py311

.github/workflows/codestyle.yml

@@ -10,11 +10,11 @@ jobs:
     steps:
       - name: Checkout repository
         uses: actions/checkout@v2
-      - name: Install Conda w/ Python 3.12
+      - name: Install Conda w/ Python 3.11
         uses: conda-incubator/setup-miniconda@v2
         with:
           auto-activate-base: false
-          python-version: '3.12'
+          python-version: '3.11'
           channels: conda-forge
       - name: Install Dependencies
         shell: bash -el {0}

.github/workflows/compatibility.yml

@@ -9,8 +9,8 @@ jobs:
       fail-fast: false
       matrix:
         os: [ubuntu-latest]
-        python-version: ['3.12']
-        toxenv: [py312-test-all-latest]
+        python-version: ['3.11']
+        toxenv: [py311-test-all-latest]
         # release: [main, latest] # there are no releases yet so this would break
         release: [main]
     steps:

.github/workflows/testing.yml

@@ -13,8 +13,8 @@ jobs:
 
           - name: latest supported versions
             os: ubuntu-latest
-            python-version: '3.12'
-            toxenv: py312-test-all-latest-cov
+            python-version: '3.11'
+            toxenv: py311-test-all-latest-cov
 
           - name: oldest supported versions
             os: ubuntu-latest
@@ -23,8 +23,8 @@ jobs:
 
           - name: macOS 11
             os: macos-11
-            python-version: '3.12'
-            toxenv: py312-test-latest
+            python-version: '3.11'
+            toxenv: py311-test-latest
 
     steps:
       - name: Checkout repository

soliket/clusters/clusters.py

@@ -20,11 +20,11 @@
 import numpy as np
 import pandas as pd
 from scipy.interpolate import interp1d
-from importlib import resources
 
 import pyccl as ccl
 
 from ..poisson import PoissonLikelihood
+from ..utils import package_data_file
 from . import massfunc as mf
 from .survey import SurveyData
 from .sz_utils import szutils
@@ -43,10 +43,10 @@ class ClusterLikelihood(PoissonLikelihood):
     name = "Clusters"
     columns = ["tsz_signal", "z", "tsz_signal_err"]
 
-    data_path = str(resources.path('soliket.clusters.data', 'selFn_equD56'))
+    data_path = package_data_file('soliket.clusters.data', 'selFn_equD56')
 
     # data_path = resource_filename("soliket", "clusters/data/selFn_SO")
-    data_name = str(resources.path('soliket.clusters.data', 'E-D56Clusters.fits'))
+    data_name = package_data_file('soliket.clusters.data', 'E-D56Clusters.fits')
 
     # data_name = resource_filename("soliket",
     #                   "clusters/data/MFMF_WebSkyHalos_A10tSZ_3freq_tiles_mass.fits")

soliket/lensing/lensing.py

@@ -12,8 +12,6 @@
 """
 
 import os
-from importlib import resources
-
 import numpy as np
 import sacc
 from cobaya.likelihoods.base_classes import InstallableLikelihood
@@ -22,6 +20,7 @@
 # from cobaya.install import NotInstalledError
 
 from ..ps import BinnedPSLikelihood
+from ..utils import package_data_file
 
 
 class LensingLikelihood(BinnedPSLikelihood, InstallableLikelihood):
@@ -237,6 +236,6 @@ class LensingLiteLikelihood(BinnedPSLikelihood):
     """
     kind: str = "pp"
     lmax: int = 3000
-    datapath: str = str(resources.path('soliket.lensing.data', 'binnedauto.txt'))
-    covpath: str = str(resources.path('soliket.lensing.data', 'binnedcov.txt'))
-    binning_matrix_path: str = str(resources.path('soliket.lensing.data', 'binningmatrix.txt'))
+    datapath: str = package_data_file('soliket.lensing.data', 'binnedauto.txt')
+    covpath: str = package_data_file('soliket.lensing.data', 'binnedcov.txt')
+    binning_matrix_path: str = package_data_file('soliket.lensing.data', 'binningmatrix.txt')

soliket/utils.py

@@ -5,7 +5,7 @@
 
 """
 
-from importlib import import_module
+from importlib import import_module, resources
 
 from scipy.stats import binned_statistic as binnedstat
 import numpy as np
@@ -20,15 +20,15 @@ def binner(ls, cls, bin_edges):
     band powers with a top hat window function.
 
     Note that the centers are computed as :math:`0.5({\rm LHE}+{\rm RHE})`,
-    where :math:`{\rm LHE}` and :math:`{\rm RHE}` are the bin edges. 
-    While this is ok for plotting purposes, the user may need 
-    to recompute the bin center in case of integer ``ls`` 
+    where :math:`{\rm LHE}` and :math:`{\rm RHE}` are the bin edges.
+    While this is ok for plotting purposes, the user may need
+    to recompute the bin center in case of integer ``ls``
     if the correct baricenter is needed.
 
     :param ls: Axis along which to bin
     :param cls: Values to be binned
     :param bin_edges: The edges of the bins. Note that all but the last bin
-                      are open to the right. The last bin is closed. 
+                      are open to the right. The last bin is closed.
 
     :return: The centers of the bins and the average of ``cls`` within the bins.
     """
@@ -54,13 +54,18 @@ def get_likelihood(name, options=None):
     return t(options)
 
 
+def package_data_file(package, fname):
+    with resources.path(package, fname) as path:
+        return str(path)
+
+
 class OneWithCls(one):
     r"""
     Extension of
-    `cobaya.likelihoods.one 
+    `cobaya.likelihoods.one
     <https://cobaya.readthedocs.io/en/latest/likelihood_one.html>`_
     which creates a dummy :math:`C_\ell` requirements dictionary with an
-    :math:`\ell_{\rm max}` of 1000 to force computation of ``pp``, ``tt``, ``te``, ``ee`` 
+    :math:`\ell_{\rm max}` of 1000 to force computation of ``pp``, ``tt``, ``te``, ``ee``
     and ``bb`` :math:`C_\ell` s.
     """
     lmax = 10000