# -*- coding: utf-8 -*-
"""
Elemental abundance data handling module
"""
import io
import json
import logging
import warnings
from collections.abc import MutableMapping
import numpy as np
from flex.extensions.bindata import BinaryDataExtension
from .persistence import IPersist
logger = logging.getLogger(__name__)
class _AbundanceView(MutableMapping):
def __init__(self, abund, kind):
self.abund = abund
self.kind = kind
def __getitem__(self, elem):
return self.abund._view_get(self.kind, elem)
def __setitem__(self, elem, value):
self.abund._view_set(self.kind, elem, value)
def __delitem__(self, elem):
raise TypeError("Abundance views do not support item deletion")
def __iter__(self):
return iter(self.abund.elem)
def __len__(self):
return len(self.abund.elem)
_citation_anders1989 = r"""
@ARTICLE{1989GeCoA..53..197A,
author = {{Anders}, E. and {Grevesse}, N.},
title = "{Abundances of the elements: Meteoritic and solar}",
journal = {\gca},
keywords = {Abundance, Chemical Analysis, Chondrites, Meteoritic Composition, Photosphere, Solar Corona, Energetic Particles, Isotopes, Solar Wind, METEORITES, ABUNDANCE, SAMPLES, METEORITE, CI CHONDRITES, SUN, CORONA, PHOTOSPHERE, REVIEW, ELEMENTS, FRACTIONATION, SOLAR SYSTEM, NUCLIDES, SOLAR WIND, CHARGED PARTICLES, RARE GASES, REFRACTORY ELEMENTS, COMETS, SIDEROPHILES, VOLATILES, NUCLEOSYNTHESIS, HALLEY, COMPARISONS},
year = 1989,
month = jan,
volume = {53},
number = {1},
pages = {197-214},
doi = {10.1016/0016-7037(89)90286-X},
adsurl = {https://ui.adsabs.harvard.edu/abs/1989GeCoA..53..197A},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
"""
_citation_grevesse1996 = r"""
@INPROCEEDINGS{1996ASPC...99..117G,
author = {{Grevesse}, N. and {Noels}, A. and {Sauval}, A.~J.},
title = "{Standard Abundances}",
booktitle = {Cosmic Abundances},
year = 1996,
editor = {{Holt}, Stephen S. and {Sonneborn}, George},
series = {Astronomical Society of the Pacific Conference Series},
volume = {99},
month = jan,
pages = {117},
adsurl = {https://ui.adsabs.harvard.edu/abs/1996ASPC...99..117G},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
"""
_citation_grevesse1998 = r"""
@ARTICLE{1998SSRv...85..161G,
author = {{Grevesse}, N. and {Sauval}, A.~J.},
title = "{Standard Solar Composition}",
journal = {\ssr},
keywords = {Sun: abundances, Meteorites: abundances, Solar spectroscopy},
year = 1998,
month = may,
volume = {85},
pages = {161-174},
doi = {10.1023/A:1005161325181},
adsurl = {https://ui.adsabs.harvard.edu/abs/1998SSRv...85..161G},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
"""
_citation_asplund2005 = r"""
@INPROCEEDINGS{2005ASPC..336...25A,
author = {{Asplund}, M. and {Grevesse}, N. and {Sauval}, A.~J.},
title = "{The Solar Chemical Composition}",
booktitle = {Cosmic Abundances as Records of Stellar Evolution and Nucleosynthesis},
year = 2005,
editor = {{Barnes}, III, Thomas G. and {Bash}, Frank N.},
series = {Astronomical Society of the Pacific Conference Series},
volume = {336},
month = sep,
pages = {25},
adsurl = {https://ui.adsabs.harvard.edu/abs/2005ASPC..336...25A},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
"""
_citation_grevesse2007 = r"""
@ARTICLE{2007SSRv..130..105G,
author = {{Grevesse}, N. and {Asplund}, M. and {Sauval}, A.~J.},
title = "{The Solar Chemical Composition}",
journal = {\ssr},
keywords = {Sun: abundances, photosphere, corona},
year = 2007,
month = jun,
volume = {130},
number = {1-4},
pages = {105-114},
doi = {10.1007/s11214-007-9173-7},
adsurl = {https://ui.adsabs.harvard.edu/abs/2007SSRv..130..105G},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
"""
_citation_asplund2009 = r"""
@ARTICLE{2009ARA&A..47..481A,
author = {{Asplund}, Martin and {Grevesse}, Nicolas and {Sauval}, A. Jacques and
{Scott}, Pat},
title = "{The Chemical Composition of the Sun}",
journal = {\araa},
keywords = {Astrophysics - Solar and Stellar Astrophysics, Astrophysics - Earth and Planetary Astrophysics},
year = "2009",
month = "Sep",
volume = {47},
number = {1},
pages = {481-522},
doi = {10.1146/annurev.astro.46.060407.145222},
archivePrefix = {arXiv},
eprint = {0909.0948},
primaryClass = {astro-ph.SR},
adsurl = {https://ui.adsabs.harvard.edu/abs/2009ARA&A..47..481A},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
"""
_citation_asplund2021 = r"""
@ARTICLE{2021A&A...653A.141A,
author = {{Asplund}, M. and {Amarsi}, A.~M. and {Grevesse}, N.},
title = "{The chemical make-up of the Sun: A 2020 vision}",
journal = {\aap},
keywords = {Sun: abundances, Sun: photosphere, Sun: atmosphere, line: formation, meteorites, meteors, meteoroids, Sun: helioseismology, Astrophysics - Solar and Stellar Astrophysics, Astrophysics - Earth and Planetary Astrophysics},
year = 2021,
month = sep,
volume = {653},
eid = {A141},
pages = {A141},
doi = {10.1051/0004-6361/202140445},
archivePrefix = {arXiv},
eprint = {2105.01661},
primaryClass = {astro-ph.SR},
adsurl = {https://ui.adsabs.harvard.edu/abs/2021A&A...653A.141A},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
"""
_citation_lodders2003 = r"""
@ARTICLE{2003ApJ...591.1220L,
author = {{Lodders}, Katharina},
title = "{Solar System Abundances and Condensation Temperatures of the Elements}",
journal = {\apj},
keywords = {Astrochemistry, Meteors, Meteoroids, Solar System: Formation- Sun: Abundances, Sun: Photosphere},
year = "2003",
month = "Jul",
volume = {591},
number = {2},
pages = {1220-1247},
doi = {10.1086/375492},
adsurl = {https://ui.adsabs.harvard.edu/abs/2003ApJ...591.1220L},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
"""
_citation_lodders2010 = r"""
@INPROCEEDINGS{2010ASSP...16..379L,
author = {{Lodders}, Katharina},
title = "{Solar System Abundances of the Elements}",
keywords = {Physics, Astrophysics - Solar and Stellar Astrophysics, Astrophysics - Earth and Planetary Astrophysics},
booktitle = {Principles and Perspectives in Cosmochemistry},
year = 2010,
editor = {{Goswami}, Aruna and {Reddy}, B. Eswar},
series = {Astrophysics and Space Science Proceedings},
volume = {16},
month = jan,
pages = {379},
doi = {10.1007/978-3-642-10352-0_8},
archivePrefix = {arXiv},
eprint = {1010.2746},
primaryClass = {astro-ph.SR},
adsurl = {https://ui.adsabs.harvard.edu/abs/2010ASSP...16..379L},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
"""
_citation_atomic_weights = r"""
@article{loss2003atomic,
title={Atomic weights of the elements 2001 (IUPAC Technical Report)},
author={Loss, RD},
journal={Pure and Applied Chemistry},
volume={75},
number={8},
pages={1107--1122},
year={2003},
publisher={De Gruyter}
}
"""
# fmt: off
elements = (
"H", "He",
"Li", "Be", "B" , "C" , "N" , "O" , "F" , "Ne",
"Na", "Mg", "Al", "Si", "P" , "S" , "Cl", "Ar",
"K" , "Ca", "Sc", "Ti", "V" , "Cr", "Mn", "Fe",
"Co", "Ni", "Cu", "Zn", "Ga", "Ge", "As", "Se",
"Br", "Kr", "Rb", "Sr", "Y" , "Zr", "Nb", "Mo",
"Tc", "Ru", "Rh", "Pd", "Ag", "Cd", "In", "Sn",
"Sb", "Te", "I" , "Xe", "Cs", "Ba", "La", "Ce",
"Pr", "Nd", "Pm", "Sm", "Eu", "Gd", "Tb", "Dy",
"Ho", "Er", "Tm", "Yb", "Lu", "Hf", "Ta", "W" ,
"Re", "Os", "Ir", "Pt", "Au", "Hg", "Tl", "Pb",
"Bi", "Po", "At", "Rn", "Fr", "Ra", "Ac", "Th",
"Pa", "U" , "Np", "Pu", "Am", "Cm", "Bk", "Cf",
"Es",)
# index of each element in the pattern data array
elements_dict = {el:i for i, el in enumerate(elements)}
# Array of atomic weights
# From Loss, R. D. 2003, Pure Appl. Chem., 75, 1107, "Atomic Weights
# of the Elements 2001". The isotopic composition of the Sun and stars
# may differ from the terrestrial values listed here!
# For radionuclides that appear only in Table 3, we have adopted the
# atomic mass of the longest lived isotope, rounding to at most two
# digits after the decimal point. These elements are: 43_Tc_98,
# 61_Pm_145, 85_At_210, 86_Rn_222, 87_Fr_223, 88_Ra_226, 89_Ac_227,
# 93_Np_237, 94_Pu_244, 95_Am_243, 96_Cm_247, 97_Bk_247, 98_Cf_251,
# 99_Es_252
_atom_weight = (
1.00794, 4.002602,
6.941, 9.012182, 10.811, 12.0107, 14.0067, 15.9994, 18.9984032, 20.1797,
22.989770, 24.3050, 26.981538, 28.0855, 30.973761, 32.065, 35.453, 39.948,
39.0983, 40.078, 44.955910, 47.867, 50.9415, 51.9961, 54.938049, 55.845,
58.933200, 58.6934, 63.546, 65.409, 69.723, 72.64, 74.92160, 78.96,
79.904, 83.798, 85.4678, 87.62, 88.90585, 91.224, 92.90638,
95.94, 97.91, 95.94, 101.07, 102.90550, 106.42, 107.8682, 112.411,
114.818, 118.710, 121.760, 127.60, 126.90447, 131.293, 132.90545, 137.327,
138.9055, 140.116, 140.90765, 144.24, 144.91, 150.36, 151.964, 157.25,
158.92534, 162.500, 164.93032, 167.259, 168.93421, 173.04, 174.967, 178.49,
180.9479, 183.84, 186.207, 190.23, 192.217, 195.078, 196.966, 200.59,
204.3833, 207.2, 208.98038, 209.99, 222.02, 223.02, 226.03, 227.03,
232.0381, 231.03588, 238.02891, 237.05, 244.06, 243.06, 247.07, 247.07,
251.08, 252.08,)
# Anders, Grevesse, 1989, GeCo Acta 53, 197
_anders1989 = (
12.00, 10.99,
1.16, 1.15, 2.60, 8.56, 8.05, 8.93, 4.56, 8.09,
6.33, 7.58, 6.47, 7.55, 5.45, 7.21, 5.50, 6.56,
5.12, 6.36, 3.10, 4.99, 4.00, 5.67, 5.39, 7.67,
4.92, 6.25, 4.21, 4.60, 2.88, 3.41, None, None,
None, None, 2.60, 2.90, 2.24, 2.60, 1.42, 1.92,
None, 1.84, 1.12, 1.69, 0.94, 1.86, 1.66, 2.00,
1.00, None, None, None, None, 2.13, 1.22, 1.55,
0.71, 1.50, None, 1.00, 0.51, 1.12, -0.10, 1.10,
0.26, 0.93, 0.00, 1.08, 0.76, 0.88, None, 1.11,
None, 1.45, 1.35, 1.80, 1.01, None, 0.90, 1.85,
None, None, None, None, None, None, None, 0.12,
None, None, None, None, None, None, None, None,
None,
)
# Grevesse, Noels, Sauval, 1996, ASPC 99, 177
_grevesse1996 = (
12.00, 10.99,
1.16, 1.15, 2.60, 8.55, 7.97, 8.87, 4.56, 8.08,
6.33, 7.58, 6.47, 7.55, 5.45, 7.33, 5.50, 6.52,
5.12, 6.36, 3.17, 5.02, 4.00, 5.67, 5.39, 7.50,
4.92, 6.25, 4.21, 4.60, 2.88, 3.41, None, None,
None, None, 2.60, 2.97, 2.24, 2.60, 1.42, 1.92,
None, 1.84, 1.12, 1.69, 0.94, 1.77, 1.66, 2.00,
1.00, None, None, None, None, 2.13, 1.17, 1.58,
0.71, 1.50, None, 1.01, 0.51, 1.12, -0.10, 1.14,
0.26, 0.93, 0.00, 1.08, 0.76, 0.88, None, 1.11,
None, 1.45, 1.35, 1.80, 1.01, None, 0.90, 1.95,
None, None, None, None, None, None, None, None,
None, None, None, None, None, None, None, None,
None,
)
# Grevesse, Sauval, 1998, SSR 85, 161
_grevesse1998 = (
12.00, 10.93,
1.10, 1.40, 2.55, 8.56, 7.92, 8.83, 4.56, 8.08,
6.33, 7.58, 6.47, 7.55, 5.45, 7.33, 5.50, 6.40,
5.12, 6.36, 3.17, 5.02, 4.00, 5.67, 5.39, 7.50,
4.92, 6.25, 4.21, 4.60, 2.88, 3.41, None, None,
None, None, 2.60, 2.97, 2.24, 2.60, 1.42, 1.92,
None, 1.84, 1.12, 1.69, 0.94, 1.77, 1.66, 2.00,
1.00, None, None, None, None, 2.13, 1.17, 1.58,
0.71, 1.50, None, 1.01, 0.51, 1.12, -0.10, 1.14,
0.26, 0.93, 0.00, 1.08, 0.06, 0.88, None, 1.11,
None, 1.45, 1.35, 1.80, 1.01, None, 0.90, 1.95,
None, None, None, None, None, None, None, None,
None, None, None, None, None, None, None, None,
None,
)
# Asplund, Grevesse, Sauval, 2005, ASPC 336, 252
_asplund2005 = (
12.00, 10.93,
1.05, 1.38, 2.70, 8.39, 7.78, 8.66, 4.56, 7.84,
6.17, 7.53, 6.37, 7.51, 5.36, 7.14, 5.50, 6.18,
5.08, 6.31, 3.05, 4.90, 4.00, 5.64, 5.39, 7.45,
4.92, 6.23, 4.21, 4.60, 2.88, 3.58, None, None,
None, 3.28, 2.60, 2.92, 2.21, 2.59, 1.42, 1.92,
None, 1.84, 1.12, 1.69, 0.94, 1.77, 1.60, 2.00,
1.00, None, None, 2.27, None, 2.17, 1.13, 1.58,
0.71, 1.45, None, 1.01, 0.52, 1.12, 0.28, 1.14,
0.51, 0.93, 0.00, 1.08, 0.06, 0.88, None, 1.11,
None, 1.45, 1.38, None, 1.01, None, 0.90, 2.00,
None, None, None, None, None, None, None, None,
None, None, None, None, None, None, None, None,
None,
)
# Grevesse, Asplund, Sauval (2007, Space Science Review, 130, 105)
_grevesse2007 = (
12.00, 10.93,
1.05, 1.38, 2.70, 8.39, 7.78, 8.66, 4.56, 7.84,
6.17, 7.53, 6.37, 7.51, 5.36, 7.14, 5.50, 6.18,
5.08, 6.31, 3.17, 4.90, 4.00, 5.64, 5.39, 7.45,
4.92, 6.23, 4.21, 4.60, 2.88, 3.58, 2.29, 3.33,
2.56, 3.25, 2.60, 2.92, 2.21, 2.58, 1.42, 1.92,
None, 1.84, 1.12, 1.66, 0.94, 1.77, 1.60, 2.00,
1.00, 2.19, 1.51, 2.24, 1.07, 2.17, 1.13, 1.70,
0.58, 1.45, None, 1.00, 0.52, 1.11, 0.28, 1.14,
0.51, 0.93, 0.00, 1.08, 0.06, 0.88, -0.17, 1.11,
0.23, 1.25, 1.38, 1.64, 1.01, 1.13, 0.90, 2.00,
0.65, None, None, None, None, None, None, 0.06,
None, -0.52, None, None, None, None, None, None,
None,
)
# Asplund, Grevesse, Sauval, Scott (2009, Annual Review of Astronomy
# and Astrophysics, 47, 481)
_asplund2009 = (
12.00, 10.93,
1.05, 1.38, 2.70, 8.43, 7.83, 8.69, 4.56, 7.93,
6.24, 7.60, 6.45, 7.51, 5.41, 7.12, 5.50, 6.40,
5.03, 6.34, 3.15, 4.95, 3.93, 5.64, 5.43, 7.50,
4.99, 6.22, 4.19, 4.56, 3.04, 3.65, 2.30, 3.34,
2.54, 3.25, 2.52, 2.87, 2.21, 2.58, 1.46, 1.88,
None, 1.75, 0.91, 1.57, 0.94, 1.71, 0.80, 2.04,
1.01, 2.18, 1.55, 2.24, 1.08, 2.18, 1.10, 1.58,
0.72, 1.42, None, 0.96, 0.52, 1.07, 0.30, 1.10,
0.48, 0.92, 0.10, 0.84, 0.10, 0.85, -0.12, 0.85,
0.26, 1.40, 1.38, 1.62, 0.92, 1.17, 0.90, 1.75,
0.65, None, None, None, None, None, None, 0.02,
None, -0.54, None, None, None, None, None, None,
None,
)
# Asplund, Grevesse, Sauval, Scott (2009, Annual Review of Astronomy
# and Astrophysics, 47, 481)
_asplund2021 = (
12.00, 10.914,
0.96, 1.38, 2.70, 8.46, 7.83, 8.69, 4.40, 8.06,
6.22, 7.55, 6.43, 7.51, 5.41, 7.12, 5.31, 6.38,
5.07, 6.30, 3.14, 4.97, 3.90, 5.62, 5.42, 7.46,
4.94, 6.20, 4.18, 4.56, 3.02, 3.62, 2.30, 3.34,
2.54, 3.12, 2.32, 2.83, 2.21, 2.59, 1.47, 1.88,
None, 1.75, 0.78, 1.57, 0.96, 1.71, 0.80, 2.02,
1.01, 2.18, 1.55, 2.22, 1.08, 2.17, 1.11, 1.58,
0.75, 1.42, None, 0.95, 0.52, 1.08, 0.31, 1.10,
0.48, 0.93, 0.10, 0.85, 0.10, 0.85, -0.15, 0.79,
0.26, 1.35, 1.32, 1.61, 0.91, 1.17, 0.92, 1.95,
0.65, None, None, None, None, None, None, 0.03,
None, -0.54, None, None, None, None, None, None,
None,
)
# Lodders 2003 (ApJ, 591, 1220)
_lodders2003 = (
12, 10.899,
3.28, 1.41, 2.78, 8.39, 7.83, 8.69, 4.46, 7.87,
6.30, 7.55, 6.46, 7.54, 5.46, 7.19, 5.26, 6.55,
5.11, 6.34, 3.07, 4.92, 4.00, 5.65, 5.50, 7.47,
4.91, 6.22, 4.26, 4.63, 3.10, 3.62, 2.32, 3.36,
2.59, 3.28, 2.36, 2.91, 2.20, 2.60, 1.42, 1.96,
1.82, 1.11, 1.70, 1.23, 1.74, 0.80, 2.11, 1.06,
2.22, 1.54, 2.27, 1.10, 2.18, 1.18, 1.61, 0.75,
1.46, 0.95, 0.85, 1.06, 0.31, 1.13, 0.49, 0.95,
0.11, 0.94, 0.09, 0.77, -0.14, 0.65, 0.26, 1.37,
1.35, 1.67, 0.72, 1.16, 0.81, 2.05, 0.68, 0.09,
None, -0.49, None, None, None, None, None, None,
None, None, None, None, None, None, None, None,
None,
)
# Lodders 2010, ASSP 16, 379
_lodders2010 = (
12.00, 10.93,
3.28, 1.32, 2.81, 8.39, 7.86, 8.73, 4.44, 8.05,
6.29, 7.54, 6.46, 7.53, 5.45, 7.16, 5.25, 6.50,
5.11, 6.31, 3.07, 4.93, 3.99, 5.65, 5.50, 7.46,
4.90, 6.22, 4.27, 4.65, 3.10, 3.59, 2.32, 3.36,
2.56, 3.28, 2.38, 2.90, 2.20, 2.57, 1.42, 1.94,
None, 1.78, 1.10, 1.67, 1.22, 1.73, 0.78, 2.09,
1.03, 2.20, 1.57, 2.27, 1.10, 2.18, 1.19, 1.60,
0.77, 1.47, None, 0.96, 0.53, 1.09, 0.34, 1.14,
0.49, 0.95, 0.14, 0.94, 0.11, 0.73, -0.14, 0.67,
0.28, 1.37, 1.36, 1.64, 0.82, 1.19, 0.79, 2.06,
0.67, None, None, None, None, None, None, 0.08,
None, -0.52, None, None, None, None, None, None,
None,
)
[docs]
class Abund(IPersist):
"""Elemental abundance data and methods.
Valid abundance pattern types are:
'sme' - For hydrogen, the abundance value is the fraction of all
nuclei that are hydrogen, including all ionization states
and treating molecules as constituent atoms. For the other
elements, the abundance values are log10 of the fraction of
nuclei of each element in any form relative to the total for
all elements in any form. For the Sun, the abundance values
of H, He, and Li are approximately 0.92, -1.11, and -11.0.
'n/nTot' - Abundance values are the fraction of nuclei
of each element in any form relative to the total for all
elements in any form. For the Sun, the abundance values of
H, He, and Li are approximately 0.92, 0.078, and 1.03e-11.
'n/nH' - Abundance values are the fraction of nuclei
of each element in any form relative to the number of
hydrogen nuclei in any form. For the Sun, the abundance
values of H, He, and Li are approximately 1, 0.085, and
1.12e-11.
'H=12' - Abundance values are log10 of the fraction of nuclei of
each element in any form relative to the number of hydrogen
in any form plus an offset of 12. For the Sun, the nuclei
abundance values of H, He, and Li are approximately 12,
10.9, and 1.05.
"""
def __init__(
self,
monh=0,
pattern="solar",
type="sme",
citation_info=_citation_atomic_weights,
):
self.monh = monh
# The internal type is fixed to this value
self._type_internal = "H=12"
self.type = type
self.citation_info = citation_info
if isinstance(pattern, str):
self.set_pattern_by_name(pattern)
else:
self.set_pattern_by_value(pattern, type)
def __call__(self, type="H=12", raw=False):
"""Return abundances for all elements.
Apply current [M/H] value to the current abundance pattern.
Transform the resulting abundances to the requested abundance type.
"""
pattern = np.copy(self._pattern)
if self.monh is not None:
pattern[2:] += self.monh
return self.totype(pattern, type, raw=raw, copy=False)
def __getitem__(self, elem):
return self.get_element(elem)
def __setitem__(self, elem, abund):
warnings.warn(
'Direct abundance assignment via sme.abund["X"] is ambiguous and kept for '
'backward compatibility. Use sme.abund.A["X"] to set the abundance used in '
'synthesis, or sme.abund.pattern["X"] to set the internal SME pattern.',
FutureWarning,
stacklevel=2,
)
self.update_pattern({elem: abund})
def __str__(self):
if self._pattern is None:
if self._monh is None:
return "[M/H] is not set. Abundance pattern is not set."
else:
return f"[M/H]={self._monh:.3f}. Abundance pattern is not set"
else:
a = self.get_pattern("H=12", raw=True)
if self._monh is None:
out = "[M/H] is not set. Values below are the abundance pattern.\n"
else:
a = np.copy(a)
a[2:] += self._monh
out = (
f" [M/H]={self._monh:.3f} applied to abundance pattern. "
"Values below are abundances.\n"
)
for i in range(9):
for j in range(11):
out += " {:<5s}".format(elements[11 * i + j])
out += "\n"
for j in range(11):
out += "{:7.3f}".format(a[11 * i + j])
if i < 8:
out += "\n"
return out
def __repr__(self):
return self.__str__()
def __getattribute__(self, name):
if name == "solar":
if not object.__getattribute__(self, "_reference_is_solar"):
raise ValueError(
"The current abundance reference is not marked as a solar pattern. "
"Use sme.abund.reference['X'] instead."
)
return _AbundanceView(self, "reference")
return object.__getattribute__(self, name)
# These are there for the atmosphere interpolation
# The internal format is always H=12, so that should be fine
def __add__(self, other):
result = Abund(
monh=self.monh, pattern=np.copy(self._pattern), type=self._type_internal
)
if isinstance(other, Abund):
result._pattern += other.get_pattern(self._type_internal, raw=True)
result.monh += other.monh
else:
raise NotImplementedError
result.type = self.type
result._reference_pattern = self._reference_pattern.copy()
result._reference_name = self._reference_name
result._reference_is_solar = self._reference_is_solar
return result
def __radd__(self, other):
return self.__add__(other)
def __mul__(self, other):
result = Abund(
monh=self.monh, pattern=np.copy(self._pattern), type=self._type_internal
)
if isinstance(other, Abund):
raise NotImplementedError
else:
result._pattern *= other
result.monh *= other
result.type = self.type
result._reference_pattern = self._reference_pattern.copy()
result._reference_name = self._reference_name
result._reference_is_solar = self._reference_is_solar
return result
def __rmul__(self, other):
return self.__mul__(other)
def _get_index(self, elem):
try:
return elements_dict[elem]
except KeyError:
raise KeyError(
f"Got element abreviation {elem}, expected one of {elements}"
)
def __copy__(self):
pattern = self._pattern.copy()
other = Abund(
monh=self.monh,
type=self.type,
pattern=pattern,
citation_info=self.citation_info,
)
other._reference_pattern = self._reference_pattern.copy()
other._reference_name = self._reference_name
other._reference_is_solar = self._reference_is_solar
return other
[docs]
@staticmethod
def fromtype(pattern, fromtype, raw=False):
"""Return a copy of the input abundance pattern, transformed from
the input type to the 'H=12' type. Valid abundance pattern types
are 'sme', 'n/nTot', 'n/nH', 'n/nFe', and 'H=12'.
"""
elem = elements
if isinstance(pattern, dict):
abund = np.array([pattern[el] for el in elem], dtype=float)
else:
abund = np.array(pattern, dtype=float)
if np.isnan(abund[0]):
raise ValueError("Pattern must define abundance of H")
# print(abund)
type = fromtype.lower()
if type == "h=12":
pass
elif type == "sme":
# sme -> H=12
abund[1:] += 12 - np.log10(abund[0])
abund[0] = 12
elif type == "kurucz":
# kurucz -> H=12
abund[2:] = abund[2:] + np.log10(abund[1] / abund[0] + 1) + 12
abund[1] = np.log10(abund[1]/abund[0]) + 12
abund[0] = 12
elif type == "n/ntot":
abund /= abund[0]
abund = 12 + np.log10(abund)
elif type == "n/nh":
abund = 12 + np.log10(abund)
elif type == "n/nfe":
abund /= abund[0]
abund = 12 + np.log10(abund)
elif type == "fe=12":
abund = 10 ** (abund - 12)
abund /= abund[0]
abund = 12 + np.log10(abund)
else:
raise ValueError(
"got abundance type '{}',".format(type)
+ " should be 'H=12', 'n/nH', 'n/nTot', 'n/nFe', 'Fe=12', or 'sme'"
)
if raw:
return abund
else:
return {el: abund[elements_dict[el]] for el in elements}
[docs]
@staticmethod
def totype(pattern, totype, raw=False, copy=True, X=None):
"""Return a copy of the input abundance pattern, transformed from
the 'H=12' type to the output type. Valid abundance pattern types
are 'sme', 'kurucz', 'n/nTot', 'n/nH', and 'H=12'.
"""
if isinstance(pattern, dict):
abund = [pattern[el] if el in pattern.keys() else np.nan for el in elements]
abund = np.array(abund)
elif copy:
abund = np.copy(pattern)
else:
abund = pattern
type = totype.lower()
if type == "h=12":
pass
elif type == "sme":
abund[0] = 1 / (1 + np.nansum(10**(abund[1:]-12)))
abund[1:] = np.log10(abund[0] * 10**(abund[1:] - 12))
elif type == "kurucz":
# H=12 -> kurucz
abund[0] = 1 / (1 + np.nansum(10**(abund[1:] - 12)))
abund[1] = 1 / (10**(12-abund[1]) + 1 + 10**(12-abund[1]) * np.nansum(10**(abund[2:]-12)))
abund[2:] = abund[2:] - 12 - np.log10(1 + 10**(abund[1]-12))
elif type == "n/ntot":
abund = 10 ** (abund - 12)
abund /= np.nansum(abund)
elif type == "n/nh":
abund = 10 ** (abund - 12)
elif type == "n/nfe":
idx_fe = elements_dict["Fe"]
abund = 10 ** (abund - 12)
abund /= abund[idx_fe]
elif type == "fe=12":
idx_fe = elements_dict["Fe"]
abund = 10 ** (abund - 12)
abund /= abund[idx_fe]
abund = np.log10(abund) + 12
else:
raise ValueError(
"got abundance type '{}',".format(type)
+ " should be 'H=12', 'kurucz', 'n/nH', 'n/nTot', 'n/nFe', 'Fe=12', or 'sme'"
)
if raw:
return abund
else:
return {el: abund[elements_dict[el]] for el in elements}
_formats = ["H=12", "sme", "n/nTot", "n/nH", "n/nFe", "Fe=12"]
@property
def elem(self):
"""Return the standard abbreviation for each element.
Use property so user will not redefine elements.
"""
return elements
@property
def elem_dict(self):
"""Return the position of each element in the raw array"""
return elements_dict
@property
def monh(self):
"""float: Metallicity, the logarithmic offset added to
the abundance pattern for all elements except hydrogen and helium."""
return self._monh
@monh.setter
def monh(self, monh):
self._monh = float(monh)
def _metallicity_offset(self):
return 0.0 if self.monh is None else float(self.monh)
def _is_metallicity_scaled(self, elem):
return self._get_index(elem) >= 2
def _require_xm_element(self, elem):
if not self._is_metallicity_scaled(elem):
raise ValueError(
f"[{elem}/M]_PySME is only defined for elements heavier than He."
)
[docs]
def get_pattern_abundance(self, elem):
return self._pattern[self._get_index(elem)]
[docs]
def set_pattern_abundance(self, elem, value):
self._pattern[self._get_index(elem)] = float(value)
[docs]
def get_reference_abundance(self, elem):
return self._reference_pattern[self._get_index(elem)]
[docs]
def get_A(self, elem):
value = self.get_pattern_abundance(elem)
if self._is_metallicity_scaled(elem):
value += self._metallicity_offset()
return value
[docs]
def set_A(self, elem, value):
value = float(value)
if self._is_metallicity_scaled(elem):
value -= self._metallicity_offset()
self.set_pattern_abundance(elem, value)
[docs]
def get_xh(self, elem):
return self.get_A(elem) - self.get_reference_abundance(elem)
[docs]
def set_xh(self, elem, value):
self.set_A(elem, self.get_reference_abundance(elem) + float(value))
[docs]
def get_xm(self, elem):
self._require_xm_element(elem)
return self.get_pattern_abundance(elem) - self.get_reference_abundance(elem)
[docs]
def set_xm(self, elem, value):
self._require_xm_element(elem)
self.set_pattern_abundance(elem, self.get_reference_abundance(elem) + float(value))
def _view_get(self, kind, elem):
if kind == "A":
return self.get_A(elem)
if kind == "xh":
return self.get_xh(elem)
if kind == "xm":
return self.get_xm(elem)
if kind == "pattern":
return self.get_pattern_abundance(elem)
if kind == "reference":
return self.get_reference_abundance(elem)
raise ValueError(f"Unknown abundance view {kind!r}")
def _view_set(self, kind, elem, value):
if kind == "A":
self.set_A(elem, value)
return
if kind == "xh":
self.set_xh(elem, value)
return
if kind == "xm":
self.set_xm(elem, value)
return
if kind == "pattern":
self.set_pattern_abundance(elem, value)
return
if kind == "reference":
raise TypeError("The abundance reference view is read-only")
raise ValueError(f"Unknown abundance view {kind!r}")
def _set_reference_metadata(self, pattern, name=None, is_solar=False):
self._reference_pattern = np.array(pattern, dtype=float, copy=True)
self._reference_name = name
self._reference_is_solar = bool(is_solar)
@property
def pattern(self):
"""Mutable mapping view of the current internal abundance pattern."""
return _AbundanceView(self, "pattern")
@property
def A(self):
"""Mutable mapping view of abundances used in synthesis (H=12 scale)."""
return _AbundanceView(self, "A")
@property
def xh(self):
"""Mutable mapping view of [X/H] relative to the reference pattern."""
return _AbundanceView(self, "xh")
@property
def xm(self):
"""Mutable mapping view of [X/M]_PySME relative to the reference pattern."""
return _AbundanceView(self, "xm")
@property
def reference(self):
"""Read-only mapping view of the fixed abundance reference pattern."""
return _AbundanceView(self, "reference")
[docs]
def set_pattern_by_name(self, pattern_name):
"""Set the abundance pattern to one of the predefined options
Parameters
----------
pattern_name : str
Name of the predefined option to use. One of:
'grevesse2007', 'asplund2009', 'asplund2021', 'asplund2005',
'lodders2003', 'anders1989', 'grevesse1996', 'grevesse1998', ,'lodders2010',
'empty'
Raises
------
ValueError
If an undefined pattern_name was given
"""
self.type = "H=12"
self.citation_info = _citation_atomic_weights + "\n"
if pattern_name.lower() in ["anders1989"]:
self._pattern = np.array(_anders1989, dtype=float)
self.citation_info += _citation_anders1989
elif pattern_name.lower() in ["grevesse1996"]:
self._pattern = np.array(_grevesse1996, dtype=float)
self.citation_info += _citation_grevesse1996
elif pattern_name.lower() in ["grevesse1998"]:
self._pattern = np.array(_grevesse1998, dtype=float)
self.citation_info += _citation_grevesse1998
elif pattern_name.lower() in ["asplund2005"]:
self._pattern = np.array(_asplund2005, dtype=float)
self.citation_info += _citation_asplund2005
elif pattern_name.lower() in ["grevesse2007", "solar"]:
self._pattern = np.array(_grevesse2007, dtype=float)
self.citation_info += _citation_grevesse2007
elif pattern_name.lower() in ["asplund2009"]:
self._pattern = np.array(_asplund2009, dtype=float)
self.citation_info += _citation_asplund2009
elif pattern_name.lower() in ["asplund2021"]:
self._pattern = np.array(_asplund2021, dtype=float)
self.citation_info += _citation_asplund2021
elif pattern_name.lower() == "lodders2003":
self._pattern = np.array(_lodders2003, dtype=float)
self.citation_info += _citation_lodders2003
elif pattern_name.lower() == "lodders2010":
self._pattern = np.array(_lodders2010, dtype=float)
self.citation_info += _citation_lodders2010
elif pattern_name.lower() == "empty":
self._pattern = self.empty_pattern()
else:
raise ValueError(
f"Got abundance pattern name {pattern_name}. It should be one of: "
"'grevesse2007' (or 'solar'), 'asplund2009', 'asplund2021', "
"'asplund2005', 'lodders2003', 'lodders2010', 'anders1989', "
"'grevesse1996', 'grevesse1998', or 'empty'."
)
self._set_reference_metadata(
self._pattern,
name=pattern_name,
is_solar=pattern_name.lower() != "empty",
)
[docs]
def set_pattern_by_value(self, pattern, type, update_reference=True):
self._pattern = self.fromtype(pattern, type, raw=True)
self.type = type
if update_reference:
self._set_reference_metadata(self._pattern, name=None, is_solar=False)
[docs]
def update_pattern(self, updates):
"""Update the abundance pattern for several elements at once
The abundance is first converted into the initially specified format,
before being converted back to the internal format
Parameters
----------
updates : dict{str:float}
the elements to update
Raises
------
KeyError
If any of the element keys is not valid
"""
pattern = self.get_pattern(type=self.type, raw=True)
for key in updates:
pos = self._get_index(key)
pattern[pos] = updates[key]
self.set_pattern_by_value(pattern, self.type, update_reference=False)
[docs]
def get_pattern(self, type=None, raw=False):
"""
Transform the specified abundance pattern from type used
internally by SME to the requested type. Valid abundance pattern
types are: 'sme', 'n/nTot', 'n/nH', 'H=12'
Parameters
----------
type : str
The pattern format to retrieve the pattern as. Defaults to the
original input format.
raw : bool
If True will return the pattern as a numpy array, with indices as defined in elem dict.
Otherwise the return value is a dictionary, with the elements as keys.
"""
if type is None:
type = self.type
return self.totype(self._pattern, type, raw=raw)
[docs]
def get_element(self, elem, type=None):
if type is None:
type = self.type
pattern = self(type, raw=True)
i = self._get_index(elem)
return pattern[i]
[docs]
def empty_pattern(self):
"""Return an abundance pattern with value None for all elements."""
pattern = np.full(len(elements), np.nan)
pattern[0] = 0
return pattern
[docs]
def to_dict(self):
data = {
"monh": self.monh,
"type_internal": self._type_internal,
"type": self.type,
"citation_info": self.citation_info,
"data": self._pattern,
"reference_pattern": self._reference_pattern,
"reference_name": self._reference_name,
"reference_is_solar": self._reference_is_solar,
}
return data
[docs]
@classmethod
def from_dict(cls, data):
obj = cls(
monh=data["monh"],
pattern=data["data"],
type=data["type_internal"],
citation_info=data["citation_info"],
)
obj.type = data["type"]
obj._reference_pattern = np.array(
data.get("reference_pattern", obj._pattern), dtype=float, copy=True
)
obj._reference_name = data.get("reference_name")
obj._reference_is_solar = bool(data.get("reference_is_solar", False))
return obj
def _save(self):
header = {
"monh": self.monh,
"type_internal": self._type_internal,
"type": self.type,
"citation_info": self.citation_info,
"reference_pattern": self._reference_pattern.tolist(),
"reference_name": self._reference_name,
"reference_is_solar": self._reference_is_solar,
}
data = self._pattern
ext = BinaryDataExtension(header, data)
return ext
@classmethod
def _load(cls, ext: BinaryDataExtension):
header = ext.header
pattern = ext.data
abund = cls(
monh=header["monh"],
pattern=pattern,
type=header["type"],
citation_info=header["citation_info"],
)
abund._reference_pattern = np.array(
header.get("reference_pattern", pattern), dtype=float, copy=True
)
abund._reference_name = header.get("reference_name")
abund._reference_is_solar = bool(header.get("reference_is_solar", False))
return abund
def _save_v1(self, file, folder="abund"):
"""Save the data to a file handler"""
if folder != "" or folder[-1] != "/":
folder += "/"
monh = float(self.monh) if self.monh is not None else None
info = {
"format": self.type,
"monh": monh,
"citation_info": self.citation_info,
"reference_name": self._reference_name,
"reference_is_solar": self._reference_is_solar,
}
file.writestr(f"{folder}info.json", json.dumps(info))
b = io.BytesIO()
np.save(b, self.get_pattern(raw=True))
file.writestr(f"{folder}pattern.npy", b.getvalue())
b = io.BytesIO()
np.save(b, self._reference_pattern)
file.writestr(f"{folder}reference_pattern.npy", b.getvalue())
@staticmethod
def _load_v1(file, names, folder=""):
"""Load the data from a file handler"""
for name in names:
if name.endswith("info.json"):
info = file.read(name)
info = json.loads(info)
abund_format = info["format"]
monh = info["monh"]
citation_info = info.get("citation_info", _citation_atomic_weights)
elif name.endswith("reference_pattern.npy"):
b = io.BytesIO(file.read(name))
reference_pattern = np.load(b)
elif name.endswith("pattern.npy"):
b = io.BytesIO(file.read(name))
pattern = np.load(b)
abund = Abund(
monh=monh,
pattern=pattern,
type=abund_format,
citation_info=citation_info,
)
abund._reference_pattern = np.array(
locals().get("reference_pattern", abund._pattern), dtype=float, copy=True
)
abund._reference_name = info.get("reference_name")
abund._reference_is_solar = bool(info.get("reference_is_solar", False))
return abund
[docs]
@staticmethod
def solar():
"""Return solar abundances of Grevesse 2007"""
solar = Abund(pattern="solar", monh=0)
return solar
