neurom.check.morphtree¶
Python module of NeuroM to check neuronal trees.
Functions
Get neurites that have backtracks. 

Check if a neuron has neurites that are flat within a tolerance. 

Get neurites that are not monotonic. 

Check if a neurite process backtracks to a previous node. 

Check if neurite is flat using the given method. 

Check if neurite tree is monotonic. 

class
neurom.check.morphtree.
COLS
[source]¶ Bases:
object
Column labels for internal data representation.

neurom.check.morphtree.
get_back_tracking_neurites
(neuron)[source]¶ Get neurites that have backtracks.
A backtrack is the placement of a point near a previous segment during the reconstruction, causing a zigzag jump in the morphology which can cause issues with meshing algorithms.
 Parameters
neuron (Neuron) – neurite to operate on
 Returns
List of neurons with backtracks

neurom.check.morphtree.
get_flat_neurites
(neuron, tol=0.1, method='ratio')[source]¶ Check if a neuron has neurites that are flat within a tolerance.

neurom.check.morphtree.
get_nonmonotonic_neurites
(neuron, tol=1e06)[source]¶ Get neurites that are not monotonic.
 Parameters
neuron (Neuron) – neuron to operate on
tol (float) – the tolerance or the ratio
 Returns
list of neurites that do not satisfy monotonicity test

neurom.check.morphtree.
is_back_tracking
(neurite)[source]¶ Check if a neurite process backtracks to a previous node.
Backtracking takes place when a daughter of a branching process goes back and either overlaps with a previous point, or lies inside the cylindrical volume of the latter.
 Parameters
neurite (Neurite) – neurite to operate on
 Returns
A segment endpoint falls back and overlaps with a previous segment’s point
The geometry of a segment overlaps with a previous one in the section
 Return type
True Under the following scenaria

neurom.check.morphtree.
is_flat
(neurite, tol, method='tolerance')[source]¶ Check if neurite is flat using the given method.
 Parameters
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

neurom.check.morphtree.
is_monotonic
(neurite, tol)[source]¶ Check if neurite tree is monotonic.
If each child has smaller or equal diameters from its parent
 Parameters
neurite (Neurite) – neurite to operate on
tol (float) – tolerance
 Returns
True if neurite monotonic

neurom.check.morphtree.
principal_direction_extent
(points)[source]¶ Calculate the extent of a set of 3D points.
The extent is defined as the maximum distance between the projections on the principal directions of the covariance matrix of the points.
 Parameter:
points : a 2D numpy array of points
 Returns
the extents for each of the eigenvectors of the cov matrix eigs : eigenvalues of the covariance matrix eigv : respective eigenvectors of the covariance matrix
 Return type
extents