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def | __init__ (self, use=False, limit=np.inf, point_type="finite") |
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def | fit (self, X, y=None) |
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def | transform (self, X) |
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def | __call__ (self, diag) |
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This is a class for extracting finite or essential points in persistence diagrams.
◆ __init__()
def gudhi.representations.preprocessing.DiagramSelector.__init__ |
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self, |
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use = False , |
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limit = np.inf , |
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point_type = "finite" |
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Constructor for the DiagramSelector class.
Parameters:
use (bool): whether to use the class or not (default False).
limit (double): second coordinate value that is the criterion for being an essential point (default numpy.inf).
point_type (string): either "finite" or "essential". The type of the points that are going to be extracted.
◆ __call__()
def gudhi.representations.preprocessing.DiagramSelector.__call__ |
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self, |
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diag |
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Apply DiagramSelector on a single persistence diagram and outputs the result.
Parameters:
diag (n x 2 numpy array): input persistence diagram.
Returns:
n x 2 numpy array: extracted persistence diagram.
◆ fit()
def gudhi.representations.preprocessing.DiagramSelector.fit |
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self, |
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X, |
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y = None |
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Fit the DiagramSelector class on a list of persistence diagrams (this function actually does nothing but is useful when DiagramSelector is included in a scikit-learn Pipeline).
Parameters:
X (list of n x 2 or n x 1 numpy arrays): input persistence diagrams.
y (n x 1 array): persistence diagram labels (unused).
◆ transform()
def gudhi.representations.preprocessing.DiagramSelector.transform |
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self, |
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X |
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Extract and return the finite or essential points of each persistence diagram individually.
Parameters:
X (list of n x 2 or n x 1 numpy arrays): input persistence diagrams.
Returns:
list of n x 2 or n x 1 numpy arrays: extracted persistence diagrams.
The documentation for this class was generated from the following file:
- src/python/gudhi/representations/preprocessing.py