Merge pull request #10 from LSSTDESC/issue/4/update-unit-tests-for-py311

Fixing up unit tests

.gitignore

@@ -23,3 +23,4 @@ __pycache__/
 
 auxiliary_files/cosmo
 auxiliary_files/cosmo.hpp
+.DS_Store

resspect/cosmo_metric_utils.py

@@ -83,10 +83,10 @@ def fish_deriv_m(redshift, model, step, screen=False):
          at given redshifts.
     """
 
-    Ob0=0.022
-    Om0=model[1]
-    Ode0 =model[2]
-    cosmo = w0waCDM(model[0], Ob0, Om0, Ode0, model[3],model[4], name="w0waCDM")
+    Ob0 = 0.022
+    Om0 = model[1]
+    Ode0 = model[2]
+    cosmo = w0waCDM(H0=model[0], Ob0=Ob0, Om0=Om0, Ode0=Ode0, w0=model[3], wa=model[4], name="w0waCDM")
 
     cosmo=assign_cosmo(cosmo, model)
 

tests/conftest.py

@@ -12,6 +12,10 @@
 def test_data_path():
     return Path(__file__).parent.parent / "data" / "tests"
 
+@pytest.fixture
+def test_des_data_path():
+    return Path(__file__).parent.parent / "data" / "tests" / "DES_data"
+
 
 @pytest.fixture(scope="session")
 def base_temp(tmp_path_factory):

tests/test_batch_functions.py

@@ -3,13 +3,15 @@
 import numpy as np
 
 
-@pytest.mark.skip(reason='Test failing with numpy.AxisError - Check inputs')
 def test_entropy_from_probs_b_M_C():
 
     from resspect import batch_functions
 
     np.random.seed(42)
-    x = np.random.rand(100)
+    num_data_points = 3
+    committee_size = 10
+    num_classes = 5
+    x = np.random.rand(num_data_points, committee_size, num_classes)
 
     foo = batch_functions.entropy_from_probs_b_M_C(x)
 

tests/test_learn_loop.py

@@ -1,33 +1,28 @@
-
+import os
 import pytest
-
-
-# ToDo @emilleishida - Check this test later
-@pytest.mark.skip("Test failing for now")
-def test_can_run_learn_loop(extract_feature):
-    """Just a sanity test"""
-
-    from resspect.learn_loop import learn_loop
-
-    learn_loop(nloops=1,
-               features_method="bazin",
-               strategy="RandomSampling",
-               path_to_features=extract_feature,
-               output_metrics_file="just_a_name.csv",
-               output_queried_file="just_other_name.csv")
-
-
-@pytest.fixture(scope="function")
-def extract_feature(path_to_test_data):
-    from resspect import fit_snpcc
-
-    path_to_data_dir = path_to_test_data
-    output_file = 'output_file.dat'
-
-    fit_snpcc(path_to_data_dir=path_to_data_dir, features_file=output_file)
-
-    return output_file
-
+import tempfile
+
+from resspect import fit_snpcc
+from resspect.learn_loop import learn_loop
+
+def test_can_run_learn_loop(test_des_data_path):
+    """Test that learn_loop can load data and run."""
+    with tempfile.TemporaryDirectory() as dir_name:
+        # Create the feature files to use for the learning loop.
+        output_file = os.path.join(dir_name, "output_file.dat")
+        fit_snpcc(
+            path_to_data_dir=test_des_data_path,
+            features_file=output_file,
+        )
+
+        learn_loop(
+            nloops=1,
+            features_method="bazin",
+            strategy="RandomSampling",
+            path_to_features=output_file,
+            output_metrics_file=os.path.join(dir_name,"just_a_name.csv"),
+            output_queried_file=os.path.join(dir_name,"just_other_name.csv"),
+        )
 
 if __name__ == '__main__':
     pytest.main()