mirror of
https://github.com/Xaymar/obs-StreamFX
synced 2024-12-05 01:27:26 +00:00
271 lines
7.7 KiB
C++
271 lines
7.7 KiB
C++
/*
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* Modern effects for a modern Streamer
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* Copyright (C) 2018 Michael Fabian Dirks
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*
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* This program is free software; you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation; either version 2 of the License, or
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* (at your option) any later version.
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*
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* This program is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with this program; if not, write to the Free Software
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* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA
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*/
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#pragma once
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#include <cinttypes>
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#include <cstddef>
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#include <string>
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#include <type_traits>
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#include <vector>
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extern "C" {
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#ifdef _MSC_VER
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#pragma warning(push)
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#pragma warning(disable : 4201)
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#endif
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#include <obs.h>
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#include <graphics/vec2.h>
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#include <graphics/vec3.h>
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#include <graphics/vec4.h>
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#ifdef _MSC_VER
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#pragma warning(pop)
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#endif
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}
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// Constants
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#define S_PI 3.1415926535897932384626433832795 // PI = pi
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#define S_PI2 6.283185307179586476925286766559 // 2PI = 2 * pi
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#define S_PI2_SQROOT 2.506628274631000502415765284811 // sqrt(2 * pi)
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#define S_RAD 57.295779513082320876798154814105 // 180/pi
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#define S_DEG 0.01745329251994329576923690768489 // pi/180
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#define D_DEG_TO_RAD(x) (x * S_DEG)
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#define D_RAD_TO_DEG(x) (x * S_RAD)
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#define D_STR(s) #s
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#define D_VSTR(s) D_STR(s)
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namespace streamfx::util {
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bool inline are_property_groups_broken()
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{
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return obs_get_version() < MAKE_SEMANTIC_VERSION(24, 0, 0);
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}
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obs_property_t* obs_properties_add_tristate(obs_properties_t* props, const char* name, const char* desc);
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inline bool is_tristate_enabled(int64_t tristate)
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{
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return tristate == 1;
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}
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inline bool is_tristate_disabled(int64_t tristate)
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{
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return tristate == 0;
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}
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inline bool is_tristate_default(int64_t tristate)
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{
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return tristate == -1;
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}
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struct vec2a : public vec2 {
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// 16-byte Aligned version of vec2
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static void* operator new(std::size_t count);
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static void* operator new[](std::size_t count);
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static void operator delete(void* p);
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static void operator delete[](void* p);
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};
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#ifdef _MSC_VER
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__declspec(align(16))
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#endif
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struct vec3a : public vec3 {
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// 16-byte Aligned version of vec3
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static void* operator new(std::size_t count);
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static void* operator new[](std::size_t count);
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static void operator delete(void* p);
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static void operator delete[](void* p);
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};
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#ifdef _MSC_VER
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__declspec(align(16))
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#endif
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struct vec4a : public vec4 {
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// 16-byte Aligned version of vec4
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static void* operator new(std::size_t count);
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static void* operator new[](std::size_t count);
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static void operator delete(void* p);
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static void operator delete[](void* p);
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};
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std::pair<int64_t, int64_t> size_from_string(std::string text, bool allowSquare = true);
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namespace math {
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template<typename T>
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inline T pow(T base, T exp)
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{
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T res = 1;
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while (exp) {
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if (exp & 1)
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res *= base;
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exp >>= 1;
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base *= base;
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}
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return res;
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}
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// Proven by tests to be the fastest implementation on Intel and AMD CPUs.
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// Ranking: log10, loop < bitscan < pow
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// loop and log10 trade blows, usually almost identical.
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// loop is used for integers, log10 for anything else.
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template<typename T>
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inline bool is_power_of_two(T v)
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{
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return T(1ull << uint64_t(floor(log10(T(v)) / log10(2.0)))) == v;
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}
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template<typename T>
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inline bool is_power_of_two_loop(T v)
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{
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bool have_bit = false;
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for (std::size_t index = 0; index < (sizeof(T) * 8); index++) {
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bool cur = (v & (static_cast<T>(1ull) << index)) != 0;
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if (cur) {
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if (have_bit)
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return false;
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have_bit = true;
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}
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}
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return true;
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}
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#pragma push_macro("P_IS_POWER_OF_TWO_AS_LOOP")
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#define P_IS_POWER_OF_TWO_AS_LOOP(x) \
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template<> \
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inline bool is_power_of_two(x v) \
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{ \
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return is_power_of_two_loop(v); \
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}
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P_IS_POWER_OF_TWO_AS_LOOP(int8_t)
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P_IS_POWER_OF_TWO_AS_LOOP(uint8_t)
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P_IS_POWER_OF_TWO_AS_LOOP(int16_t)
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P_IS_POWER_OF_TWO_AS_LOOP(uint16_t)
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P_IS_POWER_OF_TWO_AS_LOOP(int32_t)
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P_IS_POWER_OF_TWO_AS_LOOP(uint32_t)
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P_IS_POWER_OF_TWO_AS_LOOP(int64_t)
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P_IS_POWER_OF_TWO_AS_LOOP(uint64_t)
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#undef P_IS_POWER_OF_TWO_AS_LOOP
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#pragma pop_macro("P_IS_POWER_OF_TWO_AS_LOOP")
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template<typename T>
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inline uint64_t get_power_of_two_exponent_floor(T v)
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{
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return uint64_t(floor(log10(T(v)) / log10(2.0)));
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}
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template<typename T>
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inline uint64_t get_power_of_two_exponent_ceil(T v)
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{
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return uint64_t(ceil(log10(T(v)) / log10(2.0)));
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}
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template<typename T, typename C>
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inline bool is_equal(T target, C value)
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{
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return (target > (value - std::numeric_limits<T>::epsilon()))
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&& (target < (value + std::numeric_limits<T>::epsilon()));
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}
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template<typename T>
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inline bool is_close(T target, T value, T delta)
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{
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return (target > (value - delta)) && (target < (value + delta));
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}
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template<typename T>
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inline std::vector<T> pascal_triangle(size_t n)
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{
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std::vector<T> line;
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line.push_back(1);
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for (uint64_t k = 0; k < n; k++) {
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T v = static_cast<T>(line.at(k) * static_cast<double_t>(n - k) / static_cast<double_t>(k + 1));
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line.push_back(v);
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}
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return line;
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}
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template<typename T>
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inline T gaussian(T x, T o /*, T u = 0*/)
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{
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// u/µ can be simulated by subtracting that value from x.
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//static const double_t pi = 3.1415926535897932384626433832795;
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//static const double_t two_pi = pi * 2.;
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static const double_t two_pi_sqroot = 2.506628274631000502415765284811; //sqrt(two_pi);
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if (is_equal<double_t>(0, o)) {
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return T(std::numeric_limits<double_t>::infinity());
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}
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// g(x) = (1 / o√(2Π)) * e(-(1/2) * ((x-u)/o)²)
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double_t left_e = 1. / (o * two_pi_sqroot);
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double_t mid_right_e = ((x /* - u*/) / o);
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double_t right_e = -0.5 * mid_right_e * mid_right_e;
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double_t final = left_e * exp(right_e);
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return T(final);
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}
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template<typename T>
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inline T lerp(T a, T b, double_t v)
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{
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return static_cast<T>((static_cast<double_t>(a) * (1.0 - v)) + (static_cast<double_t>(b) * v));
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}
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template<typename T>
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class kalman1D {
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T _q_process_noise_covariance;
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T _r_measurement_noise_covariance;
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T _x_value_of_interest;
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T _p_estimation_error_covariance;
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T _k_kalman_gain;
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public:
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kalman1D()
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: _q_process_noise_covariance(0), _r_measurement_noise_covariance(0), _x_value_of_interest(0),
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_p_estimation_error_covariance(0), _k_kalman_gain(0.0)
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{}
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kalman1D(T pnc, T mnc, T eec, T value)
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: _q_process_noise_covariance(pnc), _r_measurement_noise_covariance(mnc), _x_value_of_interest(value),
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_p_estimation_error_covariance(eec), _k_kalman_gain(0.0)
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{}
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~kalman1D() {}
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T filter(T measurement)
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{
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_p_estimation_error_covariance += _q_process_noise_covariance;
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_k_kalman_gain =
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_p_estimation_error_covariance / (_p_estimation_error_covariance + _r_measurement_noise_covariance);
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_x_value_of_interest += _k_kalman_gain * (measurement - _x_value_of_interest);
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_p_estimation_error_covariance = (1 - _k_kalman_gain) * _p_estimation_error_covariance;
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return _x_value_of_interest;
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}
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T get()
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{
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return _x_value_of_interest;
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}
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};
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} // namespace math
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inline std::size_t aligned_offset(std::size_t align, std::size_t pos)
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{
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return ((pos / align) + 1) * align;
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}
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void* malloc_aligned(std::size_t align, std::size_t size);
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void free_aligned(void* mem);
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} // namespace streamfx::util
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