Functions and operators

(Proximal) functions and operators.

alpaqa.prox(*args, **kwargs)

Overloaded function.

1. prox(self: alpaqa._alpaqa.float64.functions.NuclearNorm, input: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], output: numpy.ndarray[numpy.float64[m, n], flags.writeable, flags.f_contiguous], γ: float = 1) -> float

C++ documentation: alpaqa::prox Compute the proximal mapping of self at in with step size γ. This version overwrites the given output arguments.

See also

alpaqa.prox_step()

2. prox(self: alpaqa._alpaqa.float64.functions.NuclearNorm, input: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], γ: float = 1) -> Tuple[float, numpy.ndarray[numpy.float64[m, n]]]

C++ documentation: alpaqa::prox Compute the proximal mapping of self at in with step size γ. This version returns the outputs as a tuple.

See also

alpaqa.prox_step()

3. prox(self: alpaqa._alpaqa.float64.functions.L1Norm, input: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], output: numpy.ndarray[numpy.float64[m, n], flags.writeable, flags.f_contiguous], γ: float = 1) -> float

C++ documentation: alpaqa::prox Compute the proximal mapping of self at in with step size γ. This version overwrites the given output arguments.

See also

alpaqa.prox_step()

4. prox(self: alpaqa._alpaqa.float64.functions.L1Norm, input: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], γ: float = 1) -> Tuple[float, numpy.ndarray[numpy.float64[m, n]]]

C++ documentation: alpaqa::prox Compute the proximal mapping of self at in with step size γ. This version returns the outputs as a tuple.

See also

alpaqa.prox_step()

5. prox(self: alpaqa._alpaqa.float64.functions.L1NormElementwise, input: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], output: numpy.ndarray[numpy.float64[m, n], flags.writeable, flags.f_contiguous], γ: float = 1) -> float

C++ documentation: alpaqa::prox Compute the proximal mapping of self at in with step size γ. This version overwrites the given output arguments.

See also

alpaqa.prox_step()

6. prox(self: alpaqa._alpaqa.float64.functions.L1NormElementwise, input: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], γ: float = 1) -> Tuple[float, numpy.ndarray[numpy.float64[m, n]]]

C++ documentation: alpaqa::prox Compute the proximal mapping of self at in with step size γ. This version returns the outputs as a tuple.

See also

alpaqa.prox_step()

7. prox(self: alpaqa._alpaqa.float64.Box, input: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], output: numpy.ndarray[numpy.float64[m, n], flags.writeable, flags.f_contiguous], γ: float = 1) -> float

C++ documentation: alpaqa::prox Compute the proximal mapping of self at in with step size γ. This version overwrites the given output arguments.

See also

alpaqa.prox_step()

8. prox(self: alpaqa._alpaqa.float64.Box, input: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], γ: float = 1) -> Tuple[float, numpy.ndarray[numpy.float64[m, n]]]

C++ documentation: alpaqa::prox Compute the proximal mapping of self at in with step size γ. This version returns the outputs as a tuple.

See also

alpaqa.prox_step()

alpaqa.prox_step(*args, **kwargs)

Overloaded function.

1. prox_step(self: alpaqa._alpaqa.float64.functions.NuclearNorm, input: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], input_step: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], output: numpy.ndarray[numpy.float64[m, n], flags.writeable, flags.f_contiguous], output_step: numpy.ndarray[numpy.float64[m, n], flags.writeable, flags.f_contiguous], γ: float = 1, γ_step: float = -1) -> float

C++ documentation: alpaqa::prox_step Compute a generalized forward-backward step. This version overwrites the given output arguments.

See also

alpaqa.prox()

2. prox_step(self: alpaqa._alpaqa.float64.functions.NuclearNorm, input: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], input_step: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], γ: float = 1, γ_step: float = -1) -> Tuple[float, numpy.ndarray[numpy.float64[m, n]], numpy.ndarray[numpy.float64[m, n]]]

C++ documentation: alpaqa::prox_step Compute a generalized forward-backward step. This version returns the outputs as a tuple.

See also

alpaqa.prox()

3. prox_step(self: alpaqa._alpaqa.float64.functions.L1Norm, input: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], input_step: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], output: numpy.ndarray[numpy.float64[m, n], flags.writeable, flags.f_contiguous], output_step: numpy.ndarray[numpy.float64[m, n], flags.writeable, flags.f_contiguous], γ: float = 1, γ_step: float = -1) -> float

C++ documentation: alpaqa::prox_step Compute a generalized forward-backward step. This version overwrites the given output arguments.

See also

alpaqa.prox()

4. prox_step(self: alpaqa._alpaqa.float64.functions.L1Norm, input: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], input_step: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], γ: float = 1, γ_step: float = -1) -> Tuple[float, numpy.ndarray[numpy.float64[m, n]], numpy.ndarray[numpy.float64[m, n]]]

C++ documentation: alpaqa::prox_step Compute a generalized forward-backward step. This version returns the outputs as a tuple.

See also

alpaqa.prox()

5. prox_step(self: alpaqa._alpaqa.float64.functions.L1NormElementwise, input: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], input_step: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], output: numpy.ndarray[numpy.float64[m, n], flags.writeable, flags.f_contiguous], output_step: numpy.ndarray[numpy.float64[m, n], flags.writeable, flags.f_contiguous], γ: float = 1, γ_step: float = -1) -> float

C++ documentation: alpaqa::prox_step Compute a generalized forward-backward step. This version overwrites the given output arguments.

See also

alpaqa.prox()

6. prox_step(self: alpaqa._alpaqa.float64.functions.L1NormElementwise, input: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], input_step: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], γ: float = 1, γ_step: float = -1) -> Tuple[float, numpy.ndarray[numpy.float64[m, n]], numpy.ndarray[numpy.float64[m, n]]]

C++ documentation: alpaqa::prox_step Compute a generalized forward-backward step. This version returns the outputs as a tuple.

See also

alpaqa.prox()

7. prox_step(self: alpaqa._alpaqa.float64.Box, input: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], input_step: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], output: numpy.ndarray[numpy.float64[m, n], flags.writeable, flags.f_contiguous], output_step: numpy.ndarray[numpy.float64[m, n], flags.writeable, flags.f_contiguous], γ: float = 1, γ_step: float = -1) -> float

C++ documentation: alpaqa::prox_step Compute a generalized forward-backward step. This version overwrites the given output arguments.

See also

alpaqa.prox()

8. prox_step(self: alpaqa._alpaqa.float64.Box, input: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], input_step: numpy.ndarray[numpy.float64[m, n], flags.f_contiguous], γ: float = 1, γ_step: float = -1) -> Tuple[float, numpy.ndarray[numpy.float64[m, n]], numpy.ndarray[numpy.float64[m, n]]]

C++ documentation: alpaqa::prox_step Compute a generalized forward-backward step. This version returns the outputs as a tuple.

See also

alpaqa.prox()