86 lines
1.5 KiB
Nix
86 lines
1.5 KiB
Nix
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{
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lib,
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buildPythonPackage,
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fetchFromGitHub,
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# dependencies
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networkx,
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numpy,
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scipy,
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scikit-learn,
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pandas,
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pyparsing,
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torch,
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statsmodels,
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tqdm,
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joblib,
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opt-einsum,
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xgboost,
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google-generativeai,
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# tests
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pytestCheckHook,
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pytest-cov,
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coverage,
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mock,
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black,
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}:
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buildPythonPackage rec {
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pname = "pgmpy";
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version = "0.1.26";
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pyproject = true;
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src = fetchFromGitHub {
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owner = "pgmpy";
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repo = "pgmpy";
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rev = "refs/tags/v${version}";
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hash = "sha256-RusVREhEXYaJuQXTaCQ7EJgbo4+wLB3wXXCAc3sBGtU=";
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};
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dependencies = [
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networkx
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numpy
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scipy
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scikit-learn
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pandas
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pyparsing
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torch
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statsmodels
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tqdm
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joblib
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opt-einsum
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xgboost
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google-generativeai
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];
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disabledTests = [
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# flaky:
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# AssertionError: -45.78899127622197 != -45.788991276221964
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"test_score"
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# self.assertTrue(np.isclose(coef, dep_coefs[i], atol=1e-4))
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# AssertionError: False is not true
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"test_pillai"
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# requires optional dependency daft
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"test_to_daft"
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];
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nativeCheckInputs = [
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pytestCheckHook
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# xdoctest
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pytest-cov
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coverage
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mock
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black
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];
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meta = {
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description = "Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks";
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homepage = "https://github.com/pgmpy/pgmpy";
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changelog = "https://github.com/pgmpy/pgmpy/releases/tag/v${version}";
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license = lib.licenses.mit;
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maintainers = with lib.maintainers; [ happysalada ];
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};
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}
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