Added note on reproducibility of paper figures

Author: lindonroberts

README.rst

@@ -16,7 +16,7 @@ DFO-LS: Derivative-Free Optimizer for Least-Squares
 
 DFO-LS is a flexible package for solving nonlinear least-squares minimisation, without requiring derivatives of the objective. It is particularly useful when evaluations of the objective function are expensive and/or noisy.
 
-This is an implementation of the algorithm from our paper: C. Cartis, J. Fiala, B. Marteau and L. Roberts, `Improving the Flexibility and Robustness of Model-Based Derivative-Free Optimization Solvers <https://arxiv.org/abs/1804.00154>`_, technical report, University of Oxford, (2018). DFO-LS is more flexible version of `DFO-GN <https://github.com/numericalalgorithmsgroup/dfogn>`_.
+This is an implementation of the algorithm from our paper: C. Cartis, J. Fiala, B. Marteau and L. Roberts, `Improving the Flexibility and Robustness of Model-Based Derivative-Free Optimization Solvers <https://arxiv.org/abs/1804.00154>`_, technical report, University of Oxford, (2018). For reproducibility of all figures in this paper, please feel free to contact the authors. DFO-LS is more flexible version of `DFO-GN <https://github.com/numericalalgorithmsgroup/dfogn>`_.
 
 If you are interested in solving general optimization problems (without a least-squares structure), you may wish to try `Py-BOBYQA <https://github.com/numericalalgorithmsgroup/pybobyqa>`_, which has many of the same features as DFO-LS.