% Caller for Seed Dispersal

function Xt = seed_v_w(v_e, beta_p, lambda_p, X0)

    if (nargin < 4)

        v_e = 1;         % wind speed average [m/s]. Default value

        % The term ±β v_e − v_w(t) represents the probability associated with
        % drift toward the mean wind speed of v_e.
        beta_p = 0.1; 
  
        % λ∆t represents the probability associated with random diffusion of the wind speed
        lambda_p = 0.2; 

        X0 = 0;
    end

    % Constants
    T = 500; 
    N = 2^10;
    dtMult = 1; 
    prec = 2; % decimal precion just for legend

    % --- Wind speed SDE calculation
    % SDE linear: dX = c1*X dt + sigma1*X dW
    % f(t,Xt) = c1 Xt + c2
    % g(t,Xt) = sigma1 Xt + sigma2
    f = @(c1X, c2) (c1X + c2);
    g = @(sigma1X, sigma2) (sigma1X + sigma2)

    name = "Euler–Maruyama linear - Xt: Wind speed"
    fprintf("Executing: %s", name);

    dimSystemEq = 1;   

    legend_str = [ strcat("Wind speed - Wind speed average v_e=", num2str(v_e, prec)," [m/s], /beta=", ...
                            num2str(beta_p, prec), ", /lamba=", num2str(lambda_p)) ];

    st.c1X = @(x) (2*lambda_p*beta_p*(v_e-x) );
    st.c2 = 0;

    st.sigma1X = @(x) ( sqrt(2*(lambda_p^2)*lambda_p) ); % x is ignored
    st.sigma2 = 0;

    % Resolve EM method
    Xt = EM_linear(name, f, g, st, X0, T, N, dtMult, dimSystemEq, legend_str);

end