numpy - Read text file only for certain rows to split up file in Python -


i loading text file using np.loadtxt , have python split in four. copy paste each set of data different text files , np.loadtxt each text file, i'm going have hundreds of times way time consuming.

here shortened version of text file. i'd have python read first number (0.6999) , discard it, read 5 following rows of values , assign variable names each column, , next 5 rows variables each column again, , on.

is there way tell python maybe np.loadtext row 1, row 2 6, 7 12 etc?

   0.699999988    1    0.2000    0.0618    2    0.2500    0.0417    3    0.3000    0.0371    4    0.3500    0.0390    5    0.4500    0.0761     670.0000  169.4000 6.708e-09     635.0001  169.1806 1.584e-08     612.9515  168.6255 2.724e-08     591.2781  168.2719 4.647e-08   670.00  0.0e+00  0.0e+00  0.0e+00  0.0e+00  0.0e+00  0.0e+00  0.0e+00   635.00  9.8e-07  4.2e-07  2.1e-07  1.2e-07  4.4e-08  1.8e-08  1.4e-08   612.95  6.0e-06  3.5e-06  2.1e-06  1.3e-06  4.7e-07  1.8e-07  1.4e-07   591.28  2.2e-05  1.3e-05  7.7e-06  4.9e-06  1.8e-06  6.6e-07  5.0e-07   569.98  8.3e-05  5.0e-05  2.8e-05  1.8e-05  6.4e-06  2.4e-06  1.8e-06   549.06  3.0e-04  1.8e-04  1.0e-04  6.2e-05  2.3e-05  8.4e-06  6.4e-06   528.51  7.8e-04  5.0e-04  2.8e-04  1.7e-04  6.2e-05  2.3e-05  1.8e-05   508.34  1.6e-03  1.0e-03  5.8e-04  3.4e-04  1.3e-04  4.9e-05  3.7e-05

here using 3 different text files:

altvall,t,pp= np.loadtxt('file1.txt',usecols = (0,1,2),unpack=true) # load text file  tau1,tau2,tau3,tau4,tau5,tau6,tau7 = np.loadtxt('file2.txt',usecols = (1,2,3,4,5,6,7),unpack=true) # load text file  wvln,alb = np.loadtxt('file3.txt',usecols = (1,2),unpack=true) # load text file

now want similar without splitting text file different parts.

a simple way use itertools.izip_longest group rows of input file groups of 5. key following:

for rows in izip_longest(*[file_object]*n):     # rows tuple of n consecutive rows     # rows

full example:

import numpy np itertools import izip_longest  data = [] open(filehandle, 'r') fin:     fin.next() # skip first line     rows in izip_longest(*[fin]*5): # read fin 5 rows @ time         rows = [map(float, r.strip().split()) r in rows]         data.append(np.array(rows))

this yields list of 5xn arrays:

>>> print data [array([[ 1.    ,  0.2   ,  0.0618],        [ 2.    ,  0.25  ,  0.0417],        [ 3.    ,  0.3   ,  0.0371],        [ 4.    ,  0.35  ,  0.039 ],        [ 5.    ,  0.45  ,  0.0761]]),  array([[  6.70000000e+02,   1.69400000e+02,   6.70800000e-09],        [  6.35000100e+02,   1.69180600e+02,   1.58400000e-08],        [  6.12951500e+02,   1.68625500e+02,   2.72400000e-08],        [  5.91278100e+02,   1.68271900e+02,   4.64700000e-08],        [  5.69980100e+02,   1.68055300e+02,   7.85900000e-08]]),  array([[  6.70000000e+02,   0.00000000e+00,   0.00000000e+00,           0.00000000e+00,   0.00000000e+00,   0.00000000e+00,           0.00000000e+00,   0.00000000e+00],        [  6.35000000e+02,   9.80000000e-07,   4.20000000e-07,           2.10000000e-07,   1.20000000e-07,   4.40000000e-08,           1.80000000e-08,   1.40000000e-08],        [  6.12950000e+02,   6.00000000e-06,   3.50000000e-06,           2.10000000e-06,   1.30000000e-06,   4.70000000e-07,           1.80000000e-07,   1.40000000e-07],        [  5.91280000e+02,   2.20000000e-05,   1.30000000e-05,           7.70000000e-06,   4.90000000e-06,   1.80000000e-06,           6.60000000e-07,   5.00000000e-07],        [  5.69980000e+02,   8.30000000e-05,   5.00000000e-05,           2.80000000e-05,   1.80000000e-05,   6.40000000e-06,           2.40000000e-06,   1.80000000e-06]])]

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