tick.prox.ProxMulti

class tick.prox.ProxMulti(proxs: tuple)[source]

Multiple proximal operator. This allows to apply sequentially a list of proximal operators. This is convenient when one wants to apply different proximal operators on different parts of a vector.

Parameters

proxs : tuple of Prox

A tuple of prox operators to be applied successively.

Attributes

dtype : {'float64', 'float32'}

Type of the arrays used.

__init__(proxs: tuple)[source]

Initialize self. See help(type(self)) for accurate signature.

call(coeffs, step=1.0, out=None)

Apply proximal operator on a vector. It computes:

\[argmin_x \big( f(x) + \frac{1}{2} \|x - v\|_2^2 \big)\]
Parameters

coeffs : numpy.ndarray, shape=(n_coeffs,)

Input vector on which is applied the proximal operator

step : float or np.array, default=1.

The amount of penalization is multiplied by this amount

  • If float, the amount of penalization is multiplied by this amount

  • If np.array, then each coordinate of coeffs (within the given range), receives an amount of penalization multiplied by t (available only for separable prox)

out : numpy.ndarray, shape=(n_params,), default=None

If not None, the output is stored in the given out. Otherwise, a new vector is created.

Returns

output : numpy.ndarray, shape=(n_coeffs,)

Same object as out

Notes

step must have the same size as coeffs whenever range is None, or a size matching the one given by the range otherwise

value(coeffs: numpy.ndarray)[source]

Returns the value of the penalization at coeffs. This returns the sum of the values of each prox called on the same coeffs.

Parameters

coeffs : numpy.ndarray, shape=(n_coeffs,)

The value of the penalization is computed at this point

Returns

output : float

Value of the penalization at coeffs

Examples using tick.prox.ProxMulti