neurom.check.morphtree¶
Python module of NeuroM to check neuronal trees.
Functions
Get neurites that have back-tracks. |
|
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. |
|
Calculate the extent of a set of 3D points. |
Classes
Column labels for internal data representation. |
-
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 back-tracks.
A back-track 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
neurite (Neurite) – 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=1e-06)[source]¶ Get neurites that are not monotonic.
- Parameters
neurite (Neurite) – neurite 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.
Back-tracking 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