tick.prox.ProxBinarsity¶

class tick.prox.ProxBinarsity(strength: float, blocks_start, blocks_length, range: tuple = None, positive: bool = False)[source]¶

Proximal operator of binarsity. It is simply a succession of two steps on different intervals: ProxTV plus a centering translation. More precisely, total-variation regularization is applied on a coefficient vector being a concatenation of multiple coefficient vectors corresponding to blocks, followed by centering within sub-blocks. Blocks (non-overlapping) are specified by the blocks_start and blocks_length parameters.

Parameters:

strength : float

Level of total-variation penalization

blocks_start : np.array, shape=(n_blocks,)

First entry of each block

blocks_length : np.array, shape=(n_blocks,)

Size of each block

range : tuple of two int, default=`None`

Range on which the prox is applied. If None then the prox is applied on the whole vector

positive : bool, default=`False`

If True, apply in the end a projection onto the set of vectors with non-negative entries

Attributes:

n_blocks : int

Number of blocks

dtype : {'float64', 'float32'}

Type of the arrays used.

References

ProxBinarsity uses the fast-TV algorithm described in:

Condat, L. (2012). A Direct Algorithm for 1D Total Variation Denoising.

Examples using tick.prox.ProxBinarsity¶