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-rw-r--r--modules/noise/noise.cpp152
1 files changed, 108 insertions, 44 deletions
diff --git a/modules/noise/noise.cpp b/modules/noise/noise.cpp
index b8c1587ec3..1115d92f58 100644
--- a/modules/noise/noise.cpp
+++ b/modules/noise/noise.cpp
@@ -32,21 +32,40 @@
#include <float.h>
-Ref<Image> Noise::get_seamless_image(int p_width, int p_height, int p_depth, bool p_invert, bool p_in_3d_space, real_t p_blend_skirt, bool p_normalize) const {
- ERR_FAIL_COND_V(p_width <= 0 || p_height <= 0, Ref<Image>());
+Vector<Ref<Image>> Noise::_get_seamless_image(int p_width, int p_height, int p_depth, bool p_invert, bool p_in_3d_space, real_t p_blend_skirt, bool p_normalize) const {
+ ERR_FAIL_COND_V(p_width <= 0 || p_height <= 0 || p_depth <= 0, Vector<Ref<Image>>());
int skirt_width = MAX(1, p_width * p_blend_skirt);
int skirt_height = MAX(1, p_height * p_blend_skirt);
+ int skirt_depth = MAX(1, p_depth * p_blend_skirt);
int src_width = p_width + skirt_width;
int src_height = p_height + skirt_height;
+ int src_depth = p_depth + skirt_depth;
+
+ Vector<Ref<Image>> src = _get_image(src_width, src_height, src_depth, p_invert, p_in_3d_space, p_normalize);
+ bool grayscale = (src[0]->get_format() == Image::FORMAT_L8);
- Ref<Image> src = get_image(src_width, src_height, p_depth, p_invert, p_in_3d_space, p_normalize);
- bool grayscale = (src->get_format() == Image::FORMAT_L8);
if (grayscale) {
- return _generate_seamless_image<uint8_t>(src, p_width, p_height, p_invert, p_blend_skirt);
+ return _generate_seamless_image<uint8_t>(src, p_width, p_height, p_depth, p_invert, p_blend_skirt);
} else {
- return _generate_seamless_image<uint32_t>(src, p_width, p_height, p_invert, p_blend_skirt);
+ return _generate_seamless_image<uint32_t>(src, p_width, p_height, p_depth, p_invert, p_blend_skirt);
+ }
+}
+
+Ref<Image> Noise::get_seamless_image(int p_width, int p_height, bool p_invert, bool p_in_3d_space, real_t p_blend_skirt, bool p_normalize) const {
+ Vector<Ref<Image>> images = _get_seamless_image(p_width, p_height, 1, p_invert, p_in_3d_space, p_blend_skirt, p_normalize);
+ return images[0];
+}
+
+TypedArray<Image> Noise::get_seamless_image_3d(int p_width, int p_height, int p_depth, bool p_invert, real_t p_blend_skirt, bool p_normalize) const {
+ Vector<Ref<Image>> images = _get_seamless_image(p_width, p_height, p_depth, p_invert, true, p_blend_skirt, p_normalize);
+
+ TypedArray<Image> ret;
+ ret.resize(images.size());
+ for (int i = 0; i < images.size(); i++) {
+ ret[i] = images[i];
}
+ return ret;
}
// Template specialization for faster grayscale blending.
@@ -58,61 +77,104 @@ uint8_t Noise::_alpha_blend<uint8_t>(uint8_t p_bg, uint8_t p_fg, int p_alpha) co
return (uint8_t)((alpha * p_fg + inv_alpha * p_bg) >> 8);
}
-Ref<Image> Noise::get_image(int p_width, int p_height, int p_depth, bool p_invert, bool p_in_3d_space, bool p_normalize) const {
- ERR_FAIL_COND_V(p_width <= 0 || p_height <= 0, Ref<Image>());
-
- Vector<uint8_t> data;
- data.resize(p_width * p_height);
+Vector<Ref<Image>> Noise::_get_image(int p_width, int p_height, int p_depth, bool p_invert, bool p_in_3d_space, bool p_normalize) const {
+ ERR_FAIL_COND_V(p_width <= 0 || p_height <= 0 || p_depth <= 0, Vector<Ref<Image>>());
- uint8_t *wd8 = data.ptrw();
+ Vector<Ref<Image>> images;
+ images.resize(p_depth);
if (p_normalize) {
// Get all values and identify min/max values.
- Vector<real_t> values;
- values.resize(p_width * p_height);
+ LocalVector<real_t> values;
+ values.resize(p_width * p_height * p_depth);
+
real_t min_val = FLT_MAX;
real_t max_val = -FLT_MAX;
- for (int y = 0, i = 0; y < p_height; y++) {
- for (int x = 0; x < p_width; x++, i++) {
- values.set(i, p_in_3d_space ? get_noise_3d(x, y, p_depth) : get_noise_2d(x, y));
- if (values[i] > max_val) {
- max_val = values[i];
- }
- if (values[i] < min_val) {
- min_val = values[i];
+ int idx = 0;
+ for (int d = 0; d < p_depth; d++) {
+ for (int y = 0; y < p_height; y++) {
+ for (int x = 0; x < p_width; x++) {
+ values[idx] = p_in_3d_space ? get_noise_3d(x, y, d) : get_noise_2d(x, y);
+ if (values[idx] > max_val) {
+ max_val = values[idx];
+ }
+ if (values[idx] < min_val) {
+ min_val = values[idx];
+ }
+ idx++;
}
}
}
+ idx = 0;
// Normalize values and write to texture.
- uint8_t ivalue;
- for (int i = 0, x = 0; i < p_height; i++) {
- for (int j = 0; j < p_width; j++, x++) {
- if (max_val == min_val) {
- ivalue = 0;
- } else {
- ivalue = static_cast<uint8_t>(CLAMP((values[x] - min_val) / (max_val - min_val) * 255.f, 0, 255));
- }
-
- if (p_invert) {
- ivalue = 255 - ivalue;
+ for (int d = 0; d < p_depth; d++) {
+ Vector<uint8_t> data;
+ data.resize(p_width * p_height);
+
+ uint8_t *wd8 = data.ptrw();
+ uint8_t ivalue;
+
+ for (int y = 0; y < p_height; y++) {
+ for (int x = 0; x < p_width; x++) {
+ if (max_val == min_val) {
+ ivalue = 0;
+ } else {
+ ivalue = static_cast<uint8_t>(CLAMP((values[idx] - min_val) / (max_val - min_val) * 255.f, 0, 255));
+ }
+
+ if (p_invert) {
+ ivalue = 255 - ivalue;
+ }
+
+ wd8[x + y * p_width] = ivalue;
+ idx++;
}
-
- wd8[x] = ivalue;
}
+ Ref<Image> img = memnew(Image(p_width, p_height, false, Image::FORMAT_L8, data));
+ images.write[d] = img;
}
} else {
// Without normalization, the expected range of the noise function is [-1, 1].
- uint8_t ivalue;
- for (int y = 0, i = 0; y < p_height; y++) {
- for (int x = 0; x < p_width; x++, i++) {
- float value = (p_in_3d_space ? get_noise_3d(x, y, p_depth) : get_noise_2d(x, y));
- ivalue = static_cast<uint8_t>(CLAMP(value * 127.5f + 127.5f, 0.0f, 255.0f));
- wd8[i] = p_invert ? (255 - ivalue) : ivalue;
+
+ for (int d = 0; d < p_depth; d++) {
+ Vector<uint8_t> data;
+ data.resize(p_width * p_height);
+
+ uint8_t *wd8 = data.ptrw();
+
+ uint8_t ivalue;
+ int idx = 0;
+ for (int y = 0; y < p_height; y++) {
+ for (int x = 0; x < p_width; x++) {
+ float value = (p_in_3d_space ? get_noise_3d(x, y, d) : get_noise_2d(x, y));
+ ivalue = static_cast<uint8_t>(CLAMP(value * 127.5f + 127.5f, 0.0f, 255.0f));
+ wd8[idx] = p_invert ? (255 - ivalue) : ivalue;
+ idx++;
+ }
}
+
+ Ref<Image> img = memnew(Image(p_width, p_height, false, Image::FORMAT_L8, data));
+ images.write[d] = img;
}
}
- return memnew(Image(p_width, p_height, false, Image::FORMAT_L8, data));
+ return images;
+}
+
+Ref<Image> Noise::get_image(int p_width, int p_height, bool p_invert, bool p_in_3d_space, bool p_normalize) const {
+ Vector<Ref<Image>> images = _get_image(p_width, p_height, 1, p_invert, p_in_3d_space, p_normalize);
+ return images[0];
+}
+
+TypedArray<Image> Noise::get_image_3d(int p_width, int p_height, int p_depth, bool p_invert, bool p_normalize) const {
+ Vector<Ref<Image>> images = _get_image(p_width, p_height, p_depth, p_invert, true, p_normalize);
+
+ TypedArray<Image> ret;
+ ret.resize(images.size());
+ for (int i = 0; i < images.size(); i++) {
+ ret[i] = images[i];
+ }
+ return ret;
}
void Noise::_bind_methods() {
@@ -124,6 +186,8 @@ void Noise::_bind_methods() {
ClassDB::bind_method(D_METHOD("get_noise_3dv", "v"), &Noise::get_noise_3dv);
// Textures.
- ClassDB::bind_method(D_METHOD("get_image", "width", "height", "depth", "invert", "in_3d_space", "normalize"), &Noise::get_image, DEFVAL(false), DEFVAL(false), DEFVAL(true));
- ClassDB::bind_method(D_METHOD("get_seamless_image", "width", "height", "depth", "invert", "in_3d_space", "skirt", "normalize"), &Noise::get_seamless_image, DEFVAL(false), DEFVAL(false), DEFVAL(0.1), DEFVAL(true));
+ ClassDB::bind_method(D_METHOD("get_image", "width", "height", "invert", "in_3d_space", "normalize"), &Noise::get_image, DEFVAL(false), DEFVAL(false), DEFVAL(true));
+ ClassDB::bind_method(D_METHOD("get_seamless_image", "width", "height", "invert", "in_3d_space", "skirt", "normalize"), &Noise::get_seamless_image, DEFVAL(false), DEFVAL(false), DEFVAL(0.1), DEFVAL(true));
+ ClassDB::bind_method(D_METHOD("get_image_3d", "width", "height", "depth", "invert", "normalize"), &Noise::get_image_3d, DEFVAL(false), DEFVAL(true));
+ ClassDB::bind_method(D_METHOD("get_seamless_image_3d", "width", "height", "depth", "invert", "skirt", "normalize"), &Noise::get_seamless_image_3d, DEFVAL(false), DEFVAL(0.1), DEFVAL(true));
}