proj/gentoo: Initial commit

This commit represents a new era for Gentoo:
Storing the gentoo-x86 tree in Git, as converted from CVS.

This commit is the start of the NEW history.
Any historical data is intended to be grafted onto this point.

Creation process:
1. Take final CVS checkout snapshot
2. Remove ALL ChangeLog* files
3. Transform all Manifests to thin
4. Remove empty Manifests
5. Convert all stale $Header$/$Id$ CVS keywords to non-expanded Git $Id$
5.1. Do not touch files with -kb/-ko keyword flags.

Signed-off-by: Robin H. Johnson <robbat2@gentoo.org>
X-Thanks: Alec Warner <antarus@gentoo.org> - did the GSoC 2006 migration tests
X-Thanks: Robin H. Johnson <robbat2@gentoo.org> - infra guy, herding this project
X-Thanks: Nguyen Thai Ngoc Duy <pclouds@gentoo.org> - Former Gentoo developer, wrote Git features for the migration
X-Thanks: Brian Harring <ferringb@gentoo.org> - wrote much python to improve cvs2svn
X-Thanks: Rich Freeman <rich0@gentoo.org> - validation scripts
X-Thanks: Patrick Lauer <patrick@gentoo.org> - Gentoo dev, running new 2014 work in migration
X-Thanks: Michał Górny <mgorny@gentoo.org> - scripts, QA, nagging
X-Thanks: All of other Gentoo developers - many ideas and lots of paint on the bikeshed

1 files changed, 31 insertions, 0 deletions

diff --git a/sci-libs/ceres-solver/metadata.xml b/sci-libs/ceres-solver/metadata.xml
new file mode 100644
index 000000000000..c61f580793c1
--- /dev/null
+++ b/sci-libs/ceres-solver/metadata.xml
@@ -0,0 +1,31 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<!DOCTYPE pkgmetadata SYSTEM "http://www.gentoo.org/dtd/metadata.dtd">
+<pkgmetadata>
+<herd>sci</herd>
+<longdescription lang="en">
+  Ceres Solver is a portable C++ library that allows for
+  modeling and solving large complicated nonlinear least squares
+  problems. It features:
+    * automatic differentiation
+    * robust loss functions
+    * local parameterizations
+    * threaded Jacobian evaluators and linear solvers
+    * Levenberg-Marquardt and Dogleg (Powell, Subspace) solvers
+    * Dense QR and Cholesky factorization (using Eigen) for small problems
+    * Sparse Cholesky factorization (using SuiteSparse) for large sparse
+      problems
+    * Specialized solvers for bundle adjustment problems in computer vision
+    * Iterative linear solvers for general sparse and bundle
+      adjustment problems
+</longdescription>
+<use>
+  <flag name="cxsparse">Enable simple support for sparse matrix algebra from
+  <pkg>sci-libs/cxsparse</pkg> with no LAPACK dependencies</flag>
+  <flag name="schur">Enable fixed-size schur specializations (disable if
+  binary size is an issue)</flag>
+  <flag name="sparse">Enable support for sparse matrix algebra with various
+  packages from SuiteSparse</flag>
+  <flag name="gflags">Use <pkg>dev-cpp/gflags</pkg> for flag parsing</flag>
+  <flag name="protobuf">Use <pkg>dev-libs/protobuf</pkg> to encode structured data</flag>
+</use>
+</pkgmetadata>