Merge branch 'refs/heads/feature/mpi'

src/matrix.py

@@ -85,11 +85,8 @@ class Matrix:
 
     @staticmethod
     def flatten_internal(matrices):
-        flattened_data = []
+        flattened_data = [element for matrix in matrices for row in matrix.get_data() for element in row]
-        rows = 0
+        rows = sum(matrix.__shape__[0] for matrix in matrices)
-        for matrix in matrices:
-            flattened_data.extend(matrix.get_data())
-            rows += matrix.__shape__[0]
         cols = matrices[0].__shape__[1]
         return flattened_data, (rows, cols)
 
@@ -114,13 +111,8 @@ class Matrix:
         return self.__shape__
 
     def __transpose_internal__(self):
-        rows = self.__shape__[0]
+        rows, cols = self.__shape__
-        cols = self.__shape__[1]
+        return [[self.__data__[i][j] for i in range(rows)] for j in range(cols)], (cols, rows)
-        transposed_data = [([0] * rows) for _ in range(cols)]
-        for i in range(rows):
-            for j in range(cols):
-                transposed_data[j][i] = self.__data__[i][j]
-        return transposed_data, (cols, rows)
 
     def transpose(self):
         """
@@ -144,6 +136,9 @@ class Matrix:
         :param other: The object to compare to; must be either a ``Matrix``, a ``list`` or a ``numpy.ndarray``
         :return: True if data in the matrix are equal to the given data in other for each component, otherwise False
         """
+        if not isinstance(other, (Matrix, list, numpy.ndarray)):
+            raise ValueError("Matrix type is not comparable to type of given ``other``")
+        data_to_compare = other
         if isinstance(other, Matrix):
             if self.__shape__ != other.__shape__:
                 return False
@@ -154,45 +149,33 @@ class Matrix:
                 return False
         elif isinstance(other, numpy.ndarray):
             data_to_compare = other.tolist()
-        else:
+        return all(value == other_value
-            raise ValueError("Matrix type is not comparable to type of given ``other``")
+                   for row, other_row in zip(self.__data__, data_to_compare)
-
+                   for value, other_value in zip(row, other_row))
-        for i in range(len(self.__data__)):
-            for j in range(len(self.__data__[i])):
-                if self.__data__[i][j] != data_to_compare[i][j]:
-                    return False
-        return True
 
     def __str__(self):
         return str(numpy.array(self.__data__))
 
     def __neg_internal__(self):
-        rows = range(self.__shape__[0])
+        return list(map(lambda row: [-value for value in row], self.__data__))
-        cols = range(self.__shape__[1])
-        return [[-(self.__data__[i][j]) for j in cols] for i in rows]
 
     def __neg__(self):
         return Matrix(self.__neg_internal__(), self.__shape__)
 
     def __add_matrix_internal__(self, other):
-        rows = self.__shape__[0]
+        return [list(map(sum, zip(*rows))) for rows in zip(self.__data__, other.__data__)]
-        cols = self.__shape__[1]
-        return [[(self.__data__[i][j] + other.__data__[i][j]) for j in range(cols)] for i in range(rows)]
 
     def __add_scalar_internal__(self, other):
-        rows = self.__shape__[0]
+        return [[value + other for value in row] for row in self.__data__]
-        cols = self.__shape__[1]
-        return [[(self.__data__[i][j] + other) for j in range(cols)] for i in range(rows)]
 
     def __add__(self, other):
+        if not isinstance(other, (Matrix, int, float)):
+            raise ValueError("Only a number or another ``Matrix`` can be added to a ``Matrix``")
         if isinstance(other, Matrix):
             if self.__shape__ != other.__shape__:
                 raise ValueError("The shape of the operands must be the same")
             return Matrix(self.__add_matrix_internal__(other), self.__shape__)
-        elif isinstance(other, int) or isinstance(other, float):
         return Matrix(self.__add_scalar_internal__(other), self.__shape__)
-        else:
-            raise ValueError("Only a number or another ``Matrix`` can be added to a ``Matrix``")
 
     def __radd__(self, other):
         return self + other
@@ -204,28 +187,21 @@ class Matrix:
         return -self + other
 
     def __truediv_scalar_internal__(self, other):
-        rows = self.__shape__[0]
+        return [list(map(lambda value: value / other, row)) for row in self.__data__]
-        cols = self.__shape__[1]
-        return [[(self.__data__[i][j] / other) for j in range(cols)] for i in range(rows)]
 
     def __truediv__(self, other):
-        if isinstance(other, int) or isinstance(other, float):
+        if not isinstance(other, (int, float)):
-            return Matrix(self.__truediv_scalar_internal__(other), self.__shape__)
-        else:
             raise ValueError("A ``Matrix`` can only be divided ba a number")
+        return Matrix(self.__truediv_scalar_internal__(other), self.__shape__)
 
     def __mul_rowmatrix_matrix__internal__(self, other):
-        cols = other.__shape__[1]
+        rows, cols = self.__shape__[1], other.__shape__[1]
-        new_data = [0] * cols
+        return [sum(self.__data__[0][j] * other.__data__[j][i] for j in range(rows)) for i in range(cols)]
-        for i in range(cols):
-            new_data[i] = sum([self.__data__[0][j] * other.__data__[j][i] for j in range(self.__shape__[1])])
-        return new_data
 
     def __mul_matrix_internal__(self, other):
         if self.__shape__[0] == 1:
             return self.__mul_rowmatrix_matrix__internal__(other)
-        rows = self.__shape__[0]
+        rows, cols = self.__shape__[0], other.__shape__[1]
-        cols = other.__shape__[1]
         new_data = [([0] * cols) for _ in range(rows)]
         for i in range(rows):
             for k in range(cols):
@@ -233,9 +209,7 @@ class Matrix:
         return new_data
 
     def __mul_scalar_internal__(self, other):
-        rows = range(self.__shape__[0])
+        return [list(map(lambda value: value * other, row)) for row in self.__data__]
-        cols = range(self.__shape__[1])
-        return [[(self.__data__[i][j] * other) for j in cols] for i in rows]
 
     def __mul__(self, other):
         if isinstance(other, Matrix):
@@ -255,31 +229,13 @@ class Matrix:
         return self.__abs_sum_of_squares__()
 
     def __abs_sum_of_squares__(self):
-        rows = self.__shape__[0]
+        return sum(abs(element) ** 2 for row in self.__data__ for element in row)
-        cols = self.__shape__[1]
-        abs_sum = 0
-        for i in range(rows):
-            for j in range(cols):
-                abs_sum += abs(self.__data__[i][j]) ** 2
-        return abs_sum
 
     def __col_sums__(self):
-        rows = self.__shape__[0]
+        return [sum(abs(row[j]) for row in self.__data__) for j in range(self.__shape__[1])]
-        cols = self.__shape__[1]
-        col_sums = [0] * cols
-        for j in range(cols):
-            for i in range(rows):
-                col_sums[j] += abs(self.__data__[i][j])
-        return col_sums
 
     def __row_sums__(self):
-        rows = self.__shape__[0]
+        return [sum(abs(value) for value in row) for row in self.__data__]
-        cols = self.__shape__[1]
-        row_sums = [0] * rows
-        for i in range(rows):
-            for j in range(cols):
-                row_sums[i] += abs(self.__data__[i][j])
-        return row_sums
 
     def norm(self, f: str = "frobenius"):
         """

src/matrix_mpi.py

@@ -111,7 +111,7 @@ class MatrixMPI:
         :return: True if data in the matrix are equal to the given data in other for each component, otherwise False
         """
         if isinstance(other, MatrixMPI):
-            return self.__data__ == other.__data__
+            return all(self.__mpi_comm__.allgather(self.__rank_subdata__ == other.__rank_subdata__))
         else:
             return self.__data__ == other
 

src/vector.py

@@ -80,8 +80,7 @@ class Vector(Matrix):
             raise ValueError("Only a number or another ``Vector`` can be added to a ``Vector``")
 
     def __mul_vector_same_shape_internal__(self, other):
-        rows = self.__shape__[0]
+        rows, cols = self.__shape__
-        cols = self.__shape__[1]
         if rows >= cols:
             new_data = [(self.__data__[i][0] * other.__data__[i][0]) for i in range(rows)]
         else:
@@ -89,8 +88,7 @@ class Vector(Matrix):
         return new_data
 
     def __mul_tensor_internal__(self, other):
-        rows = self.__shape__[0]
+        rows, cols = self.__shape__[0], other.__shape__[1]
-        cols = other.__shape__[1]
         return [[self.__data__[i][0] * other.__data__[0][j] for j in range(cols)] for i in range(rows)], (rows, cols)
 
     def __mul__(self, other):
@@ -112,31 +110,24 @@ class Vector(Matrix):
                              "a compatible ``Matrix`` or a scalar")
 
     def __mul_matrix_vector_internal__(self, other):
-        rows = other.__shape__[0]
+        rows, vector_rows = other.__shape__[0], self.__shape__[0]
-        new_data = [0] * rows
+        return [sum([other.__data__[i][j] * self.__data__[j][0] for j in range(vector_rows)]) for i in range(rows)]
-        for i in range(rows):
-            new_data[i] = sum([other.__data__[i][j] * self.__data__[j][0] for j in range(self.__shape__[0])])
-        return new_data
 
     def __rmul__(self, other):
-        if isinstance(other, Matrix):
+        return Vector(self.__mul_matrix_vector_internal__(other)) if isinstance(other, Matrix) else self * other
-            return Vector(self.__mul_matrix_vector_internal__(other))
-        return self * other
 
     def __truediv_vector_internal__(self, other):
-        rows = self.__shape__[0]
+        rows, cols = self.__shape__
-        cols = self.__shape__[1]
         return [[(self.__data__[i][j] / other.__data__[i][j]) for j in range(cols)] for i in range(rows)]
 
     def __truediv__(self, other):
+        if not isinstance(other, (Vector, int, float)):
+            raise ValueError("A ``Vector`` can only be divided ba a number or another same-shaped ``Vector``")
         if isinstance(other, Vector):
             if self.__shape__ != other.__shape__:
                 raise ValueError("The ``Vector``s to be divided must have the same shape")
             return Vector(self.__truediv_vector_internal__(other))
-        elif isinstance(other, int) or isinstance(other, float):
         return Vector(super().__truediv_scalar_internal__(other))
-        else:
-            raise ValueError("A ``Vector`` can only be divided ba a number or another same-shaped ``Vector``")
 
     def norm(self, **kwargs):
         """