示例#1
0
    def populate_hagmann_density(self, WM_img, ROI_img):
        """Populate hagmann density."""

        def inverse_sum(elements):
            inverse_elements = []
            for element in elements:
                inverse_elements.append( 1.0 / element )
            from math import fsum
            return fsum(inverse_elements)

        # get surface areas for ROIs
        import images
        surface_area = images.surface_area_for_rois(ROI_img, WM_img)
        # make sure our surface areas are well formed, this means an
        # entry for every key
        epsilon = 0.00000000001
        for n in self.nodes():
            try:
                surface_area[n]
            except KeyError:
                surface_area[n] = epsilon
            except Exception as e:
                raise e
                
        # for every edge...
        for i,j in self.edges_iter():
            calc_hd = ( ( 2.0 / ( surface_area[i] + surface_area[j] ) ) * \
                        inverse_sum( self[i][j]['streamlines_length'] ) )
            self[i][j]['hagmann_density'] = calc_hd
示例#2
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    def populate_hagmann_density(self, WM_img, ROI_img):
        """Populate hagmann density."""
        def inverse_sum(elements):
            inverse_elements = []
            for element in elements:
                inverse_elements.append(1.0 / element)
            from math import fsum
            return fsum(inverse_elements)

        # get surface areas for ROIs
        import images
        surface_area = images.surface_area_for_rois(ROI_img, WM_img)
        # make sure our surface areas are well formed, this means an
        # entry for every key
        epsilon = 0.00000000001
        for n in self.nodes():
            try:
                surface_area[n]
            except KeyError:
                surface_area[n] = epsilon
            except Exception as e:
                raise e

        # for every edge...
        for i, j in self.edges_iter():
            calc_hd = ( ( 2.0 / ( surface_area[i] + surface_area[j] ) ) * \
                        inverse_sum( self[i][j]['streamlines_length'] ) )
            self[i][j]['hagmann_density'] = calc_hd
示例#3
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 def test_can_get_surface_areas(self):
     # the following compares images and test images that are known
     # to satisfy the condition that an ROI w/ label n will have n
     # voxels that border white matter... labels in these images
     # are defined for 1:10
     roiImage = images.TNImage(filename = 'test_data/images/ROI_50x50x50.nii.gz')
     maskImage = images.TNImage(filename = 'test_data/images/ROI_WM_MASK_50x50x50.nii.gz')
     result = images.surface_area_for_rois(roiImage, maskImage)
     for label in range(1,11): # 1:10
         assert result[label] == label
示例#4
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 def test_can_get_surface_areas(self):
     # the following compares images and test images that are known
     # to satisfy the condition that an ROI w/ label n will have n
     # voxels that border white matter... labels in these images
     # are defined for 1:10
     roiImage = images.TNImage(
         filename='test_data/images/ROI_50x50x50.nii.gz')
     maskImage = images.TNImage(
         filename='test_data/images/ROI_WM_MASK_50x50x50.nii.gz')
     result = images.surface_area_for_rois(roiImage, maskImage)
     for label in range(1, 11):  # 1:10
         assert result[label] == label
示例#5
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def extract_hagmann_density(connectome, roi_img, wm_img):
    """Populate hagmann density for given connectome"""

    def inverse_sum(elements):
        inverse_elements = []
        for element in elements:
            inverse_elements.append( 1.0 / element )
        from math import fsum
        return fsum(inverse_elements)

    # get surface areas for ROIs
    import images
    surface_area = images.surface_area_for_rois(roi_img, wm_img)

    # for every edge...
    for i,j in connectome.edges_iter():
        calc_hd = ( ( 2.0 / ( surface_area[i] + surface_area[j] ) ) * \
                  inverse_sum( connectome[i][j]['streamlines_length'] ) )
        connectome[i][j]['hagmann_density'] = calc_hd
示例#6
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    def populate_hagmann_density(self, WM_img, ROI_img):
        """Populate hagmann density."""

        def inverse_sum(elements):
            inverse_elements = []
            for element in elements:
                inverse_elements.append( 1.0 / element )
            from math import fsum
            return fsum(inverse_elements)

        # get surface areas for ROIs
        import images
        surface_area = images.surface_area_for_rois(ROI_img, WM_img)

        # for every edge...
        for i,j in self.edges_iter():
            calc_hd = ( ( 2.0 / ( surface_area[i] + surface_area[j] ) ) * \
                        inverse_sum( self[i][j]['streamlines_length'] ) )
            self[i][j]['hagmann_density'] = calc_hd