I am with you on #3 and I had that thought this morning but I thought it surely uses something more interesting. I think I might pass in the random generator from the Runner to use for the random.nextLong(). I should do that rather than reusing the same generator inside each agent because, if I remember correctly it is not threadsafe:

There are actually two versions of Mersenne Twister: the class ec.util.MersenneTwister and the class ec.util.MersenneTwisterFast. The former is a drop-in subclass replacement for java.util.Random, and is threadsafe. The latter is not threadsafe, is not a subclass of java.util.Random, and has many methods (perhaps nowadays unnecessarily) heavily inlined, and as a result is significantly faster. MersenneTwisterFast is the only class provided with and used by MASON.


Which, in my limited understanding, makes me think re-using it in every Agent is a bad idea. Does that agree with your understanding?

Thanks
Steve 

On Sat, Sep 3, 2016 at 10:22 PM, Joey Harrison <[log in to unmask]> wrote:
A couple quick thoughts:

1) My first thought is that there's a transient phase (or something else strange) in your RNG. Try writing a test program that calls vonMises.nextDouble() 1000 times and save the values in a text file. Read the file into R or whatever you use and plot the distribution. Does it look like what you expect? Do there happen to be five clusters or are your samples nearly uniform?

2) The κ you picked, 1e-7, should give you a distribution very close to uniform. Try using MASON's RNG instead, which is uniform, and see what happens. 
Change this:
double direction = vonMises.nextDouble();
To this:
double direction = (runner.random.nextDouble() - 0.5) * 2 * Math.PI;

If it looks normal, you know there's something strange happening with the vonMises RNG.

3) It's possible that you're creating a bunch of RNGs with the same seed. When you instantiate a MersenneTwisterFast without giving it a seed, it uses System.currentTimeMillis(). I'm guessing it takes about 5 milliseconds to create all your agents, which is why you see only five different angles. Either seed them with an incrementing value, or use random.nextLong().

I'm pretty sure it's #3.

Good luck,
Joey

On Sat, Sep 3, 2016 at 11:41 PM, Steven Pousty <[log in to unmask]> wrote:
Greetings all:
I am writing an agent based model to explore wildflife corridor selection. I started by taking the woims example from the tutorial and then modifying it. Everything was going fine until I implemented choosing movement based on a random angle and a random distance.

I had to use the COLT library integration for the Von Mise distribution (typically used for circular valued numbers). I put in the burn for the constructor to see if that would help. I also 

I am seeing that on the first step, there is only a small number different angles being chosen but then for the rest of the steps it seems to working as expected. I tried debugging and seeing that I am generating new agents each with their own instance of the MersenneTwister. 

I would really love if someone could look at the code and see what I am missing (I do not believe anything is broken in MASON or COLT - things are just broken in my brain ;)  ). 

Here is the agent code


and here is the runnable


I have attached the screen shot showing the weird behavior on step 1 for multiple simulations. 

I am sure others have seen this and I am just forgetting something important.  

Thanks in advance!
Steve