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fast_noise_lite.f90
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fast_noise_lite.f90
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module fast_noise_lite
use :: iso_c_binding
implicit none
private
! MIT License
!
! Copyright(c) 2023 Jordan Peck (jordan.me2@gmail.com)
! Copyright(c) 2023 Contributors
! Translated by jordan4ibanez: 2024
!
! 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 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.
!
! .'',;:cldxkO00KKXXNNWWWNNXKOkxdollcc::::::;:::ccllloooolllllllllooollc:,'... ...........',;cldxkO000Okxdlc::;;;,,;;;::cclllllll
! ..',;:ldxO0KXXNNNNNNNNXXK0kxdolcc::::::;;;,,,,,,;;;;;;;;;;:::cclllllc:;'.... ...........',;:ldxO0KXXXK0Okxdolc::;;;;::cllodddddo
! ...',:loxO0KXNNNNNXXKK0Okxdolc::;::::::::;;;,,'''''.....''',;:clllllc:;,'............''''''''',;:loxO0KXNNNNNXK0Okxdollccccllodxxxxxxd
! ....';:ldkO0KXXXKK00Okxdolcc:;;;;;::cclllcc:;;,''..... ....',;clooddolcc:;;;;,,;;;;;::::;;;;;;:cloxk0KXNWWWWWWNXKK0Okxddoooddxxkkkkkxx
! .....';:ldxkOOOOOkxxdolcc:;;;,,,;;:cllooooolcc:;'... ..,:codxkkkxddooollloooooooollcc:::::clodkO0KXNWWWWWWNNXK00Okxxxxxxxxkkkkxxx
! . ....';:cloddddo___________,,,,;;:clooddddoolc:,... ..,:ldx__00OOOkkk___kkkkkkxxdollc::::cclodkO0KXXNNNNNNXXK0OOkxxxxxxxxxxxxddd
! .......',;:cccc:| |,,,;;:cclooddddoll:;'.. ..';cox| \KKK000| |KK00OOkxdocc___;::clldxxkO0KKKKK00Okkxdddddddddddddddoo
! .......'',,,,,''| ________|',,;;::cclloooooolc:;'......___:ldk| \KK000| |XKKK0Okxolc| |;;::cclodxxkkkkxxdoolllcclllooodddooooo
! ''......''''....| | ....'',,,,;;;::cclloooollc:;,''.'| |oxk| \OOO0| |KKK00Oxdoll|___|;;;;;::ccllllllcc::;;,,;;;:cclloooooooo
! ;;,''.......... | |_____',,;;;____:___cllo________.___| |___| \xkk| |KK_______ool___:::;________;;;_______...'',;;:ccclllloo
! c:;,''......... | |:::/ ' |lo/ | | \dx| |0/ \d| |cc/ |'/ \......',,;;:ccllo
! ol:;,'..........| _____|ll/ __ |o/ ______|____ ___| | \o| |/ ___ \| |o/ ______|/ ___ \ .......'',;:clo
! dlc;,...........| |::clooo| / | |x\___ \KXKKK0| |dol| |\ \| | | | | |d\___ \..| | / / ....',:cl
! xoc;'... .....'| |llodddd| \__| |_____\ \KKK0O| |lc:| |'\ | |___| | |_____\ \.| |_/___/... ...',;:c
! dlc;'... ....',;| |oddddddo\ | |Okkx| |::;| |..\ |\ /| | | \ |... ....',;:c
! ol:,'.......',:c|___|xxxddollc\_____,___|_________/ddoll|___|,,,|___|...\_____|:\ ______/l|___|_________/...\________|'........',;::cc
! c:;'.......';:codxxkkkkxxolc::;::clodxkOO0OOkkxdollc::;;,,''''',,,,''''''''''',,'''''',;:loxkkOOkxol:;,'''',,;:ccllcc:;,'''''',;::ccll
! ;,'.......',:codxkOO0OOkxdlc:;,,;;:cldxxkkxxdolc:;;,,''.....'',;;:::;;,,,'''''........,;cldkO0KK0Okdoc::;;::cloodddoolc:;;;;;::ccllooo
! .........',;:lodxOO0000Okdoc:,,',,;:clloddoolc:;,''.......'',;:clooollc:;;,,''.......',:ldkOKXNNXX0Oxdolllloddxxxxxxdolccccccllooodddd
! . .....';:cldxkO0000Okxol:;,''',,;::cccc:;,,'.......'',;:cldxxkkxxdolc:;;,'.......';coxOKXNWWWNXKOkxddddxxkkkkkkxdoollllooddxxxxkkk
! ....',;:codxkO000OOxdoc:;,''',,,;;;;,''.......',,;:clodkO00000Okxolc::;,,''..',;:ldxOKXNWWWNNK0OkkkkkkkkkkkxxddooooodxxkOOOOO000
! ....',;;clodxkkOOOkkdolc:;,,,,,,,,'..........,;:clodxkO0KKXKK0Okxdolcc::;;,,,;;:codkO0XXNNNNXKK0OOOOOkkkkxxdoollloodxkO0KKKXXXXX
!
! VERSION: 1.1.1
! https://github.com/Auburn/FastNoiseLite
! Allow switching from f64 to f32 by changing kind with comment swap.
! real(c_double), parameter :: data_sample = 0.0d0
real(c_float), parameter :: data_sample = 0.0
integer, parameter :: fnl_float = kind(c_double)
real(fnl_float) :: f__
real(c_float), public, parameter :: FLT_MAX = huge(f__)
! Enums
integer(c_int), parameter :: fnl_noise_type = 0
integer(c_int), parameter, public :: FNL_NOISE_OPENSIMPLEX2 = 1
integer(c_int), parameter, public :: FNL_NOISE_OPENSIMPLEX2S = 2
integer(c_int), parameter, public :: FNL_NOISE_CELLULAR = 3
integer(c_int), parameter, public :: FNL_NOISE_PERLIN = 4
integer(c_int), parameter, public :: FNL_NOISE_VALUE_CUBIC = 5
integer(c_int), parameter, public :: FNL_NOISE_VALUE = 6
integer(c_int), parameter :: fnl_rotation_type_3d = 7
integer(c_int), parameter, public :: FNL_ROTATION_NONE = 8
integer(c_int), parameter, public :: FNL_ROTATION_IMPROVE_XY_PLANES = 9
integer(c_int), parameter, public :: FNL_ROTATION_IMPROVE_XZ_PLANES = 10
integer(c_int), parameter :: fnl_fractal_type = 11
integer(c_int), parameter, public :: FNL_FRACTAL_NONE = 12
integer(c_int), parameter, public :: FNL_FRACTAL_FBM = 13
integer(c_int), parameter, public :: FNL_FRACTAL_RIDGED = 14
integer(c_int), parameter, public :: FNL_FRACTAL_PINGPONG = 15
integer(c_int), parameter, public :: FNL_FRACTAL_DOMAIN_WARP_PROGRESSIVE = 16
integer(c_int), parameter, public :: FNL_FRACTAL_DOMAIN_WARP_INDEPENDENT = 17
integer(c_int), parameter :: fnl_cellular_distance_func = 18
integer(c_int), parameter, public :: FNL_CELLULAR_DISTANCE_EUCLIDEAN = 19
integer(c_int), parameter, public :: FNL_CELLULAR_DISTANCE_EUCLIDEANSQ = 20
integer(c_int), parameter, public :: FNL_CELLULAR_DISTANCE_MANHATTAN = 21
integer(c_int), parameter, public :: FNL_CELLULAR_DISTANCE_HYBRID = 22
integer(c_int), parameter :: fnl_cellular_return_type = 23
integer(c_int), parameter, public :: FNL_CELLULAR_RETURN_TYPE_CELLVALUE = 24
integer(c_int), parameter, public :: FNL_CELLULAR_RETURN_TYPE_DISTANCE = 25
integer(c_int), parameter, public :: FNL_CELLULAR_RETURN_TYPE_DISTANCE2 = 26
integer(c_int), parameter, public :: FNL_CELLULAR_RETURN_TYPE_DISTANCE2ADD = 27
integer(c_int), parameter, public :: FNL_CELLULAR_RETURN_TYPE_DISTANCE2SUB = 28
integer(c_int), parameter, public :: FNL_CELLULAR_RETURN_TYPE_DISTANCE2MUL = 29
integer(c_int), parameter, public :: FNL_CELLULAR_RETURN_TYPE_DISTANCE2DIV = 30
integer(c_int), parameter :: fnl_domain_warp_type = 31
integer(c_int), parameter, public :: FNL_DOMAIN_WARP_OPENSIMPLEX2 = 32
integer(c_int), parameter, public :: FNL_DOMAIN_WARP_OPENSIMPLEX2_REDUCED = 33
integer(c_int), parameter, public :: FNL_DOMAIN_WARP_BASICGRID = 34
!*
!* Structure containing entire noise system state.
!* @note Must only be created using fnlCreateState(optional: seed). To ensure defaults are set.
!*
type, public :: fnl_state
!
! Seed used for all noise types.
! @remark Default: 1337
!
integer(c_int) :: seed = 1337
!
! The frequency for all noise types.
! @remark Default: 0.01
!
real(c_float) :: frequency = 0.01
!
! The noise algorithm to be used by GetNoise(...).
! @remark Default: FNL_NOISE_OPENSIMPLEX2
!
integer(kind(fnl_noise_type)) :: noise_type = FNL_NOISE_OPENSIMPLEX2
!
! Sets noise rotation type for 3D.
! @remark Default: FNL_ROTATION_NONE
!
integer(kind(fnl_rotation_type_3d)) :: rotation_type_3d = FNL_NOISE_OPENSIMPLEX2
!
! The method used for combining octaves for all fractal noise types.
! @remark Default: FNL_FRACTAL_NONE
! @remark FNL_FRACTAL_DOMAIN_WARP_... only effects fnlDomainWarp...
!
integer(kind(fnl_fractal_type)) :: fractal_type = FNL_FRACTAL_NONE
!
! The octave count for all fractal noise types.
! @remark Default: 3
!
integer(c_int) :: octaves = 3
!
! The octave lacunarity for all fractal noise types.
! @remark Default: 2.0
!
real(c_float) :: lacunarity = 2.0
!
! The octave gain for all fractal noise types.
! @remark Default: 0.5
!
real(c_float) :: gain = 0.5
!
! The octave weighting for all none Domaain Warp fractal types.
! @remark Default: 0.0
! @remark
!
real(c_float) :: weighted_strength = 0.0
!
! The strength of the fractal ping pong effect.
! @remark Default: 2.0
!
real(c_float) :: ping_pong_strength = 2.0
!
! The distance function used in cellular noise calculations.
! @remark Default: FNL_CELLULAR_DISTANCE_EUCLIDEANSQ
!
integer(kind(fnl_cellular_distance_func)) :: cellular_distance_func = FNL_CELLULAR_DISTANCE_EUCLIDEANSQ
!
! The cellular return type from cellular noise calculations.
! @remark Default: FNL_CELLULAR_RETURN_TYPE_DISTANCE
!
integer(kind(fnl_cellular_return_type)) :: cellular_return_type = FNL_CELLULAR_RETURN_TYPE_DISTANCE
!
! The maximum distance a cellular point can move from it's grid position.
! @remark Default: 1.0
! @note Setting this higher than 1 will cause artifacts.
!
real(c_float) :: cellular_jitter_mod = 1.0
!
! The warp algorithm when using fnlDomainWarp...
! @remark Default: OpenSimplex2
!
integer(kind(fnl_domain_warp_type)) :: domain_warp_type = FNL_DOMAIN_WARP_OPENSIMPLEX2_REDUCED
!
! The maximum warp distance from original position when using fnlDomainWarp...
! @remark Default: 1.0
!
real(c_float) :: domain_warp_amp = 1.0
end type fnl_state
interface fnl_state
module procedure :: constructor_fnl_state
end interface fnl_state
! Expose public api.
public :: fnl_get_noise_2d
public :: fnl_get_noise_3d
public :: fnl_domain_warp_2d
public :: fnl_domain_warp_3d
! =====================================
! Below this line is the implementation
! =====================================
! Constants
real(c_float), dimension(256), parameter :: GRADIENTS_2D = (/ &
0.130526192220052, 0.99144486137381, 0.38268343236509, 0.923879532511287, 0.608761429008721, 0.793353340291235, 0.793353340291235, 0.608761429008721, &
0.923879532511287, 0.38268343236509, 0.99144486137381, 0.130526192220051, 0.99144486137381, -0.130526192220051, 0.923879532511287, -0.38268343236509, &
0.793353340291235, -0.60876142900872, 0.608761429008721, -0.793353340291235, 0.38268343236509, -0.923879532511287, 0.130526192220052, -0.99144486137381, &
-0.130526192220052, -0.99144486137381, -0.38268343236509, -0.923879532511287, -0.608761429008721, -0.793353340291235, -0.793353340291235, -0.608761429008721, &
-0.923879532511287, -0.38268343236509, -0.99144486137381, -0.130526192220052, -0.99144486137381, 0.130526192220051, -0.923879532511287, 0.38268343236509, &
-0.793353340291235, 0.608761429008721, -0.608761429008721, 0.793353340291235, -0.38268343236509, 0.923879532511287, -0.130526192220052, 0.99144486137381, &
0.130526192220052, 0.99144486137381, 0.38268343236509, 0.923879532511287, 0.608761429008721, 0.793353340291235, 0.793353340291235, 0.608761429008721, &
0.923879532511287, 0.38268343236509, 0.99144486137381, 0.130526192220051, 0.99144486137381, -0.130526192220051, 0.923879532511287, -0.38268343236509, &
0.793353340291235, -0.60876142900872, 0.608761429008721, -0.793353340291235, 0.38268343236509, -0.923879532511287, 0.130526192220052, -0.99144486137381, &
-0.130526192220052, -0.99144486137381, -0.38268343236509, -0.923879532511287, -0.608761429008721, -0.793353340291235, -0.793353340291235, -0.608761429008721, &
-0.923879532511287, -0.38268343236509, -0.99144486137381, -0.130526192220052, -0.99144486137381, 0.130526192220051, -0.923879532511287, 0.38268343236509, &
-0.793353340291235, 0.608761429008721, -0.608761429008721, 0.793353340291235, -0.38268343236509, 0.923879532511287, -0.130526192220052, 0.99144486137381, &
0.130526192220052, 0.99144486137381, 0.38268343236509, 0.923879532511287, 0.608761429008721, 0.793353340291235, 0.793353340291235, 0.608761429008721, &
0.923879532511287, 0.38268343236509, 0.99144486137381, 0.130526192220051, 0.99144486137381, -0.130526192220051, 0.923879532511287, -0.38268343236509, &
0.793353340291235, -0.60876142900872, 0.608761429008721, -0.793353340291235, 0.38268343236509, -0.923879532511287, 0.130526192220052, -0.99144486137381, &
-0.130526192220052, -0.99144486137381, -0.38268343236509, -0.923879532511287, -0.608761429008721, -0.793353340291235, -0.793353340291235, -0.608761429008721, &
-0.923879532511287, -0.38268343236509, -0.99144486137381, -0.130526192220052, -0.99144486137381, 0.130526192220051, -0.923879532511287, 0.38268343236509, &
-0.793353340291235, 0.608761429008721, -0.608761429008721, 0.793353340291235, -0.38268343236509, 0.923879532511287, -0.130526192220052, 0.99144486137381, &
0.130526192220052, 0.99144486137381, 0.38268343236509, 0.923879532511287, 0.608761429008721, 0.793353340291235, 0.793353340291235, 0.608761429008721, &
0.923879532511287, 0.38268343236509, 0.99144486137381, 0.130526192220051, 0.99144486137381, -0.130526192220051, 0.923879532511287, -0.38268343236509, &
0.793353340291235, -0.60876142900872, 0.608761429008721, -0.793353340291235, 0.38268343236509, -0.923879532511287, 0.130526192220052, -0.99144486137381, &
-0.130526192220052, -0.99144486137381, -0.38268343236509, -0.923879532511287, -0.608761429008721, -0.793353340291235, -0.793353340291235, -0.608761429008721, &
-0.923879532511287, -0.38268343236509, -0.99144486137381, -0.130526192220052, -0.99144486137381, 0.130526192220051, -0.923879532511287, 0.38268343236509, &
-0.793353340291235, 0.608761429008721, -0.608761429008721, 0.793353340291235, -0.38268343236509, 0.923879532511287, -0.130526192220052, 0.99144486137381, &
0.130526192220052, 0.99144486137381, 0.38268343236509, 0.923879532511287, 0.608761429008721, 0.793353340291235, 0.793353340291235, 0.608761429008721, &
0.923879532511287, 0.38268343236509, 0.99144486137381, 0.130526192220051, 0.99144486137381, -0.130526192220051, 0.923879532511287, -0.38268343236509, &
0.793353340291235, -0.60876142900872, 0.608761429008721, -0.793353340291235, 0.38268343236509, -0.923879532511287, 0.130526192220052, -0.99144486137381, &
-0.130526192220052, -0.99144486137381, -0.38268343236509, -0.923879532511287, -0.608761429008721, -0.793353340291235, -0.793353340291235, -0.608761429008721, &
-0.923879532511287, -0.38268343236509, -0.99144486137381, -0.130526192220052, -0.99144486137381, 0.130526192220051, -0.923879532511287, 0.38268343236509, &
-0.793353340291235, 0.608761429008721, -0.608761429008721, 0.793353340291235, -0.38268343236509, 0.923879532511287, -0.130526192220052, 0.99144486137381, &
0.38268343236509, 0.923879532511287, 0.923879532511287, 0.38268343236509, 0.923879532511287, -0.38268343236509, 0.38268343236509, -0.923879532511287, &
-0.38268343236509, -0.923879532511287, -0.923879532511287, -0.38268343236509, -0.923879532511287, 0.38268343236509, -0.38268343236509, 0.923879532511287 &
/)
real(c_float), dimension(512), parameter :: RAND_VECS_2D = (/ &
-0.2700222198, -0.9628540911, 0.3863092627, -0.9223693152, 0.04444859006, -0.999011673, -0.5992523158, -0.8005602176, -0.7819280288, 0.6233687174, 0.9464672271, 0.3227999196, -0.6514146797, -0.7587218957, 0.9378472289, 0.347048376, &
-0.8497875957, -0.5271252623, -0.879042592, 0.4767432447, -0.892300288, -0.4514423508, -0.379844434, -0.9250503802, -0.9951650832, 0.0982163789, 0.7724397808, -0.6350880136, 0.7573283322, -0.6530343002, -0.9928004525, -0.119780055, &
-0.0532665713, 0.9985803285, 0.9754253726, -0.2203300762, -0.7665018163, 0.6422421394, 0.991636706, 0.1290606184, -0.994696838, 0.1028503788, -0.5379205513, -0.84299554, 0.5022815471, -0.8647041387, 0.4559821461, -0.8899889226, &
-0.8659131224, -0.5001944266, 0.0879458407, -0.9961252577, -0.5051684983, 0.8630207346, 0.7753185226, -0.6315704146, -0.6921944612, 0.7217110418, -0.5191659449, -0.8546734591, 0.8978622882, -0.4402764035, -0.1706774107, 0.9853269617, &
-0.9353430106, -0.3537420705, -0.9992404798, 0.03896746794, -0.2882064021, -0.9575683108, -0.9663811329, 0.2571137995, -0.8759714238, -0.4823630009, -0.8303123018, -0.5572983775, 0.05110133755, -0.9986934731, -0.8558373281, -0.5172450752, &
0.09887025282, 0.9951003332, 0.9189016087, 0.3944867976, -0.2439375892, -0.9697909324, -0.8121409387, -0.5834613061, -0.9910431363, 0.1335421355, 0.8492423985, -0.5280031709, -0.9717838994, -0.2358729591, 0.9949457207, 0.1004142068, &
0.6241065508, -0.7813392434, 0.662910307, 0.7486988212, -0.7197418176, 0.6942418282, -0.8143370775, -0.5803922158, 0.104521054, -0.9945226741, -0.1065926113, -0.9943027784, 0.445799684, -0.8951327509, 0.105547406, 0.9944142724, &
-0.992790267, 0.1198644477, -0.8334366408, 0.552615025, 0.9115561563, -0.4111755999, 0.8285544909, -0.5599084351, 0.7217097654, -0.6921957921, 0.4940492677, -0.8694339084, -0.3652321272, -0.9309164803, -0.9696606758, 0.2444548501, &
0.08925509731, -0.996008799, 0.5354071276, -0.8445941083, -0.1053576186, 0.9944343981, -0.9890284586, 0.1477251101, 0.004856104961, 0.9999882091, 0.9885598478, 0.1508291331, 0.9286129562, -0.3710498316, -0.5832393863, -0.8123003252, &
0.3015207509, 0.9534596146, -0.9575110528, 0.2883965738, 0.9715802154, -0.2367105511, 0.229981792, 0.9731949318, 0.955763816, -0.2941352207, 0.740956116, 0.6715534485, -0.9971513787, -0.07542630764, 0.6905710663, -0.7232645452, &
-0.290713703, -0.9568100872, 0.5912777791, -0.8064679708, -0.9454592212, -0.325740481, 0.6664455681, 0.74555369, 0.6236134912, 0.7817328275, 0.9126993851, -0.4086316587, -0.8191762011, 0.5735419353, -0.8812745759, -0.4726046147, &
0.9953313627, 0.09651672651, 0.9855650846, -0.1692969699, -0.8495980887, 0.5274306472, 0.6174853946, -0.7865823463, 0.8508156371, 0.52546432, 0.9985032451, -0.05469249926, 0.1971371563, -0.9803759185, 0.6607855748, -0.7505747292, &
-0.03097494063, 0.9995201614, -0.6731660801, 0.739491331, -0.7195018362, -0.6944905383, 0.9727511689, 0.2318515979, 0.9997059088, -0.0242506907, 0.4421787429, -0.8969269532, 0.9981350961, -0.061043673, -0.9173660799, -0.3980445648, &
-0.8150056635, -0.5794529907, -0.8789331304, 0.4769450202, 0.0158605829, 0.999874213, -0.8095464474, 0.5870558317, -0.9165898907, -0.3998286786, -0.8023542565, 0.5968480938, -0.5176737917, 0.8555780767, -0.8154407307, -0.5788405779, &
0.4022010347, -0.9155513791, -0.9052556868, -0.4248672045, 0.7317445619, 0.6815789728, -0.5647632201, -0.8252529947, -0.8403276335, -0.5420788397, -0.9314281527, 0.363925262, 0.5238198472, 0.8518290719, 0.7432803869, -0.6689800195, &
-0.985371561, -0.1704197369, 0.4601468731, 0.88784281, 0.825855404, 0.5638819483, 0.6182366099, 0.7859920446, 0.8331502863, -0.553046653, 0.1500307506, 0.9886813308, -0.662330369, -0.7492119075, -0.668598664, 0.743623444, &
0.7025606278, 0.7116238924, -0.5419389763, -0.8404178401, -0.3388616456, 0.9408362159, 0.8331530315, 0.5530425174, -0.2989720662, -0.9542618632, 0.2638522993, 0.9645630949, 0.124108739, -0.9922686234, -0.7282649308, -0.6852956957, &
0.6962500149, 0.7177993569, -0.9183535368, 0.3957610156, -0.6326102274, -0.7744703352, -0.9331891859, -0.359385508, -0.1153779357, -0.9933216659, 0.9514974788, -0.3076565421, -0.08987977445, -0.9959526224, 0.6678496916, 0.7442961705, &
0.7952400393, -0.6062947138, -0.6462007402, -0.7631674805, -0.2733598753, 0.9619118351, 0.9669590226, -0.254931851, -0.9792894595, 0.2024651934, -0.5369502995, -0.8436138784, -0.270036471, -0.9628500944, -0.6400277131, 0.7683518247, &
-0.7854537493, -0.6189203566, 0.06005905383, -0.9981948257, -0.02455770378, 0.9996984141, -0.65983623, 0.751409442, -0.6253894466, -0.7803127835, -0.6210408851, -0.7837781695, 0.8348888491, 0.5504185768, -0.1592275245, 0.9872419133, &
0.8367622488, 0.5475663786, -0.8675753916, -0.4973056806, -0.2022662628, -0.9793305667, 0.9399189937, 0.3413975472, 0.9877404807, -0.1561049093, -0.9034455656, 0.4287028224, 0.1269804218, -0.9919052235, -0.3819600854, 0.924178821, &
0.9754625894, 0.2201652486, -0.3204015856, -0.9472818081, -0.9874760884, 0.1577687387, 0.02535348474, -0.9996785487, 0.4835130794, -0.8753371362, -0.2850799925, -0.9585037287, -0.06805516006, -0.99768156, -0.7885244045, -0.6150034663, &
0.3185392127, -0.9479096845, 0.8880043089, 0.4598351306, 0.6476921488, -0.7619021462, 0.9820241299, 0.1887554194, 0.9357275128, -0.3527237187, -0.8894895414, 0.4569555293, 0.7922791302, 0.6101588153, 0.7483818261, 0.6632681526, &
-0.7288929755, -0.6846276581, 0.8729032783, -0.4878932944, 0.8288345784, 0.5594937369, 0.08074567077, 0.9967347374, 0.9799148216, -0.1994165048, -0.580730673, -0.8140957471, -0.4700049791, -0.8826637636, 0.2409492979, 0.9705377045, &
0.9437816757, -0.3305694308, -0.8927998638, -0.4504535528, -0.8069622304, 0.5906030467, 0.06258973166, 0.9980393407, -0.9312597469, 0.3643559849, 0.5777449785, 0.8162173362, -0.3360095855, -0.941858566, 0.697932075, -0.7161639607, &
-0.002008157227, -0.9999979837, -0.1827294312, -0.9831632392, -0.6523911722, 0.7578824173, -0.4302626911, -0.9027037258, -0.9985126289, -0.05452091251, -0.01028102172, -0.9999471489, -0.4946071129, 0.8691166802, -0.2999350194, 0.9539596344, &
0.8165471961, 0.5772786819, 0.2697460475, 0.962931498, -0.7306287391, -0.6827749597, -0.7590952064, -0.6509796216, -0.907053853, 0.4210146171, -0.5104861064, -0.8598860013, 0.8613350597, 0.5080373165, 0.5007881595, -0.8655698812, &
-0.654158152, 0.7563577938, -0.8382755311, -0.545246856, 0.6940070834, 0.7199681717, 0.06950936031, 0.9975812994, 0.1702942185, -0.9853932612, 0.2695973274, 0.9629731466, 0.5519612192, -0.8338697815, 0.225657487, -0.9742067022, &
0.4215262855, -0.9068161835, 0.4881873305, -0.8727388672, -0.3683854996, -0.9296731273, -0.9825390578, 0.1860564427, 0.81256471, 0.5828709909, 0.3196460933, -0.9475370046, 0.9570913859, 0.2897862643, -0.6876655497, -0.7260276109, &
-0.9988770922, -0.047376731, -0.1250179027, 0.992154486, -0.8280133617, 0.560708367, 0.9324863769, -0.3612051451, 0.6394653183, 0.7688199442, -0.01623847064, -0.9998681473, -0.9955014666, -0.09474613458, -0.81453315, 0.580117012, &
0.4037327978, -0.9148769469, 0.9944263371, 0.1054336766, -0.1624711654, 0.9867132919, -0.9949487814, -0.100383875, -0.6995302564, 0.7146029809, 0.5263414922, -0.85027327, -0.5395221479, 0.841971408, 0.6579370318, 0.7530729462, &
0.01426758847, -0.9998982128, -0.6734383991, 0.7392433447, 0.639412098, -0.7688642071, 0.9211571421, 0.3891908523, -0.146637214, -0.9891903394, -0.782318098, 0.6228791163, -0.5039610839, -0.8637263605, -0.7743120191, -0.6328039957 &
/)
real(c_float), dimension(256), parameter :: GRADIENTS_3D = (/ &
0.0, 1.0, 1.0, 0.0, 0.0,-1.0, 1.0, 0.0, 0.0, 1.0,-1.0, 0.0, 0.0,-1.0,-1.0, 0.0, &
1.0, 0.0, 1.0, 0.0, -1.0, 0.0, 1.0, 0.0, 1.0, 0.0,-1.0, 0.0, -1.0, 0.0,-1.0, 0.0, &
1.0, 1.0, 0.0, 0.0, -1.0, 1.0, 0.0, 0.0, 1.0,-1.0, 0.0, 0.0, -1.0,-1.0, 0.0, 0.0, &
0.0, 1.0, 1.0, 0.0, 0.0,-1.0, 1.0, 0.0, 0.0, 1.0,-1.0, 0.0, 0.0,-1.0,-1.0, 0.0, &
1.0, 0.0, 1.0, 0.0, -1.0, 0.0, 1.0, 0.0, 1.0, 0.0,-1.0, 0.0, -1.0, 0.0,-1.0, 0.0, &
1.0, 1.0, 0.0, 0.0, -1.0, 1.0, 0.0, 0.0, 1.0,-1.0, 0.0, 0.0, -1.0,-1.0, 0.0, 0.0, &
0.0, 1.0, 1.0, 0.0, 0.0,-1.0, 1.0, 0.0, 0.0, 1.0,-1.0, 0.0, 0.0,-1.0,-1.0, 0.0, &
1.0, 0.0, 1.0, 0.0, -1.0, 0.0, 1.0, 0.0, 1.0, 0.0,-1.0, 0.0, -1.0, 0.0,-1.0, 0.0, &
1.0, 1.0, 0.0, 0.0, -1.0, 1.0, 0.0, 0.0, 1.0,-1.0, 0.0, 0.0, -1.0,-1.0, 0.0, 0.0, &
0.0, 1.0, 1.0, 0.0, 0.0,-1.0, 1.0, 0.0, 0.0, 1.0,-1.0, 0.0, 0.0,-1.0,-1.0, 0.0, &
1.0, 0.0, 1.0, 0.0, -1.0, 0.0, 1.0, 0.0, 1.0, 0.0,-1.0, 0.0, -1.0, 0.0,-1.0, 0.0, &
1.0, 1.0, 0.0, 0.0, -1.0, 1.0, 0.0, 0.0, 1.0,-1.0, 0.0, 0.0, -1.0,-1.0, 0.0, 0.0, &
0.0, 1.0, 1.0, 0.0, 0.0,-1.0, 1.0, 0.0, 0.0, 1.0,-1.0, 0.0, 0.0,-1.0,-1.0, 0.0, &
1.0, 0.0, 1.0, 0.0, -1.0, 0.0, 1.0, 0.0, 1.0, 0.0,-1.0, 0.0, -1.0, 0.0,-1.0, 0.0, &
1.0, 1.0, 0.0, 0.0, -1.0, 1.0, 0.0, 0.0, 1.0,-1.0, 0.0, 0.0, -1.0,-1.0, 0.0, 0.0, &
1.0, 1.0, 0.0, 0.0, 0.0,-1.0, 1.0, 0.0, -1.0, 1.0, 0.0, 0.0, 0.0,-1.0,-1.0, 0.0 &
/)
real(c_float), dimension(1024), parameter :: RAND_VECS_3D = (/ &
-0.7292736885, -0.6618439697, 0.1735581948, 0.0, 0.790292081, -0.5480887466, -0.2739291014, 0.0, 0.7217578935, 0.6226212466, -0.3023380997, 0.0, 0.565683137, -0.8208298145, -0.0790000257, 0.0, 0.760049034, -0.5555979497, -0.3370999617, 0.0, 0.3713945616, 0.5011264475, 0.7816254623, 0.0, -0.1277062463, -0.4254438999, -0.8959289049, 0.0, -0.2881560924, -0.5815838982, 0.7607405838, 0.0, &
0.5849561111, -0.662820239, -0.4674352136, 0.0, 0.3307171178, 0.0391653737, 0.94291689, 0.0, 0.8712121778, -0.4113374369, -0.2679381538, 0.0, 0.580981015, 0.7021915846, 0.4115677815, 0.0, 0.503756873, 0.6330056931, -0.5878203852, 0.0, 0.4493712205, 0.601390195, 0.6606022552, 0.0, -0.6878403724, 0.09018890807, -0.7202371714, 0.0, -0.5958956522, -0.6469350577, 0.475797649, 0.0, &
-0.5127052122, 0.1946921978, -0.8361987284, 0.0, -0.9911507142, -0.05410276466, -0.1212153153, 0.0, -0.2149721042, 0.9720882117, -0.09397607749, 0.0, -0.7518650936, -0.5428057603, 0.3742469607, 0.0, 0.5237068895, 0.8516377189, -0.02107817834, 0.0, 0.6333504779, 0.1926167129, -0.7495104896, 0.0, -0.06788241606, 0.3998305789, 0.9140719259, 0.0, -0.5538628599, -0.4729896695, -0.6852128902, 0.0, &
-0.7261455366, -0.5911990757, 0.3509933228, 0.0, -0.9229274737, -0.1782808786, 0.3412049336, 0.0, -0.6968815002, 0.6511274338, 0.3006480328, 0.0, 0.9608044783, -0.2098363234, -0.1811724921, 0.0, 0.06817146062, -0.9743405129, 0.2145069156, 0.0, -0.3577285196, -0.6697087264, -0.6507845481, 0.0, -0.1868621131, 0.7648617052, -0.6164974636, 0.0, -0.6541697588, 0.3967914832, 0.6439087246, 0.0, &
0.6993340405, -0.6164538506, 0.3618239211, 0.0, -0.1546665739, 0.6291283928, 0.7617583057, 0.0, -0.6841612949, -0.2580482182, -0.6821542638, 0.0, 0.5383980957, 0.4258654885, 0.7271630328, 0.0, -0.5026987823, -0.7939832935, -0.3418836993, 0.0, 0.3202971715, 0.2834415347, 0.9039195862, 0.0, 0.8683227101, -0.0003762656404, -0.4959995258, 0.0, 0.791120031, -0.08511045745, 0.6057105799, 0.0, &
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/)
integer(c_int), parameter :: PRIME_X = 501125321
integer(c_int), parameter :: PRIME_Y = 1136930381
integer(c_int), parameter :: PRIME_Z = 1720413743
contains
! Utilities
real(c_float) function internal_fnl_inv_sqrt(a) result(out)
implicit none
real(c_float), intent(in), value :: a
real(c_float) :: xhalf
integer(c_int), parameter :: magic = int(z"5f3759df", c_int)
xhalf = 0.5 * a
out = real(magic - (shiftr(int(a), 1)))
out = out * (1.5 - xhalf * a * a)
end function internal_fnl_inv_sqrt
real(c_float) function internal_fnl_lerp(a, b, t) result(output)
implicit none
real(c_float), intent(in), value :: a, b, t
output = a + t * (b - a)
end function internal_fnl_lerp
real(c_float) function internal_fnl_interp_hermite(t) result(output)
implicit none
real(c_float), intent(in), value :: t
output = t * t * (3 - 2 * t)
end function internal_fnl_interp_hermite
real(c_float) function internal_fnl_interp_quintic(t) result(output)
implicit none
real(c_float), intent(in), value :: t
output = t * t * t * (t * (t * 6 - 15) + 10)
end function internal_fnl_interp_quintic
real(c_float) function internal_fnl_cubic_lerp(a, b, c, d, t) result(output)
implicit none
real(c_float), intent(in), value :: a, b, c, d, t
real(c_float) :: p
p = (d - c) - (a - b)
output = t * t * t * p + t * t * ((a - b) - p) + t * (c - a) + b
end function internal_fnl_cubic_lerp
real(c_float) function internal_fnl_ping_pong(t) result(output)
implicit none
real(c_float), intent(in), value :: t
real(c_float) :: i
i = i - (int(t * 0.5) * 2)
output = merge(t, 2 - t, i < 1)
end function internal_fnl_ping_pong
real(c_float) function internal_fnl_calculate_fractal_bounding(state) result(output)
implicit none
type(fnl_state), intent(in) :: state
real(c_float) :: gain, amp, amp_fractal
integer(c_int) :: i
gain = abs(state%gain)
amp = gain
amp_fractal = 1.0
do i = 1,state%octaves - 1
amp_fractal = amp_fractal + amp
amp = amp * gain
end do
output = 1.0 / amp_fractal
end function internal_fnl_calculate_fractal_bounding
! Hashing
integer(c_int) function internal_fnl_hash_2d(seed, x_primed, y_primed) result(hash)
implicit none
integer(c_int), intent(in), value :: seed, x_primed, y_primed
integer(c_int), parameter :: magic = int(z"27d4eb2d")
hash = xor(xor(seed, x_primed), y_primed)
hash = hash * magic
end function internal_fnl_hash_2d
integer(c_int) function internal_fnl_hash_3d(seed, x_primed, y_primed, z_primed) result(hash)
implicit none
integer(c_int), intent(in), value :: seed, x_primed, y_primed, z_primed
integer(c_int), parameter :: magic = int(z"27d4eb2d")
hash = xor(xor(xor(seed, x_primed), y_primed), z_primed)
hash = hash * magic
end function internal_fnl_hash_3d
real(c_float) function internal_fnl_val_coord_2d(seed, x_primed, y_primed) result(hash)
implicit none
integer(c_int), intent(in), value :: seed, x_primed, y_primed
integer(c_int) :: int_hash
int_hash = internal_fnl_hash_2d(seed, x_primed, y_primed)
int_hash = int_hash * int_hash
int_hash = xor(int_hash, (shiftl(int_hash, 19)))
hash = int_hash * (1 / 2147483648.0)
end function internal_fnl_val_coord_2d
real(c_float) function internal_fnl_val_coord_3d(seed, x_primed, y_primed, z_primed) result(hash)
implicit none
integer(c_int), intent(in), value :: seed, x_primed, y_primed, z_primed
integer(c_int) :: int_hash
int_hash = internal_fnl_hash_3d(seed, x_primed, y_primed, z_primed)
int_hash = int_hash * int_hash
int_hash = xor(int_hash, shiftl(int_hash, 19))
hash = int_hash * (1 / 2147483648.0)
end function internal_fnl_val_coord_3d
real(c_float) function internal_fnl_grad_coord_2d(seed, x_primed, y_primed, xd, yd) result(hash)
implicit none
integer(c_int), intent(in), value :: seed, x_primed, y_primed
real(c_float), intent(in), value :: xd, yd
integer(c_int) :: int_hash
int_hash = internal_fnl_hash_2d(seed, x_primed, y_primed)
int_hash = xor(int_hash, shiftr(int_hash, 15))
int_hash = and(int_hash, shiftl(127, 1))
hash = xd * GRADIENTS_2D(int_hash + 1) + yd * GRADIENTS_2D(ior(int_hash, 1) + 1)
end function internal_fnl_grad_coord_2d
real(c_float) function internal_fnl_grad_coord_3d(seed, x_primed, y_primed, z_primed, xd, yd, zd) result(hash)
implicit none
integer(c_int), intent(in), value :: seed, x_primed, y_primed, z_primed
real(c_float), intent(in), value :: xd, yd, zd
integer(c_int) :: int_hash
int_hash = internal_fnl_hash_3d(seed, x_primed, y_primed, z_primed)
int_hash = xor(int_hash, shiftr(int_hash, 15))
int_hash = and(int_hash, shiftl(63, 2))
hash = xd * GRADIENTS_3D(int_hash + 1) + yd * GRADIENTS_3D(ior(int_hash, 1) + 1) + zd * GRADIENTS_3D(ior(int_hash, 2) + 1)
end function internal_fnl_grad_coord_3d
subroutine internal_fnl_grad_coord_out_2d(seed, x_primed, y_primed, xo, yo)
implicit none
integer(c_int), intent(in), value :: seed, x_primed, y_primed
real(c_float), intent(inout) :: xo, yo
integer(c_int) :: int_hash
int_hash = and(internal_fnl_hash_2d(seed, x_primed, y_primed), shiftl(255, 1))
xo = RAND_VECS_2D(int_hash + 1)
yo = RAND_VECS_2D(ior(int_hash, 1) + 1)
end subroutine internal_fnl_grad_coord_out_2d
subroutine internal_fnl_grad_coord_out_3d(seed, x_primed, y_primed, z_primed, xo, yo, zo)
implicit none
integer(c_int), intent(in), value :: seed, x_primed, y_primed, z_primed
real(c_float), intent(inout) :: xo, yo, zo
integer(c_int) :: int_hash
int_hash = and(internal_fnl_hash_3d(seed, x_primed, y_primed, z_primed), shiftl(255, 2))
xo = RAND_VECS_3D(int_hash + 1)
yo = RAND_VECS_3D(ior(int_hash, 1) + 1)
zo = RAND_VECS_3D(ior(int_hash, 2) + 1)
end subroutine internal_fnl_grad_coord_out_3d
subroutine internal_fnl_grad_coord_dual_2d(seed, x_primed, y_primed, xd, yd, xo, yo)
implicit none
integer(c_int), intent(in), value :: seed, x_primed, y_primed
real(c_float), intent(in) :: xd, yd
real(c_float), intent(inout) :: xo, yo
integer(c_int) :: int_hash, index_1, index_2
real(c_float) :: xg, yg, value, xgo, ygo
int_hash = internal_fnl_hash_2d(seed, x_primed, y_primed)
index_1 = and(int_hash, shiftl(127, 1))
index_2 = and(shiftr(int_hash, 7), shiftl(255, 1))
xg = GRADIENTS_2D(index_1 + 1)
yg = GRADIENTS_2D(ior(index_1, 1) + 1)
value = xd * xg + yd * yg
xgo = RAND_VECS_2D(index_2 + 1)
ygo = RAND_VECS_2D(ior(index_2, 1) + 1)
xo = value * xgo
yo = value * ygo
end subroutine internal_fnl_grad_coord_dual_2d
subroutine internal_fnl_grad_coord_dual_3d(seed, x_primed, y_primed, z_primed, xd, yd, zd, xo, yo, zo)
implicit none
integer(c_int), intent(in), value :: seed, x_primed, y_primed, z_primed
real(c_float), intent(in) :: xd, yd, zd
real(c_float), intent(inout) :: xo, yo, zo
integer(c_int) :: int_hash, index_1, index_2
real(c_float) :: xg, yg, zg, value, xgo, ygo, zgo
int_hash = internal_fnl_hash_3d(seed, x_primed, y_primed, z_primed)
index_1 = and(int_hash, shiftl(63, 2))
index_2 = and(shiftr(int_hash, 6), shiftl(255, 2))
xg = GRADIENTS_3D(index_1 + 1)
yg = GRADIENTS_3D(ior(index_1, 1) + 1)
zg = GRADIENTS_3D(ior(index_1, 2) + 1)
value = xd * xg + yd * yg + zd * zg
xgo = RAND_VECS_3D(index_2 + 1)
ygo = RAND_VECS_3D(ior(index_2, 1) + 1)
zgo = RAND_VECS_3D(ior(index_2, 2) + 1)
xo = value * xgo
yo = value * ygo
zo = value * zgo
end subroutine internal_fnl_grad_coord_dual_3d
! Generic Noise Gen
real(c_float) function internal_fnl_gen_noise_single_2d(state, seed, x, y) result(output)
implicit none
type(fnl_state), intent(in) :: state
integer(c_int), intent(in), value :: seed
real(fnl_float), intent(in), value :: x, y
select case(state%noise_type)
case (FNL_NOISE_OPENSIMPLEX2)
output = internal_fnl_single_simplex_2d(seed, x, y)
case (FNL_NOISE_OPENSIMPLEX2S)
output = internal_fnl_single_open_simplex_2s_2d(seed, x, y)
case (FNL_NOISE_CELLULAR)
output = internal_fnl_single_cellular_2d(state, seed, x, y)
case (FNL_NOISE_PERLIN)
output = internal_fnl_single_perlin_2d(seed, x, y)
case (FNL_NOISE_VALUE_CUBIC)
output = internal_fnl_single_value_cubic_2d(seed, x, y)
case (FNL_NOISE_VALUE)
output = internal_fnl_single_value_2d(seed, x, y)
case default
output = 0.0
end select
end function internal_fnl_gen_noise_single_2d
real(c_float) function internal_fnl_gen_noise_single_3d(state, seed, x, y, z) result(output)
implicit none
type(fnl_state), intent(in) :: state
integer(c_int), intent(in), value :: seed
real(fnl_float), intent(in), value :: x, y, z
select case (state%noise_type)
case (FNL_NOISE_OPENSIMPLEX2)
output = internal_fnl_single_open_simplex_2_3d(seed, x, y, z)
case (FNL_NOISE_OPENSIMPLEX2S)
output = internal_fnl_single_open_simplex_2d_3d(seed, x, y, z)
case (FNL_NOISE_CELLULAR)
output = internal_fnl_single_cellular_3d(state, seed, x, y, z)
case (FNL_NOISE_PERLIN)
output = internal_fnl_single_perlin_3d(seed, x, y, z)
case (FNL_NOISE_VALUE_CUBIC)
output = internal_fnl_single_value_cubic_3d(seed, x, y, z)
case (FNL_NOISE_VALUE)
output = internal_fnl_single_value_3d(seed, x, y, z)
case default
output = 0.0
end select
end function internal_fnl_gen_noise_single_3d
! Noise Coordinate Transforms (frequency, and possible skew or rotation)
subroutine internal_fnl_transform_noise_coordinate_2d(state, x, y)
implicit none
type(fnl_state), intent(in) :: state
real(fnl_float), intent(inout) :: x, y
real(fnl_float) :: t
real(fnl_float), parameter :: SQRT_3 = real(1.7320508075688772935274463415059, fnl_float)
real(fnl_float), parameter :: F2 = 0.5 * (SQRT_3 - 1.0)
x = x * state%frequency
y = y * state%frequency
select case(state%noise_type)
case (FNL_NOISE_OPENSIMPLEX2, FNL_NOISE_OPENSIMPLEX2S)
t = (x + y) * F2
x = x + t
y = y + t
case default
end select
end subroutine internal_fnl_transform_noise_coordinate_2d
subroutine internal_fnl_transform_noise_coordinates_3d(state, x, y, z)
implicit none
type(fnl_state), intent(in) :: state
real(fnl_float), intent(inout) :: x, y, z
real(fnl_float) xy, s2, xz, r3, r
x = x * state%frequency
y = y * state%frequency
z = z * state%frequency
select case (state%rotation_type_3d)
case (FNL_ROTATION_IMPROVE_XY_PLANES)
xy = x + y
s2 = xy * (-real(0.211324865405187, fnl_float))
z = z * real(0.577350269189626, fnl_float)
x = x + (s2 - z)
y = y + s2 - z
z = z + (xy * real(0.577350269189626, fnl_float))
case (FNL_ROTATION_IMPROVE_XZ_PLANES)
xz = x + z
s2 = xz * (-real(0.211324865405187, fnl_float))
y = y * real(0.577350269189626, fnl_float)
x = x + (s2 - y)
z = z + (s2 - y)
y = y + (xz * real(0.577350269189626, fnl_float))
case default
select case (state%noise_type)
case (FNL_NOISE_OPENSIMPLEX2S, FNL_NOISE_OPENSIMPLEX2)
r3 = real((2.0 / 3.0), fnl_float)
r = (x + y + z) * r3 ! Rotation, not skew
x = r - x
y = r - y
z = r - z
case default
end select
end select ! state%rotation_type_3d
end subroutine internal_fnl_transform_noise_coordinates_3d
! Domain Warp Coordinate Transforms
subroutine internal_fnl_transform_domain_warp_coordinate_2d(state, x, y)
implicit none
type(fnl_state), intent(in) :: state
real(fnl_float), intent(inout) :: x, y
real(fnl_float) :: t
real(fnl_float), parameter :: SQRT_3 = real(1.7320508075688772935274463415059, fnl_float)
real(fnl_float), parameter :: F2 = 0.5 * (SQRT_3 - 1.0)
select case (state%domain_warp_type)
case (FNL_DOMAIN_WARP_OPENSIMPLEX2_REDUCED, FNL_DOMAIN_WARP_OPENSIMPLEX2)
t = (x + y) * F2
x = x + t
y = y + t
case default
end select
end subroutine internal_fnl_transform_domain_warp_coordinate_2d
subroutine internal_fnl_transform_domain_warp_coordinate_3d(state, x, y, z)
implicit none
type(fnl_state), intent(in) :: state
real(fnl_float), intent(inout) :: x, y, z
real(fnl_float) :: xy, s2, xz, r3, r
select case (state%rotation_type_3d)
case (FNL_ROTATION_IMPROVE_XY_PLANES)
xy = x + y
s2 = xy * (-real(0.211324865405187, fnl_float))
z = z * real(0.577350269189626, fnl_float)
x = x + (s2 - z)
y = y + s2 - z
z = z + (xy * real(0.577350269189626, fnl_float))
case (FNL_ROTATION_IMPROVE_XZ_PLANES)
xz = x + z
s2 = xz * (-real(0.211324865405187, fnl_float))
y = y * real(0.577350269189626, fnl_float)
x = x + (s2 - y)
z = z + (s2 - y)
y = y + (xz * real(0.577350269189626, fnl_float))
case default
select case (state%domain_warp_type)
case (FNL_DOMAIN_WARP_OPENSIMPLEX2_REDUCED, FNL_DOMAIN_WARP_OPENSIMPLEX2)
r3 = real(2.0 / 3.0, fnl_float)
r = (x + y + z) * r3 ! Rotation, not skew
x = r - x
y = r - y
z = r - z
case default
end select
end select
end subroutine internal_fnl_transform_domain_warp_coordinate_3d
! Fractal FBm
real(c_float) function internal_fnl_gen_fraction_fbm_2d(state, x, y) result(sum)
implicit none
type(fnl_state), intent(in) :: state
real(fnl_float), intent(in), value :: x, y
integer(c_int) :: seed, i
real(c_float) :: amp, noise
real(fnl_float) :: xx, yy
xx = x
yy = y
seed = state%seed
sum = 0
amp = internal_fnl_calculate_fractal_bounding(state)
do i = 1,state%octaves
seed = seed + 1
noise = internal_fnl_gen_noise_single_2d(state, seed, xx, yy)
sum = sum + (noise * amp)
amp = amp * (internal_fnl_lerp(1.0, min(noise + 1.0, 2.0) * 0.5, state%weighted_strength))
xx = xx * state%lacunarity
yy = yy * state%lacunarity
amp = amp * state%gain
end do
end function internal_fnl_gen_fraction_fbm_2d
real(c_float) function internal_fnl_gen_fractal_fbm_3d(state, x, y, z) result(sum)
implicit none
type(fnl_state), intent(in) :: state
real(fnl_float), intent(in), value :: x, y, z
integer(c_int) :: seed, i
real(c_float) :: amp, noise
real(fnl_float) :: xx, yy, zz
xx = x
yy = y
zz = z
seed = state%seed
sum = 0
amp = internal_fnl_calculate_fractal_bounding(state)
do i = 1, state%octaves
seed = seed + 1
noise = internal_fnl_gen_noise_single_3d(state, seed, xx, yy, zz)
sum = sum + (noise * amp)
amp = amp * (internal_fnl_lerp(1.0, (noise + 1.0) * 0.5, state%weighted_strength))
xx = xx * state%lacunarity
yy = yy * state%lacunarity
zz = zz * state%lacunarity
amp = amp * state%gain
end do
end function internal_fnl_gen_fractal_fbm_3d
! Fractal Ridged
real(c_float) function internal_fnm_gen_fractal_ridged_2d(state, x, y) result(sum)
implicit none
type(fnl_state), intent(in) :: state
real(fnl_float), intent(in), value :: x, y
integer(c_int) :: seed, i
real(c_float) :: amp, noise
real(fnl_float) :: xx, yy
xx = x
yy = y
seed = state%seed
sum = 0.0
amp = internal_fnl_calculate_fractal_bounding(state)
do i = 1, state%octaves
seed = seed + 1
noise = abs(internal_fnl_gen_noise_single_2d(state, seed, xx, yy))
sum = sum + ((noise * (-2.0) + 1.0) * amp)
amp = amp * (internal_fnl_lerp(1.0, 1.0 - noise, state%weighted_strength))
xx = xx * state%lacunarity
yy = yy * state%lacunarity
amp = amp * state%gain
end do
end function internal_fnm_gen_fractal_ridged_2d
real(c_float) function internal_fnl_gen_fractal_ridged_3d(state, x, y, z) result(sum)
implicit none
type(fnl_state), intent(in) :: state
real(fnl_float), intent(in), value :: x, y, z
integer(c_int) :: seed, i
real(c_float) :: amp, noise
real(fnl_float) :: xx, yy, zz
xx = x
yy = y
zz = z
seed = state%seed
sum = 0.0
amp = internal_fnl_calculate_fractal_bounding(state)
do i = 1, state%octaves
seed = seed + 1
noise = abs(internal_fnl_gen_noise_single_3d(state, seed, xx, yy, zz))
sum = sum + ((noise * (-2.0) + 1.0) * amp)
amp = amp * (internal_fnl_lerp(1.0, 1.0 - noise, state%weighted_strength))
xx = xx * state%lacunarity
yy = yy * state%lacunarity
zz = zz * state%lacunarity
amp = amp * state%gain
end do
end function internal_fnl_gen_fractal_ridged_3d
! Fractal PingPong
real(c_float) function internal_fnl_gen_fractal_ping_pong_2d(state, x, y) result(sum)
implicit none
type(fnl_state), intent(in) :: state
real(fnl_float), intent(in), value :: x, y
integer(c_int) :: seed, i
real(c_float) :: amp, noise
real(fnl_float) :: xx, yy
xx = x
yy = y
seed = state%seed
sum = 0
amp = internal_fnl_calculate_fractal_bounding(state)
do i = 1, state%octaves
seed = seed + 1
noise = internal_fnl_ping_pong((internal_fnl_gen_noise_single_2d(state, seed, xx, yy) + 1.0) * state%ping_pong_strength)
sum = sum + ((noise - 0.5) * 2.0 * amp)
amp = amp * (internal_fnl_lerp(1.0, noise, state%weighted_strength))
xx = xx * state%lacunarity
yy = yy * state%lacunarity
amp = amp * state%gain
end do
end function internal_fnl_gen_fractal_ping_pong_2d
real(c_float) function internal_fnl_gen_fractal_ping_pong_3d(state, x, y, z) result(sum)
implicit none
type(fnl_state), intent(in) :: state
real(fnl_float), intent(in), value :: x, y, z
integer(c_int) :: seed, i
real(c_float) :: amp, noise
real(fnl_float) :: xx, yy, zz
xx = x
yy = y
zz = z
seed = state%seed
sum = 0
amp = internal_fnl_calculate_fractal_bounding(state)
do i = 1, state%octaves
seed = seed + 1
noise = internal_fnl_ping_pong((internal_fnl_gen_noise_single_3d(state, seed, xx, yy, zz) + 1) * state%ping_pong_strength)
sum = sum + ((noise - 0.5) * 2.0 * amp)
amp = amp * (internal_fnl_lerp(1.0, noise, state%weighted_strength))
xx = xx * state%lacunarity
yy = yy * state%lacunarity
zz = zz * state%lacunarity
amp = amp * state%gain
end do