Telluric Models¶

Similarly to stellar templates, the telluric model is constructed through a manager that will handle the construction and data storage.

The construction of the telluric model follows a recipe:

1. Construct a transmittance model from a given source (by default, Telfit)
2. Find the wavelength regions in which the transmittance model is smaller than a given percentage of the continuum
3. Account for the BERV by either using the +- Maximum yearly variation or by shifting the mask to all BERVS in our dataset.

The following workflow summarizes the main steps in this process:

In [1]:

from pathlib import Path

from ASTRA.data_objects import DataClassManager
from ASTRA.data_objects.DataClass import DataClass
from ASTRA.Instruments import ESPRESSO
from ASTRA.template_creation.TelluricModel import TelluricModel
from ASTRA.utils.choices import TELLURIC_CREATION_MODE, TELLURIC_EXTENSION

storage_path = Path("../../tmp")
manager = DataClassManager()
manager.start()

data: DataClass = manager.DataClass(
    list(Path("/home/amiguel/spectra_collection/ESPRESSO/proxima").glob("*.fits")),
    storage_path=storage_path,
    instrument=ESPRESSO,
)

ModelTell = TelluricModel(
    usage_mode="individual",
    user_configs={
        "CREATION_MODE": TELLURIC_CREATION_MODE.telfit,
        "EXTENSION_MODE": TELLURIC_EXTENSION.LINES,
    },
    root_folder_path=storage_path,
)

ModelTell.Generate_Model(
    dataClass=data,
    telluric_configs={"continuum_percentage_drop": 1},
    force_computation=False,
    store_templates=True,
)

from pathlib import Path from ASTRA.data_objects import DataClassManager from ASTRA.data_objects.DataClass import DataClass from ASTRA.Instruments import ESPRESSO from ASTRA.template_creation.TelluricModel import TelluricModel from ASTRA.utils.choices import TELLURIC_CREATION_MODE, TELLURIC_EXTENSION storage_path = Path("../../tmp") manager = DataClassManager() manager.start() data: DataClass = manager.DataClass( list(Path("/home/amiguel/spectra_collection/ESPRESSO/proxima").glob("*.fits")), storage_path=storage_path, instrument=ESPRESSO, ) ModelTell = TelluricModel( usage_mode="individual", user_configs={ "CREATION_MODE": TELLURIC_CREATION_MODE.telfit, "EXTENSION_MODE": TELLURIC_EXTENSION.LINES, }, root_folder_path=storage_path, ) ModelTell.Generate_Model( dataClass=data, telluric_configs={"continuum_percentage_drop": 1}, force_computation=False, store_templates=True, )

After the model is constructed, we can remove the tellurics from all observations at once through

In [2]:

data.remove_telluric_features(ModelTell)

data.remove_telluric_features(ModelTell)

---

A posteriori masking of tellurics¶

ASTRA also allows you to add a telluric mask on top of a previously created stellar template

In [3]:

from pathlib import Path

from ASTRA.data_objects import DataClassManager
from ASTRA.data_objects.DataClass import DataClass
from ASTRA.Instruments import ESPRESSO
from ASTRA.template_creation.StellarModel import StellarModel

storage_path = Path("../../tmp")
manager = DataClassManager()
manager.start()

d: DataClass = manager.DataClass(
    list(Path("/home/amiguel/spectra_collection/ESPRESSO/proxima").glob("*.fits")),
    storage_path=storage_path,
    instrument=ESPRESSO,
)

stell = StellarModel(
    storage_path,
    user_configs={},
)
stell.Generate_Model(
    dataClass=d,
    template_configs={},
    force_computation=False,
)

stellar_template = stell.request_data(d.get_available_subInstruments()[0])
wave, flux, err, mask = stellar_template.get_data_from_spectral_order(order=147)
fig, axis = stellar_template.plot_spectra(
    order=147,
    return_fig_and_axis=True,
    plot_options={"label": "Stellar template without telluric mask"},
)

# Ingest the telluric mask into the stellar template mask
stellar_template.remove_telluric_features(ModelTell)

fig, axis = stellar_template.plot_spectra(
    order=147,
    fig_and_axis=(fig, axis),
    return_fig_and_axis=True,
    plot_options={"label": "Template with telluric mask"},
)
axis.legend(ncol=2, loc=4, bbox_to_anchor=(1, 1))

from pathlib import Path from ASTRA.data_objects import DataClassManager from ASTRA.data_objects.DataClass import DataClass from ASTRA.Instruments import ESPRESSO from ASTRA.template_creation.StellarModel import StellarModel storage_path = Path("../../tmp") manager = DataClassManager() manager.start() d: DataClass = manager.DataClass( list(Path("/home/amiguel/spectra_collection/ESPRESSO/proxima").glob("*.fits")), storage_path=storage_path, instrument=ESPRESSO, ) stell = StellarModel( storage_path, user_configs={}, ) stell.Generate_Model( dataClass=d, template_configs={}, force_computation=False, ) stellar_template = stell.request_data(d.get_available_subInstruments()[0]) wave, flux, err, mask = stellar_template.get_data_from_spectral_order(order=147) fig, axis = stellar_template.plot_spectra( order=147, return_fig_and_axis=True, plot_options={"label": "Stellar template without telluric mask"}, ) # Ingest the telluric mask into the stellar template mask stellar_template.remove_telluric_features(ModelTell) fig, axis = stellar_template.plot_spectra( order=147, fig_and_axis=(fig, axis), return_fig_and_axis=True, plot_options={"label": "Template with telluric mask"}, ) axis.legend(ncol=2, loc=4, bbox_to_anchor=(1, 1))

Out[3]:

<matplotlib.legend.Legend at 0x7f8310b27a10>