[Numpy-discussion] Nested recarrays with subarrays and loadtxt: a bug in loadtxt?
Fernando Perez
fperez.net@gmail....
Wed May 27 16:53:20 CDT 2009
Howdy,
I'm wondering if the code below illustrates a bug in loadtxt, or just
a 'live with it' limitation.
I'm inlining it for ease of discussion, but the same code is attached
to ensure that anyone willing to look at this can just download and
run without pasting/whitespace issues.
The code is, I hope, sufficiently commented to explain the problem in
full detail.
Thanks for any input!
Cheers,
f
###
"""Simple illustration of nested record arrays.
Note: possible numpy.loadtxt bug?"""
from StringIO import StringIO
import numpy as np
from numpy import array, dtype, loadtxt, recarray
# Consider the task of loading data that is stored in plain text in a file such
# as the string below, where the last block of numbers is meant to be
# interpreted as a single 2x3 int array, whose field name in the resulting
# structured array will be 'block'.
txtdata = StringIO("""
# name x y block - 2x3 ints
aaaa 1.0 8.0 1 2 3 4 5 6
aaaa 2.0 7.4 2 11 22 3 4 5 6
bbbb 3.5 8.5 3 0 22 44 5 6
aaaa 6.4 4.0 4 1 3 33 54 65
aaaa 8.8 4.1 5 5 3 4 44 77
bbbb 5.5 9.1 6 3 4 5 0 55
bbbb 7.7 8.5 7 2 3 4 5 66
""")
# We make the dtype for it:
dt = dtype(dict(names=['name','x','y','block'],
formats=['S4',float,float,(int,(2,3))]))
# And we load it with loadtxt and make a recarray version for convenience
data = loadtxt(txtdata,dt)
rdata = data.view(recarray)
# Unfortunately, if we look at the block data, it repeats the first number
# found. This seems to be a loadtxt bug:
# In [176]: rdata.block[0,1]
# Out[176]: array([1, 1, 1]) # we'd expect array([4, 5, 6])
if np.any(rdata.block[0,1] != array([4, 5, 6])):
print 'WARNING: loadtxt bug??'
# A workaround can be used by doing a second pass on the file, loading the
# columns corresponding to the block as plain ints and doing a reassignment of
# that data into the original data.
# Rewind the data and reload only the 'block' of ints:
txtdata.seek(0)
block_data = loadtxt(txtdata,int,usecols=range(3,9))
# Let's work with a copy of the original so we can compare interactively...
rdata2 = rdata.copy()
# We assign to the block field in our real array the block_data one,
# appropriately reshaped
rdata2.block[:] = block_data.reshape(rdata.block.shape)
# Same check as before, with the new one
if np.any(rdata2.block[0,1] != array([4, 5, 6])):
print 'WARNING: loadtxt bug??'
else:
print 'Second pass - data loaded OK.'
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