  In recent years tamed schemes have become an important technique for
simulating SDEs and SPDEs whose continuous coefficients display superlinear
growth. The taming method, which involves curbing the growth of the
coefficients as a function of stepsize, has so far however not been adapted to
preserve the monotonicity of the coefficients. This has arisen as an issue
particularly in \cite{articletam}, where the lack of a strongly monotonic tamed
scheme forces strong conditions on the setting.
  In the present work we give a novel and explicit method for truncating
monotonic functions in separable Hilbert spaces, and show how this can be used
to define a polygonal (tamed) Euler scheme on finite dimensional space,
preserving the monotonicity of the drift coefficient. This new method of
truncation is well-defined with almost no assumptions and, unlike the
well-known Moreau-Yosida regularisation, does not require an optimisation
problem to be solved at each evaluation. Our construction is the first infinite
dimensional method for truncating monotone functions that we are aware of, as
well as the first explicit method in any number of dimensions.
