Triangulation: Basic level with ability to place points

Diagrams.org

@@ -1,7 +1,9 @@
+# -*- mode: Org; eval: (olivetti-mode 0) -*- #
+
 * The topics
 #+begin_src syntree
 ("Game Programming Fundamentals"
-  ("Math" "_:Data Structures" "_:Algorithms" "_:Linear Algebra")
+  ("Math" "_:Data Structures" "_:Algorithms" "_:Linear Algebra" "_:Geometry")
   ("Engineering"
    ("Machine Architecture" "_:CPU Design" "_:Memory Hierarchy" "_:Processes" "_:Concurrency")
    "_:Networking"
@@ -12,16 +14,26 @@
 #+RESULTS:
 #+begin_example
                                                           Game Programming Fundamentals                                                                                     
-                      ._________________________________________|_________________________________________.                                                       
+                            .___________________________________________|___________________________________________.                                                       
                             |                                                                                       |                                                       
                            Math                                                                                Engineering                                                  
-       .______________|_____________.                                  .________________________________._|________._________________________.                    
+       .______________._____|_______.____________.                               .________________________________._|________._________________________.                    
-       |              |             |                                  |                                |          |                         |                    
+       |              |             |            |                               |                                |          |                         |                    
-.______|______.  .____|___.  .______|_____.                  Machine Architecture                  .____|___.  .___|___.             Operating Systems            
+.______|______.  .____|___.  .______|_____.  .___|__.                  Machine Architecture                  .____|___.  .___|___.             Operating Systems            
-|_____________|  |________|  |____________|       .______________._____|_______.___________.       |________|  |_______|       .____________.|_____________.      
+|_____________|  |________|  |____________|  |______|       .______________._____|_______.___________.       |________|  |_______|       .____________.|_____________.      
-Data Structures  Algorithms  Linear Algebra       |              |             |           |       Networking  Compilers       |            |              |      
+Data Structures  Algorithms  Linear Algebra  Geometry       |              |             |           |       Networking  Compilers       |            |              |      
                                                        .____|___.  ._______|______.  .___|___.  .____|____.                         .____|___.  ._____|____.  .______|_____.
                                                        |________|  |______________|  |_______|  |_________|                         |________|  |__________|  |____________|
                                                        CPU Design  Memory Hierarchy  Processes  Concurrency                         Scheduling  File Systems  Virtual Memory
                                                                                                                                                                             
 #+end_example
+
+#+begin_src syntree
+("Graphics"
+  ("Math" "_:Data Structures" "_:Algorithms" "_:Linear Algebra")
+  ("Engineering"
+   ("Machine Architecture" "_:CPU Design" "_:Memory Hierarchy" "_:Processes" "_:Concurrency")
+   "_:Networking"
+   "_:Compilers"
+   ("Operating Systems" "_:Scheduling" "_:File Systems" "_:Virtual Memory")))
+#+end_src

Topics.org

@@ -0,0 +1,10 @@
+#+TITLE Topics for Gaming Pads
+
+* GAIMENPAAADS
+* List of things to study
+** Quadtrees (Ongoing)
+** Triangulation
+** Bezier Curves
+** SIMD
+** Multithreading
+** Boids

content/GamingPads.org

@@ -0,0 +1,19 @@
+* Gaming Pads
+It's how the acronym GAIMENPAAADS sounds, but that's a crappy acronym. Here is
+a hierarchical overview of the topics
+** Math
+*** Trigonometry
+*** Data Structures
+*** Algorithms
+*** Linear Algebra
+*** Geometry
+**** Bezier Curves
+**** Triangulation
+**** Spatial Partitioning
+#+transclude: [[file:Quadtree.org]] :level 5 :exclude-elements "keyword"
+#+transclude: [[file:KD-Tree.org]] :level 5 :exclude-elements "keyword"
+** Engineering
+*** Machine Architecture
+*** Networking
+*** Compilers
+*** Operating Systems

content/Geometry.org

@@ -0,0 +1,6 @@
+#+TODO: ⬜ 🟩️ | ✅
+
+* Geometry
+** [[file:SpatialPartitioning.org][Spatial Partitioning]]
+** [[file:Triangulation.org][Triangulation]]
+** Bezier Curves

content/KD-Tree.org

@@ -0,0 +1,8 @@
+#+NAVIGATION_UP: [[file:SpatialPartitioning.org][Spacial Partitioning]]
+
+* KD-Tree
+Info about a KD-Tree
+** Linked Implementation                                     :datastructure:
+** Array Implementation                                      :datastructure:
+** Insertion                                                     :algorithm:
+** Find Nearest Neighbor                                         :algorithm:

content/Math.org

@@ -0,0 +1 @@
+* Math

content/Quadtree.org

@@ -0,0 +1,57 @@
+#+TEST: [[file:SpatialPartitioning.org][Spacial Partitioning]]
+
+* Quadtree
+Recursively subdivide an AABB into 4 regions, hence Quad. They are usually
+denoted as North West, North East, South West, and South East (NW, NE, SW, SE).
+Several things can be created with this;
+** Linked Implementation                                     :datastructure:
+** Array Implementation                                      :datastructure:
+** Insertion                                                     :algorithm:
+** Query                                                         :algorithm:
+** Find Nearest Neighbor                                         :algorithm:
+** Resources
+[[http://ericandrewlewis.github.io/how-a-quadtree-works/][Visualize a Quadtree]]
+[[http://donar.umiacs.umd.edu/quadtree/][Academic Interactive Demo]]
+** Notes
+// exclude node if point is farther away than best distance in either axis
+if (x < x1 - best.d || x > x2 + best.d || y < y1 - best.d || y > y2 + best.d) {
+    return best;
+}
+
+ 
+I don't know how to explain but I get it. Because of the euclidian distance and the fact that we're dealing with rectangles, the closest distance to a rectangle is a straight line in one of the x or y axis
+So if the point we're checking is farther away from the rectangle on either axis, then it cannot possible be the case that it is closer
+I still can't visualize or understand it intuitively, I more just trust that it works, maybe if I see it in action it'll click better
+JosephFerano
+ — 
+Today at 4:15 PM
+This is some clever math shit this guy is doing
+Or that he picked up
+https://gist.github.com/patricksurry/6478178
+Gist
+D3JS quadtree nearest neighbor algorithm
+D3JS quadtree nearest neighbor algorithm. GitHub Gist: instantly share code, notes, and snippets.
+D3JS quadtree nearest neighbor algorithm
+
+    // check if kid is on the right or left, and top or bottom
+    // and then recurse on most likely kids first, so we quickly find a 
+    // nearby point and then exclude many larger rectangles later
+    var kids = node.nodes;
+    var rl = (2*x > x1 + x2), bt = (2*y > y1 + y2);
+    if (kids[bt*2+rl]) best = nearest(x, y, best, kids[bt*2+rl]);
+    if (kids[bt*2+(1-rl)]) best = nearest(x, y, best, kids[bt*2+(1-rl)]);
+    if (kids[(1-bt)*2+rl]) best = nearest(x, y, best, kids[(1-bt)*2+rl]);
+    if (kids[(1-bt)*2+(1-rl)]) best = nearest(x, y, best, kids[(1-bt)*2+(1-rl)]);
+
+That's kinda neat, estimating probability with some math and then going into the index of the array where the point is more likely to be
+No idea why this works
+But I think I'm done with this
+Interesting, he doesn't even check if any of the rects contain the point
+Hmmm
+Oh I see
+It's because he's tracking whether a node is visited or not, and I'm putting in a lot of work to make sure you don't revisit the same node twice, but I don't do it with a "visited" bool, which I intentionally avoided but now seeing his solution, I realize it may have been a mistake
+JosephFerano
+ — 
+Today at 4:27 PM
+Actually I don't think adding "visited" is a good idea, because you have to walk through the whole thing again once you're done to uncheck all the visited bools. That's a linear walk through all the nodes, which might not be much, but it's certainly  making things slower
+I'll have to investigate further

content/SpatialPartitioning.org

@@ -0,0 +1,9 @@
+# -*- mode: Org; eval: (org-transclusion-mode 0) -*- #
+#+NAVIGATION-UP: [[file:Geometry.org][Geometry]]
+
+* Spatial Partitioning
+These are used to divide a space in either a 2D or 3D world into smaller spaces
+that can make operations like searching and filtering more efficient.
+
+#+transclude: [[file:Quadtree.org]] :level 2
+#+transclude: [[file:KD-Tree.org]] :level 2

content/Triangulation.org

@@ -0,0 +1,57 @@
+#+TEST: [[file:Geometry][Geometry]]
+
+* Quadtree
+Recursively subdivide an AABB into 4 regions, hence Quad. They are usually
+denoted as North West, North East, South West, and South East (NW, NE, SW, SE).
+Several things can be created with this;
+** Linked Implementation                                     :datastructure:
+** Array Implementation                                      :datastructure:
+** Insertion                                                     :algorithm:
+** Query                                                         :algorithm:
+** Find Nearest Neighbor                                         :algorithm:
+** Resources
+[[http://ericandrewlewis.github.io/how-a-quadtree-works/][Visualize a Quadtree]]
+[[http://donar.umiacs.umd.edu/quadtree/][Academic Interactive Demo]]
+** Notes
+// exclude node if point is farther away than best distance in either axis
+if (x < x1 - best.d || x > x2 + best.d || y < y1 - best.d || y > y2 + best.d) {
+    return best;
+}
+
+ 
+I don't know how to explain but I get it. Because of the euclidian distance and the fact that we're dealing with rectangles, the closest distance to a rectangle is a straight line in one of the x or y axis
+So if the point we're checking is farther away from the rectangle on either axis, then it cannot possible be the case that it is closer
+I still can't visualize or understand it intuitively, I more just trust that it works, maybe if I see it in action it'll click better
+JosephFerano
+ — 
+Today at 4:15 PM
+This is some clever math shit this guy is doing
+Or that he picked up
+https://gist.github.com/patricksurry/6478178
+Gist
+D3JS quadtree nearest neighbor algorithm
+D3JS quadtree nearest neighbor algorithm. GitHub Gist: instantly share code, notes, and snippets.
+D3JS quadtree nearest neighbor algorithm
+
+    // check if kid is on the right or left, and top or bottom
+    // and then recurse on most likely kids first, so we quickly find a 
+    // nearby point and then exclude many larger rectangles later
+    var kids = node.nodes;
+    var rl = (2*x > x1 + x2), bt = (2*y > y1 + y2);
+    if (kids[bt*2+rl]) best = nearest(x, y, best, kids[bt*2+rl]);
+    if (kids[bt*2+(1-rl)]) best = nearest(x, y, best, kids[bt*2+(1-rl)]);
+    if (kids[(1-bt)*2+rl]) best = nearest(x, y, best, kids[(1-bt)*2+rl]);
+    if (kids[(1-bt)*2+(1-rl)]) best = nearest(x, y, best, kids[(1-bt)*2+(1-rl)]);
+
+That's kinda neat, estimating probability with some math and then going into the index of the array where the point is more likely to be
+No idea why this works
+But I think I'm done with this
+Interesting, he doesn't even check if any of the rects contain the point
+Hmmm
+Oh I see
+It's because he's tracking whether a node is visited or not, and I'm putting in a lot of work to make sure you don't revisit the same node twice, but I don't do it with a "visited" bool, which I intentionally avoided but now seeing his solution, I realize it may have been a mistake
+JosephFerano
+ — 
+Today at 4:27 PM
+Actually I don't think adding "visited" is a good idea, because you have to walk through the whole thing again once you're done to uncheck all the visited bools. That's a linear walk through all the nodes, which might not be much, but it's certainly  making things slower
+I'll have to investigate further

quadtree.py

@@ -1,13 +1,13 @@
 import pyray as RL
-from pyray import (Rectangle as Rect)
+from pyray import (Rectangle as Rect, Vector2 as Vec2)
 import math
 import pdb
 import random
 from typing import Optional, Tuple, List
 from dataclasses import dataclass, field
 
-screen_width = 1280
+screen_width = 1200
-screen_height = 1024
+screen_height = 960
 
 ball_r = 6
 ball_speed = 3.5
@@ -44,6 +44,10 @@ class World:
     tick = 0
     paused = False
     mouse_clicks = []
+    nearest_points = []
+    visited_quadrants = []
+    nearest_pairs = []
+    current_visited = 0
 
 w = World()
 
@@ -85,79 +89,55 @@ def qt_insert(qt: Quadtree, p):
         return True
 
 def qt_find_nearest_point(qt: Quadtree, point) -> Tuple[float, float]:
-    closest_point = None
-    closest_dist = None
-    last_direction = None
     containing_qt = qt
-    # Find the containing subnode
     while containing_qt.subdivided:
-        if RL.check_collision_point_rec(point, qt.nw.node.aabb):
+        if RL.check_collision_point_rec(point, containing_qt.nw.node.aabb):
-            containing_qt = qt.nw
+            containing_qt = containing_qt.nw
-        elif RL.check_collision_point_rec(point, qt.ne.node.aabb):
+        elif RL.check_collision_point_rec(point, containing_qt.ne.node.aabb):
-            containing_qt = qt.ne
+            containing_qt = containing_qt.ne
-        elif RL.check_collision_point_rec(point, qt.sw.node.aabb):
+        elif RL.check_collision_point_rec(point, containing_qt.sw.node.aabb):
-            containing_qt = qt.sw
+            containing_qt = containing_qt.sw
-        elif RL.check_collision_point_rec(point, qt.se.node.aabb):
+        elif RL.check_collision_point_rec(point, containing_qt.se.node.aabb):
-            containing_qt = qt.se
+            containing_qt = containing_qt.se
 
-    while containing_qt.parent is not None:
+    def search_for_nearest(qt: Quadtree, direction = ''):
-        # If it's greater than 1, then we  have a point inside we can compare to
+        nonlocal closest_point, closest_dist
-        if len(containing_qt.node.points) > 1:
+        contains_point = RL.check_collision_point_rec(point, qt.node.aabb)
+        if not contains_point:
+            px, py = point.x, point.y
+            dx, dy = 0,0
+            if px < qt.node.aabb.x:
+                dx = qt.node.aabb.x - px
+            elif px > qt.node.aabb.x + qt.node.aabb.width:
+                dx = px - (qt.node.aabb.x + qt.node.aabb.width)
+            if py < qt.node.aabb.y:
+                dy = qt.node.aabb.y - py
+            elif py > qt.node.aabb.y + qt.node.aabb.height:
+                dy = py - (qt.node.aabb.y + qt.node.aabb.height)
+            dist = RL.vector2_length(Vec2(dx, dy))
+            if dist >= closest_dist:
+                return
+        if qt.subdivided:
+            if direction != 'NW': search_for_nearest(qt.nw)
+            if direction != 'NE': search_for_nearest(qt.ne)
+            if direction != 'SW': search_for_nearest(qt.sw)
+            if direction != 'SE': search_for_nearest(qt.se)
+
+        w.visited_quadrants.append(qt)
         for p in qt.node.points:
-                if p == point:
+            d = RL.vector_2distance(point, Vec2(p[0], p[1]))
-                    continue
+            if d < closest_dist:
-                if closest_dist is None or RL.vector_2distance(Vec2(*point), Vec2(*p)) < closest_dist:
                 closest_point = p
-            last_direction = containing_qt.direction
+                closest_dist = d
+    closest_point = None
+    closest_dist = float('inf')
+    previous_direction = ''
+    while containing_qt is not None:
+        search_for_nearest(containing_qt, previous_direction)
+        previous_direction = containing_qt.direction
         containing_qt = containing_qt.parent
-        else:
-            # If there aren't any other points in here, then we can't create a
-            # closest_point or a closest_dist. We would have to handle that later on
-            if not containing_qt.subdivided:
-                last_direction = containing_qt.direction
-                containing_qt = containing_qt.parent
-            else:
-                # def search_for_nearest(child_qt: Quadtree):
-                # We have to generalize this code, most likely, because it feels like
-                # we have to do this recursively until we have exhausted all quadrants
 
-                px, py = point
+    return closest_point
-                # This is where we check the surrounding nodes and try to discard nodes
-                if last_direction == 'NW':
-                    xse, yse = containing_qt.se.node.aabb.x, containing_qt.se.node.aabb.y
-
-                    ne_dist = containing_qt.ne.node.aabb.x - px
-                    if ne_dist < closest_dist:
-                        closest_dist = True
-                        # Now we have to search inside, but we would have to do recursively
-                        pass
-                    sw_dist = containing_qt.sw.node.aabb.y - py
-                    se_dist = RL.vector_2distance(Vec2(*point), Vec2(xse, yse)) 
-                    assert se_dist >= 0, 'ITS LESS THAN 0!!!!'
-                if last_direction == 'NE':
-                    xsw, ysw = containing_qt.sw.node.aabb.x, containing_qt.sw.node.aabb.y
-
-                    nw_dist = px - containing_qt.nw.node.aabb.x
-                    sw_dist = RL.vector_2distance(Vec2(xsw, ysw), Vec2(*point))
-                    assert sw_dist >= 0, 'ITS LESS THAN 0!!!!'
-                    se_dist = containing_qt.se.node.aabb.y - py
-                if last_direction == 'SW':
-                    xne, yne = containing_qt.ne.node.aabb.x, containing_qt.ne.node.aabb.y
-
-                    nw_dist = px - containing_qt.nw.node.aabb.x
-                    ne_dist = RL.vector_2distance(Vec2(xne, yne), Vec2(*point))
-                    assert ne_dist >= 0, 'ITS LESS THAN 0!!!!'
-                    se_dist = containing_qt.se.node.aabb.x - px
-                if last_direction == 'SE':
-                    xnw, ynw = containing_qt.nw.node.aabb.x, containing_qt.nw.node.aabb.y
-
-                    nw_dist = RL.vector_2distance(Vec2(xnw, ynw), Vec2(*point))
-                    ne_dist = py - containing_qt.nw.node.aabb.y
-                    assert ne_dist >= 0, 'ITS LESS THAN 0!!!!'
-                    sw_dist = px - containing_qt.se.node.aabb.x
-
-                last_direction = containing_qt.direction
-                containing_qt = containing_qt.parent
                 
 
 def construct_quadtree(points):
@@ -185,17 +165,17 @@ def player_input():
     if RL.is_key_pressed(RL.KEY_SPACE):
         w.paused = not w.paused
     if RL.is_mouse_button_pressed(0):
-        print(RL.get_mouse_position())
+        mouse_pos = RL.get_mouse_position()
-        w.mouse_clicks.append(RL.get_mouse_position())
+        nearest = qt_find_nearest_point(w.qt, mouse_pos)
+        w.nearest_pairs.append((mouse_pos, nearest))
+        w.paused = True
+    if RL.is_key_pressed(RL.KEY_ENTER):
+        w.current_visited += 1
     
 def update():
     # Recontruct quadtree
     if w.paused:
         return
-    points = []
-    for b in w.balls:
-        points.append((b.px, b.py))
-    w.qt = construct_quadtree(points)
     
     for ball in w.balls:
         ball.px += ball.vx
@@ -209,6 +189,11 @@ def update():
             ball.py = RL.clamp(ball.py, ball_r + 0.1, screen_height - ball_r - 0.1)
             ball.vy *= -1
 
+    points = []
+    for b in w.balls:
+        points.append((b.px, b.py))
+    w.qt = construct_quadtree(points)
+
 def draw_qt_dfs(qt: Quadtree):
     if not qt:
         return
@@ -223,10 +208,19 @@ def draw():
 
     RL.clear_background(RL.WHITE)
     draw_qt_dfs(w.qt)
+    for i in range(w.current_visited):
+        RL.draw_rectangle_rec(w.visited_quadrants[i].node.aabb, RL.LIGHTGRAY)
     for ball in w.balls:
         RL.draw_circle_lines_v((ball.px, ball.py), ball_r, RL.BLACK)
     for mc in w.mouse_clicks:
         RL.draw_circle_v(mc, 5, RL.RED)
+    for np in w.nearest_points:
+        RL.draw_circle_lines_v(Vec2(np[0], np[1]), ball_r, RL.GREEN)
+    for mc,(px,py) in w.nearest_pairs:
+        pos = Vec2(px, py)
+        RL.draw_circle_v(mc, 5, RL.RED)
+        RL.draw_circle_lines_v(pos, ball_r, RL.GREEN)
+        RL.draw_line_v(mc, pos, RL.BLUE)
 
     RL.end_drawing()
 

starter.py

@@ -1,5 +1,5 @@
 import pyray as RL
-from pyray import (Rectangle as Rect)
+from pyray import (Rectangle as Rect, Vector2 as Vec2, Vector3 as Vec3, Camera3D)
 import math
 import pdb
 import random
@@ -11,29 +11,44 @@ screen_height = 1024
 
 @dataclass
 class World:
+    cam: Camera3D
+    frame_count: int = 0
+
+def init() -> World:
     pass
 
-def init():
+def player_input(w: World):
     pass
 
-def player_input():
+def update(w: World):
     pass
 
-def update():
+def draw_3d(w: World):
     pass
 
-def draw():
+def draw_2d(w: World):
-    RL.begin_drawing()
+    pass
-    RL.clear_background(RL.WHITE)
-
-    RL.end_drawing()
 
 RL.init_window(screen_width, screen_height, "Starter");
 RL.set_target_fps(60)
 
 init()
+cam = Camera3D(Vec3(0, 0, 10), RL.vector3_zero(), Vec3(0, 1, 0), 60, 1)
+w = World(cam)
 while not RL.window_should_close():
-    player_input()
+    player_input(w)
-    update()
+    update(w)
-    draw()
+
+    # Drawing
+    RL.begin_drawing()
+    RL.clear_background(RL.WHITE)
+
+    RL.begin_mode_3d(w.cam)
+    draw_3d(w)
+    RL.end_mode_3d()
+
+    draw_2d(w)
+
+    RL.end_drawing()
+    w.frame_count += 1
     

triangulation.py

@@ -0,0 +1,73 @@
+import pyray as RL
+from pyray import (Rectangle as Rect, Vector2 as Vec2, Vector3 as Vec3, Camera3D, BoundingBox)
+import math
+import pdb
+import random
+from typing import Optional, Tuple, List
+from dataclasses import dataclass, field
+
+screen_width = 1280
+screen_height = 1024
+grid_slices = 100
+grid_spacing = 0.2
+
+@dataclass
+class World:
+    cam: Camera3D
+    floor_bb: BoundingBox
+    rotate_cam: bool = True
+    frame_count: int = 0
+    vertices: List[Vec3] = field(default_factory=list)
+
+def init() -> World:
+    cam = Camera3D(Vec3(0, 10, 10), Vec3(0, 0, 0), Vec3(0, 1, 0), 45, RL.CAMERA_PERSPECTIVE)
+    half_grid = grid_slices * grid_spacing * 0.5
+    floor_bb = BoundingBox(Vec3(-half_grid, -0.01, -half_grid), Vec3(half_grid, 0.01, half_grid))
+    return World(cam, floor_bb)
+
+def player_input(w: World):
+    if RL.is_key_pressed(RL.KEY_SPACE):
+        w.rotate_cam = not w.rotate_cam
+    if RL.is_mouse_button_pressed(0):
+        mouse_pos = RL.get_mouse_position()
+        ray = RL.get_mouse_ray(mouse_pos, w.cam)
+        collision = RL.get_ray_collision_box(ray, w.floor_bb)
+        if collision.hit:
+            p = collision.point
+            w.vertices.append(Vec3(p.x, 0, p.z))
+
+def update(w: World):
+    pass
+
+def draw_3d(w: World):
+    RL.draw_grid(grid_slices, grid_spacing)
+    RL.draw_bounding_box(w.floor_bb, RL.GREEN)
+    for vert in w.vertices:
+        RL.draw_sphere(vert, 0.1, RL.GREEN)
+
+def draw_2d(w: World):
+    pass
+
+RL.init_window(screen_width, screen_height, "Starter");
+RL.set_target_fps(60)
+
+w = init()
+while not RL.window_should_close():
+    player_input(w)
+    update(w)
+
+    # Drawing
+    if w.rotate_cam:
+        RL.update_camera(w.cam, RL.CameraMode.CAMERA_ORBITAL)
+    RL.begin_drawing()
+    RL.clear_background(RL.WHITE)
+
+    RL.begin_mode_3d(w.cam)
+    draw_3d(w)
+    RL.end_mode_3d()
+
+    draw_2d(w)
+
+    RL.end_drawing()
+    w.frame_count += 1
+