win test (#178)

* win test * workaround * workaround * workaround * workaround * move deps from conda env to requirements * add gsl and openmpi to conda env * move back swig, cmake, fftw to env * add back mpi4py * try again with openmpi * return deps configuration to original * Add version import (#180) * add version import * import on runtime and add test of import * add write_to * Fix package name * Flake fixes * setuptools_scm defaults? * remove unnecssary extra arg --------- Co-authored-by: Giacomo Galloni <[email protected]> * Add some examples for the f2f (#179) * added mflike example * update install instructions * docs formatting * win test working * formatting * formatting * formatting * formatting --------- Co-authored-by: Ian Harrison <[email protected]> Co-authored-by: Giacomo Galloni <[email protected]>
simonsobs · Jul 31, 2024 · a53b922 · a53b922
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commit a53b922
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Showing 13 changed files with 128 additions and 101 deletions.
diff --git a/.github/workflows/testing.yml b/.github/workflows/testing.yml
@@ -30,6 +30,14 @@ jobs:
             python-version: '3.11'
             toxenv: py311-test-latest
 
+          - name: Windows latest
+            os: windows-latest
+            python-version: '3.11'
+            toxenv: py311-test-latest
+            env:
+              PYTHONIOENCODING: utf-8
+              PYTHONUTF8: 1
+
     steps:
       - name: Checkout repository
         uses: actions/checkout@v3

diff --git a/pyproject.toml b/pyproject.toml
@@ -10,7 +10,6 @@ requires-python = ">=3.8, <3.12"
 license = {text = "MIT"}
 dependencies = [
     "requests",
-    'importlib-metadata; python_version<"3.8"',
     "numpy",
     "scipy>=1.6",
     "pandas", # to remove
@@ -104,3 +103,8 @@ exclude_lines = [
     # Don't complain about IPython completion helper
     "def _ipython_key_completions_",
 ]
+
+[tool.pytest.ini_options]
+markers = [
+    "require_ccl",
+]
diff --git a/requirements.txt b/requirements.txt
@@ -13,8 +13,8 @@ fuzzywuzzy
 astropy
 getdist
 cobaya
-pyccl
+pyccl >= 3.0; platform_system!='Windows'
 sacc
 fgspectra>=1.1.0
 syslibrary
-pyhalomodel
+pyhalomodel
diff --git a/soliket-tests.yml b/soliket-tests.yml
@@ -16,4 +16,4 @@ dependencies:
   - mpi4py
   - camb
   - pip:
-      - -r requirements.txt
+      - -r requirements.txt
diff --git a/soliket/clusters/clusters.py b/soliket/clusters/clusters.py
@@ -21,14 +21,14 @@
 
 import numpy as np
 import pandas as pd
-import pyccl as ccl
 from scipy.interpolate import interp1d
 
 from soliket.clusters import massfunc as mf
 from soliket.poisson import PoissonLikelihood
 
 from .survey import SurveyData
 from .sz_utils import szutils
+from cobaya import LoggedError
 
 C_KM_S = 2.99792e5
 
@@ -54,8 +54,15 @@ def initialize(self):
 
         self.zarr = np.arange(0, 2, 0.05)
         self.k = np.logspace(-4, np.log10(5), 200)
-        # self.mdef = ccl.halos.MassDef(500, 'critical')
-
+        # self.mdef = self.ccl.halos.MassDef(500, 'critical')
+
+        try:
+            import pyccl as ccl
+        except ImportError:
+            raise LoggedError(self.log, "Could not import ccl. "
+                                        "Install pyccl to use ClusterLikelihood.")
+        else:
+            self.ccl = ccl
         super().initialize()
 
     def get_requirements(self):
@@ -82,11 +89,11 @@ def get_requirements(self):
 
     def _get_sz_model(self, cosmo):
         model = SZModel()
-        model.hmf = ccl.halos.MassFuncTinker08(cosmo, mass_def=self.mdef)
-        model.hmb = ccl.halos.HaloBiasTinker10(
+        model.hmf = self.ccl.halos.MassFuncTinker08(cosmo, mass_def=self.mdef)
+        model.hmb = self.ccl.halos.HaloBiasTinker10(
             cosmo, mass_def=self.mdef, mass_def_strict=False
         )
-        model.hmc = ccl.halos.HMCalculator(cosmo, model.hmf, model.hmb, self.mdef)
+        model.hmc = self.ccl.halos.HMCalculator(cosmo, model.hmf, model.hmb, self.mdef)
         # model.szk = SZTracer(cosmo)
         return model
 

diff --git a/soliket/lensing/lensing.py b/soliket/lensing/lensing.py
@@ -1,4 +1,4 @@
-r"""
+"""
 .. module:: lensing
 
 :Synopsis: Gaussian Likelihood for CMB Lensing for Simons Observatory
@@ -21,8 +21,8 @@
 
 from soliket.ps import BinnedPSLikelihood
 
-# from cobaya.install import NotInstalledError
 
+# from cobaya.install import NotInstalledError
 
 
 class LensingLikelihood(BinnedPSLikelihood, InstallableLikelihood):
@@ -46,6 +46,7 @@ class LensingLikelihood(BinnedPSLikelihood, InstallableLikelihood):
     Likelihood install itself at run time. Please see the cobaya documentation for more
     information about installable likelihoods.
     """
+
     _url = "https://portal.nersc.gov/project/act/jia_qu/lensing_like/likelihood.tar.gz"
     install_options = {"download_url": _url}
     data_folder = "LensingLikelihood/"
@@ -109,7 +110,7 @@ def initialize(self):
         Cls = self._get_fiducial_Cls()
 
         # Set the fiducial spectra
-        self.ls = np.arange(0, self.lmax)
+        self.ls = np.arange(0, self.lmax, dtype=np.longlong)
         self.fcltt = Cls["tt"][0: self.lmax]
         self.fclpp = Cls["pp"][0: self.lmax]
         self.fclee = Cls["ee"][0: self.lmax]
@@ -207,7 +208,7 @@ def _get_binning_matrix(self):
         return binning_matrix
 
     def _get_theory(self, **params_values):
-        """
+        r"""
         Generate binned theory vector of :math:`\kappa \kappa` with correction terms.
 
         :param params_values: Dictionary of cosmological parameters.

diff --git a/soliket/mflike/theoryforge_MFLike.py b/soliket/mflike/theoryforge_MFLike.py
@@ -1,4 +1,4 @@
-"""
+r"""
 .. module:: theoryforge
 
 The ``TheoryForge_MFLike`` class applies the foreground spectra and systematic
@@ -175,7 +175,7 @@ def get_cmbfg_dict(self):
         return self.current_state["cmbfg_dict"]
 
     def get_modified_theory(self, Dls, fg_dict, **params):
-        """
+        r"""
         Takes the theory :math:`D_{\ell}`, sums it to the total
         foreground power spectrum (possibly computed with bandpass
         shift and bandpass integration) and applies calibration,
@@ -320,7 +320,7 @@ def _init_template_from_file(self):
         self.dltempl_from_file = templ_from_file(ell=self.ell)
 
     def _get_template_from_file(self, dls_dict, **nuis_params):
-        """
+        r"""
         Adds the systematics template, modulated by ``nuis_params['templ_freq']``
         parameters, to the :math:`D_{\ell}`.
 

diff --git a/soliket/tests/conftest.py b/soliket/tests/conftest.py
@@ -1,4 +1,13 @@
 import pytest
+import sys
+
+
+def pytest_collection_modifyitems(config, items):
+    if sys.platform.startswith('win'):
+        skip_on_windows = pytest.mark.skip(reason="Skipped on Windows")
+        for item in items:
+            if "require_ccl" in item.keywords:
+                item.add_marker(skip_on_windows)
 
 
 @pytest.fixture

diff --git a/soliket/tests/test_ccl.py b/soliket/tests/test_ccl.py
@@ -2,17 +2,21 @@
 Check that CCL works correctly.
 """
 import numpy as np
+import pytest
 from cobaya.likelihood import Likelihood
 from cobaya.model import get_model
 
+pytestmark = pytest.mark.require_ccl
+
 
 class CheckLike(Likelihood):
     """
     This is a mock likelihood that simply forces soliket.CCL to calculate
     a CCL object.
     """
+
     def logp(self, **params_values):
-        ccl = self.provider.get_CCL() # noqa F841
+        ccl = self.provider.get_CCL()  # noqa F841
         return -1.0
 
     def get_requirements(self):

diff --git a/soliket/tests/test_cluster.ipynb b/soliket/tests/test_cluster.ipynb
@@ -149,8 +149,8 @@
     {
      "data": {
       "text/plain": [
-       "\u001b[0;31mSignature:\u001b[0m \u001b[0mhmf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_mass_function\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcosmo\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mM\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmdef_other\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-       "\u001b[0;31mDocstring:\u001b[0m\n",
+       "\u001B[0;31mSignature:\u001B[0m \u001B[0mhmf\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mget_mass_function\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0mcosmo\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0mM\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0ma\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0mmdef_other\u001B[0m\u001B[0;34m=\u001B[0m\u001B[0;32mNone\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n",
+       "\u001B[0;31mDocstring:\u001B[0m\n",
        "Returns the mass function for input parameters.\n",
        "\n",
        "Args:\n",
@@ -162,8 +162,8 @@
        "\n",
        "Returns:\n",
        "    float or array_like: mass function                 :math:`dn/d\\log_{10}M` in units of Mpc^-3.\n",
-       "\u001b[0;31mFile:\u001b[0m      ~/miniconda3/envs/soliket/lib/python3.8/site-packages/pyccl/halos/hmfunc.py\n",
-       "\u001b[0;31mType:\u001b[0m      method\n"
+       "\u001B[0;31mFile:\u001B[0m      ~/miniconda3/envs/soliket/lib/python3.8/site-packages/pyccl/halos/hmfunc.py\n",
+       "\u001B[0;31mType:\u001B[0m      method\n"
       ]
      },
      "metadata": {},
@@ -416,13 +416,13 @@
      "evalue": "Could not find anything to use input parameter(s) {'num_massive_neutrinos'}.",
      "output_type": "error",
      "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mLoggedError\u001b[0m                               Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-8-228cccd52c87>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     43\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mcobaya\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmodel\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mget_model\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     44\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 45\u001b[0;31m \u001b[0mmodel_fiducial\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_model\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minfo_fiducial\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     46\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     47\u001b[0m \u001b[0mlnl\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmodel_fiducial\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloglikes\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m~/miniconda3/envs/soliket/lib/python3.8/site-packages/cobaya/model.py\u001b[0m in \u001b[0;36mget_model\u001b[0;34m(info)\u001b[0m\n\u001b[1;32m    103\u001b[0m             yaml_dump(sort_cosmetic(updated_info)))\n\u001b[1;32m    104\u001b[0m     \u001b[0;31m# Initialize the parameters and posterior\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 105\u001b[0;31m     return Model(updated_info[_params], updated_info[kinds.likelihood],\n\u001b[0m\u001b[1;32m    106\u001b[0m                  \u001b[0mupdated_info\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0m_prior\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mupdated_info\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkinds\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtheory\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    107\u001b[0m                  \u001b[0mpackages_path\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0minfo\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0m_packages_path\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtiming\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mupdated_info\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0m_timing\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m~/miniconda3/envs/soliket/lib/python3.8/site-packages/cobaya/model.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, info_params, info_likelihood, info_prior, info_theory, packages_path, timing, allow_renames, stop_at_error, post, prior_parameterization)\u001b[0m\n\u001b[1;32m    149\u001b[0m         \u001b[0;31m# Assign input/output parameters\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    150\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_assign_params\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minfo_likelihood\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minfo_theory\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 151\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_set_dependencies_and_providers\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    152\u001b[0m         \u001b[0;31m# Add to the updated info some values that are only available after initialisation\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    153\u001b[0m         self._updated_info = recursive_update(\n",
-      "\u001b[0;32m~/miniconda3/envs/soliket/lib/python3.8/site-packages/cobaya/model.py\u001b[0m in \u001b[0;36m_set_dependencies_and_providers\u001b[0;34m(self, manual_requirements)\u001b[0m\n\u001b[1;32m    642\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_unassigned_input\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdifference_update\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mdirect_param_dependence\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    643\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_unassigned_input\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 644\u001b[0;31m                 raise LoggedError(\n\u001b[0m\u001b[1;32m    645\u001b[0m                     \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlog\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"Could not find anything to use input parameter(s) %r.\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    646\u001b[0m                     self._unassigned_input)\n",
-      "\u001b[0;31mLoggedError\u001b[0m: Could not find anything to use input parameter(s) {'num_massive_neutrinos'}."
+      "\u001B[0;31m---------------------------------------------------------------------------\u001B[0m",
+      "\u001B[0;31mLoggedError\u001B[0m                               Traceback (most recent call last)",
+      "\u001B[0;32m<ipython-input-8-228cccd52c87>\u001B[0m in \u001B[0;36m<module>\u001B[0;34m\u001B[0m\n\u001B[1;32m     43\u001B[0m \u001B[0;32mfrom\u001B[0m \u001B[0mcobaya\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mmodel\u001B[0m \u001B[0;32mimport\u001B[0m \u001B[0mget_model\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[1;32m     44\u001B[0m \u001B[0;34m\u001B[0m\u001B[0m\n\u001B[0;32m---> 45\u001B[0;31m \u001B[0mmodel_fiducial\u001B[0m \u001B[0;34m=\u001B[0m \u001B[0mget_model\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0minfo_fiducial\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[0m\u001B[1;32m     46\u001B[0m \u001B[0;34m\u001B[0m\u001B[0m\n\u001B[1;32m     47\u001B[0m \u001B[0mlnl\u001B[0m \u001B[0;34m=\u001B[0m \u001B[0mmodel_fiducial\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mloglikes\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0;34m{\u001B[0m\u001B[0;34m}\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m[\u001B[0m\u001B[0;36m0\u001B[0m\u001B[0;34m]\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n",
+      "\u001B[0;32m~/miniconda3/envs/soliket/lib/python3.8/site-packages/cobaya/model.py\u001B[0m in \u001B[0;36mget_model\u001B[0;34m(info)\u001B[0m\n\u001B[1;32m    103\u001B[0m             yaml_dump(sort_cosmetic(updated_info)))\n\u001B[1;32m    104\u001B[0m     \u001B[0;31m# Initialize the parameters and posterior\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[0;32m--> 105\u001B[0;31m     return Model(updated_info[_params], updated_info[kinds.likelihood],\n\u001B[0m\u001B[1;32m    106\u001B[0m                  \u001B[0mupdated_info\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mget\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0m_prior\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0mupdated_info\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mget\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0mkinds\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mtheory\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m,\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[1;32m    107\u001B[0m                  \u001B[0mpackages_path\u001B[0m\u001B[0;34m=\u001B[0m\u001B[0minfo\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mget\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0m_packages_path\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0mtiming\u001B[0m\u001B[0;34m=\u001B[0m\u001B[0mupdated_info\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mget\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0m_timing\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m,\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n",
+      "\u001B[0;32m~/miniconda3/envs/soliket/lib/python3.8/site-packages/cobaya/model.py\u001B[0m in \u001B[0;36m__init__\u001B[0;34m(self, info_params, info_likelihood, info_prior, info_theory, packages_path, timing, allow_renames, stop_at_error, post, prior_parameterization)\u001B[0m\n\u001B[1;32m    149\u001B[0m         \u001B[0;31m# Assign input/output parameters\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[1;32m    150\u001B[0m         \u001B[0mself\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0m_assign_params\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0minfo_likelihood\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0minfo_theory\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[0;32m--> 151\u001B[0;31m         \u001B[0mself\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0m_set_dependencies_and_providers\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[0m\u001B[1;32m    152\u001B[0m         \u001B[0;31m# Add to the updated info some values that are only available after initialisation\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[1;32m    153\u001B[0m         self._updated_info = recursive_update(\n",
+      "\u001B[0;32m~/miniconda3/envs/soliket/lib/python3.8/site-packages/cobaya/model.py\u001B[0m in \u001B[0;36m_set_dependencies_and_providers\u001B[0;34m(self, manual_requirements)\u001B[0m\n\u001B[1;32m    642\u001B[0m             \u001B[0mself\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0m_unassigned_input\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mdifference_update\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0;34m*\u001B[0m\u001B[0mdirect_param_dependence\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mvalues\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[1;32m    643\u001B[0m             \u001B[0;32mif\u001B[0m \u001B[0mself\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0m_unassigned_input\u001B[0m\u001B[0;34m:\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[0;32m--> 644\u001B[0;31m                 raise LoggedError(\n\u001B[0m\u001B[1;32m    645\u001B[0m                     \u001B[0mself\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mlog\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0;34m\"Could not find anything to use input parameter(s) %r.\"\u001B[0m\u001B[0;34m,\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[1;32m    646\u001B[0m                     self._unassigned_input)\n",
+      "\u001B[0;31mLoggedError\u001B[0m: Could not find anything to use input parameter(s) {'num_massive_neutrinos'}."
      ]
     }
    ],

diff --git a/soliket/tests/test_clusters.py b/soliket/tests/test_clusters.py
@@ -1,6 +1,9 @@
 import numpy as np
+import pytest
 from cobaya.model import get_model
 
+pytestmark = pytest.mark.require_ccl
+
 clusters_like_and_theory = {
     "likelihood": {"soliket.ClusterLikelihood": {"stop_at_error": True}},
     "theory": {
@@ -20,15 +23,13 @@
 
 
 def test_clusters_model(evaluate_one_info, test_cosmology_params):
-
     evaluate_one_info["params"] = test_cosmology_params
     evaluate_one_info.update(clusters_like_and_theory)
 
-    model_fiducial = get_model(evaluate_one_info) # noqa F841
+    model_fiducial = get_model(evaluate_one_info)  # noqa F841
 
 
 def test_clusters_loglike(evaluate_one_info, test_cosmology_params):
-
     evaluate_one_info["params"] = test_cosmology_params
     evaluate_one_info.update(clusters_like_and_theory)
 
@@ -40,7 +41,6 @@ def test_clusters_loglike(evaluate_one_info, test_cosmology_params):
 
 
 def test_clusters_n_expected(evaluate_one_info, test_cosmology_params):
-
     evaluate_one_info["params"] = test_cosmology_params
     evaluate_one_info.update(clusters_like_and_theory)