Finite Vectorization methods ##############.
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def | __init__ (self, bandwidth=1., weight=lambda x:1, resolution=[20, 20], im_range=[np.nan, np.nan, np.nan, np.nan]) |
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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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Finite Vectorization methods ##############.
This is a class for computing persistence images from a list of persistence diagrams. A persistence image is a 2D function computed from a persistence diagram by convolving the diagram points with a weighted Gaussian kernel. The plane is then discretized into an image with pixels, which is flattened and returned as a vector. See http://jmlr.org/papers/v18/16-337.html for more details.
◆ __init__()
def gudhi.representations.vector_methods.PersistenceImage.__init__ |
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self, |
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bandwidth = 1. , |
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weight = lambda x: 1 , |
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resolution = [20,20] , |
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im_range = [np.nan, np.nan, np.nan, np.nan] |
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Constructor for the PersistenceImage class.
Parameters:
bandwidth (double): bandwidth of the Gaussian kernel (default 1.).
weight (function): weight function for the persistence diagram points (default constant function, ie lambda x: 1). This function must be defined on 2D points, ie lists or numpy arrays of the form [p_x,p_y].
resolution ([int,int]): size (in pixels) of the persistence image (default [20,20]).
im_range ([double,double,double,double]): minimum and maximum of each axis of the persistence image, of the form [x_min, x_max, y_min, y_max] (default [numpy.nan, numpy.nan, numpy.nan, numpyp.nan]). If one of the values is numpy.nan, it can be computed from the persistence diagrams with the fit() method.
◆ __call__()
def gudhi.representations.vector_methods.PersistenceImage.__call__ |
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self, |
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diag |
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Apply PersistenceImage on a single persistence diagram and outputs the result.
Parameters:
diag (n x 2 numpy array): input persistence diagram.
Returns:
numpy array with shape (number of pixels = **resolution[0]** x **resolution[1]**):: output persistence image.
◆ fit()
def gudhi.representations.vector_methods.PersistenceImage.fit |
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self, |
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X, |
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y = None |
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Fit the PersistenceImage class on a list of persistence diagrams: if any of the values in **im_range** is numpy.nan, replace it with the corresponding value computed on the given list of persistence diagrams.
Parameters:
X (list of n x 2 numpy arrays): input persistence diagrams.
y (n x 1 array): persistence diagram labels (unused).
◆ transform()
def gudhi.representations.vector_methods.PersistenceImage.transform |
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self, |
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X |
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Compute the persistence image for each persistence diagram individually and store the results in a single numpy array.
Parameters:
X (list of n x 2 numpy arrays): input persistence diagrams.
Returns:
numpy array with shape (number of diagrams) x (number of pixels = **resolution[0]** x **resolution[1]**): output persistence images.
The documentation for this class was generated from the following file:
- src/python/gudhi/representations/vector_methods.py