/* * This file is part of OpenTTD. * OpenTTD 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, version 2. * OpenTTD 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 OpenTTD. If not, see . */ /** @file tgp.cpp OTTD Perlin Noise Landscape Generator, aka TerraGenesis Perlin */ #include "stdafx.h" #include "clear_map.h" #include "void_map.h" #include "genworld.h" #include "core/random_func.hpp" #include "landscape_type.h" #include "safeguards.h" /* * * Quickie guide to Perlin Noise * Perlin noise is a predictable pseudo random number sequence. By generating * it in 2 dimensions, it becomes a useful random map that, for a given seed * and starting X & Y, is entirely predictable. On the face of it, that may not * be useful. However, it means that if you want to replay a map in a different * terrain, or just vary the sea level, you just re-run the generator with the * same seed. The seed is an int32_t, and is randomised on each run of New Game. * The Scenario Generator does not randomise the value, so that you can * experiment with one terrain until you are happy, or click "Random" for a new * random seed. * * Perlin Noise is a series of "octaves" of random noise added together. By * reducing the amplitude of the noise with each octave, the first octave of * noise defines the main terrain sweep, the next the ripples on that, and the * next the ripples on that. I use 6 octaves, with the amplitude controlled by * a power ratio, usually known as a persistence or p value. This I vary by the * smoothness selection, as can be seen in the table below. The closer to 1, * the more of that octave is added. Each octave is however raised to the power * of its position in the list, so the last entry in the "smooth" row, 0.35, is * raised to the power of 6, so can only add 0.001838... of the amplitude to * the running total. * * In other words; the first p value sets the general shape of the terrain, the * second sets the major variations to that, ... until finally the smallest * bumps are added. * * Usefully, this routine is totally scalable; so when 32bpp comes along, the * terrain can be as bumpy as you like! It is also infinitely expandable; a * single random seed terrain continues in X & Y as far as you care to * calculate. In theory, we could use just one seed value, but randomly select * where in the Perlin XY space we use for the terrain. Personally I prefer * using a simple (0, 0) to (X, Y), with a varying seed. * * * Other things i have had to do: mountainous wasn't mountainous enough, and * since we only have 0..15 heights available, I add a second generated map * (with a modified seed), onto the original. This generally raises the * terrain, which then needs scaling back down. Overall effect is a general * uplift. * * However, the values on the top of mountains are then almost guaranteed to go * too high, so large flat plateaus appeared at height 15. To counter this, I * scale all heights above 12 to proportion up to 15. It still makes the * mountains have flattish tops, rather than craggy peaks, but at least they * aren't smooth as glass. * * * For a full discussion of Perlin Noise, please visit: * http://freespace.virgin.net/hugo.elias/models/m_perlin.htm * * * Evolution II * * The algorithm as described in the above link suggests to compute each tile height * as composition of several noise waves. Some of them are computed directly by * noise(x, y) function, some are calculated using linear approximation. Our * first implementation of perlin_noise_2D() used 4 noise(x, y) calls plus * 3 linear interpolations. It was called 6 times for each tile. This was a bit * CPU expensive. * * The following implementation uses optimized algorithm that should produce * the same quality result with much less computations, but more memory accesses. * The overall speedup should be 300% to 800% depending on CPU and memory speed. * * I will try to explain it on the example below: * * Have a map of 4 x 4 tiles, our simplified noise generator produces only two * values -1 and +1, use 3 octaves with wave length 1, 2 and 4, with amplitudes * 3, 2, 1. Original algorithm produces: * * h00 = lerp(lerp(-3, 3, 0/4), lerp(3, -3, 0/4), 0/4) + lerp(lerp(-2, 2, 0/2), lerp( 2, -2, 0/2), 0/2) + -1 = lerp(-3.0, 3.0, 0/4) + lerp(-2, 2, 0/2) + -1 = -3.0 + -2 + -1 = -6.0 * h01 = lerp(lerp(-3, 3, 1/4), lerp(3, -3, 1/4), 0/4) + lerp(lerp(-2, 2, 1/2), lerp( 2, -2, 1/2), 0/2) + 1 = lerp(-1.5, 1.5, 0/4) + lerp( 0, 0, 0/2) + 1 = -1.5 + 0 + 1 = -0.5 * h02 = lerp(lerp(-3, 3, 2/4), lerp(3, -3, 2/4), 0/4) + lerp(lerp( 2, -2, 0/2), lerp(-2, 2, 0/2), 0/2) + -1 = lerp( 0, 0, 0/4) + lerp( 2, -2, 0/2) + -1 = 0 + 2 + -1 = 1.0 * h03 = lerp(lerp(-3, 3, 3/4), lerp(3, -3, 3/4), 0/4) + lerp(lerp( 2, -2, 1/2), lerp(-2, 2, 1/2), 0/2) + 1 = lerp( 1.5, -1.5, 0/4) + lerp( 0, 0, 0/2) + 1 = 1.5 + 0 + 1 = 2.5 * * h10 = lerp(lerp(-3, 3, 0/4), lerp(3, -3, 0/4), 1/4) + lerp(lerp(-2, 2, 0/2), lerp( 2, -2, 0/2), 1/2) + 1 = lerp(-3.0, 3.0, 1/4) + lerp(-2, 2, 1/2) + 1 = -1.5 + 0 + 1 = -0.5 * h11 = lerp(lerp(-3, 3, 1/4), lerp(3, -3, 1/4), 1/4) + lerp(lerp(-2, 2, 1/2), lerp( 2, -2, 1/2), 1/2) + -1 = lerp(-1.5, 1.5, 1/4) + lerp( 0, 0, 1/2) + -1 = -0.75 + 0 + -1 = -1.75 * h12 = lerp(lerp(-3, 3, 2/4), lerp(3, -3, 2/4), 1/4) + lerp(lerp( 2, -2, 0/2), lerp(-2, 2, 0/2), 1/2) + 1 = lerp( 0, 0, 1/4) + lerp( 2, -2, 1/2) + 1 = 0 + 0 + 1 = 1.0 * h13 = lerp(lerp(-3, 3, 3/4), lerp(3, -3, 3/4), 1/4) + lerp(lerp( 2, -2, 1/2), lerp(-2, 2, 1/2), 1/2) + -1 = lerp( 1.5, -1.5, 1/4) + lerp( 0, 0, 1/2) + -1 = 0.75 + 0 + -1 = -0.25 * * * Optimization 1: * * 1) we need to allocate a bit more tiles: (size_x + 1) * (size_y + 1) = (5 * 5): * * 2) setup corner values using amplitude 3 * { -3.0 X X X 3.0 } * { X X X X X } * { X X X X X } * { X X X X X } * { 3.0 X X X -3.0 } * * 3a) interpolate values in the middle * { -3.0 X 0.0 X 3.0 } * { X X X X X } * { 0.0 X 0.0 X 0.0 } * { X X X X X } * { 3.0 X 0.0 X -3.0 } * * 3b) add patches with amplitude 2 to them * { -5.0 X 2.0 X 1.0 } * { X X X X X } * { 2.0 X -2.0 X 2.0 } * { X X X X X } * { 1.0 X 2.0 X -5.0 } * * 4a) interpolate values in the middle * { -5.0 -1.5 2.0 1.5 1.0 } * { -1.5 -0.75 0.0 0.75 1.5 } * { 2.0 0.0 -2.0 0.0 2.0 } * { 1.5 0.75 0.0 -0.75 -1.5 } * { 1.0 1.5 2.0 -1.5 -5.0 } * * 4b) add patches with amplitude 1 to them * { -6.0 -0.5 1.0 2.5 0.0 } * { -0.5 -1.75 1.0 -0.25 2.5 } * { 1.0 1.0 -3.0 1.0 1.0 } * { 2.5 -0.25 1.0 -1.75 -0.5 } * { 0.0 2.5 1.0 -0.5 -6.0 } * * * * Optimization 2: * * As you can see above, each noise function was called just once. Therefore * we don't need to use noise function that calculates the noise from x, y and * some prime. The same quality result we can obtain using standard Random() * function instead. * */ /** Fixed point type for heights */ using Height = int16_t; static const int height_decimal_bits = 4; /** Fixed point array for amplitudes (and percent values) */ using Amplitude = int; static const int amplitude_decimal_bits = 10; /** Height map - allocated array of heights (MapSizeX() + 1) x (MapSizeY() + 1) */ struct HeightMap { std::vector h; //< array of heights /* Even though the sizes are always positive, there are many cases where * X and Y need to be signed integers due to subtractions. */ int dim_x; //< height map size_x Map::SizeX() + 1 int size_x; //< Map::SizeX() int size_y; //< Map::SizeY() /** * Height map accessor * @param x X position * @param y Y position * @return height as fixed point number */ inline Height &height(uint x, uint y) { return h[x + y * dim_x]; } }; /** Global height map instance */ static HeightMap _height_map = { {}, 0, 0, 0 }; /** Conversion: int to Height */ #define I2H(i) ((i) << height_decimal_bits) /** Conversion: Height to int */ #define H2I(i) ((i) >> height_decimal_bits) /** Conversion: int to Amplitude */ #define I2A(i) ((i) << amplitude_decimal_bits) /** Conversion: Amplitude to int */ #define A2I(i) ((i) >> amplitude_decimal_bits) /** Conversion: Amplitude to Height */ #define A2H(a) ((a) >> (amplitude_decimal_bits - height_decimal_bits)) /** Maximum number of TGP noise frequencies. */ static const int MAX_TGP_FREQUENCIES = 10; /** Desired water percentage (100% == 1024) - indexed by _settings_game.difficulty.quantity_sea_lakes */ static const Amplitude _water_percent[4] = {70, 170, 270, 420}; /** * Gets the maximum allowed height while generating a map based on * mapsize, terraintype, and the maximum height level. * @return The maximum height for the map generation. * @note Values should never be lower than 3 since the minimum snowline height is 2. */ static Height TGPGetMaxHeight() { if (_settings_game.difficulty.terrain_type == CUSTOM_TERRAIN_TYPE_NUMBER_DIFFICULTY) { /* TGP never reaches this height; this means that if a user inputs "2", * it would create a flat map without the "+ 1". But that would * overflow on "255". So we reduce it by 1 to get back in range. */ return I2H(_settings_game.game_creation.custom_terrain_type + 1) - 1; } /** * Desired maximum height - indexed by: * - _settings_game.difficulty.terrain_type * - min(Map::LogX(), Map::LogY()) - MIN_MAP_SIZE_BITS * * It is indexed by map size as well as terrain type since the map size limits the height of * a usable mountain. For example, on a 64x64 map a 24 high single peak mountain (as if you * raised land 24 times in the center of the map) will leave only a ring of about 10 tiles * around the mountain to build on. On a 4096x4096 map, it won't cover any major part of the map. */ static const int max_height[5][MAX_MAP_SIZE_BITS - MIN_MAP_SIZE_BITS + 1] = { /* 64 128 256 512 1024 2048 4096 */ { 3, 3, 3, 3, 4, 5, 7 }, ///< Very flat { 5, 7, 8, 9, 14, 19, 31 }, ///< Flat { 8, 9, 10, 15, 23, 37, 61 }, ///< Hilly { 10, 11, 17, 19, 49, 63, 73 }, ///< Mountainous { 12, 19, 25, 31, 67, 75, 87 }, ///< Alpinist }; int map_size_bucket = std::min(Map::LogX(), Map::LogY()) - MIN_MAP_SIZE_BITS; int max_height_from_table = max_height[_settings_game.difficulty.terrain_type][map_size_bucket]; /* If there is a manual map height limit, clamp to it. */ if (_settings_game.construction.map_height_limit != 0) { max_height_from_table = std::min(max_height_from_table, _settings_game.construction.map_height_limit); } return I2H(max_height_from_table); } /** * Get an overestimation of the highest peak TGP wants to generate. */ uint GetEstimationTGPMapHeight() { return H2I(TGPGetMaxHeight()); } /** * Get the amplitude associated with the currently selected * smoothness and maximum height level. * @param frequency The frequency to get the amplitudes for * @return The amplitudes to apply to the map. */ static Amplitude GetAmplitude(int frequency) { /* Base noise amplitudes (multiplied by 1024) and indexed by "smoothness setting" and log2(frequency). */ static const Amplitude amplitudes[][7] = { /* lowest frequency ...... highest (every corner) */ {16000, 5600, 1968, 688, 240, 16, 16}, ///< Very smooth {24000, 12800, 6400, 2700, 1024, 128, 16}, ///< Smooth {32000, 19200, 12800, 8000, 3200, 256, 64}, ///< Rough {48000, 24000, 19200, 16000, 8000, 512, 320}, ///< Very rough }; /* * Extrapolation factors for ranges before the table. * The extrapolation is needed to account for the higher map heights. They need larger * areas with a particular gradient so that we are able to create maps without too * many steep slopes up to the wanted height level. It's definitely not perfect since * it will bring larger rectangles with similar slopes which makes the rectangular * behaviour of TGP more noticeable. However, these height differentiations cannot * happen over much smaller areas; we basically double the "range" to give a similar * slope for every doubling of map height. */ static const double extrapolation_factors[] = { 3.3, 2.8, 2.3, 1.8 }; int smoothness = _settings_game.game_creation.tgen_smoothness; /* Get the table index, and return that value if possible. */ int index = frequency - MAX_TGP_FREQUENCIES + static_cast(std::size(amplitudes[smoothness])); Amplitude amplitude = amplitudes[smoothness][std::max(0, index)]; if (index >= 0) return amplitude; /* We need to extrapolate the amplitude. */ double extrapolation_factor = extrapolation_factors[smoothness]; int height_range = I2H(16); do { amplitude = (Amplitude)(extrapolation_factor * (double)amplitude); height_range <<= 1; index++; } while (index < 0); return Clamp((TGPGetMaxHeight() - height_range) / height_range, 0, 1) * amplitude; } /** * Check if a X/Y set are within the map. * @param x coordinate x * @param y coordinate y * @return true if within the map */ static inline bool IsValidXY(int x, int y) { return x >= 0 && x < _height_map.size_x && y >= 0 && y < _height_map.size_y; } /** * Allocate array of (MapSizeX()+1)*(MapSizeY()+1) heights and init the _height_map structure members * @return true on success */ static inline bool AllocHeightMap() { assert(_height_map.h.empty()); _height_map.size_x = Map::SizeX(); _height_map.size_y = Map::SizeY(); /* Allocate memory block for height map row pointers */ size_t total_size = static_cast(_height_map.size_x + 1) * (_height_map.size_y + 1); _height_map.dim_x = _height_map.size_x + 1; _height_map.h.resize(total_size); return true; } /** Free height map */ static inline void FreeHeightMap() { _height_map.h.clear(); } /** * Generates new random height in given amplitude (generated numbers will range from - amplitude to + amplitude) * @param rMax Limit of result * @return generated height */ static inline Height RandomHeight(Amplitude rMax) { /* Spread height into range -rMax..+rMax */ return A2H(RandomRange(2 * rMax + 1) - rMax); } /** * Base Perlin noise generator - fills height map with raw Perlin noise. * * This runs several iterations with increasing precision; the last iteration looks at areas * of 1 by 1 tiles, the second to last at 2 by 2 tiles and the initial 2**MAX_TGP_FREQUENCIES * by 2**MAX_TGP_FREQUENCIES tiles. */ static void HeightMapGenerate() { /* Trying to apply noise to uninitialized height map */ assert(!_height_map.h.empty()); int start = std::max(MAX_TGP_FREQUENCIES - (int)std::min(Map::LogX(), Map::LogY()), 0); bool first = true; for (int frequency = start; frequency < MAX_TGP_FREQUENCIES; frequency++) { const Amplitude amplitude = GetAmplitude(frequency); /* Ignore zero amplitudes; it means our map isn't height enough for this * amplitude, so ignore it and continue with the next set of amplitude. */ if (amplitude == 0) continue; const int step = 1 << (MAX_TGP_FREQUENCIES - frequency - 1); if (first) { /* This is first round, we need to establish base heights with step = size_min */ for (int y = 0; y <= _height_map.size_y; y += step) { for (int x = 0; x <= _height_map.size_x; x += step) { Height height = (amplitude > 0) ? RandomHeight(amplitude) : 0; _height_map.height(x, y) = height; } } first = false; continue; } /* It is regular iteration round. * Interpolate height values at odd x, even y tiles */ for (int y = 0; y <= _height_map.size_y; y += 2 * step) { for (int x = 0; x <= _height_map.size_x - 2 * step; x += 2 * step) { Height h00 = _height_map.height(x + 0 * step, y); Height h02 = _height_map.height(x + 2 * step, y); Height h01 = (h00 + h02) / 2; _height_map.height(x + 1 * step, y) = h01; } } /* Interpolate height values at odd y tiles */ for (int y = 0; y <= _height_map.size_y - 2 * step; y += 2 * step) { for (int x = 0; x <= _height_map.size_x; x += step) { Height h00 = _height_map.height(x, y + 0 * step); Height h20 = _height_map.height(x, y + 2 * step); Height h10 = (h00 + h20) / 2; _height_map.height(x, y + 1 * step) = h10; } } /* Add noise for next higher frequency (smaller steps) */ for (int y = 0; y <= _height_map.size_y; y += step) { for (int x = 0; x <= _height_map.size_x; x += step) { _height_map.height(x, y) += RandomHeight(amplitude); } } } } /** Returns min, max and average height from height map */ static void HeightMapGetMinMaxAvg(Height *min_ptr, Height *max_ptr, Height *avg_ptr) { Height h_min, h_max, h_avg; int64_t h_accu = 0; h_min = h_max = _height_map.height(0, 0); /* Get h_min, h_max and accumulate heights into h_accu */ for (const Height &h : _height_map.h) { if (h < h_min) h_min = h; if (h > h_max) h_max = h; h_accu += h; } /* Get average height */ h_avg = (Height)(h_accu / (_height_map.size_x * _height_map.size_y)); /* Return required results */ if (min_ptr != nullptr) *min_ptr = h_min; if (max_ptr != nullptr) *max_ptr = h_max; if (avg_ptr != nullptr) *avg_ptr = h_avg; } /** Dill histogram and return pointer to its base point - to the count of zero heights */ static int *HeightMapMakeHistogram(Height h_min, [[maybe_unused]] Height h_max, int *hist_buf) { int *hist = hist_buf - h_min; /* Count the heights and fill the histogram */ for (const Height &h : _height_map.h) { assert(h >= h_min); assert(h <= h_max); hist[h]++; } return hist; } /** Applies sine wave redistribution onto height map */ static void HeightMapSineTransform(Height h_min, Height h_max) { for (Height &h : _height_map.h) { double fheight; if (h < h_min) continue; /* Transform height into 0..1 space */ fheight = (double)(h - h_min) / (double)(h_max - h_min); /* Apply sine transform depending on landscape type */ switch (_settings_game.game_creation.landscape) { case LT_TOYLAND: case LT_TEMPERATE: /* Move and scale 0..1 into -1..+1 */ fheight = 2 * fheight - 1; /* Sine transform */ fheight = sin(fheight * M_PI_2); /* Transform it back from -1..1 into 0..1 space */ fheight = 0.5 * (fheight + 1); break; case LT_ARCTIC: { /* Arctic terrain needs special height distribution. * Redistribute heights to have more tiles at highest (75%..100%) range */ double sine_upper_limit = 0.75; double linear_compression = 2; if (fheight >= sine_upper_limit) { /* Over the limit we do linear compression up */ fheight = 1.0 - (1.0 - fheight) / linear_compression; } else { double m = 1.0 - (1.0 - sine_upper_limit) / linear_compression; /* Get 0..sine_upper_limit into -1..1 */ fheight = 2.0 * fheight / sine_upper_limit - 1.0; /* Sine wave transform */ fheight = sin(fheight * M_PI_2); /* Get -1..1 back to 0..(1 - (1 - sine_upper_limit) / linear_compression) == 0.0..m */ fheight = 0.5 * (fheight + 1.0) * m; } } break; case LT_TROPIC: { /* Desert terrain needs special height distribution. * Half of tiles should be at lowest (0..25%) heights */ double sine_lower_limit = 0.5; double linear_compression = 2; if (fheight <= sine_lower_limit) { /* Under the limit we do linear compression down */ fheight = fheight / linear_compression; } else { double m = sine_lower_limit / linear_compression; /* Get sine_lower_limit..1 into -1..1 */ fheight = 2.0 * ((fheight - sine_lower_limit) / (1.0 - sine_lower_limit)) - 1.0; /* Sine wave transform */ fheight = sin(fheight * M_PI_2); /* Get -1..1 back to (sine_lower_limit / linear_compression)..1.0 */ fheight = 0.5 * ((1.0 - m) * fheight + (1.0 + m)); } } break; default: NOT_REACHED(); break; } /* Transform it back into h_min..h_max space */ h = (Height)(fheight * (h_max - h_min) + h_min); if (h < 0) h = I2H(0); if (h >= h_max) h = h_max - 1; } } /** * Additional map variety is provided by applying different curve maps * to different parts of the map. A randomized low resolution grid contains * which curve map to use on each part of the make. This filtered non-linearly * to smooth out transitions between curves, so each tile could have between * 100% of one map applied or 25% of four maps. * * The curve maps define different land styles, i.e. lakes, low-lands, hills * and mountain ranges, although these are dependent on the landscape style * chosen as well. * * The level parameter dictates the resolution of the grid. A low resolution * grid will result in larger continuous areas of a land style, a higher * resolution grid splits the style into smaller areas. * @param level Rough indication of the size of the grid sections to style. Small level means large grid sections. */ static void HeightMapCurves(uint level) { Height mh = TGPGetMaxHeight() - I2H(1); // height levels above sea level only /** Basically scale height X to height Y. Everything in between is interpolated. */ struct ControlPoint { Height x; ///< The height to scale from. Height y; ///< The height to scale to. }; /* Scaled curve maps; value is in height_ts. */ #define F(fraction) ((Height)(fraction * mh)) const ControlPoint curve_map_1[] = { { F(0.0), F(0.0) }, { F(0.8), F(0.13) }, { F(1.0), F(0.4) } }; const ControlPoint curve_map_2[] = { { F(0.0), F(0.0) }, { F(0.53), F(0.13) }, { F(0.8), F(0.27) }, { F(1.0), F(0.6) } }; const ControlPoint curve_map_3[] = { { F(0.0), F(0.0) }, { F(0.53), F(0.27) }, { F(0.8), F(0.57) }, { F(1.0), F(0.8) } }; const ControlPoint curve_map_4[] = { { F(0.0), F(0.0) }, { F(0.4), F(0.3) }, { F(0.7), F(0.8) }, { F(0.92), F(0.99) }, { F(1.0), F(0.99) } }; #undef F static const std::span curve_maps[] = { curve_map_1, curve_map_2, curve_map_3, curve_map_4 }; std::array ht{}; /* Set up a grid to choose curve maps based on location; attempt to get a somewhat square grid */ float factor = sqrt((float)_height_map.size_x / (float)_height_map.size_y); uint sx = Clamp((int)(((1 << level) * factor) + 0.5), 1, 128); uint sy = Clamp((int)(((1 << level) / factor) + 0.5), 1, 128); std::vector c(static_cast(sx) * sy); for (uint i = 0; i < sx * sy; i++) { c[i] = RandomRange(static_cast(std::size(curve_maps))); } /* Apply curves */ for (int x = 0; x < _height_map.size_x; x++) { /* Get our X grid positions and bi-linear ratio */ float fx = (float)(sx * x) / _height_map.size_x + 1.0f; uint x1 = (uint)fx; uint x2 = x1; float xr = 2.0f * (fx - x1) - 1.0f; xr = sin(xr * M_PI_2); xr = sin(xr * M_PI_2); xr = 0.5f * (xr + 1.0f); float xri = 1.0f - xr; if (x1 > 0) { x1--; if (x2 >= sx) x2--; } for (int y = 0; y < _height_map.size_y; y++) { /* Get our Y grid position and bi-linear ratio */ float fy = (float)(sy * y) / _height_map.size_y + 1.0f; uint y1 = (uint)fy; uint y2 = y1; float yr = 2.0f * (fy - y1) - 1.0f; yr = sin(yr * M_PI_2); yr = sin(yr * M_PI_2); yr = 0.5f * (yr + 1.0f); float yri = 1.0f - yr; if (y1 > 0) { y1--; if (y2 >= sy) y2--; } uint corner_a = c[x1 + sx * y1]; uint corner_b = c[x1 + sx * y2]; uint corner_c = c[x2 + sx * y1]; uint corner_d = c[x2 + sx * y2]; /* Bitmask of which curve maps are chosen, so that we do not bother * calculating a curve which won't be used. */ uint corner_bits = 0; corner_bits |= 1 << corner_a; corner_bits |= 1 << corner_b; corner_bits |= 1 << corner_c; corner_bits |= 1 << corner_d; Height *h = &_height_map.height(x, y); /* Do not touch sea level */ if (*h < I2H(1)) continue; /* Only scale above sea level */ *h -= I2H(1); /* Apply all curve maps that are used on this tile. */ for (size_t t = 0; t < std::size(curve_maps); t++) { if (!HasBit(corner_bits, static_cast(t))) continue; [[maybe_unused]] bool found = false; auto &cm = curve_maps[t]; for (size_t i = 0; i < cm.size() - 1; i++) { const ControlPoint &p1 = cm[i]; const ControlPoint &p2 = cm[i + 1]; if (*h >= p1.x && *h < p2.x) { ht[t] = p1.y + (*h - p1.x) * (p2.y - p1.y) / (p2.x - p1.x); #ifdef WITH_ASSERT found = true; #endif break; } } assert(found); } /* Apply interpolation of curve map results. */ *h = (Height)((ht[corner_a] * yri + ht[corner_b] * yr) * xri + (ht[corner_c] * yri + ht[corner_d] * yr) * xr); /* Readd sea level */ *h += I2H(1); } } } /** Adjusts heights in height map to contain required amount of water tiles */ static void HeightMapAdjustWaterLevel(Amplitude water_percent, Height h_max_new) { Height h_min, h_max, h_avg, h_water_level; int64_t water_tiles, desired_water_tiles; int *hist; HeightMapGetMinMaxAvg(&h_min, &h_max, &h_avg); /* Allocate histogram buffer and clear its cells */ int *hist_buf = CallocT(h_max - h_min + 1); /* Fill histogram */ hist = HeightMapMakeHistogram(h_min, h_max, hist_buf); /* How many water tiles do we want? */ desired_water_tiles = A2I(((int64_t)water_percent) * (int64_t)(_height_map.size_x * _height_map.size_y)); /* Raise water_level and accumulate values from histogram until we reach required number of water tiles */ for (h_water_level = h_min, water_tiles = 0; h_water_level < h_max; h_water_level++) { water_tiles += hist[h_water_level]; if (water_tiles >= desired_water_tiles) break; } /* We now have the proper water level value. * Transform the height map into new (normalized) height map: * values from range: h_min..h_water_level will become negative so it will be clamped to 0 * values from range: h_water_level..h_max are transformed into 0..h_max_new * where h_max_new is depending on terrain type and map size. */ for (Height &h : _height_map.h) { /* Transform height from range h_water_level..h_max into 0..h_max_new range */ h = (Height)(((int)h_max_new) * (h - h_water_level) / (h_max - h_water_level)) + I2H(1); /* Make sure all values are in the proper range (0..h_max_new) */ if (h < 0) h = I2H(0); if (h >= h_max_new) h = h_max_new - 1; } free(hist_buf); } static double perlin_coast_noise_2D(const double x, const double y, const double p, const int prime); /** * This routine sculpts in from the edge a random amount, again a Perlin * sequence, to avoid the rigid flat-edge slopes that were present before. The * Perlin noise map doesn't know where we are going to slice across, and so we * often cut straight through high terrain. The smoothing routine makes it * legal, gradually increasing up from the edge to the original terrain height. * By cutting parts of this away, it gives a far more irregular edge to the * map-edge. Sometimes it works beautifully with the existing sea & lakes, and * creates a very realistic coastline. Other times the variation is less, and * the map-edge shows its cliff-like roots. * * This routine may be extended to randomly sculpt the height of the terrain * near the edge. This will have the coast edge at low level (1-3), rising in * smoothed steps inland to about 15 tiles in. This should make it look as * though the map has been built for the map size, rather than a slice through * a larger map. * * Please note that all the small numbers; 53, 101, 167, etc. are small primes * to help give the perlin noise a bit more of a random feel. */ static void HeightMapCoastLines(uint8_t water_borders) { int smallest_size = std::min(_settings_game.game_creation.map_x, _settings_game.game_creation.map_y); const int margin = 4; int y, x; double max_x; double max_y; /* Lower to sea level */ for (y = 0; y <= _height_map.size_y; y++) { if (HasBit(water_borders, BORDER_NE)) { /* Top right */ max_x = abs((perlin_coast_noise_2D(_height_map.size_y - y, y, 0.9, 53) + 0.25) * 5 + (perlin_coast_noise_2D(y, y, 0.35, 179) + 1) * 12); max_x = std::max((smallest_size * smallest_size / 64) + max_x, (smallest_size * smallest_size / 64) + margin - max_x); if (smallest_size < 8 && max_x > 5) max_x /= 1.5; for (x = 0; x < max_x; x++) { _height_map.height(x, y) = 0; } } if (HasBit(water_borders, BORDER_SW)) { /* Bottom left */ max_x = abs((perlin_coast_noise_2D(_height_map.size_y - y, y, 0.85, 101) + 0.3) * 6 + (perlin_coast_noise_2D(y, y, 0.45, 67) + 0.75) * 8); max_x = std::max((smallest_size * smallest_size / 64) + max_x, (smallest_size * smallest_size / 64) + margin - max_x); if (smallest_size < 8 && max_x > 5) max_x /= 1.5; for (x = _height_map.size_x; x > (_height_map.size_x - 1 - max_x); x--) { _height_map.height(x, y) = 0; } } } /* Lower to sea level */ for (x = 0; x <= _height_map.size_x; x++) { if (HasBit(water_borders, BORDER_NW)) { /* Top left */ max_y = abs((perlin_coast_noise_2D(x, _height_map.size_y / 2, 0.9, 167) + 0.4) * 5 + (perlin_coast_noise_2D(x, _height_map.size_y / 3, 0.4, 211) + 0.7) * 9); max_y = std::max((smallest_size * smallest_size / 64) + max_y, (smallest_size * smallest_size / 64) + margin - max_y); if (smallest_size < 8 && max_y > 5) max_y /= 1.5; for (y = 0; y < max_y; y++) { _height_map.height(x, y) = 0; } } if (HasBit(water_borders, BORDER_SE)) { /* Bottom right */ max_y = abs((perlin_coast_noise_2D(x, _height_map.size_y / 3, 0.85, 71) + 0.25) * 6 + (perlin_coast_noise_2D(x, _height_map.size_y / 3, 0.35, 193) + 0.75) * 12); max_y = std::max((smallest_size * smallest_size / 64) + max_y, (smallest_size * smallest_size / 64) + margin - max_y); if (smallest_size < 8 && max_y > 5) max_y /= 1.5; for (y = _height_map.size_y; y > (_height_map.size_y - 1 - max_y); y--) { _height_map.height(x, y) = 0; } } } } /** Start at given point, move in given direction, find and Smooth coast in that direction */ static void HeightMapSmoothCoastInDirection(int org_x, int org_y, int dir_x, int dir_y) { const int max_coast_dist_from_edge = 35; const int max_coast_Smooth_depth = 35; int x, y; int ed; // coast distance from edge int depth; Height h_prev = I2H(1); Height h; assert(IsValidXY(org_x, org_y)); /* Search for the coast (first non-water tile) */ for (x = org_x, y = org_y, ed = 0; IsValidXY(x, y) && ed < max_coast_dist_from_edge; x += dir_x, y += dir_y, ed++) { /* Coast found? */ if (_height_map.height(x, y) >= I2H(1)) break; /* Coast found in the neighborhood? */ if (IsValidXY(x + dir_y, y + dir_x) && _height_map.height(x + dir_y, y + dir_x) > 0) break; /* Coast found in the neighborhood on the other side */ if (IsValidXY(x - dir_y, y - dir_x) && _height_map.height(x - dir_y, y - dir_x) > 0) break; } /* Coast found or max_coast_dist_from_edge has been reached. * Soften the coast slope */ for (depth = 0; IsValidXY(x, y) && depth <= max_coast_Smooth_depth; depth++, x += dir_x, y += dir_y) { h = _height_map.height(x, y); h = static_cast(std::min(h, h_prev + (4 + depth))); // coast softening formula _height_map.height(x, y) = h; h_prev = h; } } /** Smooth coasts by modulating height of tiles close to map edges with cosine of distance from edge */ static void HeightMapSmoothCoasts(uint8_t water_borders) { int x, y; /* First Smooth NW and SE coasts (y close to 0 and y close to size_y) */ for (x = 0; x < _height_map.size_x; x++) { if (HasBit(water_borders, BORDER_NW)) HeightMapSmoothCoastInDirection(x, 0, 0, 1); if (HasBit(water_borders, BORDER_SE)) HeightMapSmoothCoastInDirection(x, _height_map.size_y - 1, 0, -1); } /* First Smooth NE and SW coasts (x close to 0 and x close to size_x) */ for (y = 0; y < _height_map.size_y; y++) { if (HasBit(water_borders, BORDER_NE)) HeightMapSmoothCoastInDirection(0, y, 1, 0); if (HasBit(water_borders, BORDER_SW)) HeightMapSmoothCoastInDirection(_height_map.size_x - 1, y, -1, 0); } } /** * This routine provides the essential cleanup necessary before OTTD can * display the terrain. When generated, the terrain heights can jump more than * one level between tiles. This routine smooths out those differences so that * the most it can change is one level. When OTTD can support cliffs, this * routine may not be necessary. */ static void HeightMapSmoothSlopes(Height dh_max) { for (int y = 0; y <= (int)_height_map.size_y; y++) { for (int x = 0; x <= (int)_height_map.size_x; x++) { Height h_max = std::min(_height_map.height(x > 0 ? x - 1 : x, y), _height_map.height(x, y > 0 ? y - 1 : y)) + dh_max; if (_height_map.height(x, y) > h_max) _height_map.height(x, y) = h_max; } } for (int y = _height_map.size_y; y >= 0; y--) { for (int x = _height_map.size_x; x >= 0; x--) { Height h_max = std::min(_height_map.height(x < _height_map.size_x ? x + 1 : x, y), _height_map.height(x, y < _height_map.size_y ? y + 1 : y)) + dh_max; if (_height_map.height(x, y) > h_max) _height_map.height(x, y) = h_max; } } } /** * Height map terraform post processing: * - water level adjusting * - coast Smoothing * - slope Smoothing * - height histogram redistribution by sine wave transform */ static void HeightMapNormalize() { int sea_level_setting = _settings_game.difficulty.quantity_sea_lakes; const Amplitude water_percent = sea_level_setting != (int)CUSTOM_SEA_LEVEL_NUMBER_DIFFICULTY ? _water_percent[sea_level_setting] : _settings_game.game_creation.custom_sea_level * 1024 / 100; const Height h_max_new = TGPGetMaxHeight(); const Height roughness = 7 + 3 * _settings_game.game_creation.tgen_smoothness; HeightMapAdjustWaterLevel(water_percent, h_max_new); uint8_t water_borders = _settings_game.construction.freeform_edges ? _settings_game.game_creation.water_borders : 0xF; if (water_borders == BORDERS_RANDOM) water_borders = GB(Random(), 0, 4); HeightMapCoastLines(water_borders); HeightMapSmoothSlopes(roughness); HeightMapSmoothCoasts(water_borders); HeightMapSmoothSlopes(roughness); HeightMapSineTransform(I2H(1), h_max_new); if (_settings_game.game_creation.variety > 0) { HeightMapCurves(_settings_game.game_creation.variety); } HeightMapSmoothSlopes(I2H(1)); } /** * The Perlin Noise calculation using large primes * The initial number is adjusted by two values; the generation_seed, and the * passed parameter; prime. * prime is used to allow the perlin noise generator to create useful random * numbers from slightly different series. */ static double int_noise(const long x, const long y, const int prime) { long n = x + y * prime + _settings_game.game_creation.generation_seed; n = (n << 13) ^ n; /* Pseudo-random number generator, using several large primes */ return 1.0 - (double)((n * (n * n * 15731 + 789221) + 1376312589) & 0x7fffffff) / 1073741824.0; } /** * This routine determines the interpolated value between a and b */ static inline double linear_interpolate(const double a, const double b, const double x) { return a + x * (b - a); } /** * This routine returns the smoothed interpolated noise for an x and y, using * the values from the surrounding positions. */ static double interpolated_noise(const double x, const double y, const int prime) { const int integer_X = (int)x; const int integer_Y = (int)y; const double fractional_X = x - (double)integer_X; const double fractional_Y = y - (double)integer_Y; const double v1 = int_noise(integer_X, integer_Y, prime); const double v2 = int_noise(integer_X + 1, integer_Y, prime); const double v3 = int_noise(integer_X, integer_Y + 1, prime); const double v4 = int_noise(integer_X + 1, integer_Y + 1, prime); const double i1 = linear_interpolate(v1, v2, fractional_X); const double i2 = linear_interpolate(v3, v4, fractional_X); return linear_interpolate(i1, i2, fractional_Y); } /** * This is a similar function to the main perlin noise calculation, but uses * the value p passed as a parameter rather than selected from the predefined * sequences. as you can guess by its title, i use this to create the indented * coastline, which is just another perlin sequence. */ static double perlin_coast_noise_2D(const double x, const double y, const double p, const int prime) { double total = 0.0; for (int i = 0; i < 6; i++) { const double frequency = (double)(1 << i); const double amplitude = pow(p, (double)i); total += interpolated_noise((x * frequency) / 64.0, (y * frequency) / 64.0, prime) * amplitude; } return total; } /** A small helper function to initialize the terrain */ static void TgenSetTileHeight(TileIndex tile, int height) { SetTileHeight(tile, height); /* Only clear the tiles within the map area. */ if (IsInnerTile(tile)) { MakeClear(tile, CLEAR_GRASS, 3); } } /** * The main new land generator using Perlin noise. Desert landscape is handled * different to all others to give a desert valley between two high mountains. * Clearly if a low height terrain (flat/very flat) is chosen, then the tropic * areas won't be high enough, and there will be very little tropic on the map. * Thus Tropic works best on Hilly or Mountainous. */ void GenerateTerrainPerlin() { if (!AllocHeightMap()) return; GenerateWorldSetAbortCallback(FreeHeightMap); HeightMapGenerate(); IncreaseGeneratingWorldProgress(GWP_LANDSCAPE); HeightMapNormalize(); IncreaseGeneratingWorldProgress(GWP_LANDSCAPE); /* First make sure the tiles at the north border are void tiles if needed. */ if (_settings_game.construction.freeform_edges) { for (uint x = 0; x < Map::SizeX(); x++) MakeVoid(TileXY(x, 0)); for (uint y = 0; y < Map::SizeY(); y++) MakeVoid(TileXY(0, y)); } int max_height = H2I(TGPGetMaxHeight()); /* Transfer height map into OTTD map */ for (int y = 0; y < _height_map.size_y; y++) { for (int x = 0; x < _height_map.size_x; x++) { TgenSetTileHeight(TileXY(x, y), Clamp(H2I(_height_map.height(x, y)), 0, max_height)); } } IncreaseGeneratingWorldProgress(GWP_LANDSCAPE); FreeHeightMap(); GenerateWorldSetAbortCallback(nullptr); }