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pNbody/pNbody/SSP/libvazdekis.py
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libvazdekis.py
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#!/usr/bin/env python
import sys,os
import types,string
import scipy
import scipy.interpolate
from numpy import *
from libSSPluminosity import SSPLuminosities
#####################################################
def read_ascii(file,columns=None,lines=None,dtype=float,skipheader=False,cchar='#'):
#####################################################
"""[X,Y,Z] = READ('FILE',[1,4,13],lines=[10,1000])
Read columns 1,4 and 13 from 'FILE' from line 10 to 1000
into array X,Y and Z
file is either fd or name file
"""
def RemoveComments(l):
if l[0]==cchar:
return None
else:
return l
def toNumList(l):
return map(dtype,l)
if type(file) != types.FileType:
f = open(file,'r')
else:
f = file
# read header while there is one
while 1:
fpos = f.tell()
header = f.readline()
if header[0] != cchar:
f.seek(fpos)
header = None
break
else:
if skipheader:
header = None
else:
# create dict from header
header = string.strip(header[2:])
elts = string.split(header)
break
'''
# read header if there is one
header = f.readline()
if header[0] != cchar:
f.seek(0)
header = None
else:
if skipheader:
header = None
else:
# create dict from header
header = string.strip(header[2:])
elts = string.split(header)
'''
# now, read the file content
lines = f.readlines()
# remove trailing
lines = map(string.strip, lines)
# remove comments
#lines = map(RemoveComments, lines)
# split
lines = map(string.split, lines)
# convert into float
lines = map(toNumList, lines)
# convert into array
lines = array(map(array, lines))
# transpose
lines = transpose(lines)
if header != None:
iobs = {}
i = 0
for elt in elts:
iobs[elt]=i
i = i + 1
vals = {}
for key in iobs.keys():
vals[key] = lines[iobs[key]]
return vals
# return
if columns == None:
return lines
else:
return lines.take(axis=0,indices=columns)
class VazdekisLuminosities(SSPLuminosities):
def Read(self):
'''
read file and create a data table
'''
self.data = read_ascii(self.file,cchar='#',skipheader=True)
def CreateMatrix(self):
'''
from data extract
metalicites (zs)
ages (ages)
and ML (vs)
'''
zs = self.data[1,:]
ages = self.data[2,:]
mls = self.data[20,:]
# create borders
Zs = [-2.3152,-1.7129,-1.3146,-0.7052,-0.3960,0.0000,0.2223]
Ages = compress(Zs[1]==zs,ages)
MatLv = zeros((len(Zs),len(Ages)))
for iZ,Z in enumerate(Zs):
zs,ages,mls
c = (zs==Z)
age = compress(c,ages)
ml = compress(c,mls)
Lv = 1/ml
if len(age)<len(Ages):
n = len(Ages)-len(age)
age = concatenate((Ages[:n],age))
Lv = concatenate((1e-10*ones(n),Lv))
MatLv[iZ,:] = Lv
self.MatLv = MatLv
self.Ages = Ages
self.Zs = Zs
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