测试SciPy时出错

Question

当使用nose包测试scipy时scipy.test(),测试在Ubuntu 12.04下失败,安装了所有的vanilla软件包.我是否必须担心,如果是,我该如何解决这个问题？

In [8]: scipy.test()
Running unit tests for scipy
NumPy version 1.5.1
NumPy is installed in /usr/lib/python2.7/dist-packages/numpy
SciPy version 0.9.0
SciPy is installed in /usr/lib/python2.7/dist-packages/scipy
Python version 2.7.2+ (default, Jan 21 2012, 23:31:34) [GCC 4.6.2]
nose version 1.1.2

[................]

======================================================================
FAIL: test_io.test_imread
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/lib/python2.7/dist-packages/nose/case.py", line 197, in runTest
    self.test(*self.arg)
  File "/usr/lib/python2.7/dist-packages/numpy/testing/decorators.py", line 146, in skipper_func
    return f(*args, **kwargs)
  File "/usr/lib/python2.7/dist-packages/scipy/ndimage/tests/test_io.py", line 16, in test_imread
    assert_array_equal(img.shape, (300, 420, 3))
  File "/usr/lib/python2.7/dist-packages/numpy/testing/utils.py", line 686, in assert_array_equal
    verbose=verbose, header='Arrays are not equal')
  File "/usr/lib/python2.7/dist-packages/numpy/testing/utils.py", line 579, in assert_array_compare
    raise AssertionError(msg)
AssertionError: 
Arrays are not equal

(shapes (2,), (3,) mismatch)
 x: array([300, 420])
 y: array([300, 420,   3])

----------------------------------------------------------------------
Ran 3780 tests in 32.328s

FAILED (KNOWNFAIL=11, SKIP=20, failures=1)

Answer 1

如果你看看里面/usr/lib/python2.7/dist-packages/scipy/ndimage/tests/test_io.py你应该看到:

def test_imread():
    lp = os.path.join(os.path.dirname(__file__), 'dots.png')
    img = ndi.imread(lp)
    assert_array_equal(img.shape, (300, 420, 3))

    img = ndi.imread(lp, flatten=True)
    assert_array_equal(img.shape, (300, 420))

如果flatten=True将RGB图像转换为1位灰度图像,则此测试似乎正在测试.

但是,在我的Ubuntu 11.10系统上,dots.png已经是一个1位的图像文件:

% file /usr/share/pyshared/scipy/ndimage/tests/dots.png
/usr/share/pyshared/scipy/ndimage/tests/dots.png: PNG image data, 420 x 300, 1-bit colormap, non-interlaced

如果我在RGBA图像上执行测试(手动),那么测试工作:

In [18]: z = ndi.imread('image.png')

In [20]: z.shape
Out[20]: (250, 250, 4)

In [24]: w = ndi.imread('image.png', flatten = True)

In [25]: w.shape
Out[25]: (250, 250)

所以我认为这里没有任何严重的错误,只是可能发送的dots.png文件应该是RGB图像而不是灰度图像.