Created
May 29, 2013 16:04
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Heisenbug: segfault when debugging problem with pdb, but only erroneous output when running in python or iPython.
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| nuneziglesiasj@jni-lscc-mbp Thu May 30 01:38 | |
| ~ $ ipython --pylab | |
| Activating auto-logging. Current session state plus future input saved. | |
| Filename : /Users/nuneziglesiasj/ipython-logs/automatic-log--2013.5.30--1.38.py | |
| Mode : backup | |
| Output logging : False | |
| Raw input log : False | |
| Timestamping : False | |
| State : active | |
| Welcome to pylab, a matplotlib-based Python environment [backend: MacOSX]. | |
| For more information, type 'help(pylab)'. | |
| In [1]: from skimage.segmentation import slic | |
| Exception AttributeError: "'UmfpackContext' object has no attribute '_symbolic'" in <bound method UmfpackContext.__del__ of <scipy.sparse.linalg.dsolve.umfpack.umfpack.UmfpackContext object at 0x106735a50>> ignored | |
| In [2]: import pdb | |
| In [3]: import numpy as np | |
| In [4]: cpaste | |
| Pasting code; enter '--' alone on the line to stop or use Ctrl-D. | |
| : rnd = np.random.RandomState(0) | |
| : img = np.zeros((20, 21, 3)) | |
| : img[:10, :10, 0] = 1 | |
| : img[10:, :10, 1] = 1 | |
| : img[10:, 10:, 2] = 1 | |
| : img += 0.01 * rnd.normal(size=img.shape) | |
| : img[img > 1] = 1 | |
| : img[img < 0] = 0 | |
| :-- | |
| In [5]: img.shape | |
| Out[5]: (20, 21, 3) | |
| In [6]: pdb.run('seg = slic(img, sigma=0, n_segments=4)', globals=globals()) | |
| > <string>(1)<module>() | |
| (Pdb) s | |
| --Call-- | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(11)slic() | |
| -> def slic(image, n_segments=100, ratio=10., max_iter=10, sigma=1, | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(80)slic() | |
| -> spatial_dims = guess_spatial_dimensions(image) | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(81)slic() | |
| -> if spatial_dims is None and multichannel is None: | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(83)slic() | |
| -> " by default. Use `multichannel=False` to interpret as " + | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(84)slic() | |
| -> " 3D image with last dimension of length 3.") | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(85)slic() | |
| -> warnings.warn(RuntimeWarning(msg)) | |
| (Pdb) n | |
| /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py:85: RuntimeWarning: Images with dimensions (M, N, 3) are interpreted as 2D+RGB by default. Use `multichannel=False` to interpret as 3D image with last dimension of length 3. | |
| warnings.warn(RuntimeWarning(msg)) | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(86)slic() | |
| -> multichannel = True | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(89)slic() | |
| -> if ((not multichannel and image.ndim not in [2, 3]) or | |
| (Pdb) list | |
| 84 " 3D image with last dimension of length 3.") | |
| 85 warnings.warn(RuntimeWarning(msg)) | |
| 86 multichannel = True | |
| 87 elif multichannel is None: | |
| 88 multichannel = (spatial_dims + 1 == image.ndim) | |
| 89 -> if ((not multichannel and image.ndim not in [2, 3]) or | |
| 90 (multichannel and image.ndim not in [3, 4]) or | |
| 91 (multichannel and image.shape[-1] != 3)): | |
| 92 ValueError("Only 1- or 3-channel 2- or 3-D images are supported.") | |
| 93 image = img_as_float(image) | |
| 94 if not multichannel: | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(90)slic() | |
| -> (multichannel and image.ndim not in [3, 4]) or | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(91)slic() | |
| -> (multichannel and image.shape[-1] != 3)): | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(93)slic() | |
| -> image = img_as_float(image) | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(94)slic() | |
| -> if not multichannel: | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(96)slic() | |
| -> if image.ndim == 3: | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(98)slic() | |
| -> image = image[np.newaxis, ...] | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(99)slic() | |
| -> if not isinstance(sigma, coll.Iterable): | |
| (Pdb) p image.shape | |
| (1, 20, 21, 3) | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(100)slic() | |
| -> sigma = np.array([sigma, sigma, sigma, 0]) | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(101)slic() | |
| -> if (sigma > 0).any(): | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(103)slic() | |
| -> if convert2lab: | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(104)slic() | |
| -> image = rgb2lab(image) | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(107)slic() | |
| -> depth, height, width = image.shape[:3] | |
| (Pdb) p np.mean(image.ravel()) | |
| 22.885328104930853 | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(109)slic() | |
| -> grid_z, grid_y, grid_x = np.mgrid[:depth, :height, :width] | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(110)slic() | |
| -> slices = regular_grid(image.shape[:3], n_segments) | |
| (Pdb) p grid_z | |
| array([[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], | |
| [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], | |
| [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], | |
| [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], | |
| [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], | |
| [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], | |
| [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], | |
| [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], | |
| [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], | |
| [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], | |
| [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], | |
| [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], | |
| [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], | |
| [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], | |
| [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], | |
| [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], | |
| [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], | |
| [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], | |
| [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], | |
| [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]]) | |
| (Pdb) p grid_y | |
| array([[[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, | |
| 0, 0, 0, 0, 0], | |
| [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, | |
| 1, 1, 1, 1, 1], | |
| [ 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, | |
| 2, 2, 2, 2, 2], | |
| [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, | |
| 3, 3, 3, 3, 3], | |
| [ 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, | |
| 4, 4, 4, 4, 4], | |
| [ 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, | |
| 5, 5, 5, 5, 5], | |
| [ 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, | |
| 6, 6, 6, 6, 6], | |
| [ 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, | |
| 7, 7, 7, 7, 7], | |
| [ 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, | |
| 8, 8, 8, 8, 8], | |
| [ 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, | |
| 9, 9, 9, 9, 9], | |
| [10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, | |
| 10, 10, 10, 10, 10], | |
| [11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, | |
| 11, 11, 11, 11, 11], | |
| [12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, | |
| 12, 12, 12, 12, 12], | |
| [13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, | |
| 13, 13, 13, 13, 13], | |
| [14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, | |
| 14, 14, 14, 14, 14], | |
| [15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, | |
| 15, 15, 15, 15, 15], | |
| [16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, | |
| 16, 16, 16, 16, 16], | |
| [17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, | |
| 17, 17, 17, 17, 17], | |
| [18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, | |
| 18, 18, 18, 18, 18], | |
| [19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, | |
| 19, 19, 19, 19, 19]]]) | |
| (Pdb) p grid_x | |
| array([[[ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, | |
| 16, 17, 18, 19, 20], | |
| [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, | |
| 16, 17, 18, 19, 20], | |
| [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, | |
| 16, 17, 18, 19, 20], | |
| [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, | |
| 16, 17, 18, 19, 20], | |
| [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, | |
| 16, 17, 18, 19, 20], | |
| [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, | |
| 16, 17, 18, 19, 20], | |
| [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, | |
| 16, 17, 18, 19, 20], | |
| [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, | |
| 16, 17, 18, 19, 20], | |
| [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, | |
| 16, 17, 18, 19, 20], | |
| [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, | |
| 16, 17, 18, 19, 20], | |
| [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, | |
| 16, 17, 18, 19, 20], | |
| [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, | |
| 16, 17, 18, 19, 20], | |
| [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, | |
| 16, 17, 18, 19, 20], | |
| [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, | |
| 16, 17, 18, 19, 20], | |
| [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, | |
| 16, 17, 18, 19, 20], | |
| [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, | |
| 16, 17, 18, 19, 20], | |
| [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, | |
| 16, 17, 18, 19, 20], | |
| [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, | |
| 16, 17, 18, 19, 20], | |
| [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, | |
| 16, 17, 18, 19, 20], | |
| [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, | |
| 16, 17, 18, 19, 20]]]) | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(111)slic() | |
| -> step_z, step_y, step_x = [int(s.step) for s in slices] | |
| (Pdb) p slices | |
| [slice(0.0, None, 1.0), slice(5.0, None, 10.0), slice(5.0, None, 10.0)] | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(111)slic() | |
| -> step_z, step_y, step_x = [int(s.step) for s in slices] | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(111)slic() | |
| -> step_z, step_y, step_x = [int(s.step) for s in slices] | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(111)slic() | |
| -> step_z, step_y, step_x = [int(s.step) for s in slices] | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(112)slic() | |
| -> means_z = grid_z[slices] | |
| (Pdb) p means_x, means_y, means_z | |
| *** NameError: NameError("name 'means_x' is not defined",) | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(113)slic() | |
| -> means_y = grid_y[slices] | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(114)slic() | |
| -> means_x = grid_x[slices] | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(116)slic() | |
| -> means_color = np.zeros(means_z.shape + (3,)) | |
| (Pdb) p means_x, means_y, means_z | |
| (array([[[ 5, 15], | |
| [ 5, 15]]]), array([[[ 5, 5], | |
| [15, 15]]]), array([[[0, 0], | |
| [0, 0]]])) | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(117)slic() | |
| -> means = np.concatenate([means_z[..., np.newaxis], means_y[..., np.newaxis], | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(118)slic() | |
| -> means_x[..., np.newaxis], means_color | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(119)slic() | |
| -> ], axis=-1).reshape(-1, 6) | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(122)slic() | |
| -> ratio = (ratio / float(max((step_z, step_y, step_x)))) ** 2 | |
| (Pdb) p means | |
| array([[ 0., 5., 5., 0., 0., 0.], | |
| [ 0., 5., 15., 0., 0., 0.], | |
| [ 0., 15., 5., 0., 0., 0.], | |
| [ 0., 15., 15., 0., 0., 0.]]) | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(123)slic() | |
| -> image_zyx = np.concatenate([grid_z[..., np.newaxis], | |
| (Pdb) p ratio | |
| 1.0 | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(124)slic() | |
| -> grid_y[..., np.newaxis], | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(125)slic() | |
| -> grid_x[..., np.newaxis], | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(126)slic() | |
| -> image / ratio], axis=-1).copy("C") | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(127)slic() | |
| -> nearest_mean = np.zeros((depth, height, width), dtype=np.intp) | |
| (Pdb) p image_zyx.shape | |
| (1, 20, 21, 6) | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(128)slic() | |
| -> distance = np.empty((depth, height, width), dtype=np.float) | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(129)slic() | |
| -> segment_map = _slic_cython(image_zyx, nearest_mean, distance, means, | |
| (Pdb) p np.__version__ | |
| '1.6.1' | |
| (Pdb) n | |
| > /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py(130)slic() | |
| -> ratio, max_iter, n_segments) | |
| (Pdb) n | |
| Segmentation fault: 11 | |
| (skimdev-travis) | |
| nuneziglesiasj@jni-lscc-mbp Thu May 30 01:52 | |
| ~ $ python projects/skimage/skimage/segmentation/tests/test_slic.py | |
| Exception AttributeError: "'UmfpackContext' object has no attribute '_symbolic'" in <bound method UmfpackContext.__del__ of <scipy.sparse.linalg.dsolve.umfpack.umfpack.UmfpackContext object at 0x107e50c50>> ignored | |
| /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py:85: RuntimeWarning: Images with dimensions (M, N, 3) are interpreted as 2D+RGB by default. Use `multichannel=False` to interpret as 3D image with last dimension of length 3. | |
| warnings.warn(RuntimeWarning(msg)) | |
| FF.. | |
| ====================================================================== | |
| FAIL: test_slic.test_color_2d | |
| ---------------------------------------------------------------------- | |
| Traceback (most recent call last): | |
| File "/Library/Frameworks/EPD64.framework/Versions/7.3/lib/python2.7/site-packages/nose-1.1.2-py2.7.egg/nose/case.py", line 197, in runTest | |
| self.test(*self.arg) | |
| File "/Users/nuneziglesiasj/projects/skimage/skimage/segmentation/tests/test_slic.py", line 22, in test_color_2d | |
| assert_array_equal(seg[:10, 10:], 1) | |
| File "/Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/numpy/testing/utils.py", line 707, in assert_array_equal | |
| verbose=verbose, header='Arrays are not equal') | |
| File "/Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/numpy/testing/utils.py", line 636, in assert_array_compare | |
| raise AssertionError(msg) | |
| AssertionError: | |
| Arrays are not equal | |
| (mismatch 43.6363636364%) | |
| x: array([[3, 3, 3, 3, 3, 3, 3, 1, 1, 1, 1], | |
| [3, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1], | |
| [3, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1],... | |
| y: array(1) | |
| ====================================================================== | |
| FAIL: test_slic.test_gray_2d | |
| ---------------------------------------------------------------------- | |
| Traceback (most recent call last): | |
| File "/Library/Frameworks/EPD64.framework/Versions/7.3/lib/python2.7/site-packages/nose-1.1.2-py2.7.egg/nose/case.py", line 197, in runTest | |
| self.test(*self.arg) | |
| File "/Users/nuneziglesiasj/projects/skimage/skimage/segmentation/tests/test_slic.py", line 38, in test_gray_2d | |
| assert_array_equal(seg[:10, :10], 0) | |
| File "/Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/numpy/testing/utils.py", line 707, in assert_array_equal | |
| verbose=verbose, header='Arrays are not equal') | |
| File "/Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/numpy/testing/utils.py", line 636, in assert_array_compare | |
| raise AssertionError(msg) | |
| AssertionError: | |
| Arrays are not equal | |
| (mismatch 100.0%) | |
| x: array([[3, 3, 3, 3, 3, 3, 3, 3, 3, 3], | |
| [3, 3, 3, 3, 3, 3, 3, 3, 3, 3], | |
| [3, 3, 3, 3, 3, 3, 3, 3, 3, 3],... | |
| y: array(0) | |
| ---------------------------------------------------------------------- | |
| Ran 4 tests in 0.055s | |
| FAILED (failures=2) | |
| (skimdev-travis) | |
| nuneziglesiasj@jni-lscc-mbp Thu May 30 01:53 | |
| ~ $ ipython --pylab | |
| Activating auto-logging. Current session state plus future input saved. | |
| Filename : /Users/nuneziglesiasj/ipython-logs/automatic-log--2013.5.30--1.54.py | |
| Mode : backup | |
| Output logging : False | |
| Raw input log : False | |
| Timestamping : False | |
| State : active | |
| Welcome to pylab, a matplotlib-based Python environment [backend: MacOSX]. | |
| For more information, type 'help(pylab)'. | |
| In [1]: from skimage.segmentation import slic | |
| Exception AttributeError: "'UmfpackContext' object has no attribute '_symbolic'" in <bound method UmfpackContext.__del__ of <scipy.sparse.linalg.dsolve.umfpack.umfpack.UmfpackContext object at 0x103f66050>> ignored | |
| In [2]: import numpy as np | |
| In [3]: import pdb | |
| In [4]: cpaste | |
| Pasting code; enter '--' alone on the line to stop or use Ctrl-D. | |
| : rnd = np.random.RandomState(0) | |
| : img = np.zeros((20, 21, 3)) | |
| : img[:10, :10, 0] = 1 | |
| : img[10:, :10, 1] = 1 | |
| : img[10:, 10:, 2] = 1 | |
| : img += 0.01 * rnd.normal(size=img.shape) | |
| : img[img > 1] = 1 | |
| : img[img < 0] = 0 | |
| :-- | |
| In [5]: seg = slic(img, sigma=0, n_segments=4) | |
| /Users/nuneziglesiasj/venv/skimdev-travis/lib/python2.7/site-packages/scikit_image-0.9dev-py2.7-macosx-10.5-x86_64.egg/skimage/segmentation/slic_superpixels.py:85: RuntimeWarning: Images with dimensions (M, N, 3) are interpreted as 2D+RGB by default. Use `multichannel=False` to interpret as 3D image with last dimension of length 3. | |
| warnings.warn(RuntimeWarning(msg)) | |
| In [6]: imshow(seg) | |
| Out[6]: <matplotlib.image.AxesImage at 0x103f115d0> |
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