Unverified Commit 6e083a90 authored by Pol Dellaiera's avatar Pol Dellaiera Committed by GitHub
Browse files

python3Packages.tess: fix build failure; adopt (#501491)

parents a93bb0c6 da6c1d34

pkgs/development/python-modules/tess/default.nix

+12 −8
Original line number Diff line number Diff line 
{

  lib,

  buildPythonPackage,

  fetchPypi,

  cython,

  setuptools,

  fetchPypi,

  lib,

  numpy,

  scipy,

  pytestCheckHook,

  python,

  scipy,

  setuptools,

}:



buildPythonPackage rec {

buildPythonPackage (finalAttrs: {

  pname = "tess";

  version = "0.3.1";

  pyproject = true;



  src = fetchPypi {

    inherit pname version;

    inherit (finalAttrs) pname version;

    hash = "sha256-5Ic06+K7CWRh1t2v3aJ5JlBACvHXqQyYzvU71jZJFtI=";

  };
@@ -30,6 +30,10 @@ buildPythonPackage rec { 
    scipy

  ];



  # scipy has depecrated since version 1.15.0 the function `sph_harm`, and has

  # been removed in 1.17.0 in favor of `sph_harm_y`

  patches = [ ./scipy_sph_harm.patch ];



  pythonImportsCheck = [ "tess" ];



  nativeCheckInputs = [ pytestCheckHook ];
@@ -44,6 +48,6 @@ buildPythonPackage rec { 
    description = "Module for calculating and analyzing Voronoi tessellations";

    homepage = "https://tess.readthedocs.org";

    license = lib.licenses.bsd3;

    maintainers = [ ];

    maintainers = with lib.maintainers; [ drawbu ];

  };

}
 
})

pkgs/development/python-modules/tess/scipy_sph_harm.patch

0 → 100644
+20 −0
Original line number Diff line number Diff line 
diff --git a/tess/__init__.py b/tess/__init__.py

index b7f8f80..91c518f 100644

--- a/tess/__init__.py

+++ b/tess/__init__.py

@@ -374,13 +374,13 @@ def orderQ(l, xyz, weights=1):

     :math:`w_i` are the `weights`, defaulting to uniform: (:math:`\frac{1}{N_b}`)

     """

     import numpy as np

-    from scipy.special import sph_harm

+    from scipy.special import sph_harm_y

 

     theta, phi = cart_to_spher(xyz).T

     weights = np.ones(xyz.shape[0]) * weights

     weights /= np.sum(weights)

     mmeans = np.zeros(2 * l + 1, dtype=float)

     for m in range(-l, l + 1):

-        sph_weighted = sph_harm(m, l, phi, theta).dot(weights)  # Average of Y_{6m}

+        sph_weighted = sph_harm_y(l, m, theta, phi).dot(weights)  # Average of Y_{6m}

         mmeans[m] = abs(sph_weighted) ** 2

     return np.sqrt(4 * np.pi / (2 * l + 1) * np.sum(mmeans))