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author | ROUVREAU Vincent <vincent.rouvreau@inria.fr> | 2021-05-25 21:29:12 +0200 |
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committer | ROUVREAU Vincent <vincent.rouvreau@inria.fr> | 2021-05-25 21:29:12 +0200 |
commit | 8859128da7386955b00658ff5d71659a5de08c46 (patch) | |
tree | 35080d0755a3c6d35b6718e460e0f1a2a2ef9f53 /src/python/gudhi/sklearn | |
parent | bcb317bf2dada68dfff02dd6a3fc53c0c70741d6 (diff) |
First version of CubicalPersistence
Diffstat (limited to 'src/python/gudhi/sklearn')
-rw-r--r-- | src/python/gudhi/sklearn/__init__.py | 0 | ||||
-rw-r--r-- | src/python/gudhi/sklearn/cubical_persistence.py | 64 |
2 files changed, 64 insertions, 0 deletions
diff --git a/src/python/gudhi/sklearn/__init__.py b/src/python/gudhi/sklearn/__init__.py new file mode 100644 index 00000000..e69de29b --- /dev/null +++ b/src/python/gudhi/sklearn/__init__.py diff --git a/src/python/gudhi/sklearn/cubical_persistence.py b/src/python/gudhi/sklearn/cubical_persistence.py new file mode 100644 index 00000000..a58fa77c --- /dev/null +++ b/src/python/gudhi/sklearn/cubical_persistence.py @@ -0,0 +1,64 @@ +from .. import CubicalComplex +from sklearn.base import TransformerMixin + +class CubicalPersistence(TransformerMixin): + # Fast way to find primes and should be enough + available_primes_ = [2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97] + """ + This is a class for computing the persistence diagrams from a cubical complex. + """ + def __init__(self, dimensions=None, persistence_dim=0, min_persistence=0): + """ + Constructor for the CubicalPersistence class. + + Parameters: + dimensions (list of int): A list of number of top dimensional cells. + persistence_dim (int): The returned persistence diagrams dimension. Default value is `0`. + min_persistence (float): The minimum persistence value to take into account (strictly greater than + `min_persistence`). Default value is `0.0`. Sets `min_persistence` to `-1.0` to see all values. + """ + self.dimensions_ = dimensions + self.persistence_dim_ = persistence_dim + + self.homology_coeff_field_ = None + for dim in self.available_primes_: + if dim > persistence_dim + 1: + self.homology_coeff_field_ = dim + break + if self.homology_coeff_field_ == None: + raise ValueError("persistence_dim must be less than 96") + + self.min_persistence_ = min_persistence + + def transform(self, X): + """ + Compute all the cubical complexes and their persistence diagrams. + + Parameters: + X (list of double OR numpy.ndarray): Cells filtration values. + + Returns: + Persistence diagrams + """ + cubical_complex = CubicalComplex(top_dimensional_cells = X, + dimensions = self.dimensions_) + cubical_complex.compute_persistence(homology_coeff_field = self.homology_coeff_field_, + min_persistence = self.min_persistence_) + self.diagrams_ = cubical_complex.persistence_intervals_in_dimension(self.persistence_dim_) + if self.persistence_dim_ == 0: + # return all but the last, always [ 0., inf] + self.diagrams_ = self.diagrams_[:-1] + return self.diagrams_ + + def fit_transform(self, X): + """ + Compute all the cubical complexes and their persistence diagrams. + + Parameters: + X (list of double OR numpy.ndarray): Cells filtration values. + + Returns: + Persistence diagrams + """ + self.transform(X) + return self.diagrams_ |