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ptools/build/lib/Ptools/io.py
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io.py
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# standard modules
import os,sys,string,copy,types
from numpy import *
import pickle
#####################################################
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)
#####################################################
def old_read_ascii(file,columns,lines=None,dtype=float):
#####################################################
"""[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
"""
try: import mmap
except: pass
if type(file) != types.FileType:
f = open(file,'r+')
else:
f = file
f.seek(0,2)
fsize = f.tell()
f.seek(0,0)
start = 1
end = 0
numcols=len(columns)
if lines is None:
lines = [start,end]
elif len(lines) != 2:
raise "lines!=[start,end]"
[start,end] = map(int,lines)
start = start - 1
nl = len(f.readlines())
f.seek(0)
if (end == 0) or (end > nl):
end = nl
numlines = end - start
block = 65536 # chunk to read, in bytes
data = mmap.mmap(f.fileno(), fsize)
for i in range(start):
junk = data.readline()
numcols = len(columns)
if dtype == int:
a = zeros((numlines,numcols), 'l')
else:
a = zeros((numlines,numcols), 'd')
i = 0
line = data.readline()
while line and ( i < numlines):
d = array(map(dtype,string.split(line)))
a[i,:] = take(d,columns)
line = data.readline()
i = i + 1
data.close()
if type(file) != types.FileType:
f.close()
b = []
for i in range(numcols):
b.append(a[:,i])
del a
return b
##########################################################################################################
#
# hdf5 routines
#
##########################################################################################################
try:
from tables import *
is_hdf5 = True
except:
is_hdf5 = False
def info_hdf5(file,all=False):
if not is_hdf5:
raise "function info_hdf5 needs tables"
h5file = openFile(file, mode = "r")
for elt in h5file.root._v_attrs._f_list("user"):
val = getattr(h5file.root._v_attrs,elt)
print "%s : %s"%(elt,val.__repr__())
print
print
for elt in h5file.root._f_iterNodes():
vec = elt.read()
print "-- %s -- "%(elt.name)
print "len %s : %s"%(elt.name,len(vec).__repr__())
print "shape %s : %s"%(elt.name,vec.shape.__repr__())
if all:
print "%s pos[0] : %s"%(elt.name,vec[0].__repr__())
print "%s pos[-1] : %s"%(elt.name,vec[-1].__repr__())
print
def read_hdf5(file):
if not is_hdf5:
raise "function read_hdf5 needs tables"
h5file = openFile(file, mode = "r")
data = {}
for elt in h5file.root._f_iterNodes():
data[elt.name] = elt.read()
for elt in h5file.root._v_attrs._f_list("user"):
data[elt] = getattr(h5file.root._v_attrs,elt)
return data
def write_hdf5(file,data,title='hdf5'):
if not is_hdf5:
raise "function write_hdf5 needs tables"
h5file = openFile(file, mode = "w", title = title)
for elt in data.keys():
if type(data[elt])==ndarray:
h5file.createArray('/', elt, data[elt],"")
else:
setattr(h5file.root._v_attrs,elt,data[elt])
h5file.flush()
h5file.close()
#####################################################
def write_dmp(file,data):
#####################################################
'''
Write a dmp (pickle) file. In other word,
dump the data object.
Parameters
----------
file : the path to a file
data : a pickable python object
Examples
--------
>>> x = {'a':1,'b':2}
>>> io.write_dmp('/tmp/afile.dmp',x)
'''
f = open(file,'w')
pickle.dump(data, f)
f.close()
#####################################################
def read_dmp(file):
#####################################################
'''
Read a dmp (pickle) file.
Parameters
----------
file : the path to a file
Returns
-------
data : a python object
Examples
--------
>>> x = {'a':1,'b':2}
>>> io.write_dmp('/tmp/afile.dmp',x)
>>> y = io.read_dmp('/tmp/afile.dmp')
>>> y
{'a': 1, 'b': 2}
'''
f = open(file,'r')
data = pickle.load(f)
f.close()
return data
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