Merge pull request #357 from JuliaOpt/rearrange

Rearrange exports; deprecate `lambdamin`, `lambdamax`

Author: ericphanson

docs/examples_literate/general_examples/basic_usage.jl

@@ -81,7 +81,7 @@ x.value
 
 
 y = Semidefinite(2)
-p = maximize(lambdamin(y), tr(y)<=6)
+p = maximize(eigmin(y), tr(y)<=6)
 solve!(p, SCS.Optimizer(verbose=0))
 p.optval
 

docs/examples_literate/mixed_integer/aux_files/antidiag.jl

@@ -8,9 +8,8 @@
 # All expressions and atoms are subtpyes of AbstractExpr.
 # Please read expressions.jl first.
 #############################################################################
-
 import Convex.sign, Convex.monotonicity, Convex.curvature, Convex.evaluate, Convex.conic_form!
-export antidiag, sign, monotonicity, curvature, evaluate, conic_form!
+export antidiag
 
 ### Diagonal
 ### Represents the kth diagonal of an mxn matrix as a (min(m, n) - k) x 1 vector

docs/src/operations.md

@@ -110,8 +110,8 @@ solver (including SCS and Mosek).
 | ------------------ | --------------------------------- | ------- | ------------- | ------------------------------ |
 | `nuclearnorm(x)`   | sum of singular values of $x$ | convex  | not monotonic | none                           |
 | `operatornorm(x)`  | max of singular values of $x$ | convex  | not monotonic | none                           |
-| `lambdamax(x)`     | max eigenvalue of $x$         | convex  | not monotonic | none                           |
-| `lambdamin(x)`     | min eigenvalue of $x$         | concave | not monotonic | none                           |
+| `eigmax(x)`     | max eigenvalue of $x$         | convex  | not monotonic | none                           |
+| `eigmin(x)`     | min eigenvalue of $x$         | concave | not monotonic | none                           |
 | `matrixfrac(x, P)` | $x^TP^{-1}x$                  | convex  | not monotonic | IC: P is positive semidefinite |
 
 Exponential + SDP representable Functions

src/Convex.jl

@@ -4,13 +4,36 @@ module Convex
 using OrderedCollections: OrderedDict
 using LinearAlgebra
 using SparseArrays
+using AbstractTrees: AbstractTrees
 
 using MathOptInterface
 const MOI = MathOptInterface
 const MOIU = MOI.Utilities
 const MOIB = MOI.Bridges
 
-global DEFAULT_SOLVER = nothing
+# Functions
+export conv, dotsort, entropy, exp, geomean, hinge_loss, huber, inner_product, invpos
+export log_perspective, logisticloss, logsumexp, matrixfrac, neg, norm2, norm_1, norm_inf, nuclearnorm
+export partialtrace, partialtranspose, pos, qol_elementwise, quadform, quadoverlin, rationalnorm
+export relative_entropy, scaledgeomean, sigmamax, square, sumlargest, sumlargesteigs, sumsmallest, sumsquares
+
+# rexports from LinearAlgebra
+export diag, diagm, Diagonal, dot, eigmax, eigmin, kron, logdet, norm, tr
+
+# Constraints
+export isposdef, ⪰, ⪯ # PSD constraints
+export socp
+
+# Variables
+export Constant, ComplexVariable, HermitianSemidefinite, Semidefinite, Variable
+export curvature, evaluate, fix!, free!, monotonicity, sign, vexity
+
+# Signs
+export Positive, Negative, ComplexSign, NoSign
+
+# Problems
+export add_constraint!, add_constraints!, maximize, minimize, Problem, satisfy, solve!
+
 ### modeling framework
 include("dcp.jl")
 include("expressions.jl")
@@ -71,7 +94,7 @@ include("atoms/second_order_cone/huber.jl")
 ### SDP atoms
 include("atoms/sdp_cone/nuclearnorm.jl")
 include("atoms/sdp_cone/operatornorm.jl")
-include("atoms/sdp_cone/lambda_min_max.jl")
+include("atoms/sdp_cone/eig_min_max.jl")
 include("atoms/sdp_cone/matrixfrac.jl")
 include("atoms/sdp_cone/sumlargesteigs.jl")
 
@@ -98,4 +121,7 @@ function clearmemory()
     Base.depwarn("Convex.clearmemory() is deprecated, as the memory leak it works around has been closed (in https://github.com/JuliaOpt/Convex.jl/pull/322). This function no longer does anything and will be removed in a future Convex.jl release.", :clearmemory )
 end
 
+@deprecate lambdamin eigmin
+@deprecate lambdamax eigmax
+
 end

src/atoms/affine/add_subtract.jl

@@ -6,9 +6,6 @@
 # Please read expressions.jl first.
 #############################################################################
 
-export +, -
-export sign, curvature, monotonicity, evaluate
-
 ### Unary Negation
 
 struct NegateAtom <: AbstractExpr

src/atoms/affine/conjugate.jl

@@ -1,6 +1,4 @@
 import Base.conj
-export conj
-export sign, curvature, monotonicity, evaluate, conic_form!
 struct ConjugateAtom <: AbstractExpr
     head::Symbol
     id_hash::UInt64

src/atoms/affine/conv.jl

@@ -3,8 +3,6 @@
 # Handles convolution between a constant vector and an expression vector.
 #############################################################################
 
-export conv
-
 function conv(x::Value, y::AbstractExpr)
     if (size(x,2) != 1 && length(size(x)) != 1) || size(y,2) != 1
         error("convolution only supported between two vectors")

src/atoms/affine/diag.jl

@@ -7,8 +7,6 @@
 
 # k >= min(num_cols, num_rows) || k <= -min(num_rows, num_cols)
 import LinearAlgebra.diag
-export diag
-#export sign, curvature, monotonicity, evaluate
 
 ### Diagonal
 ### Represents the kth diagonal of an mxn matrix as a (min(m, n) - k) x 1 vector

src/atoms/affine/diagm.jl

@@ -6,7 +6,6 @@
 #############################################################################
 
 import LinearAlgebra.diagm, LinearAlgebra.Diagonal
-export diagm, Diagonal
 
 struct DiagMatrixAtom <: AbstractExpr
     head::Symbol

src/atoms/affine/dot.jl

@@ -1,5 +1,4 @@
 import LinearAlgebra.dot
-export dot
 
 ismatrix(x::AbstractExpr) = (s = size(x); length(s) == 2 && s[1] > 1 && s[2] > 1)
 ismatrix(::AbstractMatrix) = true