Initial commit of Ceres Solver.
diff --git a/internal/ceres/loss_function.cc b/internal/ceres/loss_function.cc
new file mode 100644
index 0000000..00b2b18
--- /dev/null
+++ b/internal/ceres/loss_function.cc
@@ -0,0 +1,93 @@
+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2010, 2011, 2012 Google Inc. All rights reserved.
+// http://code.google.com/p/ceres-solver/
+//
+// Redistribution and use in source and binary forms, with or without
+// modification, are permitted provided that the following conditions are met:
+//
+// * Redistributions of source code must retain the above copyright notice,
+// this list of conditions and the following disclaimer.
+// * Redistributions in binary form must reproduce the above copyright notice,
+// this list of conditions and the following disclaimer in the documentation
+// and/or other materials provided with the distribution.
+// * Neither the name of Google Inc. nor the names of its contributors may be
+// used to endorse or promote products derived from this software without
+// specific prior written permission.
+//
+// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
+// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
+// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
+// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
+// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
+// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+// POSSIBILITY OF SUCH DAMAGE.
+//
+// Author: sameeragarwal@google.com (Sameer Agarwal)
+//
+// Purpose: See .h file.
+
+#include "ceres/loss_function.h"
+
+#include <cmath>
+#include <cstddef>
+
+namespace ceres {
+
+void TrivialLoss::Evaluate(double s, double rho[3]) const {
+ rho[0] = s;
+ rho[1] = 1;
+ rho[2] = 0;
+}
+
+void HuberLoss::Evaluate(double s, double rho[3]) const {
+ if (s > b_) {
+ // Outlier region.
+ // 'r' is always positive.
+ const double r = sqrt(s);
+ rho[0] = 2 * a_ * r - b_;
+ rho[1] = a_ / r;
+ rho[2] = - rho[1] / (2 * s);
+ } else {
+ // Inlier region.
+ rho[0] = s;
+ rho[1] = 1;
+ rho[2] = 0;
+ }
+}
+
+void SoftLOneLoss::Evaluate(double s, double rho[3]) const {
+ const double sum = 1 + s * c_;
+ const double tmp = sqrt(sum);
+ // 'sum' and 'tmp' are always positive, assuming that 's' is.
+ rho[0] = 2 * b_ * (tmp - 1);
+ rho[1] = 1 / tmp;
+ rho[2] = - (c_ * rho[1]) / (2 * sum);
+}
+
+void CauchyLoss::Evaluate(double s, double rho[3]) const {
+ const double sum = 1 + s * c_;
+ const double inv = 1 / sum;
+ // 'sum' and 'inv' are always positive, assuming that 's' is.
+ rho[0] = b_ * log(sum);
+ rho[1] = inv;
+ rho[2] = - c_ * (inv * inv);
+}
+
+void ScaledLoss::Evaluate(double s, double rho[3]) const {
+ if (rho_.get() == NULL) {
+ rho[0] = a_ * s;
+ rho[1] = a_;
+ rho[2] = 0.0;
+ } else {
+ rho_->Evaluate(s, rho);
+ rho[0] *= a_;
+ rho[1] *= a_;
+ rho[2] *= a_;
+ }
+}
+
+} // namespace ceres