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README.rst

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``adaptive`` is an open-source Python library designed to
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make adaptive parallel function evaluation simple. With ``adaptive`` you
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just supply a function with its bounds, and it will be evaluated at the
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“best” points in parameter space, rather than unecessarily computing *all* points.
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With just a few lines of code you can evaluate functions on a computing cluster,
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“best” points in parameter space, rather than unecessarily computing *all* points on a dense grid.
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With just a few lines of code you can evaluate functions on a computing cluster,
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live-plot the data as it returns, and fine-tune the adaptive sampling algorithm.
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``adaptive`` shines on computations where each evaluation of the function
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takes *at least* ≈100ms. Other approaches for parallisation should be chosen for
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function calls that are faster than this.
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takes *at least* ≈100ms due to the overhead of picking potentially interesting points.
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Run the ``adaptive`` example notebook `live on
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Binder <https://mybinder.org/v2/gh/python-adaptive/adaptive/master?filepath=example-notebook.ipynb>`_

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