From 708cd0c9bf5c6d6c7f8fd93d96ed22f02c64343f Mon Sep 17 00:00:00 2001 From: Thomas Aarholt Date: Mon, 12 Apr 2021 21:09:47 +0200 Subject: [PATCH 1/2] Update README.rst --- README.rst | 10 +++++++--- 1 file changed, 7 insertions(+), 3 deletions(-) diff --git a/README.rst b/README.rst index 5403bd137..aa9a6bb73 100644 --- a/README.rst +++ b/README.rst @@ -11,9 +11,13 @@ ``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. +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. Other approaches for parallisation should be chosen for +function calls that are faster than this. Run the ``adaptive`` example notebook `live on Binder `_ From c523469fecd10143f8fadce407f1bb68e90718d3 Mon Sep 17 00:00:00 2001 From: Bas Nijholt Date: Mon, 10 May 2021 11:14:46 +0200 Subject: [PATCH 2/2] small rephrase --- README.rst | 7 +++---- 1 file changed, 3 insertions(+), 4 deletions(-) diff --git a/README.rst b/README.rst index aa9a6bb73..d05979308 100644 --- a/README.rst +++ b/README.rst @@ -11,13 +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, rather than unecessarily computing *all* points. -With just a few lines of code you can evaluate functions on a computing cluster, +“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. Other approaches for parallisation should be chosen for -function calls that are faster than this. +takes *at least* ≈100ms due to the overhead of picking potentially interesting points. Run the ``adaptive`` example notebook `live on Binder `_