Add class matrix.py (wip)
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# pwr_project
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# Project for PWR
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Project in python for module "Praktikum Wissenschaftliche Rechnen" in "Applied Mathematics" at *TU Bergakademie Freiberg*.
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#
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# Task
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Implement MPI parallel Matrix and Vector classes in Python and apply them to a numerical problem / algorithm.
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class Matrix:
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import numpy
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class Matrix:
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__data__ = []
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__shape__ = ()
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def __init__(self, data=None, shape=None, structure=None, model=None, size=None):
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if isinstance(data, numpy.ndarray):
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try:
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data.shape[1]
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except IndexError:
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self.__shape__ = (data.shape[0], 1)
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else:
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self.__shape__ = data.shape
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self.__data__ = data.tolist()
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elif isinstance(data, list) and isinstance(shape, tuple):
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self.__shape__ = shape
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self.__data__ = numpy.array(data).reshape(shape).tolist()
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elif isinstance(data, list) and isinstance(structure, str) and isinstance(size, int):
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...
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elif isinstance(model, str) and isinstance(size, int):
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...
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else:
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raise ValueError("Only following signatures are allowed: "
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"(numpy.ndarray), (list, tuple), (list, str, int), (str, int)")
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def get_data(self):
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return self.__data__
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def shape(self):
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return self.__shape__
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def __eq__(self, other):
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return self.__data__ == other.__data__
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@ -1,4 +1,7 @@
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class Vector:
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from matrix import Matrix
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class Vector(Matrix):
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__data__ = []
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def __init__(self, data):
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@ -24,21 +27,33 @@ class Vector:
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def __str__(self):
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return f"{self.__data__}"
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def __neg__(self):
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return Vector([-x for x in self.__data__])
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def __add__(self, other):
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if isinstance(other, Vector):
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if self.get_dimension() != other.get_dimension():
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raise ValueError("The vectors to be added must have the same dimension")
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return Vector([(x + y) for (x, y) in zip(self, other)])
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elif isinstance(other, int) or isinstance(other, float):
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return Vector([(x + other) for x in self.__data__])
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else:
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raise ValueError("A vector can only be multiplied with an vector (dot product) or a scalar")
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data = []
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for (i, j) in zip(self, other):
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data.append(i + j)
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def __radd__(self, other):
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return self + other
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return Vector(data)
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def __sub__(self, other):
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return self + (-other)
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def __rsub__(self, other):
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return -self + other
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def __mul__(self, other):
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if isinstance(other, Vector):
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...
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return sum([(x * y) for (x, y) in zip(self, other)])
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elif isinstance(other, int) or isinstance(other, float):
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...
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return Vector([(other * x) for x in self.__data__])
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else:
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raise ValueError("A vector can only be multiplied with an vector (dot product) or a scalar")
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55
test/test_matrix.py
Normal file
55
test/test_matrix.py
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from unittest import TestCase
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import numpy
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from matrix import Matrix
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class TestMatrix(TestCase):
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def test_should_create_matrix_from_numpy_array_with_shape_3_2(self):
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data = numpy.array([[0, 1], [2, 3], [4, 5]])
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m = Matrix(data)
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actual_shape = m.shape()
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expected_shape = (3, 2)
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self.assertEqual(expected_shape, actual_shape)
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actual_data = m.get_data()
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expected_data = [[0, 1], [2, 3], [4, 5]]
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self.assertEqual(expected_data, actual_data)
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def test_should_create_matrix_from_numpy_array_with_shape_1_3(self):
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data = numpy.array([[0, 1, 2]])
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m = Matrix(data)
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actual_shape = m.shape()
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expected_shape = (1, 3)
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self.assertEqual(expected_shape, actual_shape)
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actual_data = m.get_data()
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expected_data = [[0, 1, 2]]
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self.assertEqual(expected_data, actual_data)
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def test_should_create_vectorlike_matrix_from_numpy_array_with_shape_3_1(self):
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data = numpy.array([0, 1, 2])
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m = Matrix(data)
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actual_shape = m.shape()
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expected_shape = (3, 1)
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self.assertEqual(expected_shape, actual_shape)
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actual_data = m.get_data()
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expected_data = [0, 1, 2]
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self.assertEqual(expected_data, actual_data)
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def test_should_create_matrix_from_list_with_shape_2_2(self):
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data = [0, 1, 2, 3]
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m = Matrix(data, shape=(2, 2))
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actual_shape = m.shape()
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expected_shape = (2, 2)
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self.assertEqual(expected_shape, actual_shape)
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actual_data = m.get_data()
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expected_data = [[0, 1], [2, 3]]
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self.assertEqual(expected_data, actual_data)
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class TestVector(TestCase):
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def test_should_create_vector_dim_5(self):
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dim = 5
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vector = Vector(dim)
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vector = Vector(5)
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actual = vector.get_dimension()
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expected = dim
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expected = 5
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self.assertEqual(expected, actual)
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def test_should_create_zero_vector(self):
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dim = 5
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vector = Vector(dim)
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vector = Vector(5)
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actual = vector.get_data()
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expected = [0, 0, 0, 0, 0]
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self.assertEqual(expected, actual)
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def test_should_create_vector(self):
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@ -28,7 +24,13 @@ class TestVector(TestCase):
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actual = vector.get_data()
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expected = [0, 1, 2, 3, 4]
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self.assertEqual(expected, actual)
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def test_should_neg_vector(self):
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v = Vector([1, 2])
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expected = Vector([-1, -2])
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actual = -v
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self.assertEqual(expected, actual)
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def test_should_add_vectors(self):
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expected = Vector([4, 6])
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actual = v1 + v2
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self.assertEqual(expected, actual)
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def test_should_raise_error_while_adding_vectors(self):
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def test_should_add_scalar_to_vector(self):
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v = Vector([1, 2])
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s = 2
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expected = Vector([3, 4])
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actual = v + s
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self.assertEqual(expected, actual)
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def test_should_radd_scalar_to_vector(self):
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v = Vector([1, 2])
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s = 2
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expected = Vector([3, 4])
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actual = s + v
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self.assertEqual(expected, actual)
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def test_should_raise_value_missmatch_error_while_adding_vectors(self):
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v1 = Vector(1)
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v2 = Vector(2)
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self.assertRaises(ValueError, lambda: v1 + v2)
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def test_should_raise_dimension_error_while_adding_vectors(self):
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v1 = Vector(1)
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v2 = '0'
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self.assertRaises(ValueError, lambda: v1 + v2)
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def test_should_subtract_vectors(self):
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v1 = Vector([1, 2])
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v2 = Vector([3, 4])
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expected = Vector([-2, -2])
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actual = v1 - v2
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self.assertEqual(expected, actual)
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def test_should_subtract_scalar_of_vector(self):
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v = Vector([1, 2])
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s = 2
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expected = Vector([-1, 0])
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actual = v - s
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self.assertEqual(expected, actual)
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def test_should_rsubtract_scalar_of_vector(self):
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v = Vector([1, 2])
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s = 2
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expected = Vector([1, 0])
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actual = s - v
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self.assertEqual(expected, actual)
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def test_should_multiply_vectors(self):
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v1 = Vector([1, 2])
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v2 = Vector([3, 4])
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expected = 11
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actual = v1 * v2
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self.assertEqual(expected, actual)
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def test_should_multiply_scalar_with_vector(self):
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v = Vector([1, 2])
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s = 2
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expected = Vector([2, 4])
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actual = v * s
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self.assertEqual(expected, actual)
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def test_should_rmultiply_scalar_with_vector(self):
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v = Vector([1, 2])
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s = 2
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expected = Vector([2, 4])
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actual = s * v
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self.assertEqual(expected, actual)
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def test_should_raise_value_missmatch_error_while_multiplying_vectors(self):
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v1 = Vector([1, 2])
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v2 = '0'
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self.assertRaises(ValueError, lambda: v1 * v2)
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