[SciPy-user] install - floating point exception (scipy-tests)

python@axtom.com python at axtom.com
Thu Apr 27 04:08:46 CDT 2006


Hi all,

I have installed scipy, and have some fp exceptions when running the tests. 
Does anyone else experiment the same thing?

Thanks

--
Jean Pierre


configuration
-----------------
Debian GNU/Linux 3.1
  kernel  2.6
compilers: gcc-3.3.5 and g77-3.3.5 (c++ not installed)
python-2.4.2
blas http://www.netlib.org/blas/blas.tgz -- installation from src
lapack http://www.netlib.org/lapack/lapack.tgz -- installation from src
fftw http://www.fftw.org/fftw-2.1.5.tar.gz -- installation from src
numpy-0.9.6
scipy-0.4.8 (without cluster and weave packages)

output of the tests (by package and by module when there is an exception)
------------------------------------------------------------------

>>> from scipy import integrate;NumpyTest(integrate).test(level=10)
  Found 10 tests for scipy.integrate.quadpack
  Found 1 tests for scipy.integrate
  Found 0 tests for __main__
..Floating point exception

>>> from scipy import fftpack;NumpyTest(fftpack).test(level=10)
  Found 23 tests for scipy.fftpack.basic
  Found 24 tests for scipy.fftpack.pseudo_diffs
  Found 4 tests for scipy.fftpack.helper
  Found 0 tests for __main__

                 Fast Fourier Transform
=================================================
      |    real input     |   complex input
-------------------------------------------------
 size |  scipy  | Numeric |  scipy  | Numeric
-------------------------------------------------
  100 |    0.10 |  N/A   |    0.10 |  N/A    (secs for 7000 calls)
 1000 |    0.08 |  N/A   |    0.12 |  N/A    (secs for 2000 calls)
  256 |    0.17 |  N/A   |    0.19 |  N/A    (secs for 10000 calls)
  512 |    0.23 |  N/A   |    0.31 |  N/A    (secs for 10000 calls)
 1024 |    0.04 |  N/A   |    0.05 |  N/A    (secs for 1000 calls)
 2048 |    0.08 |  N/A   |    0.11 |  N/A    (secs for 1000 calls)
 4096 |    0.07 |  N/A   |    0.13 |  N/A    (secs for 500 calls)
 8192 |    0.19 |  N/A   |    0.57 |  N/A    (secs for 500 calls)
..Warning: Skipping check_djbfft (failed to import FFT)
..
    Multi-dimensional Fast Fourier Transform
===================================================
          |    real input     |   complex input
---------------------------------------------------
   size   |  scipy  | Numeric |  scipy  |  Numeric
---------------------------------------------------
  100x100 |    0.09 |  N/A   |    0.07 |  N/A    (secs for 100 calls)
 1000x100 |    0.09 |  N/A   |    0.08 |  N/A    (secs for 7 calls)
  256x256 |    0.11 |  N/A   |    0.12 |  N/A    (secs for 10 calls)
  512x512 |    0.30 |  N/A   |    0.30 |  N/A    (secs for 3 calls)
.....
       Inverse Fast Fourier Transform
===============================================
      |     real input    |    complex input
-----------------------------------------------
 size |  scipy  | Numeric |  scipy  | Numeric
-----------------------------------------------
  100 |    0.09 |  N/A   |    0.13 |  N/A    (secs for 7000 calls)
 1000 |    0.09 |  N/A   |    0.18 |  N/A    (secs for 2000 calls)
  256 |    0.17 |  N/A   |    0.22 |  N/A    (secs for 10000 calls)
  512 |    0.26 |  N/A   |    0.35 |  N/A    (secs for 10000 calls)
 1024 |    0.04 |  N/A   |    0.07 |  N/A    (secs for 1000 calls)
 2048 |    0.09 |  N/A   |    0.12 |  N/A    (secs for 1000 calls)
 4096 |    0.09 |  N/A   |    0.15 |  N/A    (secs for 500 calls)
 8192 |    0.21 |  N/A   |    0.59 |  N/A    (secs for 500 calls)
.......
Inverse Fast Fourier Transform (real data)
==================================
 size |  scipy  | Numeric
----------------------------------
  100 |    0.12 |  N/A    (secs for 7000 calls)
 1000 |    0.10 |  N/A    (secs for 2000 calls)
  256 |    0.19 |  N/A    (secs for 10000 calls)
  512 |    0.26 |  N/A    (secs for 10000 calls)
 1024 |    0.04 |  N/A    (secs for 1000 calls)
 2048 |    0.08 |  N/A    (secs for 1000 calls)
 4096 |    0.09 |  N/A    (secs for 500 calls)
 8192 |    0.19 |  N/A    (secs for 500 calls)
..Warning: Skipping check_djbfft (failed to import FFT)
..
Fast Fourier Transform (real data)
==================================
 size |  scipy  | Numeric
----------------------------------
  100 |    0.10 |  N/A    (secs for 7000 calls)
 1000 |    0.08 |  N/A    (secs for 2000 calls)
  256 |    0.18 |  N/A    (secs for 10000 calls)
  512 |    0.24 |  N/A    (secs for 10000 calls)
 1024 |    0.03 |  N/A    (secs for 1000 calls)
 2048 |    0.07 |  N/A    (secs for 1000 calls)
 4096 |    0.07 |  N/A    (secs for 500 calls)
 8192 |    0.17 |  N/A    (secs for 500 calls)
..Warning: Skipping check_djbfft (failed to import FFT: No module named FFT)
.
Differentiation of periodic functions
=====================================
 size  |  convolve |    naive
-------------------------------------
   100 |      0.03 |      0.23  (secs for 1500 calls)
  1000 |      0.03 |      0.21  (secs for 300 calls)
   256 |      0.04 |      0.34  (secs for 1500 calls)
   512 |      0.04 |      0.38  (secs for 1000 calls)
  1024 |      0.02 |      0.34  (secs for 500 calls)
  2048 |      0.03 |      0.27  (secs for 200 calls)
  4096 |      0.02 |      0.28  (secs for 100 calls)
  8192 |      0.04 |      0.33  (secs for 50 calls)
..........
 Hilbert transform of periodic functions
=========================================
 size  | optimized |    naive
-----------------------------------------
   100 |      0.03 |      0.17  (secs for 1500 calls)
  1000 |      0.03 |      0.14  (secs for 300 calls)
   256 |      0.04 |      0.24  (secs for 1500 calls)
   512 |      0.03 |      0.26  (secs for 1000 calls)
  1024 |      0.03 |      0.23  (secs for 500 calls)
  2048 |      0.02 |      0.16  (secs for 200 calls)
  4096 |      0.03 |      0.19  (secs for 100 calls)
  8192 |      0.03 |      0.25  (secs for 50 calls)
........
 Shifting periodic functions
==============================
 size  | optimized |    naive
------------------------------
   100 |      0.03 |      0.23  (secs for 1500 calls)
  1000 |      0.01 |      0.25  (secs for 300 calls)
   256 |      0.03 |      0.38  (secs for 1500 calls)
   512 |      0.03 |      0.43  (secs for 1000 calls)
  1024 |      0.02 |      0.39  (secs for 500 calls)
  2048 |      0.01 |      0.30  (secs for 200 calls)
  4096 |      0.03 |      0.31  (secs for 100 calls)
  8192 |      0.03 |      0.32  (secs for 50 calls)
..
 Tilbert transform of periodic functions
=========================================
 size  | optimized |    naive
-----------------------------------------
   100 |      0.02 |      0.23  (secs for 1500 calls)
  1000 |      0.02 |      0.17  (secs for 300 calls)
   256 |      0.04 |      0.33  (secs for 1500 calls)
   512 |      0.04 |      0.32  (secs for 1000 calls)
  1024 |      0.03 |      0.28  (secs for 500 calls)
  2048 |      0.03 |      0.20  (secs for 200 calls)
  4096 |      0.03 |      0.21  (secs for 100 calls)
  8192 |      0.04 |      0.25  (secs for 50 calls)
........
----------------------------------------------------------------------
Ran 51 tests in 26.269s

OK
<unittest.TextTestRunner object at 0x406432ac>


>>> from scipy import interpolate;NumpyTest(interpolate).test(level=10)
  Found 5 tests for scipy.interpolate.fitpack
  Found 0 tests for __main__
/opt/scipy/lib/scipy/interpolate/fitpack2.py:410: UserWarning:
The coefficients of the spline returned have been computed as the
minimal norm least-squares solution of a (numerically) rank deficient
system (deficiency=7). If deficiency is large, the results may be
inaccurate. Deficiency may strongly depend on the value of eps.
  warnings.warn(message)
.....
----------------------------------------------------------------------
Ran 5 tests in 0.012s

OK
<unittest.TextTestRunner object at 0x40643c4c>


>>> from scipy import io;NumpyTest(io).test(level=10)
  Found 4 tests for scipy.io.array_import
  Found 12 tests for scipy.io.mmio
  Found 0 tests for __main__

Don't worry about a warning regarding the number of bytes read.
Warning: 1000000 bytes requested, 20 bytes read.
................
----------------------------------------------------------------------
Ran 16 tests in 0.137s

OK
<unittest.TextTestRunner object at 0x406ce66c>


>>> from scipy import lib;NumpyTest(lib).test(level=10);

****************************************************************
WARNING: clapack module is empty
-----------
See scipy/INSTALL.txt for troubleshooting.
Notes:
* If atlas library is not found by numpy/distutils/system_info.py,
  then scipy uses flapack instead of clapack.
****************************************************************

  Found 42 tests for scipy.lib.lapack
  Found 0 tests for __main__
..........................................
----------------------------------------------------------------------
Ran 42 tests in 0.059s

OK
<unittest.TextTestRunner object at 0x410bb9ec>

>>> from scipy import linalg;NumpyTest(linalg).test(level=10)
  Found 128 tests for scipy.linalg.fblas
  Found 37 tests for scipy.linalg.decomp
  Found 4 tests for scipy.linalg.lapack
  Found 44 tests for scipy.linalg.basic
  Found 7 tests for scipy.linalg.matfuncs
  Found 14 tests for scipy.linalg.blas
  Found 0 tests for __main__
...caxpy:n=4
..caxpy:n=3
....ccopy:n=4
..ccopy:n=3
.............cscal:n=4
....cswap:n=4
..cswap:n=3
.....daxpy:n=4
..daxpy:n=3
....dcopy:n=4
..dcopy:n=3
.............dscal:n=4
....dswap:n=4
..dswap:n=3
.....saxpy:n=4
..saxpy:n=3
....scopy:n=4
..scopy:n=3
.............sscal:n=4
....sswap:n=4
..sswap:n=3
.....zaxpy:n=4
..zaxpy:n=3
....zcopy:n=4
..zcopy:n=3
.............zscal:n=4
....zswap:n=4
..zswap:n=3
.........
           Finding matrix eigenvalues
      ==================================
      |    contiguous
----------------------------------------------
 size |  scipy
   20 |   0.08     (secs for 150 calls)
  100 |   0.17     (secs for 7 calls)
  200 |   0.36     (secs for 2 calls)
.................Floating point exception



>>> from scipy import maxentropy;NumpyTest(maxentropy).test(level=10)
  Found 2 tests for scipy.maxentropy
  Found 0 tests for __main__
..
----------------------------------------------------------------------
Ran 2 tests in 0.003s

OK
<unittest.TextTestRunner object at 0x406e550c>

>>> from scipy import ndimage;NumpyTest(ndimage).test(level=10)
  Found 397 tests for scipy.ndimage
  Found 0 tests for __main__
.............................................................................................................................................................................................................................................................................................................................................................................................................
----------------------------------------------------------------------
Ran 397 tests in 1.174s

OK
<unittest.TextTestRunner object at 0x406edcac>

>>> from scipy import optimize;NumpyTest(optimize).test(level=10)
  Found 6 tests for scipy.optimize.optimize
  Found 2 tests for scipy.optimize.zeros
  Found 1 tests for scipy.optimize.cobyla
  Found 0 tests for __main__
......%s

f2 is a symmetric parabola, x**2 - 1
f3 is a quartic polynomial with large hump in interval
f4 is step function with a discontinuity at 1
f5 is a hyperbola with vertical asymptote at 1
f6 has random values positive to left of 1 , negative to right

of course these are not real problems. They just test how the
'good' solvers behave in bad circumstances where bisection is
really the best. A good solver should not be much worse than
bisection in such circumstance, while being faster for smooth
monotone sorts of functions.

TESTING SPEED

times in seconds for 2000 iterations

function f2
cc.bisect : 0.080
cc.ridder : 0.040
cc.brenth : 0.030
cc.brentq : 0.030

function f3
cc.bisect : 0.110
cc.ridder : 0.030
cc.brenth : 0.040
cc.brentq : 0.030

function f4
cc.bisect : 0.090
cc.ridder : 0.110
cc.brenth : 0.100
cc.brentq : 0.110

function f5
cc.bisect : 0.090
cc.ridder : 0.120
cc.brenth : 0.110
cc.brentq : 0.110

function f6
cc.bisect : 0.100
cc.ridder : 0.120
cc.brenth : 0.110
cc.brentq : 0.130

.TESTING CONVERGENCE

zero should be 1

function f2
cc.bisect :    1.0000000000001952
cc.ridder :    1.0000000000004658
cc.brenth :    0.9999999999999997
cc.brentq :    0.9999999999999577

function f3
cc.bisect :    1.0000000000001952
cc.ridder :    1.0000000000000000
cc.brenth :    1.0000000000000009
cc.brentq :    1.0000000000000011

function f4
cc.bisect :    1.0000000000001952
cc.ridder :    1.0000000000001452
cc.brenth :    0.9999999999993339
cc.brentq :    0.9999999999993339

function f5
cc.bisect :    1.0000000000001952
cc.ridder :    1.0000000000004574
cc.brenth :    0.9999999999991442
cc.brentq :    0.9999999999991442

function f6
cc.bisect :    1.0000000000001952
cc.ridder :    0.9999999999995509
cc.brenth :    1.0000000000004117
cc.brentq :    0.9999999999988777

.Result: [ 4.957975    0.64690335] (exact result = 4.955356249106168,
0.666666666666666)
.
----------------------------------------------------------------------
Ran 9 tests in 2.344s

OK
<unittest.TextTestRunner object at 0x40ece94c>

>>> from scipy import signal;NumpyTest(signal).test(level=10)
  Found 4 tests for scipy.signal.signaltools
  Found 0 tests for __main__
....
----------------------------------------------------------------------
Ran 4 tests in 0.005s

OK
<unittest.TextTestRunner object at 0x410b00cc>

>>> from scipy import sparse;NumpyTest(sparse).test(level=10)
  Found 89 tests for scipy.sparse.sparse
  Found 0 tests for __main__
 2 3 1 2 2
 3 2 1 3 3
 3 3 1 3 3
. 3 3 1 3 3
...........Use minimum degree ordering on A'+A.
.....................Use minimum degree ordering on A'+A.
.....................Use minimum degree ordering on A'+A.
.......................Use minimum degree ordering on A'+A.
............
----------------------------------------------------------------------
Ran 89 tests in 0.487s

OK
<unittest.TextTestRunner object at 0x410b022c>

>>> from scipy import special;NumpyTest(special).test(level=10)
  Found 341 tests for scipy.special.basic
  Found 0 tests for __main__
.........Floating point exception

>>> from scipy import stats;NumpyTest(stats).test(level=10)
  Found 95 tests for scipy.stats.stats
  Found 70 tests for scipy.stats.distributions
  Found 10 tests for scipy.stats.morestats
  Found 0 tests for __main__
..................................................................................................................................................Floating
point exception


***************BY MODULE******************


python ./integrate/tests/test_integrate.py -l 10
  Found 1 tests for __main__
Residual: 1.05006950433e-07
.
----------------------------------------------------------------------
Ran 1 test in 0.010s

OK

python ./integrate/tests/test_quadpack.py -l 10
  Found 10 tests for __main__
..Floating point exception


python ./linalg/tests/test_atlas_version.py -l 10
NO ATLAS INFO AVAILABLE

python ./linalg/tests/test_basic.py -l 10
  Found 44 tests for __main__

           Finding matrix determinant
      ==================================
      |    contiguous     |   non-contiguous
----------------------------------------------
 size |  scipy  | basic   |  scipy  | basic
   20 |   0.21  |   0.22  |   0.26  |   0.28     (secs for 2000 calls)
  100 |   0.52  |   0.47  |   0.66  |   0.68     (secs for 300 calls)
  500 |   0.68  |   0.68  |   0.72  |   0.73     (secs for 4 calls)
......
           Finding matrix inverse
      ==================================
      |    contiguous     |   non-contiguous
----------------------------------------------
 size |  scipy  | basic   |  scipy  | basic
   20 |   0.34  |   0.31  |   0.36  |   0.36     (secs for 2000 calls)
  100 |   1.21  |   1.51  |   1.22  |   1.68     (secs for 300 calls)
  500 |   2.42  |   2.73  |   2.40  |   2.68     (secs for 4 calls)
....../opt/numpy/lib/numpy/core/oldnumeric.py:573: DeprecationWarning: integer
argument expected, got float
  result = a.round(decimals)
.......Floating point exception


python ./linalg/tests/test_blas.py -l 10
  Found 14 tests for __main__

****************************************************************
WARNING: cblas module is empty
-----------
See scipy/INSTALL.txt for troubleshooting.
Notes:
* If atlas library is not found by numpy/distutils/system_info.py,
  then scipy uses fblas instead of cblas.
****************************************************************

..............
----------------------------------------------------------------------
Ran 14 tests in 0.013s

OK


python ./linalg/tests/test_decomp.py -l 10
  Found 37 tests for __main__
.......
           Finding matrix eigenvalues
      ==================================
      |    contiguous
----------------------------------------------
 size |  scipy
   20 |   0.08     (secs for 150 calls)
  100 |   0.16     (secs for 7 calls)
  200 |   0.35     (secs for 2 calls)
.................Floating point exception

python ./linalg/tests/test_fblas.py -l 10
  Found 128 tests for __main__
...caxpy:n=4
..caxpy:n=3
....ccopy:n=4
..ccopy:n=3
.............cscal:n=4
....cswap:n=4
..cswap:n=3
.....daxpy:n=4
..daxpy:n=3
....dcopy:n=4
..dcopy:n=3
.............dscal:n=4
....dswap:n=4
..dswap:n=3
.....saxpy:n=4
..saxpy:n=3
....scopy:n=4
..scopy:n=3
.............sscal:n=4
....sswap:n=4
..sswap:n=3
.....zaxpy:n=4
..zaxpy:n=3
....zcopy:n=4
..zcopy:n=3
.............zscal:n=4
....zswap:n=4
..zswap:n=3
..
----------------------------------------------------------------------
Ran 128 tests in 0.074s

OK

python ./linalg/tests/test_lapack.py -l 10
  Found 4 tests for __main__
..
****************************************************************
WARNING: clapack module is empty
-----------
See scipy/INSTALL.txt for troubleshooting.
Notes:
* If atlas library is not found by numpy/distutils/system_info.py,
  then scipy uses flapack instead of clapack.
****************************************************************

..
----------------------------------------------------------------------
Ran 4 tests in 0.004s

OK

python ./linalg/tests/test_matfuncs.py -l 10
  Found 7 tests for __main__
.Floating point exception

python ./stats/tests/test_distributions.py -l 10
  Found 70 tests for stats.distributions
  Found 0 tests for __main__
...................................................Floating point exception

python ./stats/tests/test_morestats.py -l 10
  Found 10 tests for __main__
..Ties preclude use of exact statistic.
..Ties preclude use of exact statistic.
.....Floating point exception

python ./stats/tests/test_stats.py -l 10
  Found 95 tests for __main__
...............................................................................................
----------------------------------------------------------------------
Ran 95 tests in 0.050s

OK



python ./special/tests/test_basic.py -l 10
  Found 341 tests for __main__
.........Floating point exception









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