[SciPy-User] many test failures on windows 64

Bruce Southey bsouthey@gmail....
Mon Jul 5 21:36:52 CDT 2010


On Mon, Jul 5, 2010 at 5:40 AM, Robin <robince@gmail.com> wrote:
> Hi,
>
> I am using Python.org amd64 python build on windows 7 64 bit.
>
> I am using numpy and scipy builds from here:
> http://www.lfd.uci.edu/~gohlke/pythonlibs/
>
> I get many errors in scipy test (none for numpy). Particularly in
> scipy.sparse.linalg which I need to use (and in my code it appears
> spsolve is giving incorrect results).
>
> Is there a better 64 bit windows build to use?
>
>>>> scipy.test()
> Running unit tests for scipy
> NumPy version 1.4.1
> NumPy is installed in C:\Python26\lib\site-packages\numpy
> SciPy version 0.8.0b1
> SciPy is installed in C:\Python26\lib\site-packages\scipy
> Python version 2.6.5 (r265:79096, Mar 19 2010, 18:02:59) [MSC v.1500
> 64 bit (AMD64)]
> nose version 0.11.3
> ........................................................................................................................
> ............................E....................................F......................................................
> ..............................C:\Python26\lib\site-packages\scipy\interpolate\fitpack2.py:639:
> 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)
> .....C:\Python26\lib\site-packages\scipy\interpolate\fitpack2.py:580:
> UserWarning:
> The required storage space exceeds the available storage space: nxest
> or nyest too small, or s too small.
> The weighted least-squares spline corresponds to the current set of
> knots.
>  warnings.warn(message)
> ...........................................K..K.........................................................................
> ........................................................................................................................
> ........................................................................................................................
> EC:\Python26\lib\site-packages\numpy\lib\utils.py:140:
> DeprecationWarning: `write_array` is deprecated!
>
> This function is replaced by numpy.savetxt which allows the same functionality
> through a different syntax.
>
>  warnings.warn(depdoc, DeprecationWarning)
> C:\Python26\lib\site-packages\numpy\lib\utils.py:140:
> DeprecationWarning: `read_array` is deprecated!
>
> The functionality of read_array is in numpy.loadtxt which allows the same
> functionality using different syntax.
>
>  warnings.warn(depdoc, DeprecationWarning)
> ...........................................Exception AttributeError:
> "'netcdf_file' object has no attribute 'mode'" in <
> bound method netcdf_file.close of <scipy.io.netcdf.netcdf_file object
> at 0x000000000C64D6D8>> ignored
> ............C:\Python26\lib\site-packages\numpy\lib\utils.py:140:
> DeprecationWarning: `npfile` is deprecated!
>
> You can achieve the same effect as using npfile using numpy.save and
> numpy.load.
>
> You can use memory-mapped arrays and data-types to map out a
> file format for direct manipulation in NumPy.
>
>  warnings.warn(depdoc, DeprecationWarning)
> .........C:\Python26\lib\site-packages\scipy\io\wavfile.py:30:
> WavFileWarning: Unfamiliar format bytes
>  warnings.warn("Unfamiliar format bytes", WavFileWarning)
> C:\Python26\lib\site-packages\scipy\io\wavfile.py:120: WavFileWarning:
> chunk not understood
>  warnings.warn("chunk not understood", WavFileWarning)
> ........................................................................................................................
> .......................................................................................................SSSSSS......SSSSS
> S......SSSS...............................................................S.............................................
> ........................................................................................................................
> ..............................................E.........................................................................
> ........................................................................................................................
> ....SSS.........S.......................................................................................................
> .............................................................F..........................................................
> ........................................................................................................................
> .....................................................FFF.....................................................C:\Python26
> \lib\site-packages\scipy\signal\filter_design.py:247: BadCoefficients:
> Badly conditioned filter coefficients (numerator)
> : the results may be meaningless
>  "results may be meaningless", BadCoefficients)
> ........................................................................................................................
> ................................................................................................E.......................
> ..........................SSSSSSSSSSS.FE.EE.EE......K.........E.E...................................E...................
> ....................................................................K..................E................................
> ............K..................E.................................................E......................................
> ..............................................KK........................E...............................................
> ........................................................................................................................
> ..................................................................................................................F.....
> ...............................................................................K.K......................................
> ........................................................................................................................
> ........................................................................................................................
> ..........................F...F..............................................................K........K.........SSSSS...
> ........................................................................................................................
> ........................................................................................................................
> ........................................................................................................................
> ........................................................................................................................
> .............................S..........................................................................................
> ...........................................................................................C:\Python26\lib\site-packages
> \scipy\stats\morestats.py:702: UserWarning: Ties preclude use of exact
> statistic.
>  warnings.warn("Ties preclude use of exact statistic.")
> ........................................................................................................................
> ........................................................................................................................
> ....................................................error removing
> c:\users\robince\appdata\local\temp\tmpr3s_aecat_test
> : c:\users\robince\appdata\local\temp\tmpr3s_aecat_test: The directory
> is not empty
> ..................................................................................................
> ======================================================================
> ERROR: Testing that kmeans2 init methods work.
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>  File "C:\Python26\lib\site-packages\scipy\cluster\tests\test_vq.py",
> line 166, in test_kmeans2_init
>    kmeans2(data, 3, minit = 'points')
>  File "C:\Python26\lib\site-packages\scipy\cluster\vq.py", line 671, in kmeans2
>    clusters = init(data, k)
>  File "C:\Python26\lib\site-packages\scipy\cluster\vq.py", line 523,
> in _kpoints
>    p = np.random.permutation(n)
>  File "mtrand.pyx", line 4231, in mtrand.RandomState.permutation
> (build\scons\numpy\random\mtrand\mtrand.c:18669)
>  File "mtrand.pyx", line 4174, in mtrand.RandomState.shuffle
> (build\scons\numpy\random\mtrand\mtrand.c:18261)
> TypeError: len() of unsized object
>
> ======================================================================
> ERROR: test_basic (test_array_import.TestNumpyio)
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>  File "C:\Python26\lib\site-packages\scipy\io\tests\test_array_import.py",
> line 29, in test_basic
>    b = numpyio.fread(fid,1000000,N.Int16,N.Int)
> MemoryError
>
> ======================================================================
> ERROR: test_decomp.test_lapack_misaligned(<function solve at
> 0x0000000006366438>, (array([[  1.734e-255,   8.189e-217,
>  4.025e-178,   1.903e-139,   9.344e-101,
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>  File "C:\Python26\lib\site-packages\nose-0.11.3-py2.6.egg\nose\case.py",
> line 186, in runTest
>    self.test(*self.arg)
>  File "C:\Python26\lib\site-packages\scipy\linalg\tests\test_decomp.py",
> line 1074, in check_lapack_misaligned
>    func(*a,**kwargs)
>  File "C:\Python26\lib\site-packages\scipy\linalg\basic.py", line 49, in solve
>    a1, b1 = map(asarray_chkfinite,(a,b))
>  File "C:\Python26\lib\site-packages\numpy\lib\function_base.py",
> line 586, in asarray_chkfinite
>    raise ValueError, "array must not contain infs or NaNs"
> ValueError: array must not contain infs or NaNs
>
> ======================================================================
> ERROR: Regression test for #880: empty array for zi crashes.
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>  File "C:\Python26\lib\site-packages\scipy\signal\tests\test_signaltools.py",
> line 422, in test_empty_zi
>    y, zf = lfilter(b, a, x, zi=zi)
>  File "C:\Python26\lib\site-packages\scipy\signal\signaltools.py",
> line 610, in lfilter
>    return sigtools._linear_filter(b, a, x, axis, zi)
> TypeError: array cannot be safely cast to required type
>
> ======================================================================
> ERROR: test_linsolve.TestSplu.test_lu_refcount
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>  File "C:\Python26\lib\site-packages\nose-0.11.3-py2.6.egg\nose\case.py",
> line 186, in runTest
>    self.test(*self.arg)
>  File "C:\Python26\lib\site-packages\scipy\sparse\linalg\dsolve\tests\test_linsolve.py",
> line 122, in test_lu_refcount
>    lu = splu(a_)
>  File "C:\Python26\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py",
> line 173, in splu
>    ilu=False, options=_options)
> RuntimeError: Factor is exactly singular
>
> ======================================================================
> ERROR: test_linsolve.TestSplu.test_spilu_smoketest
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>  File "C:\Python26\lib\site-packages\nose-0.11.3-py2.6.egg\nose\case.py",
> line 186, in runTest
>    self.test(*self.arg)
>  File "C:\Python26\lib\site-packages\scipy\sparse\linalg\dsolve\tests\test_linsolve.py",
> line 60, in test_spilu_smokete
> st
>    lu = spilu(self.A, drop_tol=1e-2, fill_factor=5)
>  File "C:\Python26\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py",
> line 245, in spilu
>    ilu=True, options=_options)
> RuntimeError: Factor is exactly singular
>
> ======================================================================
> ERROR: test_linsolve.TestSplu.test_splu_basic
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>  File "C:\Python26\lib\site-packages\nose-0.11.3-py2.6.egg\nose\case.py",
> line 186, in runTest
>    self.test(*self.arg)
>  File "C:\Python26\lib\site-packages\scipy\sparse\linalg\dsolve\tests\test_linsolve.py",
> line 87, in test_splu_basic
>    lu = splu(a_)
>  File "C:\Python26\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py",
> line 173, in splu
>    ilu=False, options=_options)
> RuntimeError: Factor is exactly singular
>
> ======================================================================
> ERROR: test_linsolve.TestSplu.test_splu_perm
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>  File "C:\Python26\lib\site-packages\nose-0.11.3-py2.6.egg\nose\case.py",
> line 186, in runTest
>    self.test(*self.arg)
>  File "C:\Python26\lib\site-packages\scipy\sparse\linalg\dsolve\tests\test_linsolve.py",
> line 100, in test_splu_perm
>    lu = splu(a_)
>  File "C:\Python26\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py",
> line 173, in splu
>    ilu=False, options=_options)
> RuntimeError: Factor is exactly singular
>
> ======================================================================
> ERROR: test_linsolve.TestSplu.test_splu_smoketest
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>  File "C:\Python26\lib\site-packages\nose-0.11.3-py2.6.egg\nose\case.py",
> line 186, in runTest
>    self.test(*self.arg)
>  File "C:\Python26\lib\site-packages\scipy\sparse\linalg\dsolve\tests\test_linsolve.py",
> line 53, in test_splu_smoketes
> t
>    lu = splu(self.A)
>  File "C:\Python26\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py",
> line 173, in splu
>    ilu=False, options=_options)
> RuntimeError: Factor is exactly singular
>
> ======================================================================
> ERROR: Check that QMR works with left and right preconditioners
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>  File "C:\Python26\lib\site-packages\scipy\sparse\linalg\isolve\tests\test_iterative.py",
> line 161, in test_leftright_p
> recond
>    L_solver = splu(L)
>  File "C:\Python26\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py",
> line 173, in splu
>    ilu=False, options=_options)
> RuntimeError: Factor is exactly singular
>
> ======================================================================
> ERROR: test_preconditioner (test_lgmres.TestLGMRES)
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>  File "C:\Python26\lib\site-packages\scipy\sparse\linalg\isolve\tests\test_lgmres.py",
> line 38, in test_preconditioner
>    pc = splu(Am.tocsc())
>  File "C:\Python26\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py",
> line 173, in splu
>    ilu=False, options=_options)
> RuntimeError: Factor is exactly singular
>
> ======================================================================
> ERROR: test_mu (test_base.TestBSR)
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>  File "C:\Python26\lib\site-packages\scipy\sparse\tests\test_base.py",
> line 966, in test_mu
>    D1 = A * B.T
>  File "C:\Python26\lib\site-packages\numpy\matrixlib\defmatrix.py",
> line 319, in __mul__
>    return N.dot(self, asmatrix(other))
> TypeError: array cannot be safely cast to required type
>
> ======================================================================
> ERROR: test_mu (test_base.TestCSC)
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>  File "C:\Python26\lib\site-packages\scipy\sparse\tests\test_base.py",
> line 966, in test_mu
>    D1 = A * B.T
>  File "C:\Python26\lib\site-packages\numpy\matrixlib\defmatrix.py",
> line 319, in __mul__
>    return N.dot(self, asmatrix(other))
> TypeError: array cannot be safely cast to required type
>
> ======================================================================
> ERROR: test_mu (test_base.TestCSR)
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>  File "C:\Python26\lib\site-packages\scipy\sparse\tests\test_base.py",
> line 966, in test_mu
>    D1 = A * B.T
>  File "C:\Python26\lib\site-packages\numpy\matrixlib\defmatrix.py",
> line 319, in __mul__
>    return N.dot(self, asmatrix(other))
> TypeError: array cannot be safely cast to required type
>
> ======================================================================
> ERROR: test_mu (test_base.TestDIA)
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>  File "C:\Python26\lib\site-packages\scipy\sparse\tests\test_base.py",
> line 966, in test_mu
>    D1 = A * B.T
>  File "C:\Python26\lib\site-packages\numpy\matrixlib\defmatrix.py",
> line 319, in __mul__
>    return N.dot(self, asmatrix(other))
> TypeError: array cannot be safely cast to required type
>
> ======================================================================
> ERROR: test_mu (test_base.TestLIL)
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>  File "C:\Python26\lib\site-packages\scipy\sparse\tests\test_base.py",
> line 966, in test_mu
>    D1 = A * B.T
>  File "C:\Python26\lib\site-packages\numpy\matrixlib\defmatrix.py",
> line 319, in __mul__
>    return N.dot(self, asmatrix(other))
> TypeError: array cannot be safely cast to required type
>
> ======================================================================
> FAIL: test_complex (test_basic.TestLongDoubleFailure)
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>  File "C:\Python26\lib\site-packages\scipy\fftpack\tests\test_basic.py",
> line 527, in test_complex
>    np.longcomplex)
> AssertionError: Type <type 'numpy.complex128'> not supported but does not fail
>
> ======================================================================
> FAIL: extrema 3
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>  File "C:\Python26\lib\site-packages\scipy\ndimage\tests\test_ndimage.py",
> line 3149, in test_extrema03
>    self.failUnless(numpy.all(output1[2]  == output4))
> AssertionError
>
> ======================================================================
> FAIL: test_lorentz (test_odr.TestODR)
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>  File "C:\Python26\lib\site-packages\scipy\odr\tests\test_odr.py",
> line 292, in test_lorentz
>    3.7798193600109009e+00]),
>  File "C:\Python26\lib\site-packages\numpy\testing\utils.py", line
> 765, in assert_array_almost_equal
>    header='Arrays are not almost equal')
>  File "C:\Python26\lib\site-packages\numpy\testing\utils.py", line
> 609, in assert_array_compare
>    raise AssertionError(msg)
> AssertionError:
> Arrays are not almost equal
>
> (mismatch 100.0%)
>  x: array([  1.00000000e+03,   1.00000000e-01,   3.80000000e+00])
>  y: array([  1.43067808e+03,   1.33905090e-01,   3.77981936e+00])
>
> ======================================================================
> FAIL: test_multi (test_odr.TestODR)
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>  File "C:\Python26\lib\site-packages\scipy\odr\tests\test_odr.py",
> line 188, in test_multi
>    0.5101147161764654,  0.5173902330489161]),
>  File "C:\Python26\lib\site-packages\numpy\testing\utils.py", line
> 765, in assert_array_almost_equal
>    header='Arrays are not almost equal')
>  File "C:\Python26\lib\site-packages\numpy\testing\utils.py", line
> 609, in assert_array_compare
>    raise AssertionError(msg)
> AssertionError:
> Arrays are not almost equal
>
> (mismatch 100.0%)
>  x: array([ 4. ,  2. ,  7. ,  0.4,  0.5])
>  y: array([ 4.37998803,  2.43330576,  8.00288459,  0.51011472,  0.51739023])
>
> ======================================================================
> FAIL: test_pearson (test_odr.TestODR)
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>  File "C:\Python26\lib\site-packages\scipy\odr\tests\test_odr.py",
> line 235, in test_pearson
>    np.array([ 5.4767400299231674, -0.4796082367610305]),
>  File "C:\Python26\lib\site-packages\numpy\testing\utils.py", line
> 765, in assert_array_almost_equal
>    header='Arrays are not almost equal')
>  File "C:\Python26\lib\site-packages\numpy\testing\utils.py", line
> 609, in assert_array_compare
>    raise AssertionError(msg)
> AssertionError:
> Arrays are not almost equal
>
> (mismatch 100.0%)
>  x: array([ 1.,  1.])
>  y: array([ 5.47674003, -0.47960824])
>
> ======================================================================
> FAIL: test_twodiags (test_linsolve.TestLinsolve)
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>  File "C:\Python26\lib\site-packages\scipy\sparse\linalg\dsolve\tests\test_linsolve.py",
> line 39, in test_twodiags
>    assert( norm(b - Asp*x) < 10 * cond_A * eps )
> AssertionError
>
> ======================================================================
> FAIL: test_kdtree.test_vectorization.test_single_query
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>  File "C:\Python26\lib\site-packages\nose-0.11.3-py2.6.egg\nose\case.py",
> line 186, in runTest
>    self.test(*self.arg)
>  File "C:\Python26\lib\site-packages\scipy\spatial\tests\test_kdtree.py",
> line 154, in test_single_query
>    assert isinstance(i,int)
> AssertionError
>
> ======================================================================
> FAIL: test_data.test_boost(<Data for arccosh: acosh_data_ipp-acosh_data>,)
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>  File "C:\Python26\lib\site-packages\nose-0.11.3-py2.6.egg\nose\case.py",
> line 186, in runTest
>    self.test(*self.arg)
>  File "C:\Python26\lib\site-packages\scipy\special\tests\test_data.py",
> line 205, in _test_factory
>    test.check(dtype=dtype)
>  File "C:\Python26\lib\site-packages\scipy\special\tests\testutils.py",
> line 187, in check
>    assert False, "\n".join(msg)
> AssertionError:
> Max |adiff|: 1.77636e-15
> Max |rdiff|: 1.09352e-13
> Bad results for the following points (in output 0):
>            1.0000014305114746 =>          0.0016914556651294794 !=
>      0.0016914556651292944  (rdiff         1.093
> 5249113484058e-13)
>             1.000007152557373 =>          0.0037822080446614169 !=
>      0.0037822080446612951  (rdiff         3.222
> 0418006721235e-14)
>            1.0000138282775879 =>           0.005258943946801071 !=
>      0.0052589439468011014  (rdiff         5.772
> 5773723182603e-15)
>            1.0000171661376953 =>          0.0058593666181291238 !=
>      0.0058593666181292027  (rdiff         1.347
> 0725302071254e-14)
>            1.0000600814819336 =>            0.01096183199218881 !=
>       0.010961831992188852  (rdiff         3.798
> 0296955025714e-15)
>            1.0001168251037598 =>           0.015285472131830317 !=
>       0.015285472131830425  (rdiff         7.036
> 2795851489781e-15)
>            1.0001487731933594 =>           0.017249319093529933 !=
>       0.017249319093529877  (rdiff         3.218
> 1647826365358e-15)
>            1.0003981590270996 =>           0.028218171738655599 !=
>       0.028218171738655373  (rdiff         7.991
> 8023735059643e-15)
>             1.000638484954834 =>           0.035732814682314498 !=
>       0.035732814682314568  (rdiff         1.941
> 8828227213605e-15)
>            1.0010714530944824 =>           0.046287402472878984 !=
>       0.046287402472878776  (rdiff         4.497
> 2672043800306e-15)
>            1.0049939155578613 =>           0.099897593086028066 !=
>       0.099897593086027803  (rdiff         2.639
> 4826962588157e-15)
>                1.024169921875 =>            0.21942279004958387 !=
>        0.21942279004958354  (rdiff         1.517
> 9230348510424e-15)
>
> ======================================================================
> FAIL: test_data.test_boost(<Data for arctanh: atanh_data_ipp-atanh_data>,)
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>  File "C:\Python26\lib\site-packages\nose-0.11.3-py2.6.egg\nose\case.py",
> line 186, in runTest
>    self.test(*self.arg)
>  File "C:\Python26\lib\site-packages\scipy\special\tests\test_data.py",
> line 205, in _test_factory
>    test.check(dtype=dtype)
>  File "C:\Python26\lib\site-packages\scipy\special\tests\testutils.py",
> line 187, in check
>    assert False, "\n".join(msg)
> AssertionError:
> Max |adiff|: 6.39488e-12
> Max |rdiff|: 1.01982e-12
> Bad results for the following points (in output 0):
>          -0.99999284744262695 =>            -6.2705920974721474 !=
>        -6.2705920974657525  (rdiff         1.019
> 8214973073088e-12)
>          -0.99998283386230469 =>             -5.832855225376532 !=
>         -5.832855225378502  (rdiff         3.377
> 3849320373679e-13)
>
> ----------------------------------------------------------------------
> Ran 4410 tests in 29.842s
>
> FAILED (KNOWNFAIL=11, SKIP=38, errors=16, failures=9)
> <nose.result.TextTestResult run=4410 errors=16 failures=9>
>>>>
> _______________________________________________
> SciPy-User mailing list
> SciPy-User@scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-user
>

Under 32-bit Python and the scipy 0.8 rc1 under Windows 7 64bit, I
only get the test_boost error the directory removal error (from this
test: "test_create_catalog (test_catalog.TestGetCatalog) ...").

Some of the errors could be due to Window's lack of support for 64-bit
like the "test_complex (test_basic.TestLongDoubleFailure)". However,
you probably would have to build your own find out those if no one
else has them.

Given all the issues with 64-bit windows, do you really need 64-bit numpy/scipy?

Bruce


>>> scipy.test()
Running unit tests for scipy
NumPy version 1.4.1
NumPy is installed in E:\Python26\lib\site-packages\numpy
SciPy version 0.8.0rc1
SciPy is installed in E:\Python26\lib\site-packages\scipy
Python version 2.6.3 (r263rc1:75186, Oct  2 2009, 20:40:30) [MSC
v.1500 32 bit (Intel)]
nose version 0.11.1
[snip]
======================================================================
FAIL: test_data.test_boost(<Data for arccosh: acosh_data_ipp-acosh_data>,)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "E:\Python26\lib\site-packages\nose-0.11.1-py2.6.egg\nose\case.py",
line 183, in runTest
    self.test(*self.arg)
  File "E:\Python26\lib\site-packages\scipy\special\tests\test_data.py",
line 205, in _test_factory
    test.check(dtype=dtype)
  File "E:\Python26\lib\site-packages\scipy\special\tests\testutils.py",
line 223, in check
    assert False, "\n".join(msg)
AssertionError:
Max |adiff|: 1.77636e-15
Max |rdiff|: 2.44233e-14
Bad results for the following points (in output 0):
            1.0000014305114746 =>          0.0016914556651292853 !=
      0.0016914556651292944  (rdiff         5.3842961637318929e-15)
             1.000007152557373 =>          0.0037822080446613874 !=
      0.0037822080446612951  (rdiff         2.4423306175913249e-14)
            1.0000138282775879 =>          0.0052589439468011612 !=
      0.0052589439468011014  (rdiff         1.1380223962570286e-14)
            1.0000600814819336 =>           0.010961831992188913 !=
       0.010961831992188852  (rdiff         5.5387933059412495e-15)
            1.0001168251037598 =>           0.015285472131830449 !=
       0.015285472131830425  (rdiff         1.5888373256788015e-15)
            1.0003981590270996 =>           0.028218171738655283 !=
       0.028218171738655373  (rdiff         3.1967209494023856e-15)

----------------------------------------------------------------------


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