differential-equations

This question is a continuation of this one . My goal is to find the turning points in stock price data. So far I: Tried differentiating the smoothed price set, with the help of Dr. Andrew Burnett-Thompson using the centered five-point method, as explained here . I use the EMA20 of tick data for smoothing the data set. For each point on the chart I get the 1st derivative (dy/dx). I create a second chart for the turning points. Each time the dy/dx is between [-some_small_value] and [+some_small_value] - I add a point to this chart. The problems are: I don't get the real turning points, I get

I have a large (>2000 equations) system of ODE's that I want to solve with python scipy's odeint. I have three problems that I want to solve (maybe I will have to ask 3 different questions?). For simplicity, I will explain them here with a toy model, but please keep in mind that my system is large. Suppose I have the following system of ODE's: dS/dt = -beta*S dI/dt = beta*S - gamma*I dR/dt = gamma*I with beta = c p I where c, p and gamma are parameters that I want to pass to odeint. odeint is expecting a file like this: def myODEs(y, t, params): c,p, gamma = params beta = c*p S = y[0] I = y[1]

I am building (my first...) MatLab program, it needs to differentiate an equations symbolically and then use this solution many many times (with different numeric inputs). I do not want it to recalculate the symbolic differentiation every time it needs to put in a new set of numeric values. This would probably greatly add to the time taken to run this program (which - given its nature, a numeric optimiser, will probably already be hours). My question is how can I structure my program such that it will not recalculate the symbolic differentiation? The class in question is: function [ result ] =

Pretty noob question so please bear with me. I am following the example given here--> http://www.codeproject.com/Articles/268589/odeint-v2-Solving-ordinary-differential-equations In particular, I am looking at this function: void lorenz( state_type &x , state_type &dxdt , double t ) { dxdt[0] = sigma * ( x[1] - x[0] ); dxdt[1] = R * x[0] - x[1] - x[0] * x[2]; dxdt[2] = x[0]*x[1] - b * x[2]; } In my case, R takes on a series of values (vector with 100 doubles). odeint is called as: integrate_const( runge_kutta4< state_type >() , lorenz , x , 0.0 , 10.0 , dt ); I would like to do this for each

I'm using odeint to simulate a system wherein there are several variables which should not go less than zero. Is there an appropriate way to bound a variable in odeint to a particular range? There is no such possibility in odeint. And I guess there are no algorithms which could do that. You must somehow encode the bound in your ODE. If you only want to find a bound during the evolution of your system use a loop like while( t < tmax ) { stepper.do_step( ode , x , t , dt ); t += dt; if( check_bound( x , t ) ) break; } Two side nodes, maybe this is the case for your problem: There are special