def test_setitem_column_as_int(self):
all_matrices = copy.deepcopy(utils.ALL_MATRICES)
for mat, k in itertools.product(all_matrices, utils.ALL_SCALARS):
vec = Vector([k] * mat.num_rows)
for start in range(0, mat.num_columns):
mat[:, start] = k
utils.assert_vectors_almost_equal(mat[:, start], vec)
def test_make_unitary(self):
for vec in utils.ALL_VECTORS:
if vec.norm > 0:
v = Vector.make_unitary(vec)
self.assertAlmostEqual(v.norm, 1, PRECISION)
self.assertEqual(v.dim, vec.dim)
utils.assert_vectors_almost_equal(vec.norm * v, vec)
def _make_identity_rowvectors(num_rows, num_columns):
rowvectors = []
for i in range(num_rows):
components = [0] * num_columns
if i < num_columns:
components[i] = 1
rowvectors.append(Vector(components))
return rowvectors
def make_row_addition(
cls, num_rows: int, num_columns: int, i: int, j: int, m: t.Union[int, float]
):
rowvectors = _make_identity_rowvectors(num_rows, num_columns)
rowvectors[j] = rowvectors[j] + Vector(
m if j_ == i else 0 for j_ in range(num_columns)
)
return cls(rowvectors)
def test_cross_jacobi_identity(self):
for v1, v2 in itertools.product(utils.ALL_VECTORS, utils.ALL_VECTORS):
for v3 in utils.ALL_VECTORS:
vec1 = vector_ops.cross(v1, vector_ops.cross(v2, v3))
vec2 = vector_ops.cross(v2, vector_ops.cross(v3, v1))
vec3 = vector_ops.cross(v3, vector_ops.cross(v1, v2))
utils.assert_vectors_almost_equal(vec1 + vec2 + vec3,
Vector.make_zero(3))
def test_setitem_column_as_sequence(self):
factories = [lambda x: x, lambda x: x.components, list, tuple]
all_matrices = copy.deepcopy(utils.ALL_MATRICES)
for mat, k in itertools.product(all_matrices, utils.ALL_SCALARS):
vec = Vector([k] * mat.num_rows)
for start in range(0, mat.num_columns):
for fac in factories:
mat[:, start] = fac(vec)
utils.assert_vectors_almost_equal(mat[:, start], vec)
def test_setitem_column_slice_as_int(self):
all_matrices = copy.deepcopy(utils.ALL_MATRICES)
for mat, k in itertools.product(all_matrices, utils.ALL_SCALARS):
vec = Vector([k] * mat.num_rows)
for start in range(0, mat.num_columns):
for stop in range(start + 1, mat.num_columns + 1):
for step in range(1, stop):
mat[:, start:stop:step] = k
for i in range(start, stop, step):
utils.assert_vectors_almost_equal(mat[:, i], vec)
def test_setitem_slice_to_sequence(self):
all_vecs = copy.deepcopy(utils.ALL_VECTORS)
for vec, k in itertools.product(all_vecs, utils.ALL_SCALARS):
for start in range(0, vec.dim + 1):
for stop in range(start + 1, vec.dim + 2):
for step in range(1, stop):
length = math.ceil((stop - start) / step)
expected = Vector([k] * length)
vec[start:stop:step] = expected
real = vec[start:stop:step]
self.assertIsInstance(real, Vector)
self.assertEqual(real, expected)
def __getitem__(self, slice_):
if isinstance(slice_, int):
return self._rowvectors[slice_]
elif isinstance(slice_, slice):
rowvectors = self._rowvectors[slice_]
return type(self)(rowvectors)
elif isinstance(slice_, tuple):
row, col = slice_
if isinstance(row, int) and isinstance(col, int):
return self._rowvectors[row][col]
elif isinstance(row, slice) and isinstance(col, int):
return Vector(v[col] for v in self.iterrows())
elif isinstance(row, int) and isinstance(col, slice):
return Vector(self._rowvectors[row][col])
else:
start, stop, step = self._read_slice(row, self.num_rows)
rowvectors = (
self._rowvectors[i][col] for i in range(start, stop, step)
)
return type(self)(rowvectors)
else:
raise RuntimeError(f"unsupported slice type {slice_}")
def from_columnvectors(cls, vectors: t.Iterable[Vector]):
vectors = list(vectors)
_validate_vector_dimensions(vectors)
rowvectors = [Vector(v[i] for v in vectors) for i in range(vectors[0].dim)]
return cls(rowvectors)
def itercolumns(self) -> t.Generator[Vector, None, None]:
for j in range(self.num_columns):
yield Vector(self._rowvectors[i][j] for i in range(self.num_rows))
import math
import lac.vector as vector_ops
import lac.matrix as matrix_ops
from lac import Matrix, Vector
VEC1 = Vector([1, 2, -3])
VEC2 = Vector([0, 0, 0])
VEC3 = Vector([math.pi, 1 / math.pi, math.e])
ALL_VECTORS = [VEC1, VEC2, VEC3]
ALL_SCALARS = [0, 1, -1, -math.pi, 0.5]
MAT1 = Matrix([Vector([1, 0, 0]), Vector([0, 1, 0]), Vector([0, 0, 1])])
REDUCED_MATRICES = [
(
Matrix([
Vector([2, 5, 8, 7]),
Vector([5, 2, 2, 8]),
Vector([7, 5, 6, 6]),
Vector([5, 4, 4, 8]),
]),
Matrix([
Vector([7, 5, 6, 6]),
Vector(
[0, 3.5714285714285716, 6.285714285714286, 5.285714285714286]),
Vector([0, 0, -1.04, 3.08]),
Vector([0, 0, 0, 7.46153846153846]),
]),
def test_make_zero(self):
dim = 3
vec = Vector.make_zero(dim)
self.assertEqual(vec.norm, 0, PRECISION)
self.assertEqual(vec.dim, dim)
def test_angle_between_antiparallel(self):
v1 = Vector([-1, 0, 0])
v2 = Vector([2, 0, 0])
self.assertAlmostEqual(vector_ops.angle_between(v1, v2), math.pi,
PRECISION)
def test_angle_between_orthogonal(self):
v1 = Vector([0, 1, 0])
v2 = Vector([1, 0, 0])
self.assertAlmostEqual(vector_ops.angle_between(v1, v2), math.pi / 2,
PRECISION)
def test_dot_orthogonal(self):
v1 = Vector([0, 1, 0])
v2 = Vector([1, 0, 0])
self.assertAlmostEqual(vector_ops.dot(v1, v2), 0, PRECISION)
def test_cross_parallel(self):
v1 = Vector([1, 0, 0])
v2 = Vector([2, 0, 0])
utils.assert_vectors_almost_equal(vector_ops.cross(v1, v2),
Vector.make_zero(3))
def test_cross_orthogonal(self):
v1 = Vector([0, 1, 0])
v2 = Vector([1, 0, 0])
utils.assert_vectors_almost_equal(vector_ops.cross(v1, v2),
Vector([0, 0, -1]))
def test_cross_self(self):
for v1, v2 in itertools.product(utils.ALL_VECTORS, utils.ALL_VECTORS):
if v1 == v2:
vec = vector_ops.cross(v1, v2)
utils.assert_vectors_almost_equal(vec, Vector.make_zero(3))
def make_random(cls, num_rows: int, num_columns: int):
"""A Matrix built out of random unit row vectors. """
return cls(Vector.make_random(num_columns) for _ in range(num_rows))
def test_dim(self):
components = [3, 2, 1]
vec = Vector(components)
self.assertEqual(len(components), vec.dim)
def make_zero(cls, num_rows: int, num_columns: int):
return cls(Vector.make_zero(num_columns) for _ in range(num_rows))
def test_from_columnvectors(self):
mat = Matrix.from_columnvectors(
[Vector([1, 0]), Vector([0, 1]),
Vector([0, 0])])
self.assertTupleEqual(mat.shape, (2, 3))
def __init__(self, rowvectors: t.Iterable[t.Union[Vector, t.Iterable[t.Union[int, float]]]]):
self._rowvectors = [
Vector(row) if not isinstance(row, Vector) else row for row in rowvectors
]
_validate_vector_dimensions(self._rowvectors)
def make_random(self):
dim = 3
vec = Vector.make_random(dim)
self.assertEqual(vec.norm, 1, PRECISION)
