trial_cost_fn.m

%Determine cost of funding trials (stochastically) for phase comp.phase
%Input:
%@comp.phase is a cell of strings where each is 'DSC','PRE','P1','P2','P3','NDA', 'APP', 'SLD'
%@params is a struct containing the initial set of parameters set by the function init_params_fn
%Output:
%@cost is of type double and is the returned funding cost
function cost = trial_cost_fn(comp_phase, params, comp_types)

    cost = zeros(size(comp_phase));
    rowidxs    = phase2index_fn(comp_phase);
    elig_idx = ~( strcmp('DSC',comp_phase) | strcmp('NDA',comp_phase) | strcmp('APP',comp_phase) | strcmp('SLD',comp_phase) );
    if(~any(elig_idx))
       return;
    end
    
    mu = nan(size(comp_phase));
    sigma = nan(size(comp_phase));    
    mx = nan(size(comp_phase));    
    for i=1:length(unique(comp_types))
        mu(elig_idx) = params.assets(i).pricing_params(rowidxs(elig_idx), name2index_fn(params.assets(i), 'pricing_params', 'mu', false))';
        sigma(elig_idx) = params.assets(i).pricing_params(rowidxs(elig_idx), name2index_fn(params.assets(i), 'pricing_params', 'sigma', false));
        mx(elig_idx) = params.assets(i).pricing_params(rowidxs(elig_idx), name2index_fn(params.assets(i), 'pricing_params', 'max', false));
    end
    
    raw_cost  = lognrnd(mu',sigma');
    cost = min(raw_cost, mx')';
end
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