geomstats.test package#
Submodules#
geomstats.test.conf module#
geomstats.test.data module#
- class geomstats.test.data.TestData[source]#
Bases:
object
Class for TestData objects.
- N_RANDOM_POINTS = [1, 2]#
- N_SHAPE_POINTS = [1, 4]#
- N_TIME_POINTS = [1, 4]#
- N_VEC_REPS = [4]#
- fail_for_autodiff_exceptions = True#
- fail_for_not_implemented_errors = True#
- generate_tests(test_data, marks=())[source]#
Wrap test data with corresponding marks.
- Parameters:
test_data (list or dict)
marks (list) – pytest marks,
- Returns:
data (list or dict) – Tests.
- skip_all = False#
- skip_vec = False#
- skips = ()#
- tolerances = {}#
- trials = 3#
- xfails = ()#
geomstats.test.parametrizers module#
geomstats.test.random module#
- class geomstats.test.random.EmbeddedSpaceRandomDataGenerator(space, amplitude=2.0)[source]#
Bases:
RandomDataGenerator
- class geomstats.test.random.HypersphereIntrinsicRandomDataGenerator(space, amplitude=2.0)[source]#
Bases:
RandomDataGenerator
- class geomstats.test.random.LieGroupVectorRandomDataGenerator(space, amplitude=1.0)[source]#
Bases:
RandomDataGenerator
- class geomstats.test.random.NFoldManifoldRandomDataGenerator(space, amplitude=2.0)[source]#
Bases:
RandomDataGenerator
- class geomstats.test.random.RankKPSDMatricesRandomDataGenerator(space, amplitude=1.0)[source]#
Bases:
RandomDataGenerator
- class geomstats.test.random.ShapeBundleRandomDataGenerator(space, n_discretized_curves=5)[source]#
Bases:
RandomDataGenerator
- class geomstats.test.random.VectorSpaceRandomDataGenerator(space, amplitude=2.0)[source]#
Bases:
RandomDataGenerator
geomstats.test.test_case module#
geomstats.test.utils module#
- class geomstats.test.utils.IdentityPointTransformer[source]#
Bases:
PointTransformer
- class geomstats.test.utils.PointTransformerFromDiffeo(diffeo)[source]#
Bases:
PointTransformer
geomstats.test.vectorization module#
- geomstats.test.vectorization.generate_vectorization_data(data, arg_names, expected_name=None, n_reps=2, vectorization_type='sym')[source]#
Create new data with vectorized version of inputs.
- Parameters:
data (list of dict) – Data. Each to vectorize.
arg_names (list) – Name of inputs to vectorize.
expected_name (str or list of str) – Output name in case it needs to be repeated.
n_reps (int) – Number of times the input points should be repeated.
vectorization_type (str) – Possible values are ‘sym’, ‘basic’, or the format ‘repeat-(int)’ (e.g. “repeat-0-2”). ‘sym’: tests all repetition combinations. ‘basic’: tests only no repetition and repetition of all. ‘repeat-(int)’: tests repetition of provided indices.