neurots.generate.tree¶
NeuroTS class: Tree.
Module Attributes
Parameter that defines the slope of exponential probability. |
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The default diameter used to add new sections before they are diametrized later. |
Classes
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Tree class. |
- neurots.generate.tree.DEFAULT_DIAMETER = 1¶
The default diameter used to add new sections before they are diametrized later.
- neurots.generate.tree.LAMBDA = 1.0¶
Parameter that defines the slope of exponential probability.
- class neurots.generate.tree.SectionParameters(randomness, targeting, scale_prob, history)¶
Bases:
tuple
- _asdict()¶
Return a new dict which maps field names to their values.
- classmethod _make(iterable)¶
Make a new SectionParameters object from a sequence or iterable
- _replace(**kwds)¶
Return a new SectionParameters object replacing specified fields with new values
- history¶
Alias for field number 3
- randomness¶
Alias for field number 0
- scale_prob¶
Alias for field number 2
- targeting¶
Alias for field number 1
- class neurots.generate.tree.TreeGrower(neuron, initial_direction, initial_point, parameters, distributions, context=None, random_generator=numpy.random)¶
Bases:
object
Tree class.
- Parameters:
neuron (morphio.mut.Morphology) – The morphology in which groups and points are stored.
initial_direction (list[float]) – 3D vector that defines the starting direction of the tree.
initial_point (list[float]) – 3D vector that defines the starting point of the tree.
parameters (dict) – A dictionary with
tree_type
,radius
,randomness
andtargeting
keys.distributions (dict) – The distributions used.
context (Any) – The context used for the tree.
random_generator (numpy.random.Generator) – The random number generator to use.
- _initialize_algorithm()¶
Initialization steps for TreeGrower.
- add_section(parent, direction, first_point, stop, pathlength, process=None, children=0)¶
Generates a section from the parent section “act” from all the required information.
The section is added to the neuron.sections and activated.
- Parameters:
parent (morphio.Section) – The parent of the section.
stop (dict) – The stop criteria used for this section.
pathlength (float) – The path length of the section.
process (str) – The process type.
children (int) – The number of children.
- append_section(section)¶
Append section to the MorphIO neuron.
- Parameters:
section (SectionGrowerPath) – The section that is going to be appended.
- Returns:
The new appended section.
- Return type:
section (morphio.Section)
- end()¶
Ends the growth.
- next_point()¶
Operates the tree growth according to the selected algorithm.
- static order_per_bif(secs)¶
Orders sections according to bifurcation times.
- static order_per_process(secs)¶
Orders sections according to process type, major first.