function ex = temporal_sens_params(ex, wntime, sens_time, sens_reps, ...
	adapt_time, probe_time, ntrials, nrounds)
%
% FUNCTION ex = temporal_sens_params(ex, wntime, sens_time, ...
%	adapt_time, probe_time, ntrials, nrounds)
%
% Sets up the stimulus parameters for the pure temporal frequency sensitization
% experiment.
%
% INPUT:
%	ex			- Experimental structure
%	wntime		- Length of white noise stimulus block (seconds)
%	sens_time	- Length of high/low blocks for sensitization stimulus (seconds)
%	sens_reps	- Number of high/low blocks
%	adapt_time	- Length of adapt blocks (seconds)
%	probe_time	- Length of probe blocks (seconds)
%	ntrials		- Number of adapt/probe trials per block
%	nrounds		- Number of repetitions of each round
%
% OUTPUT:
%	ex			- Experimental structure
%
% (c) bnaecker@stanford.edu 2014 
% 28 May 2014 - wrote it
% 11 Jun 2014 - adding trials, blocks and sensitization stimulus

%% Initialize the structure
stim = struct();

%% Basic info
stim.name             = 'temporal-sens';					% Experiment name
stim.date             = datestr(now, 31);					% Date, ISO 8601 format
ex.disp.aperture_size = 512;								% Size of stimulus aperture
ex.disp.dstrect       = CenterRectOnPoint(...  				% Stimulus destination rectangle 
	[0 0 ex.disp.aperture_size ex.disp.aperture_size], ...  
	ex.disp.winctr(1), ex.disp.winctr(2));
ex.disp.waitframes    = 2;									% Number of frames between monitor flips
ex.disp.pdscale       = 0.6;								% Scale factor for photodiode signal
flip_time = ex.disp.nominalifi * ex.disp.waitframes;		% Nominal time between flips

%% White noise information
% NOTE: White noise stimuli themselves are generated on the fly.
% After the experiment, the full white noise movies are saved, if they 
% don't already exist, using `stimdb('add', ...)`. They can be loaded
% again with `stimdb('load', ... )`.
stim.wntime     = wntime;									% Time the white noise stimulus (seconds)
stim.nwnboxes   = 32;										% Number of boxes
stim.wncontrast = 0.25;										% Contrast of gaussian white noise
stim.nwnframes  = round(stim.wntime / flip_time);			% Number of frames in the stimulus

%% Basic sensitization stimulus
stim.sens_time 		= sens_time;							% Time of high/low contrast blocks
stim.sens_reps 		= sens_reps;							% Number of repetitions
stim.sens_contrast 	= [0.35 0.10];							% High/low contrast blocks
stim.nsens_frames_per_contrast = ...						% Frames in each contrast
	round(stim.sens_time ./ flip_time);
stim.nsens_frames_per_trial = ...							% Frames in each trial
	sum(stim.nsens_frames_per_contrast);
stim.nsens_frames = sum(stim.nsens_frames_per_trial * ...	% Total frames
	stim.sens_reps);

%% Temporal sensitization stimulus parameters
stim.adapt_time       = adapt_time;							% Length of an adapt block (seconds)
stim.probe_time       = probe_time;							% Length of a probe block (seconds)
stim.ntrials		  = ntrials;							% Number of adapt/probe trials per block
stim.nrounds          = nrounds;							% Number of rounds
stim.cutoff			  = 2;									% Cutoff frequency for low/high pass filters (see ../notes/kernels)
stim.nbands			  = 2;									% Only using low/high pass bands
stim.adapt_contrast   = [0.20 0.40];						% Contrasts for adapting stimulus
stim.probe_contrast   = [0.10];								% Contrasts for probe stimulus
stim.nadapt_contrasts = length(stim.adapt_contrast);		% Number of adapt contrasts
stim.nprobe_contrasts = length(stim.probe_contrast);		% Number of probe contrasts

%% Characteristics of filters used to construct the adapt stimuli
stim.filter_order = 4;		% Order of the Butterworth filter used to filter noise into bands
stim.low_cutoff   = 0.1;	% Cutoff frequency, frequencies below this are zeroed to prevent mean adaptation

%% Compute condition matrix
stim.condition_desc = ...				% Strings describing ordering of condition matrix 
	{'band', 'adapt_contrast', 'probe_contrast'};
stim.condition_list = cartprod(...		% Condition matrix 
	1:stim.nbands, stim.adapt_contrast, stim.probe_contrast);
stim.nconditions    = ...				% Number of conditions
	size(stim.condition_list, 1);

%% Describe the rounds, which are constructed to have all possible
% transitions between blocks of each unique condition (i.e., all 
% transitions A->B where A~=B).
stim.single_round = vec(nchoosek(1:stim.nconditions, 2)');
stim.round_list = repmat(stim.single_round, stim.nrounds, 1);
stim.nblocks_per_round = length(stim.single_round);

%% Compute number of frames
stim.nframes_per_adapt = round(stim.adapt_time / ...		% Frames in each adapt trial
	flip_time);
stim.nframes_per_probe = round(stim.probe_time / ...		% Frames in each probe trial
	flip_time);
stim.nframes_per_trial = stim.nframes_per_adapt + ...		% Frames in each adapt/probe trial
	stim.nframes_per_probe;
stim.nframes_per_block = stim.nframes_per_trial * ...		% Frames in each condition block
	stim.ntrials;
stim.nframes_per_round = stim.nframes_per_block * ...		% Frames in each round
	stim.nblocks_per_round;

%% Compute ostensible total experiment time. Actual time will diverge slightly,
% due to deviations in the true inter-frame interval.
stim.exp_length = stim.wntime + ...
	(sum(stim.sens_time) * stim.sens_reps) + ...
	((stim.adapt_time + stim.probe_time) * stim.ntrials) * ...
	stim.nblocks_per_round * stim.nrounds;

%% Create a PRNG for the basic sensitization stimulus
stim.sens_rn      = getrng();
stim.sens_rnseed  = get(stim.sens_rn, 'Seed');
stim.sens_rnstate = get(stim.sens_rn, 'State');

%% Create a PRNG for the temporal sensitization stimulus
stim.rn      = getrng();
stim.rnseed  = get(stim.rn, 'Seed');
stim.rnstate = get(stim.rn, 'State');

%% Create the basic sensitization stimulus, with contrasts
stim.sens_stim = ...
	[randn(stim.sens_rn, stim.nsens_frames_per_contrast(1), stim.sens_reps) ...
		* stim.sens_contrast(1); ...
	randn(stim.sens_rn, stim.nsens_frames_per_contrast(2), stim.sens_reps) * ...
		stim.sens_contrast(2)];

%% Create the white noise probe stimuli, without resetting the PRNG state
% so that the probe and filtered adapter are uncorrelated.
stim.probe = randn(stim.rn, stim.nrounds, stim.nblocks_per_round, ...
	stim.ntrials, stim.nframes_per_probe);

%% Initialize the VBL timestamp arrays
ex.disp.wnvbl      = zeros(stim.nwnframes, 1);				% VBL for white noise block
ex.disp.sens_vbl   = zeros(stim.nsens_frames_per_trial, ... % VBL for basic sens trials
	stim.sens_reps);			
ex.disp.adapt_vbl  = zeros(stim.nrounds, ...				% VBL for adapting blocks
	stim.nblocks_per_round, stim.ntrials, stim.nframes_per_adapt);
ex.disp.probe_vbl  = zeros(stim.nrounds, ...				% VBL for probe blocks
	stim.nblocks_per_round, stim.ntrials, stim.nframes_per_probe);
ex.disp.flipmissed = [];									% Array to hold index of any missed flips

%% Initialize call to GetSecs MEX-function
GetSecs();

%% Attach stim substructure to experimental structure
ex.stim = stim;

%% Set smaller Screen font size, for printing condition description to the monitor
Screen('TextSize', ex.disp.winptr, 18);