weston/shared/matrix.c

583 lines
14 KiB
C

/*
* Copyright © 2011 Intel Corporation
* Copyright © 2012 Collabora, Ltd.
*
* Permission is hereby granted, free of charge, to any person obtaining
* a copy of this software and associated documentation files (the
* "Software"), to deal in the Software without restriction, including
* without limitation the rights to use, copy, modify, merge, publish,
* distribute, sublicense, and/or sell copies of the Software, and to
* permit persons to whom the Software is furnished to do so, subject to
* the following conditions:
*
* The above copyright notice and this permission notice (including the
* next paragraph) shall be included in all copies or substantial
* portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
* EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
* MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
* NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS
* BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN
* ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
* CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "config.h"
#include <assert.h>
#include <float.h>
#include <string.h>
#include <stdlib.h>
#include <math.h>
#include <wayland-server.h>
#include <libweston/matrix.h>
/*
* Matrices are stored in column-major order, that is the array indices are:
* 0 4 8 12
* 1 5 9 13
* 2 6 10 14
* 3 7 11 15
*/
WL_EXPORT void
weston_matrix_init(struct weston_matrix *matrix)
{
static const struct weston_matrix identity = {
.d = { 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1 },
.type = 0,
};
memcpy(matrix, &identity, sizeof identity);
}
/* m <- n * m, that is, m is multiplied on the LEFT. */
WL_EXPORT void
weston_matrix_multiply(struct weston_matrix *m, const struct weston_matrix *n)
{
struct weston_matrix tmp;
const float *row, *column;
int i, j, k;
for (i = 0; i < 4; i++) {
row = m->d + i * 4;
for (j = 0; j < 4; j++) {
tmp.d[4 * i + j] = 0;
column = n->d + j;
for (k = 0; k < 4; k++)
tmp.d[4 * i + j] += row[k] * column[k * 4];
}
}
tmp.type = m->type | n->type;
memcpy(m, &tmp, sizeof tmp);
}
WL_EXPORT void
weston_matrix_translate(struct weston_matrix *matrix, float x, float y, float z)
{
struct weston_matrix translate = {
.d = { 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, x, y, z, 1 },
.type = WESTON_MATRIX_TRANSFORM_TRANSLATE,
};
weston_matrix_multiply(matrix, &translate);
}
WL_EXPORT void
weston_matrix_scale(struct weston_matrix *matrix, float x, float y,float z)
{
struct weston_matrix scale = {
.d = { x, 0, 0, 0, 0, y, 0, 0, 0, 0, z, 0, 0, 0, 0, 1 },
.type = WESTON_MATRIX_TRANSFORM_SCALE,
};
weston_matrix_multiply(matrix, &scale);
}
WL_EXPORT void
weston_matrix_rotate_xy(struct weston_matrix *matrix, float cos, float sin)
{
struct weston_matrix translate = {
.d = { cos, sin, 0, 0, -sin, cos, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1 },
.type = WESTON_MATRIX_TRANSFORM_ROTATE,
};
weston_matrix_multiply(matrix, &translate);
}
/* v <- m * v */
WL_EXPORT void
weston_matrix_transform(const struct weston_matrix *matrix,
struct weston_vector *v)
{
int i, j;
struct weston_vector t;
for (i = 0; i < 4; i++) {
t.f[i] = 0;
for (j = 0; j < 4; j++)
t.f[i] += v->f[j] * matrix->d[i + j * 4];
}
*v = t;
}
WL_EXPORT struct weston_coord
weston_matrix_transform_coord(const struct weston_matrix *matrix,
struct weston_coord c)
{
struct weston_coord out;
struct weston_vector t = { { c.x, c.y, 0.0, 1.0 } };
weston_matrix_transform(matrix, &t);
assert(fabsf(t.f[3]) > 1e-6);
out.x = t.f[0] / t.f[3];
out.y = t.f[1] / t.f[3];
return out;
}
static inline void
swap_rows(double *a, double *b)
{
unsigned k;
double tmp;
for (k = 0; k < 13; k += 4) {
tmp = a[k];
a[k] = b[k];
b[k] = tmp;
}
}
static inline void
swap_unsigned(unsigned *a, unsigned *b)
{
unsigned tmp;
tmp = *a;
*a = *b;
*b = tmp;
}
static inline unsigned
find_pivot(double *column, unsigned k)
{
unsigned p = k;
for (++k; k < 4; ++k)
if (fabs(column[p]) < fabs(column[k]))
p = k;
return p;
}
/*
* reference: Gene H. Golub and Charles F. van Loan. Matrix computations.
* 3rd ed. The Johns Hopkins University Press. 1996.
* LU decomposition, forward and back substitution: Chapter 3.
*/
static int
matrix_invert(double *A, unsigned *p, const struct weston_matrix *matrix)
{
unsigned i, j, k;
unsigned pivot;
double pv;
for (i = 0; i < 4; ++i)
p[i] = i;
for (i = 16; i--; )
A[i] = matrix->d[i];
/* LU decomposition with partial pivoting */
for (k = 0; k < 4; ++k) {
pivot = find_pivot(&A[k * 4], k);
if (pivot != k) {
swap_unsigned(&p[k], &p[pivot]);
swap_rows(&A[k], &A[pivot]);
}
pv = A[k * 4 + k];
if (fabs(pv) < 1e-9)
return -1; /* zero pivot, not invertible */
for (i = k + 1; i < 4; ++i) {
A[i + k * 4] /= pv;
for (j = k + 1; j < 4; ++j)
A[i + j * 4] -= A[i + k * 4] * A[k + j * 4];
}
}
return 0;
}
static void
inverse_transform(const double *LU, const unsigned *p, float *v)
{
/* Solve A * x = v, when we have P * A = L * U.
* P * A * x = P * v => L * U * x = P * v
* Let U * x = b, then L * b = P * v.
*/
double b[4];
unsigned j;
/* Forward substitution, column version, solves L * b = P * v */
/* The diagonal of L is all ones, and not explicitly stored. */
b[0] = v[p[0]];
b[1] = (double)v[p[1]] - b[0] * LU[1 + 0 * 4];
b[2] = (double)v[p[2]] - b[0] * LU[2 + 0 * 4];
b[3] = (double)v[p[3]] - b[0] * LU[3 + 0 * 4];
b[2] -= b[1] * LU[2 + 1 * 4];
b[3] -= b[1] * LU[3 + 1 * 4];
b[3] -= b[2] * LU[3 + 2 * 4];
/* backward substitution, column version, solves U * y = b */
#if 1
/* hand-unrolled, 25% faster for whole function */
b[3] /= LU[3 + 3 * 4];
b[0] -= b[3] * LU[0 + 3 * 4];
b[1] -= b[3] * LU[1 + 3 * 4];
b[2] -= b[3] * LU[2 + 3 * 4];
b[2] /= LU[2 + 2 * 4];
b[0] -= b[2] * LU[0 + 2 * 4];
b[1] -= b[2] * LU[1 + 2 * 4];
b[1] /= LU[1 + 1 * 4];
b[0] -= b[1] * LU[0 + 1 * 4];
b[0] /= LU[0 + 0 * 4];
#else
for (j = 3; j > 0; --j) {
unsigned k;
b[j] /= LU[j + j * 4];
for (k = 0; k < j; ++k)
b[k] -= b[j] * LU[k + j * 4];
}
b[0] /= LU[0 + 0 * 4];
#endif
/* the result */
for (j = 0; j < 4; ++j)
v[j] = b[j];
}
WL_EXPORT int
weston_matrix_invert(struct weston_matrix *inverse,
const struct weston_matrix *matrix)
{
double LU[16]; /* column-major */
unsigned perm[4]; /* permutation */
unsigned c;
if (matrix_invert(LU, perm, matrix) < 0)
return -1;
weston_matrix_init(inverse);
for (c = 0; c < 4; ++c)
inverse_transform(LU, perm, &inverse->d[c * 4]);
inverse->type = matrix->type;
return 0;
}
static bool
near_zero(float a)
{
if (fabs(a) > 0.00001)
return false;
return true;
}
static float
get_el(const struct weston_matrix *matrix, int row, int col)
{
assert(row >= 0 && row <= 3);
assert(col >= 0 && col <= 3);
return matrix->d[col * 4 + row];
}
static bool
near_zero_at(const struct weston_matrix *matrix, int row, int col)
{
return near_zero(get_el(matrix, row, col));
}
static bool
near_one_at(const struct weston_matrix *matrix, int row, int col)
{
return near_zero(get_el(matrix, row, col) - 1.0);
}
static bool
near_pm_one_at(const struct weston_matrix *matrix, int row, int col)
{
return near_zero(fabs(get_el(matrix, row, col)) - 1.0);
}
static bool
near_int_at(const struct weston_matrix *matrix, int row, int col)
{
float el = get_el(matrix, row, col);
return near_zero(roundf(el) - el);
}
/* Lazy decompose the matrix to figure out whether its operations will
* cause an image to look ugly without some kind of filtering.
*
* while this is a 3D transformation matrix, we only concern ourselves
* with 2D for this test. We do use some small rounding to try to catch
* sequences of operations that lead back to a matrix that doesn't
* require filters.
*
* We assume the matrix won't be used to transform a vector with w != 1.0
*
* Filtering will be necessary when:
* a non-integral translation is applied
* non-affine (perspective) translation is in use
* any scaling (other than -1) is in use
* a rotation that isn't a multiple of 90 degrees about Z is present
*/
WL_EXPORT bool
weston_matrix_needs_filtering(const struct weston_matrix *matrix)
{
/* check for non-integral X/Y translation - ignore Z */
if (!near_int_at(matrix, 0, 3) ||
!near_int_at(matrix, 1, 3))
return true;
/* Any transform matrix that matches this will be non-affine. */
if (!near_zero_at(matrix, 3, 0) ||
!near_zero_at(matrix, 3, 1) ||
!near_zero_at(matrix, 3, 2) ||
!near_pm_one_at(matrix, 3, 3))
return true;
/* Check for anything that could come from a rotation that isn't
* around the Z axis:
* [ ? ? 0 ? ]
* [ ? ? 0 ? ]
* [ 0 0 ±1 ? ]
* [ ? ? ? 1 ]
* It's not clear that we'd realistically see a -1 in [2][2], but
* it wouldn't require filtering if we did, so allow it.
*/
if (!near_zero_at(matrix, 0, 2) ||
!near_zero_at(matrix, 1, 2) ||
!near_zero_at(matrix, 2, 0) ||
!near_zero_at(matrix, 2, 1) ||
!near_pm_one_at(matrix, 2, 2))
return true;
/* We've culled the low hanging fruit, now let's match the only
* matrices left we don't have to filter, before defaulting to
* filtering.
*
* These are a combination of testing rotation and scaling at once: */
if (near_pm_one_at(matrix, 0, 0)) {
/* This could be a multiple of 90 degree rotation about Z,
* possibly with a flip, if the matrix is of the form:
* [ ±1 0 0 ? ]
* [ 0 ±1 0 ? ]
* [ 0 0 1 ? ]
* [ 0 0 0 1 ]
* Forcing ±1 excludes non-unity scale.
*/
if (near_zero_at(matrix, 1, 0) &&
near_zero_at(matrix, 0, 1) &&
near_pm_one_at(matrix, 1, 1))
return false;
}
if (near_zero_at(matrix, 0, 0)) {
/* This could be a multiple of 90 degree rotation about Z,
* possibly with a flip, if the matrix is of the form:
* [ 0 ±1 0 ? ]
* [ ±1 0 0 ? ]
* [ 0 0 1 ? ]
* [ 0 0 0 1 ]
* Forcing ±1 excludes non-unity scale.
*/
if (near_zero_at(matrix, 1, 1) &&
near_pm_one_at(matrix, 1, 0) &&
near_pm_one_at(matrix, 0, 1))
return false;
}
/* The matrix wasn't "simple" enough to classify with dumb
* heuristics, so recommend filtering */
return true;
}
/** Examine a matrix to see if it applies a standard output transform.
*
* \param mat matrix to examine
* \param[out] transform the transform, if applicable
* \return true if a standard transform is present
* Note that the check only considers rotations and flips.
* If any other scale or translation is present, those may have to
* be dealt with by the caller in some way.
*/
WL_EXPORT bool
weston_matrix_to_transform(const struct weston_matrix *mat,
enum wl_output_transform *transform)
{
/* As a first pass we can eliminate any matrix that doesn't have
* zeroes in these positions:
* [ ? ? 0 ? ]
* [ ? ? 0 ? ]
* [ 0 0 ? ? ]
* [ 0 0 0 ? ]
* As they will be non-affine, or rotations about axes
* other than Z.
*/
if (!near_zero_at(mat, 2, 0) ||
!near_zero_at(mat, 3, 0) ||
!near_zero_at(mat, 2, 1) ||
!near_zero_at(mat, 3, 1) ||
!near_zero_at(mat, 0, 2) ||
!near_zero_at(mat, 1, 2) ||
!near_zero_at(mat, 3, 2))
return false;
/* Enforce the form:
* [ ? ? 0 ? ]
* [ ? ? 0 ? ]
* [ 0 0 ? ? ]
* [ 0 0 0 1 ]
* While we could scale all the elements by a constant to make
* 3,3 == 1, we choose to be lazy and not bother. A matrix
* that doesn't fit this form seems likely to be too complicated
* to pass the other checks.
*/
if (!near_one_at(mat, 3, 3))
return false;
if (near_zero_at(mat, 0, 0)) {
if (!near_zero_at(mat, 1, 1))
return false;
/* We now have a matrix like:
* [ 0 A 0 ? ]
* [ B 0 0 ? ]
* [ 0 0 ? ? ]
* [ 0 0 0 1 ]
* When transforming a vector with a matrix of this form, the X
* and Y coordinates are effectively exchanged, so we have a
* 90 or 270 degree rotation (not 0 or 180), and could have
* a flip depending on the signs of A and B.
*
* We don't require A and B to have the same absolute value,
* so there may be independent scales in the X or Y dimensions.
*/
if (get_el(mat, 0, 1) > 0) {
/* A is positive */
if (get_el(mat, 1, 0) > 0)
*transform = WL_OUTPUT_TRANSFORM_FLIPPED_90;
else
*transform = WL_OUTPUT_TRANSFORM_90;
} else {
/* A is negative */
if (get_el(mat, 1, 0) > 0)
*transform = WL_OUTPUT_TRANSFORM_270;
else
*transform = WL_OUTPUT_TRANSFORM_FLIPPED_270;
}
} else if (near_zero_at(mat, 1, 0)) {
if (!near_zero_at(mat, 0, 1))
return false;
/* We now have a matrix like:
* [ A 0 0 ? ]
* [ 0 B 0 ? ]
* [ 0 0 ? ? ]
* [ 0 0 0 1 ]
* This case won't exchange the X and Y inputs, so the
* transform is 0 or 180 degrees. We could have a flip
* depending on the signs of A and B.
*
* We don't require A and B to have the same absolute value,
* so there may be independent scales in the X or Y dimensions.
*/
if (get_el(mat, 0, 0) > 0) {
/* A is positive */
if (get_el(mat, 1, 1) > 0)
*transform = WL_OUTPUT_TRANSFORM_NORMAL;
else
*transform = WL_OUTPUT_TRANSFORM_FLIPPED_180;
} else {
/* A is negative */
if (get_el(mat, 1, 1) > 0)
*transform = WL_OUTPUT_TRANSFORM_FLIPPED;
else
*transform = WL_OUTPUT_TRANSFORM_180;
}
} else {
return false;
}
return true;
}
WL_EXPORT void
weston_matrix_init_transform(struct weston_matrix *matrix,
enum wl_output_transform transform,
int x, int y, int width, int height,
int scale)
{
weston_matrix_init(matrix);
weston_matrix_translate(matrix, -x, -y, 0);
switch (transform) {
case WL_OUTPUT_TRANSFORM_FLIPPED:
case WL_OUTPUT_TRANSFORM_FLIPPED_90:
case WL_OUTPUT_TRANSFORM_FLIPPED_180:
case WL_OUTPUT_TRANSFORM_FLIPPED_270:
weston_matrix_scale(matrix, -1, 1, 1);
weston_matrix_translate(matrix, width, 0, 0);
break;
default:
break;
}
switch (transform) {
default:
case WL_OUTPUT_TRANSFORM_NORMAL:
case WL_OUTPUT_TRANSFORM_FLIPPED:
break;
case WL_OUTPUT_TRANSFORM_90:
case WL_OUTPUT_TRANSFORM_FLIPPED_90:
weston_matrix_rotate_xy(matrix, 0, -1);
weston_matrix_translate(matrix, 0, width, 0);
break;
case WL_OUTPUT_TRANSFORM_180:
case WL_OUTPUT_TRANSFORM_FLIPPED_180:
weston_matrix_rotate_xy(matrix, -1, 0);
weston_matrix_translate(matrix,
width, height, 0);
break;
case WL_OUTPUT_TRANSFORM_270:
case WL_OUTPUT_TRANSFORM_FLIPPED_270:
weston_matrix_rotate_xy(matrix, 0, 1);
weston_matrix_translate(matrix, height, 0, 0);
break;
}
weston_matrix_scale(matrix, scale, scale, 1);
}