def principal_direction_extent(tree):
'''Calculate the extent of a tree, that is the maximum distance between
the projections on the principal directions of the covariance matrix
of the x,y,z points of the nodes of the tree.
Input:
tree : a tree object
Returns:
extents : the extents for each of the eigenvectors of the cov matrix
eigs : eigenvalues of the covariance matrix
eigv : respective eigenvectors of the covariance matrix
'''
# extract the x,y,z coordinates of all the points in the tree
points = np.array([p.value[COLS.X: COLS.R] for p in tree.ipreorder()])
return mm.principal_direction_extent(points)
def is_flat(neurite, tol, method='tolerance'):
'''Check if neurite is flat using the given method
Args:
neurite(Neurite): neurite to operate on
tol(float): tolerance
method(string): the method of flatness estimation:
'tolerance' returns true if any extent of the tree is smaller
than the given tolerance
'ratio' returns true if the ratio of the smallest directions
is smaller than tol. e.g. [1,2,3] -> 1/2 < tol
Returns:
True if neurite is flat
'''
ext = principal_direction_extent(neurite.points[:, COLS.XYZ])
assert method in ('tolerance', 'ratio'), "Method must be one of 'tolerance', 'ratio'"
if method == 'ratio':
sorted_ext = np.sort(ext)
return sorted_ext[0] / sorted_ext[1] < float(tol)
return any(ext < float(tol))
def is_flat(neurite, tol, method='tolerance'):
"""Check if neurite is flat using the given method.
Args:
neurite(Neurite): neurite to operate on
tol(float): tolerance
method(string): the method of flatness estimation:
'tolerance' returns true if any extent of the tree is smaller
than the given tolerance
'ratio' returns true if the ratio of the smallest directions
is smaller than tol. e.g. [1,2,3] -> 1/2 < tol
Returns:
True if neurite is flat
"""
ext = principal_direction_extent(neurite.points[:, COLS.XYZ])
assert method in ('tolerance',
'ratio'), "Method must be one of 'tolerance', 'ratio'"
if method == 'ratio':
sorted_ext = np.sort(ext)
return sorted_ext[0] / sorted_ext[1] < float(tol)
return any(ext < float(tol))
def is_flat(neurite, tol, method='tolerance'):
'''Check if neurite is flat using the given method
Input:
neurite : the neurite tree object
tol : tolerance
method : the method of flatness estimation. 'tolerance'
returns true if any extent of the tree
is smaller than the given tolerance
'ratio' returns true if the ratio of the smallest directions
is smaller than tol. e.g. [1,2,3] -> 1/2 < tol
Returns:
True if it is flat
'''
ext = principal_direction_extent(neurite.points[:, :3])
if method == 'ratio':
sorted_ext = np.sort(ext)
return sorted_ext[0] / sorted_ext[1] < float(tol)
else:
return any(ext < float(tol))
def _pde(neurite):
'''Get the PDE of a single neurite'''
# Get the X, Y,Z coordinates of the points in each section
points = neurite.points[:, :3]
return morphmath.principal_direction_extent(points)[direction]
def _pde(neurite):
"""Get the PDE of a single neurite"""
# Get the X, Y,Z coordinates of the points in each section
points = neurite.points[:, :3]
return morphmath.principal_direction_extent(points)[direction]
def _pde(neurite):
'''Get the PDE of a single neurite'''
# Get the X, Y,Z coordinates of the points in each section
points = neurite.points[:, :3]
return mm.principal_direction_extent(points)[direction]
