myODE

function [ output_args ] = myODE( input_args )
%UNTITLED2 Summary of this function goes here
%   Detailed explanation goes here










% u = matrix of vectors [v, theta, x, y]
% use Euler method: solve at initial coditions + time step, set that as new initial conditions, repeat

tstep = 1; % set time step for Euler method
t = [0:tstep:100]; % time vector (seconds)

[TOUT,YOUT] = ode23(dv_dt,[0 100],y0);
plot(TOUT, YOUT);
%axis([0 1 0 3]) % set axis limits
    
% plan: optimize in v, then theta, then v, then theta...





%{
v = u[0]
    theta = u[1]
    x = u[2]
    y = u[3]
    return numpy.array([-g*sin(theta) - C_D/C_L*g/v_t**2*v**2,
                      -g*cos(theta)/v + g/v_t**2*v,
                      v*cos(theta),
                      v*sin(theta)])
%}



end