Merge remote-tracking branch 'origin/master'

# Conflicts:
#	SoSe24/lec04_trees/avl_tree.py
#	SoSe24/lec04_trees/b_tree.py
#	SoSe24/lec05_hash/hash_table.py

SoSe24/lec04_trees/avl_tree.py

@@ -2,7 +2,6 @@ from SoSe24.algodat.foundation import AlgoDatArray, AlgoDatValue, read_int_seque
 from SoSe24.lec04_trees.bin_tree import BinTree, BinTreeNode
 from time import perf_counter as pfc
 
-
 class AVLTreeNode(BinTreeNode):
     def __init__(self, value: AlgoDatValue):
         super().__init__(value)

SoSe24/lec04_trees/b_tree.py

@@ -12,7 +12,6 @@ class BTreeNode:
     def __str__(self):
         return "(" + " ".join([str(self.keys[i]) for i in range(self.n)]) + ")"
 
-
 class BTree:
     def __init__(self, m: int):
         self.m = m

SoSe24/lec05_hash/hash_table.py

@@ -4,45 +4,36 @@ from time import perf_counter as pfc
 #Goldener Schnitt
 import math
 a = (math.sqrt(5) - 1) / 2
-explore_steps = 0
 
 def h(x, m):
     return int(x*a - int(x*a) * m)
 
-
 def f(x, i, m):
     return (h(x, m) + i + 14*i*i) % m
 
-
 def f1(x, i, m):
     if i % 2 == 0:
         return (h(x, m) + i*i) % m
     return ((h(x, m) - i*i) % m + m) % m
 
-
 class HashTable:
-    def __init__(self, m, hash_function, exploratory_function=None):
+    def __init__(self, m, h, f=None):
         self.m = m
-        self.h = hash_function
+        self.h = h
-        self.f = exploratory_function
+        self.f = f
-        self.n = 0
         self.table = AlgoDatArray(m)
 
     def insert(self, x):
-        global explore_steps
         i = 0
         while i < self.m:
             j = self.f(x.value, i, self.m)
             if self.is_free(j):
                 self.table[j].value = x.value
-                self.n += 1
                 return True
             i += 1
-            explore_steps += 1
         return False
 
     def search(self, x):
-        global explore_steps
         i = 0
         while i < self.m:
             j = f(x, i, self.m)
@@ -51,29 +42,30 @@ class HashTable:
             if self.table[j] == None:
                 return False
             i += 1
-            explore_steps += 1
         return False
 
     def delete(self, x):
-        global explore_steps
         i = 0
         while i < self.m:
             j = f(x, i, self.m)
             if self.table[j].value == x:
                 self.table[j].value = "DELETED"
-                self.n -= 1
                 return True
             if self.table[j].value is None:
                 return False
             i += 1
-            explore_steps += 1
         return False
 
     def __str__(self):
         return str(self.table)
 
     def alpha(self):
-        return self.n / self.m
+        i=0
+        used = 0
+        while i < self.m:
+            used += 0 if self.is_free(i) else 1
+            i += 1
+        return used / self.m
 
     def is_free(self, i):
         if self.table[i] == None:
@@ -82,20 +74,18 @@ class HashTable:
             return True
         return False
 
-
 if __name__ == "__main__":
     z = read_int_sequence("../../seq1.txt")
     start = pfc()
     hash = HashTable(31, h, f)
-    for algodat_value in z:
+    for i in z:
-        hash.insert(algodat_value)
+        hash.insert(i)
     print(hash)
     print(f"Alpha: {hash.alpha()}")
-    hash.delete(11)
+    hash.delete(34)
     hash.search(47)
     hash.search(243)
     print(hash)
     print(f"Alpha: {hash.alpha()}")
     print(f"Dauer: {pfc() - start:.4f}s")
-    print(f"Sondierungsschritte: {explore_steps}")
     AlgoDatValue.summary()

SoSe24/lec06_graph/bfs.py

@@ -0,0 +1,181 @@
+from collections import deque
+from typing import List
+import re
+from enum import Enum
+
+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
+
+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):
+        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 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 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
+
+
+
+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):
+        adjacency_list = self.adjacency_map[name1]
+        dest = self.vertex_map[name2]
+        adjacency_list.append(dest)
+
+    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 self.adjacency_map[name]
+
+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(0)
+            self.adjacency_matrix.append([0] * len(self.vertex_list)) # add a new row
+
+    def connect(self, name1: str, name2: str):
+        index1 = self.index_map[name1]
+        index2 = self.index_map[name2]
+        self.adjacency_matrix[index1][index2] = 1
+
+    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] == 1:
+                name = self.vertex_list[i].value
+                result.append(self.get_vertex(name))
+        return result
+
+def read_cave_into_graph(graph: Graph, filename: str):
+    """Read a cave description from a file and insert it into the given graph."""
+    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)
+
+
+if __name__ == "__main__":
+    graph = AdjacencyListGraph()
+    #graph = AdjacencyMatrixGraph()
+    read_cave_into_graph(graph, "../../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)