Finalize matrix.py

src/matrix.py

@@ -1,4 +1,5 @@
 import numpy
+from numpy import linalg
 
 
 class Matrix:
@@ -47,7 +48,8 @@ class Matrix:
             elif structure == "tridiagonal":
                 if len(data) != 3:
                     raise ValueError("If structure is tridiagonal, then the given data must be of length 3")
-                tridiag = numpy.diag([data[0]] * (n-1), -1) + numpy.diag([data[1]] * n, 0) + numpy.diag([data[2]] * (n-1), 1)
+                tridiag = numpy.diag([data[0]] * (n - 1), -1) + numpy.diag([data[1]] * n, 0) + numpy.diag(
+                    [data[2]] * (n - 1), 1)
                 self.__data__ = tridiag
                 self.__shape__ = tridiag.shape
         # Case: Matrix(list, str, int)
@@ -64,7 +66,8 @@ class Matrix:
                 self.__shape__ = data.shape
             self.__data__ = data
         else:
-            raise ValueError("Only following signatures are allowed: (numpy.ndarray), (list, tuple), (list, str, int), (str, int)")
+            raise ValueError(
+                "Only following signatures are allowed: (numpy.ndarray), (list, tuple), (list, str, int), (str, int)")
 
     def get_data(self):
         """
@@ -126,16 +129,47 @@ class Matrix:
     def __rsub__(self, other):
         return -self + other
 
+    def __mul__(self, other):
+        if isinstance(other, Matrix):
+            if self.__shape__[1] != other.__shape__[0]:
+                raise ValueError(
+                    "The amount of columns of the first operand must match the amount of rows of the second operand")
+            return Matrix(self.__data__ @ other.__data__)
+        elif isinstance(other, int) or isinstance(other, float):
+            return Matrix(other * self.__data__)
+        else:
+            raise ValueError("Only a number or another ``Matrix`` can be multiplied to a ``Matrix``")
+
+    def __rmul__(self, other):
+        return self * other
+
     def __truediv__(self, other):
         if isinstance(other, int) or isinstance(other, float):
             return self.__data__ / other
         else:
             raise ValueError("A ``Matrix`` can only be divided ba a number")
 
-    def __mul__(self, other):
-        if isinstance(other, Matrix):
-            if self.__shape__[1] != other.__shape__[0]:
-                raise ValueError("The amount of columns of the first operand must match the amount of rows of the second operand")
-            return Matrix(self.__data__ * other.__data__)
-        elif isinstance(other, int) or isinstance(other, float):
-            ...
+    def norm(self, f: str = "frobenius"):
+        """
+        Calculates the norm of the matrix.
+
+        A norm is a positive definit, absolute homogeneous and subadditive function.
+        For Matrices a norm is also sub-multiplicative.
+
+        :param f: The norm to be used, could be either "frobenius", "rowsum" or "colsum"
+
+        :return: the norm as a number
+        """
+        t = "fro"
+        if f == "colsum":
+            t = 1
+        elif f == "rowsum":
+            t = numpy.inf
+        return linalg.norm(self.__data__, t)
+
+    def __getitem__(self, key):
+        return self.__data__[key]
+
+    def __setitem__(self, key, value):
+        self.__data__[key] = value
+