diff --git a/docs/examples/emulator/robustgasp/plot_scalargasp.py b/docs/examples/emulator/robustgasp/plot_scalargasp.py index 7e0b58992b629291d461f6c8a0d51b0e8ed3502d..a9baa354a95e8040d9f3a951c7bd235412e16c55 100644 --- a/docs/examples/emulator/robustgasp/plot_scalargasp.py +++ b/docs/examples/emulator/robustgasp/plot_scalargasp.py @@ -115,10 +115,10 @@ plt.tight_layout() # %% md # -# Above example shows how to train a GP emulator based on noise-free training data, -# which is often the case of emulating a deterministic simulator. If you are dealing -# with noisy training data, you can +# .. tip:: Above example shows how to train a GP emulator based on noise-free training data, +# which is often the case of emulating a deterministic simulator. If you are dealing +# with noisy training data, you can # -# - set the parameter ``nugget`` to a desired value, or -# - set ``nugget`` to :math:`0` and ``nugget_est`` to `True`, meaning that ``nugget`` -# is estimated from the noisy training data. \ No newline at end of file +# - set the parameter ``nugget`` to a desired value, or +# - set ``nugget`` to :math:`0` and ``nugget_est`` to `True`, meaning that ``nugget`` +# is estimated from the noisy training data. \ No newline at end of file