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Doc: fixed equation in rMS #249

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1 change: 1 addition & 0 deletions .gitignore
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Expand Up @@ -21,6 +21,7 @@ pyproximal.egg-info/
pyproximal/version.py

# Development #
.codacy
.vscode
.ipynb_checkpoints/
notebooks
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4 changes: 2 additions & 2 deletions pyproximal/optimization/primaldual.py
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Expand Up @@ -64,10 +64,10 @@ def PrimalDual(
Linear operator of g
x0 : :obj:`numpy.ndarray`
Initial vector
tau : :obj:`float` or :obj:`np.ndarray`
tau : :obj:`float` or :obj:`numpy.ndarray`
Stepsize of subgradient of :math:`f`. This can be constant
or function of iterations (in the latter cases provided as np.ndarray)
mu : :obj:`float` or :obj:`np.ndarray`
mu : :obj:`float` or :obj:`numpy.ndarray`
Stepsize of subgradient of :math:`g^*`. This can be constant
or function of iterations (in the latter cases provided as np.ndarray)
y0 : :obj:`numpy.ndarray`
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2 changes: 1 addition & 1 deletion pyproximal/optimization/segmentation.py
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Expand Up @@ -29,7 +29,7 @@ def Segment(

Parameters
----------
y : :obj:`np.ndarray`
y : :obj:`numpy.ndarray`
Image to segment (must have 2 or more dimensions)
cl : :obj:`numpy.ndarray`
Classes
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4 changes: 2 additions & 2 deletions pyproximal/optimization/sr3.py
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Expand Up @@ -41,15 +41,15 @@ def _lsqr(
Data
iter_lim: :obj:`int`
Maximum number of iterations
z_old: :obj:`np.ndarray`
z_old: :obj:`numpy.ndarray`
The previous outer iteration
x0: :obj:`numpy.ndarray`
initial guess
kappa: :obj:`float`
The regularization parameter for the inner iteration
eps: :obj:`float`
The regularization parameter for the outer iteration
Reg: :obj:`np.ndarray`
Reg: :obj:`numpy.ndarray`
The regularization operator L

Returns
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12 changes: 6 additions & 6 deletions pyproximal/projection/Box.py
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Expand Up @@ -8,9 +8,9 @@ class BoxProj:

Parameters
----------
lower : :obj:`float` or :obj:`np.ndarray`, optional
lower : :obj:`float` or :obj:`numpy.ndarray`, optional
Lower bound
upper : :obj:`float` or :obj:`np.ndarray`, optional
upper : :obj:`float` or :obj:`numpy.ndarray`, optional
Upper bound

Notes
Expand Down Expand Up @@ -56,13 +56,13 @@ class HyperPlaneBoxProj:

Parameters
----------
coeffs : :obj:`np.ndarray`
coeffs : :obj:`numpy.ndarray`
Vector of coefficients used in the definition of the hyperplane
scalar : :obj:`float`
Scalar used in the definition of the hyperplane
lower : :obj:`float` or :obj:`np.ndarray`, optional
lower : :obj:`float` or :obj:`numpy.ndarray`, optional
Lower bound of Box
upper : :obj:`float` or :obj:`np.ndarray`, optional
upper : :obj:`float` or :obj:`numpy.ndarray`, optional
Upper bound of Box
maxiter : :obj:`int`, optional
Maximum number of iterations used by :func:`scipy.optimize.bisect`
Expand Down Expand Up @@ -123,7 +123,7 @@ def __call__(self, x: NDArray) -> NDArray:

Parameters
----------
x : :obj:`np.ndarray`
x : :obj:`numpy.ndarray`
Vector

"""
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2 changes: 1 addition & 1 deletion pyproximal/projection/Euclidean.py
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Expand Up @@ -7,7 +7,7 @@ class EuclideanBallProj:

Parameters
----------
center : :obj:`np.ndarray` or :obj:`float`
center : :obj:`numpy.ndarray` or :obj:`float`
Center of the ball
radius : :obj:`float`
Radius
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2 changes: 1 addition & 1 deletion pyproximal/projection/Intersection.py
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Expand Up @@ -11,7 +11,7 @@ class IntersectionProj:
Size of vector to be projected
n : :obj:`int`
Number of vectors to be projected simultaneously
sigma : :obj:`np.ndarray`
sigma : :obj:`numpy.ndarray`
Matrix of distances of size :math:`k \times k`
niter : :obj:`int`, optional
Number of iterations
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2 changes: 1 addition & 1 deletion pyproximal/projection/Simplex.py
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Expand Up @@ -45,7 +45,7 @@ def __call__(self, x: NDArray) -> NDArray:

Parameters
----------
x : :obj:`np.ndarray`
x : :obj:`numpy.ndarray`
Vector
maxiter : :obj:`int`, optional
Maximum number of iterations used by :func:`scipy.optimize.bisect`
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4 changes: 2 additions & 2 deletions pyproximal/proximal/Box.py
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Expand Up @@ -12,9 +12,9 @@ class Box(ProxOperator):

Parameters
----------
lower : :obj:`float` or :obj:`np.ndarray`, optional
lower : :obj:`float` or :obj:`numpy.ndarray`, optional
Lower bound
upper : :obj:`float` or :obj:`np.ndarray`, optional
upper : :obj:`float` or :obj:`numpy.ndarray`, optional
Upper bound

Notes
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2 changes: 1 addition & 1 deletion pyproximal/proximal/Euclidean.py
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Expand Up @@ -70,7 +70,7 @@ class EuclideanBall(ProxOperator):

Parameters
----------
center : :obj:`np.ndarray` or :obj:`float`
center : :obj:`numpy.ndarray` or :obj:`float`
Center of the ball
radius : :obj:`float`
Radius
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2 changes: 1 addition & 1 deletion pyproximal/proximal/Intersection.py
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Expand Up @@ -14,7 +14,7 @@ class Intersection(ProxOperator):
Size of vector to be projected
n : :obj:`int`
Number of vectors to be projected simultaneously
sigma : :obj:`np.ndarray` or :obj:`float`
sigma : :obj:`numpy.ndarray` or :obj:`float`
Matrix of distances of size :math:`k \times k` (or single value in the
case of constant matrix)
niter : :obj:`int`, optional
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2 changes: 1 addition & 1 deletion pyproximal/proximal/L0.py
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Expand Up @@ -58,7 +58,7 @@ class L0(ProxOperator):

Parameters
----------
sigma : :obj:`float` or :obj:`np.ndarray` or :obj:`func`, optional
sigma : :obj:`float` or :obj:`numpy.ndarray` or :obj:`func`, optional
Multiplicative coefficient of L0 norm. This can be a constant number, a list
of values (for multidimensional inputs, acting on the second dimension) or
a function that is called passing a counter which keeps track of how many
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4 changes: 2 additions & 2 deletions pyproximal/proximal/L1.py
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Expand Up @@ -60,13 +60,13 @@ class L1(ProxOperator):

Parameters
----------
sigma : :obj:`float` or :obj:`np.ndarray` or :obj:`func`, optional
sigma : :obj:`float` or :obj:`numpy.ndarray` or :obj:`func`, optional
Multiplicative coefficient of L1 norm. This can be a constant number, a list
of values (for 2-dimensional inputs, acting on the second dimension) or
a function that is called passing a counter which keeps track of how many
times the ``prox`` method has been invoked before and returns a scalar (or a list of)
``sigma`` to be used.
g : :obj:`np.ndarray`, optional
g : :obj:`numpy.ndarray`, optional
Vector to be subtracted

Notes
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4 changes: 2 additions & 2 deletions pyproximal/proximal/L2.py
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Expand Up @@ -48,7 +48,7 @@ class L2(ProxOperator):
This can be a constant number or a function that is called passing a
counter which keeps track of how many times the ``prox`` method has
been invoked before and returns the ``niter`` to be used.
x0 : :obj:`np.ndarray`, optional
x0 : :obj:`numpy.ndarray`, optional
Initial vector
warm : :obj:`bool`, optional
Warm start (``True``) or not (``False``). Uses estimate from previous
Expand Down Expand Up @@ -316,7 +316,7 @@ class L2Convolve(ProxOperator):

Parameters
----------
h : :obj:`np.ndarray`
h : :obj:`numpy.ndarray`
Kernel of convolution operator
b : :obj:`numpy.ndarray`
Data vector
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2 changes: 1 addition & 1 deletion pyproximal/proximal/Nonlinear.py
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Expand Up @@ -29,7 +29,7 @@ class Nonlinear(ABC, ProxOperator):

Parameters
----------
x0 : :obj:`np.ndarray`
x0 : :obj:`numpy.ndarray`
Initial vector
niter : :obj:`int`, optional
Number of iterations of iterative scheme used to compute the proximal
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2 changes: 1 addition & 1 deletion pyproximal/proximal/Orthogonal.py
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Expand Up @@ -25,7 +25,7 @@ class Orthogonal(ProxOperator):
Orthogonal operator
partial : :obj:`bool`, optional
Partial (``True``) of full (``False``) orthogonality
b : :obj:`np.ndarray`, optional
b : :obj:`numpy.ndarray`, optional
Vector
alpha : :obj:`float`, optional
Positive coefficient for partial orthogonality. It will be ignored if
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8 changes: 4 additions & 4 deletions pyproximal/proximal/Quadratic.py
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Expand Up @@ -22,13 +22,13 @@ class Quadratic(ProxOperator):
----------
Op : :obj:`pylops.LinearOperator`, optional
Linear operator (must be square)
b : :obj:`np.ndarray`, optional
b : :obj:`numpy.ndarray`, optional
Vector
c : :obj:`float`, optional
Scalar
niter : :obj:`int`, optional
Number of iterations of iterative scheme used to compute the proximal
x0 : :obj:`np.ndarray`, optional
x0 : :obj:`numpy.ndarray`, optional
Initial vector
warm : :obj:`bool`, optional
Warm start (``True``) or not (``False``). Uses estimate from previous
Expand Down Expand Up @@ -121,12 +121,12 @@ def grad(self, x: NDArray) -> NDArray:

Parameters
----------
x : :obj:`np.ndarray`
x : :obj:`numpy.ndarray`
Vector

Returns
-------
g : :obj:`np.ndarray`
g : :obj:`numpy.ndarray`
Gradient vector

"""
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10 changes: 5 additions & 5 deletions pyproximal/proximal/RelaxedMS.py
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Expand Up @@ -40,13 +40,13 @@ class RelaxedMumfordShah(ProxOperator):

Parameters
----------
sigma : :obj:`float` or :obj:`np.ndarray` or :obj:`func`, optional
sigma : :obj:`float` or :obj:`numpy.ndarray` or :obj:`func`, optional
Multiplicative coefficient of L2 norm that controls the smoothness of the solutuon.
This can be a constant number, a list of values (for multidimensional inputs, acting
on the second dimension) or a function that is called passing a counter which keeps
track of how many times the ``prox`` method has been invoked before and returns a
scalar (or a list of) ``sigma`` to be used.
kappa : :obj:`float` or :obj:`np.ndarray` or :obj:`func`, optional
kappa : :obj:`float` or :obj:`numpy.ndarray` or :obj:`func`, optional
Constant value in the rMS norm which essentially controls when the norm allows a jump. This can be a
constant number, a list of values (for multidimensional inputs, acting on the second dimension) or
a function that is called passing a counter which keeps track of how many
Expand All @@ -58,10 +58,10 @@ class RelaxedMumfordShah(ProxOperator):
The :math:`rMS` proximal operator is defined as [1]_:

.. math::
\text{prox}_{\tau \text{rMS}}(x) =
\text{prox}_{\tau \text{rMS}}(\mathbf{x}) =
\begin{cases}
\frac{1}{1+2\tau\alpha}x & \text{ if } & \vert x\vert \leq \sqrt{\frac{\kappa}{\alpha}(1 + 2\tau\alpha)} \\
\kappa & \text{ else }
\frac{1}{1+2\tau\alpha}x_i & \text{ if } & \vert x_i\vert \leq \sqrt{\frac{\kappa}{\alpha}(1 + 2\tau\alpha)} \\
x_i & \text{ else }
\end{cases}.

.. [1] Strekalovskiy, E., and D. Cremers, 2014, Real-time minimization of the piecewise smooth
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4 changes: 2 additions & 2 deletions pyproximal/proximal/Sum.py
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Expand Up @@ -20,7 +20,7 @@ class Sum(ProxOperator):
----------
ops : :obj:`list`
A list of proximable functions :math:`f_1, \ldots, f_m`.
weights : :obj:`np.ndarray` or :obj:`list` or :obj:`None`, optional, default=None
weights : :obj:`numpy.ndarray` or :obj:`list` or :obj:`None`, optional, default=None
Weights :math:`\sum_{i=1}^m w_i = 1, \ 0 < w_i < 1`,
used when :math:`m > 2`, or :math:`m = 2` and ``use_parallel=True``.
Defaults to None, which means :math:`w_1 = \cdots = w_m = \frac{1}{m}.`
Expand Down Expand Up @@ -142,7 +142,7 @@ def __call__(self, x: NDArray) -> bool | float:

Parameters
----------
x : :obj:`np.ndarray`
x : :obj:`numpy.ndarray`
Vector

Returns
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10 changes: 5 additions & 5 deletions pyproximal/proximal/_Simplex_cuda.py
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Expand Up @@ -39,23 +39,23 @@ def simplex_jit_cuda(x, coeffs, scalar, lower, upper, maxiter, ftol, xtol, y):

Parameters
----------
x : :obj:`np.ndarray`
x : :obj:`numpy.ndarray`
Input vector
coeffs : :obj:`np.ndarray`
coeffs : :obj:`numpy.ndarray`
Vector of coefficients used in the definition of the hyperplane
scalar : :obj:`float`
Scalar used in the definition of the hyperplane
lower : :obj:`float` or :obj:`np.ndarray`, optional
lower : :obj:`float` or :obj:`numpy.ndarray`, optional
Lower bound of Box
upper : :obj:`float` or :obj:`np.ndarray`, optional
upper : :obj:`float` or :obj:`numpy.ndarray`, optional
Upper bound of Box
maxiter : :obj:`int`, optional
Maximum number of iterations
ftol : :obj:`float`, optional
Function tolerance
xtol : :obj:`float`, optional
Solution absolute tolerance
y : :obj:`np.ndarray`
y : :obj:`numpy.ndarray`
Output vector

"""
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20 changes: 10 additions & 10 deletions pyproximal/proximal/_Simplex_numba.py
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Expand Up @@ -37,19 +37,19 @@ def bisect_jit(

Parameters
----------
x : :obj:`np.ndarray`
x : :obj:`numpy.ndarray`
Input vector
coeffs : :obj:`np.ndarray`
coeffs : :obj:`numpy.ndarray`
Vector of coefficients used in the definition of the hyperplane
scalar : :obj:`float`
Scalar used in the definition of the hyperplane
lower : :obj:`float` or :obj:`np.ndarray`, optional
lower : :obj:`float` or :obj:`numpy.ndarray`, optional
Lower bound of Box
upper : :obj:`float` or :obj:`np.ndarray`, optional
upper : :obj:`float` or :obj:`numpy.ndarray`, optional
Upper bound of Box
bisect_lower : :obj:`float` or :obj:`np.ndarray`, optional
bisect_lower : :obj:`float` or :obj:`numpy.ndarray`, optional
Lower end of bisection
bisect_upper : :obj:`float` or :obj:`np.ndarray`, optional
bisect_upper : :obj:`float` or :obj:`numpy.ndarray`, optional
Upper end of bisection
maxiter : :obj:`int`, optional
Maximum number of iterations
Expand Down Expand Up @@ -91,15 +91,15 @@ def simplex_jit(

Parameters
----------
x : :obj:`np.ndarray`
x : :obj:`numpy.ndarray`
Input vector
coeffs : :obj:`np.ndarray`
coeffs : :obj:`numpy.ndarray`
Vector of coefficients used in the definition of the hyperplane
scalar : :obj:`float`
Scalar used in the definition of the hyperplane
lower : :obj:`float` or :obj:`np.ndarray`, optional
lower : :obj:`float` or :obj:`numpy.ndarray`, optional
Lower bound of Box
upper : :obj:`float` or :obj:`np.ndarray`, optional
upper : :obj:`float` or :obj:`numpy.ndarray`, optional
Upper bound of Box
maxiter : :obj:`int`, optional
Maximum number of iterations
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2 changes: 1 addition & 1 deletion pyproximal/utils/moreau.py
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Expand Up @@ -25,7 +25,7 @@ def moreau(
----------
prox : :obj:`pyproximal.ProxOperator`
Proximal operator
x : :obj:`np.ndarray`
x : :obj:`numpy.ndarray`
Vector
tau : :obj:`float`
Positive scalar weight
Expand Down