspAll = xmspAll' - p.slope*(xmppAll - p.threshRL); %use slope of 1 to mod xmsp for plot
elseif isrow(xmppAll)
pxmspAll = xmspAll - p.slope*(xmppAll' - p.threshRL); %use slope of 1 to mod xmsp for plot
else
pxmspAll = xmspAll - p.slope*(xmppAll - p.threshRL); %use slope of 1 to mod xmsp for plot
end
plot(h51,pxmspAll,xmppAll,'o','MarkerEdgeColor',[.7,.7,.7],'UserData',clickTimes)
title(h51,['Based on ',num2str(length(xmppAll)),' clicks']);
% apply RMS threshold to figure (51)
% if (p.threshRMS > 0)
% if onerun == 1
% if p.threshPP > 0
% badClickTime = clickTimes(pxmspAll < p.threshRMS &...
% xmppAll' < p.threshPP); % for all false if below RMS threshold
% else
% badClickTime = clickTimes(pxmspAll < p.threshRMS);
% end
% disp(['Number of Detections Below RMS threshold = ',num2str(length(badClickTime))])
% zFD = [zFD; badClickTime]; % cummulative False Detection matrix
% save(fnameFD,'zFD')
% end
% if p.threshPP > 0
% xtline = [p.threshRMS,p.threshRMS]; ytline = [ min(xmppAll),p.threshPP];
% else
% xtline = [p.threshRMS,p.threshRMS]; ytline = [ min(xmppAll),max(xmppAll)];
% end
% hold(h51,'on');
% plot(h51,xtline,ytline,'r')
% hold(h51,'off');
% %p.threshRMS = 0;
% end
% plot RMS vs frequency plot, keeping RMS vertical like in fig(51)
freqAll = fmsp(im + fimint-1);
plot(h53,pxmspAll,freqAll,'o','MarkerEdgeColor',[.7,.7,.7],'UserData',clickTimes)
title(h53,['Based on total of ',num2str(length(freqAll)),' clicks']);
% apply High Frequency threshold to figure (53)
% if onerun == 1
% if (p.threshHiFreq > 0)
% badClickTime = clickTimes(freqAll > p.threshHiFreq); % for all false if below RMS threshold
% disp(['Number of Detections Below Freq threshold = ',num2str(length(badClickTime))])
% zFD = [zFD; badClickTime]; % cummulative False Detection matrix
% save(fnameFD,'zFD')
% %p.threshHiFreq = 0;
% end
% end
% if (p.threshHiFreq > 0)
% xtline = [min(pxmspAll),max(pxmspAll)]; ytline = [p.threshHiFreq ,p.threshHiFreq];
% hold(h53,'on');
% plot(h53,xtline,ytline,'r')
% hold(h53,'off');
% end
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% find detections and false detections within this bout (session)
J = []; JFD =[]; Jtrue = []; XFD = []; JID = [];
J = find(clickTimes >= sb(k) & clickTimes <= eb(k));
if specploton && loadMSP
% have to load consecutive detections if reading from disk
J = J(1):J(end);
csnJ = csn(J,:);
cspJ = csp(J,:);
elseif specploton % only load the ones you need for this session
csnJ = inFileMat.MSN(keepers(J),:);
cspJ = inFileMat.MSP(keepers(J),:);
end
% get indices of test clicks in this session
XFD = [];
% XFD = find(clickTimes(testClickIdx) >= sb(k) &...
% clickTimes(testClickIdx) <= eb(k));
% zTD(k,1) = length(XFD);
%
% Test for XFD and strcmp('x or z or w') - if no test points skip
% x = true, z = false, w = window
% if (isempty(XFD) && (strcmp(cc,'x') || ...
% strcmp(cc,'z') || strcmp(cc,'w')));
% disp(' NO Test Detections, so skip')
% k = k + 1;
% continue
% end
if ~isempty(J) % if there are detection in this session
t = clickTimes(J); % detection times in this session
disp([' Detection times:',num2str(length(t))]);
if (~isempty(XFD))
xt = clickTimes(testClickIdx(XFD)); %times to test for False Detection
xPP = clickLevels(testClickIdx(XFD)); %amplitude for test False Detection
disp([' Test False Detection times:',num2str(zTD(k,1))]),
else
xt = [];
end
RL = clickLevels(J); % received levels in this session
nd = length(J); % number of detections in this session
% get false detection times that intersect with detection times
K2 = []; % holds false indices
ff2 = 0;
tfd = [];
if (~isempty(zFD)) % get times and indices of false detections
[tfd,K2,~] = intersect(t,zFD(:,1));
rlFD = RL(K2);
end
if ~isempty(K2) % if this session contains false detections
ff2 = 1; % set false flag to true
if specploton
wavFD = norm_wav(mean(csnJ(K2,:),1)); % calculate mean false time series
specFD = cspJ(K2,:); % get set of false spectra
end
disp([' False detections:',num2str(length(K2))])
else
ff2 = 0;
disp(' No False Detections')
end
% get ID'd detection times that intersect with detection times
K3 = []; % holds Id'd indices
ff3 = 0; % becomes positive if you have ID's detections in this session
tID = []; % times of ID'd detections
IDidx = [];
if ~isempty(zID)
[tID,K3,IDidx] = intersect(t,zID(:,1));
rlID = RL(K3);
end
if ~isempty(K3)
ff3 = 1;
spCodeSet = zID(IDidx,2); % get ID codes for everything in this session
specIDs = unique(spCodeSet); % get unique ID codes
if specploton % get mean spectra for each ID'd type
wavID = [];
specID = [];
for iSpID = 1:length(specIDs)
thisSet = spCodeSet == specIDs(iSpID);
wavID(iSpID,:) = norm_wav(mean(csnJ(K3(thisSet,:),:),1));
specID(iSpID,:) = mean(cspJ(K3(thisSet,:),:),1);
end
end
disp([' ID detections:',num2str(length(K3))])
else
ff3 = 0;
disp(' No identified detections (ID)')
end
% get MisID detection times that intersect with detection times
K4 = []; % holds MD'd indices
ff4 = 0; % becomes positive if you have MD's detections in this session
tMD = []; % times of MD'd detections
MDidx = [];
if ~isempty(zMD)
[tMD,K4,MDidx] = intersect(t,zMD(:,1));
rlMD = RL(K4);
end
if ~isempty(K4) % if this session contains mis-ID detections
ff4 = 1; % set false flag to true
if specploton
wavMD = norm_wav(mean(csnJ(K4,:),1)); % calculate mean MD series
specMD = cspJ(K4,:); % get set of MD spectra
end
disp([' MD detections:',num2str(length(K4))])
else
ff4 = 0;
disp(' No misidentified Detections (MD)')
end
% Calculate indices of detections which are neither false, ID'd,
% or MD
JFD = J(K2);
JID = J(K3);
JMD = J(K4);
JFIM = union(union(JFD,JID),JMD);
JFM = union(JFD,JMD);
[Jtrue,iJ,~]= setxor(J,JFIM); % find all true detections
%[JtrueWithID,~,~]= setxor(J,JFM); % find all true detections no ID
trueTimes = clickTimes(Jtrue);% vector of true times in this session
if specploton
cspJtrue = cspJ(iJ,:); % true spectra in this session
csnJtrue = csnJ(iJ,:); % true time series in this session
wtrue = norm_wav(nanmean(csnJtrue,1)); % mean of true spectra in this session
strue = nanmean(cspJtrue,1); % mean of true time series in this session
end
disp([' True Detections: ',num2str(length(trueTimes))])
else
disp('Error: no detections between bout start and end')
return
end
dt = diff(t)*24*60*60; % inter-detection interval (IDI) and convert from days to seconds
if ff2 % calculate IDI for false and id'd detections
dtFD = dt(K2(1:end-1));
end
if ff3
dtID = dt(K3(1:end-1));
end
if ff4
dtMD = dt(K4(1:end-1));
end
disp(['END SESSION: ',num2str(k),' Start: ',datestr(sb(k)),...
' End:',datestr(eb(k))])
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% calculate number of detections per bin
[KB,binCX,binT,binC] = ndets_per_bin(t,xt,RL,dt,minNdet,nd);
% filter empty and low number bins
if isempty(KB) % not sure what this case does?
disp(['No bins with at least ',num2str(minNdet),' detections'])
binT = 0;
binRL = 0;
binC = 0;
k = k + 1; % go to next
continue
end
if (strcmp(cc,'w') && (zTD(k,2) == 0))
disp(['Session: ',num2str(k),' # Test Detect Bins: ',...
num2str(length(binCX)),' but NO False']);
zTD(k,3) = length(binCX);
zTD(k,4) = 0;
save(fnameTD,'zTD');
k = k + 1;
continue
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Number detection per spectral bin in LTSA
% make a spectra in figure 50
PT = pt{1,k}; % LTSA session time vector
pwr1 = pwr{1,k}; % LTSA power vector
nbinS = length(PT);
if (nbinS == 0)
disp('No LTSA for this Session');
PT(1) = sb(k) ; PT(2) = eb(k); % start end times for plots
pwr1(1:length(f)) = ones; % make uniform LTSA
else
pwr1 = pwr1((1000*fiminLTSA/df)+1:round(1000*fimaxLTSA/df)+1,:);
end
durS = PT(end) - PT(1);
if specploton
% allSPEC = norm_spec(cspJ,fimint,fimint,fimaxt);
figure(50);clf;set(50,'name','Frequency Spectra')
h50 = gca;
figure(52);clf;set(52,'name','Waveform')
h52 = gca;
trueSpec = [];
if ~isempty(trueTimes)
% plot average true click spectrum
trueSpec = norm_spec_simple(cspJtrue,fimint,fimaxt);
plot(h50,ft,trueSpec,'Linewidth',4)
% average true click waveform
plot(h52, wtrue);
else
disp(['No true with at least ',num2str(minNdet),' detections'])
end
if ff2 % average false click spec
SPEC2 = norm_spec_simple(specFD,fimint,fimaxt);
% plot average false click spectrum
hold(h50, 'on')
plot(h50,ft,SPEC2,'r','Linewidth',4)
hold(h50, 'off')
% plot average false click waveform
hold(h52, 'on')
plot(h52,wavFD + 0.5 ,'r');
hold(h52, 'off')
end
if ff3 % average id click spec
specID_norm = [];
for iSpec = 1:size(specID,1)
specID_norm(iSpec,:) = norm_spec_simple(specID(iSpec,:),fimint,fimaxt);
end
% plot average ID'd click spectra
hold(h50, 'on')
hID = plot(h50,ft,specID_norm,'Linewidth',4);
hold(h50, 'off')
% plot average ID'd click waveform(s)
hold(h52, 'on')
hID2 = plot(h52,(wavID + repmat(-1*rand(size(hID)),1,length(wavID)))');
for iC = 1:length(hID) % set colors
set(hID(iC),'Color',colorTab(specIDs(iC),:))
set(hID2(iC),'Color',colorTab(specIDs(iC),:))
end
hold(h52, 'off')
end
if ff4 % average false click spec
SPEC4 = norm_spec_simple(specMD,fimint,fimaxt);
% plot average false click spectrum
hold(h50, 'on')
plot(h50,ft,SPEC4,'g','Linewidth',4)
hold(h50, 'off')
% plot average false click waveform
hold(h52, 'on')
plot(h52,wavMD + 1,'g');
hold(h52, 'off')
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Add detections of this session in figure 51 and 53
% for all detections in this session, calculate xmpp and xmsp
xmsp0 = cspJ + repmat(Ptfpp,size(cspJ,1),1); % add transfer fun to session's spectra
[xmsp,im] = max(xmsp0(:,fimint:fimaxt),[],2);
if isrow(RL)
xmpp = RL - tf + Ptfpp([im + fimint - 1]);
else
xmpp = RL' - tf + Ptfpp([im + fimint - 1]);
end
% turn diagonal to vertical
if ~isempty(xmsp) && ~isempty(xmpp)
if isrow(xmsp)
pxmsp = xmsp' - p.slope*(xmpp - p.threshRL); %use slope of 1 to mod xmsp for plot
elseif isrow(xmpp)
pxmsp = xmsp - p.slope*(xmpp' - p.threshRL);
else
pxmsp = xmsp - p.slope*(xmpp - p.threshRL);
end
end
% Plot PP versus RMS Plot for this session
hold(h51, 'on')
plot(h51,pxmsp,xmpp,'.','UserData',t)% true ones in blue
if ~loadMSP % plot threshold line now because no background data
% if (p.threshRMS > 0)
% if onerun == 1
% if p.threshPP > 0
% badClickTime = t(pxmsp < p.threshRMS &...
% xmpp' < p.threshPP); % for all false if below RMS threshold
% else
% badClickTime = t(pxmsp < p.threshRMS);
% end
% disp(['Number of Detections Below RMS threshold = ',num2str(length(badClickTime))])
% zFD = [zFD; badClickTime]; % cummulative False Detection matrix
% save(fnameFD,'zFD')
if ~isempty(zFD) % get times and indices of false detections
[tfd,K2,~] = intersect(t,zFD(:,1));
rlFD = RL(K2);
end
if ~isempty(K2) % if this session contains false detections
ff2 = 1; % set false flag to true
if specploton
wavFD = norm_wav(mean(csnJ(K2,:),1)); % calculate mean false time series
specFD = cspJ(K2,:); % get set of false spectra
end
dtFD = dt(K2(1:end-1));
disp([' False detections:',num2str(length(K2))])
else
ff2 = 0;
disp(' No False Detections')
end
% end
% end
% if p.threshPP > 0 && exist('plotaxes','var')
% xtline = [p.threshRMS,p.threshRMS]; ytline = [ plotaxes.minPP,p.threshPP];
% elseif p.threshPP > 0
% xtline = [p.threshRMS,p.threshRMS]; ytline = [ min(xmpp),p.threshPP];
% else
% xtline = [p.threshRMS,p.threshRMS]; ytline = [ min(xmpp),max(xmpp)];
% end
% plot(h51,xtline,ytline,'r')
end
if ff2 % false in red
plot(h51,pxmsp(K2),xmpp(K2),'r.','UserData',t(K2))
end
if ff3 % ID'd in associated color
for iC2 = 1:length(specIDs) % set colors
thisIDset = spCodeSet ==specIDs(iC2);
hPP = plot(h51,pxmsp(K3(thisIDset)),xmpp(K3(thisIDset)),'.','UserData',t(K3(thisIDset)));
set(hPP,'Color',colorTab(specIDs(iC2),:))
end
end
if ff4 % MD in green
plot(h51,pxmsp(K4),xmpp(K4),'g.','UserData',t(K4))
end
hold(h51, 'off')
% Plot RMS vs frequency plot for this session
hold(h53, 'on')
freq = fmsp(im + fimint -1);
plot(h53,pxmsp,freq,'.','UserData',t) % true ones in blue
if ~loadMSP
% if onerun == 1
% if (p.threshHiFreq > 0)
% badClickTime = t(freq > p.threshHiFreq); % for all false if below RMS threshold
% disp(['Number of Detections Below Freq threshold = ',num2str(length(badClickTime))])
% zFD = [zFD; badClickTime]; % cummulative False Detection matrix
% save(fnameFD,'zFD')
if ~isempty(zFD) % get times and indices of false detections
[tfd,K2,~] = intersect(t,zFD(:,1));
rlFD = RL(K2);
end
if ~isempty(K2) % if this session contains false detections
ff2 = 1; % set false flag to true
if specploton
wavFD = norm_wav(mean(csnJ(K2,:),1)); % calculate mean false time series
specFD = cspJ(K2,:); % get set of false spectra
end
disp([' False detections:',num2str(length(K2))])
dtFD = dt(K2(1:end-1));
else
ff2 = 0;
disp(' No False Detections')
end
% end
% end
% if p.threshHiFreq > 0 && exist('plotaxes','var')
% xtline = [plotaxes.minRMS,plotaxes.maxRMS]; ytline = [p.threshHiFreq ,p.threshHiFreq];
% elseif p.threshHiFreq > 0
% xtline = [min(pxmsp),max(pxmsp)]; ytline = [p.threshHiFreq ,p.threshHiFreq];
% end
% plot(h53,xtline,ytline,'r')
end
if ff2 % false in red
plot(h53,pxmsp(K2),freq(K2),'r.','UserData',t(K2))
end
if ff3 % ID'd in associated color
for iC2 = 1:length(specIDs) % set colors
thisIDset = spCodeSet ==specIDs(iC2);
hPP = plot(h53,pxmsp(K3(thisIDset)),freq(K3(thisIDset)),'.','UserData',t(K3(thisIDset)));
set(hPP,'Color',colorTab(specIDs(iC2),:))
end
end
if ff4 % MD in green
plot(h53,pxmsp(K4),freq(K4),'g.','UserData',t(K4))
end
hold(h53, 'off')
if p.threshHiFreq > 0
ylim(h53,[p.fLow ymax+10])
else
ylim(h53,[p.fLow ymax])
end
end
% add figure labels
xlabel(h50,'Frequency (kHz)');
grid(h50,'on')
xlim(h50, 'manual');
ylim(h50,[0 1]);
xlim(h50,[p.fLow,p.fHi])
xlabel(h51,'dB RMS')
ylabel(h51,'dB Peak-to-peak')
if exist('plotaxes','var')
xlim(h51,[plotaxes.minRMS,plotaxes.maxRMS])
ylim(h51,[plotaxes.minPP,plotaxes.maxPP])
end
xlabel(h52,'Time (1ms @ 200kHz)');
ylabel(h52,' Normalized Amplitude');
xlabel(h53,'dB RMS')
ylabel(h53,'Peak Frequency (kHz)')
if exist('plotaxes','var')
xlim(h53,[plotaxes.minRMS,plotaxes.maxRMS])
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% plots stuff now in figure(201)
warning('off')
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
figure(201);clf
set(201,'name','LTSA and time series')
hA201 = subplot_layout; % Top panel, Figure 201: Received Level
plot(hA201(1),t,RL,'b.','UserData',t)
hold(hA201(1),'on')
if ff2 % plot False detections in red
plot(hA201(1),tfd,rlFD,'r.','UserData',tfd)
% disp([' false det plotted:',num2str(length(tfd))])
end
if ff3 % plot ID'd detections in associated color
spCodeSet = zID(IDidx,2); % get species codes for everything in this session
specIDs = unique(spCodeSet); % get unigue species codes
for iC2 = 1:length(specIDs) % set colors
thisIDset = spCodeSet ==specIDs(iC2);
hRLID = plot(hA201(1),tID(thisIDset),rlID(thisIDset),'.','UserData',tID(thisIDset));
set(hRLID,'Color',colorTab(specIDs(iC2),:))
end
end
if ff4 % plot MD detections in green
plot(hA201(1),tMD,rlMD,'g.','UserData',tfd)
end
hold(hA201(1),'off')
axis(hA201(1),[PT(1) PT(end) p.rlLow p.rlHi])
datetick(hA201(1),'x',15,'keeplimits')
grid(hA201(1),'on')
tstr(1) = {fnTPWS};
tstr(2) = {['Session: ',num2str(k),'/',num2str(nb),' Start Time ',...
datestr(sb(k)),' Detect = ',num2str(nd)]};
title(hA201(1),tstr);
ylabel(hA201(1),'RL [dB re 1\muPa]')
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% middle panel LTSA
c = (p.ltsaContrast/100) .* pwr1 + p.ltsaBright;
image(PT,f/1000,c,'parent',hA201(2))
set(hA201(2),'yDir','normal')
axis(hA201(2),[PT(1) PT(end) p.ltsaLims])%v2(4)
ylabel(hA201(2),'Frequency (kHz)')
datetick(hA201(2),'keeplimits')
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Bottom panel, Figure 201: Inter-Detection Interval
% make two copies of dt points for brush
tdt2 = [];
dt2 = [];
ldt = length(dt);
if ldt > 0
tdt2 = reshape([t(1:ldt),t((1:ldt)+1)]',2*ldt,1);
dt2 = reshape([dt,dt]',2*ldt,1);
[AX,H1,H2] = plotyy(hA201(3),tdt2,dt2,binT,binC,'plot','semilogy');
set(H1,'Marker','.','MarkerFaceColor','b','LineStyle','none','UserData',tdt2)
set(H2,'Marker','o','MarkerFaceColor','c','LineStyle','none',...
'Markersize',4.5,'UserData',dt2)
% Note: plotyy is buggy in 2012b, axis handles work only if called
% using "axes" and avoid calls to "subplot"
% Do setup for 1st axes
axis(AX(1),[PT(1) PT(end) 0 p.dtHi])
datetick(AX(1),'x',15,'keeplimits')
Ytick = 0:p.dtHi/10:p.dtHi; % make 0.05 Kogia, 0.2 BW
set(AX(1),'YTick',Ytick)
datetick(AX(1),'x',15,'keeplimits')
grid(AX(1),'on')
ylabel(AX(1),'Time between detections [s]')
% Do setup for 2nd axes
axis(AX(2),[PT(1), PT(end), 1, 100])
datetick(AX(2),'x',15,'keeplimits')
Ytick2 = [.1 1 10 100 1000 10000];
set(AX(2),'YTick',Ytick2)
ylabel(AX(2),'Det/bin')
xlabel(AX(2),'Time [GMT]')
title(AX(2),'Inter-Detection Interval (IDI)')
%grid(AX(2),'on')
%%% plot FD, ID, MD
hold(AX(1),'on')
if ff2
plot(AX(1),tfd(2:end),dtFD,'.r','UserData',tfd(2:end))