centrosome.filter ZeroDivisionError

[mcquin]

__________________________________________________________________________________________________________________ TestLineIntegration.test_01_02_two_lines __________________________________________________________________________________________________________________

self = <test_filter.TestLineIntegration testMethod=test_01_02_two_lines>

    def test_01_02_two_lines(self):
        img = np.ones((20,30)) * .5
        img[8,10:20] = 1
        img[12,10:20] = 0
>       result = F.line_integration(img, 0, 1, 0)

tests/test_filter.py:1770:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
centrosome/filter.py:1189: in line_integration
    smoothed = scind.gaussian_filter1d(rotated, sigma)
/usr/local/lib/python2.7/site-packages/scipy/ndimage/filters.py:271: in gaussian_filter1d
    weights = _gaussian_kernel1d(sigma, order, lw)[::-1]
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

sigma = 0, order = 0, radius = 0

    def _gaussian_kernel1d(sigma, order, radius):
        """
        Computes a 1D Gaussian convolution kernel.
        """
        if order < 0:
            raise ValueError('order must be non-negative')
>       p = numpy.polynomial.Polynomial([0, 0, -0.5 / (sigma * sigma)])
E       ZeroDivisionError: float division by zero

/usr/local/lib/python2.7/site-packages/scipy/ndimage/filters.py:207: ZeroDivisionError
_______________________________________________________________________________________________________________ TestLineIntegration.test_01_03_diagonal_lines ________________________________________________________________________________________________________________

self = <test_filter.TestLineIntegration testMethod=test_01_03_diagonal_lines>

    def test_01_03_diagonal_lines(self):
        img = np.ones((20,30)) * .5
        i,j = np.mgrid[0:20,0:30]
        img[(i == j-3) & (i <= 15)] = 1
        img[(i == j + 3)] = 0
        expected = np.zeros((20,30), bool)
        expected[(i >= j-3) & (i <= j+3)] = True
>       result = F.line_integration(img, -45, 1, 0)

tests/test_filter.py:1784:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
centrosome/filter.py:1189: in line_integration
    smoothed = scind.gaussian_filter1d(rotated, sigma)
/usr/local/lib/python2.7/site-packages/scipy/ndimage/filters.py:271: in gaussian_filter1d
    weights = _gaussian_kernel1d(sigma, order, lw)[::-1]
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

sigma = 0, order = 0, radius = 0

    def _gaussian_kernel1d(sigma, order, radius):
        """
        Computes a 1D Gaussian convolution kernel.
        """
        if order < 0:
            raise ValueError('order must be non-negative')
>       p = numpy.polynomial.Polynomial([0, 0, -0.5 / (sigma * sigma)])
E       ZeroDivisionError: float division by zero

/usr/local/lib/python2.7/site-packages/scipy/ndimage/filters.py:207: ZeroDivisionError
____________________________________________________________________________________________________________________ TestLineIntegration.test_01_04_decay ____________________________________________________________________________________________________________________

self = <test_filter.TestLineIntegration testMethod=test_01_04_decay>

    def test_01_04_decay(self):
        img = np.ones((25,23)) * .5
        img[10,10] = 1
        img[20,10] = 0
>       result = F.line_integration(img, 0, .9, 0)

tests/test_filter.py:1792:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
centrosome/filter.py:1189: in line_integration
    smoothed = scind.gaussian_filter1d(rotated, sigma)
/usr/local/lib/python2.7/site-packages/scipy/ndimage/filters.py:271: in gaussian_filter1d
    weights = _gaussian_kernel1d(sigma, order, lw)[::-1]
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

sigma = 0, order = 0, radius = 0

    def _gaussian_kernel1d(sigma, order, radius):
        """
        Computes a 1D Gaussian convolution kernel.
        """
        if order < 0:
            raise ValueError('order must be non-negative')
>       p = numpy.polynomial.Polynomial([0, 0, -0.5 / (sigma * sigma)])
E       ZeroDivisionError: float division by zero

/usr/local/lib/python2.7/site-packages/scipy/ndimage/filters.py:207: ZeroDivisionError

SciPy version:

$ pip freeze | grep scipy
scipy==1.0.0