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""" |
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Functions for reading different Models type objects with Gammapy |
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objects. |
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""" |
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import xmltodict |
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from gammapy.maps import Map |
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from gammapy.modeling.models import ( |
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SPATIAL_MODEL_REGISTRY, |
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SPECTRAL_MODEL_REGISTRY, |
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EBLAbsorptionNormSpectralModel, |
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SkyModel, |
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create_fermi_isotropic_diffuse_model, |
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) |
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from asgardpy.data.target import read_models_from_asgardpy_config |
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from asgardpy.gammapy.interoperate_models import ( |
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get_gammapy_spectral_model, |
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xml_spatial_model_to_gammapy, |
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xml_spectral_model_to_gammapy, |
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) |
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__all__ = [ |
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"create_gal_diffuse_skymodel", |
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"create_iso_diffuse_skymodel", |
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"create_source_skymodel", |
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"read_fermi_xml_models_list", |
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"update_aux_info_from_fermi_xml", |
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] |
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def read_fermi_xml_models_list( |
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list_source_models, dl3_aux_path, xml_file, diffuse_models, asgardpy_target_config=None |
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): |
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""" |
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Read from the Fermi-XML file to enlist the various objects and get their |
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SkyModels. |
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Parameters |
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---------- |
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list_source_models: list |
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List of source models to be filled. |
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dl3_aux_path: str |
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Path location of the DL3 auxiliary files for reading Spatial Models |
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from separate files. |
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xml_file: str |
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Path of the Fermi-XML file to be read. |
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diffuse_models: dict |
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Dict containing diffuse models' filenames and instrument key. |
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asgardpy_target_config: `AsgardpyConfig` |
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Config section containing the Target source information. |
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Returns |
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------- |
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list_source_models: list |
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List of filled source models. |
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diffuse_models: dict |
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Dict containing diffuse models objects replacing the filenames. |
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""" |
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with open(xml_file, encoding="utf-8") as file: |
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xml_data = xmltodict.parse(file.read())["source_library"]["source"] |
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is_target_source = False |
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for source_info in xml_data: |
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match source_info["@name"]: |
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# Nomenclature as per enrico and fermipy |
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case "IsoDiffModel" | "isodiff": |
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diffuse_models["iso_diffuse"] = create_iso_diffuse_skymodel( |
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diffuse_models["iso_diffuse"], diffuse_models["key_name"] |
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) |
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source_info = diffuse_models["iso_diffuse"] |
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case "GalDiffModel" | "galdiff": |
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diffuse_models["gal_diffuse"], diffuse_models["gal_diffuse_map"] = create_gal_diffuse_skymodel( |
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diffuse_models["gal_diffuse"] |
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) |
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source_info = diffuse_models["gal_diffuse"] |
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case _: |
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source_info, is_target_source = create_source_skymodel( |
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source_info, |
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dl3_aux_path, |
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base_model_type="Fermi-XML", |
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asgardpy_target_config=asgardpy_target_config, |
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) |
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if is_target_source: |
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list_source_models.insert(0, source_info) |
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is_target_source = False # To not let it repeat |
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else: |
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list_source_models.append(source_info) |
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return list_source_models, diffuse_models |
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def update_aux_info_from_fermi_xml( |
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diffuse_models_file_names_dict, xml_file, fetch_iso_diff=False, fetch_gal_diff=False |
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): |
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""" |
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When no glob_search patterns on axuillary files are provided, fetch |
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them from the XML file and update the dict containing diffuse models' file |
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names. |
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Parameters |
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---------- |
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diffuse_models_file_names_dict: `dict` |
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Dict containing the information on the DL3 files input. |
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xml_file: str |
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Path of the Fermi-XML file to be read. |
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fetch_iso_diff: bool |
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Boolean to get the information of the Isotropic diffuse model from the |
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Fermi-XML file |
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fetch_gal_diff: bool |
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Boolean to get the information of the Galactic diffuse model from the |
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Fermi-XML file |
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Returns |
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------- |
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diffuse_models_file_names_dict: `dict` |
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Dict containing the updated information on the DL3 files input. |
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""" |
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with open(xml_file) as file: |
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data = xmltodict.parse(file.read())["source_library"]["source"] |
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for source in data: |
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match source["@name"]: |
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case "IsoDiffModel" | "isodiff": |
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if fetch_iso_diff: |
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file_path = source["spectrum"]["@file"] |
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file_name = file_path.split("/")[-1] |
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diffuse_models_file_names_dict["iso_diffuse"] = file_name |
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case "GalDiffModel" | "galdiff": |
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if fetch_gal_diff: |
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file_path = source["spatialModel"]["@file"] |
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file_name = file_path.split("/")[-1] |
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diffuse_models_file_names_dict["gal_diffuse"] = file_name |
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return diffuse_models_file_names_dict |
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def get_target_model_from_config(source_name, asgardpy_target_config): |
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""" """ |
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spectral_model = None |
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is_source_target = False |
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# If Target source model's spectral component is to be taken from Config |
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# and not from 3D dataset. |
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if asgardpy_target_config: |
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source_name_check = source_name.replace("_", "").replace(" ", "") |
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target_check = asgardpy_target_config.source_name.replace("_", "").replace(" ", "") |
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if source_name_check == target_check: |
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source_name = asgardpy_target_config.source_name |
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is_source_target = True |
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# Only taking the spectral model information right now. |
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if not asgardpy_target_config.from_3d: |
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models_ = read_models_from_asgardpy_config(asgardpy_target_config) |
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spectral_model = models_[0].spectral_model |
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return source_name, spectral_model, is_source_target |
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def add_ebl_model_from_config(spectral_model, asgardpy_target_config=None, is_source_target=False): |
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""" """ |
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# Only of Asgardpy config is provided |
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if asgardpy_target_config: |
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config_spectral = asgardpy_target_config.components[0].spectral |
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ebl_absorption_included = config_spectral.ebl_abs.reference != "" |
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if is_source_target and ebl_absorption_included: |
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ebl_model = config_spectral.ebl_abs |
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if ebl_model.filename.is_file(): |
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ebl_spectral_model = EBLAbsorptionNormSpectralModel.read( |
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str(ebl_model.filename), redshift=ebl_model.redshift |
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) |
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ebl_model.reference = ebl_model.filename.name[:-8].replace("-", "_") |
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else: |
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ebl_spectral_model = EBLAbsorptionNormSpectralModel.read_builtin( |
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ebl_model.reference, redshift=ebl_model.redshift |
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) |
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spectral_model = spectral_model * ebl_spectral_model |
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return spectral_model |
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def create_source_skymodel(source_info, dl3_aux_path, base_model_type="Fermi-XML", asgardpy_target_config=None): |
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""" |
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Build SkyModels from given base model information. |
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If AsgardpyConfig section of the target is provided for the target |
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source information, it will be used to check if the target `source_name` |
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is provided in the base_model file. If it exists, then check if the model |
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information is to be read from AsgardpyConfig using `from_3d` boolean value. |
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Also, if EBL model information is provided in the AsgardpyConfig, it will |
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be added to the SkyModel object. |
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Parameters |
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---------- |
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source_info: dict |
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Dictionary containing the source models information from XML file. |
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dl3_aux_path: str |
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Path location of the DL3 auxiliary files for reading Spatial Models |
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from separate files. |
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base_model_type: str |
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Name indicating the model format used to read the skymodels from. |
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asgardpy_target_config: `AsgardpyConfig` |
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Config section containing the Target source information. |
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Returns |
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------- |
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source_sky_model: `gammapy.modeling.SkyModel` |
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SkyModels object for the given source information. |
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is_source_target: bool |
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Boolean to check if the Models belong to the target source. |
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""" |
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if base_model_type == "Fermi-XML": |
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source_name = source_info["@name"] |
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spectrum_type = source_info["spectrum"]["@type"] |
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spectrum_params = source_info["spectrum"]["parameter"] |
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# initialized to check for the case if target spectral model information |
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# is to be taken from the Config |
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spectral_model = None |
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# Check if target_source file exists |
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is_source_target = False |
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ebl_atten = False |
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source_name, spectral_model, is_source_target = get_target_model_from_config( |
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source_name, asgardpy_target_config |
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) |
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if spectral_model is None: |
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# Define the Spectral Model type for Gammapy |
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spectral_model, ebl_atten = get_gammapy_spectral_model( |
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spectrum_type, |
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ebl_atten, |
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base_model_type, |
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) |
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spectrum_type = spectrum_type.split("EblAtten::")[-1] |
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# Read the parameter values from XML file to create SpectralModel |
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params_list = xml_spectral_model_to_gammapy( |
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spectrum_params, |
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spectrum_type, |
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is_target=is_source_target, |
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keep_sign=ebl_atten, |
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base_model_type=base_model_type, |
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) |
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for param_ in params_list: |
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setattr(spectral_model, param_.name, param_) |
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spectral_model = add_ebl_model_from_config(spectral_model, asgardpy_target_config, is_source_target) |
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# Reading Spatial model from the XML file |
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spatial_model = xml_spatial_model_to_gammapy(dl3_aux_path, source_info["spatialModel"], base_model_type) |
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spatial_model.freeze() |
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source_sky_model = SkyModel( |
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spectral_model=spectral_model, |
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spatial_model=spatial_model, |
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name=source_name, |
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) |
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return source_sky_model, is_source_target |
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def create_iso_diffuse_skymodel(iso_file, key_name): |
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""" |
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Create a SkyModel of the Fermi Isotropic Diffuse Model and assigning |
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name as per the observation key. If there are no distinct key types of |
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files, the value is None. |
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Parameters |
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---------- |
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iso_file: str |
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Path to the isotropic diffuse model file |
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key: str |
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Instrument key-name, if exists |
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Returns |
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------- |
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diff_iso: `gammapy.modeling.SkyModel` |
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SkyModel object of the isotropic diffuse model. |
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""" |
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diff_iso = create_fermi_isotropic_diffuse_model(filename=iso_file, interp_kwargs={"fill_value": None}) |
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if key_name: |
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diff_iso._name = f"{diff_iso.name}-{key_name}" |
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# Parameters' limits |
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diff_iso.spectral_model.model1.parameters[0].min = 0.001 |
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diff_iso.spectral_model.model1.parameters[0].max = 10 |
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diff_iso.spectral_model.model2.parameters[0].min = 0 |
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diff_iso.spectral_model.model2.parameters[0].max = 10 |
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return diff_iso |
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def create_gal_diffuse_skymodel(diff_gal_file): |
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""" |
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Create SkyModel of the Diffuse Galactic sources either by reading a file or |
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by using a provided Map object. |
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|
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Parameters |
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---------- |
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diff_gal_file: Path, `gammapy.maps.Map` |
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Path to the isotropic diffuse model file, or a Map object already read |
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from a file. |
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|
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Returns |
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------- |
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model: `gammapy.modeling.SkyModel` |
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SkyModel object read from a given galactic diffuse model file. |
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diff_gal: `gammapy.maps.Map` |
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Map object of the galactic diffuse model |
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""" |
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if not isinstance(diff_gal_file, Map): |
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# assuming it is Path or str type |
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diff_gal_filename = diff_gal_file |
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diff_gal = Map.read(diff_gal_file) |
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diff_gal.meta["filename"] = diff_gal_filename |
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else: |
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diff_gal = diff_gal_file |
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|
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template_diffuse = SPATIAL_MODEL_REGISTRY.get_cls("TemplateSpatialModel")( |
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diff_gal, normalize=False, filename=diff_gal.meta["filename"] |
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) |
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model = SkyModel( |
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spectral_model=SPECTRAL_MODEL_REGISTRY.get_cls("PowerLawNormSpectralModel")(), |
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spatial_model=template_diffuse, |
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name="diffuse-iem", |
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) |
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model.parameters["norm"].min = 0 |
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model.parameters["norm"].max = 10 |
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model.parameters["norm"].frozen = False |
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|
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return model, diff_gal |
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