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Change default value of nan_fill_value in PersistenceEntropy to -1 #474

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Sep 2, 2020
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Change default value of nan_fill_value in PersistenceEntropy to -1 #474

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017d761
Change default value of nan_fill_value in PersistenceEntropy to -1
ulupo Sep 2, 2020
367820e
Change -1 to -1. for consistency with docs
ulupo Sep 2, 2020
c3562e7
Linting
ulupo Sep 2, 2020
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12 changes: 7 additions & 5 deletions gtda/diagrams/features.py
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Original file line number Diff line number Diff line change
Expand Up @@ -47,9 +47,10 @@ class PersistenceEntropy(BaseEstimator, TransformerMixin):
Can aid comparison between diagrams in an input collection when these
have different numbers of (non-trivial) points. [1]_

nan_fill_value : float or None, optional, default: ``None``
nan_fill_value : float or None, optional, default: ``-1.``
If a float, (normalized) persistence entropies initially computed as
``numpy.nan`` are replaced with this value.
``numpy.nan`` are replaced with this value. If ``None``, these values
are left as ``numpy.nan``.

n_jobs : int or None, optional, default: ``None``
The number of jobs to use for the computation. ``None`` means 1 unless
Expand Down Expand Up @@ -78,9 +79,10 @@ class PersistenceEntropy(BaseEstimator, TransformerMixin):

_hyperparameters = {
'normalize': {'type': bool},
'nan_fill_value': {'type': (Real, type(None))}}
'nan_fill_value': {'type': (Real, type(None))}
}

def __init__(self, normalize=False, nan_fill_value=None, n_jobs=None):
def __init__(self, normalize=False, nan_fill_value=-1., n_jobs=None):
self.normalize = normalize
self.nan_fill_value = nan_fill_value
self.n_jobs = n_jobs
Expand Down Expand Up @@ -170,7 +172,7 @@ def transform(self, X, y=None):
_subdiagrams(X[s], [dim]),
normalize=self.normalize,
nan_fill_value=self.nan_fill_value
)
)
for dim in self.homology_dimensions_
for s in gen_even_slices(len(X), effective_n_jobs(self.n_jobs))
)
Expand Down
4 changes: 2 additions & 2 deletions gtda/diagrams/tests/test_features_representations.py
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Expand Up @@ -40,7 +40,7 @@ def test_fit_transform_plot_one_hom_dim(transformer, hom_dim_idx):
transformer.fit_transform_plot(
X, sample=0, homology_dimension_idx=hom_dim_idx,
plotly_params=plotly_params
)
)


@pytest.mark.parametrize('transformer',
Expand All @@ -51,7 +51,7 @@ def test_fit_transform_plot_many_hom_dims(transformer, hom_dims):
{"traces": line_plots_traces_params, "layout": layout_params}
transformer.fit_transform_plot(
X, sample=0, homology_dimensions=hom_dims, plotly_params=plotly_params
)
)


@pytest.mark.parametrize('transformer',
Expand Down