#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Nov 9 15:52:15 2021
@author: yangyangli
"""
import numpy as np
import h5py
import glob
[docs]def get_keys_and_atmos_pars(ewlibpath, stellar_type):
"""
Get keys of the EW library for corresponding combinations of atmospheric
stellar parameters, given the type of star.
Parameters
----------
ewlibpath : str
The path for the libary of EW, it must be a h5 file
stellar_type : str
The stellar type of your star, like:
{spectral type, e.g. F, G, K}/{giant or subgiant or dwarf}/{metal_rich or metal_poor or very_metal_poor} or
the estimation of your atmospheric parameters in such form:
{{T_low}_{T_high}/{logg_low}_{logg_high}/{feh_low}_{feh_high}}
Returns
-------
keys : list of strs
Keys of corresponding combinations of atmospheric
stellar parameters
ini_cents : list
the list of stellar parameters given the range defined by the stellar type
the shape of the list is (N_selected_gridpoints, 4)
"""
from ..utils import generate_ranges
def visitor_func(name, node):
if isinstance(node, h5py.Group):
pass
elif isinstance(node, h5py.Dataset):
ini_cent = [float("".join(c for c in node.name.split("/")[i] if not c.isalpha())) for i in range(-5,-1)]
if all([lower[i] <= ini_cent[i] <= upper[i] for i in range(len(ini_cent))]):
allkeys.append(node.name.replace("/table", ''))
ini_cents.append(ini_cent)
f = h5py.File(ewlibpath, 'r')
allkeys = []
ini_cents = []
Teff_range, logg_range, feh_range = generate_ranges(stellar_type)
upper = [Teff_range[1], logg_range[1], feh_range[1], np.inf]
lower = [Teff_range[0], logg_range[0], feh_range[0], -np.inf]
f.visititems(visitor_func)
keys = allkeys
ini_cents = ini_cents
f.close()
return keys, ini_cents
[docs]def find_closest_model(wl, ep, ele, search_path, interp_method, interpolation, tarfile=None):
"""
Find closest interpolated model under designated direcctory
Parameters
----------
wl : float
wavelength of line
ep : float
excitation potential of line
ele : str
"FeI" or "FeII"
search_path : str
designated directory
interp_method: str
"[2-5]" for multivariate polynomial interpolation
interpolation: bool
True: use interpolated GCOG
False: get GCOG from EW library
tarfile: tarfile.Tarfile or None
if None, search closest model in a directory
else search in a tarfile
Returns
-------
list:
length > 0 : closest model found;
length = 0 : can't find closest model
"""
for w in [wl-0.01, wl, wl+0.01]:
for e in [ep-0.01, ep, ep+0.01]:
line = format(w, ".2f") +"_"+ format(e, ".2f") +"_" + ele
if interpolation:
fname = glob.glob(search_path + line + "_" + interp_method + ".sav")
else:
if tarfile == None:
fname = glob.glob(search_path + line + "_" + interp_method + ".sav")
else:
names = tarfile.getnames()
fname = list(filter(lambda x: search_path + line in x, names))
if len(fname) > 0:
return fname
return fname
