70 lines
1.6 KiB
Nix
70 lines
1.6 KiB
Nix
{ stdenv
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, buildPythonPackage
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, fetchFromGitHub
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, isPy27
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, pytestCheckHook
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, numpy
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, scipy
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, scikitlearn
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, pandas
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, tqdm
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, slicer
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, numba
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, matplotlib
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, nose
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, ipython
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}:
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buildPythonPackage rec {
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pname = "shap";
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version = "0.36.0";
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disabled = isPy27;
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src = fetchFromGitHub {
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owner = "slundberg";
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repo = pname;
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rev = "v${version}";
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sha256 = "1wxnxvbz6avzzfqjfbcqd4v879hvpq4021v31fhdpccr2q317rr9";
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};
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propagatedBuildInputs = [
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numpy
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scipy
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scikitlearn
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pandas
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tqdm
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slicer
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numba
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];
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preCheck = ''
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export HOME=$TMPDIR
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# when importing the local copy the extension is not found
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rm -r shap
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'';
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checkInputs = [ pytestCheckHook matplotlib nose ipython ];
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# Those tests access the network
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disabledTests = [
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"test_kernel_shap_with_a1a_sparse_zero_background"
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"test_kernel_shap_with_a1a_sparse_nonzero_background"
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"test_kernel_shap_with_high_dim_sparse"
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"test_sklearn_random_forest_newsgroups"
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"test_sum_match_random_forest"
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"test_sum_match_extra_trees"
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"test_single_row_random_forest"
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"test_sum_match_gradient_boosting_classifier"
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"test_single_row_gradient_boosting_classifier"
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"test_HistGradientBoostingClassifier_proba"
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"test_HistGradientBoostingClassifier_multidim"
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"test_sum_match_gradient_boosting_regressor"
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"test_single_row_gradient_boosting_regressor"
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];
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meta = with stdenv.lib; {
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description = "A unified approach to explain the output of any machine learning model";
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homepage = "https://github.com/slundberg/shap";
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license = licenses.mit;
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maintainers = with maintainers; [ evax ];
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platforms = platforms.unix;
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};
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}
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