Change Aufgabe 4:

umbau auf klasse

s1_a51.py

@@ -1,23 +1,41 @@
+import collections
+
 import numpy as np
 from scipy import sparse
 
+
+class Matrix:
+    def __init__(self):
+        self.matrix = collections.defaultdict(dict)
+
+    def set(self, col, ro, value):
+        if value == 0:
+            if self.matrix.get(col) and self.matrix.get(col).get(ro):
+                del self.matrix[col][ro]
+        else:
+            self.matrix[col][ro] = value
+
+    def get(self, col, ro):
+        if self.matrix.get(col) and self.matrix.get(col).get(row):
+            return self.matrix[col][row]
+        else:
+            return 0
+
+
 if __name__ == "__main__":
     # Aufgabe 1b
     input_matrix = [[3, 0, -2, 11],
                     [0, 0, 9, 0],
                     [0, 7, 0, 0],
                     [0, 0, 0, 0]]
-    sparse_matrix = []
+    mar = Matrix()
     for row in range(len(input_matrix)):
         for column in range(len(input_matrix[0])):
-            if input_matrix[row][column] != 0:
-                # Aufgabe 1d
-                print("Index: ["+str(row)+"]"+"["+str(column)+"] = "+str(input_matrix[row][column]))
-                triplet = [row, column, input_matrix[row][column]]  # saving index of not null values
-                sparse_matrix.append(triplet)
+            mar.set(row, column, input_matrix[row][column])
 
+    print(mar.matrix)
     # Aufgabe 1c
-    print("\nThe sparce matrix computed without numpy\n" + str(sparse_matrix))
+    # print("\nThe sparce matrix computed without numpy\n" + str(sparse_matrix))
 
     # faster way with numpy
     input_matrix = np.array(input_matrix)