class persim.PersImage(*args, **kwargs)[source]

Initialize a persistence image generator.

  • pixels (pair of ints like (int, int)) – Tuple representing number of pixels in return image along x and y axis.

  • spread (float) – Standard deviation of gaussian kernel.

  • specs (dict) –

    Parameters for shape of image with respect to diagram domain. This is used if you would like images to have a particular range. Shaped like:

        "maxBD": float,
        "minBD": float

  • kernel_type (string or ...) – TODO: Implement this feature. Determine which type of kernel used in the convolution, or pass in custom kernel. Currently only implements Gaussian.

  • weighting_type (string or ...) – TODO: Implement this feature. Determine which type of weighting function used, or pass in custom weighting function. Currently only implements linear weighting.

Deprecated since version 0.1.5: Replaced with the class persim.PersistenceImager.

__init__(pixels=(20, 20), spread=None, specs=None, kernel_type='gaussian', weighting_type='linear', verbose=True)[source]


__init__([pixels, spread, specs, ...])

fit_transform(X[, y])

Fit to data, then transform it.


This will return whatever kind of kernel we want to use.

set_output(*[, transform])

Set output container.

show(imgs[, ax])

Visualize the persistence image


Convert a diagram to a landscape (b,d) -> (b, d-b)


Convert diagram or list of diagrams to a persistence image.


Define a weighting function, for stability results to hold, the function must be 0 at y=0.