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{ lib
, buildPythonPackage
, cmake
, fetchFromGitHub
, joblib
, jupyter
, jupyter-client
, matplotlib
, nbconvert
, ninja
, numba
, numpy
, pandas
, pybind11
, pytestCheckHook
, pythonOlder
, scikit-build
, scipy
, setuptools
}:
buildPythonPackage rec {
pname = "phik";
version = "0.12.4";
pyproject = true;
disabled = pythonOlder "3.7";
src = fetchFromGitHub {
owner = "KaveIO";
repo = "PhiK";
rev = "refs/tags/v${version}";
hash = "sha256-YsH7vVn6gzejunUjUY/RIcvWtaQ/W1gbciJWKi5LDTk=";
};
nativeBuildInputs = [
cmake
ninja
scikit-build
setuptools
];
propagatedBuildInputs = [
joblib
numpy
scipy
pandas
matplotlib
numba
pybind11
];
nativeCheckInputs = [
pytestCheckHook
nbconvert
jupyter
jupyter-client
];
# Uses setuptools to drive build process
dontUseCmakeConfigure = true;
pythonImportsCheck = [
"phik"
];
postInstall = ''
rm -r $out/bin
'';
preCheck = ''
# import from $out
rm -r phik
'';
disabledTests = [
# TypeError: 'numpy.float64' object cannot be interpreted as an integer
# https://github.com/KaveIO/PhiK/issues/73
"test_significance_matrix_hybrid"
"test_significance_matrix_mc"
];
disabledTestPaths = [
# Don't test integrations
"tests/phik_python/integration/"
];
meta = with lib; {
description = "Phi_K correlation analyzer library";
longDescription = ''
Phi_K is a new and practical correlation coefficient based on several refinements to
Pearson’s hypothesis test of independence of two variables.
'';
homepage = "https://phik.readthedocs.io/";
changelog = "https://github.com/KaveIO/PhiK/blob/${version}/CHANGES.rst";
license = licenses.asl20;
maintainers = with maintainers; [ melsigl ];
};
}
|
