Sorry, I misused the Utilities::MPI::sum() function and thought it might
not work right at first.
Now I use the Utilities::MPI::sum() function to sum up the energy in all
processors, is that right?
在 2019年6月4日星期二 UTC+8上午8:50:25，llf m写道：
>
> Dear Wolfgang,
> how to do this in distributed parallel mode( to sum up the energy in all
> processors)?
> as the vector and matrix has the "compress(...::add)" function,
> what about a scalar?
>
> 在 2017年9月16日星期六 UTC+8上午12:19:01，Wolfgang Bangerth写道：
>>
>> On 09/15/2017 08:32 AM, Yiyang Zhang wrote:
>> > For example, consider the sine-Gordon equation, which is in Step-25.
>> > With the help of the DataPostprocessor class, we can output a plot for
>> > the energy density.
>> > But then, how could we calculate the total energy?
>> >
>> > The best scenario would be computing the energy density and total
>> energy
>> > at the same time...
>>
>> Yiyang -- it's not easily possible to do it both at the same time
>> (because DataPostprocessor only creates output, but not do any kind of
>> integration -- so you are missing some information). But it's easy to do
>> by hand. For example, for the Laplace equation, you would do something
>> like this (pseudo-code):
>>
>> double compute_energy ()
>> {
>> FEValues fe_values (...);
>> std::vector<Tensor<1,dim> > solution_gradients (n_q_points);
>>
>> double energy = 0;
>>
>> for (cell=...)
>> {
>> fe_values.reinit(cell);
>> fe_values.get_function_gradients (solution,
>> solution_gradients);
>>
>> for (q=0...n_q_points)
>> energy += solution_gradients[q] * solution_gradients[q] *
>> fe_values.JxW(q);
>> }
>>
>> return energy;
>> }
>>
>> Best
>> W.
>>
>
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