numpy fromfile and structured arrays

Question

I'm trying to use numpy.fromfile to read a structured array (file header) by passing in a user defined data-type. For some reason, my structured array elements are coming back as 2-d Arrays instead of flat 1D arrays:

headerfmt='20i,20f,a80'
dt = np.dtype(headerfmt)
header = np.fromfile(fobj,dtype=dt,count=1)
ints,floats,chars = header['f0'][0], header['f1'][0], header['f2'][0]
#                                ^?               ^?               ^?

How do I modify headerfmt so that it will read them as flat 1D arrays?

Joe Kington · Accepted Answer · 2013-06-07 17:52:47Z

2

If the count will always be 1, just do:

header = np.fromfile(fobj, dtype=dt, count=1)[0]

You'll still be able to index by field name, though the repr of the array won't show the field names.

For example:

import numpy as np

headerfmt='20i,20f,a80'
dt = np.dtype(headerfmt)

# Note the 0-index!
x = np.zeros(1, dtype=dt)[0]

print x['f0'], x['f1'], x['f2']
ints, floats, chars = x

It may or may not be ideal for your purposes, but it's simple, at any rate.

answered Jun 7, 2013 at 17:52

Joe Kington

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3 Comments

mgilson Over a year ago

Ahh, I see ... fromfile is giving me an array of count record arrays then? And I'm essentially slicing down a different axis when I do header['f0'].

Joe Kington Over a year ago

Yep! Or more precisely, in a structured array, every element is actually a sequence. fromfile with count=1 will always return a length-1 array, and in this case, the first and only element in the array is the sequence you're wanting.

mgilson Over a year ago

Excellent. If you keep answering all my questions, my boss just might offer you my job ... :-P

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