blob: 6a071c1aae0a881f5314a6a5d13bf337b24a4c96 [file] [log] [blame]
Romain Guy5d4bae72016-11-08 09:49:25 -08001/*
2 * Copyright 2013 The Android Open Source Project
3 *
4 * Licensed under the Apache License, Version 2.0 (the "License");
5 * you may not use this file except in compliance with the License.
6 * You may obtain a copy of the License at
7 *
8 * http://www.apache.org/licenses/LICENSE-2.0
9 *
10 * Unless required by applicable law or agreed to in writing, software
11 * distributed under the License is distributed on an "AS IS" BASIS,
12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13 * See the License for the specific language governing permissions and
14 * limitations under the License.
15 */
16
17#ifndef UI_MAT3_H_
18#define UI_MAT3_H_
19
20#include <ui/quat.h>
21#include <ui/TMatHelpers.h>
22#include <ui/vec3.h>
23#include <stdint.h>
24#include <sys/types.h>
25
26#define PURE __attribute__((pure))
27
28namespace android {
29// -------------------------------------------------------------------------------------
30namespace details {
31
32template<typename T>
33class TQuaternion;
34
35/**
36 * A 3x3 column-major matrix class.
37 *
38 * Conceptually a 3x3 matrix is a an array of 3 column vec3:
39 *
40 * mat3 m =
41 * \f$
42 * \left(
43 * \begin{array}{ccc}
44 * m[0] & m[1] & m[2] \\
45 * \end{array}
46 * \right)
47 * \f$
48 * =
49 * \f$
50 * \left(
51 * \begin{array}{ccc}
52 * m[0][0] & m[1][0] & m[2][0] \\
53 * m[0][1] & m[1][1] & m[2][1] \\
54 * m[0][2] & m[1][2] & m[2][2] \\
55 * \end{array}
56 * \right)
57 * \f$
58 * =
59 * \f$
60 * \left(
61 * \begin{array}{ccc}
62 * m(0,0) & m(0,1) & m(0,2) \\
63 * m(1,0) & m(1,1) & m(1,2) \\
64 * m(2,0) & m(2,1) & m(2,2) \\
65 * \end{array}
66 * \right)
67 * \f$
68 *
69 * m[n] is the \f$ n^{th} \f$ column of the matrix and is a vec3.
70 *
71 */
72template <typename T>
73class TMat33 : public TVecUnaryOperators<TMat33, T>,
74 public TVecComparisonOperators<TMat33, T>,
75 public TVecAddOperators<TMat33, T>,
76 public TMatProductOperators<TMat33, T>,
77 public TMatSquareFunctions<TMat33, T>,
78 public TMatTransform<TMat33, T>,
79 public TMatHelpers<TMat33, T>,
80 public TMatDebug<TMat33, T> {
81public:
82 enum no_init { NO_INIT };
83 typedef T value_type;
84 typedef T& reference;
85 typedef T const& const_reference;
86 typedef size_t size_type;
87 typedef TVec3<T> col_type;
88 typedef TVec3<T> row_type;
89
90 static constexpr size_t COL_SIZE = col_type::SIZE; // size of a column (i.e.: number of rows)
91 static constexpr size_t ROW_SIZE = row_type::SIZE; // size of a row (i.e.: number of columns)
92 static constexpr size_t NUM_ROWS = COL_SIZE;
93 static constexpr size_t NUM_COLS = ROW_SIZE;
94
95private:
96 /*
97 * <-- N columns -->
98 *
99 * a[0][0] a[1][0] a[2][0] ... a[N][0] ^
100 * a[0][1] a[1][1] a[2][1] ... a[N][1] |
101 * a[0][2] a[1][2] a[2][2] ... a[N][2] M rows
102 * ... |
103 * a[0][M] a[1][M] a[2][M] ... a[N][M] v
104 *
105 * COL_SIZE = M
106 * ROW_SIZE = N
107 * m[0] = [ a[0][0] a[0][1] a[0][2] ... a[0][M] ]
108 */
109
110 col_type m_value[NUM_COLS];
111
112public:
113 // array access
114 inline constexpr col_type const& operator[](size_t column) const {
115#if __cplusplus >= 201402L
116 // only possible in C++0x14 with constexpr
117 assert(column < NUM_COLS);
118#endif
119 return m_value[column];
120 }
121
122 inline col_type& operator[](size_t column) {
123 assert(column < NUM_COLS);
124 return m_value[column];
125 }
126
127 // -----------------------------------------------------------------------
128 // we want the compiler generated versions for these...
129 TMat33(const TMat33&) = default;
130 ~TMat33() = default;
131 TMat33& operator = (const TMat33&) = default;
132
133 /**
134 * constructors
135 */
136
137 /**
138 * leaves object uninitialized. use with caution.
139 */
140 explicit
141 constexpr TMat33(no_init)
142 : m_value{ col_type(col_type::NO_INIT),
143 col_type(col_type::NO_INIT),
144 col_type(col_type::NO_INIT) } {}
145
146
147 /**
148 * initialize to identity.
149 *
150 * \f$
151 * \left(
152 * \begin{array}{ccc}
153 * 1 & 0 & 0 \\
154 * 0 & 1 & 0 \\
155 * 0 & 0 & 1 \\
156 * \end{array}
157 * \right)
158 * \f$
159 */
160 TMat33();
161
162 /**
163 * initialize to Identity*scalar.
164 *
165 * \f$
166 * \left(
167 * \begin{array}{ccc}
168 * v & 0 & 0 \\
169 * 0 & v & 0 \\
170 * 0 & 0 & v \\
171 * \end{array}
172 * \right)
173 * \f$
174 */
175 template<typename U>
176 explicit TMat33(U v);
177
178 /**
179 * sets the diagonal to a vector.
180 *
181 * \f$
182 * \left(
183 * \begin{array}{ccc}
184 * v[0] & 0 & 0 \\
185 * 0 & v[1] & 0 \\
186 * 0 & 0 & v[2] \\
187 * \end{array}
188 * \right)
189 * \f$
190 */
191 template <typename U>
192 explicit TMat33(const TVec3<U>& v);
193
194 /**
195 * construct from another matrix of the same size
196 */
197 template <typename U>
198 explicit TMat33(const TMat33<U>& rhs);
199
200 /**
201 * construct from 3 column vectors.
202 *
203 * \f$
204 * \left(
205 * \begin{array}{ccc}
206 * v0 & v1 & v2 \\
207 * \end{array}
208 * \right)
209 * \f$
210 */
211 template <typename A, typename B, typename C>
212 TMat33(const TVec3<A>& v0, const TVec3<B>& v1, const TVec3<C>& v2);
213
214 /** construct from 9 elements in column-major form.
215 *
216 * \f$
217 * \left(
218 * \begin{array}{ccc}
219 * m[0][0] & m[1][0] & m[2][0] \\
220 * m[0][1] & m[1][1] & m[2][1] \\
221 * m[0][2] & m[1][2] & m[2][2] \\
222 * \end{array}
223 * \right)
224 * \f$
225 */
226 template <
227 typename A, typename B, typename C,
228 typename D, typename E, typename F,
229 typename G, typename H, typename I>
230 TMat33(A m00, B m01, C m02,
231 D m10, E m11, F m12,
232 G m20, H m21, I m22);
233
234 /**
235 * construct from a quaternion
236 */
237 template <typename U>
238 explicit TMat33(const TQuaternion<U>& q);
239
240 /**
241 * construct from a C array in column major form.
242 */
243 template <typename U>
244 explicit TMat33(U const* rawArray);
245
246 /**
247 * orthogonalize only works on matrices of size 3x3
248 */
249 friend inline
250 TMat33 orthogonalize(const TMat33& m) {
251 TMat33 ret(TMat33::NO_INIT);
252 ret[0] = normalize(m[0]);
253 ret[2] = normalize(cross(ret[0], m[1]));
254 ret[1] = normalize(cross(ret[2], ret[0]));
255 return ret;
256 }
257};
258
259// ----------------------------------------------------------------------------------------
260// Constructors
261// ----------------------------------------------------------------------------------------
262
263// Since the matrix code could become pretty big quickly, we don't inline most
264// operations.
265
266template <typename T>
267TMat33<T>::TMat33() {
268 m_value[0] = col_type(1, 0, 0);
269 m_value[1] = col_type(0, 1, 0);
270 m_value[2] = col_type(0, 0, 1);
271}
272
273template <typename T>
274template <typename U>
275TMat33<T>::TMat33(U v) {
276 m_value[0] = col_type(v, 0, 0);
277 m_value[1] = col_type(0, v, 0);
278 m_value[2] = col_type(0, 0, v);
279}
280
281template<typename T>
282template<typename U>
283TMat33<T>::TMat33(const TVec3<U>& v) {
284 m_value[0] = col_type(v.x, 0, 0);
285 m_value[1] = col_type(0, v.y, 0);
286 m_value[2] = col_type(0, 0, v.z);
287}
288
289// construct from 16 scalars. Note that the arrangement
290// of values in the constructor is the transpose of the matrix
291// notation.
292template<typename T>
293template <
294 typename A, typename B, typename C,
295 typename D, typename E, typename F,
296 typename G, typename H, typename I>
297TMat33<T>::TMat33(A m00, B m01, C m02,
298 D m10, E m11, F m12,
299 G m20, H m21, I m22) {
300 m_value[0] = col_type(m00, m01, m02);
301 m_value[1] = col_type(m10, m11, m12);
302 m_value[2] = col_type(m20, m21, m22);
303}
304
305template <typename T>
306template <typename U>
307TMat33<T>::TMat33(const TMat33<U>& rhs) {
308 for (size_t col = 0; col < NUM_COLS; ++col) {
309 m_value[col] = col_type(rhs[col]);
310 }
311}
312
313// Construct from 3 column vectors.
314template <typename T>
315template <typename A, typename B, typename C>
316TMat33<T>::TMat33(const TVec3<A>& v0, const TVec3<B>& v1, const TVec3<C>& v2) {
317 m_value[0] = v0;
318 m_value[1] = v1;
319 m_value[2] = v2;
320}
321
322// Construct from raw array, in column-major form.
323template <typename T>
324template <typename U>
325TMat33<T>::TMat33(U const* rawArray) {
326 for (size_t col = 0; col < NUM_COLS; ++col) {
327 for (size_t row = 0; row < NUM_ROWS; ++row) {
328 m_value[col][row] = *rawArray++;
329 }
330 }
331}
332
333template <typename T>
334template <typename U>
335TMat33<T>::TMat33(const TQuaternion<U>& q) {
336 const U n = q.x*q.x + q.y*q.y + q.z*q.z + q.w*q.w;
337 const U s = n > 0 ? 2/n : 0;
338 const U x = s*q.x;
339 const U y = s*q.y;
340 const U z = s*q.z;
341 const U xx = x*q.x;
342 const U xy = x*q.y;
343 const U xz = x*q.z;
344 const U xw = x*q.w;
345 const U yy = y*q.y;
346 const U yz = y*q.z;
347 const U yw = y*q.w;
348 const U zz = z*q.z;
349 const U zw = z*q.w;
350 m_value[0] = col_type(1-yy-zz, xy+zw, xz-yw); // NOLINT
351 m_value[1] = col_type( xy-zw, 1-xx-zz, yz+xw); // NOLINT
352 m_value[2] = col_type( xz+yw, yz-xw, 1-xx-yy); // NOLINT
353}
354
355// ----------------------------------------------------------------------------------------
356// Arithmetic operators outside of class
357// ----------------------------------------------------------------------------------------
358
359/* We use non-friend functions here to prevent the compiler from using
360 * implicit conversions, for instance of a scalar to a vector. The result would
361 * not be what the caller expects.
362 *
363 * Also note that the order of the arguments in the inner loop is important since
364 * it determines the output type (only relevant when T != U).
365 */
366
367// matrix * column-vector, result is a vector of the same type than the input vector
368template <typename T, typename U>
369typename TMat33<U>::col_type PURE operator *(const TMat33<T>& lhs, const TVec3<U>& rhs) {
370 // Result is initialized to zero.
371 typename TMat33<U>::col_type result;
372 for (size_t col = 0; col < TMat33<T>::NUM_COLS; ++col) {
373 result += lhs[col] * rhs[col];
374 }
375 return result;
376}
377
378// row-vector * matrix, result is a vector of the same type than the input vector
379template <typename T, typename U>
380typename TMat33<U>::row_type PURE operator *(const TVec3<U>& lhs, const TMat33<T>& rhs) {
381 typename TMat33<U>::row_type result(TMat33<U>::row_type::NO_INIT);
382 for (size_t col = 0; col < TMat33<T>::NUM_COLS; ++col) {
383 result[col] = dot(lhs, rhs[col]);
384 }
385 return result;
386}
387
388// matrix * scalar, result is a matrix of the same type than the input matrix
389template<typename T, typename U>
390constexpr typename std::enable_if<std::is_arithmetic<U>::value, TMat33<T>>::type PURE
391operator*(TMat33<T> lhs, U rhs) {
392 return lhs *= rhs;
393}
394
395// scalar * matrix, result is a matrix of the same type than the input matrix
396template<typename T, typename U>
397constexpr typename std::enable_if<std::is_arithmetic<U>::value, TMat33<T>>::type PURE
398operator*(U lhs, const TMat33<T>& rhs) {
399 return rhs * lhs;
400}
401
402//------------------------------------------------------------------------------
403template <typename T>
404TMat33<T> orthogonalize(const TMat33<T>& m) {
405 TMat33<T> ret(TMat33<T>::NO_INIT);
406 ret[0] = normalize(m[0]);
407 ret[2] = normalize(cross(ret[0], m[1]));
408 ret[1] = normalize(cross(ret[2], ret[0]));
409 return ret;
410}
411
412// ----------------------------------------------------------------------------------------
413
414/* FIXME: this should go into TMatSquareFunctions<> but for some reason
415 * BASE<T>::col_type is not accessible from there (???)
416 */
417template<typename T>
418typename TMat33<T>::col_type PURE diag(const TMat33<T>& m) {
419 return matrix::diag(m);
420}
421
422} // namespace details
423
424// ----------------------------------------------------------------------------------------
425
426typedef details::TMat33<double> mat3d;
427typedef details::TMat33<float> mat3;
428typedef details::TMat33<float> mat3f;
429
430// ----------------------------------------------------------------------------------------
431} // namespace android
432
433#undef PURE
434
435#endif // UI_MAT3_H_