1 // Ceres Solver - A fast non-linear least squares minimizer
2 // Copyright 2012 Google Inc. All rights reserved.
3 // http://code.google.com/p/ceres-solver/
4 //
5 // Redistribution and use in source and binary forms, with or without
6 // modification, are permitted provided that the following conditions are met:
7 //
8 // * Redistributions of source code must retain the above copyright notice,
9 // this list of conditions and the following disclaimer.
10 // * Redistributions in binary form must reproduce the above copyright notice,
11 // this list of conditions and the following disclaimer in the documentation
12 // and/or other materials provided with the distribution.
13 // * Neither the name of Google Inc. nor the names of its contributors may be
14 // used to endorse or promote products derived from this software without
15 // specific prior written permission.
16 //
17 // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
18 // AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
19 // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
20 // ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
21 // LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
22 // CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
23 // SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
24 // INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
25 // CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
26 // ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
27 // POSSIBILITY OF SUCH DAMAGE.
28 //
29 // Author: moll.markus@arcor.de (Markus Moll)
30 // sameeragarwal@google.com (Sameer Agarwal)
31
32 #include "ceres/polynomial.h"
33
34 #include <limits>
35 #include <cmath>
36 #include <cstddef>
37 #include <algorithm>
38 #include "gtest/gtest.h"
39 #include "ceres/test_util.h"
40
41 namespace ceres {
42 namespace internal {
43 namespace {
44
45 // For IEEE-754 doubles, machine precision is about 2e-16.
46 const double kEpsilon = 1e-13;
47 const double kEpsilonLoose = 1e-9;
48
49 // Return the constant polynomial p(x) = 1.23.
ConstantPolynomial(double value)50 Vector ConstantPolynomial(double value) {
51 Vector poly(1);
52 poly(0) = value;
53 return poly;
54 }
55
56 // Return the polynomial p(x) = poly(x) * (x - root).
AddRealRoot(const Vector & poly,double root)57 Vector AddRealRoot(const Vector& poly, double root) {
58 Vector poly2(poly.size() + 1);
59 poly2.setZero();
60 poly2.head(poly.size()) += poly;
61 poly2.tail(poly.size()) -= root * poly;
62 return poly2;
63 }
64
65 // Return the polynomial
66 // p(x) = poly(x) * (x - real - imag*i) * (x - real + imag*i).
AddComplexRootPair(const Vector & poly,double real,double imag)67 Vector AddComplexRootPair(const Vector& poly, double real, double imag) {
68 Vector poly2(poly.size() + 2);
69 poly2.setZero();
70 // Multiply poly by x^2 - 2real + abs(real,imag)^2
71 poly2.head(poly.size()) += poly;
72 poly2.segment(1, poly.size()) -= 2 * real * poly;
73 poly2.tail(poly.size()) += (real*real + imag*imag) * poly;
74 return poly2;
75 }
76
77 // Sort the entries in a vector.
78 // Needed because the roots are not returned in sorted order.
SortVector(const Vector & in)79 Vector SortVector(const Vector& in) {
80 Vector out(in);
81 std::sort(out.data(), out.data() + out.size());
82 return out;
83 }
84
85 // Run a test with the polynomial defined by the N real roots in roots_real.
86 // If use_real is false, NULL is passed as the real argument to
87 // FindPolynomialRoots. If use_imaginary is false, NULL is passed as the
88 // imaginary argument to FindPolynomialRoots.
89 template<int N>
RunPolynomialTestRealRoots(const double (& real_roots)[N],bool use_real,bool use_imaginary,double epsilon)90 void RunPolynomialTestRealRoots(const double (&real_roots)[N],
91 bool use_real,
92 bool use_imaginary,
93 double epsilon) {
94 Vector real;
95 Vector imaginary;
96 Vector poly = ConstantPolynomial(1.23);
97 for (int i = 0; i < N; ++i) {
98 poly = AddRealRoot(poly, real_roots[i]);
99 }
100 Vector* const real_ptr = use_real ? &real : NULL;
101 Vector* const imaginary_ptr = use_imaginary ? &imaginary : NULL;
102 bool success = FindPolynomialRoots(poly, real_ptr, imaginary_ptr);
103
104 EXPECT_EQ(success, true);
105 if (use_real) {
106 EXPECT_EQ(real.size(), N);
107 real = SortVector(real);
108 ExpectArraysClose(N, real.data(), real_roots, epsilon);
109 }
110 if (use_imaginary) {
111 EXPECT_EQ(imaginary.size(), N);
112 const Vector zeros = Vector::Zero(N);
113 ExpectArraysClose(N, imaginary.data(), zeros.data(), epsilon);
114 }
115 }
116 } // namespace
117
TEST(Polynomial,InvalidPolynomialOfZeroLengthIsRejected)118 TEST(Polynomial, InvalidPolynomialOfZeroLengthIsRejected) {
119 // Vector poly(0) is an ambiguous constructor call, so
120 // use the constructor with explicit column count.
121 Vector poly(0, 1);
122 Vector real;
123 Vector imag;
124 bool success = FindPolynomialRoots(poly, &real, &imag);
125
126 EXPECT_EQ(success, false);
127 }
128
TEST(Polynomial,ConstantPolynomialReturnsNoRoots)129 TEST(Polynomial, ConstantPolynomialReturnsNoRoots) {
130 Vector poly = ConstantPolynomial(1.23);
131 Vector real;
132 Vector imag;
133 bool success = FindPolynomialRoots(poly, &real, &imag);
134
135 EXPECT_EQ(success, true);
136 EXPECT_EQ(real.size(), 0);
137 EXPECT_EQ(imag.size(), 0);
138 }
139
TEST(Polynomial,LinearPolynomialWithPositiveRootWorks)140 TEST(Polynomial, LinearPolynomialWithPositiveRootWorks) {
141 const double roots[1] = { 42.42 };
142 RunPolynomialTestRealRoots(roots, true, true, kEpsilon);
143 }
144
TEST(Polynomial,LinearPolynomialWithNegativeRootWorks)145 TEST(Polynomial, LinearPolynomialWithNegativeRootWorks) {
146 const double roots[1] = { -42.42 };
147 RunPolynomialTestRealRoots(roots, true, true, kEpsilon);
148 }
149
TEST(Polynomial,QuadraticPolynomialWithPositiveRootsWorks)150 TEST(Polynomial, QuadraticPolynomialWithPositiveRootsWorks) {
151 const double roots[2] = { 1.0, 42.42 };
152 RunPolynomialTestRealRoots(roots, true, true, kEpsilon);
153 }
154
TEST(Polynomial,QuadraticPolynomialWithOneNegativeRootWorks)155 TEST(Polynomial, QuadraticPolynomialWithOneNegativeRootWorks) {
156 const double roots[2] = { -42.42, 1.0 };
157 RunPolynomialTestRealRoots(roots, true, true, kEpsilon);
158 }
159
TEST(Polynomial,QuadraticPolynomialWithTwoNegativeRootsWorks)160 TEST(Polynomial, QuadraticPolynomialWithTwoNegativeRootsWorks) {
161 const double roots[2] = { -42.42, -1.0 };
162 RunPolynomialTestRealRoots(roots, true, true, kEpsilon);
163 }
164
TEST(Polynomial,QuadraticPolynomialWithCloseRootsWorks)165 TEST(Polynomial, QuadraticPolynomialWithCloseRootsWorks) {
166 const double roots[2] = { 42.42, 42.43 };
167 RunPolynomialTestRealRoots(roots, true, false, kEpsilonLoose);
168 }
169
TEST(Polynomial,QuadraticPolynomialWithComplexRootsWorks)170 TEST(Polynomial, QuadraticPolynomialWithComplexRootsWorks) {
171 Vector real;
172 Vector imag;
173
174 Vector poly = ConstantPolynomial(1.23);
175 poly = AddComplexRootPair(poly, 42.42, 4.2);
176 bool success = FindPolynomialRoots(poly, &real, &imag);
177
178 EXPECT_EQ(success, true);
179 EXPECT_EQ(real.size(), 2);
180 EXPECT_EQ(imag.size(), 2);
181 ExpectClose(real(0), 42.42, kEpsilon);
182 ExpectClose(real(1), 42.42, kEpsilon);
183 ExpectClose(std::abs(imag(0)), 4.2, kEpsilon);
184 ExpectClose(std::abs(imag(1)), 4.2, kEpsilon);
185 ExpectClose(std::abs(imag(0) + imag(1)), 0.0, kEpsilon);
186 }
187
TEST(Polynomial,QuarticPolynomialWorks)188 TEST(Polynomial, QuarticPolynomialWorks) {
189 const double roots[4] = { 1.23e-4, 1.23e-1, 1.23e+2, 1.23e+5 };
190 RunPolynomialTestRealRoots(roots, true, true, kEpsilon);
191 }
192
TEST(Polynomial,QuarticPolynomialWithTwoClustersOfCloseRootsWorks)193 TEST(Polynomial, QuarticPolynomialWithTwoClustersOfCloseRootsWorks) {
194 const double roots[4] = { 1.23e-1, 2.46e-1, 1.23e+5, 2.46e+5 };
195 RunPolynomialTestRealRoots(roots, true, true, kEpsilonLoose);
196 }
197
TEST(Polynomial,QuarticPolynomialWithTwoZeroRootsWorks)198 TEST(Polynomial, QuarticPolynomialWithTwoZeroRootsWorks) {
199 const double roots[4] = { -42.42, 0.0, 0.0, 42.42 };
200 RunPolynomialTestRealRoots(roots, true, true, kEpsilonLoose);
201 }
202
TEST(Polynomial,QuarticMonomialWorks)203 TEST(Polynomial, QuarticMonomialWorks) {
204 const double roots[4] = { 0.0, 0.0, 0.0, 0.0 };
205 RunPolynomialTestRealRoots(roots, true, true, kEpsilon);
206 }
207
TEST(Polynomial,NullPointerAsImaginaryPartWorks)208 TEST(Polynomial, NullPointerAsImaginaryPartWorks) {
209 const double roots[4] = { 1.23e-4, 1.23e-1, 1.23e+2, 1.23e+5 };
210 RunPolynomialTestRealRoots(roots, true, false, kEpsilon);
211 }
212
TEST(Polynomial,NullPointerAsRealPartWorks)213 TEST(Polynomial, NullPointerAsRealPartWorks) {
214 const double roots[4] = { 1.23e-4, 1.23e-1, 1.23e+2, 1.23e+5 };
215 RunPolynomialTestRealRoots(roots, false, true, kEpsilon);
216 }
217
TEST(Polynomial,BothOutputArgumentsNullWorks)218 TEST(Polynomial, BothOutputArgumentsNullWorks) {
219 const double roots[4] = { 1.23e-4, 1.23e-1, 1.23e+2, 1.23e+5 };
220 RunPolynomialTestRealRoots(roots, false, false, kEpsilon);
221 }
222
TEST(Polynomial,DifferentiateConstantPolynomial)223 TEST(Polynomial, DifferentiateConstantPolynomial) {
224 // p(x) = 1;
225 Vector polynomial(1);
226 polynomial(0) = 1.0;
227 const Vector derivative = DifferentiatePolynomial(polynomial);
228 EXPECT_EQ(derivative.rows(), 1);
229 EXPECT_EQ(derivative(0), 0);
230 }
231
TEST(Polynomial,DifferentiateQuadraticPolynomial)232 TEST(Polynomial, DifferentiateQuadraticPolynomial) {
233 // p(x) = x^2 + 2x + 3;
234 Vector polynomial(3);
235 polynomial(0) = 1.0;
236 polynomial(1) = 2.0;
237 polynomial(2) = 3.0;
238
239 const Vector derivative = DifferentiatePolynomial(polynomial);
240 EXPECT_EQ(derivative.rows(), 2);
241 EXPECT_EQ(derivative(0), 2.0);
242 EXPECT_EQ(derivative(1), 2.0);
243 }
244
TEST(Polynomial,MinimizeConstantPolynomial)245 TEST(Polynomial, MinimizeConstantPolynomial) {
246 // p(x) = 1;
247 Vector polynomial(1);
248 polynomial(0) = 1.0;
249
250 double optimal_x = 0.0;
251 double optimal_value = 0.0;
252 double min_x = 0.0;
253 double max_x = 1.0;
254 MinimizePolynomial(polynomial, min_x, max_x, &optimal_x, &optimal_value);
255
256 EXPECT_EQ(optimal_value, 1.0);
257 EXPECT_LE(optimal_x, max_x);
258 EXPECT_GE(optimal_x, min_x);
259 }
260
TEST(Polynomial,MinimizeLinearPolynomial)261 TEST(Polynomial, MinimizeLinearPolynomial) {
262 // p(x) = x - 2
263 Vector polynomial(2);
264
265 polynomial(0) = 1.0;
266 polynomial(1) = 2.0;
267
268 double optimal_x = 0.0;
269 double optimal_value = 0.0;
270 double min_x = 0.0;
271 double max_x = 1.0;
272 MinimizePolynomial(polynomial, min_x, max_x, &optimal_x, &optimal_value);
273
274 EXPECT_EQ(optimal_x, 0.0);
275 EXPECT_EQ(optimal_value, 2.0);
276 }
277
278
TEST(Polynomial,MinimizeQuadraticPolynomial)279 TEST(Polynomial, MinimizeQuadraticPolynomial) {
280 // p(x) = x^2 - 3 x + 2
281 // min_x = 3/2
282 // min_value = -1/4;
283 Vector polynomial(3);
284 polynomial(0) = 1.0;
285 polynomial(1) = -3.0;
286 polynomial(2) = 2.0;
287
288 double optimal_x = 0.0;
289 double optimal_value = 0.0;
290 double min_x = -2.0;
291 double max_x = 2.0;
292 MinimizePolynomial(polynomial, min_x, max_x, &optimal_x, &optimal_value);
293 EXPECT_EQ(optimal_x, 3.0/2.0);
294 EXPECT_EQ(optimal_value, -1.0/4.0);
295
296 min_x = -2.0;
297 max_x = 1.0;
298 MinimizePolynomial(polynomial, min_x, max_x, &optimal_x, &optimal_value);
299 EXPECT_EQ(optimal_x, 1.0);
300 EXPECT_EQ(optimal_value, 0.0);
301
302 min_x = 2.0;
303 max_x = 3.0;
304 MinimizePolynomial(polynomial, min_x, max_x, &optimal_x, &optimal_value);
305 EXPECT_EQ(optimal_x, 2.0);
306 EXPECT_EQ(optimal_value, 0.0);
307 }
308
TEST(Polymomial,ConstantInterpolatingPolynomial)309 TEST(Polymomial, ConstantInterpolatingPolynomial) {
310 // p(x) = 1.0
311 Vector true_polynomial(1);
312 true_polynomial << 1.0;
313
314 vector<FunctionSample> samples;
315 FunctionSample sample;
316 sample.x = 1.0;
317 sample.value = 1.0;
318 sample.value_is_valid = true;
319 samples.push_back(sample);
320
321 const Vector polynomial = FindInterpolatingPolynomial(samples);
322 EXPECT_NEAR((true_polynomial - polynomial).norm(), 0.0, 1e-15);
323 }
324
TEST(Polynomial,LinearInterpolatingPolynomial)325 TEST(Polynomial, LinearInterpolatingPolynomial) {
326 // p(x) = 2x - 1
327 Vector true_polynomial(2);
328 true_polynomial << 2.0, -1.0;
329
330 vector<FunctionSample> samples;
331 FunctionSample sample;
332 sample.x = 1.0;
333 sample.value = 1.0;
334 sample.value_is_valid = true;
335 sample.gradient = 2.0;
336 sample.gradient_is_valid = true;
337 samples.push_back(sample);
338
339 const Vector polynomial = FindInterpolatingPolynomial(samples);
340 EXPECT_NEAR((true_polynomial - polynomial).norm(), 0.0, 1e-15);
341 }
342
TEST(Polynomial,QuadraticInterpolatingPolynomial)343 TEST(Polynomial, QuadraticInterpolatingPolynomial) {
344 // p(x) = 2x^2 + 3x + 2
345 Vector true_polynomial(3);
346 true_polynomial << 2.0, 3.0, 2.0;
347
348 vector<FunctionSample> samples;
349 {
350 FunctionSample sample;
351 sample.x = 1.0;
352 sample.value = 7.0;
353 sample.value_is_valid = true;
354 sample.gradient = 7.0;
355 sample.gradient_is_valid = true;
356 samples.push_back(sample);
357 }
358
359 {
360 FunctionSample sample;
361 sample.x = -3.0;
362 sample.value = 11.0;
363 sample.value_is_valid = true;
364 samples.push_back(sample);
365 }
366
367 Vector polynomial = FindInterpolatingPolynomial(samples);
368 EXPECT_NEAR((true_polynomial - polynomial).norm(), 0.0, 1e-15);
369 }
370
TEST(Polynomial,DeficientCubicInterpolatingPolynomial)371 TEST(Polynomial, DeficientCubicInterpolatingPolynomial) {
372 // p(x) = 2x^2 + 3x + 2
373 Vector true_polynomial(4);
374 true_polynomial << 0.0, 2.0, 3.0, 2.0;
375
376 vector<FunctionSample> samples;
377 {
378 FunctionSample sample;
379 sample.x = 1.0;
380 sample.value = 7.0;
381 sample.value_is_valid = true;
382 sample.gradient = 7.0;
383 sample.gradient_is_valid = true;
384 samples.push_back(sample);
385 }
386
387 {
388 FunctionSample sample;
389 sample.x = -3.0;
390 sample.value = 11.0;
391 sample.value_is_valid = true;
392 sample.gradient = -9;
393 sample.gradient_is_valid = true;
394 samples.push_back(sample);
395 }
396
397 const Vector polynomial = FindInterpolatingPolynomial(samples);
398 EXPECT_NEAR((true_polynomial - polynomial).norm(), 0.0, 1e-14);
399 }
400
401
TEST(Polynomial,CubicInterpolatingPolynomialFromValues)402 TEST(Polynomial, CubicInterpolatingPolynomialFromValues) {
403 // p(x) = x^3 + 2x^2 + 3x + 2
404 Vector true_polynomial(4);
405 true_polynomial << 1.0, 2.0, 3.0, 2.0;
406
407 vector<FunctionSample> samples;
408 {
409 FunctionSample sample;
410 sample.x = 1.0;
411 sample.value = EvaluatePolynomial(true_polynomial, sample.x);
412 sample.value_is_valid = true;
413 samples.push_back(sample);
414 }
415
416 {
417 FunctionSample sample;
418 sample.x = -3.0;
419 sample.value = EvaluatePolynomial(true_polynomial, sample.x);
420 sample.value_is_valid = true;
421 samples.push_back(sample);
422 }
423
424 {
425 FunctionSample sample;
426 sample.x = 2.0;
427 sample.value = EvaluatePolynomial(true_polynomial, sample.x);
428 sample.value_is_valid = true;
429 samples.push_back(sample);
430 }
431
432 {
433 FunctionSample sample;
434 sample.x = 0.0;
435 sample.value = EvaluatePolynomial(true_polynomial, sample.x);
436 sample.value_is_valid = true;
437 samples.push_back(sample);
438 }
439
440 const Vector polynomial = FindInterpolatingPolynomial(samples);
441 EXPECT_NEAR((true_polynomial - polynomial).norm(), 0.0, 1e-14);
442 }
443
TEST(Polynomial,CubicInterpolatingPolynomialFromValuesAndOneGradient)444 TEST(Polynomial, CubicInterpolatingPolynomialFromValuesAndOneGradient) {
445 // p(x) = x^3 + 2x^2 + 3x + 2
446 Vector true_polynomial(4);
447 true_polynomial << 1.0, 2.0, 3.0, 2.0;
448 Vector true_gradient_polynomial = DifferentiatePolynomial(true_polynomial);
449
450 vector<FunctionSample> samples;
451 {
452 FunctionSample sample;
453 sample.x = 1.0;
454 sample.value = EvaluatePolynomial(true_polynomial, sample.x);
455 sample.value_is_valid = true;
456 samples.push_back(sample);
457 }
458
459 {
460 FunctionSample sample;
461 sample.x = -3.0;
462 sample.value = EvaluatePolynomial(true_polynomial, sample.x);
463 sample.value_is_valid = true;
464 samples.push_back(sample);
465 }
466
467 {
468 FunctionSample sample;
469 sample.x = 2.0;
470 sample.value = EvaluatePolynomial(true_polynomial, sample.x);
471 sample.value_is_valid = true;
472 sample.gradient = EvaluatePolynomial(true_gradient_polynomial, sample.x);
473 sample.gradient_is_valid = true;
474 samples.push_back(sample);
475 }
476
477 const Vector polynomial = FindInterpolatingPolynomial(samples);
478 EXPECT_NEAR((true_polynomial - polynomial).norm(), 0.0, 1e-14);
479 }
480
TEST(Polynomial,CubicInterpolatingPolynomialFromValuesAndGradients)481 TEST(Polynomial, CubicInterpolatingPolynomialFromValuesAndGradients) {
482 // p(x) = x^3 + 2x^2 + 3x + 2
483 Vector true_polynomial(4);
484 true_polynomial << 1.0, 2.0, 3.0, 2.0;
485 Vector true_gradient_polynomial = DifferentiatePolynomial(true_polynomial);
486
487 vector<FunctionSample> samples;
488 {
489 FunctionSample sample;
490 sample.x = -3.0;
491 sample.value = EvaluatePolynomial(true_polynomial, sample.x);
492 sample.value_is_valid = true;
493 sample.gradient = EvaluatePolynomial(true_gradient_polynomial, sample.x);
494 sample.gradient_is_valid = true;
495 samples.push_back(sample);
496 }
497
498 {
499 FunctionSample sample;
500 sample.x = 2.0;
501 sample.value = EvaluatePolynomial(true_polynomial, sample.x);
502 sample.value_is_valid = true;
503 sample.gradient = EvaluatePolynomial(true_gradient_polynomial, sample.x);
504 sample.gradient_is_valid = true;
505 samples.push_back(sample);
506 }
507
508 const Vector polynomial = FindInterpolatingPolynomial(samples);
509 EXPECT_NEAR((true_polynomial - polynomial).norm(), 0.0, 1e-14);
510 }
511
512 } // namespace internal
513 } // namespace ceres
514