Hello,

I'm a mechanical engineering grad student and my adviser has just asked me to write

a data visualization utility for one of our sensor projects. As it's summer and he wants me to have some fun with it, I thought

this would be a great time to learn a language adept at scientific

computing, so I went ahead and plowed right into F#.

As I'm new to the functional programming paradigm I'm having a

little difficulty structuring my program properly, especially given the

possibility of easily combining OO/FP in F#. My task is the following:

1. We have dozens of sensors constantly reporting data (once every few seconds).

2. I need to connect to all sensors simultaneously, create an

   in-memory timeseries of each sensor's output, and then calculate in

   real time various statistics on these timeseries.

3. Every few hours I need to flush the data into a binary file for logging purposes.

How should I be designing my application? I've thought about

something like this:

1. I was planning on connecting to each sensor to start receiving data

and then dump this data onto a message queue.

2. I'd have an event-driven processing function receives data on the

queue. When data is received, it is determined which sensor the data

came from, and then the data is placed into the timeseries object of

the corresponding sensor. 3. Every time a sensor data timeseries object

is added to, I could fire an Event and have my statistics functions

crunch new data for the sensor.

Obviously I need to maintain some kind of state in this application.

So I'd add the following mutable data structures. I would use a generic

.NET resizable List for storing my timeseries data and implement a new

derivative to fire on data add events. I could store the mappings

between sensorid and the actual timeseries container in a Dictionary

(when data is popped off the queue, I can read the sensorid field, grab

the timeseries container for that sensorid, and then easily add new

data). I could also have a second dictionary to store mappings between

sensorid and the various timeseries containing statistics for that

sensorid timeseries). When a main sensor timeseries is added to, it

fires an event to call all of the statistics functions to run

themselves on the new data and store their information in the

appropriate dictionary for that sensorid.

I haven't thought about how to save the data much yet, but I figured I could just write out binary files with the data.

Any advice, ideas, or references are appreciated.

Thanks :)