94 lines
3.4 KiB
Ruby
94 lines
3.4 KiB
Ruby
class Nlopt < Formula
|
|
desc "Free/open-source library for nonlinear optimization"
|
|
homepage "https://nlopt.readthedocs.io/"
|
|
url "https://github.com/stevengj/nlopt/releases/download/nlopt-2.4.2/nlopt-2.4.2.tar.gz"
|
|
sha256 "8099633de9d71cbc06cd435da993eb424bbcdbded8f803cdaa9fb8c6e09c8e89"
|
|
revision 2
|
|
|
|
bottle do
|
|
cellar :any
|
|
sha256 "9b08f332287446d6eb32c7b6fdf3732b1459dae9b9d04af3bf11d7924d549ebc" => :mojave
|
|
sha256 "8b24f8a85b1b9e553cfd97a88fb22093926fe787bbeeaa598636baf7adfb1ea3" => :high_sierra
|
|
sha256 "183d661c2b34ff468162b4bcc3bc7c287bcab47ff1bd4b902ea00fe188db1e52" => :sierra
|
|
sha256 "cfb26ea39b36e9a9ad472e2600864d040f02531ba2c922798f82455a25b73a30" => :el_capitan
|
|
sha256 "eed62f227cdfd93ba00d7abe061b4136945a4511d67651d0fa4aa07b196b7b7d" => :yosemite
|
|
end
|
|
|
|
head do
|
|
url "https://github.com/stevengj/nlopt.git"
|
|
depends_on "cmake" => :build
|
|
depends_on "swig" => :build
|
|
end
|
|
|
|
depends_on "numpy" => :recommended
|
|
|
|
def install
|
|
ENV.deparallelize
|
|
|
|
if build.head?
|
|
system "cmake", ".", *std_cmake_args,
|
|
"-DBUILD_MATLAB=OFF",
|
|
"-DBUILD_OCTAVE=OFF",
|
|
"-DWITH_CXX=ON"
|
|
else
|
|
system "./configure", "--prefix=#{prefix}",
|
|
"--enable-shared",
|
|
"--with-cxx",
|
|
"--without-octave"
|
|
system "make"
|
|
end
|
|
system "make", "install"
|
|
|
|
# Create library links for C programs
|
|
%w[0.dylib dylib a].each do |suffix|
|
|
lib.install_symlink "#{lib}/libnlopt_cxx.#{suffix}" => "#{lib}/libnlopt.#{suffix}"
|
|
end
|
|
end
|
|
|
|
test do
|
|
# Based on http://ab-initio.mit.edu/wiki/index.php/NLopt_Tutorial#Example_in_C.2FC.2B.2B
|
|
(testpath/"test.c").write <<~EOS
|
|
#include <math.h>
|
|
#include <nlopt.h>
|
|
#include <stdio.h>
|
|
double myfunc(unsigned n, const double *x, double *grad, void *my_func_data) {
|
|
if (grad) {
|
|
grad[0] = 0.0;
|
|
grad[1] = 0.5 / sqrt(x[1]);
|
|
}
|
|
return sqrt(x[1]);
|
|
}
|
|
typedef struct { double a, b; } my_constraint_data;
|
|
double myconstraint(unsigned n, const double *x, double *grad, void *data) {
|
|
my_constraint_data *d = (my_constraint_data *) data;
|
|
double a = d->a, b = d->b;
|
|
if (grad) {
|
|
grad[0] = 3 * a * (a*x[0] + b) * (a*x[0] + b);
|
|
grad[1] = -1.0;
|
|
}
|
|
return ((a*x[0] + b) * (a*x[0] + b) * (a*x[0] + b) - x[1]);
|
|
}
|
|
int main() {
|
|
double lb[2] = { -HUGE_VAL, 0 }; /* lower bounds */
|
|
nlopt_opt opt;
|
|
opt = nlopt_create(NLOPT_LD_MMA, 2); /* algorithm and dimensionality */
|
|
nlopt_set_lower_bounds(opt, lb);
|
|
nlopt_set_min_objective(opt, myfunc, NULL);
|
|
my_constraint_data data[2] = { {2,0}, {-1,1} };
|
|
nlopt_add_inequality_constraint(opt, myconstraint, &data[0], 1e-8);
|
|
nlopt_add_inequality_constraint(opt, myconstraint, &data[1], 1e-8);
|
|
nlopt_set_xtol_rel(opt, 1e-4);
|
|
double x[2] = { 1.234, 5.678 }; /* some initial guess */
|
|
double minf; /* the minimum objective value, upon return */
|
|
|
|
if (nlopt_optimize(opt, x, &minf) < 0)
|
|
return 1;
|
|
else
|
|
printf("found minimum at f(%g,%g) = %0.10g", x[0], x[1], minf);
|
|
nlopt_destroy(opt);
|
|
}
|
|
EOS
|
|
system ENV.cc, "test.c", "-o", "test", "-L#{opt_lib}", "-lnlopt", "-lm"
|
|
assert_match "found minimum", shell_output("./test")
|
|
end
|
|
end
|