weird interaction: pickle, numpy, matplotlib.hist [sort() method problem?]

Community matplotlib-users
1

OK, I think I’ve managed to track the problem down a bit further:

the sort() method is failing for arrays pickled on another machine!

That is, it’s definitely not sorting the array, but changing to a very strange order (neither the way it started nor sorted).

Again, the array seems to otherwise behave fine (indeed, it even satisfies all(a==a1) for a pair that behave differently in this circumstance).

Hmmm…

A

···

On 4/5/06, Andrew Jaffe <a.h.jaffe@…287…> wrote:

Hi All,

I’ve encountered a strange problem: I’ve been running some python code
on both a linux box and OS X, both with python 2.4.1 and the latest
numpy and matplotlib from svn.

I have found that when I transfer pickled numpy arrays from one machine

to the other (in either direction), the resulting data looks all right
(i.e., it is a numpy array of the correct type with the correct values
at the correct indices), but it seems to produce the wrong result in (at

least) one circumstance: matplotlib.hist() gives the completely wrong
picture (and set of bins).

This can be ameliorated by running the array through
arr=numpy.asarray(arr, dtype=numpy.float64)
but this seems like a complete kludge (and is only needed when you do

the transfer between machines).

I’ve attached a minimal code that exhibits the problem: try
test_pickle_hist.test(write=True)
on one machine, transfer the output file to another machine, and run

    test_pickle_hist.test(write=False)

on another, and you should see a very strange result (and it should be
fixed if you set asarray=True).

Any ideas?

Andrew

import cPickle
import numpy

import pylab

def test(write=True,asarray=False):

a = numpy.linspace(-3,3,num=100)

if write:
    f1 = file("a.cpkl", 'w')
    cPickle.dump(a, f1)
    f1.close

()

f1 = open("a.cpkl", 'r')
a1 = cPickle.load(f1)
f1.close()

pylab.subplot(1,2,1)
h = pylab.hist(a)

if asarray:
    a1 = numpy.asarray(a1, dtype=numpy.float64

)

pylab.subplot(1,2,2)
h1 = pylab.hist(a1)

return a, a1