Package: python-scipy
Version: 0.10.1+dfsg1-3
Severity: serious
Justification: fails to build from source (but built successfully in the past)
Please see attached a somewhat minimalistic code to reproduce the
problem.
it fails only on s390x -- fine on s390 and any other architecture/port where
pymvpa2 was just built.
Traceback (most recent call last):
File "scipy-fx-failure2.py", line 65, in <module>
1.47441522, 1.78073152, 2.08704783, 2.39336413, 2.69968044]))
File "scipy-fx-failure2.py", line 52, in least_sq_fit
return leastsq(efx, params)
File "/usr/lib/python2.7/dist-packages/scipy/optimize/minpack.py", line 324,
in leastsq
raise errors[info][1](errors[info][0])
TypeError: Improper input parameters.
-- System Information:
Debian Release: wheezy/sid
APT prefers testing
APT policy: (900, 'testing'), (600, 'unstable'), (300, 'experimental'), (100,
'stable')
Architecture: amd64 (x86_64)
Kernel: Linux 3.2.0-2-amd64 (SMP w/2 CPU cores)
Locale: LANG=en_US, LC_CTYPE=en_US.UTF-8 (charmap=UTF-8)
Shell: /bin/sh linked to /bin/bash
Versions of packages python-scipy depends on:
ii libamd2.2.0 1:3.4.0-2
ii libatlas3-base [liblapack.so.3gf] 3.8.4-7
ii libatlas3gf-base 3.8.4-7
ii libblas3 [libblas3gf] 1.2.20110419-5
ii libblas3gf 1.2.20110419-5
ii libc6 2.13-33
ii libgcc1 1:4.7.1-2
ii libgfortran3 4.7.1-2
ii liblapack3 [liblapack3gf] 3.4.1-4
ii liblapack3gf 3.4.1-4
ii libquadmath0 4.7.1-2
ii libstdc++6 4.7.1-2
ii libumfpack5.4.0 1:3.4.0-2
ii python 2.7.3~rc2-1
ii python-numpy [python-numpy-abi9] 1:1.6.2-1
ii python2.6 2.6.8-0.2
ii python2.7 2.7.3~rc2-2.1
Versions of packages python-scipy recommends:
ii g++ [c++-compiler] 4:4.7.1-1
ii g++-4.4 [c++-compiler] 4.4.7-1
iu g++-4.6 [c++-compiler] 4.6.3-8
ii g++-4.7 [c++-compiler] 4.7.1-2
ii python-dev 2.7.3~rc2-1
ii python-imaging 1.1.7-4
Versions of packages python-scipy suggests:
ii python [python-profiler] 2.7.3~rc2-1
-- no debconf information
# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
#
# See COPYING file distributed along with the PyMVPA package for the
# copyright and license terms.
#
### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
"""Misc. functions (in the mathematical sense)"""
__docformat__ = 'restructuredtext'
import numpy as np
from numpy import array
from scipy.optimize import leastsq
def dual_gaussian(x, amp1=1.0, mean1=0.0, std1=1.0,
amp2=1.0, mean2=0.0, std2=1.0):
from scipy.stats import norm
print x
if std1 <= 0 or std2 <= 0:
return np.nan
return (amp1 * norm.pdf(x, mean1, std1)) + (amp2 * norm.pdf(x, mean2, std2))
def least_sq_fit(fx, params, y, x=None, **kwargs):
y = np.asanyarray(y)
if len(y.shape) > 1:
nsamp, ylen = y.shape
else:
nsamp, ylen = (1, len(y))
# contruct matching x-values if necessary
if x is None:
x = np.arange(ylen)
# transform x and y into 1d arrays
if nsamp > 1:
x = np.array([x] * nsamp).ravel()
y = y.ravel()
# define error function
def efx(p):
print "EFX: ", p
err = y - fx(x, *p, **kwargs)
return err
# do fit
return leastsq(efx, params)
if __name__ == '__main__':
print least_sq_fit(dual_gaussian,
(1000, 0.5, 0.1, 1000, 0.8, 0.05),
array([[ 1, 0, 0, 0, 5, 2, 6, 9, 6, 12, 14, 9, 12, 7, 7, 5, 2,
2, 0, 1],
[ 1, 0, 0, 0, 5, 2, 6, 9, 6, 12, 14, 9, 12, 7, 7, 5, 2,
2, 0, 1]]),
array([-3.12032937, -2.81401307, -2.50769676, -2.20138046, -1.89506415,
-1.58874784, -1.28243154, -0.97611523, -0.66979893, -0.36348262,
-0.05716631, 0.24914999, 0.5554663 , 0.8617826 , 1.16809891,
1.47441522, 1.78073152, 2.08704783, 2.39336413, 2.69968044]))
