import numpy as np
from struct import pack
from scipy.sparse import coo_array
import pytest
from opengauss_sqlalchemy.utils import Bit, Vector, SparseVector
class TestBit:
def test_list(self):
assert Bit([True, False, True]).to_list() == [True, False, True]
def test_tuple(self):
assert Bit((True, False, True)).to_list() == [True, False, True]
def test_str(self):
assert Bit('101').to_list() == [True, False, True]
def test_ndarray_uint8(self):
arr = np.array([254, 7, 0], dtype=np.uint8)
assert Bit(arr).to_text() == '111111100000011100000000'
def test_ndarray_uint16(self):
arr = np.array([254, 7, 0], dtype=np.uint16)
with pytest.raises(ValueError) as error:
Bit(arr)
assert str(error.value) == 'expected dtype to be bool or uint8'
def test_ndarray_same_object(self):
arr = np.array([True, False, True])
assert Bit(arr).to_list() == [True, False, True]
assert Bit(arr).to_numpy() is arr
def test_ndim_two(self):
with pytest.raises(ValueError) as error:
Bit([[True, False], [True, False]])
assert str(error.value) == 'expected ndim to be 1'
def test_ndim_zero(self):
with pytest.raises(ValueError) as error:
Bit(True)
assert str(error.value) == 'expected ndim to be 1'
def test_repr(self):
assert repr(Bit([True, False, True])) == 'Bit(101)'
assert str(Bit([True, False, True])) == 'Bit(101)'
def test_equality(self):
assert Bit([True, False, True]) == Bit([True, False, True])
assert Bit([True, False, True]) != Bit([True, False, False])
class TestSparseVector:
def test_list(self):
vec = SparseVector([1, 0, 2, 0, 3, 0])
assert vec.to_list() == [1, 0, 2, 0, 3, 0]
assert np.array_equal(vec.to_numpy(), [1, 0, 2, 0, 3, 0])
assert vec.indices() == [0, 2, 4]
def test_list_dimensions(self):
with pytest.raises(ValueError) as error:
SparseVector([1, 0, 2, 0, 3, 0], 6)
assert str(error.value) == 'extra argument'
def test_ndarray(self):
vec = SparseVector(np.array([1, 0, 2, 0, 3, 0]))
assert vec.to_list() == [1, 0, 2, 0, 3, 0]
assert vec.indices() == [0, 2, 4]
def test_dict(self):
vec = SparseVector({2: 2, 4: 3, 0: 1, 3: 0}, 6)
assert vec.to_list() == [1, 0, 2, 0, 3, 0]
assert vec.indices() == [0, 2, 4]
def test_dict_no_dimensions(self):
with pytest.raises(ValueError) as error:
SparseVector({0: 1, 2: 2, 4: 3})
assert str(error.value) == 'missing dimensions'
def test_coo_array(self):
arr = coo_array(np.array([1, 0, 2, 0, 3, 0]))
vec = SparseVector(arr)
assert vec.to_list() == [1, 0, 2, 0, 3, 0]
assert vec.indices() == [0, 2, 4]
def test_coo_array_dimensions(self):
with pytest.raises(ValueError) as error:
SparseVector(coo_array(np.array([1, 0, 2, 0, 3, 0])), 6)
assert str(error.value) == 'extra argument'
def test_dok_array(self):
arr = coo_array(np.array([1, 0, 2, 0, 3, 0])).todok()
vec = SparseVector(arr)
assert vec.to_list() == [1, 0, 2, 0, 3, 0]
assert vec.indices() == [0, 2, 4]
def test_repr(self):
assert repr(SparseVector([1, 0, 2, 0, 3, 0])) == 'SparseVector({0: 1.0, 2: 2.0, 4: 3.0}, 6)'
assert str(SparseVector([1, 0, 2, 0, 3, 0])) == 'SparseVector({0: 1.0, 2: 2.0, 4: 3.0}, 6)'
def test_equality(self):
assert SparseVector([1, 0, 2, 0, 3, 0]) == SparseVector([1, 0, 2, 0, 3, 0])
assert SparseVector([1, 0, 2, 0, 3, 0]) != SparseVector([1, 0, 2, 0, 3, 1])
assert SparseVector([1, 0, 2, 0, 3, 0]) == SparseVector({2: 2, 4: 3, 0: 1, 3: 0}, 6)
assert SparseVector({}, 1) != SparseVector({}, 2)
def test_dimensions(self):
assert SparseVector([1, 0, 2, 0, 3, 0]).dimensions() == 6
def test_indices(self):
assert SparseVector([1, 0, 2, 0, 3, 0]).indices() == [0, 2, 4]
def test_values(self):
assert SparseVector([1, 0, 2, 0, 3, 0]).values() == [1, 2, 3]
def test_to_coo(self):
assert np.array_equal(SparseVector([1, 0, 2, 0, 3, 0]).to_coo().toarray(), [[1, 0, 2, 0, 3, 0]])
def test_zero_vector_text(self):
vec = SparseVector({}, 3)
assert vec.to_list() == SparseVector.from_text(vec.to_text()).to_list()
def test_from_text(self):
vec = SparseVector.from_text('{1:1.5,3:2,5:3}/6')
assert vec.dimensions() == 6
assert vec.indices() == [0, 2, 4]
assert vec.values() == [1.5, 2, 3]
assert vec.to_list() == [1.5, 0, 2, 0, 3, 0]
assert np.array_equal(vec.to_numpy(), [1.5, 0, 2, 0, 3, 0])
def test_from_binary(self):
data = pack('>iii3i3f', 6, 3, 0, 0, 2, 4, 1.5, 2, 3)
vec = SparseVector.from_binary(data)
assert vec.dimensions() == 6
assert vec.indices() == [0, 2, 4]
assert vec.values() == [1.5, 2, 3]
assert vec.to_list() == [1.5, 0, 2, 0, 3, 0]
assert np.array_equal(vec.to_numpy(), [1.5, 0, 2, 0, 3, 0])
assert vec.to_binary() == data
class TestVector:
def test_list(self):
assert Vector([1, 2, 3]).to_list() == [1, 2, 3]
def test_list_str(self):
with pytest.raises(ValueError, match='could not convert string to float'):
Vector([1, 'two', 3])
def test_tuple(self):
assert Vector((1, 2, 3)).to_list() == [1, 2, 3]
def test_ndarray(self):
arr = np.array([1, 2, 3])
assert Vector(arr).to_list() == [1, 2, 3]
assert Vector(arr).to_numpy() is not arr
def test_ndarray_same_object(self):
arr = np.array([1, 2, 3], dtype='>f4')
assert Vector(arr).to_list() == [1, 2, 3]
assert Vector(arr).to_numpy() is arr
def test_ndim_two(self):
with pytest.raises(ValueError) as error:
Vector([[1, 2], [3, 4]])
assert str(error.value) == 'expected ndim to be 1'
def test_ndim_zero(self):
with pytest.raises(ValueError) as error:
Vector(1)
assert str(error.value) == 'expected ndim to be 1'
def test_repr(self):
assert repr(Vector([1, 2, 3])) == 'Vector([1.0, 2.0, 3.0])'
assert str(Vector([1, 2, 3])) == 'Vector([1.0, 2.0, 3.0])'
def test_equality(self):
assert Vector([1, 2, 3]) == Vector([1, 2, 3])
assert Vector([1, 2, 3]) != Vector([1, 2, 4])
def test_dimensions(self):
assert Vector([1, 2, 3]).dimensions() == 3
def test_from_text(self):
vec = Vector.from_text('[1.5,2,3]')
assert vec.to_list() == [1.5, 2, 3]
assert np.array_equal(vec.to_numpy(), [1.5, 2, 3])
def test_from_binary(self):
data = pack('>HH3f', 3, 0, 1.5, 2, 3)
vec = Vector.from_binary(data)
assert vec.to_list() == [1.5, 2, 3]
assert np.array_equal(vec.to_numpy(), [1.5, 2, 3])
assert vec.to_binary() == data