diff options
Diffstat (limited to 'src/python/gudhi/sklearn/cubical_persistence.py')
| -rw-r--r-- | src/python/gudhi/sklearn/cubical_persistence.py | 14 |
1 files changed, 7 insertions, 7 deletions
diff --git a/src/python/gudhi/sklearn/cubical_persistence.py b/src/python/gudhi/sklearn/cubical_persistence.py index 3997bc8a..ed56d2dd 100644 --- a/src/python/gudhi/sklearn/cubical_persistence.py +++ b/src/python/gudhi/sklearn/cubical_persistence.py @@ -32,7 +32,7 @@ class CubicalPersistence(BaseEstimator, TransformerMixin): def __init__( self, - dimensions=None, + newshape=None, persistence_dimension=-1, homology_coeff_field=11, min_persistence=0.0, @@ -42,7 +42,7 @@ class CubicalPersistence(BaseEstimator, TransformerMixin): Constructor for the CubicalPersistence class. Parameters: - dimensions (list of int): A list of number of top dimensional cells if cells filtration values will require + newshape (list of int): A list of number of top dimensional cells if cells filtration values will require to be reshaped (cf. :func:`~gudhi.sklearn.cubical_persistence.CubicalPersistence.transform`) persistence_dimension (int or list of int): The returned persistence diagrams dimension(s). Short circuit the use of :class:`~gudhi.representations.preprocessing.DimensionSelector` when only one @@ -52,7 +52,7 @@ class CubicalPersistence(BaseEstimator, TransformerMixin): `min_persistence`). Default value is `0.0`. Set `min_persistence` to `-1.0` to see all values. n_jobs (int): cf. https://joblib.readthedocs.io/en/latest/generated/joblib.Parallel.html """ - self.dimensions = dimensions + self.newshape = newshape self.persistence_dimension = persistence_dimension self.homology_coeff_field = homology_coeff_field self.min_persistence = min_persistence @@ -65,7 +65,7 @@ class CubicalPersistence(BaseEstimator, TransformerMixin): return self def __transform(self, cells): - cubical_complex = CubicalComplex(top_dimensional_cells=cells, dimensions=self.dimensions) + cubical_complex = CubicalComplex(top_dimensional_cells=cells, dimensions=self.newshape) cubical_complex.compute_persistence( homology_coeff_field=self.homology_coeff_field, min_persistence=self.min_persistence ) @@ -74,7 +74,7 @@ class CubicalPersistence(BaseEstimator, TransformerMixin): ] def __transform_only_this_dim(self, cells): - cubical_complex = CubicalComplex(top_dimensional_cells=cells, dimensions=self.dimensions) + cubical_complex = CubicalComplex(top_dimensional_cells=cells, dimensions=self.newshape) cubical_complex.compute_persistence( homology_coeff_field=self.homology_coeff_field, min_persistence=self.min_persistence ) @@ -83,8 +83,8 @@ class CubicalPersistence(BaseEstimator, TransformerMixin): def transform(self, X, Y=None): """Compute all the cubical complexes and their associated persistence diagrams. - :param X: List of cells filtration values that should be flatten if `dimensions` is set in the constructor, or - already with the correct shape in a numpy.ndarray (and `dimensions` must not be set). + :param X: List of cells filtration values that should be flatten if `newshape` is set in the constructor, or + already with the correct shape in a numpy.ndarray (and `newshape` must not be set). :type X: list of list of float OR list of numpy.ndarray :return: Persistence diagrams in the format: |