2020-02-13 12:31:08 +00:00
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{ lib
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, buildPythonPackage
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, fetchFromGitHub
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, python
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2021-05-14 19:46:36 +01:00
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, scikit-learn
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2020-02-13 12:31:08 +00:00
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, scipy
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, pytest
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2020-11-18 16:39:33 +00:00
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, isPy27
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2020-02-13 12:31:08 +00:00
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}:
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buildPythonPackage rec {
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pname = "bayesian-optimization";
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2020-10-16 06:41:18 +01:00
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version = "1.2.0";
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2020-11-18 16:39:33 +00:00
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disabled = isPy27;
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2020-02-13 12:31:08 +00:00
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src = fetchFromGitHub {
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owner = "fmfn";
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repo = "BayesianOptimization";
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2020-10-16 06:41:18 +01:00
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rev = version;
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sha256 = "01mg9npiqh1qmq5ldnbpjmr8qkiw827msiv3crpkhbj4bdzasbfm";
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2020-02-13 12:31:08 +00:00
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};
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propagatedBuildInputs = [
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2021-05-14 19:46:36 +01:00
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scikit-learn
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2020-02-13 12:31:08 +00:00
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scipy
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];
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2020-08-25 03:07:09 +01:00
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2020-02-13 12:31:08 +00:00
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checkInputs = [ pytest ];
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checkPhase = ''
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2020-09-23 19:52:04 +01:00
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# New sklearn broke one test: https://github.com/fmfn/BayesianOptimization/issues/243
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pytest tests -k "not test_suggest_with_one_observation"
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2020-02-13 12:31:08 +00:00
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'';
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meta = with lib; {
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description = "A Python implementation of global optimization with gaussian processes";
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homepage = "https://github.com/fmfn/BayesianOptimization";
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license = licenses.mit;
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maintainers = [ maintainers.juliendehos ];
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};
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}
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