def plotlines(z, ax, atmos=None, lines=None, labels=False, ls="dotted", color="k", trim=False, fontsize=10, **kwargs):
""" Draw vertical dotted lines showing expected positions of
absorption and emission lines, given a redshift.
Parameters
----------
atmos : list of float pairs, or True (None)
Regions of atmospheric absorption to plot. If True, it uses an
internal list of regions.
lines : stuctured array, optional
If given, it must be a record array with fields 'name' and 'wa'.
Returns the mpl artists representing the lines.
"""
if lines is None:
lines = readtxt(DATAPATH + "linelists/galaxy_lines", names="wa,name,select")
else:
lines = np.rec.fromrecords([(l["name"], l["wa"]) for l in lines], names="name,wa")
autoscale = ax.get_autoscale_on()
if autoscale:
ax.set_autoscale_on(False)
artists = []
w0, w1 = ax.get_xlim()
wa = lines.wa * (z + 1)
if trim:
c0 = between(wa, w0, w1)
wa = wa[c0]
lines = lines[c0]
artists.append(axvlines(wa, ax=ax, ls=ls, color=color, **kwargs))
if labels:
for i in range(3):
for w, l in zip(wa[i::3], lines[i::3]):
if not (w0 < w < w1) and trim:
continue
# name = l.name + '%.2f' % l.wa
name = l.name
artists.append(
puttext(
w,
0.7 + i * 0.08,
name,
ax,
xcoord="data",
alpha=1,
fontsize=fontsize,
rotation=90,
ha="right",
color=color,
)
)
if atmos:
if atmos == True:
atmos = None
artists.append(plotatmos(ax, atmos=atmos))
if autoscale:
ax.set_autoscale_on(True)
return artists
def read_pc_all():
""" Principle components (eigenvectors of the covariance matrix)
for Suzuki et al. (2005) QSO spectra from 1020 to 1600 Angstroms.
"""
path = os.path.abspath(os.path.dirname(__file__))
filename = path + '/PCAcont/Suzuki05/tab3.txt'
names = 'wa,mu,musig,e1,e2,e3,e4,e5,e6,e7,e8,e9,e10'
p = readtxt(filename, skip=23, names=names)
pc = np.array([p['e%i' % i] for i in range(1, 11)])
return p.wa, p.mu, pc
def read_pc_all():
""" Principle components (eigenvectors of the covariance matrix)
for Suzuki et al. (2005) QSO spectra from 1020 to 1600 Angstroms.
"""
path = os.path.abspath(os.path.dirname(__file__))
filename = path + '/PCAcont/Suzuki05/tab3.txt'
names = 'wa,mu,musig,e1,e2,e3,e4,e5,e6,e7,e8,e9,e10'
p = readtxt(filename, skip=23, names=names)
pc = np.array([p['e%i' % i] for i in range(1, 11)])
return p.wa, p.mu, pc
def pca_qso_cont(nspec, seed=None, return_weights=False):
""" Make qso continua using the PCA and weights from N. Suzuki et
al. 2005 and N. Suzuki 2006.
Parameters
----------
nspec : int
Number of spectra to create
Returns
-------
wavelength (shape N), array of spectra [shape (nspec, N)]
Memory use might be prohibitive for nspec > ~1e4.
"""
# read the principle components
filename = DATAPATH + "/PCAcont/Suzuki05/tab3.txt"
names = "wa,mu,musig,e1,e2,e3,e4,e5,e6,e7,e8,e9,e10"
co = readtxt(filename, skip=23, names=names)
# use only the first 7 eigenvetors
eig = [co["e%i" % i] for i in range(1, 8)]
# from Suzuki et al 2006.
csig = np.array([7.563, 3.604, 2.351, 2.148, 1.586, 1.479, 1.137]) # , 0.778, 0.735, 0.673])
# generate weights for each eigenvector
if seed is not None:
np.random.seed(seed)
weights = []
for sig in csig:
temp = np.random.randn(2 * nspec)
# make sure we don't have any very large deviations from the mean
temp = temp[np.abs(temp) < 3][:nspec]
assert len(temp) == nspec
weights.append(temp * sig)
# generate nspec continua. loop over pixels
sp = []
for i in range(len(co.wa)):
sp.append(co.mu[i] + np.sum(w * e[i] for w, e in zip(weights, eig)))
sp = np.transpose(sp)
if return_weights:
return co.wa, sp, weights
else:
return co.wa, sp
It contains the values `tc` and `tc50` for each element, where `tc`
is the condensation temperature in K when condensation begins, and
`tc50` is the temperature when 50% of the element is left in a
gaseous state.
"""
import numpy as np
from utilities import get_data_path
from io import readtxt
from collections import OrderedDict
datapath = get_data_path()
Asolar = OrderedDict(
(t.el, t.A) for t in
readtxt(datapath + 'abundances/SolarAbundance.txt', readnames=1))
cond_temp = readtxt(datapath +
'abundances/CondensationTemperatures.txt',
readnames=1, sep='|')
def calc_abund(X, Y, logNX, logNY):
""" Find the abundance relative to solar given two elements and
their column densities.
Parameters
----------
X, Y : str
Element identifiers (for example 'C', 'Si', 'Mg').
logNX : array_like, shape (N,)
log10 of element X column density in cm^-2.
