Skip to content

Update Readme to emphasise when adaptive should be used #318

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
Merged
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
9 changes: 6 additions & 3 deletions README.rst
Original file line number Diff line number Diff line change
Expand Up @@ -11,9 +11,12 @@
``adaptive`` is an open-source Python library designed to
make adaptive parallel function evaluation simple. With ``adaptive`` you
just supply a function with its bounds, and it will be evaluated at the
“best” points in parameter space. With just a few lines of code you can
evaluate functions on a computing cluster, live-plot the data as it
returns, and fine-tune the adaptive sampling algorithm.
“best” points in parameter space, rather than unecessarily computing *all* points on a dense grid.
With just a few lines of code you can evaluate functions on a computing cluster,
live-plot the data as it returns, and fine-tune the adaptive sampling algorithm.

``adaptive`` shines on computations where each evaluation of the function
takes *at least* ≈100ms due to the overhead of picking potentially interesting points.

Run the ``adaptive`` example notebook `live on
Binder <https://mybinder.org/v2/gh/python-adaptive/adaptive/master?filepath=example-notebook.ipynb>`_
Expand Down