Extrapolation Experimentalist
The extrapolation sampling method identifies novel experimental conditions where the prediction of a model exhibits the highest slope compared to already existing data.
For each novel condition, denoted as $x_i$, with its corresponding prediction $y_{\text{pred}, i}$, the process begins by identifying the nearest existing datapoint, $x_{\text{nearest}, i}$, which has an associated observed value $y_{\text{existing}, i}$. The slope between these points is then calculated as follows:
$$ m_i = \frac{y_{\text{pred}, i}-y_{\text{existing}, i}}{x_i-x_{\text{nearest}, i}} $$
The condition with the highest slope is selected first:
$$ \underset{i}{argmax}(m_i) $$
Metadata
Release files for autora-experimentalist-extrapolation 1.0.1
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| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| autora_experimentalist_extrapolation-1.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 18.7 kB
Release files / autora_experimentalist_extrapolation-1.0.1.tar.gz
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