fa5436e0a7
GitOrigin-RevId: e8057b67ebf307f01bdcc8fba94d94f75039d1f6
55 lines
1.2 KiB
Nix
55 lines
1.2 KiB
Nix
{
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lib,
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buildPythonPackage,
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fetchFromGitHub,
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setuptools,
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numpy,
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pmdarima,
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scikit-learn,
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scipy,
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pytestCheckHook,
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}:
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buildPythonPackage rec {
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pname = "tbats";
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version = "1.1.3";
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pyproject = true;
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src = fetchFromGitHub {
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owner = "intive-DataScience";
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repo = "tbats";
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rev = version;
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hash = "sha256-f6QqDq/ffbnFBZRAT6KQRlqvZZSE+Pff2/o+htVabZI=";
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};
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nativeBuildInputs = [ setuptools ];
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propagatedBuildInputs = [
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numpy
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pmdarima
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scikit-learn
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scipy
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];
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nativeCheckInputs = [ pytestCheckHook ];
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pytestFlagsArray = [
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# test_R folder is just for comparison of results with R lib
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# we need only test folder
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"test/"
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# several tests has same name, so we use --deselect instead of disableTests
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# Test execution is too long > 15 min
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"--deselect=test/tbats/TBATS_test.py::TestTBATS::test_fit_predict_trigonometric_seasonal"
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];
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pythonImportsCheck = [ "tbats" ];
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meta = with lib; {
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description = "BATS and TBATS forecasting methods";
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homepage = "https://github.com/intive-DataScience/tbats";
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changelog = "https://github.com/intive-DataScience/tbats/releases/tag/${src.rev}";
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license = licenses.mit;
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maintainers = with maintainers; [ mbalatsko ];
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};
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}
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