Lecture 6

SoSe24/lec05_hash/hash_plot.py

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+from SoSe24.algodat.foundation import AlgoDatArray, AlgoDatValue, read_int_sequence, read_int_sequence_limited
+import matplotlib
+import matplotlib.pyplot as plt
+import hash_table as ht
+
+if __name__ == "__main__":
+    filename = "../../seq3.txt"
+    dummy = read_int_sequence(filename)
+    n = len(dummy)
+    step = n // 100
+
+    memory_values = []
+    compare_values = []
+    alpha_values = []
+
+    for right_end in range(1, n, step):
+        AlgoDatValue.reset()
+        z = read_int_sequence_limited(filename, right_end)
+        hash = ht.HashTable(int(right_end*2), hash_function=ht.h, exploratory_function=ht.f1)
+        for i in z:
+            hash.insert(i)
+        memory_values.append(AlgoDatValue.memory)
+        compare_values.append(AlgoDatValue.compare)
+        alpha_values.append(hash.alpha())
+
+    plt.plot(range(1, n, step), memory_values, 'b', label='Memory')
+    plt.plot(range(1, n, step), compare_values, 'r', label='Compare')
+    plt.plot(range(1, n, step), alpha_values, 'g', label='Alpha')
+
+    plt.legend()
+    plt.show()

SoSe24/lec05_hash/hash_table.py

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+from SoSe24.algodat.foundation import AlgoDatArray, AlgoDatValue, read_int_sequence, MinusInf
+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):
+        self.m = m
+        self.h = hash_function
+        self.f = exploratory_function
+        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)
+            if self.table[j] == x:
+                return True
+            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
+
+    def is_free(self, i):
+        if self.table[i] == None:
+            return True
+        if  self.table[i] == "DELETED":
+            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:
+        hash.insert(algodat_value)
+    print(hash)
+    print(f"Alpha: {hash.alpha()}")
+    hash.delete(11)
+    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()