More testing of CosmoSIS module

examples/des_y1_3x2pt/numcosmo_run.py

@@ -14,7 +14,7 @@
 
 Ncm.cfg_init()
 
-with open(r"numcosmo_firecrown_model.yml", "r", encoding="utf8") as modelfile:
+with open(r"numcosmo_firecrown_model.yml", "r", encoding="utf-8") as modelfile:
     ncmodel = yaml.load(modelfile, Loader=yaml.Loader)
 
 NcFirecrown = define_numcosmo_model(ncmodel)

examples/des_y1_3x2pt/numcosmo_run_PT.py

@@ -15,7 +15,7 @@
 
 Ncm.cfg_init()
 
-with open(r"numcosmo_firecrown_model_PT.yml", "r", encoding="utf8") as modelfile:
+with open(r"numcosmo_firecrown_model_PT.yml", "r", encoding="utf-8") as modelfile:
     ncmodel = yaml.load(modelfile, Loader=yaml.Loader)
 
 NcFirecrownPT = define_numcosmo_model(ncmodel)

examples/srd_sn/numcosmo_run.py

@@ -21,7 +21,7 @@
 
 Ncm.cfg_init()
 
-with open(r"numcosmo_firecrown_model_snia.yml", "r", encoding="utf8") as modelfile:
+with open(r"numcosmo_firecrown_model_snia.yml", "r", encoding="utf-8") as modelfile:
     ncmodel = yaml.load(modelfile, Loader=yaml.Loader)
 
 NcFirecrownSNIa = define_numcosmo_model(ncmodel)

firecrown/connector/cosmosis/likelihood.py

@@ -13,7 +13,9 @@
 from cosmosis.datablock import option_section
 from cosmosis.datablock import names as section_names
 import pyccl as ccl
+
 from firecrown.connector.mapping import mapping_builder, MappingCosmoSIS
+from firecrown.likelihood.gauss_family.gauss_family import GaussFamily
 from firecrown.likelihood.gauss_family.statistic.two_point import TwoPoint
 from firecrown.likelihood.likelihood import load_likelihood, Likelihood, NamedParameters
 from firecrown.parameters import ParamsMap
@@ -105,16 +107,19 @@ def execute(self, sample: cosmosis.datablock) -> int:
         self.tools.reset()
 
         # Save concatenated data vector and inverse covariance to enable support
-        # for the CosmoSIS fisher sampler.
-        sample.put(
-            "data_vector", "firecrown_theory", self.likelihood.predicted_data_vector
-        )
-        sample.put(
-            "data_vector", "firecrown_data", self.likelihood.measured_data_vector
-        )
-        sample.put(
-            "data_vector", "firecrown_inverse_covariance", self.likelihood.inv_cov
-        )
+        # for the CosmoSIS Fisher sampler. This can only work for likelihoods
+        # that have these quantities. Currently, this is only GaussFamily.
+
+        if isinstance(self.likelihood, GaussFamily):
+            sample.put(
+                "data_vector", "firecrown_theory", self.likelihood.predicted_data_vector
+            )
+            sample.put(
+                "data_vector", "firecrown_data", self.likelihood.measured_data_vector
+            )
+            sample.put(
+                "data_vector", "firecrown_inverse_covariance", self.likelihood.inv_cov
+            )
 
         # Write out theory and data vectors to the data block the ease
         # debugging.

tests/connector/cosmosis/test_cosmosis_module.py

@@ -3,11 +3,14 @@
 As a unit test, what this can test is very limited.
 This test do not invoke the `cosmosis` executable.
 """
-
-
-from cosmosis.datablock import DataBlock
+from os.path import expandvars
+import yaml
 import pytest
-from firecrown.connector.cosmosis.likelihood import FirecrownLikelihood
+import numpy as np
+from cosmosis.datablock import DataBlock, option_section, names as section_names
+
+from firecrown.likelihood.likelihood import NamedParameters
+from firecrown.connector.cosmosis.likelihood import FirecrownLikelihood, extract_section
 
 
 @pytest.fixture(name="minimal_module_config")
@@ -17,7 +20,7 @@ def fixture_minimal_module_config() -> DataBlock:
     This is the minimal possible configuration."""
     block = DataBlock()
     block.put_string(
-        "module_options", "likelihood_source", "tests/likelihood/lkdir/lkscript.py"
+        option_section, "likelihood_source", "tests/likelihood/lkdir/lkscript.py"
     )
     return block
 
@@ -28,13 +31,92 @@ def fixture_defective_module_config() -> DataBlock:
     parameter to configure a ParameterizedLikelihood."""
     block = DataBlock()
     block.put_string(
-        "module_options",
+        option_section,
         "likelihood_source",
-        "tests/likelihood/lkdir/lk_needing_param.py",
+        expandvars("${FIRECROWN_DIR}/tests/likelihood/lkdir/lk_needing_param.py"),
     )
     return block
 
 
+@pytest.fixture(name="minimal_config")
+def fixture_minimal_config() -> DataBlock:
+    result = DataBlock()
+    result.put_string(
+        option_section,
+        "likelihood_source",
+        expandvars("${FIRECROWN_DIR}/tests/likelihood/lkdir/lkscript.py"),
+    )
+    return result
+
+
+@pytest.fixture(name="config_with_derived_parameters")
+def fixture_config_with_derived_parameters() -> DataBlock:
+    result = DataBlock()
+    result.put_string(
+        option_section,
+        "Likelihood_source",
+        expandvars(
+            "${FIRECROWN_DIR}/tests/likelihood/lkdir" "/lk_derived_parameter.py"
+        ),
+    )
+    result.put_double("sample_parameters_sections", "derived_param0", 12.5)
+    return result
+
+
+@pytest.fixture(name="minimal_firecrown_mod")
+def fixture_minimal_firecrown_mod(minimal_config: DataBlock) -> FirecrownLikelihood:
+    return FirecrownLikelihood(minimal_config)
+
+
+@pytest.fixture(name="firecrown_mod_with_derived_parameters")
+def fixture_firecrown_mod_with_derived_parameters(
+    config_with_derived_parameters: DataBlock,
+) -> FirecrownLikelihood:
+    return FirecrownLikelihood(config_with_derived_parameters)
+
+
+@pytest.fixture(name="sample_with_cosmo")
+def fixture_sample_with_cosmo() -> DataBlock:
+    """Return a DataBlock that contains some cosmological parameters."""
+    result = DataBlock()
+    params = {
+        "h0": 0.83,
+        "omega_b": 0.22,
+        "omega_c": 0.120,
+        "omega_k": 0.0,
+        "omega_nu": 0.0,
+        "w": -1.0,
+        "wa": 0.0,
+    }
+    for name, val in params.items():
+        result.put_double("cosmological_parameters", name, val)
+    return result
+
+
+@pytest.fixture(name="minimal_sample")
+def fixture_minimal_sample(sample_with_cosmo: DataBlock) -> DataBlock:
+    with open("tests/distances.yml", encoding="utf-8") as stream:
+        rawdata = yaml.load(stream, yaml.CLoader)
+    sample = sample_with_cosmo
+    for section_name, section_data in rawdata.items():
+        for parameter_name, value in section_data.items():
+            sample.put(section_name, parameter_name, np.array(value))
+    return sample
+
+
+def test_extract_section_gets_named_parameters(defective_module_config: DataBlock):
+    params = extract_section(defective_module_config, "module_options")
+    assert isinstance(params, NamedParameters)
+    assert params.get_string("likelihood_source") == expandvars(
+        "${FIRECROWN_DIR}/tests/likelihood/lkdir/lk_needing_param.py"
+    )
+
+
+def test_extract_section_raises_on_missing_section(defective_module_config: DataBlock):
+    with pytest.raises(RuntimeError, match="Datablock section `xxx' does not exist"):
+        _ = extract_section(defective_module_config, "xxx")
+
+
 def test_parameterless_module_construction(minimal_module_config):
     """Make sure we can create a CosmoSIS likelihood modules that does not
     introduce any new parameters."""
@@ -47,3 +129,33 @@ def test_missing_required_parameter(defective_module_config):
     failure."""
     with pytest.raises(KeyError):
         _ = FirecrownLikelihood(defective_module_config)
+
+
+def test_initialize_minimal_module(minimal_firecrown_mod: FirecrownLikelihood):
+    assert isinstance(minimal_firecrown_mod, FirecrownLikelihood)
+
+
+def test_execute_missing_cosmological_parameters(
+    minimal_firecrown_mod: FirecrownLikelihood,
+):
+    no_cosmo_params = DataBlock()
+    with pytest.raises(
+        RuntimeError,
+        match="Datablock section " "`cosmological_parameters' does " "not exist.",
+    ):
+        _ = minimal_firecrown_mod.execute(no_cosmo_params)
+
+
+def test_execute_with_cosmo(
+    minimal_firecrown_mod: FirecrownLikelihood, minimal_sample: DataBlock
+):
+    assert minimal_firecrown_mod.execute(minimal_sample) == 0
+    assert minimal_sample[section_names.likelihoods, "firecrown_like"] == -3.0
+
+
+def test_execute_with_derived_parameters(
+    firecrown_mod_with_derived_parameters: FirecrownLikelihood,
+    minimal_sample: DataBlock,
+):
+    assert firecrown_mod_with_derived_parameters.execute(minimal_sample) == 0
+    assert minimal_sample.get_double("derived_section", "derived_param0") == 1.0

tests/connector/numcosmo/test_numcosmo_model.py

@@ -42,12 +42,12 @@ def test_model_save_load(tmp_path, nc_model):
     """Test saving and loading a NumCosmo model."""
 
     with open(
-        tmp_path / r"numcosmo_firecrown_model.yml", "w", encoding="utf8"
+        tmp_path / r"numcosmo_firecrown_model.yml", "w", encoding="utf-8"
     ) as modelfile:
         yaml.dump(nc_model, modelfile, Dumper=yaml.Dumper)
 
     with open(
-        tmp_path / r"numcosmo_firecrown_model.yml", "r", encoding="utf8"
+        tmp_path / r"numcosmo_firecrown_model.yml", "r", encoding="utf-8"
     ) as modelfile:
         model_copy = yaml.load(modelfile, Loader=yaml.Loader)
 

tests/distances.yml

@@ -0,0 +1,4 @@
+distances:
+  d_m: [0.0, 30.599016773238837, 61.164969838209146, 91.69730457953247, 122.19546576621251, 152.65889770161618, 183.08704437377514, 213.47934960593844, 243.83525720727596, 274.1542111236613, 304.43565558844614, 334.67903527312603, 364.8837954378314, 395.04938208154766, 425.17524209196944, 455.26082339491893, 485.30557510322814, 515.3089476650088, 545.2703930112107, 575.1893647023988, 605.0653180746485, 634.8977103844911, 664.6860009528034, 694.4296513075827, 724.1281253255095, 753.780889372219, 783.3874124412047, 812.9471662912787, 842.4596255824987, 871.9242680104995, 901.3405744391514, 930.7080290314592, 960.0261193786538, 989.2943366273881, 1018.512175604976, 1047.6791349426137, 1076.7947171965068, 1105.8584289668547, 1134.8697810146282, 1163.8282883760776, 1192.7334704749217, 1221.5848512321663, 1250.381959173494, 1279.124327534182, 1307.811494361507, 1336.4430026145776, 1365.0184002615756, 1393.5372403743443, 1421.9990812203082, 1450.4034863516767, 1478.7500246919053, 1507.0382706193889, 1535.26780404836, 1563.4382105069606, 1591.549081212481, 1619.600013143741, 1647.5906091105878, 1675.52047782052, 1703.389233942409, 1731.1964981673086, 1758.9418972663686, 1786.6250641458269, 1814.2456378990812, 1841.8032638558682, 1869.297593628516, 1896.7282851553073, 1924.095002740947, 1951.3974170941488, 1978.6352053623566, 2005.808051163614, 2032.9156446155973, 2059.957682361837, 2086.9338675951485, 2113.843910078286, 2140.6875261618634, 2167.4644387995504, 2194.1743775605864, 2220.81707863964, 2247.3922848640364, 2273.8997456984016, 2300.339217246755, 2326.7104622520724, 2353.013250093383, 2379.247356780422, 2405.4125649458747, 2431.5086638352805, 2457.535449294613, 2483.492723755584, 2509.3802962187356, 2535.1979822343474, 2560.945603881203, 2586.622989743288, 2612.2299748844357, 2637.766400820986, 2663.2321154925203, 2688.6269732306846, 2713.9508347261917, 2739.203566994024, 2764.385043336902, 2789.495143307066]
+  h: [0.0003299327135551882, 0.00033028642429886265, 0.00033064689311028655, 0.0003310141692726998, 0.0003313883014348929, 0.00033176933760470134, 0.0003321573251426722, 0.00033255231075590697, 0.0003329543404920849, 0.0003333634597336719, 0.000333779713192319, 0.00033420314490345386, 0.00033463379822107017, 0.0003350717158127181, 0.0003355169396546992, 0.00033596951102746967, 0.0003364294705112553, 0.00033689685798188004, 0.00033737171260681264, 0.0003378540728414326, 0.000338343976425519, 0.0003388414603799634, 0.00033934656100371036, 0.00033985931387092586, 0.0003403797538283965, 0.0003409079149931599, 0.00034144383075036957, 0.00034198753375139245, 0.0003425390559121421, 0.00034309842841164797, 0.0003436656816908607, 0.0003442408454516933, 0.0003448239486562996, 0.0003454150195265885, 0.00034601408554397507, 0.00034662117344936585, 0.00034723630924338015, 0.0003478595181868038, 0.0003484908248012773, 0.0003491302528702132, 0.00034977782543994503, 0.0003504335648211034, 0.0003510974925902181, 0.0003517696295915456, 0.00035244999593911667, 0.00035313861101900494, 0.00035383549349181175, 0.0003545406612953651, 0.00035525413164763013, 0.0003559759210498276, 0.0003567060452897582, 0.0003574445194453269, 0.0003581913578882677, 0.00035894657428806097, 0.00035971018161604334, 0.000360482192149704, 0.0003612626174771633, 0.0003620514685018326, 0.00036284875544724657, 0.00036365448786206757, 0.00036446867462525617, 0.0003652913239514028, 0.00036612244339621805, 0.0003669620398621739, 0.00036781011960429515, 0.0003686666882360922, 0.00036953175073563445, 0.00037040531145175553, 0.00037128737411038935, 0.00037217794182102905, 0.0003730770170833059, 0.0003739846017936815, 0.000374900697252251, 0.0003758253041696485, 0.00037675842267405384, 0.0003777000523182926, 0.0003786501920870262, 0.0003796088404040263, 0.00038057599513952853, 0.0003815516536176613, 0.00038253581262394495, 0.0003835284684128543, 0.00038452961671544254, 0.0003855392527470207, 0.00038655737121488646, 0.0003875839663260999, 0.0003886190317953005, 0.0003896625608525598, 0.000390714546251268, 0.0003917749802760464, 0.00039284385475068433, 0.0003939211610460946, 0.00039500689008828416, 0.00039610103236633395, 0.0003972035779403871, 0.00039831451644963803, 0.00039943383712032053, 0.00040056152877369016, 0.0004016975798339982, 0.0004028419783364516]
+  z: [0.0, 0.010101010101010102, 0.020202020202020204, 0.030303030303030304, 0.04040404040404041, 0.05050505050505051, 0.06060606060606061, 0.07070707070707072, 0.08080808080808081, 0.09090909090909091, 0.10101010101010102, 0.11111111111111112, 0.12121212121212122, 0.13131313131313133, 0.14141414141414144, 0.15151515151515152, 0.16161616161616163, 0.17171717171717174, 0.18181818181818182, 0.19191919191919193, 0.20202020202020204, 0.21212121212121213, 0.22222222222222224, 0.23232323232323235, 0.24242424242424243, 0.25252525252525254, 0.26262626262626265, 0.27272727272727276, 0.2828282828282829, 0.29292929292929293, 0.30303030303030304, 0.31313131313131315, 0.32323232323232326, 0.33333333333333337, 0.3434343434343435, 0.3535353535353536, 0.36363636363636365, 0.37373737373737376, 0.38383838383838387, 0.393939393939394, 0.4040404040404041, 0.4141414141414142, 0.42424242424242425, 0.43434343434343436, 0.4444444444444445, 0.4545454545454546, 0.4646464646464647, 0.4747474747474748, 0.48484848484848486, 0.494949494949495, 0.5050505050505051, 0.5151515151515152, 0.5252525252525253, 0.5353535353535354, 0.5454545454545455, 0.5555555555555556, 0.5656565656565657, 0.5757575757575758, 0.5858585858585859, 0.595959595959596, 0.6060606060606061, 0.6161616161616162, 0.6262626262626263, 0.6363636363636365, 0.6464646464646465, 0.6565656565656566, 0.6666666666666667, 0.6767676767676768, 0.686868686868687, 0.696969696969697, 0.7070707070707072, 0.7171717171717172, 0.7272727272727273, 0.7373737373737375, 0.7474747474747475, 0.7575757575757577, 0.7676767676767677, 0.7777777777777778, 0.787878787878788, 0.797979797979798, 0.8080808080808082, 0.8181818181818182, 0.8282828282828284, 0.8383838383838385, 0.8484848484848485, 0.8585858585858587, 0.8686868686868687, 0.8787878787878789, 0.888888888888889, 0.8989898989898991, 0.9090909090909092, 0.9191919191919192, 0.9292929292929294, 0.9393939393939394, 0.9494949494949496, 0.9595959595959597, 0.9696969696969697, 0.9797979797979799, 0.98989898989899, 1.0]