asterism.utils

Submodules

asterism.utils.data module

asterism.utils.data.make_dataset(template='polygons', block_size=10, n_features=100, n_equivocal=0, n_redundant=0, n_repeated=0, topic_sep=10.0, scale=1.0, wiggle=0.0, mix=0.0, return_tensor=False, seed=None)

asterism.utils.plots module

asterism.utils.plots.show_comparison(locs, labels, topics, title1='dataset', title2='predictions', **kwargs)

asterism.utils.plots.show_comparison(locs: Tensor, labels, topics, title1='dataset', title2='predictions', **kwargs)

asterism.utils.plots.show_dataset(locs, labels=None, size=15, fig_size=5, title=None, colormap='Set3', show_ax=False, show_colorbar=False, path=None, return_fig=False)

asterism.utils.sugar module

asterism.utils.sugar.attrmethod(method)

asterism.utils.sugar.attrmethod(prefix: str = '', suffix='')

asterism.utils.sugar.buildmethod(method)

asterism.utils.sugar.buildmethod(*builders: str)

asterism.utils.sugar.checkmethod(method, accept_complex=False, accept_sparse=False, accept_large_sparse=False, dtype='numeric', order=None, ensure_all_finite=True, ensure_2d=True, allow_nd=False, ensure_min_samples=1, ensure_min_features=1, estimator=None, input_name='')

Module contents

asterism.utils.batch_split(x, y, imgs=None, n_test=1)

asterism.utils.batch_split(x: Tensor, y, imgs=None, n_test=1)

asterism.utils.check_data(x, accept_complex=False, accept_sparse=False, accept_large_sparse=False, dtype='numeric', order=None, ensure_all_finite=True, ensure_2d=True, allow_nd=False, ensure_min_samples=2, ensure_min_features=1, estimator=None, input_name='')

asterism.utils.check_data(x: Tensor, accept_complex=False, accept_sparse=False, accept_large_sparse=False, dtype='numeric', order=None, ensure_all_finite=True, ensure_2d=True, allow_nd=False, ensure_min_samples=2, ensure_min_features=1, estimator=None, input_name='')

asterism.utils.fpc(x, n_topics=5, seed=None)

asterism.utils.fpc(x: Tensor, n_topics=5, seed=None)

asterism.utils.fps(x, n_samples=5, seed=None, return_idx=False)

asterism.utils.fps(x: Tensor, n_samples=5, seed=None, return_idx=False)

asterism.utils.get_kwargs(*functions, **kwargs)

asterism.utils.get_methods(cls, prefix='', suffix='', return_callable=False)

asterism.utils.knn2D(x, k=1, loop=True)

asterism.utils.knn2D(x: Tensor, k=1, loop=True)

asterism.utils.log_normalize(x)

asterism.utils.log_normalize(x: Tensor)

asterism.utils.normalize(x)

asterism.utils.pad(x, pad)

asterism.utils.pad(x: Tensor, pad)

asterism.utils.random_state(seed=None, torch_state=False)

asterism.utils.relabel(labels, target=None)

asterism.utils.relabel(labels: Tensor, target=None)

asterism.utils.set_torch_seed(seed, return_state=False)

asterism.utils.set_torch_seed(seed: RandomState, return_state=False)

asterism.utils.shuffle(x, labels=None, sort=False, cut=None, seed=None)

asterism.utils.shuffle(x: Tensor, labels=None, sort=False, cut=None, seed=None)

asterism.utils.to_list(length, *items)

asterism.utils.to_tensor(*items, dtype=torch.float32)

asterism.utils.torch_random_state(seed=None)