y
being a vector? In contrast to what?
collect_transpose
, or whatever you call it, is essentially an extremely simple wrapper around an iterator. It's still far from something that a name solve
would suggest.collect_transpose
as to how to accumulate the outputcollect_transpose
is the right name for the function we need but it's closer to what it actually does then solve
.
results(solve(...))
?
solve
).
as for the output, let's say I have a custom type to hold points:
type Point<:AbstractVector
x;y
end
getindex(::Point)=...
there is no way you can push it into a Matrix
without loosing its interpretation as a point.
Moreover, how do you imagine handling the matrix if you don't know it's size a priori? The only way you will know the size is to run the iteration, but then you still have to store the output at the same time. But if you are already storing the output (as a vector) then you would only loose on performance if you want to convert it in afterward (e.g. to a matrix).
f=solve(ode)
giving an interpolable object with call overloaded so that f(t)
=> y(t)
and f'(t)
=> dy(t)
. And with getindex
defined so that f[i]
=>y[i]
or f[i]
=>(t[i],y[i],dy[i])
.
yout(f)
returning your Matrix
or whatnot
Yes, you're right, changing the return type depending on a keyword argument is bad.
Concerning your example, yes, there can be corner cases. The beauty of building on iterators, is that one can always drop down to them and do what one wants. Alternatively, we could only return a matrix when isa(y0, Vector)
, that should cover 95% of the use-cases.
When the number of output points is not known, then make a vector, push to that and reshape in the end. (Note that the reshape does not copy but just re-interprets the memory as matrix).
I still don't want to call something a solution which is not a solution at all but can only be used to, maybe, generate a solution.
( sqrt(sum(squares)/length))
can be more efficient.