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/**
* Copyright © 2016 Mattias Andrée <maandree@member.fsf.org>
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#ifndef LIBCLUT_H
#define LIBCLUT_H
#include <stddef.h>
/**
* Modify a ramp.
*
* None of the parameter may have side-effects.
*
* This is intended for internal use.
*
* @param ramp Pointer to the gamma ramps, must have and array
* named `channel` and a scalar named `channel` followed
* by "_size".
* @param channel The channel, must be either "red", "green", or "blue".
* @param type The data type used for each stop in the ramps.
* @param expr Expression that evalutes the value a stop should have.
* It can use the variable `LIBCLUT_VALUE` to get the
* current value of the stop.
*/
#define libclut__(ramp, channel, type, expr) \
do \
{ \
size_t i__, n__ = (ramp)->channel##_size; \
type LIBCLUT_VALUE; \
for (i__ = 0; i__ < n__; i__++) \
{ \
LIBCLUT_VALUE = (ramp)->channel[i__]; \
(ramp)->channel[i__] = (type)(expr); \
} \
} \
while (0)
/**
* Apply contrast correction on the colour curves using sRGB.
*
* In this context, contrast is a measure of difference between
* the whitepoint and blackpoint, if the difference is 0 than
* they are both grey.
*
* None of the parameter may have side-effects.
*
* @param ramp Pointer to the gamma ramps, must have the arrays
* `red`, `green`, and `blue`, and the scalars
* `red_size`, `green_size`, and `blue_size`. Ramp
* structures from libgamma can be used.
* @param max The maximum value on each stop in the ramps.
* @param type The data type used for each stop in the ramps.
* @param r The contrast parameter for the red curve.
* @param g The contrast parameter for the green curve.
* @param b The contrast parameter for the blue curve.
*/
#define libclut_rgb_contrast(ramp, max, type, r, g, b) \
do \
{ \
if (r != 1.0) libclut__(ramp, red, type, LIBCLUT_VALUE - (max) / 2.0 * r + (max) / 2.0); \
if (g != 1.0) libclut__(ramp, green, type, LIBCLUT_VALUE - (max) / 2.0 * g + (max) / 2.0); \
if (b != 1.0) libclut__(ramp, blue, type, LIBCLUT_VALUE - (max) / 2.0 * b + (max) / 2.0); \
} \
while (0)
/**
* Apply contrast correction on the colour curves using CIE xyY.
*
* In this context, contrast is a measure of difference between
* the whitepoint and blackpoint, if the difference is 0 than
* they are both grey.
*
* None of the parameter may have side-effects.
*
* @param ramp Pointer to the gamma ramps, must have the arrays
* `red`, `green`, and `blue`, and the scalars
* `red_size`, `green_size`, and `blue_size`. Ramp
* structures from libgamma can be used.
* @param max The maximum value on each stop in the ramps.
* @param type The data type used for each stop in the ramps.
* @param r The contrast parameter for the red curve.
* @param g The contrast parameter for the green curve.
* @param b The contrast parameter for the blue curve.
*/
#define libclut_cie_contrast(ramp, max, type, r, g, b) \
do \
{ \
size_t rn__ = (ramp)->red_size; \
size_t gn__ = (ramp)->green_size; \
size_t bn__ = (ramp)->blue_size; \
size_t i__; \
double x__, y__, Y__, r__, g__, b__; \
type* rs__ = (ramp)->red; \
type* gs__ = (ramp)->green; \
type* bs__ = (ramp)->blue; \
if ((r == g) && (g == b) && (rn__ == gn__) && (gn__ == bn__)) \
{ \
if (r == 1.0) \
break; \
for (i__ = 0; i__ < rn__; i__) \
{ \
libclut_model_srgb_to_ciexyy(rs__[i__] / ((double)(max)), gs__[i__] / ((double)(max)), \
bs__[i__] / ((double)(max)), &x__, &y__, &Y__); \
libclut_model_ciexyy_to_srgb(x__, y__, (Y__ - 0.5) * r * 0.5, &r__, &g__, &b__); \
rs__[i__] = (type)(r__ * (double)(max)); \
gs__[i__] = (type)(g__ * (double)(max)); \
bs__[i__] = (type)(b__ * (double)(max)); \
} \
} \
else \
{ \
if ((r == 1.0) && (g == 1.0) && (b == 1.0)) \
break; \
libclut_model_srgb_to_ciexyy(rs__[i__] / ((double)(max)), gs__[i__] / ((double)(max)), \
bs__[i__] / ((double)(max)), &x__, &y__, &Y__); \
for (i__ = 0; i__ < rn__; i__) \
{ \
if (r != 1.0) \
{ \
libclut_model_ciexyy_to_srgb(x__, y__, (Y__ - 0.5) * r * 0.5, &r__, &g__, &b__); \
rs__[i__] = (type)(r__ * (double)(max)); \
} \
if (g != 1.0) \
{ \
libclut_model_ciexyy_to_srgb(x__, y__, (Y__ - 0.5) * g * 0.5, &r__, &g__, &b__); \
gs__[i__] = (type)(g__ * (double)(max)); \
} \
if (b != 1.0) \
{ \
libclut_model_ciexyy_to_srgb(x__, y__, (Y__ - 0.5) * b * 0.5, &r__, &g__, &b__); \
bs__[i__] = (type)(b__ * (double)(max)); \
} \
} \
} \
} \
while (0)
#endif
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