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test_vectorization.py
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test_vectorization.py
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"""Unit tests for vectorization functions."""
import tests.helper as helper
import geomstats.backend as gs
import geomstats.tests
import geomstats.vectorization
class TestVectorization(geomstats.tests.TestCase):
def setUp(self):
class Obj:
def __init__(self):
self.default_point_type = 'vector'
@geomstats.vectorization.decorator(['vector', 'vector'])
def func(tangent_vec_a, tangent_vec_b):
result = gs.einsum(
'...i,...i->...i', tangent_vec_a, tangent_vec_b)
result = helper.to_vector(result)
return result
@geomstats.vectorization.decorator(['vector', 'vector'])
def func_scalar_output(tangent_vec_a, tangent_vec_b):
result = gs.einsum(
'...i,...i->...', tangent_vec_a, tangent_vec_b)
result = helper.to_scalar(result)
return result
@geomstats.vectorization.decorator(['vector', 'vector', 'scalar'])
def func_scalar_input_output(tangent_vec_a, tangent_vec_b, in_scalar):
aux = gs.einsum(
'ni,ni->n', tangent_vec_a, tangent_vec_b)
result = gs.einsum('n,nk->n', aux, in_scalar)
result = helper.to_scalar(result)
return result
@geomstats.vectorization.decorator(['vector', 'vector', 'scalar'])
def func_optional_input(tangent_vec_a, tangent_vec_b, in_scalar=None):
if in_scalar is None:
in_scalar = gs.array([[1]])
aux = gs.einsum(
'ni,ni->n', tangent_vec_a, tangent_vec_b)
result = gs.einsum('n,nk->n', aux, in_scalar)
result = helper.to_scalar(result)
return result
@geomstats.vectorization.decorator(
['else', 'vector', 'else', 'vector', 'scalar'])
def func_else(else_a, tangent_vec_a, else_b, tangent_vec_b):
result = (else_a + else_b) * gs.einsum(
'ni,ni->n', tangent_vec_a, tangent_vec_b)
result = helper.to_scalar(result)
return result
@geomstats.vectorization.decorator(['scalar'])
def is_scalar_vectorized(scalar):
is_scalar_vec = gs.ndim(scalar) == 2
has_dim_1 = gs.shape(scalar)[-1] == 1
result = is_scalar_vec and has_dim_1
result = helper.to_scalar(result)
return result
@geomstats.vectorization.decorator(['vector'])
def is_vector_vectorized(vector):
is_vector_vec = gs.ndim(vector) == 2
is_vector_vec = helper.to_scalar(is_vector_vec)
return is_vector_vec
@geomstats.vectorization.decorator(['matrix'])
def is_matrix_vectorized(matrix):
is_matrix_vec = gs.ndim(matrix) == 3
is_matrix_vec = helper.to_scalar(is_matrix_vec)
return is_matrix_vec
@geomstats.vectorization.decorator(
['else', 'point', 'point_type'])
def is_point_type_vector(obj, point, point_type=None):
is_point_type_vector = point_type == 'vector'
is_point_type_vector = helper.to_scalar(is_point_type_vector)
return is_point_type_vector
@geomstats.vectorization.decorator(
['else', 'point', 'point_type'])
def is_point_type_matrix(obj, point, point_type=None):
is_point_type_matrix = point_type == 'matrix'
is_point_type_matrix = helper.to_scalar(is_point_type_matrix)
return is_point_type_matrix
@geomstats.vectorization.decorator(
['else', 'point', 'point_type'])
def is_vector_vectorized_with_point_type(obj, point, point_type=None):
is_vector_vec = gs.ndim(point) == 2
is_vector_vec = helper.to_scalar(is_vector_vec)
return is_vector_vec
@geomstats.vectorization.decorator(
['else', 'point', 'point_type'])
def is_matrix_vectorized_with_point_type(obj, point, point_type=None):
is_matrix_vec = gs.ndim(point) == 3
is_matrix_vec = helper.to_scalar(is_matrix_vec)
return is_matrix_vec
@geomstats.vectorization.decorator(
['else', 'point', 'point_type', 'output_point'])
def output_1d_vector(obj, point, point_type=None):
n_samples = point.shape[0]
result = gs.array([[5.]] * n_samples)
return result
self.func = func
self.func_scalar_output = func_scalar_output
self.func_scalar_input_output = func_scalar_input_output
self.func_optional_input = func_optional_input
self.func_else = func_else
self.is_scalar_vectorized = is_scalar_vectorized
self.is_vector_vectorized = is_vector_vectorized
self.is_matrix_vectorized = is_matrix_vectorized
self.is_point_type_vector = is_point_type_vector
self.is_point_type_matrix = is_point_type_matrix
self.is_vector_vectorized_with_point_type = \
is_vector_vectorized_with_point_type
self.is_matrix_vectorized_with_point_type = \
is_matrix_vectorized_with_point_type
self.output_1d_vector = output_1d_vector
self.obj = Obj()
def test_decorator_with_squeeze_dim0(self):
vec_a = gs.array([1, 2, 3])
vec_b = gs.array([0, 1, 0])
result = self.func(vec_a, vec_b)
expected = gs.array([0, 2, 0])
self.assertAllClose(result.shape, expected.shape)
self.assertAllClose(result, expected)
def test_decorator_with_squeeze_dim0_with_kwargs(self):
vec_a = gs.array([1, 2, 3])
vec_b = gs.array([0, 1, 0])
result = self.func(tangent_vec_a=vec_a, tangent_vec_b=vec_b)
expected = gs.array([0, 2, 0])
self.assertAllClose(result.shape, expected.shape)
self.assertAllClose(result, expected)
def test_decorator_without_squeeze_dim0(self):
vec_a = gs.array([[1, 2, 3]])
vec_b = gs.array([0, 1, 0])
result = self.func(vec_a, vec_b)
expected = gs.array([[0, 2, 0]])
self.assertAllClose(result.shape, expected.shape)
self.assertAllClose(result, expected)
def test_decorator_without_squeeze_dim0_with_kwargs(self):
vec_a = gs.array([[1, 2, 3]])
vec_b = gs.array([0, 1, 0])
result = self.func(tangent_vec_a=vec_a, tangent_vec_b=vec_b)
expected = gs.array([[0, 2, 0]])
self.assertAllClose(result.shape, expected.shape)
self.assertAllClose(result, expected)
def test_decorator_vectorization(self):
vec_a = gs.array([[1, 2, 3], [1, 2, 3]])
vec_b = gs.array([0, 1, 0])
result = self.func(vec_a, vec_b)
expected = gs.array([[0, 2, 0], [0, 2, 0]])
self.assertAllClose(result.shape, expected.shape)
self.assertAllClose(result, expected)
def test_decorator_vectorization_with_kwargs(self):
vec_a = gs.array([[1, 2, 3], [1, 2, 3]])
vec_b = gs.array([0, 1, 0])
result = self.func(tangent_vec_a=vec_a, tangent_vec_b=vec_b)
expected = gs.array([[0, 2, 0], [0, 2, 0]])
self.assertAllClose(result.shape, expected.shape)
self.assertAllClose(result, expected)
def test_decorator_scalar_with_squeeze_dim1(self):
vec_a = gs.array([1, 2, 3])
vec_b = gs.array([0, 1, 0])
result = self.func_scalar_output(vec_a, vec_b)
expected = 2
self.assertAllClose(result, expected)
def test_decorator_scalar_with_squeeze_dim1_with_kwargs(self):
vec_a = gs.array([1, 2, 3])
vec_b = gs.array([0, 1, 0])
result = self.func_scalar_output(
tangent_vec_a=vec_a, tangent_vec_b=vec_b)
expected = 2
self.assertAllClose(result, expected)
def test_decorator_scalar_without_squeeze_dim1(self):
vec_a = gs.array([1, 2, 3])
vec_b = gs.array([0, 1, 0])
scalar = 4
result = self.func_scalar_input_output(vec_a, vec_b, scalar)
expected = 8
self.assertAllClose(result, expected)
def test_decorator_scalar_without_squeeze_dim1_with_kwargs(self):
vec_a = gs.array([1, 2, 3])
vec_b = gs.array([0, 1, 0])
scalar = 4
result = self.func_scalar_input_output(
tangent_vec_a=vec_a, tangent_vec_b=vec_b, in_scalar=scalar)
expected = 8
self.assertAllClose(result, expected)
def test_decorator_scalar_output_vectorization(self):
vec_a = gs.array([[1, 2, 3], [1, 2, 3]])
vec_b = gs.array([0, 1, 0])
result = self.func_scalar_output(vec_a, vec_b)
expected = gs.array([2, 2])
self.assertAllClose(result.shape, expected.shape)
self.assertAllClose(result, expected)
def test_decorator_scalar_output_vectorization_with_kwargs(self):
vec_a = gs.array([[1, 2, 3], [1, 2, 3]])
vec_b = gs.array([0, 1, 0])
result = self.func_scalar_output(
tangent_vec_a=vec_a, tangent_vec_b=vec_b)
expected = gs.array([2, 2])
self.assertAllClose(result.shape, expected.shape)
self.assertAllClose(result, expected)
def test_decorator_optional_input(self):
vec_a = gs.array([1, 2, 3])
vec_b = gs.array([0, 1, 0])
result = self.func_optional_input(vec_a, vec_b)
expected = 2
self.assertAllClose(result, expected)
def test_decorator_optional_input_with_kwargs(self):
vec_a = gs.array([1, 2, 3])
vec_b = gs.array([0, 1, 0])
result = self.func_optional_input(
tangent_vec_a=vec_a, tangent_vec_b=vec_b, in_scalar=3)
expected = 6
self.assertAllClose(result, expected)
def test_decorator_optional_input_with_optional_kwargs(self):
vec_a = gs.array([1, 2, 3])
vec_b = gs.array([0, 1, 0])
result = self.func_optional_input(
tangent_vec_a=vec_a, tangent_vec_b=vec_b)
expected = 2
self.assertAllClose(result, expected)
def test_decorator_else(self):
vec_a = gs.array([1, 2, 3])
vec_b = gs.array([0, 1, 0])
else_a = 1
else_b = 1
result = self.func_else(else_a, vec_a, else_b, vec_b)
expected = 4
self.assertAllClose(result, expected)
def test_decorator_else_with_kwargs(self):
vec_a = gs.array([1, 2, 3])
vec_b = gs.array([0, 1, 0])
else_a = 1
else_b = 1
result = self.func_else(
else_a=else_a, tangent_vec_a=vec_a,
else_b=else_b, tangent_vec_b=vec_b)
expected = 4
self.assertAllClose(result, expected)
def test_is_scalar_vectorized(self):
scalar = 1.3
result = self.is_scalar_vectorized(scalar)
expected = True
self.assertAllClose(result, expected)
def test_is_scalar_vectorized_with_kwargs(self):
scalar = 1.3
result = self.is_scalar_vectorized(scalar=scalar)
expected = True
self.assertAllClose(result, expected)
def test_is_vector_vectorized(self):
vector = gs.array([1.3, 3.3])
result = self.is_vector_vectorized(vector)
expected = True
self.assertAllClose(result, expected)
def test_is_vector_vectorizedi_with_kwargs(self):
vector = gs.array([1.3, 3.3])
result = self.is_vector_vectorized(vector=vector)
expected = True
self.assertAllClose(result, expected)
def test_is_matrix_vectorized(self):
matrix = gs.array([[1.3, 3.3], [1.2, 3.1]])
result = self.is_matrix_vectorized(matrix)
expected = True
self.assertAllClose(result, expected)
def test_is_matrix_vectorized_with_kwargs(self):
matrix = gs.array([[1.3, 3.3], [1.2, 3.1]])
result = self.is_matrix_vectorized(matrix=matrix)
expected = True
self.assertAllClose(result, expected)
def test_vectorize_args(self):
point_types = ['scalar']
args = (1.3,)
result = geomstats.vectorization.vectorize_args(point_types, args)
expected = (gs.array([[1.3]]),)
self.assertAllClose(result, expected)
def test_vectorize_kwargs(self):
point_types = ['scalar']
kwargs = {'scalar_name': 1.3}
result_dict = geomstats.vectorization.vectorize_kwargs(
point_types, kwargs)
expected_dict = {'scalar_name': gs.array([[1.3]])}
keys = expected_dict.keys()
result = gs.array([result_dict[key] for key in keys])
expected = gs.array([expected_dict[key] for key in keys])
self.assertAllClose(result, expected)
def test_is_point_type_vector(self):
point = gs.array([1., 2., 3.])
result = self.is_point_type_vector(
self.obj, point, point_type='vector')
expected = True
self.assertAllClose(result, expected)
def test_is_point_type_vector_optional(self):
point = gs.array([1., 2., 3.])
result = self.is_point_type_vector(
self.obj, point)
expected = True
self.assertAllClose(result, expected)
def test_is_point_type_matrix(self):
point = gs.array([[1., 2., 3.], [2., 3., 4.]])
result = self.is_point_type_matrix(
self.obj, point, point_type='matrix')
expected = True
self.assertAllClose(result, expected)
def test_is_vector_vectorized_with_point_type(self):
vector = gs.array([1.3, 3.3])
result = self.is_vector_vectorized_with_point_type(
self.obj, point=vector, point_type='vector')
expected = True
self.assertAllClose(result, expected)
def test_is_vector_vectorized_with_optional_point_type(self):
vector = gs.array([1.3, 3.3])
result = self.is_vector_vectorized_with_point_type(
self.obj, point=vector)
expected = True
self.assertAllClose(result, expected)
def test_is_matrix_vectorized_with_point_type(self):
matrix = gs.array([[1.3, 3.3], [1.2, 3.1]])
result = self.is_matrix_vectorized_with_point_type(
self.obj, matrix, point_type='matrix')
expected = True
self.assertAllClose(result, expected)
def test_output_single_1d_vector(self):
point = gs.array([1., 2., 3.])
result = self.output_1d_vector(
self.obj, point)
expected = gs.array([5.])
self.assertAllClose(result, expected)
def test_output_multiple_1d_vector(self):
point = gs.array([[1., 2., 3.], [2., 3., 4.]])
result = self.output_1d_vector(
self.obj, point)
expected = gs.array([[5.], [5.]])
self.assertAllClose(result, expected)