bachelor_thesis/DataAnalysisToolbox/parse_input_peakfun.m

function [file_nums, varargout] = ...
    parse_input_peakfun(files, varargin)
%% Input parser for self-written data analysis functions
% This function parses the input for functions used for analysing double 
% recordings. It is checked whether the inputs are valid to ensure that
% the functions calling this input parser work properly. If the input is 
% not suitable an appropriate error message is displayed. A file number is 
% always needed, the other arguments are optional.
% -------------------------------------------------------------------------
% Input     [additional arguments are positional, 
% -----      optional arguments are name-value pairs]
% 
%   files:          ID(s) of the '.mat' file(s) in the directory used by
%                       the 'extract_data' function
%   trials:         number(s) of the trials to be analysed, type: integer
%   (additional)        or vector, default: 'all'
%   Filter:         select between three filter options: 
%   (optional)          'hn'    applys a hum-noise-remove filter
%                       'hnhfn' additonally applys a low pass filter to
%                               remove high frequency noise
%                       If not set, it will be set to "no" (default).
%   Tolerance:      tolerance value for data selection in ms. Default 50 ms
%   (optional)      
%   MinPeakPromT:   value for 'MinPeakProminence' which is used in the
%   (optional)          'findpeaks' function to find T cell peaks. 
%                       Type: float. Default: 15
%   StimCell:       set whether the data for the stimulated T cell or
%   (optional)          the stimulated interneuron should be used.
%                       'INT' for interneuron stimulated
%                       'T'   for T-cell stimulated (default)
%   ErrorBars:      set whether error bars (standard deviation) should be
%   (optional)          plotted (1) or not (0). Default: 1
%   Stimuli:        select which stimuli should be used in a function
%   (optional)          selection between the given stimuli by their
%                       current. Type: float or vector or 'all'. 
%                       Default: 'all'
%   PlotFlag:       set whether specific functions should create plots (1)
%   (optional)          not (0). Default: 0.
% ------
% Output
% ------
%   parsed version of the input, in detail:
%       1. file_num
%       2. (additional) trials
%       3. (optional)   filter_choice
%       4. (optional)   tol: tolerance
%       5. (optional)   MinPeakPromT
%       6. (optional)   StimCell
%       7. (optional)   ErrorBars
%       8. (optional)   Stimuli
%       9. (optional)   PlotFlag
% -------------------------------------------------------------------------
% Program by Bjarne Schultze [last modified 02.03.2022]
% -------------------------------------------------------------------------

% set default and possible values for input parameters
default_filter = "no";                  % no filter
possible_filters = ["no","hn","hnhfn"]; % three possible filter options
default_tol = 0.05;                     % 50 ms tolerance
default_MinPeakPromT = 17;              % for a T-cell
default_StimCell = "T";                 % data with stimulated T-cell
possible_stimCells = ["T", "INT"];      % two possible stim cell options 
default_errorbars = 1;                  % error bars will be plotted
possible_stimuli = [-2,-1,-0.5,0.03125,0.0625,0.125,0.25,0.5,0.75,1,...
    1.25,1.5];                          % possible stimuli to select from

% handle to anonymous function for validating input: vector input
valid_in_vector = @(x) isnumeric(x) && isvector(x) && ...
    isequal(length(x),sum(x>0));
% handle to anonymous function for validating input: scalar input
valid_in_scalar = @(x) (x>0) && isscalar(x) && isnumeric(x);

% specify the input arguments
p = inputParser;
addRequired(p, 'files', valid_in_vector);
addOptional(p, 'trials', 'all', valid_in_vector);
addParameter(p, 'Filter', default_filter, ...
    @(x) ~isempty(validatestring(x, possible_filters)));
addParameter(p, 'Tolerance', default_tol, ...
    @(x) (x>=0) && isscalar(x) && isnumeric(x));
addParameter(p, 'MinPeakPromT', default_MinPeakPromT, valid_in_scalar);
addParameter(p, 'StimCell', default_StimCell, ...
    @(x) ~isempty(validatestring(x, possible_stimCells)));
addParameter(p, 'ErrorBars', default_errorbars, @(x) (x==0) || (x==1));
addParameter(p, 'Stimuli', 'all', ...
    @(x) length(intersect(x,possible_stimuli)) == length(x));
addParameter(p, 'PlotFlag', 0, @(x) isequal(x,1) || isequal(x,0));

% parse the input
parse(p, files, varargin{:});

% assign the parsing results to the output variables 
file_nums = p.Results.files;
varargout{1} = p.Results.trials;
varargout{2} = p.Results.Filter;
varargout{3} = p.Results.Tolerance;
varargout{4} = p.Results.MinPeakPromT;
varargout{5} = p.Results.StimCell;
varargout{6} = p.Results.ErrorBars;
varargout{7} = p.Results.Stimuli;
varargout{8} = p.Results.PlotFlag;

% end of function definition
end