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Deleted unnecessary attributes from QTree.
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Added more documentations.
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@Sad-Abd
Sad-Abd committed Jul 12, 2023
1 parent c0087b4 commit dd7107c
Showing 1 changed file with 93 additions and 38 deletions.
131 changes: 93 additions & 38 deletions src/qtreemesh/_qtreemesh.py
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Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
"""
A module for generating quadtree mesh from an image.
Author : Sad_Abd
Author : Sadjad Abedi
"""

import numpy as np
Expand Down Expand Up @@ -66,21 +66,68 @@ class QTree():
----------
parent : None or QTree object
Parent leaf of current leaf
array : numpy array
Corresponding partition of image array.
crit : int, optional
The criteria used for partitioning. Default value is 1.
scale : float, optional
The ratio between pixels units and real units. For example, when scale is 2,
each pixel represents a 2*2 ($mm^2$ or $in^2$ or ...) square part of the object.
This parameter is used to calculate spatial location of pixels.
Default value is 1.
bottom_left_corner : Point, optional
A Point object that contains the coordinate of the bottom left corner of each
partition. Default position is (0.0,0.0).
top_right_corner : Point
A Point object that contains the coordinate of the top right corner of each
partition. Calculated from bottom_left_corner.
dimension : int
Dimension of the cell (number of pixels in each direction).
depth : int, optional
Depth of the node in tree. It's 0 for the root.
property : float
An indicator for material properties calculated by averaging
the pixels intensities.
divided : bool
Indicate wether the cell is divided (is an inner node) or not (is a leaf).
count_leaves : int
Total number of leaves
Total number of external nodes (leaves).
north_west : None or QTree object
Address the cell located in northwest part of current cell. None for leaves.
north_east : None or QTree object
Address the cell located in northeast part of current cell. None for leaves.
south_west : None or QTree object
Address the cell located in southwest part of current cell. None for leaves.
south_east : None or QTree object
Address the cell located in southeast part of current cell. None for leaves.
Methods
-------
sectors()
A recursive function to create subtrees.
A recursive function to partition the array and create subtrees.
save_leaves()
A method that returns a list of external nodes (leaves).
north_neighbor()
A recursive function that return north neighbor of the cell.
return none if the cell is on the top of the image.
south_neighbor()
A recursive function that return south neighbor of the cell.
return none if the cell is on the bottom of the image.
west_neighbor()
A recursive function that return west neighbor of the cell.
return none if the cell is on the left side of the image.
east_neighbor()
A recursive function that return east neighbor of the cell.
return none if the cell is on the right side of the image.
need_split(node):
Check 4 sides neighbors for more than 2:1 ratio. Return True
if the cell has to be splitted for 2:1 balancing.
balancing():
Balance QTree for 2:1 ratio.
"""
def __init__(self, parent, array, crit=1, scale=1,
def __init__(self, parent, array, crit=1, scale=1.,
bottom_left_corner=Point((0.0, 0.0)), depth = 0):
self.north_west = None # NorthWest Section Initiated Empty
self.north_east = None # NorthEast Section Initiated Empty
Expand All @@ -97,18 +144,15 @@ def __init__(self, parent, array, crit=1, scale=1,
self.bottom_left_corner = bottom_left_corner # BottomLeft Coordinates
self.top_right_corner = bottom_left_corner.coord_sum(
(array.shape[1]*scale, array.shape[0]*scale)) # TopRight Coordinates
self.element_numbers = None
self.node_numbers = list()
self.dimension = np.sqrt(array.size) # To define scale requirement
self.element_type = None

# SPLITTING
if (np.max(array)-np.min(array)) > crit: # Check Splitting Criteria
self.sectors()

def sectors(self):
"""
A recursive function to create subtrees
A recursive function to create subtrees.
Parameters
----------
Expand Down Expand Up @@ -311,7 +355,8 @@ def east_neighbor(self):
@staticmethod
def need_split(node):
"""
Check 4 sides neighbors for more than 2:1 ratio.
Check 4 sides neighbors for more than 2:1 ratio. Return True
if the cell has to be splitted for 2:1 balancing.
Returns
-------
Expand Down Expand Up @@ -374,16 +419,26 @@ class QTreeElement():
Attributes
----------
-- : --
--
number : int
Element number label.
nodes_numbers : list(int)
Number of nodes of the element. The order of nodes is counterclockwise.
nodes_coordinates : list(tuple)
A list that contains a tuple of x-y coordinates of the nodes
based on nodes_numbers.
element_type : list()
A list that contains three values. First value indicate the element
mode based on basic modes (1 to 6). The second value indicate the
angle of rotation that element needs to convert to basic modes. The
third value indicate scale parameter. [Used for SBFEM mesh]
element_property : float
Element indicator of material properties calculated by averaging
the pixels intensities.
Methods
-------
--()
--
--()
"""
Expand Down Expand Up @@ -415,7 +470,7 @@ class QTreeMesh():
--()
"""
"""
def __init__(self, quad_tree:QTree, balancing = True) -> None:
"""_summary_
Expand All @@ -435,10 +490,10 @@ def create_elements(self):
self.labeling()
self.refactor_edge()
for leaf in self.leaves:
label = leaf.element_number
node_number = leaf.node_numbers
label = leaf.cell_number
node_number = leaf.edge_points_numbers
node_coordinate = [self.nodes[n-1,:] for n in node_number]
element_type = leaf.element_type
element_type = leaf.cell_type
element_property = leaf.property
self.elements.append(QTreeElement(label,node_number,node_coordinate,
element_type,element_property))
Expand All @@ -462,7 +517,7 @@ def labeling(self):
label = 1

for leaf in self.leaves:
leaf.node_numbers = []
leaf.edge_points_numbers = []
leaf.nodes_coordinate = []
leaf.nodes_coordinate.append(np.array(leaf.bottom_left_corner.xy_coord))
leaf.nodes_coordinate.append(np.array((leaf.top_right_corner.x_coord,
Expand All @@ -473,13 +528,13 @@ def labeling(self):
leaf.top_right_corner.y_coord)))
for node in leaf.nodes_coordinate: #Creating Element node list
if any(np.equal(self.nodes,node).all(1)):
leaf.node_numbers.append(
leaf.edge_points_numbers.append(
np.where(np.equal(self.nodes,node).all(1) == True)[0][0])
else:
self.nodes = np.r_[self.nodes,[node]]
leaf.node_numbers.append(self.nodes.shape[0]-1)
leaf.edge_points_numbers.append(self.nodes.shape[0]-1)

leaf.element_number = label
leaf.cell_number = label
label += 1
self.nodes = self.nodes[1:,:]

Expand All @@ -496,50 +551,50 @@ def refactor_edge(self):
newedge = list()
mode = list()

newedge.append(leaf.node_numbers[0])
newedge.append(leaf.edge_points_numbers[0])
if leaf.south_neighbor() is not None:
if leaf.south_neighbor().divided:
newedge.append(leaf.south_neighbor().north_west.node_numbers[3])
newedge.append(leaf.south_neighbor().north_west.edge_points_numbers[3])
mode.append(True)
else:
mode.append(False)
else:
mode.append(False)

newedge.append(leaf.node_numbers[1])
newedge.append(leaf.edge_points_numbers[1])
if leaf.east_neighbor() is not None:
if leaf.east_neighbor().divided:
newedge.append(leaf.east_neighbor().north_west.node_numbers[0])
newedge.append(leaf.east_neighbor().north_west.edge_points_numbers[0])
mode.append(True)
else:
mode.append(False)
else:
mode.append(False)

newedge.append(leaf.node_numbers[2])
newedge.append(leaf.edge_points_numbers[2])
if leaf.north_neighbor() is not None:
if leaf.north_neighbor().divided:
newedge.append(leaf.north_neighbor().south_east.node_numbers[0])
newedge.append(leaf.north_neighbor().south_east.edge_points_numbers[0])
mode.append(True)
else:
mode.append(False)
else:
mode.append(False)

newedge.append(leaf.node_numbers[3])
newedge.append(leaf.edge_points_numbers[3])
if leaf.west_neighbor() is not None:
if leaf.west_neighbor().divided:
newedge.append(leaf.west_neighbor().south_east.node_numbers[2])
newedge.append(leaf.west_neighbor().south_east.edge_points_numbers[2])
mode.append(True)
else:
mode.append(False)
else:
mode.append(False)

element_type = self.mode_detection(mode)
element_type.append(leaf.dimension)
leaf.node_numbers = newedge
leaf.element_type = element_type
cell_type = self.mode_detection(mode)
cell_type.append(leaf.dimension)
leaf.edge_points_numbers = newedge
leaf.cell_type = cell_type

@staticmethod
def mode_detection(mode):
Expand Down

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