Jan Hasenauer
Jan Hasenauer
and/or to adapt the scale of the visualisation. e.g. visualise a log-transformed values on a log scale
yes, this would be a nice feature. maybe coloring of points by a exit flag. alternatively the shape might be changed.
The discussion somehow raises the question whether we should distinguish between lower and upper parameter bounds bounds, and the interval on which the uniform distribution is defined. For all distribution...
I also think that 1 & 2 are good choices. Would be good too make this options easily accessible on the pyPESTO side.
not only good but critical. if the initial population is too homogeneous the adaptation will not work properly.
In the past we used multiple results from the multi-start local optimization. not only results from the best plateau but also from other once. I guess this can be improved...
I also agree that simplifications can be very valuable. The proposed way sounds good. As finding problems caused by simplifications can be rather difficult, not sure how to "warn" the...
@paulstapor @LeonardSchmiester @yannikschaelte What did Philipp do regarding the sed-ml import. As he is using JWS online models I'm wondering if he implemented something like an sed-ml import.
I recall that sometimes simply changing the sign of the mass matrix and the vector field helped. Probably not the problem here, but easy to test.
Sounds good!