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latex_lick_table.py
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latex_lick_table.py
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# -*- coding: utf-8 -*-
"""
Created on Thu Jan 30 17:49:32 2014
@author: cbarbosa
Make LateX table for the population paper.
"""
import os
from re import split
import numpy as np
from config import *
from mcmc_model import get_model_lims
def ra2str(ra):
ra /= 15.
hours = ra.astype(int)
minutes = ((ra - hours) * 60.)
minutes = minutes.astype(int)
seconds = (3600*ra - hours * 3600 - minutes * 60)
seconds = np.around(seconds, 2)
rastr = []
for h,m,s in zip(hours, minutes, seconds):
if s < 10:
sfill = "0"
else:
sfill = ""
rastr.append(r"{0}:{1}:{3}{2}".format(h, m, s, sfill))
return rastr
def dec2str(dec):
sign=2*np.sign(dec) - 1
signstr = []
for sg in sign:
signstr.append("+" if sg == 1 else "-")
dec = np.abs(dec)
hours = dec.astype(int)
minutes = (dec - hours) * 60
minutes = minutes.astype(int)
seconds = (3600*dec - hours * 3600 - minutes * 60)
seconds = np.around(seconds, 2)
decstr = []
for sig, h,m,s in zip(signstr, hours, minutes, seconds):
if s < 10:
sfill = "0"
else:
sfill = ""
decstr.append(r"{3}{0}:{1}:{4}{2}".format(h, m, s, sig, sfill))
return decstr
def val2str(s, serr):
""" Convert value and error to string in LateX."""
vals = []
for v, verr in zip(s, serr):
if np.isnan(v) or np.isnan(verr):
vals.append(r"--")
elif np.log10(verr) < 1:
sigfig = -int(np.floor(np.log10(verr)))
newerr = np.around(verr, sigfig)
if newerr == np.power(10., -sigfig):
sigfig += 1
newerr = np.around(verr, sigfig)
v = np.around(v, sigfig)
vals.append(r"${0}\pm{1}$".format(v, newerr))
else:
vals.append(r"${0}\pm{1}$".format(int(np.around(v)),
int(np.around(verr))))
return vals
def pm_string(pp, ppm, ppp):
table = []
for (p, pm, pp) in zip(pp, ppm, ppp):
line = []
for i in range(len(p)):
s = r"${0:.2f}_{{-{1:.2f}}}^{{+{2:.2f}}}$".format(p[i], pm[i], pp[i])
line.append(s)
table.append(" & ".join(line))
return table
def test_output():
outcds = os.path.join(home, spectype, "table1.dat")
with open(outcds) as f:
table = f.readlines()
lims = [[262,271]]
for cols in lims:
v = [x[cols[0]-1:cols[1]-1] for x in table]
print v
if __name__ == "__main__":
spectype = "single2"
table = os.path.join(home, spectype, "results.tab")
spec = np.genfromtxt(table, dtype=None, usecols=(0,))
ids = [x.split("n3311")[-1].replace(".fits", "").replace("_", " ") for x \
in spec]
sns = np.loadtxt(table, usecols=(14,))
rs, pas = np.loadtxt(table, usecols=(3,4)).T
# idx = np.where(sns > sn_cut)[0]
cols = np.array([39,41,47,49,51,53,55])
model_table = os.path.join(tables_dir, "models_thomas_2010.dat")
lims, ranges = get_model_lims(model_table)
idx = np.array([12,13,16,17,18,19])
cols2 = np.array([69,72,75])
lims = lims[idx]
data = np.loadtxt(table, usecols=cols)
errs = np.loadtxt(table, usecols=cols+1)
pop = np.loadtxt(table, usecols=cols2)
popm = pop - np.loadtxt(table, usecols=cols2 + 1)
popp = np.loadtxt(table, usecols=cols2 + 2) - pop
pstring = pm_string(pop, popm, popp)
for i in range(len(data)):
for j in range(len(lims)):
if data[i,j] < lims[j,0] or data[i,j] > lims[j,1]:
data[i,j] = np.nan
results = []
cds_table = []
for iid, d, err, r, pa, sn, p in zip(ids, data, errs, rs, pas, sns, pstring):
err[np.isnan(d)] = np.nan
cols2_4 = [r, pa, sn]
cols2_4 = ["{0:.1f}".format(x) for x in cols2_4]
cols5_11 = [item for sublist in zip(d,err) for item in sublist]
cols5_11 = ["{0:.2f}".format(x) for x in cols5_11]
cols12_14 = p.replace("$", "").replace("{", "").replace("}","").split("&")
cols12_14 = [x.split("_") for x in cols12_14]
cols12_14 = [item for sublist in cols12_14 for item in sublist]
cols12_14 = [x.split("^") for x in cols12_14]
cols12_14 = [item for sublist in cols12_14 for item in sublist]
ascii = cols2_4 + cols5_11 + cols12_14
ascii = ["{0:9s}".format(iid.replace(" ", "").strip())] + ["{0:>10s}".format(x) for x in ascii]
cds_table.append("".join(ascii))
s = "{0} & {1:.1f} & {2:.1f} & {3:.1f} & ".format(iid, r, pa, sn) + \
" & ".join(val2str(d, err)) + " & " + p
results.append(s)
output = os.path.join(home, spectype, "lick.tex")
print output
results.sort()
with open(output, "w") as f:
f.write("\\\\\n".join(results) + "\\\\")
output2 = os.path.join(home, spectype, "table1.dat")
with open(output2, "w") as f:
f.write("\n".join(cds_table))
test_output()