testTableFactor.cpp
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1 /* ----------------------------------------------------------------------------
2 
3  * GTSAM Copyright 2010, Georgia Tech Research Corporation,
4  * Atlanta, Georgia 30332-0415
5  * All Rights Reserved
6  * Authors: Frank Dellaert, et al. (see THANKS for the full author list)
7 
8  * See LICENSE for the license information
9 
10  * -------------------------------------------------------------------------- */
11 
12 /*
13  * testTableFactor.cpp
14  *
15  * @date Feb 15, 2023
16  * @author Yoonwoo Kim
17  */
18 
19 #include <CppUnitLite/TestHarness.h>
20 #include <gtsam/base/Testable.h>
21 #include <gtsam/base/serializationTestHelpers.h>
22 #include <gtsam/discrete/DiscreteConditional.h>
23 #include <gtsam/discrete/DiscreteDistribution.h>
24 #include <gtsam/discrete/Signature.h>
25 #include <gtsam/discrete/TableFactor.h>
26 
27 #include <chrono>
28 #include <random>
29 
30 using namespace std;
31 using namespace gtsam;
32 
33 vector<double> genArr(double dropout, size_t size) {
34  random_device rd;
35  mt19937 g(rd());
36  vector<double> dropoutmask(size); // Chance of 0
37 
38  uniform_int_distribution<> dist(1, 9);
39  auto gen = [&dist, &g]() { return dist(g); };
40  generate(dropoutmask.begin(), dropoutmask.end(), gen);
41 
42  fill_n(dropoutmask.begin(), dropoutmask.size() * (dropout), 0);
43  shuffle(dropoutmask.begin(), dropoutmask.end(), g);
44 
45  return dropoutmask;
46 }
47 
48 map<double, pair<chrono::microseconds, chrono::microseconds>> measureTime(
49  DiscreteKeys keys1, DiscreteKeys keys2, size_t size) {
50  vector<double> dropouts = {0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9};
51  map<double, pair<chrono::microseconds, chrono::microseconds>> measured_times;
52 
53  for (auto dropout : dropouts) {
54  vector<double> arr1 = genArr(dropout, size);
55  vector<double> arr2 = genArr(dropout, size);
56  TableFactor f1(keys1, arr1);
57  TableFactor f2(keys2, arr2);
58  DecisionTreeFactor f1_dt(keys1, arr1);
59  DecisionTreeFactor f2_dt(keys2, arr2);
60 
61  // measure time TableFactor
62  auto tb_start = chrono::high_resolution_clock::now();
63  TableFactor actual = f1 * f2;
64  auto tb_end = chrono::high_resolution_clock::now();
65  auto tb_time_diff =
66  chrono::duration_cast<chrono::microseconds>(tb_end - tb_start);
67 
68  // measure time DT
69  auto dt_start = chrono::high_resolution_clock::now();
70  DecisionTreeFactor actual_dt = f1_dt * f2_dt;
71  auto dt_end = chrono::high_resolution_clock::now();
72  auto dt_time_diff =
73  chrono::duration_cast<chrono::microseconds>(dt_end - dt_start);
74 
75  bool flag = true;
76  for (auto assignmentVal : actual_dt.enumerate()) {
77  flag = actual_dt(assignmentVal.first) != actual(assignmentVal.first);
78  if (flag) {
79  std::cout << "something is wrong: " << std::endl;
80  assignmentVal.first.print();
81  std::cout << "dt: " << actual_dt(assignmentVal.first) << std::endl;
82  std::cout << "tb: " << actual(assignmentVal.first) << std::endl;
83  break;
84  }
85  }
86  if (flag) break;
87  measured_times[dropout] = make_pair(tb_time_diff, dt_time_diff);
88  }
89  return measured_times;
90 }
91 
92 void printTime(map<double, pair<chrono::microseconds, chrono::microseconds>>
93  measured_time) {
94  for (auto&& kv : measured_time) {
95  cout << "dropout: " << kv.first
96  << " | TableFactor time: " << kv.second.first.count()
97  << " | DecisionTreeFactor time: " << kv.second.second.count() << endl;
98  }
99 }
100 
101 /* ************************************************************************* */
102 // Check constructors for TableFactor.
103 TEST(TableFactor, constructors) {
104  // Declare a bunch of keys
105  DiscreteKey X(0, 2), Y(1, 3), Z(2, 2), A(3, 5);
106 
107  // Create factors
108  TableFactor f_zeros(A, {0, 0, 0, 0, 1});
109  TableFactor f1(X, {2, 8});
110  TableFactor f2(X & Y, "2 5 3 6 4 7");
111  TableFactor f3(X & Y & Z, "2 5 3 6 4 7 25 55 35 65 45 75");
112  EXPECT_LONGS_EQUAL(1, f1.size());
113  EXPECT_LONGS_EQUAL(2, f2.size());
114  EXPECT_LONGS_EQUAL(3, f3.size());
115 
116  DiscreteValues values;
117  values[0] = 1; // x
118  values[1] = 2; // y
119  values[2] = 1; // z
120  values[3] = 4; // a
121  EXPECT_DOUBLES_EQUAL(1, f_zeros(values), 1e-9);
122  EXPECT_DOUBLES_EQUAL(8, f1(values), 1e-9);
123  EXPECT_DOUBLES_EQUAL(7, f2(values), 1e-9);
124  EXPECT_DOUBLES_EQUAL(75, f3(values), 1e-9);
125 
126  // Assert that error = -log(value)
127  EXPECT_DOUBLES_EQUAL(-log(f1(values)), f1.error(values), 1e-9);
128 
129  // Construct from DiscreteConditional
130  DiscreteConditional conditional(X | Y = "1/1 2/3 1/4");
131  TableFactor f4(conditional);
132  // Manually constructed via inspection and comparison to DecisionTreeFactor
133  TableFactor expected(X & Y, "0.5 0.4 0.2 0.5 0.6 0.8");
134  EXPECT(assert_equal(expected, f4));
135 
136  // Test for 9=3x3 values.
137  DiscreteKey V(0, 3), W(1, 3);
138  DiscreteConditional conditional5(V | W = "1/2/3 5/6/7 9/10/11");
139  TableFactor f5(conditional5);
140  // GTSAM_PRINT(f5);
141  TableFactor expected_f5(
142  X & Y,
143  "0.166667 0.277778 0.3 0.333333 0.333333 0.333333 0.5 0.388889 0.366667");
144  EXPECT(assert_equal(expected_f5, f5, 1e-6));
145 }
146 
147 /* ************************************************************************* */
148 // Check multiplication between two TableFactors.
149 TEST(TableFactor, multiplication) {
150  DiscreteKey v0(0, 2), v1(1, 2), v2(2, 2);
151 
152  // Multiply with a DiscreteDistribution, i.e., Bayes Law!
153  DiscreteDistribution prior(v1 % "1/3");
154  TableFactor f1(v0 & v1, "1 2 3 4");
155  DecisionTreeFactor expected(v0 & v1, "0.25 1.5 0.75 3");
156  CHECK(assert_equal(expected, static_cast<DecisionTreeFactor>(prior) *
157  f1.toDecisionTreeFactor()));
158  CHECK(assert_equal(expected, f1 * prior));
159 
160  // Multiply two factors
161  TableFactor f2(v1 & v2, "5 6 7 8");
162  TableFactor actual = f1 * f2;
163  TableFactor expected2(v0 & v1 & v2, "5 6 14 16 15 18 28 32");
164  CHECK(assert_equal(expected2, actual));
165 
166  DiscreteKey A(0, 3), B(1, 2), C(2, 2);
167  TableFactor f_zeros1(A & C, "0 0 0 2 0 3");
168  TableFactor f_zeros2(B & C, "4 0 0 5");
169  TableFactor actual_zeros = f_zeros1 * f_zeros2;
170  TableFactor expected3(A & B & C, "0 0 0 0 0 0 0 10 0 0 0 15");
171  CHECK(assert_equal(expected3, actual_zeros));
172 }
173 
174 /* ************************************************************************* */
175 // Benchmark which compares runtime of multiplication of two TableFactors
176 // and two DecisionTreeFactors given sparsity from dense to 90% sparsity.
177 // NOTE: Enable to run.
178 TEST_DISABLED(TableFactor, benchmark) {
179  DiscreteKey A(0, 5), B(1, 2), C(2, 5), D(3, 2), E(4, 5), F(5, 2), G(6, 3),
180  H(7, 2), I(8, 5), J(9, 7), K(10, 2), L(11, 3);
181 
182  // 100
183  DiscreteKeys one_1 = {A, B, C, D};
184  DiscreteKeys one_2 = {C, D, E, F};
185  map<double, pair<chrono::microseconds, chrono::microseconds>> time_map_1 =
186  measureTime(one_1, one_2, 100);
187  printTime(time_map_1);
188  // 200
189  DiscreteKeys two_1 = {A, B, C, D, F};
190  DiscreteKeys two_2 = {B, C, D, E, F};
191  map<double, pair<chrono::microseconds, chrono::microseconds>> time_map_2 =
192  measureTime(two_1, two_2, 200);
193  printTime(time_map_2);
194  // 300
195  DiscreteKeys three_1 = {A, B, C, D, G};
196  DiscreteKeys three_2 = {C, D, E, F, G};
197  map<double, pair<chrono::microseconds, chrono::microseconds>> time_map_3 =
198  measureTime(three_1, three_2, 300);
199  printTime(time_map_3);
200  // 400
201  DiscreteKeys four_1 = {A, B, C, D, F, H};
202  DiscreteKeys four_2 = {B, C, D, E, F, H};
203  map<double, pair<chrono::microseconds, chrono::microseconds>> time_map_4 =
204  measureTime(four_1, four_2, 400);
205  printTime(time_map_4);
206  // 500
207  DiscreteKeys five_1 = {A, B, C, D, I};
208  DiscreteKeys five_2 = {C, D, E, F, I};
209  map<double, pair<chrono::microseconds, chrono::microseconds>> time_map_5 =
210  measureTime(five_1, five_2, 500);
211  printTime(time_map_5);
212  // 600
213  DiscreteKeys six_1 = {A, B, C, D, F, G};
214  DiscreteKeys six_2 = {B, C, D, E, F, G};
215  map<double, pair<chrono::microseconds, chrono::microseconds>> time_map_6 =
216  measureTime(six_1, six_2, 600);
217  printTime(time_map_6);
218  // 700
219  DiscreteKeys seven_1 = {A, B, C, D, J};
220  DiscreteKeys seven_2 = {C, D, E, F, J};
221  map<double, pair<chrono::microseconds, chrono::microseconds>> time_map_7 =
222  measureTime(seven_1, seven_2, 700);
223  printTime(time_map_7);
224  // 800
225  DiscreteKeys eight_1 = {A, B, C, D, F, H, K};
226  DiscreteKeys eight_2 = {B, C, D, E, F, H, K};
227  map<double, pair<chrono::microseconds, chrono::microseconds>> time_map_8 =
228  measureTime(eight_1, eight_2, 800);
229  printTime(time_map_8);
230  // 900
231  DiscreteKeys nine_1 = {A, B, C, D, G, L};
232  DiscreteKeys nine_2 = {C, D, E, F, G, L};
233  map<double, pair<chrono::microseconds, chrono::microseconds>> time_map_9 =
234  measureTime(nine_1, nine_2, 900);
235  printTime(time_map_9);
236 }
237 
238 /* ************************************************************************* */
239 // Check sum and max over frontals.
240 TEST(TableFactor, sum_max) {
241  DiscreteKey v0(0, 3), v1(1, 2);
242  TableFactor f1(v0 & v1, "1 2 3 4 5 6");
243 
244  TableFactor expected(v1, "9 12");
245  TableFactor::shared_ptr actual = f1.sum(1);
246  CHECK(assert_equal(expected, *actual, 1e-5));
247 
248  TableFactor expected2(v1, "5 6");
249  TableFactor::shared_ptr actual2 = f1.max(1);
250  CHECK(assert_equal(expected2, *actual2));
251 
252  TableFactor f2(v1 & v0, "1 2 3 4 5 6");
253  TableFactor::shared_ptr actual22 = f2.sum(1);
254 }
255 
256 /* ************************************************************************* */
257 // Check enumerate yields the correct list of assignment/value pairs.
258 TEST(TableFactor, enumerate) {
259  DiscreteKey A(12, 3), B(5, 2);
260  TableFactor f(A & B, "1 2 3 4 5 6");
261  auto actual = f.enumerate();
262  std::vector<std::pair<DiscreteValues, double>> expected;
263  DiscreteValues values;
264  for (size_t a : {0, 1, 2}) {
265  for (size_t b : {0, 1}) {
266  values[12] = a;
267  values[5] = b;
268  expected.emplace_back(values, f(values));
269  }
270  }
271  EXPECT(actual == expected);
272 }
273 
274 /* ************************************************************************* */
275 // Check pruning of the decision tree works as expected.
276 TEST(TableFactor, Prune) {
277  DiscreteKey A(1, 2), B(2, 2), C(3, 2);
278  TableFactor f(A & B & C, "1 5 3 7 2 6 4 8");
279 
280  // Only keep the leaves with the top 5 values.
281  size_t maxNrAssignments = 5;
282  auto pruned5 = f.prune(maxNrAssignments);
283 
284  // Pruned leaves should be 0
285  TableFactor expected(A & B & C, "0 5 0 7 0 6 4 8");
286  EXPECT(assert_equal(expected, pruned5));
287 
288  // Check for more extreme pruning where we only keep the top 2 leaves
289  maxNrAssignments = 2;
290  auto pruned2 = f.prune(maxNrAssignments);
291  TableFactor expected2(A & B & C, "0 0 0 7 0 0 0 8");
292  EXPECT(assert_equal(expected2, pruned2));
293 
294  DiscreteKey D(4, 2);
295  TableFactor factor(
296  D & C & B & A,
297  "0.0 0.0 0.0 0.60658897 0.61241912 0.61241969 0.61247685 0.61247742 0.0 "
298  "0.0 0.0 0.99995287 1.0 1.0 1.0 1.0");
299 
300  TableFactor expected3(D & C & B & A,
301  "0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 "
302  "0.999952870000 1.0 1.0 1.0 1.0");
303  maxNrAssignments = 5;
304  auto pruned3 = factor.prune(maxNrAssignments);
305  EXPECT(assert_equal(expected3, pruned3));
306 }
307 
308 /* ************************************************************************* */
309 // Check markdown representation looks as expected.
310 TEST(TableFactor, markdown) {
311  DiscreteKey A(12, 3), B(5, 2);
312  TableFactor f(A & B, "1 2 3 4 5 6");
313  string expected =
314  "|A|B|value|\n"
315  "|:-:|:-:|:-:|\n"
316  "|0|0|1|\n"
317  "|0|1|2|\n"
318  "|1|0|3|\n"
319  "|1|1|4|\n"
320  "|2|0|5|\n"
321  "|2|1|6|\n";
322  auto formatter = [](Key key) { return key == 12 ? "A" : "B"; };
323  string actual = f.markdown(formatter);
324  EXPECT(actual == expected);
325 }
326 
327 /* ************************************************************************* */
328 // Check markdown representation with a value formatter.
329 TEST(TableFactor, markdownWithValueFormatter) {
330  DiscreteKey A(12, 3), B(5, 2);
331  TableFactor f(A & B, "1 2 3 4 5 6");
332  string expected =
333  "|A|B|value|\n"
334  "|:-:|:-:|:-:|\n"
335  "|Zero|-|1|\n"
336  "|Zero|+|2|\n"
337  "|One|-|3|\n"
338  "|One|+|4|\n"
339  "|Two|-|5|\n"
340  "|Two|+|6|\n";
341  auto keyFormatter = [](Key key) { return key == 12 ? "A" : "B"; };
342  TableFactor::Names names{{12, {"Zero", "One", "Two"}}, {5, {"-", "+"}}};
343  string actual = f.markdown(keyFormatter, names);
344  EXPECT(actual == expected);
345 }
346 
347 /* ************************************************************************* */
348 // Check html representation with a value formatter.
349 TEST(TableFactor, htmlWithValueFormatter) {
350  DiscreteKey A(12, 3), B(5, 2);
351  TableFactor f(A & B, "1 2 3 4 5 6");
352  string expected =
353  "<div>\n"
354  "<table class='TableFactor'>\n"
355  " <thead>\n"
356  " <tr><th>A</th><th>B</th><th>value</th></tr>\n"
357  " </thead>\n"
358  " <tbody>\n"
359  " <tr><th>Zero</th><th>-</th><td>1</td></tr>\n"
360  " <tr><th>Zero</th><th>+</th><td>2</td></tr>\n"
361  " <tr><th>One</th><th>-</th><td>3</td></tr>\n"
362  " <tr><th>One</th><th>+</th><td>4</td></tr>\n"
363  " <tr><th>Two</th><th>-</th><td>5</td></tr>\n"
364  " <tr><th>Two</th><th>+</th><td>6</td></tr>\n"
365  " </tbody>\n"
366  "</table>\n"
367  "</div>";
368  auto keyFormatter = [](Key key) { return key == 12 ? "A" : "B"; };
369  TableFactor::Names names{{12, {"Zero", "One", "Two"}}, {5, {"-", "+"}}};
370  string actual = f.html(keyFormatter, names);
371  EXPECT(actual == expected);
372 }
373 
374 /* ************************************************************************* */
375 TEST(TableFactor, Unary) {
376  // Declare a bunch of keys
377  DiscreteKey X(0, 2), Y(1, 3);
378 
379  // Create factors
380  TableFactor f(X & Y, "2 5 3 6 2 7");
381  auto op = [](const double x) { return 2 * x; };
382  auto g = f.apply(op);
383 
384  TableFactor expected(X & Y, "4 10 6 12 4 14");
385  EXPECT(assert_equal(g, expected));
386 
387  auto sq_op = [](const double x) { return x * x; };
388  auto g_sq = f.apply(sq_op);
389  TableFactor expected_sq(X & Y, "4 25 9 36 4 49");
390  EXPECT(assert_equal(g_sq, expected_sq));
391 }
392 
393 /* ************************************************************************* */
394 TEST(TableFactor, UnaryAssignment) {
395  // Declare a bunch of keys
396  DiscreteKey X(0, 2), Y(1, 3);
397 
398  // Create factors
399  TableFactor f(X & Y, "2 5 3 6 2 7");
400  auto op = [](const Assignment<Key>& key, const double x) { return 2 * x; };
401  auto g = f.apply(op);
402 
403  TableFactor expected(X & Y, "4 10 6 12 4 14");
404  EXPECT(assert_equal(g, expected));
405 }
406 
407 /* ************************************************************************* */
408 int main() {
409  TestResult tr;
410  return TestRegistry::runAllTests(tr);
411 }
412 /* ************************************************************************* */
TestRegistry::runAllTests
static int runAllTests(TestResult &result)
Definition: TestRegistry.cpp:27
TEST
TEST(TableFactor, constructors)
Definition: testTableFactor.cpp:103
TEST_DISABLED
TEST_DISABLED(TableFactor, benchmark)
Definition: testTableFactor.cpp:178
H
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Vector v2
Definition: testSerializationBase.cpp:39
f4
double f4(double x, double y, double z)
Definition: testNumericalDerivative.cpp:105
gtsam::assert_equal
bool assert_equal(const Matrix &expected, const Matrix &actual, double tol)
Definition: Matrix.cpp:40
gtsam::DecisionTreeFactor::enumerate
std::vector< std::pair< DiscreteValues, double > > enumerate() const
Enumerate all values into a map from values to double.
Definition: DecisionTreeFactor.cpp:187
V
MatrixXcd V
Definition: EigenSolver_EigenSolver_MatrixType.cpp:15
different_sigmas::prior
const auto prior
Definition: testHybridBayesNet.cpp:238
gtsam::Key
std::uint64_t Key
Integer nonlinear key type.
Definition: types.h:97
Z
#define Z
Definition: icosphere.cpp:21
gtsam::TableFactor::shared_ptr
std::shared_ptr< TableFactor > shared_ptr
Definition: TableFactor.h:93
v1
Vector v1
Definition: testSerializationBase.cpp:38

gtsam
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autogenerated on Sat Nov 16 2024 04:08:45