v1.3.0

.github/workflows/ci.yml

@@ -12,9 +12,9 @@ jobs:
       fail-fast: false
       matrix:
         version:
-          - '1.3' # minimum Julia version that your package supports. 
           - '1' # '1' will expand to the latest stable 1.x release of Julia.
         os:
+          - macOS-latest
           - ubuntu-latest
         arch:
           - x64

Project.toml

@@ -1,8 +1,8 @@
 name = "LLLplus"
 uuid = "142c1900-a1c3-58ae-a66d-b187f9ca6423"
-keywords = ["lattice reduction", "lattice basis reduction", "shortest vector problem", "closest vector problem", "LLL", "Lenstra-Lenstra-Lovász", "Seysen", "Brun", "VBLAST", "subset-sum problem", "Lagarias-Odlyzko", "Bailey–Borwein–Plouffe formula"]
+keywords = ["lattice reduction", "lattice basis reduction", "SVP", "shortest vector problem", "CVP", "closest vector problem", "LLL", "Lenstra-Lenstra-Lovász", "Seysen", "Brun", "VBLAST", "subset-sum problem", "Lagarias-Odlyzko", "Bailey–Borwein–Plouffe formula"]
 license = "MIT"
-version = "1.3.1"
+version = "1.3.0"
 
 [deps]
 DelimitedFiles = "8bb1440f-4735-579b-a4ab-409b98df4dab"
@@ -13,4 +13,5 @@ Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [compat]
+Documenter = "0.25"
 julia = "1"

test/runtests.jl

@@ -4,7 +4,6 @@
 using LLLplus
 using Test
 using LinearAlgebra
-using DelimitedFiles
 using Documenter
 
 # --------------
@@ -75,43 +74,6 @@ uhat=cvp(Q'*y,R,Val(false),-1,1);
 errRate = sum(abs.(u-uhat))
 println("Error Rate is $(errRate). It should be zero or very small.\n")
 
-# --------------
-# test norm for matrix from http://www.latticechallenge.org/
-# --------------
-
-# we should replace this section with more useful tests
-
-println("Testing now with 200x200 matrix from latticechallenge.org.")
-println("The min norm of the input should be 30, min norm of the "*
-        "reduced bases is hopefully smaller :-)")
-mat = readdlm("challenge-200.mod",Int64) #run from parent directory
-mat = Matrix(mat');
-N = size(mat,2)
-
-nrms = zeros(N,1);
-for ix=1:N
-    nrms[ix] = norm(mat[:,ix])
-end
-println("min norm of input is $(minimum(nrms))")
-
-@time B,_ = lll(mat);
-nrms = zeros(N,1);
-for ix=1:N
-    nrms[ix] = norm(B[:,ix]);
-end
-mlll=minimum(nrms)
-println("min norm of lll-reduced basis is $(mlll)")
-@test mlll<=30+1e-6
-
-@time B,_ = seysen(mat);
-nrms = zeros(N,1)
-for ix=1:N
-    nrms[ix] = norm(B[:,ix])
-end
-mSeysen = minimum(nrms)
-println("min norm of seysen-reduced basis is $(mSeysen)")
-@test mSeysen<=30+1e-6
-
 
 # --------------
 # doctests