Re: [eigen] Matrix2i mean

[Petr Kubánek <pkubanek@xxxxxxxxx>]

Hi,

I know what's the problem. I am just looking either to document it or
for a solution.

Why would:

template <typename dt> dt sum()

break API/ABI? You will be able to call either sum() or sum<int32_t>(),
shouldn't you? I will try that and submit a patch.

Having sum<dt>() working, one can hopefully create mean<dt_sum,
dt_mean>(), so one can code:

mean<int32_t,double>()

Petr

On Tue, 2019-11-05 at 16:36 +0100, Christoph Hertzberg wrote:
> On 05/11/2019 16.11, Peter wrote:
> > [...]
> > 
> > actually, this would also be interesting for the scalar products
> > in 
> > general, namely a different
> > type for accumulating the sums within a scalar product, e.g. as
> > yet 
> > another template parameter for the matrices.
> 
> Adding another template parameter to basic types is not an option.
> This 
> would break ABI and API compatibility (even if the parameter has a
> default).
> 
> You could create your own custom type `my_int16` for which `my_int16
> * 
> my_int16` results in a `my_int32` (this needs to be told to Eigen, 
> similar to how real*complex products are handled).
> 
> > > [...]
> > 
> > I think it's more subtle than that.
> > Even
> > 
> >    int16_t  Two =  2;
> >    int16_t  Max =  INT16_MAX;
> >    int16_t mean = ( Max/2 + Max + Two + Two ) / int16_t(4);
> > 
> > doesn't produce an overflow.
> 
> Yes, because `Max/2` gets implicitly converted to `int`. Actually,
> even 
> adding two `int16_t` get implicitly converted to `int` (search for 
> integer promotion rules -- I don't know them entirely either). And 
> dividing an `int` by an `int16_t` results in an `int` which is only 
> afterwards converted to `int16_t`.
> 
> In contrast, Eigen::DenseBase::sum() does something (more or less) 
> equivalent to:
> 
>      T sum = T(0);
>      for(Index i=0; i< size(); ++i)
>          sum+=coeff(i);
>      return sum;
> 
> i.e., after each addition the result gets reduced to the scalar type
> of 
> the matrix, thus it will immediately overflow.
> 
> And mean() essentially just takes the return value of `sum()` and 
> divides it by the size.
> 
> 
> Christoph
> 
>