update meson and ci (#15)

* update meson and ci

* fixup

* fixup

* fixup

* fixup

* fixup

* fixup

* fixup

* update gitignore

* fix unittest

* fixup travis

.circleci/config.yml

@@ -0,0 +1,22 @@
+version: 2.1
+
+orbs:
+  mirci: libmir/[email protected]
+
+workflows:
+  version: 2
+  build-deploy:
+    jobs:
+      - mirci/test_and_build_docs:
+          filters:
+            tags:
+              only: /^v(\d)+(\.(\d)+)+$/
+      - mirci/upload_docs:
+          to: mir-optim.libmir.org
+          requires:
+            - mirci/test_and_build_docs
+          filters:
+            branches:
+              ignore: /.*/
+            tags:
+              only: /^v(\d)+(\.(\d)+)+$/

.gitignore

@@ -26,3 +26,5 @@ build/mir-random/
 *.dll
 x.txt
 subprojects/*/
+web
+docgen

.travis.yml

@@ -21,21 +21,9 @@ branches:
 script:
  - dub test -c unittest-blas
 #  - if [ "$DC" = "ldc2" ]; then rm -rf .dub && dub build -c blas --compiler=ldmd2 --build-mode=singleFile --build=better-c-release --force && g++ -std=c++1y -pthread -I./include examples/least_squares.cpp -L./ -lmir-optim -llapack -lblas && ./a.out; fi
-#  - meson build -D with_test=true && cd build && ninja -j4 && ninja test -v && cd ..
 
 addons:
   apt:
     update: true
     packages:
      - liblapack-dev
-     - pkg-config
-
-# install:
-#   - pyenv global system 3.6
-#   - pip3 install 'meson>=0.45'
-#   - mkdir .ntmp
-#   - curl -L https://github.com/ninja-build/ninja/releases/download/v1.8.2/ninja-linux.zip -o .ntmp/ninja-linux.zip
-#   - unzip .ntmp/ninja-linux.zip -d .ntmp
-# before_script:
-#   - export PATH=$PATH:$PWD/.ntmp
-

README.md

@@ -13,7 +13,7 @@ Dlang BetterC Nonlinear Optimisers.
  - Modified Levenberg-Marquardt Algorithm (Nonlinear Least Squares).
  - Boxed Constrained Quadratic Problem Solver
 
-See also [online documentation](https://mir-optim.dpldocs.info/mir.html) (deprecated?).
+See also [online documentation](http://mir-optim.libmir.org).
 
 ### Features
 

index.d

@@ -0,0 +1,27 @@
+Ddoc
+
+$(H1 Dlang BetterC Nonlinear Optimisers)
+
+$(P The following table is a quick reference guide for which Mir Optim modules to
+use for a given category of functionality.)
+
+$(BOOKTABLE ,
+    $(TR
+        $(TH Modules)
+        $(TH Description)
+    )
+    $(TR
+        $(TDNW $(MREF mir,optim,boxcqp))
+        $(TD High Bound Constrained Convex Quadratic Problem Solver)
+    )
+    $(TR
+        $(TDNW $(MREF mir,optim,least_squares))
+        $(TD Nonlinear Least Squares Solver)
+    )
+)
+
+Macros:
+        TITLE=Mir Optim
+        WIKI=Mir Optim
+        DDOC_BLANKLINE=
+        _=

meson.build

@@ -1,70 +1,86 @@
-project('mir-optim', 'd', version : '1.0.0', license: 'BSL-1.0')
-
-cblas_d_dep = dependency('cblas-d', fallback : ['cblas', 'cblas_dep'])
-lapack_d_dep = dependency('lapack-d', fallback : ['lapack', 'lapack_dep'])
-mir_algorithm_dep = dependency('mir-algorithm', fallback : ['mir-algorithm', 'mir_algorithm_dep'])
-mir_blas_dep = dependency('mir-blas', fallback : ['mir-blas', 'mir_blas_dep'])
-mir_core_dep = dependency('mir-core', fallback : ['mir-core', 'mir_core_dep'])
-mir_lapack_dep = dependency('mir-lapack', fallback : ['mir-lapack', 'mir_lapack_dep'])
-mir_random_dep = dependency('mir-random', fallback : ['mir-random', 'mir_random_dep'], default_options : ['extended=true'])
-
-required_deps = [
-    cblas_d_dep,
-    lapack_d_dep,
-    mir_algorithm_dep,
-    mir_blas_dep,
-    mir_core_dep,
-    mir_lapack_dep,
-    mir_random_dep,
+project('mir-optim', 'd', version: '2.0.0', license: 'BSL-1.0')
+
+description = 'Mir Optim - Nonlinear Optimisers'
+
+subprojects = [
+    'cblas-d',
+    'lapack-d',
+    'mir-algorithm',
+    'mir-blas',
+    'mir-core',
+    'mir-lapack',
+    'mir-random',
 ]
 
 if target_machine.system() == 'linux'
-    mir_linux_kernel_dep = dependency('mir-linux-kernel', fallback : ['mir-linux-kernel', 'mir_linux_kernel_dep'])
-    required_deps = [required_deps, mir_linux_kernel_dep]
+    subprojects += 'mir-linux-kernel'
 endif
 
-mir_optim_dir = include_directories('source/')
+has_cpp_headers = false
 
-mir_optim_src = [
-    'source/mir/optim/least_squares.d',
-    'source/mir/optim/boxcqp.d',
+sources_list = [
+    'mir/optim/boxcqp',
+    'mir/optim/least_squares',
 ]
 
-mir_optim_lib = library(meson.project_name(),
-    mir_optim_src,
-    include_directories: mir_optim_dir,
+sources = []
+foreach s : sources_list
+    sources += 'source/' + s + '.d'
+endforeach
+
+add_project_arguments([
+    '-preview=dip1008',
+    '-lowmem',
+], language: 'd')
+
+required_deps = []
+
+foreach p : subprojects 
+    required_deps += dependency(p, fallback : [p, 'this_dep'])
+endforeach
+
+directories = ['source']
+
+if has_cpp_headers
+    directories += 'include'
+endif
+
+directories = include_directories(directories)
+
+this_lib = library(meson.project_name(),
+    sources,
+    include_directories: directories,
     install: true,
     version: meson.project_version(),
     dependencies: required_deps,
 )
 
-mir_optim_dep = declare_dependency(
-    link_with: [mir_optim_lib],
-    include_directories: mir_optim_dir,
+this_dep = declare_dependency(
+    link_with: [this_lib],
+    include_directories: directories,
     dependencies: required_deps,
 )
 
+test_versions = ['mir_optim_test']
+
+if has_cpp_headers
+    install_subdir('include/',
+        strip_directory :true,
+        install_dir: 'include/',
+    )
+endif
+
 install_subdir('source/',
     strip_directory : true,
     install_dir: 'include/d/' + meson.project_name(),
 )
 
-import('pkgconfig').generate(mir_optim_lib,
-    description: 'Optimisation Framework',
+import('pkgconfig').generate(this_lib,
+    description: description,
     subdirs: 'd/' + meson.project_name(),
 )
 
-if get_option('with_test')
+mir_optim_dep = this_dep
+mir_optim_lib = this_lib
 
-    mir_optim_test_exe = executable(meson.project_name() + '-test',
-        mir_optim_src,
-        include_directories: mir_optim_dir,
-        d_unittest: true,
-        d_module_versions: ['mir_optim_test'],
-        link_args: '-main',
-        dependencies: required_deps,
-    )
-
-    test(meson.project_name() + '-test', mir_optim_test_exe)
-
-endif
+test_subdirs = []

source/mir/optim/boxcqp.d

@@ -1,15 +1,10 @@
 /++
 $(H1 Bound Constrained Convex Quadratic Problem Solver)
 
-Paper: $(HTTP www.cse.uoi.gr/tech_reports/publications/boxcqp.pdf,
-    BOXCQP: AN ALGORITHM FOR BOUND CONSTRAINED CONVEX QUADRATIC PROBLEMS)
+Paper: $(HTTP www.cse.uoi.gr/tech_reports/publications/boxcqp.pdf, BOXCQP: AN ALGORITHM FOR BOUND CONSTRAINED CONVEX QUADRATIC PROBLEMS)
 
 Copyright: Copyright © 2020, Symmetry Investments & Kaleidic Associates Advisory Limited
 Authors:   Ilya Yaroshenko
-
-Macros:
-NDSLICE = $(REF_ALTTEXT $(TT $2), $2, mir, ndslice, $1)$(NBSP)
-T2=$(TR $(TDNW $(LREF $1)) $(TD $+))
 +/
 module mir.optim.boxcqp;
 
@@ -81,8 +76,8 @@ Solves:
 Params:
     P = Positive-definite Matrix, NxN
     q = Linear component, N
-    l = Lower bounds in [-inf, +inf), N
-    u = Upper bounds in (-inf, +inf], N
+    l = Lower bounds in `[-inf, +inf$(RPAREN)`, N
+    u = Upper bounds in `$(LPAREN)-inf, +inf]`, N
     x = solutoin, N
     settings = Iteration settings (optional)
 +/
@@ -115,8 +110,8 @@ Params:
         The upper triangular part (and diagonal) of the matrix is used for temporary data and then can be resotored.
         Matrix diagonal is always restored.
     q = Linear component, N
-    l = Lower bounds in [-inf, +inf), N
-    u = Upper bounds in (-inf, +inf], N
+    l = Lower bounds in `[-inf, +inf$(RPAREN)`, N
+    u = Upper bounds in `$(LPAREN)-inf, +inf]`, N
     x = solutoin, N
     unconstrainedSolution = 
     work = workspace, $(LREF mir_box_qp_work_length)(N)
@@ -388,6 +383,8 @@ version(mir_optim_test)
 unittest
 {
     import mir.ndslice;
+    import mir.algorithm.iteration;
+    import mir.math.common;
 
     auto P = [
         [ 2.0, -1, 0],
@@ -401,7 +398,7 @@ unittest
     auto x = slice!double(q.length);
 
     solveBoxQP(P, q, l, u, x);
-    assert(x == [-0.5, 2, 1]);
+    assert(x.equal!approxEqual([-0.5, 2, 1]));
 }
 
 package(mir) void applyBounds(T)(Slice!(T*) x, Slice!(const(T)*) l, Slice!(const(T)*) u)

source/mir/optim/least_squares.d

@@ -278,7 +278,7 @@ version(mir_optim_test)
 {
     import mir.algorithm.iteration: all;
     import mir.ndslice.allocation: slice;
-    import mir.ndslice.slice: sliced;
+    import mir.ndslice.slice: Slice, sliced;
     import mir.blas: nrm2;
 
     LeastSquaresSettings!double settings;
@@ -450,6 +450,10 @@ Params:
     g = `m × n` Jacobian (optional)
     tm = thread manager for finite difference jacobian approximation in case of g is null (optional)
     settings = Levenberg-Marquardt data structure
+    m = length (dimension) of `y = f(x)`
+    x = initial (in) and final (out) X value
+    l = lower X bound
+    u = upper X bound
 See_also: $(LREF optimize)
 +/
 LeastSquaresResult!T optimizeLeastSquares(alias f, alias g = null, alias tm = null, T)(
@@ -575,9 +579,15 @@ alias LeastSquaresThreadManager = void delegate(
 Low level `extern(D)` instatiation.
 Params:
     settings = Levenberg-Marquardt data structure
+    m = length (dimension) of `y = f(x)`
+    x = initial (in) and final (out) X value
+    l = lower X bound
+    u = upper X bound
     f = `n -> m` function
     g = `m × n` Jacobian (optional)
     tm = thread manager for finite difference jacobian approximation in case of g is null (optional)
+    work = floating point workspace length of at least $(LREF mir_least_squares_work_length)
+    iwork = floating point workspace length of at least $(LREF mir_least_squares_iwork_length)
 +/
 pragma(inline, false)
 LeastSquaresResult!double optimizeLeastSquaresD
@@ -674,6 +684,19 @@ extern(C) @safe nothrow @nogc
         gContext = context for the Jacobian (optional)
         g = `m × n` Jacobian (optional)
         tm = thread manager for finite difference jacobian approximation in case of g is null (optional)
+        m = length (dimension) of `y = f(x)`
+        n = length (dimension) of X
+        x = initial (in) and final (out) X value
+        l = lower X bound
+        u = upper X bound
+        f = `n -> m` function
+        fContext = `f` context
+        g = `m × n` Jacobian (optional)
+        gContext = `g` context
+        tm = thread manager for finite difference jacobian approximation in case of g is null (optional)
+        tmContext = `tm` context
+        work = floating point workspace length of at least $(LREF mir_least_squares_work_length)
+        iwork = floating point workspace length of at least $(LREF mir_least_squares_iwork_length)
     +/
     extern(C)
     pragma(inline, false)

subprojects/cblas.wrap → subprojects/cblas-d.wrap

@@ -1,4 +1,4 @@
 [wrap-git]
-directory=cblas
+directory=cblas-d
 url=https://github.com/DlangScience/cblas.git
 revision=head

subprojects/lapack.wrap → subprojects/lapack-d.wrap

@@ -1,4 +1,4 @@
 [wrap-git]
-directory=lapack
+directory=lapack-d
 url=https://github.com/libmir/lapack.git
 revision=head