"""
Module with the ``Box`` classes and ``create_box`` function.
"""
import warnings
from numbers import Real
import numpy as np
from beartype import beartype
from beartype.typing import List, Tuple, Union
from scipy.signal import savgol_filter
from species.phot.syn_phot import SyntheticPhotometry
from species.read.read_filter import ReadFilter
from species.util.data_util import convert_units
from species.util.spec_util import smooth_spectrum
[docs]
class Box:
"""
Class for generic methods that can be applied on all `Box` object.
"""
def __init__(self):
"""
Returns
-------
NoneType
None
"""
[docs]
def open_box(self):
"""
Method for inspecting the content of a `Box`.
Returns
-------
NoneType
None
"""
print(f"Opening {type(self).__name__}...")
for key, value in self.__dict__.items():
print(f"{key} = {value}")
[docs]
class ColorMagBox(Box):
"""
Class for storing color-magnitude data in a
:class:`~species.core.box.Box`.
"""
def __init__(self):
"""
Returns
-------
NoneType
None
"""
self.library = None
self.iso_tag = None
self.object_type = None
self.filters_color = None
self.filter_mag = None
self.color = None
self.magnitude = None
self.names = None
self.sptype = None
self.mass = None
self.radius = None
self.age = None
[docs]
class ColorColorBox(Box):
"""
Class for storing color-color data in a
:class:`~species.core.box.Box`.
"""
def __init__(self):
"""
Returns
-------
NoneType
None
"""
self.library = None
self.iso_tag = None
self.object_type = None
self.filters = None
self.color1 = None
self.color2 = None
self.names = None
self.sptype = None
self.mass = None
self.radius = None
self.age = None
[docs]
class CoolingBox(Box):
"""
Class for storing cooling curve data in
a :class:`~species.core.box.Box`.
"""
def __init__(self):
"""
Returns
-------
NoneType
None
"""
self.model = None
self.mass = None
self.age = None
self.s_init = None
self.teff = None
self.log_lum = None
self.logg = None
self.radius = None
self.filter_mag = None
self.magnitude = None
self.filters_color = None
self.color = None
[docs]
class IsochroneBox(Box):
"""
Class for storing isochrone data in a
:class:`~species.core.box.Box`.
"""
def __init__(self):
"""
Returns
-------
NoneType
None
"""
self.model = None
self.age = None
self.s_init = None
self.mass = None
self.teff = None
self.log_lum = None
self.logg = None
self.radius = None
self.filter_mag = None
self.magnitude = None
self.filters_color = None
self.color = None
[docs]
class PhotometryBox(Box):
"""
Class for storing photometric data in a
:class:`~species.core.box.Box`.
"""
def __init__(self):
"""
Returns
-------
NoneType
None
"""
self.name = None
self.sptype = None
self.wavelength = None
self.flux = None
self.app_mag = None
self.abs_mag = None
self.filter_name = None
[docs]
class ModelBox(Box):
"""
Class for storing a model spectrum in a
:class:`~species.core.box.Box`.
"""
def __init__(self):
"""
Returns
-------
NoneType
None
"""
self.model = None
self.type = None
self.wavelength = None
self.flux = None
self.parameters = None
self.quantity = None
self.contribution = None
self.bol_flux = None
self.spec_res = None
self.extra_out = None
self.units = ("um", "W m-2 um-1")
[docs]
def smooth_spectrum(self, spec_res: Real) -> None:
"""
Method for smoothing the spectrum with a Gaussian kernel to the
instrument resolution. The method is best applied on an input
spectrum with a logarithmic wavelength sampling (i.e. constant
spectral resolution). Alternatively, the wavelength sampling
may be linear, but the smoothing is slower in that case.
Parameters
----------
spec_res : float
Spectral resolution that is used for the smoothing kernel.
Returns
-------
NoneType
None
"""
self.flux = smooth_spectrum(self.wavelength, self.flux, spec_res)
[docs]
def resample_spectrum(self, wavel_resample: np.ndarray) -> None:
"""
Method for resampling the spectrum with ``spectres`` to a new
wavelength grid.
Parameters
----------
wavel_resample : np.ndarray
Wavelength points (um) to which the spectrum will be
resampled.
Returns
-------
NoneType
None
"""
from spectres import spectres
self.flux = spectres(
wavel_resample,
self.wavelength,
self.flux,
spec_errs=None,
fill=np.nan,
verbose=True,
)
self.wavelength = wavel_resample
[docs]
def synthetic_photometry(self, filter_name: Union[str, List[str]]) -> PhotometryBox:
"""
Method for calculating synthetic photometry from the model
spectrum that is stored in the ``ModelBox``.
Parameters
----------
filter_name : str, list(str)
Single filter name or a list of filter names for which
synthetic photometry will be calculated.
Returns
-------
species.core.box.PhotometryBox
Box with the synthetic photometry.
"""
if isinstance(filter_name, str):
filter_name = [filter_name]
list_wavel = []
list_flux = []
list_app_mag = []
list_abs_mag = []
for item in filter_name:
synphot = SyntheticPhotometry(filter_name=item)
syn_flux = synphot.spectrum_to_flux(
wavelength=self.wavelength, flux=self.flux
)
syn_mag = synphot.spectrum_to_magnitude(
wavelength=self.wavelength, flux=self.flux
)
list_flux.append(syn_flux)
list_app_mag.append(syn_mag[0])
list_abs_mag.append(syn_mag[1])
filter_profile = ReadFilter(filter_name=item)
list_wavel.append(filter_profile.mean_wavelength())
phot_box = create_box(
boxtype="photometry",
name=None,
sptype=None,
wavelength=list_wavel,
flux=list_flux,
app_mag=list_app_mag,
abs_mag=list_abs_mag,
filter_name=filter_name,
)
return phot_box
[docs]
def highpass_filter(self, window_length: int = 101) -> None:
"""
Method for high-pass filtering of the model spectrum that
is stored in the ``ModelBox``. This is useful for removing
the pseudo-continuum of a high-resolution spectrum.
A `Savitzky-Golay filter <https://docs.scipy.org/doc/scipy/
reference/generated/scipy.signal.savgol_filter.html>`_
is used with a second order polynomial.
Parameters
----------
window_length : int
Window length of the Savitsky-Golay filter. The
argument needs to be optimized, depending on the
sampling resolution of the model spectrum
(default: 101).
Returns
-------
NoneType
None
"""
nan_mask = np.isnan(self.flux)
if np.sum(nan_mask) > 0:
warnings.warn(f"There are {np.sum(nan_mask)} NaNs in the model spectrum.")
filtered = self.flux.copy()
filtered[~nan_mask] = np.array(
savgol_filter(
self.flux[~nan_mask], window_length=window_length, polyorder=2
)
)
self.flux -= filtered[~nan_mask]
[docs]
def convert_units(self, units: Tuple[str, str]) -> None:
"""
Method for converting the wavelength and/or flux density
units from :math:`\\mu\\text{m}` and
:math:`\\text{W} \\text{m}^{-2} \\mu\\text{m}^{-1}`,
respectively, to any of the units listed with
the ``units`` parameter.
Parameters
----------
units : tuple(str, str)
Tuple with the units of the wavelength ("um", "angstrom",
"nm", "mm", "cm", "m", "Hz", "GHz") and the units of the
flux density ("W m-2 um-1", "W m-2 m-1", "W m-2 Hz-1",
"erg s-1 cm-2 angstrom-1" "erg s-1 cm-2 Hz-1", "uJy",
mJy", "Jy", "MJy"). One can use "um" or "µm"
interchangeably, and similarly "AA", "Å", "A", or
"angstrom".
Returns
-------
NoneType
None
"""
spec_in = np.column_stack([self.wavelength, self.flux])
spec_out = convert_units(spec_in, units, convert_from=False)
self.wavelength = spec_out[:, 0]
self.flux = spec_out[:, 1]
self.units = (units[0], units[1])
[docs]
class ObjectBox(Box):
"""
Class for storing object data in a :class:`~species.core.box.Box`.
"""
def __init__(self):
"""
Returns
-------
NoneType
None
"""
self.name = None
self.filters = None
self.mean_wavel = None
self.filter_width = None
self.magnitude = None
self.flux = None
self.spectrum = None
self.parallax = None
self.distance = None
[docs]
class ResidualsBox(Box):
"""
Class for storing best-fit residuals in a
:class:`~species.core.box.Box`.
"""
def __init__(self):
"""
Returns
-------
NoneType
None
"""
self.name = None
self.photometry = None
self.spectrum = None
self.chi2_red = None
[docs]
class SamplesBox(Box):
"""
Class for storing posterior samples in a
:class:`~species.core.box.Box`.
"""
def __init__(self):
"""
Returns
-------
NoneType
None
"""
self.spectrum = None
self.parameters = None
self.samples = None
self.ln_prob = None
self.ln_evidence = None
self.prob_sample = None
self.median_sample = None
self.attributes = None
self.uniform_priors = None
self.normal_priors = None
[docs]
class SpectrumBox(Box):
"""
Class for storing spectral data in a
:class:`~species.core.box.Box`.
"""
def __init__(self):
"""
Returns
-------
NoneType
None
"""
self.spectrum = None
self.wavelength = None
self.flux = None
self.error = None
self.name = None
self.simbad = None
self.sptype = None
self.distance = None
self.spec_res = None
[docs]
class SynphotBox(Box):
"""
Class for storing synthetic photometry in a
:class:`~species.core.box.Box`.
"""
def __init__(self):
"""
Returns
-------
NoneType
None
"""
self.name = None
self.wavelength = None
self.flux = None
self.app_mag = None
self.abs_mag = None
[docs]
def create_box(boxtype, **kwargs):
"""
Function for creating a :class:`~species.core.box.Box`.
Returns
-------
species.core.box
Box with the data and parameters.
"""
if boxtype == "colormag":
box = ColorMagBox()
box.library = kwargs["library"]
box.object_type = kwargs["object_type"]
box.filters_color = kwargs["filters_color"]
box.filter_mag = kwargs["filter_mag"]
box.color = kwargs["color"]
box.magnitude = kwargs["magnitude"]
if "names" in kwargs:
box.names = kwargs["names"]
if "sptype" in kwargs:
box.sptype = kwargs["sptype"]
if "mass" in kwargs:
box.mass = kwargs["mass"]
if "radius" in kwargs:
box.radius = kwargs["radius"]
if "iso_tag" in kwargs:
box.iso_tag = kwargs["iso_tag"]
if "age" in kwargs:
box.age = kwargs["age"]
if boxtype == "colorcolor":
box = ColorColorBox()
box.library = kwargs["library"]
box.object_type = kwargs["object_type"]
box.filters = kwargs["filters"]
box.color1 = kwargs["color1"]
box.color2 = kwargs["color2"]
if "names" in kwargs:
box.names = kwargs["names"]
if "sptype" in kwargs:
box.sptype = kwargs["sptype"]
if "mass" in kwargs:
box.mass = kwargs["mass"]
if "radius" in kwargs:
box.radius = kwargs["radius"]
if "iso_tag" in kwargs:
box.iso_tag = kwargs["iso_tag"]
if "age" in kwargs:
box.age = kwargs["age"]
elif boxtype == "cooling":
box = CoolingBox()
box.model = kwargs["model"]
box.mass = kwargs["mass"]
if "s_init" in kwargs:
box.s_init = kwargs["s_init"]
if "age" in kwargs:
box.age = kwargs["age"]
else:
box.age = kwargs["ages"]
box.teff = kwargs["teff"]
box.log_lum = kwargs["log_lum"]
box.logg = kwargs["logg"]
box.radius = kwargs["radius"]
box.filter_mag = kwargs["filter_mag"]
box.magnitude = kwargs["magnitude"]
box.filters_color = kwargs["filters_color"]
box.color = kwargs["color"]
elif boxtype == "isochrone":
box = IsochroneBox()
box.model = kwargs["model"]
box.age = kwargs["age"]
if "s_init" in kwargs:
box.s_init = kwargs["s_init"]
if "mass" in kwargs:
box.mass = kwargs["mass"]
else:
box.mass = kwargs["masses"]
box.teff = kwargs["teff"]
box.log_lum = kwargs["log_lum"]
box.logg = kwargs["logg"]
box.radius = kwargs["radius"]
box.filter_mag = kwargs["filter_mag"]
box.magnitude = kwargs["magnitude"]
box.filters_color = kwargs["filters_color"]
box.color = kwargs["color"]
elif boxtype == "model":
box = ModelBox()
box.model = kwargs["model"]
box.wavelength = kwargs["wavelength"]
box.flux = kwargs["flux"]
box.parameters = kwargs["parameters"]
box.quantity = kwargs["quantity"]
if "contribution" in kwargs:
box.contribution = kwargs["contribution"]
if "bol_flux" in kwargs:
box.bol_flux = kwargs["bol_flux"]
if "spec_res" in kwargs:
box.spec_res = kwargs["spec_res"]
if "extra_out" in kwargs:
box.extra_out = kwargs["extra_out"]
elif boxtype == "object":
box = ObjectBox()
box.name = kwargs["name"]
box.filters = kwargs["filters"]
box.mean_wavel = kwargs["mean_wavel"]
box.filter_width = kwargs["filter_width"]
box.magnitude = kwargs["magnitude"]
box.flux = kwargs["flux"]
box.spectrum = kwargs["spectrum"]
if "parallax" in kwargs:
box.parallax = kwargs["parallax"]
if "distance" in kwargs:
box.distance = kwargs["distance"]
elif boxtype == "photometry":
box = PhotometryBox()
if "name" in kwargs:
box.name = kwargs["name"]
if "sptype" in kwargs:
box.sptype = kwargs["sptype"]
if "wavelength" in kwargs:
box.wavelength = kwargs["wavelength"]
if "flux" in kwargs:
box.flux = kwargs["flux"]
if "app_mag" in kwargs:
box.app_mag = kwargs["app_mag"]
if "abs_mag" in kwargs:
box.abs_mag = kwargs["abs_mag"]
if "filter_name" in kwargs:
box.filter_name = kwargs["filter_name"]
elif boxtype == "residuals":
box = ResidualsBox()
box.name = kwargs["name"]
box.photometry = kwargs["photometry"]
if "spectrum" in kwargs:
box.spectrum = kwargs["spectrum"]
if "model_name" in kwargs:
box.model_name = kwargs["model_name"]
if "chi2_red" in kwargs:
box.chi2_red = kwargs["chi2_red"]
elif boxtype == "samples":
box = SamplesBox()
if "spectrum" in kwargs:
box.spectrum = kwargs["spectrum"]
if "model_name" in kwargs:
box.model_name = kwargs["model_name"]
box.parameters = kwargs["parameters"]
box.samples = kwargs["samples"]
box.ln_prob = kwargs["ln_prob"]
box.ln_evidence = kwargs["ln_evidence"]
box.prob_sample = kwargs["prob_sample"]
box.median_sample = kwargs["median_sample"]
box.attributes = kwargs["attributes"]
if "uniform_priors" in kwargs:
box.uniform_priors = kwargs["uniform_priors"]
if "normal_priors" in kwargs:
box.normal_priors = kwargs["normal_priors"]
elif boxtype == "spectrum":
box = SpectrumBox()
box.spectrum = kwargs["spectrum"]
box.wavelength = kwargs["wavelength"]
box.flux = kwargs["flux"]
if "error" in kwargs:
box.error = kwargs["error"]
if "name" in kwargs:
box.name = kwargs["name"]
if "simbad" in kwargs:
box.simbad = kwargs["simbad"]
if "sptype" in kwargs:
box.sptype = kwargs["sptype"]
if "parallax" in kwargs:
box.parallax = kwargs["parallax"]
if "distance" in kwargs:
box.distance = kwargs["distance"]
if "spec_res" in kwargs:
box.spec_res = kwargs["spec_res"]
elif boxtype == "synphot":
box = SynphotBox()
box.name = kwargs["name"]
box.flux = kwargs["flux"]
if "wavelength" in kwargs:
box.wavelength = kwargs["wavelength"]
if "app_mag" in kwargs:
box.app_mag = kwargs["app_mag"]
if "abs_mag" in kwargs:
box.abs_mag = kwargs["abs_mag"]
return box
