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-rw-r--r--src/python/doc/cubical_complex_sklearn_itf_ref.rst4
-rw-r--r--src/python/gudhi/tensorflow/cubical_layer.py2
2 files changed, 3 insertions, 3 deletions
diff --git a/src/python/doc/cubical_complex_sklearn_itf_ref.rst b/src/python/doc/cubical_complex_sklearn_itf_ref.rst
index 2fb8ec6a..90ae9ccd 100644
--- a/src/python/doc/cubical_complex_sklearn_itf_ref.rst
+++ b/src/python/doc/cubical_complex_sklearn_itf_ref.rst
@@ -54,9 +54,9 @@ two holes in :math:`\mathbf{H}_1`, or, like in this example, three connected com
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.4, random_state=0)
pipe = Pipeline(
[
- ("cub_pers", CubicalPersistence(homology_dimensions=0, newshape=[28, 28], n_jobs=-2)),
+ ("cub_pers", CubicalPersistence(homology_dimensions=0, newshape=[-1, 28, 28], n_jobs=-2)),
# Or for multiple persistence dimension computation
- # ("cub_pers", CubicalPersistence(homology_dimensions=[0, 1], newshape=[28, 28], n_jobs=-2)),
+ # ("cub_pers", CubicalPersistence(homology_dimensions=[0, 1], newshape=[-1, 28, 28])),
# ("H0_diags", DimensionSelector(index=0), # where index is the index in homology_dimensions array
("finite_diags", DiagramSelector(use=True, point_type="finite")),
(
diff --git a/src/python/gudhi/tensorflow/cubical_layer.py b/src/python/gudhi/tensorflow/cubical_layer.py
index 3304e719..5df2c370 100644
--- a/src/python/gudhi/tensorflow/cubical_layer.py
+++ b/src/python/gudhi/tensorflow/cubical_layer.py
@@ -18,7 +18,7 @@ def _Cubical(Xflat, Xdim, dimensions, homology_coeff_field):
cc = CubicalComplex(dimensions=Xdim[::-1], top_dimensional_cells=Xflat)
cc.compute_persistence(homology_coeff_field=homology_coeff_field)
- # Retrieve and ouput image indices/pixels corresponding to positive and negative simplices
+ # Retrieve and output image indices/pixels corresponding to positive and negative simplices
cof_pp = cc.cofaces_of_persistence_pairs()
L_cofs = []