Made pr03 ready for handing it in

.idea/AlgoDatSoSe25.iml

@@ -5,7 +5,7 @@
       <excludeFolder url="file://$MODULE_DIR$/.venv" />
       <excludeFolder url="file://$MODULE_DIR$/venv" />
     </content>
-    <orderEntry type="jdk" jdkName="Python 3.12 (AlgoDatSoSe25)" jdkType="Python SDK" />
+    <orderEntry type="jdk" jdkName="Python 3.12 (SoSe25)" jdkType="Python SDK" />
     <orderEntry type="sourceFolder" forTests="false" />
   </component>
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2024/data/input16.data

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-#.#...............................#.#...#.....#.#.#.#...#...............#.....#.....#.........#.#.......#.#.......#...#.#...#...#...#.#...#.#
-#.#.#######.###.#####.#.###.#.#.###.#.#####.###.#.###.#.###########.#.#.#.#####.###.#####.###.#.#######.#.#####.#####.#.#.#.#.###.###.###.###
-#...#.....#.#...#.....#...#.#.#.#...#.#...#.........................................#...#...#...#.....#.......#...#...#...#.#...#.......#...#
-#.#.#.###.#.#.###.#######.#.#.#.#.###.#.#.###.#.#####.#######.#.#.#.#.#####.#.#######.#.#.#####.#.###.#####.###.#.#########.###.#.#########.#
-#.#.#.#.#...#.#.....#.......#...#...#.#.#.....#.....#.....#...#.#.#.#.#.....#.........#.#.....#.#.#.#...#...#.....................#.....#...#
-#.###.#.#####.#####.#.#####.#######.#.#.###########.#.###.#.###.#.###.###.#.###########.#.###.#.#.#.###.#####.###.#.###.#####.#.###.###.#.#.#
-#...#.#.....#...#...#.#...#.#.......#.#.#.......#...#...#...............#.#.........#.#.#.............#.....#.#.#...#.#.....................#
-#.#.#.###.#.###.#.#####.#.###.#######.#.#.#.#####.###.#.#.#########.###.#.#.#.#.###.#.#.#.#######.#.#.#####.#.#.#####.#####.#.###.###.###.#.#
-#S#.......#.....#.......#.....#.........#...............#...............#.....#.......#.............#.....#...............#.................#
-#############################################################################################################################################

2024/data/input16.example

@@ -1,15 +0,0 @@
-###############
-#.......#....E#
-#.#.###.#.###.#
-#.....#.#...#.#
-#.###.#####.#.#
-#.#.#.......#.#
-#.#.#####.###.#
-#...........#.#
-###.#.#####.#.#
-#...#.....#.#.#
-#.#.#.###.#.#.#
-#.....#...#.#.#
-#.###.#.#.#.#.#
-#S..#.....#...#
-###############

data/aoc2212test.txt

@@ -1,5 +0,0 @@
-Sabqponm
-abcryxxl
-accszExk
-acctuvwj
-abdefghi

data/aoc2416test.txt

@@ -1,15 +0,0 @@
-###############
-#.......#....E#
-#.#.###.#.###.#
-#.....#.#...#.#
-#.###.#####.#.#
-#.#.#.......#.#
-#.#.#####.###.#
-#...........#.#
-###.#.#####.#.#
-#...#.....#.#.#
-#.#.#.###.#.#.#
-#.....#...#.#.#
-#.###.#.#.#.#.#
-#S..#.....#...#
-###############

data/elektro.txt

@@ -1,8 +0,0 @@
-"Höhleneingang";"Ost/West-Passage";5
-"Höhleneingang";"Nord/Süd-Passage";3
-"Nord/Süd-Passage";"Nebelraum";7
-"Steiniger Pfad";"Ost/West-Passage";2
-"Ost/West-Passage";"Schwefelgewölbe";4
-"Schwefelgewölbe";"Steiniger Pfad";1
-"Schatzkammer";"Nebelraum";2
-"Steiniger Pfad";"Schatzkammer";6

data/hoehle.txt

@@ -1,8 +0,0 @@
-"Höhleneingang" <> "Ost/West-Passage"
-"Höhleneingang" <> "Nord/Süd-Passage"
-"Nord/Süd-Passage" <> "Nebelraum"
-"Steiniger Pfad" > "Ost/West-Passage"
-"Ost/West-Passage" <> "Schwefelgewölbe"
-"Schwefelgewölbe" > "Steiniger Pfad"
-"Schatzkammer" > "Nebelraum"
-"Steiniger Pfad" > "Schatzkammer"

data/hoehleLarger.txt

@@ -1,25 +0,0 @@
-"Höhleneingang" <> "Ost/West-Passage"
-"Höhleneingang" <> "Nord/Süd-Passage"
-"Nord/Süd-Passage" <> "Nebelraum"
-"Steiniger Pfad" > "Ost/West-Passage"
-"Ost/West-Passage" <> "Schwefelgewölbe"
-"Schwefelgewölbe" > "Steiniger Pfad"
-"Schatzkammer" > "Nebelraum"
-"Steiniger Pfad" <> "Schatzkammer"
-"Steiniger Pfad" > "Höhleneingang"
-"Kristallhöhle" <> "Schwefelgewölbe"
-"Kristallhöhle" <> "Nebelraum"
-"Versteckter Gang" > "Kristallhöhle"
-"Versteckter Gang" > "Schatzkammer"
-"Unterirdischer See" <> "Kristallhöhle"
-"Unterirdischer See" <> "Ost/West-Passage"
-"Geheimgang" > "Unterirdischer See"
-"Geheimgang" > "Versteckter Gang"
-"Abgrund" > "Geheimgang"
-"Abgrund" > "Nebelraum"
-"Verlorene Kammer" > "Abgrund"
-"Verlorene Kammer" > "Schwefelgewölbe"
-"Geheimgang" > "Schatzkammer"
-"Kristallhöhle" > "Höhleneingang"
-"Schwefelgewölbe" > "Höhleneingang"
-"Abgrund" > "Schatzkammer"

data/labyrinth.txt

@@ -1,9 +0,0 @@
-xxxxxxxxxxxxxxxxxxxxx
-x                   x
-x        S          x
-x                   x
-x      xxxxxxxx     x
-x                   x
-x                   x
-x            A      x
-xxxxxxxxxxxxxxxxxxxxx

data/labyrinth1.txt

@@ -1,5 +0,0 @@
-xxxxxAxxxxxxxxx
-x           xSx
-xxxxxxxxxx xx x
-x             x
-xxxxxxxxxxxxxxx

praktika/03_quick_and_heap/priority_queue.py

@@ -1,150 +0,0 @@
-from utils.memory_array import MemoryArray
-from utils.memory_cell import MemoryCell
-from utils.memory_manager import MemoryManager
-from utils.literal import Literal
-import random
-
-class PriorityQueue:
-
-    def __init__(self, size: Literal):
-        self.items = MemoryArray(size)
-        self.heapsize = MemoryCell(0)
-
-    def __len__(self):
-        return self.heapsize.value
-
-    def insert(self, item: MemoryCell):
-        if self.heapsize == self.items.length():
-            raise Exception("Queue is full")
-        self.heapsize.set(self.heapsize.succ())
-        self.items[adjust_index(self.heapsize)].set(item.value)
-        heapyfy_up(self.items, self.heapsize)
-
-
-    def pop(self) -> MemoryCell | None:
-        if self.is_empty():
-            return None
-        result = MemoryCell(self.items[Literal(0)])
-        self.heapsize.set(self.heapsize.pred())
-        if self.heapsize > Literal(1):
-            swap(self.items, 0, int(self.heapsize))
-            max_heapyfy(self.items, Literal(1), self.heapsize)
-        return result
-
-    def peek(self) -> MemoryCell | None:
-        if self.is_empty():
-            return None
-        return MemoryCell(self.items[Literal(0)])
-
-    def is_empty(self) -> bool:
-        return self.heapsize == Literal(0)
-
-    def __str__(self):
-        result = "[ "
-        for i, cell in enumerate(self.items.cells):
-            if i == int(self.heapsize):
-                result += "| "
-            result += str(cell) + " "
-        result += "]"
-        return result
-
-def left_child(i: Literal):
-    return Literal(2 * int(i))
-
-
-def right_child(i: Literal):
-    return Literal(2 * int(i) + 1)
-
-
-def adjust_index(i: Literal):
-    return i.pred()
-
-def heapyfy_up(z: MemoryArray, i: Literal):
-    if i == Literal(1):
-        return
-    parent = Literal(int(i) // 2)
-    if z[adjust_index(parent)] >= z[adjust_index(i)]:
-        return
-    swap(z, int(i)-1, int(parent)-1)
-    heapyfy_up(z, parent)
-
-
-def max_heapyfy(z: MemoryArray, i: Literal, heapsize: Literal):
-    l = left_child(i)
-    r = right_child(i)
-    with MemoryCell(i) as max_value:
-        if l <= heapsize and z[adjust_index(l)] > z[adjust_index(i)]:
-            max_value.set(l)
-        if r <= heapsize and z[adjust_index(r)] > z[adjust_index(max_value)]:
-            max_value.set(r)
-        if max_value != i:
-            swap(z, int(i)-1, int(max_value)-1)
-            max_heapyfy(z, max_value, heapsize)
-
-
-def swap(z: MemoryArray, i: int, j: int):
-    tmp = z[Literal(i)].value
-    z[Literal(i)] = z[Literal(j)]
-    z[Literal(j)].set(tmp)
-
-
-def analyze_complexity_insert(sizes, presorted=False):
-    """
-    Analysiert die Komplexität der Insert-Funktion.
-    """
-    for size in sizes:
-        MemoryManager().purge()  # Speicher zurücksetzen
-        pq = PriorityQueue(Literal(size))
-        insert_list = [random.randint(-100, 100) for _ in range(size)]
-        if presorted:
-            insert_list.sort()
-        for insert_value in insert_list[:-1]:
-            pq.insert(MemoryCell(insert_value))
-        MemoryManager().reset()
-        pq.insert(MemoryCell(insert_list[-1]))
-        MemoryManager.save_stats(size)
-
-    MemoryManager.plot_stats(["cells", "compares", "writes"])
-
-
-def analyze_complexity_pop(sizes, presorted=False):
-    """
-    Analysiert die Komplexität der Pop-Funktion.
-    """
-    for size in sizes:
-        MemoryManager().purge()  # Speicher zurücksetzen
-        pq = PriorityQueue(Literal(size))
-        insert_list = [random.randint(-100, 100) for _ in range(size)]
-        if presorted:
-            insert_list.sort()
-        for insert_value in insert_list:
-            pq.insert(MemoryCell(insert_value))
-        MemoryManager().reset()
-        pq.pop()
-        MemoryManager.save_stats(size)
-
-    MemoryManager.plot_stats(["cells", "compares", "writes"])
-
-
-if __name__ == '__main__':
-    length = Literal(10)
-    pq = PriorityQueue(length)
-    for i in range(10):
-        space_left = int(length) - len(pq)
-        if space_left > 0:
-            insert_count = random.randint(1, space_left)
-            insert_sequence = [random.randint(1, int(length)) for _ in range(insert_count)]
-            print(f"-> {insert_sequence}")
-            for j in insert_sequence:
-                pq.insert(MemoryCell(j))
-            print(f"{pq}")
-        if not pq.is_empty():
-            pop_count = random.randint(1, len(pq))
-            output_sequence = [int(pq.pop()) for _ in range(pop_count)]
-            print(f"<- {output_sequence}")
-            print(f"{pq}")
-
-    sizes = range(10, 501, 5)
-    analyze_complexity_insert(sizes, presorted=True)
-    analyze_complexity_pop(sizes, presorted=True)
-

praktika/03_quick_and_heap/quick_sorting_enhanced.py

@@ -1,93 +0,0 @@
-from utils.memory_array import MemoryArray
-from utils.memory_cell import MemoryCell
-from utils.memory_manager import MemoryManager
-from utils.literal import Literal
-
-def quick_sort_stepwise(z: MemoryArray, l: Literal, r: Literal):
-    if l < r:
-        q = partition(z, l, r)
-        yield z
-        yield from quick_sort_stepwise(z, l, q.pred())
-        yield from quick_sort_stepwise(z, q.succ(), r)
-        yield z
-
-
-def partition(z: MemoryArray, l: Literal, r: Literal):
-    p = mid_index(z, l, r, Literal((int(l)+int(r))//2))
-    swap(z, p, r)
-    with MemoryCell(z[r]) as pivot, MemoryCell(l) as i, MemoryCell(r.pred()) as j:
-        while i < j:
-            while z[i] < pivot:
-                i.set(i.succ())
-            while j > l and z[j] >= pivot:
-                j.set(j.pred())
-            if i < j:
-                swap(z, int(i), int(j))
-                i.set(i.succ())
-                j.set(j.pred())
-        if i == j and z[i] < pivot:
-            i.set(i.succ())
-        if z[i] != pivot:
-            swap(z, int(i), int(r))
-        return Literal(i)
-
-def mid_index(z: MemoryArray, i1, i2, i3):
-    if z[i1] < z[i2] < z[i3]:
-        return i2
-    elif z[i3] < z[i2] < z[i1]:
-        return i2
-    elif z[i2] < z[i1] < z[i3]:
-        return i1
-    elif z[i3] < z[i1] < z[i2]:
-        return i1
-    else:
-        return i3
-
-def quick_sort(z: MemoryArray, l: Literal = None, r: Literal = None):
-    if l is None:
-        l = Literal(0)
-    if r is None:
-        r = z.length().pred()
-    sort_generator = quick_sort_stepwise(z, l, r)
-    while True:
-        try:
-            next(sort_generator)
-        except StopIteration:
-            break
-
-
-def sort_file(filename, sort_func):
-    z = MemoryArray.create_array_from_file(filename)
-    sort_func(z)
-    return z
-
-
-def analyze_complexity(sort_func, sizes, presorted=False):
-    """
-    Analysiert die Komplexität einer Sortierfunktion.
-
-    :param sort_func: Die Funktion, die analysiert wird.
-    :param sizes: Eine Liste von Eingabegrößen für die Analyse.
-    """
-    for size in sizes:
-        MemoryManager.purge()  # Speicher zurücksetzen
-        if presorted:
-            random_array = MemoryArray.create_sorted_array(size)
-        else:
-            random_array = MemoryArray.create_random_array(size, -100, 100)
-        sort_func(random_array)
-        MemoryManager.save_stats(size)
-
-    MemoryManager.plot_stats(["cells", "compares", "writes"])
-
-
-def swap(z: MemoryArray, i: int, j: int):
-    tmp = z[Literal(i)].value
-    z[Literal(i)] = z[Literal(j)]
-    z[Literal(j)].set(tmp)
-
-
-if __name__ == '__main__':
-    sizes = range(10, 101, 5)
-    analyze_complexity(quick_sort, sizes)
-    analyze_complexity(quick_sort, sizes, True)

praktika/04_bin_baum/bin_tree_node.py

@@ -1,15 +0,0 @@
-from utils.memory_cell import MemoryCell
-
-class BinaryTreeNode(MemoryCell):
-
-    def __init__(self, value):
-        super().__init__(value)
-        self.left = None
-        self.right = None
-
-    def __repr__(self):
-        return f"BinaryTreeNode(value={self.value}, left={self.left}, right={self.right})"
-
-    def __str__(self):
-        return str(self.value)
-

praktika/05_avl_baum/gv_avl_tree.py

@@ -1,12 +0,0 @@
-from utils.memory_array import MemoryArray
-from vorlesung.L05_binaere_baeume.avl_tree import AVLTree
-
-if __name__ == "__main__":
-    a = MemoryArray.create_array_from_file("data/seq0.txt")
-    tree = AVLTree()
-
-    for cell in a:
-        tree.insert(int(cell))
-
-    tree.graph_traversal()
-

praktika/05_avl_baum/gv_binary_tree.py

@@ -1,12 +0,0 @@
-from utils.memory_array import MemoryArray
-from vorlesung.L05_binaere_baeume.bin_tree import BinaryTree
-
-if __name__ == "__main__":
-    a = MemoryArray.create_array_from_file("data/seq0.txt")
-    tree = BinaryTree()
-
-    for cell in a:
-        tree.insert(int(cell))
-
-    tree.graph_traversal()
-

praktika/07_hashtable/praktikum.py

@@ -1,106 +0,0 @@
-import math
-import unittest
-from utils.literal import Literal
-from utils.memory_cell import MemoryCell
-from utils.memory_array import MemoryArray
-from vorlesung.L07_hashtable.hashtable import HashTableOpenAddressing
-
-#Goldener Schnitt
-a = Literal((math.sqrt(5) - 1) / 2)
-
-# Hashfunktion nach multiplikativer Methode
-def h(x: MemoryCell, m: Literal) -> Literal:
-    with MemoryCell(int(x * a)) as integer_part, MemoryCell(x * a) as full_product:
-        with MemoryCell(full_product - integer_part) as fractional_part:
-            return Literal(abs(int(fractional_part * m)))
-
-# Quadratische Sondierung
-def f(x: MemoryCell, i: Literal, m: Literal) -> Literal:
-    c1 = 1
-    c2 = 5
-    with MemoryCell(h(x, m)) as initial_hash, MemoryCell(c2 * int(i) * int(i)) as quadratic_offset:
-        with MemoryCell(initial_hash + quadratic_offset) as probe_position:
-            probe_position += Literal(c1 * int(i)) # Linear component
-            return probe_position % m
-
-# Symmetrische quadratische Sondierung
-def fs(x: MemoryCell, i: Literal, m: Literal) -> Literal:
-    with MemoryCell(h(x, m)) as base_hash, MemoryCell(int(i) * int(i)) as square:
-        if int(i) % 2 == 0:  # gerades i: Vorwärtssondierung
-            with MemoryCell(base_hash + square) as position:
-                return position % m
-        else:  # ungerades i: Rückwärtssondierung
-            with MemoryCell(base_hash - square) as position:
-                return position % m
-
-
-
-
-if __name__ == "__main__":
-
-    print("*** Aufgabe 3 ***")
-    size =  Literal(20)
-    print(f"Anlage einer Hash-Tabelle mit offener Adressierung mit Größe {size}")
-    ht = HashTableOpenAddressing(size, f)
-    print("Einfügen der Werte aus seq0.txt")
-    for cell in MemoryArray.create_array_from_file("data/seq0.txt"):
-        if not ht.insert(cell):
-            print(f"Einfügen von {cell} nicht möglich")
-    print(ht)
-    print(f"Belegungsfaktor: {ht.alpha()}")
-
-    with MemoryCell(52) as cell:
-        print(f"Suche nach {cell}")
-        if ht.search(cell):
-            print(f"{cell} gefunden, wird gelöscht.")
-            ht.delete(cell)
-        else:
-            print(f"{cell} nicht gefunden")
-    print(ht)
-    print(f"Belegungsfaktor: {ht.alpha()}")
-    print("Einfügen von 24")
-    with MemoryCell(24) as cell:
-        if not ht.insert(cell):
-            print(f"Einfügen von {cell} nicht möglich")
-    print(ht)
-    print(f"Belegungsfaktor: {ht.alpha()}")
-    print()
-
-    print("*** Aufgabe 4 ***")
-    size =  Literal(90)
-    print(f"Anlage einer Hash-Tabelle mit offener Adressierung mit Größe {size}")
-    ht = HashTableOpenAddressing(size, f)
-    print("Einfügen der Werte aus seq1.txt")
-    for cell in MemoryArray.create_array_from_file("data/seq1.txt"):
-        if not ht.insert(cell):
-            print(f"Einfügen von {cell} nicht möglich")
-    print(ht)
-    print(f"Belegungsfaktor: {ht.alpha()}")
-    print()
-
-    print("*** Aufgabe 5 ***")
-    size =  Literal(89)
-    print(f"Anlage einer Hash-Tabelle mit offener Adressierung mit Größe {size}")
-    ht = HashTableOpenAddressing(size, f)
-    print("Einfügen der Werte aus seq1.txt")
-    for cell in MemoryArray.create_array_from_file("data/seq1.txt"):
-        if not ht.insert(cell):
-            print(f"Einfügen von {cell} nicht möglich")
-    print(ht)
-    print(f"Belegungsfaktor: {ht.alpha()}")
-    print()
-
-    print("*** Aufgabe 6 ***")
-    size =  Literal(90)
-    print(f"Anlage einer Hash-Tabelle mit offener Adressierung mit Größe {size}")
-    print("Verwendung der symmetrischen quadratischen Sondierung")
-    ht = HashTableOpenAddressing(size, fs)
-    print("Einfügen der Werte aus seq1.txt")
-    for cell in MemoryArray.create_array_from_file("data/seq1.txt"):
-        if not ht.insert(cell):
-            print(f"Einfügen von {cell} nicht möglich")
-    print(ht)
-    print(f"Belegungsfaktor: {ht.alpha()}")
-    print()
-
-

praktika/08_graph/schatz.py

@@ -1,37 +0,0 @@
-import re
-from utils.project_dir import get_path
-from vorlesung.L08_graphen.graph import Graph, AdjacencyListGraph, AdjacencyMatrixGraph
-
-
-def read_cave_into_graph(graph: Graph, filename: str):
-    """Read a cave description from a file and insert it into the given graph."""
-    filename = get_path(filename)
-    with open(filename, "r") as file:
-        lines = file.readlines()
-        for line in lines:
-            # match a line with two node names and an optional direction
-            m = re.match(r"(^\s*\"(.*)\"\s*([<>]*)\s*\"(.*)\"\s*)", line)
-            if m:
-                startnode = m.group(2)
-                endnode = m.group(4)
-                opcode = m.group(3)
-                graph.insert_vertex(startnode)
-                graph.insert_vertex(endnode)
-                if '>' in opcode:
-                    graph.connect(startnode, endnode)
-                if '<' in opcode:
-                    graph.connect(endnode, startnode)
-
-
-graph = AdjacencyListGraph()
-# graph = AdjacencyMatrixGraph()
-read_cave_into_graph(graph, "data/hoehle.txt")
-_, predecessor_map = graph.bfs('Höhleneingang')
-path = graph.path('Schatzkammer', predecessor_map)
-print(path)
-_, predecessor_map = graph.bfs('Schatzkammer')
-path = graph.path('Höhleneingang', predecessor_map)
-print(path)
-graph.graph("Höhle")
-
-

praktika/09_aoc/rendeer.py

@@ -1,59 +0,0 @@
-from utils.project_dir import get_path
-from vorlesung.L08_graphen.graph import AdjacencyListGraph
-
-DIRECTIONS = [(1,0), (0, 1), (-1, 0), (0, -1)]
-
-class D16Solution:
-
-    def __init__(self):
-        with open(get_path("data/aoc2416.txt"), "r") as file:
-            self.puzzle = [line.strip() for line in file]
-        self.cells = set()
-        self.start = None
-        self.end = None
-
-    def get_cells_start_end(self):
-        for row in range(len(self.puzzle)):
-            for col in range(len(self.puzzle[row])):
-                if self.puzzle[row][col] != '#':
-                    self.cells.add((col, row))
-                if self.puzzle[row][col] == 'S':
-                    self.start = (col, row)
-                if self.puzzle[row][col] == 'E':
-                    self.end = (col, row)
-
-    def get_label(self, cell, direction):
-        """Generate a label for a cell based on its coordinates and direction."""
-        return f"{cell[0]},{cell[1]}_{direction}"
-
-    def create_graph(self):
-        graph = AdjacencyListGraph()
-        for cell in self.cells:
-            for direction in DIRECTIONS:
-                label = self.get_label(cell, direction)
-                graph.insert_vertex(label)
-        for cell in self.cells:
-            for d, direction in enumerate(DIRECTIONS):
-                label = self.get_label(cell, direction)
-                dx, dy = direction
-                neighbor = (cell[0] + dx, cell[1] + dy)
-                if neighbor in self.cells:
-                    graph.connect(label, self.get_label(neighbor, direction))
-                direction_left = DIRECTIONS[(d - 1) % 4]
-                direction_right = DIRECTIONS[(d + 1) % 4]
-                graph.connect(label, self.get_label(cell, direction_left), 1000)
-                graph.connect(label, self.get_label(cell, direction_right), 1000)
-        return graph
-
-if __name__ == "__main__":
-    solution = D16Solution()
-    solution.get_cells_start_end()
-    graph = solution.create_graph()
-    start = solution.get_label(solution.start, DIRECTIONS[0])
-    print(f"Start: {start}")
-    distance_map, predecessor_map = graph.dijkstra(start)
-    end_labels = [solution.get_label(solution.end, direction) for direction in DIRECTIONS]
-    end_vertices = [graph.get_vertex(label) for label in end_labels]
-    min_weight = min([distance_map[vertex] for vertex in end_vertices])
-    print(f"Minimum distance to End {solution.end}: {min_weight}")
-

praktika/10_electro/electro.py

@@ -1,32 +0,0 @@
-from vorlesung.L08_graphen.graph import Graph, AdjacencyMatrixGraph
-from utils.project_dir import get_path
-import re
-
-def read_elektro_into_graph(graph: Graph, filename: str):
-    pattern = re.compile(r'"([^"]+)";"([^"]+)";(\d+)')
-    with (open(filename, "r") as file):
-        for line in file:
-            m = pattern.match(line)
-            if m:
-                start_name = m.group(1)
-                end_name = m.group(2)
-                cost = int(m.group(3))
-                graph.insert_vertex(start_name)
-                graph.insert_vertex(end_name)
-                graph.connect(start_name, end_name, cost)
-                graph.connect(end_name, start_name, cost)
-
-if __name__ == "__main__":
-    graph = AdjacencyMatrixGraph()
-    read_elektro_into_graph(graph, get_path("data/elektro.txt"))
-
-    parents, cost = graph.mst_prim()
-    print(f"Kosten nach Prim: {cost}")
-    for node, parent in parents.items():
-        if parent is not None:
-            print(f"{node} - {parent}")
-
-    edges, cost = graph.mst_kruskal()
-    print(f"Kosten nach Kruskal: {cost}")
-    for start_name, end_name, _ in edges:
-        print(f"{start_name} - {end_name}")

requirements.txt

@@ -1,4 +1,3 @@
 matplotlib
 numpy
 pygame
-graphviz

schoeffelbe/pr03.py

@@ -107,7 +107,7 @@ def partitionIterative(arr : MemoryArray, l : Literal, h : Literal, mode=0):
 
     # Carefull that we do not use a reference. I suppose python would return one here if we just assign without value>Literal cast.
     # At least this helped fix weird issue
-    pivotValue : Literal = arr[h]
+    pivotValue : Literal = Literal(arr[h].value)
     i : MemoryCell = MemoryCell(l.pred())
   
     for j in mrange(l, h):
@@ -115,7 +115,7 @@ def partitionIterative(arr : MemoryArray, l : Literal, h : Literal, mode=0):
             i += Literal(1)                 # increment index of smaller element
             swap(arr, int(i), int(j))
   
-    swap(arr, i.succ().value, h.value)
+    swap(arr, int(i.succ()), int(h))
     return i.succ()
 
 def LEGACY_quickSort(z: MemoryArray, l: Literal = Literal(0), r: Literal = Literal(-1), mode=0):
@@ -185,6 +185,6 @@ if __name__ == '__main__':
         print(filename)
         toSort = MemoryArray.create_array_from_file(filename)
         timeMS(quickSortIterative, toSort, Literal(0), toSort.length().pred(), mode=1)
-        print(toSort)
+        # print(toSort)
 
     print("Kann durch die Modifikation eine besser Laufzeit als nlog(n) erreicht werden? Nein! nlog(n) ist das Minimum. Durch die Änderung kann aber der Worst-Case fall von n^2 für z.B. bereits vorsortierte Arrays oder Arrays mit vielen Duplikaten vermieden werden.")

schoeffelbe/pr04.py

@@ -1,293 +0,0 @@
-import logging
-logger = logging.getLogger(__name__)
-# logging.basicConfig(level=logging.DEBUG)
-
-import time
-
-def timeMS(func, *args, **kwargs):
-    startTime = time.perf_counter()
-    result = func(*args, **kwargs)
-    endTime = time.perf_counter()
-    elapsedMS = (endTime - startTime) * 1000  # Convert to milliseconds
-    print(f"{func.__name__} took {elapsedMS:.2f} ms")
-    return result
-
-
-from utils.memory_array import MemoryArray
-from utils.memory_cell import MemoryCell
-from utils.literal import Literal
-from utils.constants import MAX_VALUE
-from utils.memory_manager import MemoryManager
-from utils.memory_range import mrange
-
-# Impl of MemoryArray says we cant add our own Datatypes beside Literal and List
-# BUUUUT we can just wrap our Datatype in a List :-)
-# We store them in a MemoryArray internaly tho anyhow so we increment our Counters for the RAM
-class HeapEntry:
-    def __init__(self, item, priority=1):
-        self.data = MemoryArray(Literal(2))
-        # 0: Content, 1: Prio
-        self.data[Literal(0)] = Literal(item)
-        self.data[Literal(1)] = Literal(priority)
-    
-    def getItem(self):
-        return self.data[Literal(0)]
-    
-    def getPriority(self):
-        return self.data[Literal(1)]
-    
-    def setPriority(self, priority):
-        self.data[Literal(1)] = Literal(priority)
-    
-    def __lt__(self, other):
-        if other is None:
-            return True 
-        if isinstance(other, (int, float)):
-            return self.getPriority().value > other
-        return self.getPriority() > other.getPriority()
-    
-    def __gt__(self, other):
-        if other is None:
-            return False 
-        if isinstance(other, (int, float)):
-            return self.getPriority().value < other
-        return self.getPriority() < other.getPriority()
-    
-    def __eq__(self, other):
-        return self.getPriority() == other.getPriority()
-    
-    def __str__(self):
-        return f"({self.getItem()}, prio={self.getPriority()})"
-
-class PriorityQueue:
-    def __init__(self, max_size : Literal = Literal(100)):
-        self.heap = MemoryArray(max_size) 
-        # Add uninitialized HeapEntry Values so the Adds/Compares do not fail on emtpy stack. 
-        # Would have to switch to MIN_VALUE if we switch what is a "Higher" Prio
-        for i in mrange(max_size.value):
-            self.heap[i].set([HeapEntry(MAX_VALUE, MAX_VALUE)])
-        self.size = MemoryCell(0)
-    
-    def parent(self, i: Literal) -> Literal:
-        return MemoryCell(i.pred()) // Literal(2)
-    
-    def leftChild(self, i: Literal) -> Literal:
-        return MemoryCell(MemoryCell(2) * i) + Literal(1)
-    
-    def rightChild(self, i: Literal) -> Literal:
-        return MemoryCell(MemoryCell(2) * i) + Literal(2)
-    
-    # Swap the Lists -> Therefore get the value which is the List and then Set it again
-    def swap(self, i: Literal, j: Literal):
-        tmp_i = self.heap[i].value
-        tmp_j = self.heap[j].value
-        self.heap[i].set(tmp_j)
-        self.heap[j].set(tmp_i)
-    
-    def maxHeapify(self, i: Literal):
-        left = self.leftChild(i)
-        right = self.rightChild(i)
-        largest = i
-        
-        if left < Literal(self.size.value) and self.heap[left].value[0] > self.heap[largest].value[0]:
-            largest = left
-        
-        if right < Literal(self.size.value) and self.heap[right].value[0] > self.heap[largest].value[0]:
-            largest = right
-        
-        if largest != i:
-            self.swap(i, largest)
-            self.maxHeapify(largest)
-    
-    def insert(self, entry : HeapEntry):
-        if self.size >= self.heap.length():
-            raise IndexError("Heap full")
-        
-        i = self.size
-        self.heap[i].set([entry])
-        
-        while i > Literal(0) and self.heap[self.parent(i)].value[0] < self.heap[i].value[0]:
-            self.swap(i, self.parent(i))
-            i = self.parent(i)
-
-        self.size += Literal(1)
-    
-    def pop(self):
-        if self.isEmpty():
-            raise IndexError("Queue is empty!")
-        
-        max_item = self.heap[Literal(0)].value[0]
-        
-        self.heap[Literal(0)] = self.heap[self.size - Literal(1)]
-        self.size -= Literal(1)
-        
-        self.maxHeapify(Literal(0))
-        
-        return max_item
-    
-    def peek(self):
-        if self.isEmpty():
-            raise IndexError("Queue is empty")
-        return self.heap[Literal(0)].value[0]
-    
-    def isEmpty(self):
-        return self.size == Literal(0)
-    
-    def __len__(self):
-        return self.size
-
-    def __str__(self):
-        entries = []
-        for i in mrange(self.size.value):
-            entry = self.heap[i].value[0]
-            if entry.getItem() != MAX_VALUE:
-                entries.append(str(entry))
-        return "[" + ", ".join(entries) + "]"
-
-# Insert here so we dont run into import problems, but can deliver this file Standalone
-class BinaryTreeNode(MemoryCell):
-    def __init__(self, value):
-        super().__init__(value)
-        self.left = None
-        self.right = None
-
-    def __repr__(self):
-        return f"BinaryTreeNode(value={self.value}, left={self.left}, right={self.right})"
-
-    def __str__(self):
-        return str(self.value)
-
-class BinaryTree:
-    def __init__(self): 
-        self.root: BinaryTreeNode | None = None
-    
-    def insert(self, value: BinaryTreeNode):
-        # Insert at Leaf, if smaller then left one, otherwise right one
-        def _insert(node: BinaryTreeNode | None, value) -> BinaryTreeNode:
-            if node is None:
-                return BinaryTreeNode(value)
-            if value < node:
-                node.left = _insert(node.left, value)                                 # type: ignore -> Ignoring pywright errors
-            else:
-                node.right = _insert(node.right, value)                               # type: ignore -> Ignoring pywright errors
-            return node
-
-        self.root = _insert(self.root, value)
-    
-    def traverse(self, mode="in", visual=False):
-        mode = mode.lower()
-        # Have internal depth counting
-        def InternalTraverse(node, prefix="", is_left=True, depth=0):
-            if node is None:
-                return [] if not visual else []
-    
-            result = []
-            node_str = str(node)
-
-            prefixAcc = prefix + ("|   " if is_left and depth > 0 else "   ")
-    
-            if visual:
-                connector = "+-- " if is_left else "L-- "
-                line = prefix + connector + node_str if depth > 0 else node_str
-                result.append(line)
-            else:
-                result.append(node_str)
-
-            if mode == "pre":
-                result += InternalTraverse(node.left, prefixAcc, True, depth + 1)
-                result += InternalTraverse(node.right, prefixAcc, False, depth + 1)
-            elif mode == "in":
-                result += InternalTraverse(node.left, prefixAcc, True, depth + 1)
-                result += InternalTraverse(node.right, prefixAcc, False, depth + 1)
-            elif mode == "post":
-                result += InternalTraverse(node.left, prefixAcc, True, depth + 1)
-                result += InternalTraverse(node.right, prefixAcc, False, depth + 1)
-    
-            return result
-    
-        if self.root is None:
-            return "(empty tree)" if visual else []
-    
-        result = InternalTraverse(self.root)
-        return "\n".join(result) if visual else result
-
-    
-    def levelOrderWithPriorityQueue(self):
-        if not self.root:
-            return []
-        
-        # Create a priority queue, using a reduced prio for every new entry -> behaviour as regular queue FIFO
-        pq = PriorityQueue(Literal(1000))
-
-        # Again we cannot create a MemoryArray of dynamic sizes and also cannot create a string as MemoryCell does not like it
-        # Again we just create a list holding a single dummy Entry (to set its size to 1) and then just use this "list" as our string
-        # Appending to it is easy as it is just a regular list and in the end we return it
-        # Like MemoryCell("").value.append("STRING") will fail. But list-wrap works. 
-        #
-        # Sorry for Syntax, dont know any better way to have everything as RAM-Managed memory:-(
-        result = MemoryArray(["MYSTRING"])
-        result[Literal(0)].set([]);
-
-        counter = MemoryCell(0)
-        def nextPriority():
-            val = counter.value
-            counter.set(Literal(val + 1))
-            return val
-        pq.insert(HeapEntry([self.root], nextPriority()))  
-        
-        while not pq.isEmpty():
-            entry = pq.pop()
-            node = entry.getItem().value
-            
-            result[Literal(0)].value.append(str(node[0]))
-            
-            if node[0].left:
-                pq.insert(HeapEntry([node[0].left], nextPriority()))
-            if node[0].right:
-                pq.insert(HeapEntry([node[0].right], nextPriority()))
-        
-        return result[Literal(0)]
-
-
-    def __str__(self):
-        return str(self.traverse(mode="PrE", visual=True))
-
-def analyze_complexity(fn, sizes):
-    """
-    Analysiert die Komplexität einer maximalen Teilfolgenfunktion.
-
-    :param max_sequence_func: Die Funktion, die analysiert wird.
-    :param sizes: Eine Liste von Eingabegrößen für die Analyse.
-    """
-    for size in sizes:
-        MemoryManager.purge()  # Speicher zurücksetzen
-        random_array = MemoryArray.create_random_array(size, -100, 100)
-        fn(random_array, Literal(0), random_array.length().pred())
-        MemoryManager.save_stats(size)
-
-    MemoryManager.plot_stats(["cells", "adds", "compares", "reads", "writes"])
-
-
-if __name__ == '__main__':
-    # For debug, assert if working and complexity-analysis
-    # example()
-
-    print("Sorry for the Syntax and the large file, tried to keep everything as a standalone file to help make it \" download and run \".\n \
-          Also did - once again - not find a better way to have a queue managed by the RAM contain the values of non-integer-attributes I \n\
-          needed it to. Therefore i reused my Priorityqueue and its accesses via the unspecified wrapped list.");
-
-    # for filename in ["data/seq0.txt", "data/seq1.txt", "data/seq2.txt" ,"data/seq3.txt"]:
-    for filename in [ "data/seq0.txt"]:
-        print(filename)
-        binTreeData = MemoryArray.create_array_from_file(filename)
-        binTree = BinaryTree()
-        for value in binTreeData:
-            binTree.insert(BinaryTreeNode(value))
-
-        # Print overlaoded InOrder traversal
-        print(binTree)
-        # print(binTree.traverse(mode="pre", visual=False))
-        # print(binTree.traverse(mode="in", visual=False))
-        # print(binTree.traverse(mode="post", visual=False))
-        # Print Levelorder traversal:
-        print(binTree.levelOrderWithPriorityQueue())

schoeffelbe/pr05.py

@@ -1,246 +0,0 @@
-import logging
-logger = logging.getLogger(__name__)
-# logging.basicConfig(level=logging.DEBUG)
-
-import time
-
-def timeMS(func, *args, **kwargs):
-    startTime = time.perf_counter()
-    result = func(*args, **kwargs)
-    endTime = time.perf_counter()
-    elapsedMS = (endTime - startTime) * 1000  # Convert to milliseconds
-    print(f"{func.__name__} took {elapsedMS:.2f} ms")
-    return result
-
-
-from utils.memory_array import MemoryArray
-from utils.literal import Literal
-from utils.memory_manager import MemoryManager
-from vorlesung.L05_binaere_baeume.bin_tree import BinaryTree
-from vorlesung.L05_binaere_baeume.bin_tree_node import BinaryTreeNode
-
-def analyze_complexity(fn, sizes):
-    """
-    Analysiert die Komplexität einer maximalen Teilfolgenfunktion.
-
-    :param max_sequence_func: Die Funktion, die analysiert wird.
-    :param sizes: Eine Liste von Eingabegrößen für die Analyse.
-    """
-    for size in sizes:
-        MemoryManager.purge()  # Speicher zurücksetzen
-        random_array = MemoryArray.create_random_array(size, -100, 100)
-        fn(random_array, Literal(0), random_array.length().pred())
-        MemoryManager.save_stats(size)
-
-    MemoryManager.plot_stats(["cells", "adds", "compares", "reads", "writes"])
-
-lineAccumulator = []
-
-# Returnvalue does not get forwarded so we can not work with return. 
-# Will try glob vars to append the string
-# Signature: def print_node(node, indent=0, line=None):
-def clbk_graphvizify(toDecorate : BinaryTreeNode, indent=0, line=None):
-    global lineAccumulator
-
-    if isinstance(toDecorate, AVLTreeNode):
-        lineAccumulator.append(f'n_{id(toDecorate)} [label=<{toDecorate.value}<BR/><FONT COLOR="RED" POINT-SIZE="10.0" FACE="ambrosia">B: {toDecorate.balanceFactor}</FONT>>]')
-    else:
-        lineAccumulator.append(f"n_{id(toDecorate)} [label={toDecorate.value}]")
-
-    # Create edges for nodes with Child (use l - r)
-    if toDecorate.left is not None:
-        lineAccumulator.append(f"n_{id(toDecorate)} -> n_{id(toDecorate.left)}")
-    
-    if toDecorate.right is not None:
-        lineAccumulator.append(f"n_{id(toDecorate)} -> n_{id(toDecorate.right)}")
-
-
-def graphvizify() -> str:
-    # Header
-    result = "digraph {\n\t"
-    # Body
-    result += ('\n\t'.join(str(item) for item in lineAccumulator))
-    # Footer
-    result += "\n}"
-    return result
-
-class AVLTreeNode(BinaryTreeNode):
-    def __init__(self, value):
-        super().__init__(value)
-        self.parentRef = None
-        # Start balanced as we probably have no children right after insert
-        self.balanceFactor = Literal(0)
-
-    def rightRotate(self, node) -> 'AVLTreeNode|None':
-        if node is None:
-            return None
-        
-        oLeft = node.left;
-        oLeft.parentRef = node.parentRef;
-        node.left = oLeft.right;
-
-        if node.left is not None:
-            node.left.parentRef = node;
-
-        oLeft.right = node;
-        node.parentRef = oLeft;
-
-        if oLeft.parentRef is not None:
-            if oLeft.parentRef.right is node:
-                oLeft.parentRef.right = oLeft;
-            elif oLeft.parentRef.left is node:
-                oLeft.parentRef.left = oLeft;
-    
-        node.getSetBalanceFactor()
-        oLeft.getSetBalanceFactor()
-
-        return oLeft
-
-    def leftRotate(self, node) -> 'AVLTreeNode|None':
-        if node is None:
-            return None
-        
-        oRight = node.right
-        oRight.parentRef = node.parentRef
-        node.right = oRight.left
-
-        if node.right is not None:
-            node.right.parentRef = node
-
-        oRight.left = node
-        node.parentRef = oRight
-
-        if oRight.parentRef is not None:
-            if oRight.parentRef.right is node:
-                oRight.parentRef.right = oRight
-            elif oRight.parentRef.left is node:
-                oRight.parentRef.left = oRight
-
-        node.getSetBalanceFactor()
-        oRight.getSetBalanceFactor()
-
-        return oRight
-
-    def getSetBalanceFactor(self) -> Literal:
-        leftHeight = self.left.height() if self.left else 0
-        rightHeight = self.right.height() if self.right else 0
-        self.balanceFactor = Literal(rightHeight - leftHeight)
-        return self.balanceFactor
-
-    def rightLeftRotate(self, node) -> 'AVLTreeNode|None':
-        node.right = self.rightRotate(node.right)
-        return self.leftRotate(node)
-
-    def leftRightRotate(self, node) -> 'AVLTreeNode|None':
-        node.left = self.leftRotate(node.left)
-        return self.rightRotate(node)
-
-
-def debugTraverse(node, source=1):
-    if node is None:
-        return None
-    logger.debug(f"{node.value} {node.getSetBalanceFactor()} {source}")
-    debugTraverse(node.left, 10);
-    debugTraverse(node.right, 20);
-
-
-class AVLTree(BinaryTree):
-    # @override
-    def new_node(self, value) -> AVLTreeNode:
-        return AVLTreeNode(value)
-
-    def balanceAVLTree(self, node : AVLTreeNode):
-        # balance < -1 means imbalance to the left, > 1 means imbalance to the right
-        logger.debug("in")
-        if node is None:
-            return None
-        logger.debug("out")
-        
-        node.getSetBalanceFactor()
-        logger.debug(f"Parent Balancing for {node.value} -> {node.balanceFactor} {node.left.height() if node.left else None} and {node.right.height() if node.right else None}")
-        
-        # imbalance to left -> If we enter this we cannot LOGICALLY have a left=None node -> No need to chekc
-        if node.balanceFactor < Literal(-1):
-            # Left-Left
-            if node.left.balanceFactor <= Literal(0):   # type: ignore -> Ignoring pywright error, see comment above
-                # Wow, this syntax is sketchy ^^
-                # TODO Maybe declare as static if python supports this? Or just leaf param be?
-                logger.debug("rr")
-                node = node.rightRotate(node)
-            # Left-Right
-            else:
-                # TODO Maybe declare as static if python supports this? Or just leaf param be?
-                logger.debug("lrr")
-                node = node.leftRightRotate(node)
-        
-        # Right heavy
-        # imbalance to right -> If we enter this we cannot LOGICALLY have a right=None node -> No need to chekc
-        if node.balanceFactor > Literal(1):
-            # Right-Right case
-            if node.right.balanceFactor >= Literal(0):   # type: ignore -> Ignoring pywright error, see comment above
-                # TODO Maybe declare as static if python supports this? Or just leaf param be?
-                logger.debug("lr")
-                node = node.leftRotate(node)
-            # Right-Left case
-            else:
-                # TODO Maybe declare as static if python supports this? Or just leaf param be?
-                logger.debug("rlr")
-                node = node.rightLeftRotate(node)
-        
-        logger.debug(f"Reached {node.parentRef}")
-        if node.parentRef is not None:
-            logger.debug(f"Calling again for {node.parentRef.value}");
-            self.balanceAVLTree(node.parentRef);
-        else:
-            self.root = node;
-
-        # Node is balanced
-        return node
-
-    # @override
-    def insert(self, value):
-        node, parent = super().insert(value)
-        # NOTE Python does not have a Problem with NOT tellin us that we override something important
-        # or something that does not exist.... This Makes for AWESOME debugging .... ... ...
-        node.parentRef = parent
-
-        if parent:
-            node = self.balanceAVLTree(node.parentRef)
-
-        return node, parent
-
-if __name__ == '__main__':
-    tree = AVLTree()
-
-    ### Force RR
-    # testData = [30, 20, 10];
-    # for value in testData:
-    #     tree.insert(MemoryCell(value));
-
-    ### Force LR
-    # testData = [10, 20, 30];
-    # for value in testData:
-    #     tree.insert(MemoryCell(value));
-
-    ### Force LRR
-    # testData = [30, 10, 20]
-    # for value in testData:
-    #     tree.insert(MemoryCell(value))
-
-    ### Force RLR
-    # testData = [10, 30, 20]
-    # for value in testData:
-    #     tree.insert(MemoryCell(value))
-
-    # Force rebuild of our balanceFactor indices... 
-    # debugTraverse(tree.root)
-
-    binTreeData = MemoryArray.create_array_from_file("data/seq0.txt")
-    for value in binTreeData:
-        tree.insert(value)
-
-
-    lineAccumulator.clear();
-    tree.in_order_traversal(clbk_graphvizify)
-    # tree.tree_structure_traversal(clbk_graphvizify)
-    print(graphvizify())

schoeffelbe/pr06.py

@@ -1,334 +0,0 @@
-import logging
-from graphviz import Digraph
-
-logger = logging.getLogger(__name__)
-# logging.basicConfig(level=logging.DEBUG)
-
-import time
-
-def timeMS(func, *args, **kwargs):
-    startTime = time.perf_counter()
-    result = func(*args, **kwargs)
-    endTime = time.perf_counter()
-    elapsedMS = (endTime - startTime) * 1000  # Convert to milliseconds
-    print(f"{func.__name__} took {elapsedMS:.2f} ms")
-    return result
-
-
-from utils.memory_array import MemoryArray
-from utils.memory_cell import MemoryCell
-from utils.literal import Literal
-from utils.memory_range import mrange
-from utils.memory_manager import MemoryManager
-
-# We often want to "dynamically" extend our array, but thats not really what it was intended for 
-# Therefore we write a function to do so reusably
-def memArrayInsert(array: MemoryArray, position: Literal, value) -> MemoryArray:
-    logger.debug(f"Pre-Insert: {array}")
-    newSize : Literal = array.length().succ()
-    newArray = MemoryArray(newSize)
-    
-    # Copy elements til position
-    for i in mrange(position):
-        newArray[i] = array[i]
-    
-    # Insert new value with check for MemCell Type
-    newArray[position] = value if isinstance(value, MemoryCell) else MemoryCell(value)
-    
-    for i in mrange(position.succ(), newSize):
-        newArray[i] = array[i.pred()]
-    
-    logger.debug(f"Post-Insert: {array}")
-    return newArray
-
-# Likewise for the Split
-# Here we split the array at the position EXCLUSIVELY for the first MemoryArray
-def memArraySplit(array: MemoryArray, position: Literal) -> tuple[MemoryArray, MemoryArray]:
-    leftSize = position
-    rightSize = MemoryCell(array.length()) - position
-    
-    left = MemoryArray(leftSize)
-    right = MemoryArray(rightSize)
-    
-    for i in mrange(leftSize):
-        left[i] = array[i]
-    
-    for i in mrange(rightSize):
-        right[i] = array[Literal(i.value + position.value)]
-    
-    return left, right
-
-class BTreeNode(MemoryCell):
-    def __init__(self):
-        super().__init__(value=None)
-        self.value = MemoryArray([])
-        self.children = MemoryArray([])
-        self.leaf = True
-
-    def __str__(self):
-        return "( " + " ".join(str(val) for val in self.value) + " )"
-
-    def isLeaf(self):
-        return self.children.length() == Literal(0)
-
-class BTree:
-    def __init__(self, order):
-        self.order = Literal(order)
-        self.root = BTreeNode()
-
-    def _insertNonFull(self, node, key):
-        if node.leaf:
-            i = node.value.length()
-            
-            # pos for new Key
-            while i > Literal(0) and key < node.value[i.pred()]:
-                i = i.pred()
-                
-            # insert key at pos using helper fkt
-            node.value = memArrayInsert(node.value, i, key)
-        else:
-            j = Literal(0)
-            while j < node.value.length() and node.value[j] < key:
-                j = j.succ()
-                
-            child = node.children[j].value[0]
-            
-            # Splt if full
-            if child.value.length() == Literal(2 * self.order.value - 1):
-                self._splitChild(node, j)
-                if key > node.value[j]:
-                    j = j.succ()
-                    child = node.children[j].value[0]
-            
-            # insert rec in selected Child
-            self._insertNonFull(child, key)
-
-    def insert(self, key):
-        if not isinstance(key, MemoryCell):
-            key = MemoryCell(key)
-        rootRef = self.root
-        if rootRef.value.length() == MemoryCell(2 * self.order.value - 1):
-            newRoot = BTreeNode()
-            newRoot.leaf = False
-            newRoot.children = MemoryArray(["DUMMY"])
-            newRoot.children[Literal(0)].set([rootRef])
-            self._splitChild(newRoot, Literal(0))
-            self.root = newRoot
-            self._insertNonFull(newRoot, key)
-        else:
-            logger.debug("Inserting in non-full");
-            self._insertNonFull(rootRef, key)
-
-    def _splitChild(self, parent: BTreeNode, index: Literal):
-        child = parent.children[index].value[0]
-        
-        newRight = BTreeNode()
-        newRight.leaf = child.leaf
-        
-        # median index
-        mid = Literal(self.order.value - 1)
-        medianKey = child.value[mid]
-        
-        # Childs keys in l and r
-        leftKeys, rightKeys = memArraySplit(child.value, mid)
-        
-        child.value = leftKeys
-        
-        newRight.value = MemoryArray(rightKeys.length().pred())
-        for j in mrange(rightKeys.length().pred()):
-            newRight.value[j] = rightKeys[j.succ()]
-        
-        # if child is not leaf distribute itschildren
-        if not child.leaf:
-            leftChildren, rightChildren = memArraySplit(child.children, mid.succ())
-            child.children = leftChildren
-            newRight.children = rightChildren
-
-        # Insert median key in parent and insert new right as i+1's chld
-        parent.value = memArrayInsert(parent.value, index, medianKey)
-        parent.children = memArrayInsert(parent.children, index.succ(), [newRight])
-
-    def search(self, key) -> BTreeNode:
-        return BTreeNode()
-
-    # Depth-Search
-    def _traversalInOrder(self, node : BTreeNode, result):
-        logger.debug(type(node.value))
-        logger.debug(node.value)
-        for i in mrange(node.value.length()):
-            # RecTerm
-            if not node.isLeaf():
-                self._traversalInOrder(node.children[i].value[0], result)
-            result.append(str(node.value[i]))
-        # RecTerm
-        if not node.isLeaf(): 
-            self._traversalInOrder(node.children[Literal(len(node.value))].value[0], result)
-
-    def structureTraversal(self, callback):
-        def traverse(node):
-            if node is None:
-                return
-            callback(node)
-            if not node.isLeaf():
-                for i in range(len(node.children)):
-                    child = node.children[Literal(i)].value[0]
-                    traverse(child)
-        traverse(self.root)
-
-    def traversal(self) -> list:
-        resultAcc = []
-        self._traversalInOrder(self.root, resultAcc)
-        return resultAcc
-
-    def search(self, searchVal : Literal) -> BTreeNode|None:
-        if self.root is None:
-            return None
-                
-        current = self.root
-        while not current.isLeaf():
-            # Exit early if we are already way to large for our current Node. Should improve runtime
-            if searchVal > current.value[current.value.length().pred()]:
-                current = current.children[current.value.length()].value[0]
-                continue
-
-            # Go thru every value in the Node until we find anything
-            i = MemoryCell(0)
-            while i < current.value.length() and searchVal > current.value[i]:
-                i = i.succ()
-                
-            # return exact match
-            if i < current.value.length() and searchVal == current.value[i]:
-                return current
-                
-            # go to appropriate child
-            # If searchVal smaller than first value (i=0) -> leftmost child
-            # if searchVal larger than all values (i=len) -> rightmost child
-            # Otherwise -> child between values
-            current = current.children[Literal(i)].value[0]
-        
-        # Final check in leaf node
-        for i in mrange(current.value.length()):
-            if searchVal == current.value[i]:
-                return current
-            
-        return None
-
-    def height(self) -> Literal:
-        if self.root is None:
-            return Literal(0)
-            
-        current = self.root
-        height = MemoryCell(1)
-        
-        while not current.isLeaf():
-            height = height.succ()
-            current = current.children[Literal(0)].value[0]
-            
-        return height
-
-def clbk_graphvizify(toDecorate: BTreeNode, indent=0, line=None):
-    global dotAcc
-    
-    values_str = "|".join(str(val) for val in toDecorate.value)
-    dotAcc.node(f'n_{id(toDecorate)}', values_str, shape='record')
-        
-    # Create edges for all children
-    if not toDecorate.isLeaf():
-        for i in mrange(toDecorate.children.length()):
-            child = toDecorate.children[i].value[0]
-            dotAcc.edge(f'n_{id(toDecorate)}', f'n_{id(child)}')
-
-def visualizeBTree(tree: BTree, filename='build/schoeffel_btree'):
-    try:
-        import graphviz
-    except ImportError:
-        raise AssertionError("Graphviz installed? Try commenting visualizeBTree or install 'pip install graphviz'")
-    global dotAcc
-    dotAcc = Digraph()
-    dotAcc.attr(rankdir='TB')
-    dotAcc.attr('node', shape='record', style='filled', fillcolor='lightgray')
-    dotAcc.attr('edge', arrowsize='0.5')
-    
-    tree.structureTraversal(clbk_graphvizify)
-    try:
-        dotAcc.render(filename, view=True)
-    except Exception as e:
-        print(f"Could not display graph: {e}")
-        print("Saving graph file without viewing (Running WSL?)")
-        try:
-            dotAcc.render(filename, view=False)
-        except Exception as e:
-            print(f"Could not save graph file: {e}")
-
-def graphvizify() -> str:
-    result = """digraph {
-    rankdir=TB;
-    node [shape=record, style=filled, fillcolor=lightgray];
-    edge [arrowsize=0.5];
-    """
-    # Body
-    result += '\n\t'.join(str(item) for item in dotAcc)
-    # Footer
-    result += "\n}"
-    return result
-
-def analyze_complexity(fn, sizes):
-    """
-    Analysiert die Komplexität einer maximalen Teilfolgenfunktion.
-
-    :param max_sequence_func: Die Funktion, die analysiert wird.
-    :param sizes: Eine Liste von Eingabegrößen für die Analyse.
-    """
-    for size in sizes:
-        MemoryManager.purge()  # Speicher zurücksetzen
-        random_array = MemoryArray.create_random_array(size, -100, 100)
-        for value in random_array:
-            fn(value)
-        MemoryManager.save_stats(size)
-
-    MemoryManager.plot_stats(["cells", "compares", "reads", "writes"])
-
-if __name__ == '__main__':
-    tree = BTree(order=3)
-    tree.insert(Literal(10));
-    tree.insert(Literal(11));
-    tree.insert(Literal(12));
-    print(tree.traversal());
-
-    binTreeData = MemoryArray.create_array_from_file("data/seq0.txt")
-    j = 0
-    for value in binTreeData:
-        tree.insert(value)
-        j = j +1
-        # Uncomment to view progress in insertion at every step saved as PDF
-        # visualizeBTree(tree, f"build/schoeffel_btree{j}")
-
-    logger.debug(tree.root.children)
-    # Graphvizify Wrapper
-    visualizeBTree(tree)
-    print(f"InOrder Traversal: {tree.traversal()}")
-    print(tree.search(Literal(50)))
-    print(tree.height())
-
-    tree3 = BTree(order=3)
-    tree5 = BTree(order=5)
-    binTreeData = MemoryArray.create_array_from_file("data/seq2.txt")
-    for value in binTreeData:
-        tree3.insert(value)
-        tree5.insert(value)
-
-    print(f"Order three for Seq2 produces height {tree3.height()}")
-    print(f"Order five for Seq2 produces height {tree5.height()}")
-    order3 = tree3.traversal()
-    order5 = tree5.traversal()
-    assert all(int(order3[i]) <= int(order3[i+1]) for i in range(len(order3)-1)), "Order3 not in ascending order"
-    assert all(int(order5[i]) <= int(order5[i+1]) for i in range(len(order5)-1)), "Order5 not in ascending order"
-    print(tree3.search(Literal(0)))
-    print(tree5.search(Literal(0)))
-
-
-    MemoryManager.purge()
-    analyze_complexity(tree3.insert, [10, 20, 30, 40, 50, 60, 70, 80, 90, 100])
-    # tree.tree_structure_traversal(clbk_graphvizify)
-    # print(graphvizify())
-

schoeffelbe/pr07.py

@@ -1,266 +0,0 @@
-import logging
-
-logger = logging.getLogger(__name__)
-# logging.basicConfig(level=logging.DEBUG)
-
-import time
-
-def timeMS(func, *args, **kwargs):
-    startTime = time.perf_counter()
-    result = func(*args, **kwargs)
-    endTime = time.perf_counter()
-    elapsedMS = (endTime - startTime) * 1000  # Convert to milliseconds
-    print(f"{func.__name__} took {elapsedMS:.2f} ms")
-    return result
-
-from utils.memory_array import MemoryArray
-from utils.memory_cell import MemoryCell
-from utils.literal import Literal
-from utils.memory_range import mrange
-from utils.memory_manager import MemoryManager
-
-def getHashFunction(m : Literal):
-    # Hash function using golden ratio
-    # Golden ratio (sqrt(5) - 1) / 2; Allowed to to this way as it is a one-time calc ^^
-    A : Literal = Literal((5 ** 0.5 - 1) / 2)
-    def hashFunctionGoldenRatio(key : Literal|MemoryCell) -> Literal:
-        if not isinstance(key, MemoryCell):
-            key = MemoryCell(key)
-            
-        assert(isinstance(key, MemoryCell))
-
-        product : Literal = key * A
-        
-        # discard decimal part
-        intPart = Literal(int(product.value))
-        fracPart = MemoryCell(product) - intPart
-        
-        # Scale by m
-        hashVal = Literal(int(fracPart.value * m.value))
-        
-        return hashVal
-    
-    return hashFunctionGoldenRatio
-    
-# Probing function h + i + 5i^2
-def getProbingFunction(hashFunc, m: Literal, probingMethod="quadratic"):
-    def quadraticProbe(key, i: Literal|MemoryCell):
-        if not isinstance(i, MemoryCell):
-            i = MemoryCell(i)
-            
-        # TODO Can save operation/allocation of MemCEll here, but for better flow leave this way
-        hPrime_x = MemoryCell(hashFunc(key))
-        iSquared = MemoryCell(i * i)
-        
-        result = MemoryCell(MemoryCell(hPrime_x + i) + iSquared * Literal(5)) % m
-        return result
-    
-
-    def symmetricProbe(key, i: Literal|MemoryCell):
-        if not isinstance(i, MemoryCell):
-            i = MemoryCell(i)
-
-        hPrime_x = MemoryCell(hashFunc(key))
-        iSquared = MemoryCell(i * i)
-
-        if i % Literal(2) == Literal(0):
-            result = MemoryCell(hPrime_x + iSquared) % m
-        else:
-            result = MemoryCell(hPrime_x - iSquared) % m
-        return result
-
-    if probingMethod == "symmetric":
-        return symmetricProbe
-    else:
-        return quadraticProbe
-
-class HashTable:
-    # marker for deleted entries
-    DELETED = MemoryCell("DELETED")
-    
-    def __init__(self, size, probingMethod="quadratic"):
-        if not isinstance (size, Literal|MemoryCell):
-            size = Literal(size)
-        self.size = size
-
-        self.table = MemoryArray(self.size)
-        for i in mrange(self.size):
-            self.table[i].set(None)
-
-        self.count = Literal(0)                   # Count of actual elements
-        self.deletedCount = Literal(0)            # Count of deleted slots
-        
-        # Initialize hash and probe function
-        self.hashFunc = getHashFunction(self.size)
-        self.probe = getProbingFunction(self.hashFunc, self.size, probingMethod)
-    
-    def insert(self, value):
-        if not isinstance(value, MemoryCell):
-            value = MemoryCell(value)
-            
-        # Check if table is full (considering deleted entries asd well as normal count)
-        if (MemoryCell(self.count) + self.deletedCount) == self.size:
-            logger.info(f"Failed to insert {value} - table is full")
-            return False
-            
-        i = Literal(0)
-        while i < self.size:
-            # Get our Index via the ProbingFkt
-            index = self.probe(value, i)
-    
-            # Empty slot or deleted marker found
-            # Need the get here as we want to compare the value (none) to None.
-            # For the rest normal should be fine
-            if self.table[index].get() is None or self.table[index] == self.DELETED:
-                if self.table[index] == self.DELETED:
-                    # Were on a cell that was deleted. Now we write in it, but decrease delCount
-                    self.deletedCount = self.deletedCount.pred()
-                    
-                self.table[index] = value
-                self.count = self.count.succ()      # Inc fillcounter
-                logger.debug(f"value {value} was inserted successfully at {index}, count is now at \
-                        {self.count}|{self.deletedCount}");
-                return True
-                
-            # Value already exists
-            # TODO DISCUSSION Wouldnt it defcato be a successfull insert if we are already in our hashmap? Maybe then return true here?
-            if self.table[index] == value:
-                logger.info(f"value {value} already exits in the table");
-                return False
-                
-            i = i.succ()
-            
-        # Couldn't find a slot even though count < size
-        logger.info(f"Failed to insert {value} - table is full")
-        return False
-    
-    def search(self, value):
-        if not isinstance(value, MemoryCell):
-            value = MemoryCell(value)
-            
-        i = Literal(0)
-        while i < self.size:
-            index = self.probe(value, i)
-            
-            # Empty slot found - value doesn't exist
-            if self.table[index].get() is None:
-                return False
-                
-            # Value found
-            if self.table[index] == value:
-                return True
-                
-            # If deleted marker or different value, continue
-            i = i.succ()
-            
-        return False
-    
-    def delete(self, value):
-        if not isinstance(value, MemoryCell):
-            value = MemoryCell(value)
-            
-        i = Literal(0)
-        while i < self.size:
-            index = self.probe(value, i)
-            
-            # Empty slot found - value doesn't exist
-            if self.table[index].get() is None:
-                return False
-                
-            # Value found - mark as deleted
-            if self.table[index] == value:
-                # TODO Check wheter it is .set() or = here
-                self.table[index].set(self.DELETED)
-                self.count = self.count.pred()
-                self.deletedCount = self.deletedCount.succ()
-                return True
-                
-            i = i.succ()
-            
-        return False
-    
-    def __str__(self):
-        result = "["
-        for i in mrange(self.size):
-            if self.table[i].get() is None:
-                result += "None"
-            else:
-                result += str(self.table[i])
-                
-            if i < self.size.pred():
-                result += ", "
-                
-        result += "]"
-        return result
-    
-    def alpha(self):
-        # load factor (count / size)
-        return Literal(self.count.value / self.size.value)
-
-if __name__ == "__main__":
-    table = HashTable(20)
-    seq0Data = MemoryArray.create_array_from_file("data/seq0.txt")
-
-    print(f"Hash table before inserting seq0.txt: {table}")
-    
-    print("Inserting values from seq0.txt...")
-    for value in seq0Data:
-        table.insert(value)
-
-    strFirst = str(table.table[Literal(0)])
-
-    # delete first 5 entries and then try to reinsert them
-    for i in mrange(5):
-        table.delete(seq0Data[i])
-
-    assert(table.deletedCount == Literal(5)), "Deleted count should be 5"
-    for i in mrange(5):
-        table.insert(seq0Data[i])
-
-    assert(table.deletedCount == Literal(0)), "Deleted count should be 0 after reinserting"
-    assert(strFirst == str(table.table[Literal(0)])), "First entry should be the same as before"
-    print(f"Hashtable after inserting seq0.txt: {table}")
-    print(f"Load factor after inserting: {table.alpha()}")
-    
-    print("Deleting 52...")
-    table.delete(Literal(52))
-    print(f"Hash table after deletion: {table}")
-    print(f"New load factr: {table.alpha()}")
-    
-    print("\nInserting value 24...")
-    table.insert(Literal(24))
-    print(f"Hash table after inserting 24: {table}")
-
-    table90 = HashTable(90)
-    seq1Data = MemoryArray.create_array_from_file("data/seq1.txt")
-    
-    print(f"Inserting values from seq1.txt into table with size 90...")
-    insertedCount = Literal(0)
-    for value in seq1Data:
-        if table90.insert(value):
-            insertedCount = insertedCount.succ()
-    
-    print(f"Successfully inserted {insertedCount} out of {Literal(len(seq1Data))} values")
-    print(f"Load factor: {table90.alpha()}")
-    
-    table89 = HashTable(89)
-    
-    print(f"Inserting values from seq1.txt into table with 89...")
-    insertedCount = Literal(0)
-    for value in seq1Data:
-        if table89.insert(value):
-            insertedCount = insertedCount.succ()
-    
-    print(f"Successfully inserted {insertedCount} out of {Literal(len(seq1Data))} values")
-    print(f"Load factor: {table89.alpha()}")
-    
-    tableSymmetric = HashTable(90, probingMethod="symmetric")
-    print(f"Inserting values from seq1.txt into table with size 90 and symmetric probing...")
-    insertedCount = Literal(0)
-    for value in seq1Data:
-        if tableSymmetric.insert(value):
-            insertedCount = insertedCount.succ()
-    
-    print(f"Successfully inserted {insertedCount} out of {Literal(len(seq1Data))} values")
-    print(f"Load factor: {tableSymmetric.alpha()}")
-

schoeffelbe/pr08.py

@@ -1,124 +0,0 @@
-import logging
-from graphviz import Digraph
-from collections import deque
-
-logger = logging.getLogger(__name__)
-# logging.basicConfig(level=logging.DEBUG)
-
-import time
-
-def timeMS(func, *args, **kwargs):
-    startTime = time.perf_counter()
-    result = func(*args, **kwargs)
-    endTime = time.perf_counter()
-    elapsedMS = (endTime - startTime) * 1000  # Convert to milliseconds
-    print(f"{func.__name__} took {elapsedMS:.2f} ms")
-    return result
-
-from utils.memory_array import MemoryArray
-from utils.memory_cell import MemoryCell
-from utils.literal import Literal
-from utils.memory_range import mrange
-from utils.memory_manager import MemoryManager
-
-class Graph:
-    def __init__(self):
-        self.adjacencyList = {}
-
-    def addEdge(self, node1, node2, bidirectional=True):
-        if node1 not in self.adjacencyList:
-            self.adjacencyList[node1] = []
-        if node2 not in self.adjacencyList:
-            self.adjacencyList[node2] = []
-        self.adjacencyList[node1].append(node2)
-        if bidirectional:
-            self.adjacencyList[node2].append(node1)
-
-    def serialize(self):
-        return self.adjacencyList
-
-    def breadthFirstSearch(self, start, goal, edgesGonePassed = None):
-        if start not in self.adjacencyList or goal not in self.adjacencyList:
-            return None, None
-
-        # Dont want to have a class for this, set suffices
-        visited = set()
-        queue = deque([(start, [start], set())])  # (current_node, path, edgesGoneToGetHere)
-
-        while queue:
-            currentNode, path, edgesGone = queue.popleft()
-
-            if currentNode == goal:
-                return path, edgesGone
-
-            if currentNode not in visited:
-                logger.info(f"visiting {currentNode}")
-                visited.add(currentNode)
-                for neighbor in self.adjacencyList[currentNode]:
-                    edge = (currentNode, neighbor)
-                    # We already went this Edge. Read Part3 as not allowing this to happen
-                    edgeReverse = (neighbor, currentNode)
-                    if neighbor not in visited and (edgesGonePassed is None or edge not in edgesGonePassed) and (edgesGonePassed is None or edgeReverse not in edgesGonePassed):
-                        # Pythonic way of saying neighbour, path no next clear neighbour
-                        # and union of edgesGone with current edge
-                        queue.append((neighbor, path + [neighbor], edgesGone | {edge}))
-
-        return None, None
-
-
-def graphvizify(filePath: str, outputFile: str = 'build/hoehleGraph'):
-    graph = Digraph()
-    graph.attr(rankdir='TB')
-    graph.attr('node', shape='circle', style='filled', fillcolor='lightgray')
-    graph.attr('edge', arrowsize='0.7')
-
-    # Reuse the function to also create our Graph... Waste not want not^^
-    caveGraph = Graph();
-
-    with open(filePath, 'r') as f:
-        for line in f:
-            line = line.strip()
-            delimiter = '<>' if '<>' in line else '>' if '>' in line else None
-            if delimiter:
-                node1, node2 = map(str.strip, line.split(delimiter))
-                node1, node2 = map(lambda x: x.strip('"'), map(str.strip, line.split(delimiter)))
-                graph.edge(f"\"{node1}\"", f"\"{node2}\"", dir='none' if delimiter == '<>' else None)
-                caveGraph.addEdge(node1, node2, (delimiter == '<>'));
-
-    try:
-        graph.render(outputFile, view=True)
-    except Exception as e:
-        print(f"Could not display graph: {e}\n Trying to save without viewing!")
-        try:
-            graph.render(outputFile, view=False)
-            print(f"Your built map should be available here: {outputFile}.pdf")
-        except Exception as e:
-            print(f"Could not save graph file: {e}")
-
-    return caveGraph
-
-if __name__ == "__main__":
-    for filename in [ "data/hoehle.txt", "data/hoehleLarger.txt"]:
-        caveGraph = graphvizify(filename, 'build/hoehleGraph')
-
-        start = "Höhleneingang"
-        goal = "Schatzkammer"
-        shortestPath, edgesGoneInitial = caveGraph.breadthFirstSearch(start, goal)
-        logger.debug(caveGraph.adjacencyList)
-        logger.debug(edgesGoneInitial)
-        
-        if shortestPath:
-            print(f"Shortest path from {start} to {goal} is:")
-            print(" -> ".join(shortestPath))
-        else:
-            print(f"No path found from {start} to {goal}.")
-
-        returnpath, _ = caveGraph.breadthFirstSearch(goal, start, edgesGoneInitial)
-
-        if returnpath:
-            print(f"Shortest path from {goal} to {start} is:")
-            print(" -> ".join(returnpath))
-        else:
-            print("No path back Home found. Good Luck")
-
-    exit(0)

schoeffelbe/pr09.py

@@ -1,60 +0,0 @@
-import logging
-
-logger = logging.getLogger(__name__)
-
-
-with open('2024/data/input16.data') as f:
-# with open('2024/data/input16.example') as f:
-    # Dont need edges, these are irrelevant to us
-    content = [list(line.strip()[1:-1]) for line in f.readlines()[1:-1]]
-
-directions = {'N': (-1, 0), 'E': (0, 1), 'S': (1, 0), 'W': (0, -1)}
-
-start = next((row, col, 'E') for row in range(len(content)) for col in range(len(content[0])) if content[row][col] == 'S')
-end = next((row, col) for row in range(len(content)) for col in range(len(content[0])) if content[row][col] == 'E')
-
-# Python it up^^ (outer loop goes over each cell in grid and continues with non-walls,
-# for each valid cell go over all directions and applies costs dependent on turning)
-graph = { (row, col, dirName): {(row+nextdirRow, col+nextdirCol, nextDir): (0 if dirName == nextDir else 1000) + 1
-    for nextDir, (nextdirRow, nextdirCol) in directions.items()
-    if 0 <= row+nextdirRow < len(content) and 0 <= col+nextdirCol < len(content[0]) and content[row+nextdirRow][col+nextdirCol] != '#'}
-    for row in range(len(content)) for col in range(len(content[0])) if content[row][col] != '#' for dirName in directions }
-
-# Algo
-def dijsktra(graph, start, end):
-    import heapq    # Priority Queue, Do not use own for shorter Code^^
-
-    pq, costs, predecessors = [(0, start)], {node: float('inf') for node in graph}, {node: None for node in graph}
-    costs[start] = 0
-    while pq:
-        cost, node = heapq.heappop(pq)
-        logger.debug(f"Procesing node {node} with current cost {cost}")
-        if node[:2] == end[:2]:  # Stop when reaching the end position, dont care about direction
-            path = []
-            while node:
-                path.append(node)
-                node = predecessors[node]
-            logger.debug(f"Final cost: {cost}")
-            return cost, path[::-1]  # Reverse path to get start-to-end order
-        if cost > costs[node]: continue
-
-        for neighbor, edge_cost in graph[node].items():
-            if (new_cost := cost + edge_cost) < costs[neighbor]:
-                costs[neighbor], predecessors[neighbor] = new_cost, node
-                heapq.heappush(pq, (new_cost, neighbor))
-                logger.debug(f"Relaxing edge {node} -> {neighbor}, edge cost: {edge_cost}, new cost: {new_cost}")
-    return float('inf'), []  # No path found
-
-def drawGraph(content, path=None):
-    # Create copy of grid to overlay graph -> No inPlace Stuff
-    grid = [row[:] for row in content]
-    
-    if path:
-        symbols = {'N': '^', 'E': '>', 'S': 'v', 'W': '<'}
-        for row, col, direction in path:
-            grid[row][col] = symbols[direction]
-    return '\n'.join(''.join(row) for row in grid)
-
-costShortest, shortestPath = dijsktra(graph, start, end)
-print("Shortest path cost:", costShortest)
-print(drawGraph(content, shortestPath))

schoeffelbe/priorityQueue.py

@@ -1,7 +1,7 @@
 from utils.memory_array import MemoryArray
 from utils.memory_cell import MemoryCell
 from utils.literal import Literal
-from utils.constants import MIN_VALUE
+from utils.constants import MAX_VALUE
 from utils.memory_range import mrange
 
 # Impl of MemoryArray says we cant add our own Datatypes beside Literal and List
@@ -28,14 +28,14 @@ class HeapEntry:
             return True 
         if isinstance(other, (int, float)):
             return self.getPriority().value > other
-        return self.getPriority() < other.getPriority()
+        return self.getPriority() > other.getPriority()
     
     def __gt__(self, other):
         if other is None:
             return False 
         if isinstance(other, (int, float)):
             return self.getPriority().value < other
-        return self.getPriority() > other.getPriority()
+        return self.getPriority() < other.getPriority()
     
     def __eq__(self, other):
         return self.getPriority() == other.getPriority()
@@ -49,7 +49,7 @@ class PriorityQueue:
         # Add uninitialized HeapEntry Values so the Adds/Compares do not fail on emtpy stack. 
         # Would have to switch to MIN_VALUE if we switch what is a "Higher" Prio
         for i in mrange(max_size.value):
-            self.heap[i].set([HeapEntry(MIN_VALUE, MIN_VALUE)])
+            self.heap[i].set([HeapEntry(MAX_VALUE, MAX_VALUE)])
         self.size = MemoryCell(0)
     
     def parent(self, i: Literal) -> Literal:
@@ -89,13 +89,12 @@ class PriorityQueue:
         
         i = self.size
         self.heap[i].set([entry])
+        self.size += Literal(1)
         
         while i > Literal(0) and self.heap[self.parent(i)].value[0] < self.heap[i].value[0]:
             self.swap(i, self.parent(i))
             i = self.parent(i)
     
-        self.size += Literal(1)
-    
     def pop(self):
         if self.isEmpty():
             raise IndexError("Queue is empty!")
@@ -120,35 +119,6 @@ class PriorityQueue:
     def __len__(self):
         return self.size
 
-    def __str__(self):
-        entries = []
-        for i in mrange(self.size.value):
-            entry = self.heap[i].value[0]
-            if entry.getItem() != MIN_VALUE:
-                entries.append(str(entry))
-        return "[" + ", ".join(entries) + "]"
-
-def testQueueRandom(number: int):
-    import random
-    import string
-
-    pq = PriorityQueue(Literal(number))
-
-    entries = []
-    for _ in range(number):
-        value = ''.join(random.choices(string.ascii_uppercase + string.digits, k=3))
-        priority = random.randint(1, 100)
-        entry = HeapEntry(value, priority)
-        entries.append(entry)
-        pq.insert(entry)
-
-    print(pq)
-    for entry in entries:
-        print(f"Unprioritized: {entry}")
-
-    while not pq.isEmpty(): 
-        print(pq.pop())
-
 
 if __name__ == '__main__':
     # Proof of Concept
@@ -173,21 +143,16 @@ if __name__ == '__main__':
     assert(not pq.isEmpty())
     assert(pq.pop() == HeapEntry("A", 1))
     assert(pq.isEmpty())
+    pq.insert(HeapEntry("A", 1))
     pq.insert(HeapEntry("C", 3))
     pq.insert(HeapEntry("B", 2))
-    pq.insert(HeapEntry("A", 1))
     assert(pq.size == Literal(3))
-    assert(pq.pop() == HeapEntry("C", 3))
-    assert(pq.pop() == HeapEntry("B", 2))
     assert(pq.pop() == HeapEntry("A", 1))
+    assert(pq.pop() == HeapEntry("B", 2))
+    assert(pq.pop() == HeapEntry("C", 3))
     pq.insert(HeapEntry("A", 1))
     pq.insert(HeapEntry("C", 3))
     pq.insert(HeapEntry("B", 2))
-    pq.insert(HeapEntry(42, 4))
+    print(pq.pop())
-    pq.insert(HeapEntry(42, 1))
+    print(pq.pop())
-    pq.insert(HeapEntry("C", 2))
+    print(pq.pop())
-    print(pq)
-    while not pq.isEmpty(): 
-        print(pq.pop())
-
-    testQueueRandom(100)

utils/literal.py

@@ -21,8 +21,6 @@ class Literal:
 
     def __eq__(self, other):
         """Vergleicht den Wert mit einem anderen Wert."""
-        if other is None:
-            return False
         assert isinstance(other, Literal), "Can only compare with Literal or MemoryCell"
         self.compare_count += 1
         self.read_count += 1
@@ -31,8 +29,6 @@ class Literal:
 
     def __ne__(self, other):
         """Vergleicht den Wert der Speicherzelle mit einem anderen Wert."""
-        if other is None:
-            return True
         assert isinstance(other, Literal), "Can only compare with Literal or MemoryCell"
         self.compare_count += 1
         self.read_count += 1

utils/memory_array.py

@@ -1,7 +1,7 @@
 from utils.literal import Literal
 from utils.memory_cell import MemoryCell
 from utils.memory_manager import MemoryManager
-from utils.project_dir import get_path
+from pathlib import Path
 from random import randint
 
 class MemoryArray:
@@ -88,7 +88,9 @@ class MemoryArray:
     @staticmethod
     def create_array_from_file(filename, limit=None):
         """Erzeugt ein Speicherarray aus einer Datei."""
-        filename = get_path(filename)
+        this_dir = Path(__file__).resolve().parent
+        project_dir = this_dir.parent
+        filename = project_dir / filename
         with open(filename) as f:
             lines = f.readlines()
         if limit is not None:
@@ -100,13 +102,6 @@ class MemoryArray:
         a.reset_counters()
         return a
 
-    def __str__(self):
-        result = "[ "
-        for cell in self.cells:
-            result += str(cell) + ", "
-        result += "]"
-        return result
-
 
 if __name__ == "__main__":
     import random
@@ -120,7 +115,3 @@ if __name__ == "__main__":
         s += cell
     print(s)
     print(f"Anzahl der Additionen: {MemoryManager.count_adds()}")
-
-    a = MemoryArray.create_array_from_file("data/seq0.txt")
-    print(a)
-

utils/priority_queue.py

@@ -1,40 +0,0 @@
-import heapq
-
-class PriorityQueue:
-    def __init__(self):
-        self.heap = []
-        self.entry_finder = {}  # map: item -> [priority, item]
-        self.REMOVED = '<removed>'
-        self.counter = 0  # unique sequence count to break ties
-
-    def add_or_update(self, item, priority):
-        if item in self.entry_finder:
-            self.remove(item)
-        count = self.counter
-        entry = [priority, count, item]
-        self.entry_finder[item] = entry
-        heapq.heappush(self.heap, entry)
-        self.counter += 1
-
-    def remove(self, item):
-        entry = self.entry_finder.pop(item)
-        entry[-1] = self.REMOVED  # mark as removed
-
-    def pop(self):
-        while self.heap:
-            priority, count, item = heapq.heappop(self.heap)
-            if item != self.REMOVED:
-                del self.entry_finder[item]
-                return item, priority
-        return None
-
-if __name__ == "__main__":
-    pq = PriorityQueue()
-    pq.add_or_update('task1', 1)
-    pq.add_or_update('task2', float('inf'))
-    pq.add_or_update('task3', float('inf'))
-
-    print(pq.pop())  # Should print ('task1', 1)
-    pq.add_or_update('task2', 0)  # Update priority of 'task1'
-    print(pq.pop())  # Should print ('task2', 0)
-    print(pq.pop())  # Should print ('task3', 3)

utils/project_dir.py

@@ -1,13 +0,0 @@
-from pathlib import Path
-
-def get_path(filename) -> Path:
-    this_dir = Path(__file__).resolve().parent
-    project_dir = this_dir.parent
-    return project_dir / filename
-
-if __name__ == "__main__":
-    filename = get_path("data/seq0.txt")
-    print(filename)
-    print(filename.resolve())
-    print(filename.is_file())
-    print(filename.exists())

vorlesung/03_fortgeschrittenes_sortieren/quick_sorting.py

@@ -5,6 +5,7 @@ from utils.memory_range import mrange
 from utils.literal import Literal
 
 def quick_sort_stepwise(z: MemoryArray, l: Literal, r: Literal):
+    n = z.length()
     if l < r:
         q = partition(z, l, r)
         yield z
@@ -76,6 +77,6 @@ def swap(z: MemoryArray, i: int, j: int):
 
 
 if __name__ == '__main__':
-    sizes = range(10, 101, 5)
+    sizes = range(10, 101, 10)
-    #analyze_complexity(quick_sort, sizes)
+    analyze_complexity(quick_sort, sizes)
-    analyze_complexity(quick_sort, sizes, True)
+    # analyze_complexity(quick_sort, sizes, True)

vorlesung/L04_besondere_sortierverfahren/count_sorting.py

@@ -1,60 +0,0 @@
-from utils.memory_array import MemoryArray
-from utils.memory_cell import MemoryCell
-from utils.memory_manager import MemoryManager
-from utils.memory_range import mrange
-from utils.literal import Literal
-
-
-
-def count_sort(a: MemoryArray, b: MemoryArray, k: int):
-    c = MemoryArray(Literal(k + 1))
-    for i in mrange(Literal(k + 1)):
-        c[i].set(Literal(0))
-
-    for j in mrange(a.length()):
-        c[a[j]].set(c[a[j]].succ())
-
-    for i in mrange(Literal(1), Literal(k + 1)):
-        c[i].set(int(c[i]) + int(c[i.pred()]))
-
-    for j in mrange(a.length().pred(), Literal(-1), Literal(-1)):
-        b[c[a[j]].pred()].set(a[j])
-        c[a[j]].set(c[a[j]].pred())
-
-
-
-def analyze_complexity(sizes, presorted=False):
-    """
-    Analysiert die Komplexität einer Sortierfunktion.
-
-    :param sizes: Eine Liste von Eingabegrößen für die Analyse.
-    """
-    for size in sizes:
-        MemoryManager.purge()  # Speicher zurücksetzen
-        if presorted:
-            random_array = MemoryArray.create_sorted_array(size, 0, 100)
-        else:
-            random_array = MemoryArray.create_random_array(size, 0, 100)
-        dest_array = MemoryArray(Literal(size))
-        count_sort(random_array, dest_array, 100)
-        MemoryManager.save_stats(size)
-
-    MemoryManager.plot_stats(["cells", "compares", "writes"])
-
-
-def swap(z: MemoryArray, i: int, j: int):
-    tmp = z[Literal(i)].value
-    z[Literal(i)] = z[Literal(j)]
-    z[Literal(j)].set(tmp)
-
-
-if __name__ == '__main__':
-
-    # Test the count_sort function
-    a = MemoryArray([2, 5, 3, 0, 2, 3, 0, 3])
-    b = MemoryArray(Literal(len(a)))
-    count_sort(a, b, 5)
-
-    sizes = range(10, 101, 10)
-    analyze_complexity(sizes)
-    # analyze_complexity(sizes, True)

vorlesung/L05_binaere_baeume/__init__.py

@@ -1 +0,0 @@
-from vorlesung.L05_binaere_baeume.bin_tree import BinaryTree

vorlesung/L05_binaere_baeume/analyze_avl_tree.py

@@ -1,26 +0,0 @@
-from utils.memory_manager import MemoryManager
-from utils.memory_array import MemoryArray
-from utils.literal import Literal
-from vorlesung.L05_binaere_baeume.avl_tree import AVLTree
-
-def analyze_complexity(sizes):
-    """
-    Analysiert die Komplexität
-
-    :param sizes: Eine Liste von Eingabegrößen für die Analyse.
-    """
-    for size in sizes:
-        MemoryManager.purge()  # Speicher zurücksetzen
-        tree = AVLTree()
-        random_array = MemoryArray.create_random_array(size, -100, 100)
-        for i in range(size-1):
-            tree.insert(int(random_array[Literal(i)]))
-        MemoryManager.reset()
-        tree.insert(int(random_array[Literal(size-1)]))
-        MemoryManager.save_stats(size)
-
-    MemoryManager.plot_stats(["cells", "compares"])
-
-if __name__ == "__main__":
-    sizes = range(1, 1001, 2)
-    analyze_complexity(sizes)

vorlesung/L05_binaere_baeume/analyze_binary_tree.py

@@ -1,26 +0,0 @@
-from utils.memory_manager import MemoryManager
-from utils.memory_array import MemoryArray
-from utils.literal import Literal
-from vorlesung.L05_binaere_baeume.bin_tree import BinaryTree
-
-def analyze_complexity(sizes):
-    """
-    Analysiert die Komplexität
-
-    :param sizes: Eine Liste von Eingabegrößen für die Analyse.
-    """
-    for size in sizes:
-        MemoryManager.purge()  # Speicher zurücksetzen
-        tree = BinaryTree()
-        random_array = MemoryArray.create_random_array(size, -100, 100)
-        for i in range(size-1):
-            tree.insert(int(random_array[Literal(i)]))
-        MemoryManager.reset()
-        tree.insert(int(random_array[Literal(size-1)]))
-        MemoryManager.save_stats(size)
-
-    MemoryManager.plot_stats(["cells", "compares"])
-
-if __name__ == "__main__":
-    sizes = range(1, 1001, 2)
-    analyze_complexity(sizes)

vorlesung/L05_binaere_baeume/avl_tree.py

@@ -1,94 +0,0 @@
-from utils.memory_array import MemoryArray
-from vorlesung.L05_binaere_baeume.avl_tree_node import AVLTreeNode
-from vorlesung.L05_binaere_baeume.bin_tree import BinaryTree
-import logging
-
-class AVLTree(BinaryTree):
-
-    def __init__(self):
-        super().__init__()
-
-    def new_node(self, value):
-        return AVLTreeNode(value)
-
-
-    def balance(self, node: AVLTreeNode):
-        node.update_balance()
-        if node.balance == -2:
-            if node.left.balance <= 0:
-                node = node.right_rotate()
-            else:
-                node = node.left_right_rotate()
-        elif node.balance == 2:
-            if node.right.balance >= 0:
-                node = node.left_rotate()
-            else:
-                node = node.right_left_rotate()
-        if node.parent:
-            self.balance(node.parent)
-        else:
-            self.root = node
-
-    def insert(self, value):
-        insert_generator = self.insert_stepwise(value)
-        node, parent = None, None
-        while True:
-            try:
-                node, parent = next(insert_generator)
-            except StopIteration:
-                break
-        return node, parent
-
-    def insert_stepwise(self, value):
-        node, parent = super().insert(value)
-        yield None, None
-        node.parent = parent
-        if parent:
-            self.balance(parent)
-        return node, parent
-
-
-    def delete(self, value):
-        node, parent = super().delete(value)
-        if node:
-            node.parent = parent
-        if parent:
-            self.balance(parent)
-
-    def graph_filename(self):
-        return "AVLTree"
-
-if __name__ == "__main__":
-
-    def print_node(node, indent=0, level=0):
-        print((indent * 3) * " ", node.value)
-
-    tree = AVLTree()
-    #values = [5, 3, 7, 2, 4, 6, 5, 8]
-    values = MemoryArray.create_array_from_file("data/seq2.txt")
-
-    for value in values:
-        tree.insert(value)
-
-
-    print("In-order traversal:")
-    tree.in_order_traversal(print_node)
-    print("\nLevel-order traversal:")
-    tree.level_order_traversal(print_node)
-    print("\nTree structure traversal:")
-    tree.tree_structure_traversal(print_node)
-    print("\nGraph traversal:")
-    tree.graph_traversal()
-
-    tree.insert(9)
-    tree.graph_traversal()
-
-    print("\nDeleting 5:")
-    tree.delete(5)
-
-    print("In-order traversal after deletion:")
-    tree.in_order_traversal(print_node)
-    print("\nLevel-order traversal after deletion:")
-    tree.level_order_traversal(print_node)
-    print("\nTree structure traversal after deletion:")
-    tree.tree_structure_traversal(print_node)

vorlesung/L05_binaere_baeume/avl_tree_game.py

@@ -1,59 +0,0 @@
-import random
-import pygame
-from utils.game import Game
-from avl_tree import AVLTree
-
-WHITE = (255, 255, 255)
-BLUE = (0, 0, 255)
-BLACK = (0, 0, 0)
-WIDTH = 800
-HEIGHT = 400
-MARGIN = 20
-
-class AVLTreeGame(Game):
-
-    def __init__(self):
-        super().__init__("AVLTree Game", fps=10, size=(WIDTH, HEIGHT))
-        random.seed()
-        self.z = list(range(1, 501))
-        random.shuffle(self.z)
-        self.finished = False
-        self.tree = AVLTree()
-        self.tree.get_height = lambda node: 0 if node is None else 1 + max(self.tree.get_height(node.left), self.tree.get_height(node.right))
-        self.height = self.tree.get_height(self.tree.root)
-        self.generator = None
-
-    def update_game(self):
-        if not self.finished:
-            if self.generator is None:
-                self.generator = self.tree.insert_stepwise(self.z.pop())
-            try:
-                next(self.generator)
-            except StopIteration:
-                self.generator = None
-            if self.generator is None and len(self.z) == 0:
-                self.finished = True
-            self.height = self.tree.get_height(self.tree.root)
-        return True
-
-    def draw_game(self):
-        self.screen.fill(WHITE)
-        if self.height > 0:
-            self.draw_tree(self.tree.root, WIDTH // 2, MARGIN, WIDTH // 4 - MARGIN)
-        super().draw_game()
-
-    def draw_tree(self, node, x, y, x_offset):
-        y_offset = (HEIGHT - (2 * MARGIN)) / self.height
-        if node is not None:
-            pygame.draw.circle(self.screen, BLUE, (x, y), 2)
-            if node.left is not None:
-                pygame.draw.line(self.screen, BLACK, (x, y), (x - x_offset, y + y_offset))
-                self.draw_tree(node.left, x - x_offset, y + y_offset, x_offset // 2)
-            if node.right is not None:
-                pygame.draw.line(self.screen, BLACK, (x, y), (x + x_offset, y + y_offset))
-                self.draw_tree(node.right, x + x_offset, y + y_offset, x_offset // 2)
-
-if __name__ == "__main__":
-    tree_game = AVLTreeGame()
-    tree_game.run()
-

vorlesung/L05_binaere_baeume/avl_tree_node.py

@@ -1,61 +0,0 @@
-from vorlesung.L05_binaere_baeume.bin_tree_node import BinaryTreeNode
-
-class AVLTreeNode(BinaryTreeNode):
-    def __init__(self, value):
-        super().__init__(value)
-        self.parent = None
-        self.balance = 0
-
-    def __repr__(self):
-        return f"TreeNode(id={id(self)} value={self.value}, left={self.left}, right={self.right})"
-
-    def graphviz_rep(self, row, col, dot):
-        dot.node(str(id(self)), label=str(self.value), pos=f"{col},{-row}!", xlabel=str(self.balance))
-
-    def update_balance(self):
-        left_height = self.left.height() if self.left else 0
-        right_height = self.right.height() if self.right else 0
-        self.balance = right_height - left_height
-
-    def right_rotate(self):
-        new_root = self.left
-        new_root.parent = self.parent
-        self.left = new_root.right
-        if self.left:
-            self.left.parent = self
-        new_root.right = self
-        self.parent = new_root
-        if new_root.parent:
-            if new_root.parent.left is self:
-                new_root.parent.left = new_root
-            else:
-                new_root.parent.right = new_root
-        self.update_balance()
-        new_root.update_balance()
-        return new_root
-
-    def left_rotate(self):
-        new_root = self.right
-        new_root.parent = self.parent
-        self.right = new_root.left
-        if self.right:
-            self.right.parent = self
-        new_root.left = self
-        self.parent = new_root
-        if new_root.parent:
-            if new_root.parent.left is self:
-                new_root.parent.left = new_root
-            else:
-                new_root.parent.right = new_root
-        self.update_balance()
-        new_root.update_balance()
-        return new_root
-
-    def right_left_rotate(self):
-        self.right = self.right.right_rotate()
-        return self.left_rotate()
-
-    def left_right_rotate(self):
-        self.left = self.left.left_rotate()
-        return self.right_rotate()
-

vorlesung/L05_binaere_baeume/bin_search.py

@@ -1,61 +0,0 @@
-import random
-
-from utils.memory_array import MemoryArray
-from utils.memory_cell import MemoryCell
-from utils.memory_manager import MemoryManager
-from utils.memory_range import mrange
-from utils.literal import Literal
-
-
-def binary_search(z: MemoryArray, s: MemoryCell, l: Literal = None, r: Literal = None):
-    """
-    Perform a binary search on the sorted array z for the value x.
-    """
-    if l is None:
-        l = Literal(0)
-    if r is None:
-        r = Literal(z.length().pred())
-    if l > r:
-        return None
-    with MemoryCell(l) as m:
-        m += r
-        m //= Literal(2)
-        if s < z[m]:
-            return binary_search(z, s, l, m.pred())
-        elif s > z[m]:
-            return binary_search(z, s, m.succ(), r)
-        else:
-            return m
-
-
-def analyze_complexity(sizes):
-    """
-    Analysiert die Komplexität
-
-    :param sizes: Eine Liste von Eingabegrößen für die Analyse.
-    """
-    for size in sizes:
-        MemoryManager.purge()  # Speicher zurücksetzen
-        random_array = MemoryArray.create_sorted_array(size)
-        search_value = random.randint(-100, 100)
-        binary_search(random_array, MemoryCell(search_value))
-        MemoryManager.save_stats(size)
-
-    MemoryManager.plot_stats(["cells", "compares", "adds"])
-
-
-
-
-if __name__ == "__main__":
-    # Example usage
-    arr = MemoryArray([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
-    search_value = MemoryCell(8)
-    result = binary_search(arr, search_value)
-    if result is not None:
-        print(f"Value {search_value} found at index {result}.")
-    else:
-        print(f"Value {search_value} not found in the array.")
-
-
-    sizes = range(1, 1001, 2)
-    analyze_complexity(sizes)

vorlesung/L05_binaere_baeume/bin_tree.py

@@ -1,206 +0,0 @@
-from vorlesung.L05_binaere_baeume.bin_tree_node import BinaryTreeNode
-from utils.project_dir import get_path
-from datetime import datetime
-import graphviz
-
-
-class BinaryTree:
-
-    def __init__(self):
-        self.root = None
-        self.size = 0
-
-    def new_node(self, value):
-        return BinaryTreeNode(value)
-
-    def insert(self, value):
-        self.size += 1
-        value = self.new_node(value)
-        if self.root is None:
-            self.root = value
-            return self.root, None
-        else:
-            current = self.root
-            while True:
-                if value < current:
-                    if current.left:
-                        current = current.left
-                    else:
-                        current.left = value
-                        return current.left, current
-                elif value >= current:
-                    if current.right:
-                        current = current.right
-                    else:
-                        current.right = value
-                        return current.right, current
-                else:
-                    return None, None
-
-    def search(self, value):
-        current = self.root
-        value = self.new_node(value)
-        while current:
-            if value < current:
-                current = current.left
-            elif value > current:
-                current = current.right
-            else:
-                return current
-        return None
-
-    def delete(self, value):
-        # Der Wert wird im Baum gesucht und der erste Treffer gelöscht
-        # Rückgabe falls der Wert gefunden wird:
-        # der Knoten, der den zu löschenden Knoten ersetzt und der Elternknoten des gelöschten Knotens
-        parent = None
-        current = self.root
-        value = self.new_node(value)
-        while current:
-            if value < current:
-                parent = current
-                current = current.left
-            elif value > current:
-                parent = current
-                current = current.right
-            else:
-                # Knoten gefunden
-                break
-        else:
-            # Wert nicht gefunden
-            return None, None
-        return self.delete_node(current, parent)
-
-    def delete_node(self, current, parent):
-        # Der übergebene Knoten wird
-        # Rückgabe ist ein Tupel:
-        # der Knoten, der den zu löschenden Knoten ersetzt und der Elternknoten des gelöschten Knotens
-        self.size -= 1
-        # Fall 3: Es gibt zwei Kinder: wir suchen den Nachfolger
-        if current.left and current.right:
-            parent = current
-            successor = current.right
-            while successor.left:
-                parent = successor
-                successor = successor.left
-            # Wert des Nachfolgers wird in den Knoten geschrieben, der gelöscht werden soll
-            current.value = successor.value
-            # Ab jetzt muss successor gelöscht werden; parent ist bereits richtig gesetzt
-            current = successor
-
-        # Ermitteln des einen Kindes (falls es eines gibt), sonst None
-        # Das eine Kind ist der Ersatz für den Knoten, der gelöscht werden soll
-        if current.left:
-            child = current.left
-        else:
-            child = current.right
-
-        # Falls es keinen Elternknoten gibt, ist der Ersatzknoten die Wurzel
-        if not parent:
-            self.root = child
-            return child, None
-        elif parent.left is current:
-            parent.left = child
-            return child, parent
-        else:
-            parent.right = child
-            return child, parent
-
-
-    def in_order_traversal(self, callback):
-
-        def in_order_traversal_recursive(callback, current):
-            if current is not None:
-                in_order_traversal_recursive(callback, current.left)
-                callback(current)
-                in_order_traversal_recursive(callback, current.right)
-
-        in_order_traversal_recursive(callback, self.root)
-
-
-    def level_order_traversal(self, callback):
-        if self.root is None:
-            return
-        queue = [(self.root, 0)]
-        while queue:
-            current, level = queue.pop(0)
-            callback(current, level)
-            if current.left is not None:
-                queue.append((current.left, level + 1))
-            if current.right is not None:
-                queue.append((current.right, level + 1))
-
-    def tree_structure_traversal(self, callback):
-
-        def tree_structure_traversal_recursive(callback, current, level):
-            nonlocal line
-            if current:
-                tree_structure_traversal_recursive(callback, current.left, level + 1)
-                callback(current, level, line)
-                line += 1
-                tree_structure_traversal_recursive(callback, current.right, level + 1)
-
-        line = 0
-        tree_structure_traversal_recursive(callback, self.root, 0)
-
-    def graph_filename(self):
-        return "BinaryTree"
-
-    def graph_traversal(self):
-        def define_node(node, level, line):
-            nonlocal dot
-            if node is not None:
-                node.graphviz_rep(level, line, dot)
-
-        def graph_traversal_recursive(current):
-            nonlocal dot
-            if current is not None:
-                if current.left:
-                    dot.edge(str(id(current)), str(id(current.left)))
-                    graph_traversal_recursive(current.left)
-                if current.right:
-                    dot.edge(str(id(current)), str(id(current.right)))
-                    graph_traversal_recursive(current.right)
-
-        dot = graphviz.Digraph( name="BinaryTree",
-                                engine="neato",
-                                node_attr={"shape": "circle", "fontname": "Arial"},
-                                format="pdf" )
-        self.tree_structure_traversal(define_node)
-        graph_traversal_recursive(self.root)
-        timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
-        filename = f"{self.graph_filename()}_{timestamp}.gv"
-        filename = get_path(filename)
-        dot.render(filename)
-
-if __name__ == "__main__":
-    tree = BinaryTree()
-    values = [5, 3, 7, 2, 4, 6, 5, 8]
-
-    for value in values:
-        tree.insert(value)
-
-    def print_node(node, indent=0, line=None):
-        print((indent * 3) * " ", node.value)
-
-
-    print("In-order traversal:")
-    tree.in_order_traversal(print_node)
-    print("\nLevel-order traversal:")
-    tree.level_order_traversal(print_node)
-    print("\nTree structure traversal:")
-    tree.tree_structure_traversal(print_node)
-    print("\nGraph traversal:")
-    tree.graph_traversal()
-
-    print("\nDeleting 5:")
-    tree.delete(5)
-
-    print("In-order traversal after deletion:")
-    tree.in_order_traversal(print_node)
-    print("\nLevel-order traversal after deletion:")
-    tree.level_order_traversal(print_node)
-    print("\nTree structure traversal after deletion:")
-    tree.tree_structure_traversal(print_node)
-
-

vorlesung/L05_binaere_baeume/bin_tree_game.py

@@ -1,54 +0,0 @@
-import random
-import pygame
-from utils.game import Game
-from bin_tree import BinaryTree
-
-WHITE = (255, 255, 255)
-BLUE = (0, 0, 255)
-BLACK = (0, 0, 0)
-WIDTH = 800
-HEIGHT = 400
-MARGIN = 20
-
-class BinTreeGame(Game):
-
-    def __init__(self):
-        super().__init__("BinTree Game", fps=10, size=(WIDTH, HEIGHT))
-        random.seed()
-        self.z = list(range(1, 101))
-        random.shuffle(self.z)
-        self.finished = False
-        self.tree = BinaryTree()
-        self.tree.get_height = lambda node: 0 if node is None else 1 + max(self.tree.get_height(node.left), self.tree.get_height(node.right))
-        self.height = self.tree.get_height(self.tree.root)
-
-    def update_game(self):
-        if not self.finished:
-            i = self.z.pop()
-            self.tree.insert(i)
-            self.height = self.tree.get_height(self.tree.root)
-            if len(self.z) == 0:
-                self.finished = True
-        return True
-
-    def draw_game(self):
-        self.screen.fill(WHITE)
-        if self.height > 0:
-            self.draw_tree(self.tree.root, WIDTH // 2, MARGIN, WIDTH // 4 - MARGIN)
-        super().draw_game()
-
-    def draw_tree(self, node, x, y, x_offset):
-        y_offset = (HEIGHT - (2 * MARGIN)) / self.height
-        if node is not None:
-            pygame.draw.circle(self.screen, BLUE, (x, y), 2)
-            if node.left is not None:
-                pygame.draw.line(self.screen, BLACK, (x, y), (x - x_offset, y + y_offset))
-                self.draw_tree(node.left, x - x_offset, y + y_offset, x_offset // 2)
-            if node.right is not None:
-                pygame.draw.line(self.screen, BLACK, (x, y), (x + x_offset, y + y_offset))
-                self.draw_tree(node.right, x + x_offset, y + y_offset, x_offset // 2)
-
-if __name__ == "__main__":
-    tree_game = BinTreeGame()
-    tree_game.run()
-

vorlesung/L05_binaere_baeume/bin_tree_node.py

@@ -1,22 +0,0 @@
-from utils.memory_cell import MemoryCell
-
-class BinaryTreeNode(MemoryCell):
-
-    def __init__(self, value):
-        super().__init__(value)
-        self.left = None
-        self.right = None
-
-    def height(self):
-        left_height = self.left.height() if self.left else 0
-        right_height = self.right.height() if self.right else 0
-        return 1 + max(left_height, right_height)
-
-    def __repr__(self):
-        return f"TreeNode(value={self.value}, left={self.left}, right={self.right})"
-
-    def __str__(self):
-        return str(self.value)
-
-    def graphviz_rep(self, row, col, dot):
-        dot.node(str(id(self)), label=str(self.value), pos=f"{col},{-row}!")

vorlesung/L06_b_baeume/analyze_b_tree.py

@@ -1,58 +0,0 @@
-from utils.memory_manager import MemoryManager
-from utils.memory_array import MemoryArray
-from utils.literal import Literal
-from b_tree import BTree
-from b_tree_node import BTreeNode
-
-class MemoryManagerBTree(MemoryManager):
-    """
-    Diese Klasse erweitert den MemoryManager, um spezifische Statistiken für B-Bäume zu speichern.
-    """
-
-    @staticmethod
-    def count_loads():
-        return sum([cell.loaded_count for cell in MemoryManager().cells if isinstance(cell, BTreeNode)])
-
-    @staticmethod
-    def count_saves():
-        return sum([cell.saved_count for cell in MemoryManager().cells if isinstance(cell, BTreeNode)])
-
-    @staticmethod
-    def save_stats(count):
-        data = {    "cells": MemoryManager.count_cells(),
-                    "reads": MemoryManager.count_reads(),
-                    "writes": MemoryManager.count_writes(),
-                    "compares": MemoryManager.count_compares(),
-                    "adds": MemoryManager.count_adds(),
-                    "subs": MemoryManager.count_subs(),
-                    "muls": MemoryManager.count_muls(),
-                    "divs": MemoryManager.count_divs(),
-                    "bitops": MemoryManager.count_bitops(),
-                    "loads": MemoryManagerBTree.count_loads(),
-                    "saves": MemoryManagerBTree.count_saves()  }
-        MemoryManager.stats[count] = data
-
-
-
-
-def analyze_complexity(sizes):
-    """
-    Analysiert die Komplexität
-
-    :param sizes: Eine Liste von Eingabegrößen für die Analyse.
-    """
-    for size in sizes:
-        MemoryManager.purge()  # Speicher zurücksetzen
-        tree = BTree(5)
-        random_array = MemoryArray.create_random_array(size, -100, 100)
-        for i in range(size-1):
-            tree.insert(int(random_array[Literal(i)]))
-        MemoryManager.reset()
-        tree.insert(int(random_array[Literal(size-1)]))
-        MemoryManagerBTree.save_stats(size)
-
-    MemoryManager.plot_stats(["cells", "compares", "loads", "saves"])
-
-if __name__ == "__main__":
-    sizes = range(1, 1001, 2)
-    analyze_complexity(sizes)

vorlesung/L06_b_baeume/b_tree.py

@@ -1,120 +0,0 @@
-from utils.literal import Literal
-from utils.memory_cell import MemoryCell
-from utils.memory_array import MemoryArray
-from b_tree_node import BTreeNode
-
-class BTree:
-    def __init__(self, m: int):
-        self.m = m
-        self.root = BTreeNode(m)
-
-    def search(self, value, start: BTreeNode = None) -> BTreeNode | None:
-        if not start:
-            start = self.root
-        start.load()
-        i = 0
-        if not isinstance(value, MemoryCell):
-            value = MemoryCell(value)
-        while i < start.n and value > start.value[Literal(i)]:
-            i += 1
-        if i < start.n and value == start.value[Literal(i)]:
-            return start
-        if start.leaf:
-            return None
-        return self.search(value, start.children[i])
-
-    def split_child(self, parent: BTreeNode, i: int):
-        child = parent.children[i]
-        child.load()
-        h = BTreeNode(self.m)
-        h.leaf = child.leaf
-        h.n = self.m - 1
-        for j in range(self.m - 1):
-            h.value[Literal(j)] = child.value[Literal(j + self.m)]
-        if not h.leaf:
-            for j in range(self.m):
-                h.children[j] = child.children[j + self.m]
-            for j in range(self.m, child.n + 1):
-                child.children[j] = None
-        child.n = self.m - 1
-        child.save()
-        h.save()
-        for j in range(parent.n, i, -1):
-            parent.children[j + 1] = parent.children[j]
-            parent.value[Literal(j)] = parent.value[Literal(j - 1)]
-        parent.children[i + 1] = h
-        parent.value[Literal(i)] = child.value[Literal(self.m - 1)]
-        parent.n += 1
-        parent.save()
-
-    def insert(self, value):
-        if not isinstance(value, MemoryCell):
-            value = MemoryCell(value)
-        r = self.root
-        if r.n == 2 * self.m - 1:
-            h = BTreeNode(self.m)
-            self.root = h
-            h.leaf = False
-            h.n = 0
-            h.children[0] = r
-            self.split_child(h, 0)
-            self.insert_in_node(h, value)
-        else:
-            self.insert_in_node(r, value)
-
-    def insert_in_node(self, start: BTreeNode, value):
-        start.load()
-        i = start.n
-        if start.leaf:
-            while i >= 1 and value < start.value[Literal(i-1)]:
-                start.value[Literal(i)] = start.value[Literal(i-1)]
-                i -= 1
-            start.value[Literal(i)].set(value)
-            start.n += 1
-            start.save()
-        else:
-            j = 0
-            while j < start.n and value > start.value[Literal(j)]:
-                j += 1
-            if start.children[j].n == 2 * self.m - 1:
-                self.split_child(start, j)
-                if value > start.value[Literal(j)]:
-                    j += 1
-            self.insert_in_node(start.children[j], value)
-
-    def traversal(self, callback):
-        def traversal_recursive(node, callback):
-            i = 0
-            while i < node.n:
-                if not node.leaf:
-                    traversal_recursive(node.children[i], callback)
-                callback(node.value[Literal(i)])
-                i += 1
-            if not node.leaf:
-                traversal_recursive(node.children[i], callback)
-
-        traversal_recursive(self.root, callback)
-
-    def walk(self):
-        def print_key(key):
-            print(key, end=" ")
-
-        self.traversal(print_key)
-
-    def height(self, start: BTreeNode = None):
-        if not start:
-            start = self.root
-        if start.leaf:
-            return 0
-        return 1 + self.height(start.children[0])
-
-
-if __name__ == "__main__":
-    a = MemoryArray.create_array_from_file("data/seq3.txt")
-    tree = BTree(3)
-    for cell in a:
-        tree.insert(cell)
-    print(f"Height: {tree.height()}")
-    tree.walk()
-    s = tree.search(0)
-    print(f"\nKnoten mit 0: {str(s)}")

vorlesung/L06_b_baeume/b_tree_node.py

@@ -1,29 +0,0 @@
-from utils.literal import Literal
-from utils.memory_cell import MemoryCell
-from utils.memory_array import MemoryArray
-
-class BTreeNode(MemoryCell):
-
-    def __init__(self, m: int):
-        super().__init__()
-        self.m = m
-        self.n = 0
-        self.leaf = True
-        self.value = MemoryArray(Literal(2 * m - 1))
-        self.children = [None] * (2 * m)
-        self.loaded_count = 0
-        self.saved_count = 0
-
-    def reset_counters(self):
-        super().reset_counters()
-        self.loaded_count = 0
-        self.saved_count = 0
-
-    def load(self):
-        self.loaded_count += 1
-
-    def save(self):
-        self.saved_count += 1
-
-    def __str__(self):
-        return "(" + " ".join([str(self.value[Literal(i)]) for i in range(self.n)]) + ")"

vorlesung/L07_hashtable/analyze_hashtable.py

@@ -1,60 +0,0 @@
-import math
-import random
-from utils.literal import Literal
-from utils.memory_cell import MemoryCell
-from utils.memory_array import MemoryArray
-from utils.memory_manager import MemoryManager
-from vorlesung.L07_hashtable.hashtable import HashTableOpenAddressing
-
-#Goldener Schnitt
-a = Literal((math.sqrt(5) - 1) / 2)
-
-# Hashfunktion nach multiplikativer Methode
-def h(x: MemoryCell, m: Literal) -> Literal:
-    with MemoryCell(int(x * a)) as integer_part, MemoryCell(x * a) as full_product:
-        with MemoryCell(full_product - integer_part) as fractional_part:
-            return Literal(abs(int(fractional_part * m)))
-
-# Quadratische Sondierung
-def f(x: MemoryCell, i: Literal, m: Literal) -> Literal:
-    c1 = 1
-    c2 = 5
-    with MemoryCell(h(x, m)) as initial_hash, MemoryCell(c2 * int(i) * int(i)) as quadratic_offset:
-        with MemoryCell(initial_hash + quadratic_offset) as probe_position:
-            probe_position += Literal(c1 * int(i)) # Linear component
-            return probe_position % m
-
-# Symmetrische quadratische Sondierung
-def fs(x: MemoryCell, i: Literal, m: Literal) -> Literal:
-    with MemoryCell(h(x, m)) as base_hash, MemoryCell(int(i) * int(i)) as square:
-        if int(i) % 2 == 0:  # gerades i: Vorwärtssondierung
-            with MemoryCell(base_hash + square) as position:
-                return position % m
-        else:  # ungerades i: Rückwärtssondierung
-            with MemoryCell(base_hash - square) as position:
-                return position % m
-
-
-def analyze_complexity(sizes):
-    """
-    Analysiert die Komplexität
-
-    :param sizes: Eine Liste von Eingabegrößen für die Analyse.
-    """
-    for size in sizes:
-        MemoryManager.purge()  # Speicher zurücksetzen
-        ht = HashTableOpenAddressing(size, f)
-        random_array = MemoryArray.create_random_array(size, -100, 100)
-        for cell in random_array:
-            ht.insert(cell)
-        MemoryManager.reset()
-        cell = random.choice(random_array.cells)
-        ht.search(cell)
-        MemoryManager.save_stats(size)
-
-    MemoryManager.plot_stats(["cells", "compares"])
-
-
-if __name__ == "__main__":
-    sizes = range(1, 1001, 10)
-    analyze_complexity(sizes)

vorlesung/L07_hashtable/hashtable.py

@@ -1,76 +0,0 @@
-from collections.abc import Callable
-from utils.literal import Literal
-from utils.memory_array import MemoryArray
-from utils.memory_cell import MemoryCell
-from utils.memory_range import mrange
-
-
-UNUSED_MARK = "UNUSED"
-DELETED_MARK = "DELETED"
-
-class HashTableOpenAddressing:
-    def __init__(self, m: Literal, f: Callable[[MemoryCell, Literal, Literal], Literal]):
-        if not isinstance(m, Literal):
-            m = Literal(m)
-        self.m = m
-        self.f = f
-        self.table = MemoryArray(m)
-        for i in mrange(m):
-            self.table[i].value = UNUSED_MARK
-
-    def insert(self, x: MemoryCell):
-        with MemoryCell(0) as i:
-            while i < self.m:
-                j = self.f(x, i, self.m)
-                if self.is_free(j):
-                    self.table[j].set(x)
-                    return True
-                i.set(i.succ())
-        return False
-
-    def search(self, x: MemoryCell):
-        with MemoryCell(0) as i:
-            while i < self.m:
-                j = self.f(x, i, self.m)
-                if self.is_unused(j):
-                    return False
-                if self.table[j] == x:
-                    return True
-                i.set(i.succ())
-        return False
-
-    def delete(self, x: MemoryCell):
-        with MemoryCell(0) as i:
-            while i < self.m:
-                j = self.f(x, i, self.m)
-                if self.is_unused(j):
-                    return False
-                if self.table[j] == x:
-                    self.table[j].value = DELETED_MARK
-                    return True
-                i.set(i.succ())
-        return False
-
-    def __str__(self):
-        return str(self.table)
-
-    def alpha(self):
-        with MemoryCell(0) as i:
-            used = 0
-            while i < self.m:
-                used += 0 if self.is_free(i) else 1
-                i.set(i.succ())
-        return used / int(self.m)
-
-    def is_unused(self, i: Literal):
-        if self.table[i].value == UNUSED_MARK:
-            return True
-        return False
-
-    def is_deleted(self, i: Literal):
-        if self.table[i].value == DELETED_MARK:
-            return True
-        return False
-
-    def is_free(self, i: Literal):
-        return self.is_unused(i) or self.is_deleted(i)

vorlesung/L08_graphen/aoc2212.py

@@ -1,45 +0,0 @@
-from vorlesung.L08_graphen.graph import Graph, AdjacencyMatrixGraph
-from utils.project_dir import get_path
-
-graph = AdjacencyMatrixGraph()
-start = ""
-end = ""
-
-def read_file(filename: str = "data/aoc2212.txt"):
-    """Read a file and return the content as a string."""
-
-    def adjust_char(char):
-        """Adjust character for comparison."""
-        if char == 'S':
-            return 'a'
-        elif char == 'E':
-            return 'z'
-        return char
-
-    global start, end
-    with open(get_path(filename), "r") as file:
-        quest = file.read().strip().splitlines()
-    for row, line in enumerate(quest):
-        for col, char in enumerate(line):
-            label = f"{row},{col}"
-            graph.insert_vertex(label)
-            if char == "S":
-                start = label
-            if char == "E":
-                end = label
-    for row, line in enumerate(quest):
-        for col, char in enumerate(line):
-            for neighbor in [(row - 1, col), (row, col - 1), (row + 1, col), (row, col + 1)]:
-                if 0 <= neighbor[0] < len(quest) and 0 <= neighbor[1] < len(line):
-                    if ord(adjust_char(quest[neighbor[0]][neighbor[1]])) <= ord(adjust_char(char)) + 1:
-                        label1 = f"{row},{col}"
-                        label2 = f"{neighbor[0]},{neighbor[1]}"
-                        graph.connect(label1, label2)
-
-
-# Lösung des Adventskalenders 2022, Tag 12
-read_file("data/aoc2212test.txt")
-graph.graph()
-distance_map, predecessor_map = graph.bfs(start)
-print(distance_map[graph.get_vertex(end)])
-print(graph.path(end, predecessor_map))

vorlesung/L08_graphen/graph.py

@@ -1,366 +0,0 @@
-from collections import deque
-from typing import List
-from enum import Enum
-import graphviz
-import math
-import heapq
-from datetime import datetime
-from utils.project_dir import get_path
-from utils.priority_queue import PriorityQueue
-from vorlesung.L09_mst.disjoint import DisjointValue
-
-
-class NodeColor(Enum):
-    """Enumeration for node colors in a graph traversal."""
-    WHITE = 1       # WHITE: not visited
-    GRAY = 2        # GRAY: visited but not all neighbors visited
-    BLACK = 3       # BLACK: visited and all neighbors visited
-
-
-class Vertex:
-    """A vertex in a graph."""
-    def __init__(self, value):
-        self.value = value
-
-    def __str__(self):
-        return str(self.value)
-
-    def __repr__(self):
-        return f"Vertex({self.value})"
-
-
-
-class Graph:
-    """A graph."""
-    def insert_vertex(self, name: str):
-        raise NotImplementedError("Please implement this method in subclass")
-
-    def connect(self, name1: str, name2: str, weight: float = 1):
-        raise NotImplementedError("Please implement this method in subclass")
-
-    def all_vertices(self) -> List[Vertex]:
-        raise NotImplementedError("Please implement this method in subclass")
-
-    def get_vertex(self, name: str) -> Vertex:
-        raise NotImplementedError("Please implement this method in subclass")
-
-    def get_adjacent_vertices(self, name: str) -> List[Vertex]:
-        raise NotImplementedError("Please implement this method in subclass")
-
-    def get_adjacent_vertices_with_weight(self, name: str) -> List[tuple[Vertex, float]]:
-        raise NotImplementedError("Please implement this method in subclass")
-
-    def all_edges(self) -> List[tuple[str, str, float]]:
-        raise NotImplementedError("Please implement this method in subclass")
-
-    def bfs(self, start_name: str):
-        """
-        Perform a breadth-first search starting at the given vertex.
-        :param start_name: the name of the vertex to start at
-        :return: a tuple of two dictionaries, the first mapping vertices to distances from the start vertex,
-                 the second mapping vertices to their predecessors in the traversal tree
-        """
-
-        color_map = {}                  # maps vertices to their color
-        distance_map = {}               # maps vertices to their distance from the start vertex
-        predecessor_map = {}            # maps vertices to their predecessor in the traversal tree
-
-        # Initialize the maps
-        for vertex in self.all_vertices():
-            color_map[vertex] = NodeColor.WHITE
-            distance_map[vertex] = None
-            predecessor_map[vertex] = None
-
-        # Start at the given vertex
-        start_node = self.get_vertex(start_name)
-        color_map[start_node] = NodeColor.GRAY
-        distance_map[start_node] = 0
-
-        # Initialize the queue with the start vertex
-        queue = deque()
-        queue.append(start_node)
-
-        # Process the queue
-        while len(queue) > 0:
-            vertex = queue.popleft()
-            for dest in self.get_adjacent_vertices(vertex.value):
-                if color_map[dest] == NodeColor.WHITE:
-                    color_map[dest] = NodeColor.GRAY
-                    distance_map[dest] = distance_map[vertex] + 1
-                    predecessor_map[dest] = vertex
-                    queue.append(dest)
-            color_map[vertex] = NodeColor.BLACK
-
-        # Return the distance and predecessor maps
-        return distance_map, predecessor_map
-
-    def dfs(self):
-        """
-        Perform a depth-first search starting at the first vertex.
-        :return: a tuple of two dictionaries, the first mapping vertices to distances from the start vertex,
-                 the second mapping vertices to their predecessors in the traversal tree
-        """
-        color_map : dict[Vertex, NodeColor]= {}
-        enter_map : dict[Vertex, int] = {}
-        leave_map : dict[Vertex, int] = {}
-        predecessor_map : dict[Vertex, Vertex | None] = {}
-        white_vertices = set(self.all_vertices())
-        time_counter = 0
-
-        def dfs_visit(vertex):
-            nonlocal time_counter
-            color_map[vertex] = NodeColor.GRAY
-            white_vertices.remove(vertex)
-            time_counter += 1
-            enter_map[vertex] = time_counter
-            for dest in self.get_adjacent_vertices(vertex.value):
-                if color_map[dest] == NodeColor.WHITE:
-                    predecessor_map[dest] = vertex
-                    dfs_visit(dest)
-            color_map[vertex] = NodeColor.BLACK
-            time_counter += 1
-            leave_map[vertex] = time_counter
-
-        # Initialize the maps
-        for vertex in self.all_vertices():
-            color_map[vertex] = NodeColor.WHITE
-            predecessor_map[vertex] = None
-
-        while white_vertices:
-            v = white_vertices.pop()
-            dfs_visit(v)
-
-        return enter_map, leave_map, predecessor_map
-
-
-    def path(self, destination, map):
-        """
-        Compute the path from the start vertex to the given destination vertex.
-        The map parameter is the predecessor map
-        """
-        path = []
-        destination_node = self.get_vertex(destination)
-        while destination_node is not None:
-            path.insert(0, destination_node.value)
-            destination_node = map[destination_node]
-        return path
-
-    def graph(self, filename: str = "Graph"):
-        dot = graphviz.Digraph( name=filename,
-                                node_attr={"fontname": "Arial"},
-                                format="pdf" )
-        for vertex in self.all_vertices():
-            dot.node(str(id(vertex)), label=str(vertex.value))
-        for edge in self.all_edges():
-            dot.edge(str(id(self.get_vertex(edge[0]))), str(id(self.get_vertex(edge[1]))), label=str(edge[2]))
-        timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
-        filename = f"{filename}_{timestamp}.gv"
-        filename = get_path(filename)
-        dot.render(filename)
-
-    def dijkstra(self, start_name: str) -> tuple[dict[Vertex, float], dict[Vertex, Vertex | None]]:
-        """
-        Führt den Dijkstra-Algorithmus für kürzeste Pfade durch, implementiert mit Knotenfarben.
-
-        Args:
-            start_name: Name des Startknotens
-
-        Returns:
-            Ein Tupel aus zwei Dictionaries:
-            - distance_map: Abbildung von Knoten auf ihre kürzeste Distanz vom Startknoten
-            - predecessor_map: Abbildung von Knoten auf ihre Vorgänger im kürzesten Pfad
-        """
-
-        def relax(vertex, dest, weight):
-            """
-            Entspannt die Kante zwischen vertex und dest.
-            Aktualisiert die Distanz und den Vorgänger, wenn ein kürzerer Pfad gefunden wird.
-            """
-            if distance_map[vertex] + weight < distance_map[dest]:
-                distance_map[dest] = distance_map[vertex] + weight
-                predecessor_map[dest] = vertex
-                queue.add_or_update(dest, distance_map[dest])
-
-        # Initialisierung der Maps
-        distance_map = {}  # Speichert kürzeste Distanzen
-        predecessor_map = {}  # Speichert Vorgänger
-
-        # Initialisiere alle Knoten
-        queue = PriorityQueue()
-        for vertex in self.all_vertices():
-            distance_map[vertex] = float('inf')  # Initiale Distanz unendlich
-            predecessor_map[vertex] = None  # Initialer Vorgänger None
-            queue.add_or_update(vertex, distance_map[vertex])  # Füge Knoten zur Prioritätswarteschlange hinzu
-
-
-
-        # Setze Startknoten
-        start_node = self.get_vertex(start_name)
-        distance_map[start_node] = 0
-        queue.add_or_update(start_node, distance_map[start_node])
-
-        while True:
-            entry = queue.pop()
-            if entry is None:
-                break
-            vertex = entry[0]
-            for dest, weight in self.get_adjacent_vertices_with_weight(vertex.value):
-                relax(vertex, dest, weight)
-        return distance_map, predecessor_map
-
-    def mst_prim(self, start_name: str = None):
-        """ Compute the minimum spanning tree of the graph using Prim's algorithm. """
-
-        distance_map = {}   # maps vertices to their current distance from the spanning tree
-        parent_map = {}     # maps vertices to their predecessor in the spanning tree
-
-        Vertex.__lt__ = lambda self, other: distance_map[self] < distance_map[other]
-
-        queue = []
-
-        if start_name is None:
-            start_name = self.all_vertices()[0].value
-
-        # Initialize the maps
-        for vertex in self.all_vertices():
-            distance_map[vertex] = 0 if vertex.value == start_name else math.inf
-            parent_map[vertex] = None
-            queue.append(vertex)
-
-        heapq.heapify(queue)    # Convert the list into a heap
-
-        # Process the queue
-        cost = 0 # The cost of the minimum spanning tree
-        while len(queue) > 0:
-            vertex = heapq.heappop(queue)
-            cost += distance_map[vertex] # Add the cost of the edge to the minimum spanning tree
-            for (dest, w) in self.get_adjacent_vertices_with_weight(vertex.value):
-                if dest in queue and distance_map[dest] > w:
-                    # Update the distance and parent maps
-                    queue.remove(dest)
-                    distance_map[dest] = w
-                    parent_map[dest] = vertex
-                    queue.append(dest)      # Add the vertex back to the queue
-                    heapq.heapify(queue)    # Re-heapify the queue
-
-        # Return the distance and predecessor maps
-        return parent_map, cost
-
-    def mst_kruskal(self, start_name: str = None):
-        """ Compute the minimum spanning tree of the graph using Kruskal's algorithm. """
-
-        cost = 0
-        result = []
-        edges = self.all_edges()
-
-        # Create a disjoint set for each vertex
-        vertex_map = {v.value: DisjointValue(v) for v in self.all_vertices()}
-
-        # Sort the edges by weight
-        edges.sort(key=lambda edge: edge[2])
-
-        # Process the edges
-        for edge in edges:
-            start_name, end_name, weight = edge
-            # Check if the edge creates a cycle
-            if not vertex_map[start_name].same_set(vertex_map[end_name]):
-                result.append(edge)
-                vertex_map[start_name].union(vertex_map[end_name])
-                cost += weight
-
-        return result, cost
-
-
-class AdjacencyListGraph(Graph):
-    """A graph implemented as an adjacency list."""
-    def __init__(self):
-        self.adjacency_map = {}     # maps vertex names to lists of adjacent vertices
-        self.vertex_map = {}        # maps vertex names to vertices
-
-    def insert_vertex(self, name: str):
-        if name not in self.vertex_map:
-            self.vertex_map[name] = Vertex(name)
-        if name not in self.adjacency_map:
-            self.adjacency_map[name] = []
-
-    def connect(self, name1: str, name2: str, weight: float = 1):
-        adjacency_list = self.adjacency_map[name1]
-        dest = self.vertex_map[name2]
-        adjacency_list.append((dest, weight))
-
-    def all_vertices(self) -> List[Vertex]:
-        return list(self.vertex_map.values())
-
-    def get_vertex(self, name: str) -> Vertex:
-        return self.vertex_map[name]
-
-    def get_adjacent_vertices(self, name: str) -> List[Vertex]:
-        return list(map(lambda x: x[0], self.adjacency_map[name]))
-
-    def get_adjacent_vertices_with_weight(self, name: str) -> List[tuple[Vertex, float]]:
-        return self.adjacency_map[name]
-
-    def all_edges(self) -> List[tuple[str, str, float]]:
-        result = []
-        for name in self.adjacency_map:
-            for (dest, weight) in self.adjacency_map[name]:
-                result.append((name, dest.value, weight))
-        return result
-
-
-class AdjacencyMatrixGraph(Graph):
-    """A graph implemented as an adjacency matrix."""
-    def __init__(self):
-        self.index_map = {}         # maps vertex names to indices
-        self.vertex_list = []       # list of vertices
-        self.adjacency_matrix = []  # adjacency matrix
-
-    def insert_vertex(self, name: str):
-        if name not in self.index_map:
-            self.index_map[name] = len(self.vertex_list)
-            self.vertex_list.append(Vertex(name))
-            for row in self.adjacency_matrix:   # add a new column to each row
-                row.append(None)
-            self.adjacency_matrix.append([None] * len(self.vertex_list)) # add a new row
-
-    def connect(self, name1: str, name2: str, weight: float = 1):
-        index1 = self.index_map[name1]
-        index2 = self.index_map[name2]
-        self.adjacency_matrix[index1][index2] = weight
-
-
-    def all_vertices(self) -> List[Vertex]:
-        return self.vertex_list
-
-    def get_vertex(self, name: str) -> Vertex:
-        index = self.index_map[name]
-        return self.vertex_list[index]
-
-    def get_adjacent_vertices(self, name: str) -> List[Vertex]:
-        index = self.index_map[name]
-        result = []
-        for i in range(len(self.vertex_list)):
-            if self.adjacency_matrix[index][i] is not None:
-                name = self.vertex_list[i].value
-                result.append(self.get_vertex(name))
-        return result
-
-    def get_adjacent_vertices_with_weight(self, name: str) -> List[tuple[Vertex, float]]:
-        index = self.index_map[name]
-        result = []
-        for i in range(len(self.vertex_list)):
-            if self.adjacency_matrix[index][i] is not None:
-                name = self.vertex_list[i].value
-                result.append((self.get_vertex(name), self.adjacency_matrix[index][i]))
-        return result
-
-    def all_edges(self) -> List[tuple[str, str, float]]:
-        result = []
-        for i in range(len(self.vertex_list)):
-            for j in range(len(self.vertex_list)):
-                if self.adjacency_matrix[i][j] is not None:
-                    result.append((self.vertex_list[i].value, self.vertex_list[j].value, self.adjacency_matrix[i][j]))
-        return result
-
-
-

vorlesung/L09_mst/disjoint.py

@@ -1,18 +0,0 @@
-
-
-class DisjointValue():
-
-    def __init__(self, value):
-        self.value = value
-        self.parent = None
-
-    def canonical(self):
-        if self.parent:
-            return self.parent.canonical()
-        return self
-
-    def same_set(self, other):
-        return self.canonical() == other.canonical()
-
-    def union(self, other):
-        self.canonical().parent = other.canonical()