# Copyright (c) 2015, Ecole Polytechnique Federale de Lausanne, Blue Brain Project
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"""Dendrogram helper functions and class."""
import numpy as np
from neurom import NeuriteType
from neurom.core import Neurite, Neuron
from neurom.core.dataformat import COLS
from neurom.morphmath import interval_lengths
[docs]class Dendrogram(object):
"""Dendrogram."""
def __init__(self, neurom_section):
"""Dendrogram for NeuroM section tree.
Args:
neurom_section (Neurite|Neuron|Section): tree to build dendrogram for.
"""
if isinstance(neurom_section, Neuron):
self.neurite_type = NeuriteType.soma
self.height = 1
self.width = 1
self.coords = self.get_coords(
np.array([0, self.height]), np.array([.5 * self.width, .5 * self.width]))
self.children = [Dendrogram(neurite.root_node) for neurite in neurom_section.neurites]
else:
if isinstance(neurom_section, Neurite):
neurom_section = neurom_section.root_node
lengths = interval_lengths(neurom_section.points, prepend_zero=True)
radii = neurom_section.points[:, COLS.R]
self.neurite_type = neurom_section.type
self.height = np.sum(lengths)
self.width = 2 * np.max(radii)
self.coords = Dendrogram.get_coords(lengths, radii)
self.children = [Dendrogram(child) for child in neurom_section.children]
[docs] @staticmethod
def get_coords(segment_lengths, segment_radii):
"""Coordinates of dendrogram as polygon with respect to (0, 0) origin.
Args:
segment_lengths: lengths of dendrogram segments
segment_radii: radii of dendrogram segments
Returns:
(N,2) array of 2D x,y coordinates of Dendrogram polygon. N is the number of vertices.
"""
y_coords = np.cumsum(segment_lengths)
x_left_coords = -segment_radii
x_right_coords = segment_radii
left_coords = np.hstack((x_left_coords[:, np.newaxis], y_coords[:, np.newaxis]))
right_coords = np.hstack((x_right_coords[:, np.newaxis], y_coords[:, np.newaxis]))
right_coords = np.flip(right_coords, axis=0)
return np.vstack((left_coords, right_coords))
[docs]def layout_dendrogram(dendrogram, origin):
"""Lays out dendrogram as an aesthetical pleasing tree.
Args:
dendrogram (Dendrogram): dendrogram
origin (np.array): xy coordinates of layout origin
Returns:
Dict of positions per each dendrogram node. When placed in those positions, dendrogram nodes
will represent a nice tree structure.
"""
class _PositionedDendrogram(object):
"""Wrapper around dendrogram that allows to lay it out.
The layout happens only in X coordinates. Children's Y coordinate is just a parent's Y
+ parent's height. Algorithm is that we calculate bounding rectangle width of each
dendrogram's subtree. This width is a sum of all children widths calculated recursively
in `total_width`. If no children then the width is the dendrogram's width. After the
calculation we start to lay out. Each child gets its X coordinate as:
parent's X + previous sibling children widths + half of this child's width.
"""
HORIZONTAL_PADDING = 2
def __init__(self, dendrogram):
self.dendrogram = dendrogram
self.children = [_PositionedDendrogram(child) for child in dendrogram.children]
self.total_width = self.dendrogram.width
if self.children:
children_width = np.sum([child.total_width for child in self.children])
children_width += self.HORIZONTAL_PADDING * (len(self.children) - 1)
self.total_width = max(self.total_width, children_width)
def position_at(self, origin): # pylint: disable=missing-docstring
positions = {self.dendrogram: origin}
if self.children:
end_point = origin + [0, self.dendrogram.height]
left_bottom_offset = [-.5 * self.total_width, 0]
children_origin = end_point + left_bottom_offset
for child in self.children:
child_origin = children_origin + [.5 * child.total_width, 0]
positions.update(child.position_at(child_origin))
children_origin += [child.total_width + self.HORIZONTAL_PADDING, 0]
return positions
return _PositionedDendrogram(dendrogram).position_at(origin)
[docs]def get_size(positions):
"""Get the size of bounding rectangle that embodies positions.
Args:
positions (dict of Dendrogram: np.array): positions xy coordinates of dendrograms
Returns:
Tuple of width and height of bounding rectangle.
"""
max_y_list = [dendrogram.height + coords[1] for dendrogram, coords in positions.items()]
coords = np.array(list(positions.values()))
width = np.max(coords[:, 0]) - np.min(coords[:, 0])
height = np.max(max_y_list) - np.min(coords[:, 1])
return width, height
[docs]def move_positions(positions, to_origin):
"""Move positions to a new origin.
Args:
positions (dict of Dendrogram: np.array): positions
to_origin (np.array): where to move. np.array of (2,) shape for x,y coordindates.
Returns:
Moved positions.
"""
to_origin = np.asarray(to_origin)
return {dendrogram: position + to_origin for dendrogram, position in positions.items()}