classdef pricklypear < handle
    %PRICKYLPEAR Interface to the MSO neuron model from matlab
    %   PP = pricklypear() creates a new MSO neuron model interface.
    %   PP = pricklypear(expName) specifies the experiment name.
    %   PP = pricklypear(expName, irec) specifies an irec.
    %
    %   See also pricklypear/run

    properties
        seed = 1                % RNG seed
        iter = 99               % Used by model (do not touch!)

        tstop = 2000            % Length of run
        dt = 0.025              % Temporal resolution

        v_init = -65            % Initial membrane potential
        celsius = 38            % Temperature (celsius)

        axon_soma_distance = 45 % Axon soma distance (on ipsi dendrite)
        dend_n = 2              % Number of dendrites
        dend_n_syn = 10         % Number of synapses per dendrite
        dend_n_seg = 20         % Number of segments per dendrite
        dend_length = 200       % Length of dendrites (um)
        dend_syn_spread = 0.5   % Spread of synapses (index)
        dend_syn_offset = 0.45  % Offset of synapses (index)

        dend_0_exc_G = 11       % Excitatory conductance contra dendrite
        dend_1_exc_G = 11       % Excitatory conductance ipsi dendrite

        dend_0_inh_G = 0        % Inhibitory conductance contra dendrite
        dend_1_inh_G = 0        % Inhibitory conductance ipsi dendrite

        dend_0_exc_gain = 0.0008    % Excitatory gain contra dendrite
        dend_1_exc_gain = 0.0008    % Excitatory gain ipsi dendrite

        dend_0_inh_gain = 0.001     % Inhibitory gain contra dendrite
        dend_1_inh_gain = 0.001     % Inhibitory gain ipsi dendrite

        spk_thres_exc_contra    = 0 % Excitatory spike threshold contra
        spk_thres_exc_ipsi      = 0	% Excitatory spike threshold ipsi
        spk_thres_inh_contra    = 1	% Inhibitory spike threshold contra
        spk_thres_inh_ipsi      = 1	% Inhibitory spike threshold ipsi

        eventtimes_contra   = 200+(0:75:1500)	% Input spiketimes contra (ms)
        eventtimes_ipsi     = 200+(0:100:1500)	% Input spiketimes ipsi (ms)
        eventtimes_inh_contra   = []            % Inh input spiketimes contra (ms)
        eventtimes_inh_ipsi     = []            % Inh input spiketimes ipsi (ms)
        model_name          = 'default'         % Model name
        user_data           = []                % Arbitrary user data
        
        % Private
        sim_channels = {'c' 'd0p' 'd0m' 'd0d' 'd1p' 'd1m' 'd1d' 'ap' 'ad'}
        sim_metrics = {'vm'}
        sim_experiment = ''
        sim_irec = []
        template_exclude = {'eventtimes_contra' 'eventtimes_ipsi'...
                            'eventtimes_inh_contra' 'eventtimes_inh_ipsi'...
                            'template_exclude' 'model_name', 'user_data'...
                            'sim_irec' 'sim_experiment' 'sim_channels' 'sim_metrics'}
    end
    
    methods
        % Class constructor
        function obj = pricklypear(varargin)
            % Handle input
            p = inputParser();
            p.addOptional('expname', '', @ischar);
            p.addOptional('irec', []);
            p.parse(varargin{:});
            p = p.Results;
            
            % Check expname
            assert(~strcmp(p.expname, '_direct'), '_direct is a protected experiment name, pick any other.');
            
            % Handle expname
            if ~isempty(p.expname)
                obj.sim_experiment = p.expname;
            end
            
            % Handle irec
            if ~isempty(p.expname) && ~isempty(p.irec)
                obj.sim_irec = p.irec;
                
                % Check if this run exists
                if exist(obj)
                    % Get properties from old runs
                    % Compatibility issues will likely arise here...
                    props = properties(obj);
                    if p.irec == 0
                        storedProps = load(fullfile(obj.datadir(), sprintf('run_unsaved__properties.ppbin')), '-mat');
                    else
                        storedProps = load(fullfile(obj.datadir(), sprintf('run_%05i__properties.ppbin', p.irec)), '-mat');
                    end
                    
                    for ii = 1:numel(props)
                        prop = props{ii};
                        prop_ext = prop;
                        % Skip irec as it has already been dealt with
                        if isequal(prop_ext, 'sim_irec')
                            continue;
                        end
                        %%% Backwards compatibility
                        % Skip a property if not stored
                        if ~isfield(storedProps, prop)
                            continue;
                        end
                        % Renamed spiketimes to eventtimes
                        if ~isempty(strfind(prop_ext, 'spiketimes'))
                            prop_ext = strrep(prop_ext, 'spiketimes', 'eventtimes');
                        end
                        % Overwrite the field
                        obj.(prop) = storedProps.(prop_ext);
                    end
                else
                    %error('Run %i does not exist', p.irec);
                end
                
            end
            
        end
        
        disp(obj)
        plot(obj, varargin)
        obj = save(obj)
        obj = run(obj)
        obj = irec(obj)
        obj = experiment(obj)
        output = struct(obj)
        output = exist(obj, varargin)
        output = delete(obj, varargin)
        output = anadata(obj, varargin)
        output = spiketimes(obj, varargin)
        output = notes(obj, varargin)
        output = strpad(obj, varargin)
        output = basedir(obj)
        output = datadir(obj)
        output = directdir(obj)
        output = x(obj)
        output = subsref(obj, irec)
        output = parent(obj)
        output = child(obj, irec)
        output = runSubthresholdModel(obj, varargin)
    end
    
end