Andy Little <andy <at> servocomm.freeserve.co.uk> writes:
"Leland Brown"wrote
When I have a vector of mixed quantities (length, velocity, time, dimensionless - together in one vector), I end up going to something more like t3_quantity. (FYI, this occurs in the context of least-squares estimation of model parameters, where the parameters are of various dimensions.)
In cases of vectors, I have only used vectors where all elements are one type of quantity. The vectors are used to represent position, direction and so on in 3 dimensions. A container that holds different quantities I would consider to be a tuple. But I stress I am not an expert.
I see what you mean. But unfortunately, in the least-squares estimation, the tuples get used extensively as vectors in heavy linear algebra equations. So I'm stuck with using vectors of heterogeneous units in a matrix library.
The question then is: when are the benefits of strong type checking (so use a Quantity type) justified, and when arent they (so use a float type). That would be a good question to answer in the PQS docs AFAICS. But not a trivial one.
True on both counts.
I would guess that the only problem apart from slow performance would be that the t3_quantity would use a lot of space compared with a float, which would have an impact if used in some situations.
Yes, but perhaps not as much space (or time) as you would think. I allocate a few bits to each dimensionn exponent and combine them in a single iteger value. Then in a multiplication I can add all the exponents at once with only one addition operation (and I can check for matching dimensions with only one integer comparison). This works well for me because I have only integer exponents and only length and time dimensions, so I can easily allocate plenty of bits to avoid overflow. Perhaps you can make use of something similar in your design. -- Leland