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import pytest |
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from asgardpy.config import AsgardpyConfig |
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def test_config_basic(): |
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"""Test on basic Config features.""" |
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config = AsgardpyConfig() |
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assert "AsgardpyConfig\n\n" in str(config) |
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assert "AsgardpyConfig(general" in repr(config) |
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config_str_0 = """ |
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general: |
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n_jobs: 100 |
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""" |
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config_100 = AsgardpyConfig.from_yaml(config_str_0) |
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assert config_100.general.n_jobs == 100 |
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with pytest.raises(ValueError): |
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config_str_1 = """ |
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fit_params: |
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fit_range: |
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min: 10 s |
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max: 10 TeV |
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""" |
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AsgardpyConfig.from_yaml(config_str_1) |
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with pytest.raises(ValueError): |
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config_str_2 = """ |
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general: |
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outdir: ./bla/ |
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""" |
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AsgardpyConfig.from_yaml(config_str_2) |
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with pytest.raises(ValueError): |
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config_str_3 = """ |
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target: |
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sky_position: |
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lon: 30 TeV |
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""" |
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AsgardpyConfig.from_yaml(config_str_3) |
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def test_config_time(): |
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"""Test for reading Time inputs.""" |
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from pydantic import ValidationError |
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config = AsgardpyConfig() |
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with pytest.raises(ValidationError): |
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config.dataset1d.instruments[0].dataset_info.observation.obs_time = [ |
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{"format": "abc", "start": "2000-01-01", "stop": "2001-01-01"} |
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] |
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with pytest.raises(ValueError): |
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config.dataset1d.instruments[0].dataset_info.observation.obs_time = [ |
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{"format": "iso", "start": "60000", "stop": "2001-01-01"} |
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] |
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with pytest.raises(ValueError): |
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config.dataset1d.instruments[0].dataset_info.observation.obs_time = [ |
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{"format": "iso", "start": "2001-01-01", "stop": "60000"} |
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] |
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def test_get_model_template(): |
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"""Test for reading a model template by a given tag.""" |
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from asgardpy.config.operations import get_model_template |
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new_model = get_model_template("eclp") |
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new_config = AsgardpyConfig.read(new_model) |
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assert new_config.target.components[0].spectral.type == "ExpCutoffLogParabolaSpectralModel" |
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with pytest.raises(IOError): |
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new_config.write(new_model, overwrite=False) |
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def test_create_config_from_dict(): |
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"""Test to create AsgardpyConfig from a simple dict.""" |
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gen_dict = {"general": {"log": {"level": "warning"}}} |
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config = AsgardpyConfig(**gen_dict) |
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assert config.general.log.level == "warning" |
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def test_config_update_gammapy(gammapy_data_path, base_config_1d): |
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"""Tests to update target model config from Gammapy-based YAML files.""" |
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import os |
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from asgardpy.config.generator import gammapy_model_to_asgardpy_model_config |
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main_config = AsgardpyConfig() |
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other_config_path = f"{gammapy_data_path}fermi-3fhl-crab/Fermi-LAT-3FHL_models.yaml" |
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other_config_path_2 = f"{gammapy_data_path}estimators/pks2155_hess_lc/models.yaml" |
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other_config_1 = gammapy_model_to_asgardpy_model_config( |
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other_config_path, |
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recursive_merge=False, |
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) |
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other_config_2 = gammapy_model_to_asgardpy_model_config( |
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other_config_path, |
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base_config_1d, |
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recursive_merge=False, |
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) |
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main_config.write("test_base_config.yaml", overwrite=True) |
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other_config_3 = gammapy_model_to_asgardpy_model_config( |
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other_config_path_2, |
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"test_base_config.yaml", |
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recursive_merge=False, |
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) |
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main_config_1 = main_config.update(other_config_1) |
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main_config_2 = base_config_1d.update(other_config_2) |
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main_config_3 = main_config.update(other_config_3) |
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new_spectral_model_name = main_config_1.target.components[0].spectral.type |
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new_spectral_model_name_2 = main_config_2.target.components[0].spectral.type |
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new_spectral_model_name_3 = main_config_3.target.components[0].spectral.type |
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index_max = main_config_3.target.components[0].spectral.parameters[0].max |
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assert new_spectral_model_name == "LogParabolaSpectralModel" |
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assert new_spectral_model_name_2 == "LogParabolaSpectralModel" |
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assert new_spectral_model_name_3 == "PowerLawSpectralModel" |
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assert index_max == 10.0 |
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os.remove("test_base_config.yaml") |
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def test_config_update(): |
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"""Tests to update target model config from other AsgardpyConfig file.""" |
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from asgardpy.config.operations import get_model_template |
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main_config = AsgardpyConfig() |
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spec_model_template_file_1 = get_model_template("bpl") |
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spec_model_template_file_2 = get_model_template("sbpl") |
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other_config_1 = AsgardpyConfig.read(spec_model_template_file_1) |
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other_config_2 = AsgardpyConfig.read(spec_model_template_file_2) |
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main_config = main_config.update(other_config_1) |
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new_spectral_model_name_1 = main_config.target.components[0].spectral.type |
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new_config_str = """ |
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general: |
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n_jobs: 100 |
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""" |
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main_config_2 = main_config.update(new_config_str) |
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main_config = main_config.update(other_config_2, merge_recursive=True) |
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new_spectral_model_name_2 = main_config.target.components[0].spectral.type |
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spectral_model_params = main_config.target.components[0].spectral.parameters |
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assert new_spectral_model_name_1 == "BrokenPowerLawSpectralModel" |
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assert main_config_2.general.n_jobs == 100 |
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with pytest.raises(TypeError): |
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main_config.update(5) |
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assert new_spectral_model_name_2 == "SmoothBrokenPowerLawSpectralModel" |
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assert len(spectral_model_params) == 6 |
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def test_write_model_config(): |
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"""From a Gammapy Models object, write it as an AsgardpyConfig file.""" |
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from gammapy.modeling.models import ( |
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ExpCutoffPowerLaw3FGLSpectralModel, |
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Models, |
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SkyModel, |
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) |
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from asgardpy.analysis import AsgardpyAnalysis |
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from asgardpy.config.generator import AsgardpyConfig, write_asgardpy_model_to_file |
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from asgardpy.config.operations import CONFIG_PATH, get_model_template |
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config_ = AsgardpyConfig() |
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analysis_ = AsgardpyAnalysis(config_) |
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model_ = SkyModel(name="Template", spectral_model=ExpCutoffPowerLaw3FGLSpectralModel()) |
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model_.spectral_model.index.value = 1.5 |
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analysis_.final_model = Models(model_) |
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assert get_model_template("ecpl-3fgl") |
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write_asgardpy_model_to_file( |
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gammapy_model=model_, |
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output_file=str(CONFIG_PATH) + "/model_templates/model_template_ecpl-3fgl.yaml", |
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) |
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with pytest.raises(TypeError): |
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write_asgardpy_model_to_file() |
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write_asgardpy_model_to_file( |
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gammapy_model=model_, |
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output_file=None, |
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) |
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