Merge pull request #325402 from kirillrdy/pykalman

{

  lib,

  buildPythonPackage,

  fetchPypi,

  fetchFromGitHub,

  numpy,

  scipy,

  pytestCheckHook,

  nose,

  setuptools,

}:

buildPythonPackage rec {

  pname = "pykalman";

  version = "0.9.7";

  format = "setuptools";

  pyproject = true;

  src = fetchPypi {

    inherit pname version;

    hash = "sha256-E1d5IAOTxrNwIhmQ9zFnQEcvVBNG6SEdEWMOLC2PuKA=";

  src = fetchFromGitHub {

    owner = "pykalman";

    repo = "pykalman";

    rev = "aaf8c8574b0474b6f41b7b135a9a7f2dfbd0e86c"; # no tags

    hash = "sha256-++YqxGMsFGv5OxicDFO9Xz89e62NG8X+6oR6M9ePUcg=";

  };

  patches = [

    # https://github.com/pykalman/pykalman/issues/83

    ./fix-masked-arrays-not-supported.patch

    # python 3.11 issues fix: https://github.com/pykalman/pykalman/pull/101

    ./fix-p311-issues.patch

  ];

  build-system = [ setuptools ];

  propagatedBuildInputs = [

    numpy

    scipy

  ];

  nativeCheckInputs = [

    pytestCheckHook

    nose

  ];

  nativeCheckInputs = [ pytestCheckHook ];

  pythonImportsCheck = [ "pykalman" ];

  meta = with lib; {

--- a/pykalman/utils.py

+++ b/pykalman/utils.py

@@ -70,7 +70,10 @@

             cv_chol = linalg.cholesky(cv + min_covar * np.eye(n_dim),

                                       lower=True)

         cv_log_det = 2 * np.sum(np.log(np.diagonal(cv_chol)))

-        cv_sol = solve_triangular(cv_chol, (X - mu).T, lower=True).T

+        try:

+            cv_sol = solve_triangular(cv_chol, (X - mu).T, lower=True).T

+        except ValueError:

+            cv_sol = np.linalg.solve(cv_chol, (X - mu).T).T

         log_prob[:, c] = - .5 * (np.sum(cv_sol ** 2, axis=1) + \

                                      n_dim * np.log(2 * np.pi) + cv_log_det)

--- a/pykalman/utils.py

+++ b/pykalman/utils_copy.py

@@ -40,6 +40,10 @@

 from scipy import linalg

+# monkey patch

+if not hasattr(inspect, 'getargspec'):

+    inspect.getargspec = inspect.getfullargspec

+

 def array1d(X, dtype=None, order=None):

     """Returns at least 1-d array with data from X"""

     return np.asarray(np.atleast_1d(X), dtype=dtype, order=order)