Remove RuntimeNumericDiffCostFunction.
Move the GradientCheckingCostFunction to DynamicNumericDiffCostFunction.
Also fix a const correctness issue with DynamicNumericDiffCostFunction.
Change-Id: Id446810f43374e7b7db7fe4dd01a891e3c54abb9
diff --git a/internal/ceres/CMakeLists.txt b/internal/ceres/CMakeLists.txt
index 31d737d..cefe809 100644
--- a/internal/ceres/CMakeLists.txt
+++ b/internal/ceres/CMakeLists.txt
@@ -86,7 +86,6 @@
program.cc
residual_block.cc
residual_block_utils.cc
- runtime_numeric_diff_cost_function.cc
schur_complement_solver.cc
schur_eliminator.cc
schur_jacobi_preconditioner.cc
@@ -247,7 +246,6 @@
CERES_TEST(residual_block)
CERES_TEST(residual_block_utils)
CERES_TEST(rotation)
- CERES_TEST(runtime_numeric_diff_cost_function)
CERES_TEST(schur_complement_solver)
CERES_TEST(schur_eliminator)
CERES_TEST(small_blas)
diff --git a/internal/ceres/gradient_checking_cost_function.cc b/internal/ceres/gradient_checking_cost_function.cc
index 3edf95d..5503013 100644
--- a/internal/ceres/gradient_checking_cost_function.cc
+++ b/internal/ceres/gradient_checking_cost_function.cc
@@ -44,7 +44,7 @@
#include "ceres/problem_impl.h"
#include "ceres/program.h"
#include "ceres/residual_block.h"
-#include "ceres/runtime_numeric_diff_cost_function.h"
+#include "ceres/dynamic_numeric_diff_cost_function.h"
#include "ceres/stringprintf.h"
#include "ceres/types.h"
#include "glog/logging.h"
@@ -84,14 +84,24 @@
double relative_precision,
const string& extra_info)
: function_(function),
- finite_diff_cost_function_(
- CreateRuntimeNumericDiffCostFunction(function,
- CENTRAL,
- relative_step_size)),
relative_precision_(relative_precision),
extra_info_(extra_info) {
- *mutable_parameter_block_sizes() = function->parameter_block_sizes();
+ DynamicNumericDiffCostFunction<CostFunction, CENTRAL>*
+ finite_diff_cost_function =
+ new DynamicNumericDiffCostFunction<CostFunction, CENTRAL>(
+ function,
+ DO_NOT_TAKE_OWNERSHIP,
+ relative_step_size);
+
+ const vector<int16>& parameter_block_sizes =
+ function->parameter_block_sizes();
+ for (int i = 0; i < parameter_block_sizes.size(); ++i) {
+ finite_diff_cost_function->AddParameterBlock(parameter_block_sizes[i]);
+ }
+ *mutable_parameter_block_sizes() = parameter_block_sizes;
set_num_residuals(function->num_residuals());
+ finite_diff_cost_function->SetNumResiduals(num_residuals());
+ finite_diff_cost_function_.reset(finite_diff_cost_function);
}
virtual ~GradientCheckingCostFunction() { }
diff --git a/internal/ceres/runtime_numeric_diff_cost_function.cc b/internal/ceres/runtime_numeric_diff_cost_function.cc
deleted file mode 100644
index 7af275c..0000000
--- a/internal/ceres/runtime_numeric_diff_cost_function.cc
+++ /dev/null
@@ -1,217 +0,0 @@
-// 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: keir@google.com (Keir Mierle)
-//
-// Based on the templated version in public/numeric_diff_cost_function.h.
-
-#include "ceres/runtime_numeric_diff_cost_function.h"
-
-#include <algorithm>
-#include <numeric>
-#include <vector>
-#include "Eigen/Dense"
-#include "ceres/cost_function.h"
-#include "ceres/internal/scoped_ptr.h"
-#include "glog/logging.h"
-
-namespace ceres {
-namespace internal {
-namespace {
-
-bool EvaluateJacobianForParameterBlock(const CostFunction* function,
- int parameter_block_size,
- int parameter_block,
- RuntimeNumericDiffMethod method,
- double relative_step_size,
- double const* residuals_at_eval_point,
- double** parameters,
- double** jacobians) {
- using Eigen::Map;
- using Eigen::Matrix;
- using Eigen::Dynamic;
- using Eigen::RowMajor;
-
- typedef Matrix<double, Dynamic, 1> ResidualVector;
- typedef Matrix<double, Dynamic, 1> ParameterVector;
- typedef Matrix<double, Dynamic, Dynamic, RowMajor> JacobianMatrix;
-
- int num_residuals = function->num_residuals();
-
- Map<JacobianMatrix> parameter_jacobian(jacobians[parameter_block],
- num_residuals,
- parameter_block_size);
-
- // Mutate one element at a time and then restore.
- Map<ParameterVector> x_plus_delta(parameters[parameter_block],
- parameter_block_size);
- ParameterVector x(x_plus_delta);
- ParameterVector step_size = x.array().abs() * relative_step_size;
-
- // To handle cases where a paremeter is exactly zero, instead use the mean
- // step_size for the other dimensions.
- double fallback_step_size = step_size.sum() / step_size.rows();
- if (fallback_step_size == 0.0) {
- // If all the parameters are zero, there's no good answer. Use the given
- // relative step_size as absolute step_size and hope for the best.
- fallback_step_size = relative_step_size;
- }
-
- // For each parameter in the parameter block, use finite differences to
- // compute the derivative for that parameter.
- for (int j = 0; j < parameter_block_size; ++j) {
- if (step_size(j) == 0.0) {
- // The parameter is exactly zero, so compromise and use the mean step_size
- // from the other parameters. This can break in many cases, but it's hard
- // to pick a good number without problem specific knowledge.
- step_size(j) = fallback_step_size;
- }
- x_plus_delta(j) = x(j) + step_size(j);
-
- ResidualVector residuals(num_residuals);
- if (!function->Evaluate(parameters, &residuals[0], NULL)) {
- // Something went wrong; bail.
- return false;
- }
-
- // Compute this column of the jacobian in 3 steps:
- // 1. Store residuals for the forward part.
- // 2. Subtract residuals for the backward (or 0) part.
- // 3. Divide out the run.
- parameter_jacobian.col(j) = residuals;
-
- double one_over_h = 1 / step_size(j);
- if (method == CENTRAL) {
- // Compute the function on the other side of x(j).
- x_plus_delta(j) = x(j) - step_size(j);
-
- if (!function->Evaluate(parameters, &residuals[0], NULL)) {
- // Something went wrong; bail.
- return false;
- }
- parameter_jacobian.col(j) -= residuals;
- one_over_h /= 2;
- } else {
- // Forward difference only; reuse existing residuals evaluation.
- parameter_jacobian.col(j) -=
- Map<const ResidualVector>(residuals_at_eval_point, num_residuals);
- }
- x_plus_delta(j) = x(j); // Restore x_plus_delta.
-
- // Divide out the run to get slope.
- parameter_jacobian.col(j) *= one_over_h;
- }
- return true;
-}
-
-class RuntimeNumericDiffCostFunction : public CostFunction {
- public:
- RuntimeNumericDiffCostFunction(const CostFunction* function,
- RuntimeNumericDiffMethod method,
- double relative_step_size)
- : function_(function),
- method_(method),
- relative_step_size_(relative_step_size) {
- *mutable_parameter_block_sizes() = function->parameter_block_sizes();
- set_num_residuals(function->num_residuals());
- }
-
- virtual ~RuntimeNumericDiffCostFunction() { }
-
- virtual bool Evaluate(double const* const* parameters,
- double* residuals,
- double** jacobians) const {
- // Get the function value (residuals) at the the point to evaluate.
- bool success = function_->Evaluate(parameters, residuals, NULL);
- if (!success) {
- // Something went wrong; ignore the jacobian.
- return false;
- }
- if (!jacobians) {
- // Nothing to do; just forward.
- return true;
- }
-
- const vector<int16>& block_sizes = function_->parameter_block_sizes();
- CHECK(!block_sizes.empty());
-
- // Create local space for a copy of the parameters which will get mutated.
- int parameters_size = accumulate(block_sizes.begin(), block_sizes.end(), 0);
- vector<double> parameters_copy(parameters_size);
- vector<double*> parameters_references_copy(block_sizes.size());
- parameters_references_copy[0] = ¶meters_copy[0];
- for (int block = 1; block < block_sizes.size(); ++block) {
- parameters_references_copy[block] = parameters_references_copy[block - 1]
- + block_sizes[block - 1];
- }
-
- // Copy the parameters into the local temp space.
- for (int block = 0; block < block_sizes.size(); ++block) {
- memcpy(parameters_references_copy[block],
- parameters[block],
- block_sizes[block] * sizeof(*parameters[block]));
- }
-
- for (int block = 0; block < block_sizes.size(); ++block) {
- if (!jacobians[block]) {
- // No jacobian requested for this parameter / residual pair.
- continue;
- }
- if (!EvaluateJacobianForParameterBlock(function_,
- block_sizes[block],
- block,
- method_,
- relative_step_size_,
- residuals,
- ¶meters_references_copy[0],
- jacobians)) {
- return false;
- }
- }
- return true;
- }
-
- private:
- const CostFunction* function_;
- RuntimeNumericDiffMethod method_;
- double relative_step_size_;
-};
-
-} // namespace
-
-CostFunction* CreateRuntimeNumericDiffCostFunction(
- const CostFunction* cost_function,
- RuntimeNumericDiffMethod method,
- double relative_step_size) {
- return new RuntimeNumericDiffCostFunction(cost_function,
- method,
- relative_step_size);
-}
-
-} // namespace internal
-} // namespace ceres
diff --git a/internal/ceres/runtime_numeric_diff_cost_function.h b/internal/ceres/runtime_numeric_diff_cost_function.h
deleted file mode 100644
index 01b57f9..0000000
--- a/internal/ceres/runtime_numeric_diff_cost_function.h
+++ /dev/null
@@ -1,87 +0,0 @@
-// 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: keir@google.com (Keir Mierle)
-//
-// Create CostFunctions as needed by the least squares framework with jacobians
-// computed via numeric differentiation.
-//
-// To get a numerically differentiated cost function, define a subclass of
-// CostFunction such that the Evaluate() function ignores the jacobian
-// parameter. The numeric differentiation wrapper will fill in the jacobian
-// parameter if nececssary by repeatedly calling the Evaluate() function with
-// small changes to the appropriate parameters, and computing the slope. This
-// implementation is not templated (hence the "Runtime" prefix), which is a bit
-// slower than but is more convenient than the templated version in
-// numeric_diff_cost_function.h
-//
-// The numerically differentiated version of a cost function for a cost function
-// can be constructed as follows:
-//
-// CostFunction* cost_function =
-// CreateRuntimeNumericDiffCostFunction(new MyCostFunction(...),
-// CENTRAL,
-// TAKE_OWNERSHIP);
-//
-// The central difference method is considerably more accurate; consider using
-// to start and only after that works, trying forward difference.
-//
-// TODO(keir): Characterize accuracy; mention pitfalls; provide alternatives.
-
-#ifndef CERES_INTERNAL_RUNTIME_NUMERIC_DIFF_COST_FUNCTION_H_
-#define CERES_INTERNAL_RUNTIME_NUMERIC_DIFF_COST_FUNCTION_H_
-
-#include "ceres/cost_function.h"
-
-namespace ceres {
-namespace internal {
-
-enum RuntimeNumericDiffMethod {
- CENTRAL,
- FORWARD,
-};
-
-// Create a cost function that evaluates the derivative with finite differences.
-// The base cost_function's implementation of Evaluate() only needs to fill in
-// the "residuals" argument and not the "jacobians". Any data written to the
-// jacobians by the base cost_function is overwritten.
-//
-// Forward difference or central difference is selected with CENTRAL or FORWARD.
-// The relative eps, which determines the step size for forward and central
-// differencing, is set with relative eps. Caller owns the resulting cost
-// function, and the resulting cost function does not own the base cost
-// function.
-CostFunction *CreateRuntimeNumericDiffCostFunction(
- const CostFunction *cost_function,
- RuntimeNumericDiffMethod method,
- double relative_eps);
-
-} // namespace internal
-} // namespace ceres
-
-#endif // CERES_INTERNAL_RUNTIME_NUMERIC_DIFF_COST_FUNCTION_H_
diff --git a/internal/ceres/runtime_numeric_diff_cost_function_test.cc b/internal/ceres/runtime_numeric_diff_cost_function_test.cc
deleted file mode 100644
index 71469ea..0000000
--- a/internal/ceres/runtime_numeric_diff_cost_function_test.cc
+++ /dev/null
@@ -1,222 +0,0 @@
-// 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: keir@google.com (Keir Mierle)
-//
-// Based on the tests in numeric_diff_cost_function.cc.
-//
-// TODO(keir): See about code duplication.
-
-#include "ceres/runtime_numeric_diff_cost_function.h"
-
-#include <algorithm>
-#include <cmath>
-#include <string>
-#include <vector>
-#include "ceres/cost_function.h"
-#include "ceres/internal/macros.h"
-#include "ceres/internal/scoped_ptr.h"
-#include "ceres/stringprintf.h"
-#include "ceres/test_util.h"
-#include "glog/logging.h"
-#include "gtest/gtest.h"
-
-namespace ceres {
-namespace internal {
-
-const double kRelativeEps = 1e-6;
-
-// y1 = x1'x2 -> dy1/dx1 = x2, dy1/dx2 = x1
-// y2 = (x1'x2)^2 -> dy2/dx1 = 2 * x2 * (x1'x2), dy2/dx2 = 2 * x1 * (x1'x2)
-// y3 = x2'x2 -> dy3/dx1 = 0, dy3/dx2 = 2 * x2
-class TestCostFunction : public CostFunction {
- public:
- TestCostFunction() {
- set_num_residuals(3);
- mutable_parameter_block_sizes()->push_back(5); // x1.
- mutable_parameter_block_sizes()->push_back(5); // x2.
- }
- virtual bool Evaluate(double const* const* parameters,
- double* residuals,
- double** jacobians) const {
- (void) jacobians; // Ignored.
-
- residuals[0] = residuals[1] = residuals[2] = 0;
- for (int i = 0; i < 5; ++i) {
- residuals[0] += parameters[0][i] * parameters[1][i];
- residuals[2] += parameters[1][i] * parameters[1][i];
- }
- residuals[1] = residuals[0] * residuals[0];
- return true;
- }
-};
-
-TEST(NumericDiffCostFunction, EasyCase) {
- // Try both central and forward difference.
- TestCostFunction term;
- scoped_ptr<CostFunction> cfs[2];
- cfs[0].reset(
- CreateRuntimeNumericDiffCostFunction(&term, CENTRAL, kRelativeEps));
-
- cfs[1].reset(
- CreateRuntimeNumericDiffCostFunction(&term, FORWARD, kRelativeEps));
-
-
- for (int c = 0; c < 2; ++c) {
- CostFunction *cost_function = cfs[c].get();
-
- double x1[] = { 1.0, 2.0, 3.0, 4.0, 5.0 };
- double x2[] = { 9.0, 9.0, 5.0, 5.0, 1.0 };
- double *parameters[] = { &x1[0], &x2[0] };
-
- double dydx1[15]; // 3 x 5, row major.
- double dydx2[15]; // 3 x 5, row major.
- double *jacobians[2] = { &dydx1[0], &dydx2[0] };
-
- double residuals[3] = {-1e-100, -2e-100, -3e-100 };
-
- ASSERT_TRUE(cost_function->Evaluate(¶meters[0],
- &residuals[0],
- &jacobians[0]));
-
- EXPECT_EQ(residuals[0], 67);
- EXPECT_EQ(residuals[1], 4489);
- EXPECT_EQ(residuals[2], 213);
-
- for (int i = 0; i < 5; ++i) {
- LOG(INFO) << "c = " << c << " i = " << i;
- const double kEps = c == 0 ? /* central */ 3e-9 : /* forward */ 2e-5;
-
- ExpectClose(x2[i], dydx1[5 * 0 + i], kEps); // y1
- ExpectClose(x1[i], dydx2[5 * 0 + i], kEps);
- ExpectClose(2 * x2[i] * residuals[0], dydx1[5 * 1 + i], kEps); // y2
- ExpectClose(2 * x1[i] * residuals[0], dydx2[5 * 1 + i], kEps);
- ExpectClose(0.0, dydx1[5 * 2 + i], kEps); // y3
- ExpectClose(2 * x2[i], dydx2[5 * 2 + i], kEps);
- }
- }
-}
-
-// y1 = sin(x1'x2)
-// y2 = exp(-x1'x2 / 10)
-//
-// dy1/dx1 = x2 * cos(x1'x2), dy1/dx2 = x1 * cos(x1'x2)
-// dy2/dx1 = -x2 * exp(-x1'x2 / 10) / 10, dy2/dx2 = -x2 * exp(-x1'x2 / 10) / 10
-class TranscendentalTestCostFunction : public CostFunction {
- public:
- TranscendentalTestCostFunction() {
- set_num_residuals(2);
- mutable_parameter_block_sizes()->push_back(5); // x1.
- mutable_parameter_block_sizes()->push_back(5); // x2.
- }
- virtual bool Evaluate(double const* const* parameters,
- double* residuals,
- double** jacobians) const {
- (void) jacobians; // Ignored.
-
- double x1x2 = 0;
- for (int i = 0; i < 5; ++i) {
- x1x2 += parameters[0][i] * parameters[1][i];
- }
- residuals[0] = sin(x1x2);
- residuals[1] = exp(-x1x2 / 10);
- return true;
- }
-};
-
-TEST(NumericDiffCostFunction, TransendentalOperationsInCostFunction) {
- // Try both central and forward difference.
- TranscendentalTestCostFunction term;
- scoped_ptr<CostFunction> cfs[2];
- cfs[0].reset(
- CreateRuntimeNumericDiffCostFunction(&term, CENTRAL, kRelativeEps));
-
- cfs[1].reset(
- CreateRuntimeNumericDiffCostFunction(&term, FORWARD, kRelativeEps));
-
- for (int c = 0; c < 2; ++c) {
- CostFunction *cost_function = cfs[c].get();
-
- struct {
- double x1[5];
- double x2[5];
- } kTests[] = {
- { { 1.0, 2.0, 3.0, 4.0, 5.0 }, // No zeros.
- { 9.0, 9.0, 5.0, 5.0, 1.0 },
- },
- { { 0.0, 2.0, 3.0, 0.0, 5.0 }, // Some zeros x1.
- { 9.0, 9.0, 5.0, 5.0, 1.0 },
- },
- { { 1.0, 2.0, 3.0, 1.0, 5.0 }, // Some zeros x2.
- { 0.0, 9.0, 0.0, 5.0, 0.0 },
- },
- { { 0.0, 0.0, 0.0, 0.0, 0.0 }, // All zeros x1.
- { 9.0, 9.0, 5.0, 5.0, 1.0 },
- },
- { { 1.0, 2.0, 3.0, 4.0, 5.0 }, // All zeros x2.
- { 0.0, 0.0, 0.0, 0.0, 0.0 },
- },
- { { 0.0, 0.0, 0.0, 0.0, 0.0 }, // All zeros.
- { 0.0, 0.0, 0.0, 0.0, 0.0 },
- },
- };
- for (int k = 0; k < CERES_ARRAYSIZE(kTests); ++k) {
- double *x1 = &(kTests[k].x1[0]);
- double *x2 = &(kTests[k].x2[0]);
- double *parameters[] = { x1, x2 };
-
- double dydx1[10];
- double dydx2[10];
- double *jacobians[2] = { &dydx1[0], &dydx2[0] };
-
- double residuals[2];
-
- ASSERT_TRUE(cost_function->Evaluate(¶meters[0],
- &residuals[0],
- &jacobians[0]));
- LOG(INFO) << "Ran evaluate for test k=" << k << " c=" << c;
-
- double x1x2 = 0;
- for (int i = 0; i < 5; ++i) {
- x1x2 += x1[i] * x2[i];
- }
-
- for (int i = 0; i < 5; ++i) {
- const double kEps = (c == 0 ? /* central */ 3e-9 : /* forward */ 2e-5);
-
- ExpectClose( x2[i] * cos(x1x2), dydx1[5 * 0 + i], kEps); // NOLINT
- ExpectClose( x1[i] * cos(x1x2), dydx2[5 * 0 + i], kEps); // NOLINT
- ExpectClose(-x2[i] * exp(-x1x2 / 10.) / 10., dydx1[5 * 1 + i], kEps);
- ExpectClose(-x1[i] * exp(-x1x2 / 10.) / 10., dydx2[5 * 1 + i], kEps);
- }
- }
- }
-}
-
-} // namespace internal
-} // namespace ceres
