empty_element durch eine Klasse Element ersetzt, Anpassung der Funktionen

P1/main.py

@@ -1,13 +1,23 @@
 import math
 
-empty_element = {
-    "count" : 1,
-    "p(x_i)" : 0,
-    "I(x_i)" : 0
-}
+class Element:
+    id = ""
+    count = 0
+    p_x_i = 0
+    I_x_i = 0
+
+    def __init__(self, id):
+        self.id = id
+        self.count = 1
+
+def find_element(list, target_it):
+    for element in list:
+        if element.id == target_it:
+            return element
+    return None
 
 def read_text_file():
-    path = '/Users/safak/Documents/UNI/IT/P1/text.txt'
+    path = './text.txt'
 
     with open(path, 'r', encoding='utf-8') as file:
         content = file.read()
@@ -19,13 +29,14 @@ def Z_statistik():
 
     m = len(message)
 
-    elements = {}
+    elements = []
 
     for char in message:
-        if elements.__contains__(char):
-            elements[char]["count"] += 1
+        entry = find_element(elements, char)
+        if entry is not None:
+            entry.count += 1
         else:
-            elements[char] = empty_element.copy()
+            elements.append(Element(char))
 
     calculate(elements, m, message)
 
@@ -34,15 +45,17 @@ def Z2_statistik():
 
     m = len(message) - 1        # Letztes Zeichen kann kein Tupel mit "nichts" bilden
 
-    elements = {}
+    elements = []
 
     for i, char in enumerate(message):
-        if i != m:
+        if i < m:
             tuple = char + message[i+1]
-            if elements.__contains__(tuple):
-                elements[tuple]["count"] += 1
+            entry = find_element(elements, tuple)
+
+            if entry is not None:
+                entry.count += 1
             else:
-                elements[tuple] = empty_element.copy()
+                elements.append(Element(tuple))
 
     calculate(elements, m, message)
 
@@ -52,9 +65,10 @@ def W_statistik():
     m = 0
     i = 0
 
-    elements = {}
+    elements = []
+    l = len(message)
 
-    while i != len(message):
+    while i < l:
         word = ""
 
         if message[i].isalpha():
@@ -62,7 +76,7 @@ def W_statistik():
             word += message[i]
 
             # füge Zeichen hinzu bis Wortende erreicht ist
-            while message[i+1].isalpha():
+            while i+1 is not l and message[i+1].isalpha():
                 i += 1
                 word += message[i]
 
@@ -70,10 +84,12 @@ def W_statistik():
             m += 1
 
             # Zähle die Häufigkeit der Wörter
-            if elements.__contains__(word):
-                elements[word]["count"] += 1
+
+            entry = find_element(elements, word)
+            if entry is not None:
+                entry.count += 1
             else:
-                elements[word] = empty_element.copy()
+                elements.append(Element(word))
 
         # gehe weiter in der Nachricht
         i += 1
@@ -81,32 +97,17 @@ def W_statistik():
     calculate(elements, m, message)
 
 def calculate(elements, m, message):
-    for x_i in elements:
-        elements[x_i]["p(x_i)"] = elements[x_i]["count"] / m
-        elements[x_i]["I(x_i)"] = -1 * math.log2(elements[x_i]["p(x_i)"])
-
     h = 0
-    for x_i in elements:
-        h += elements[x_i]["p(x_i)"] * elements[x_i]["I(x_i)"]
+    for element in elements:
+        element.p_x_i = element.count / m
+        element.I_x_i = -1 * math.log2(element.p_x_i)
+        h += element.p_x_i * element.I_x_i
 
-
-    sorted_by_element = sorted(elements)
-
-    sorted_by_count = dict(sorted(
-                               elements.items(),
-                               key = lambda item: item[1]["count"],
-                               reverse=True
-                               ))
-
-    sorted_by_information = dict(sorted(
-                                     elements.items(),
-                                     key = lambda item: item[1]["I(x_i)"],
-                                     reverse=True
-                                     ))
     # Ausgabe
-    for x_i in sorted_by_element:
-        print(f"{elements[x_i]["count"]:3.0f} | {elements[x_i]["p(x_i)"]:10.7f} | {elements[x_i]["I(x_i)"]:10.7f} | »{x_i}«")
-    print("Entropie der Nachricht = " + h.__str__() + "\n\n")
+    elements.sort(key = lambda element: element.count, reverse = True)
+    for element in elements:
+        print(f"{element.count:3.0f} | {element.p_x_i:10.7f} | {element.I_x_i:10.7f} | »{element.id}«")
+    print("Entropie = " + h.__str__() + "\n\n")
 
 def main():
     Z_statistik()