diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..f913d88 --- /dev/null +++ b/.gitignore @@ -0,0 +1,19 @@ +# IDEA files +.idea + +# VsCode files +.vscode + +# CMake files +cmake_install.cmake +CMakeCache.txt +Makefile +CMakeFiles +cmake-build-* +build + +# python files +__pycache__ + +# main output files +output \ No newline at end of file diff --git a/.gitmodules b/.gitmodules new file mode 100644 index 0000000..37aca30 --- /dev/null +++ b/.gitmodules @@ -0,0 +1,3 @@ +[submodule "src/external/matplotplusplus"] + path = examples/external/matplotplusplus + url = https://github.com/alandefreitas/matplotplusplus.git diff --git a/CMakeLists.txt b/CMakeLists.txt new file mode 100644 index 0000000..68814da --- /dev/null +++ b/CMakeLists.txt @@ -0,0 +1,30 @@ +cmake_minimum_required(VERSION 3.22) +project(signal_processing VERSION 1.0.0 LANGUAGES CXX) +set(SIGNAL_PROCESSING_VERSION ${CMAKE_PROJECT_VERSION}) + +set(CMAKE_CXX_STANDARD 11) +set(CMAKE_CXX_STANDARD_REQUIRED ON) + +# C++11 and OpenMP +set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11 -fopenmp") +find_package(OpenMP REQUIRED) + +# Dependencies and src +include_directories(src/external src) + +# Add library to the build +add_subdirectory(src) + +# Optionally add examples +option(BUILD_EXAMPLES "Build example programs" ON) +if(BUILD_EXAMPLES) + # Add examples + add_subdirectory(examples) +endif() + +# Optionally add benchmarks +option(BUILD_BENCHMARKS "Build benchmark programs" ON) +if(BUILD_BENCHMARKS) + # Add benchmarks + add_subdirectory(benchmarks) +endif () diff --git a/CMakePresets.json b/CMakePresets.json new file mode 100644 index 0000000..8392b1a --- /dev/null +++ b/CMakePresets.json @@ -0,0 +1,92 @@ +{ + "version": 3, + "cmakeMinimumRequired": { + "major": 3, + "minor": 22, + "patch": 0 + }, + "configurePresets": [ + { + "name": "base-ninja", + "displayName": "Base Preset using Ninja", + "description": "Base preset for all builds with Ninja generator", + "hidden": true, + "generator": "Ninja", + "binaryDir": "${sourceDir}/build/${presetName}", + "cacheVariables": { + "CMAKE_CXX_STANDARD": "20", + "CMAKE_EXPORT_COMPILE_COMMANDS": "ON" + } + }, + { + "name": "base-make", + "displayName": "Base Preset using Make (Ninja is preferred, consider using it)", + "description": "Base preset for all builds with Make generator", + "hidden": true, + "generator": "Unix Makefiles", + "binaryDir": "${sourceDir}/build/${presetName}", + "cacheVariables": { + "CMAKE_CXX_STANDARD": "20", + "CMAKE_EXPORT_COMPILE_COMMANDS": "ON" + } + }, + { + "name": "ninja-dev-benchmark", + "displayName": "Build the signal processing library with examples and benchmark (required packages: opencv, matplot++, google benchmark)", + "description": "Development build with example programs and benchmark", + "generator": "Ninja", + "binaryDir": "${sourceDir}/build/${presetName}", + "cacheVariables": { + "CMAKE_CXX_STANDARD": "20", + "CMAKE_EXPORT_COMPILE_COMMANDS": "ON", + "CMAKE_BUILD_TYPE": "Release", + "BUILD_EXAMPLES": "OFF", + "BUILD_BENCHMARKS": "ON" + } + }, + { + "name": "ninja-lib", + "displayName": "Build the signal processing library with Ninja (fastest, recommended)", + "inherits": "base-ninja", + "description": "Build only the FFT library in a clean way (no examples)", + "cacheVariables": { + "CMAKE_BUILD_TYPE": "Debug", + "BUILD_EXAMPLES": "OFF", + "BUILD_BENCHMARKS": "OFF" + } + }, + { + "name": "ninja-dev", + "displayName": "Build the signal processing library with examples (required packages: opencv and matplot++)", + "inherits": "base-ninja", + "description": "Development build with example programs", + "cacheVariables": { + "CMAKE_BUILD_TYPE": "Debug", + "BUILD_EXAMPLES": "ON", + "BUILD_BENCHMARKS": "OFF" + } + }, + { + "name": "make-lib", + "displayName": "Build the signal processing library with Make (Ninja is preferred, consider using it)", + "inherits": "base-make", + "description": "Build only the FFT library in a clean way (no examples)", + "cacheVariables": { + "CMAKE_BUILD_TYPE": "Debug", + "BUILD_EXAMPLES": "OFF", + "BUILD_BENCHMARKS": "OFF" + } + }, + { + "name": "make-dev", + "displayName": "Build the signal processing library with examples (Ninja is preferred, consider using it; required packages: opencv and matplot++)", + "inherits": "base-make", + "description": "Development build with example programs", + "cacheVariables": { + "CMAKE_BUILD_TYPE": "Debug", + "BUILD_EXAMPLES": "ON", + "BUILD_BENCHMARKS": "OFF" + } + } + ] +} diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000..6a10ef3 --- /dev/null +++ b/LICENSE @@ -0,0 +1,21 @@ +MIT License + +Copyright (c) 2025 AMSC24-25 + +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. diff --git a/README.md b/README.md index 434327c..d91e28e 100644 --- a/README.md +++ b/README.md @@ -1,2 +1,1327 @@ -# FFT -Fast fourier transform +# Signal Processing + +## Fast Fourier Transform (FFT) - Group 20 + +[![OpenMP](https://img.shields.io/badge/OpenMP-5.2-blue.svg)](https://www.openmp.org/) +[![CMake](https://img.shields.io/badge/CMake-3.22-blue.svg)](https://cmake.org/) +[![C++](https://img.shields.io/badge/C++-%2300599C.svg?logo=c%2B%2B&logoColor=white)](https://en.cppreference.com/w/cpp/11) +[![License](https://img.shields.io/badge/License-MIT-green.svg)](LICENSE) + +### For the impatient + +Only `OpenMP`, `CMake 3.22` and `C++ >= 11` are required to build the library. +- For those who want to use the library: + ```bash + git clone --recursive-submodules https://github.com/AMSC-24-25/20-fft-20-fft.git + # rename folder clone + mv 20-fft-20-fft signal_processing + ``` + You can add the following lines to `CMakeLists.txt`: + ```cmake + # suppose you have cloned the repository into an external folder + add_subdirectory(external/signal_processing) + target_link_libraries(your_executable_name PRIVATE signal_processing) + ``` +- For those who want to run examples or benchmarks: + ```bash + git clone --recursive-submodules https://github.com/AMSC-24-25/20-fft-20-fft.git + # rename folder clone + mv 20-fft-20-fft signal_processing && cd signal_processing + ./build-essentials.sh # to install the dependencies + ./build-examples.sh # to build the examples + ./build-benchmarks.sh # to build the benchmarks + ``` + +--- + +## Table of Contents + +- [Overview](#overview) +- [Getting Started](#getting-started) + - [Prerequisites](#prerequisites) + - [Building with CMake Presets](#building-with-cmake-presets) + - [How to Add `signal_processing` to Your Project](#how-to-add-signal_processing-to-your-project) +- [How to Use the Library](#how-to-use-the-library) + - [Utils](#utils) +- [Description](#description) + - [Fourier Transform and Cooley-Tukey Algorithm](#fourier-transform-and-cooley-tukey-algorithm) + - [Discrete Cosine Transform Type-II (DCT-II) and DCT-III (Inverse DCT)](#discrete-cosine-transform-type-ii-dct-ii-and-dct-iii-inverse-dct) + - [Haar Wavelet Transform (HWT)](#haar-wavelet-transform-hwt) +- [Examples](#examples) + - [Fast Fourier Transform (FFT) and Inverse FFT](#fast-fourier-transform-fft-and-inverse-fft) + - [Haar Wavelet Transform (HWT)](#haar-wavelet-transform-hwt-1) +- [Benchmark](#benchmark) + - [FFT and Inverse FFT Performance](#fft-and-inverse-fft-performance) + - [ThinkPad T430](#thinkpad-t430) + - [HP Pavilion 15-cx0xxx](#hp-pavilion-15-cx0xxx) + - [Dell Inspiron 14 Plus](#dell-inspiron-14-plus) + + +--- + + +## Overview + +The Signal Processing library is a C++ educational project implementing famous transform algorithms. + +The transforms implemented in this repository are: +- The [Fast Fourier Transform (FFT)](#fourier-transform-and-cooley-tukey-algorithm) + and its inverse are both implemented in parallel using the [OpenMP framework][OpenMP] + and in sequential. + The implementation is based on the [Cooley-Tukey algorithm][CK-FFT]. + It **supports N-dimensional signals**, but obviously the signal length must be a power of 2 (radix-2 case). +- The [Discrete Cosine Transform (DCT)](#discrete-cosine-transform-type-ii-dct-ii-and-dct-iii-inverse-dct) + and its inverse are both implemented in parallel using the + [OpenMP framework][OpenMP] and in sequential. + The DCT is implemented as DCT-II (type II), and its inverse is implemented as DCT-III (type III). + It is believed to be used for image compression. +- The [Haar Wavelet Transform (HWT)](#haar-wavelet-transform-hwt) (only sequential). + +Furthermore, the DCT and the HWT are implemented for image compression. + + +--- + + +## Getting Started + +### Prerequisites + +> [!IMPORTANT] +> The library itself has only been tested on Linux. +> It is not guaranteed to work on other operating systems. +> The benchmarks and examples may not work on Windows. + + +Clone the repository: +```bash +git clone --recursive-submodules https://github.com/AMSC-24-25/20-fft-20-fft.git +# rename folder clone +mv 20-fft-20-fft signal_processing +``` +Now you are ready to go. + +However, some prerequisites are very common. +The library is written in C++11 and uses the [OpenMP][OpenMP] framework for parallelization. +In order to use it, you need to have: +- A C++ compiler that supports the C++11 standard. +- Build tools are [CMake](https://cmake.org/) $\ge 3.22$, [Make](https://www.gnu.org/software/make/), + or [Ninja](https://ninja-build.org/) (strongly recommended). +- The [OpenMP](https://www.openmp.org/) framework. + +However, you can run the following script to install the dependencies (**linux only**): +```bash +./build-essentials.sh +``` +Keep in mind that if you are a developer, +you may already have the necessary dependencies installed because +build-essential, CMake, and Ninja are very common packages. + + +> [!NOTE] +> If you have already cloned the repository without the `--recursive` flag, +> you can clone the submodules using the following command (from the repository folder): +> ```bash +> git submodule update --init --recursive +> ``` + + +--- + + +### Building with CMake Presets + +This project uses [CMake Presets](https://cmake.org/cmake/help/latest/manual/cmake-presets.7.html) +to simplify configuration. + +To list available presets: + +```bash +cmake --list-presets +``` + +The recommended way to build the library is to use the `ninja-lib` preset. +This preset only builds the library and uses Ninja as the build system. +Therefore, no examples or benchmarks are built. + +```bash +# assuming you are in the repository folder where the CMakeLists.txt file is located +# create a build directory +mkdir build && cd build +# configure the project using the ninja-lib preset +cmake .. --preset ninja-lib +cd ninja-lib +# build the project +ninja all +``` + +Other useful presets: + +| Preset Name | Description | +|-----------------------|---------------------------------------------------------| +| `ninja-dev` | Build with examples (requires OpenCV and Matplot++) | +| `ninja-dev-benchmark` | Build with benchmarks (requires Google Benchmark too) | +| `make-dev` | Same as `ninja-dev` but uses Makefiles instead of Ninja | +| `make-lib` | Build library only with Makefiles | + +The presets are defined in the [CMakePresets.json](CMakePresets.json) file. +The external libraries required for `ninja-dev`, `ninja-dev-benchmark`, and `make-dev` +can be installed using the corresponding scripts: + +```bash +./build-examples.sh +./build-benchmarks.sh +``` + +These scripts will install the dependencies required for the examples and benchmarks, respectively. +However, they also build the examples and benchmarks. You will find the examples and benchmarks in the build folder. + +> [!WARNING] +> If you are using WSL (Windows Subsystem for Linux), the `sh` scripts may not work due to +> [end-of-line issues](https://en.wikipedia.org/wiki/Newline#Issues_with_different_newline_formats). +> +> This is because Windows uses `CRLF` (Carriage Return + Line Feed) as the end-of-line character, +> whereas Linux uses `LF` (Line Feed) only. +> +> For this reason, we recommend converting the end-of-line characters to Unix format using +> the [following command](https://dos2unix.sourceforge.io/): +> ```bash +> # install dos2unix +> sudo apt update && sudo apt install dos2unix +> # convert all sh scripts to Unix format +> dos2unix clean-all.sh build-*.sh +> ``` + + +--- + + +### How to Add `signal_processing` to Your Project + +If you want to use the library in your own project, you can add the following lines to your `CMakeLists.txt` file: +```cmake +# suppose you have cloned the repository into an external folder +add_subdirectory(external/signal_processing) +target_link_libraries(your_executable_name PRIVATE signal_processing) +``` +It will add the library to your project and link it to your executable. +During the build process, it will also automatically issue a warning if some dependencies are missing. + + +--- + + +## How to Use the Library + +The library is designed to be user-friendly. + +Simply import the main header file, and you're ready to start using it. + +For example, to use the FFT solver, follow these steps: + +```cpp +#include +#include +#include +#include + +#include + +int main() { + // 2D signal, ordered in row-major order + const size_t dims = 2; + const size_t rows = 4; + const size_t cols = 4; + std::vector> rand_signal = { + {1.0, 0.0}, {2.0, 0.0}, {3.0, 0.0}, {4.0, 0.0}, + {5.0, 0.0}, {6.0, 0.0}, {7.0, 0.0}, {8.0, 0.0}, + {9.0, 0.0}, {10.0, 0.0}, {11.0, 0.0}, {12.0, 0.0}, + {13.0, 0.0}, {14.0, 0.0}, {15.0, 0.0}, {16.0, 0.0} + }; + // solver, where dims is the number of dimensions and it is a template parameter + sp::fft::solver::FastFourierTransform solver(std::array{rows, cols}); + // solve in-place (sequential) + solver.compute(rand_signal, sp::fft::solver::ComputationMode::SEQUENTIAL); + // print the result + for (const auto& s : rand_signal) { + printf("(%.2f + %.2fi)", s.real(), s.imag()); + // print a new line every 4 elements using the address of the element + if ((&s - &rand_signal[0] + 1) % 4 == 0) { + printf("\n"); + } else { + printf(", "); + } + } +} +``` + +You can also use the parallel version of the FFT solver: + +```cpp +solver.compute(rand_signal, sp::fft::solver::ComputationMode::OPENMP); +``` + +Or solve the FFT not in-place: + +```cpp +std::vector> result(rand_signal.size()); +// rand_signal will not be modified +solver.compute(rand_signal, result, sp::fft::solver::ComputationMode::SEQUENTIAL); +``` + +To restore the original signal, use the inverse FFT solver: + +```cpp +sp::fft::solver::InverseFastFourierTransform inverse_solver(std::array{rows, cols}); +// solve in-place +inverse_solver.compute(rand_signal, sp::fft::solver::ComputationMode::SEQUENTIAL); +// print the result +for (const auto& s : rand_signal) { + printf("(%.2f + %.2fi)", s.real(), s.imag()); + // print a new line every 4 elements using the address of the element + if ((&s - &rand_signal[0] + 1) % 4 == 0) { + printf("\n"); + } else { + printf(", "); + } +} +``` + +Check the [examples](#examples) section for more examples. + + +### Utils + +The library also provides some utility functions to help you with the signal generation and saving. +- The [signal_generator folder](src/signal_processing/handlers/signal_generator) + contains two classes that generate signals in the time and space domains. +- The [signal_saver folder](src/signal_processing/handlers/signal_saver) + contains a class that saves the generated signal to a CSV file. +- The [config_loader folder](src/signal_processing/handlers/config_loader) + contains a class that loads the configuration from a JSON file. + This class follows the JSON schema defined in the [resources](resources) folder. + > **Example: JSON Configuration File** + > + > ```json + > { + > "signal_domain": "time", + > "signal_length": 2048, + > "hz_frequency": 5, + > "phase": 0, + > "noise": 5 + > } + > ``` + > + > An example of JSON file that describes a signal with the following characteristics: + > - **Signal Domain**: `"time"` - The signal is represented in the time domain. + > - **Signal Length**: `2048` - The duration or length of the signal (number of samples). + > - **Frequency**: `5 Hz` - The frequency of the signal in Hertz (cycles per second). + > - **Phase**: `0` - The phase shift of the signal, which is 0 in this case. + > - **Noise**: `5` - The noise level or amplitude of noise in the signal. + > + > In short, the configuration describes a time domain signal with a frequency of `5 Hz`, + > no phase shift, and an amount of noise (`5`). + + +--- + + +## Description + +### Fourier Transform and Cooley-Tukey Algorithm + +The Fourier transform is a mathematical operation that transforms a function of time (or space) into a function of frequency. +In this library, we implement the Fast Fourier Transform (FFT) algorithm, +and its inverse (IFFT) using the Cooley-Tukey algorithm (Radix-2 case). + +The **Cooley-Tukey algorithm** is a (famous) algorithm for computing the **Fast Fourier Transform (FFT)** efficiently. +It reduces the computational complexity of the **Discrete Fourier Transform (DFT)** from $O(N^2)$ to $O(N \log N)$, +where $N$ is the number of data points. + +Under the hood, the Cooley-Tukey algorithm uses the **divide-and-conquer** strategy. +It recursively breaks a DFT of size $N$ into several smaller DFTs, computes them, and then combines the results. +Precisely, it decomposes a DFT of size $N$ into two smaller DFTs: $N = N_1 \cdot N_2$; +then it reuses the results with **twiddle factors** (complex exponential factors) to combine them: + +$$ +X(k) = \sum_{n=0}^{N-1} x(n) e^{(-2\pi i k n) \div N} = \sum_{m=0}^{N_1-1} X_1(m) W_N^{km} + \sum_{m=0}^{N_2-1} X_2(m) W_N^{km} +$$ + +- $X(k)$ is the $k$-th component of the Discrete Fourier Transform (DFT), representing the frequency domain. +- $\displaystyle\sum_{n=0}^{N-1}$ is the summation over all $N$ input samples. +- $x(n)$ is the $n$-th sample of the input signal in the time (or spatial) domain. +- $e^{(-2\pi i k n) \div N} = \exp((-2\pi i k n) \div N)$ is the complex exponential + (**twiddle factor**) that maps the time-domain signal + to the frequency domain. It introduces a phase shift and scales the input signal. + +When $N$ is a power of 2 ($N = 2^m$), the algorithm becomes very simple and efficient. +And this is the case we implement in this repository. Also called **Radix-2 Cooley-Tukey FFT**. +The algorithm is divided into two main steps: +1. **Bit-reversal permutation**: reorder the input array based on the bit-reversed indices + (see also [Wikipedia][bit-reversal]). +2. **Iteratively compute FFT**: + 1. Start with 2-point DFTs. + 2. Merge results into 4-point DFTs, then 8-point, and so on, up to $N$-point. + +Each stage computes [**butterfly operations**][butterfly], +which involve two elements $a$ and $b$, using a twiddle factor $W\_N^k$. + +Finally, for the **inverse FFT**, the algorithm is similar but with a few differences: +1. The **direction of the twiddle factor** in the inverse FFT is reversed. + +$$ +W_N^{-k} = e^{(2\pi i k) \div N} +$$ + +2. After computing the inverse FFT using Cooley-Tukey, we **normalize the result**. + Each element is divided by $N$, the size of the input. + +$$ +x_n = \frac{1}{N} \sum_{k=0}^{N-1} X_k \cdot e^{(2\pi i kn) \div N} +$$ + +This scaling ensures that the inverse transform truly inverts the original FFT and restores the original signal. + + +> [!WARNING] +> The Cooley-Tukey algorithm implemented in this repository is the **Radix-2** case. +> So the signal length must be a power of 2. + + +--- + + +### Discrete Cosine Transform Type-II (DCT-II) and DCT-III (Inverse DCT) + + +The **Discrete Cosine Transform Type-II (DCT-II)** is the most commonly used variant of the DCT, +particularly in image and video compression (e.g. JPEG). It is defined as: + +$$ +X_k = \alpha_k \sum_{n=0}^{N-1} x_n \cos\left(\dfrac{\pi(2n+1)k}{2N}\right), \quad k = 0, 1, ..., N-1 +$$ + +Where: +- $x_n$: input signal (spatial or time domain) +- $X_k$: DCT coefficient (frequency domain) +- $N$: number of input samples +- $\alpha_k$: normalization factor: + +$$ +\alpha_k = +\begin{cases} +\sqrt{\frac{1}{N}} & \text{if } k = 0 \\ +\sqrt{\frac{2}{N}} & \text{if } k > 0 +\end{cases} +$$ + + +The cosine argument determines the basis functions. It’s the **heart of the transform**: + +- $k$ determines the **frequency** of the cosine wave: higher $k$ means more oscillations. +- $(2n+1)$ causes the cosine to **sample at odd intervals**, + which makes it suitable for even symmetry extension + (fundamental for avoiding boundary discontinuities in signals/images). + + +In other words, the DCT basis functions are cosine waves of increasing frequency. + + +The summation is an **inner product** between the input signal and the cosine basis function of frequency $k$. +It measures "how much of that frequency" is present in the signal. + + +Finally, the **normalization factor** $\alpha_k$ ensures **energy preservation** and +makes the transform **orthonormal**: + +- $\alpha_0 = \sqrt{\frac{1}{N}}$ gives the DC term (average value) less weight. +- $\alpha_k = \sqrt{\frac{2}{N}}$ for $k > 0$ keeps other frequencies properly scaled. + + +Finally, the **DCT-III**, which is the inverse of the DCT-II, is defined as: + +$$ +x_n = \sum_{k=0}^{N-1} \alpha_k X_k \cos\left[\frac{\pi(2n+1)k}{2N}\right] +$$ + + +In general, the DCT is used for compression because it focuses the signal's energy into a few coefficients. +This allows for efficient representation and storage. +In this library, we use DCT-II and DCT-III for image compression. +These methods are supported by [quantization][quantization], [zigzag scanning][zigzag], and [RLE encoding][rle] +(unfortunately [Huffman encoding][Huffman] is not implemented yet). + + +--- + + +### Haar Wavelet Transform (HWT) + +The **1D Haar Wavelet Transform** (HWT) is one of the simplest wavelet transforms. +It is very useful for signal compression (our goal), denoising, and multi-resolution analysis. + +The Haar transform converts a sequence of values into **averages and differences**, +capturing both **low-frequency (smooth)** and **high-frequency (detail)** information. + +The 1D Haar transform is defined as follows. Given an input vector: + +$$ +x = [x_0, x_1, x_2, x_3, \dots, x_{N-2}, x_{N-1}] +$$ + +The transform produces two outputs: +1. **Averages** (_low_-frequency content): + +$$ +a_i = \frac{x_{2i} + x_{2i+1}}{\sqrt{2}} +$$ + +2. **Details** (_high_-frequency content): + +$$ +d_i = \frac{x_{2i} - x_{2i+1}}{\sqrt{2}} +$$ + + +> [!TIP] +> For example, for $x = [4, 6, 10, 12]$: +> +> $$ +\begin{aligned} +a_0 &= \frac{4 + 6}{\sqrt{2}} = \frac{10}{\sqrt{2}} \\ +a_1 &= \frac{10 + 12}{\sqrt{2}} = \frac{22}{\sqrt{2}} \\ +d_0 &= \frac{4 - 6}{\sqrt{2}} = \frac{-2}{\sqrt{2}} \\ +d_1 &= \frac{10 - 12}{\sqrt{2}} = \frac{-2}{\sqrt{2}} \\ +\end{aligned} +$$ +> +> So the Haar transform of `x` is: +> +> $$ +\text{HWT}(x) = [a_0, a_1, d_0, d_1] = \left[\frac{10}{\sqrt{2}}, \frac{22}{\sqrt{2}}, \frac{-2}{\sqrt{2}}, \frac{-2}{\sqrt{2}}\right] +$$ + +Our implementation is a multilevel Haar transform, which means it is recursive. +We apply the transform to the **average coefficients only**, creating a **pyramid of resolutions**. +This is known as the **Haar wavelet decomposition**, and it outputs are: +* low-frequency coefficients (averages) +* high-frequency coefficients (details) + + +> [!TIP] +> Taking in account the example above, the first level of the Haar transform (level 1) gives: +> +> $$ +[\underbrace{a_0, a_1}\_{\text{averages}}, \underbrace{d_0, d_1}\_{\text{details}}] = \left[\frac{10}{\sqrt{2}}, \frac{22}{\sqrt{2}}, \frac{-2}{\sqrt{2}}, \frac{-2}{\sqrt{2}}\right] +$$ +> +> Then, you can apply the Haar transform again on the averages from level 1: +> +> $$ +\left[\frac{10}{\sqrt{2}}, \frac{22}{\sqrt{2}}\right] +$$ +> +> Again, compute average and detail (level 2): +> +> $$ +\begin{aligned} +a_{00} &= \frac{\frac{10}{\sqrt{2}} + \frac{22}{\sqrt{2}}}{\sqrt{2}} = \frac{32}{2} = 16 \\ +d_{00} &= \frac{\frac{10}{\sqrt{2}} - \frac{22}{\sqrt{2}}}{\sqrt{2}} = \frac{-12}{2} = -6 +\end{aligned} +$$ +> +> After **2 levels**, we get: +> +> $$ +[\underbrace{a_{00}}\_{\text{lowest frequency}}, \underbrace{d_{00}}\_{\text{medium detail}}, \underbrace{d_0, d_1}\_{\text{finest details}}] = [16, -6, -\frac{2}{\sqrt{2}}, -\frac{2}{\sqrt{2}}] +$$ +> +> Where $a_{00}$ is the overall average of the signal (very low frequency), +> $d_{00}$ is the change between the first and second halves of the signal (medium detail), +> and $d_0, d_1$ are the local fluctuations (finest details, highest frequencies). +> ```text +> Level 2: a00 <-- 1 value (most compressed) +> / \ +> Level 1: a0 a1 <-- 2 values +> / \ / \ +> Input: x0 x1 x2 x3 <-- 4 values +> ``` + +The **2D Haar Wavelet Transform** is essentially just the 1D version applied twice: first across rows, +then across columns. +Given a 2D matrix (e.g., a grayscale image), we apply the **1D Haar transform** to: + +1. Each **row**; +2. Then each **column** of the result. + +This gives a decomposition of the image into components that describe **different frequency orientations**. +Finally, we apply the multilevel Haar transform recursively on each block to get a compressed representation. + +> [!TIP] +> For example, suppose we have a 4x4 matrix $A$: +> +> $$ +A = \begin{bmatrix} +4 & 6 & 10 & 12 \\ +4 & 6 & 10 & 12 \\ +8 & 10 & 14 & 16 \\ +8 & 10 & 14 & 16 +\end{bmatrix} +$$ +> +> We apply the 1D Haar transform to each row: +> +> $$ +\begin{bmatrix} +\frac{4+6}{\sqrt{2}} & \frac{10+12}{\sqrt{2}} & \frac{4-6}{\sqrt{2}} & \frac{10-12}{\sqrt{2}} \\ +\frac{4+6}{\sqrt{2}} & \frac{10+12}{\sqrt{2}} & \frac{4-6}{\sqrt{2}} & \frac{10-12}{\sqrt{2}} \\ +\frac{8+10}{\sqrt{2}} & \frac{14+16}{\sqrt{2}} & \frac{8-10}{\sqrt{2}} & \frac{14-16}{\sqrt{2}} \\ +\frac{8+10}{\sqrt{2}} & \frac{14+16}{\sqrt{2}} & \frac{8-10}{\sqrt{2}} & \frac{14-16}{\sqrt{2}} +\end{bmatrix} +$$ +> +> This gives us a new matrix with: +> +> - Left half: row averages +> - Right half: row details +> +> Now we take this result and apply the 1D Haar transform to each column. +> This gives us a final matrix divided into **four blocks**: +> ```text +> [ LL | HL ] +> [----+----] +> [ LH | HH ] +> ``` +> Where: +> - `LL`: low frequency in both directions (**approximation**). +> - `HL`: high frequency in rows, low in columns (**horizontal details**). +> - `LH`: low frequency in rows, high in columns (**vertical details**). +> - `HH`: high frequency in both directions (**diagonal details**). + + +--- + + +## Examples + + +The examples are located in the [examples](examples) folder. +To build the examples, run the following command: + +```bash +./build-examples.sh +``` + +The examples need the following dependencies: +- [OpenCV](https://opencv.org/) (for image processing) +- [Matplot++](https://alandefreitas.github.io/matplotplusplus/) (for plotting) + +### Fast Fourier Transform (FFT) and Inverse FFT + +The FFT examples are: +- [fourier_transform_solver](examples/fourier_transform_solver.cpp) + is the simplest one that shows **how to use the FFT solver with a one-dimensional (1D) signal**. + + It generates a random signal using a JSON configuration file. + It computes the FFT and IFFT in parallel and sequentially. + It saves each result in a CSV file and plots the results using Matplot++ + to demonstrate the difference between the FFT and IFFT. + FFT Example +- [fourier_transform_solver_image](examples/fourier_transform_solver_image.cpp) + is an example that shows **how to use the FFT solver with a two-dimensional (2D) signal**. + + This time, instead of generating a random signal, + we will demonstrate how to load an RGB image from a file and apply the FFT to it. + The results show that the FFT implementation can handle two-dimensional (2D) signals. + We verified its correctness by comparing the results with the original image. + + + + + + + + + + +
Original Image (2048 x 2048)Image after FFT and IFFT (2048 x 2048)
Original ImageImage after FFT and IFFT
+- [fourier_transform_solver_performance](examples/fourier_transform_solver_performance.cpp) + is a simple example that demonstrates the performance of the FFT and inverse FFT algorithms. + + Run it to see the performance of the FFT and inverse FFT algorithms. + It generates a random signal with 8,388,608 (8 million) samples and computes the FFT and inverse FFT. +- [fourier_transform_solver_video](examples/fourier_transform_solver_video.cpp) + shows how the FFT solver works well with 3D signals, too. + + It uses the OpenCV library to read a video file and apply the FFT to each frame. + The input video is RGB, and the output is grayscale. This avoids a long processing time. + + The example video has a resolution of 512 x 1024 and contains 266 frames at 60 fps. + Since the FFT algorithm is designed to work with signals that are powers of two, + the video is cropped to 256 frames. + These frames are reshaped into a 3D signal with dimensions of 512 x 1024 x 256 (134,217,728 samples, or 134 million). + + Note: The converted video on GitHub was compressed to reduce its size. + The original video is available here: [cats_fft_ifft.mp4](docs/_static/cats_fft_ifft.mp4). + + + + + + + + + + +
Original Video (266 frames x 512 x 1024)Video after FFT and IFFT (256 frames x 512 x 1024)
+- [fourier_transform_solver_video_rgb](examples/fourier_transform_solver_video_rgb.cpp) + is similar to the previous one, but it uses the RGB color space instead of grayscale. + + The FFT is applied to each frame of the video, and the result is saved as a new video file. + + The input and output videos are both RGB. + The example video has a resolution of 512 x 1024 and contains 266 frames at 60 fps. + Since the FFT algorithm is designed to work with powers of two, the video is cropped to 256 frames. + The frames are then reshaped into a 3D signal with dimensions of 512 x 1024 x 256 + (134,217,728 samples, or approximately 134 million). + + Note: The converted video on GitHub was compressed to reduce its size. + The original video is available here: [cats_fft_ifft-rgb.mp4](docs/_static/cats_fft_ifft-rgb.mp4). + + + + + + + + + + +
Original Video (266 frames x 512 x 1024)Video after FFT and IFFT (256 frames x 512 x 1024)
+ + +--- + + +### Haar Wavelet Transform (HWT) + +The Haar Wavelet Transform (HWT) examples are: +- [haar_wavelet_transform_1d](examples/haar_wavelet_transform_1d.cpp) + is a simple example that shows how to use the Haar wavelet transform (HWT) solver with a one-dimensional signal. + + A similar example is [haar_wavelet_transform_2d](examples/haar_wavelet_transform_2d.cpp). + This example shows how to use the HWT solver with a two-dimensional (2D) signal. + + Both examples generate a random signal and print the original signal, compute the HWT, and print the result. +- [haar_wavelet_transform](examples/haar_wavelet_transform.cpp) + is an example that shows how the HWT solver works with a two-dimensional (2D) signal, in this case an image. + + It loads a grayscale image from a file and applies the HWT to it to compress the image. + Finally, it restores the original image using the inverse HWT and saves it to a file. + With different levels of compression, the image quality is preserved. + + Compression is modified by adjusting the threshold for detail coefficients. + This threshold determines which coefficients in the Haar wavelet transform are set to zero during compression. + - A higher threshold removes more coefficients, resulting in greater compression and loss of detail in the image. + This can degrade the quality of the reconstructed image. + - A lower threshold retains more coefficients, preserving more detail but reducing the compression ratio. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Original Image (2048 x 2048, 3.17 MB)
Original Image
Reconstructed ImageHaar Wavelet domain
Threshold = 7.5, 170.17 KB, size reduced by ~95%Threshold = 7.5, 78.81 KB
dog-7.5dog-7.5
Threshold = 5, 392.33 KB, size reduced by ~88%Threshold = 5, 161.2 KB
dog-5dog-5
Threshold = 3, 923.82 KB, size reduced by ~72%Threshold = 3, 396.61 KB
dog-3dog-3
Threshold = 2, 1.48 MB, size reduced by ~53%Threshold = 2, 682.06 KB
dog-2dog-2
Threshold = 1, 2.37 MB, size reduced by ~25%Threshold = 1, 1.26 MB
dog-1dog-1
Threshold = 0.5, 2.96 MB, size reduced by ~7%Threshold = 0.5, 1.35 MB
dog-0.5dog-0.5
+ + +--- + + +## Benchmark + +### FFT and Inverse FFT Performance + +We conducted a comprehensive set of benchmarks to evaluate the performance and scalability of our +Fast Fourier Transform (FFT) implementation. +These benchmarks cover 1D, 2D, and 3D FFTs and compare sequential and parallel (OpenMP) +computation modes. + +- We generated random input signals of various sizes to ensure that the total number of elements + was always a power of two, as required by the radix-2 Cooley-Tukey FFT. +- We tested a wide range of input shapes for each dimension, from small to very large, + to assess performance at both small and large scales. + + Using a [backtracking approach](https://en.wikipedia.org/wiki/Backtracking#Description_of_the_method), + we generated input shapes and benchmarked all possible combinations of sizes + for each dimension that were less than or equal to 8,388,608 $\left(2^{23}\right)$ elements. +- Each benchmark was run in both sequential and OpenMP parallel modes with different thread counts to measure parallel speedup and efficiency. +- The benchmarks were executed using the [Google Benchmark framework](https://github.com/google/benchmark), + which provides reliable and statistically sound timing results. + +#### ThinkPad T430 + +We benchmarked the performance of our FFT implementation on a Lenovo ThinkPad T430: +- **CPU**: Intel(R) Core(TM) i7-3632QM CPU @ 2.20GHz + - Thread(s) per core: 2 + - Core(s) per socket: 4 + - Socket(s): 1 + - Stepping: 9 + - CPU(s) scaling MHz: 56% + - CPU max MHz: 3200.0000 + - CPU min MHz: 1200.0000 + - Caches (sum of all): + - L1d: 128 KiB (4 instances) + - L1i: 128 KiB (4 instances) + - L2: 1 MiB (4 instances) + - L3: 6 MiB (1 instance) +- **RAM**: 2 x 8 GB DDR3 1600 MHz +- **OS**: Ubuntu 24.04 LTS + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
1D FFT Speedup
1D FFT Speedup
+
    +
  • 2 threads: Modest speedup, peaks around 1.6x for large sizes ($\log_{2}(N) \ge 18$). Consistent scaling with increasing input.
  • +
  • 4 threads: Speedup exceeds 2x from $\log_{2}(N) \approx 16$. Flatter scaling curve after that, reaching a maximum around 2.2x.
  • +
  • 8 threads: Achieves the highest speedup (up to 2.75x) but is less stable. Sharp drop at $\log_{2}(N) = 14$ suggests overhead or thread contention. Gains taper off, indicating limited scalability beyond this point.
  • +
+ Speedup improves with input size for all thread counts. 8 threads offer the best speedup, but not proportionally to thread count. + Scaling is sublinear due to overhead, synchronization, and possibly thermal or hardware constraints. +
1D FFT Efficiency
1D FFT Efficiency
+
    +
  • 2 threads perform best, reaching up to 80% efficiency for large input sizes ($\log_{2}(N) \ge 17$).
  • +
  • 4 threads show moderate scaling, peaking near 55%, but efficiency drops slightly at higher sizes.
  • +
  • 8 threads have poor efficiency (max ~35%), likely due to overhead, thread contention, or hyperthreading limits.
  • +
+ Efficiency improves with input size but saturates beyond a point. + More threads don’t always mean better performance, overhead dominates with 8 threads. + Optimal thread count depends on input size; 2–4 threads offer the best trade-off on Intel i7-3632QM. +
2D FFT Speedup
2D FFT Speedup
+ For small inputs ($\log_{2}(N) < 12$), all configurations show low speedup (<1x), parallelization overhead dominates. + Speedup increases with input size, especially from $\log_{2}(N) \approx 13$. +
    +
  • 2 threads show modest speedup, maxing at ~1.1x.
  • +
  • 4 threads achieve up to 1.85x, with more stable results than 8 threads.
  • +
  • 8 threads yield the highest speedup, reaching over 2.1x, but with large variance (visible via error bars).
  • +
+ 2D FFT benefits more from parallelization at large sizes, but scaling remains sublinear. + High variance for 8 threads suggests non-determinism, possibly from memory bandwidth saturation or thread scheduling variability. + Optimal thread count depends on balancing speedup gains against stability and resource contention. +
2D FFT Efficiency
2D FFT Efficiency
+ Efficiency is low for small inputs ($\log_{2}(N) < 12$) due to high overhead relative to workload. + It steadily increases with input size across all thread counts. +
    +
  • 2 threads maintain the highest efficiency throughout, reaching ~55% at the largest sizes.
  • +
  • 4 threads follow closely, approaching ~45%.
  • +
  • 8 threads lag behind, peaking at only ~25%, with wider variance.
  • +
+ Parallelization becomes worthwhile for larger 2D FFTs. + Efficiency decreases with more threads, reflecting increased overhead and possible memory bottlenecks. + For this hardware (Thinkpad T430), 2-4 threads offer a better efficiency-to-cost ratio than 8 threads. +
3D FFT Speedup
3D FFT Speedup
+ Speedup is consistently below 1x for small inputs ($\log_{2}(N) < 17$), indicating parallel overhead dominates. +
    +
  • 2 threads scale slowly, maxing at ~0.5x.
  • +
  • 4 threads achieve a moderate peak of ~0.9x.
  • +
  • 8 threads reach the highest speedup (~1.1x) at large sizes, but with high variance.
  • +
+ 3D FFT is the hardest to parallelize efficiently on this hardware. + Even at large sizes, speedup remains limited, possibly due to a combination of factors: +
    +
  • Increased computational complexity of 3D FFTs.
  • +
  • Memory bandwidth limitations.
  • +
  • Overhead from managing more threads.
  • +
+ Parallelization is beneficial only for large volumes, and even then, gains are modest. +
3D FFT Efficiency
3D FFT Efficiency
+ Efficiency is very low across all thread counts, especially for small input sizes ($\log_{2}(N) < 16$), + where it stays below 10%. Only at larger sizes ($\log_{2}(N) \ge 20$), + 2 and 4 threads gradually reach ~25–35% efficiency; 8 threads consistently underperform, peaking at ~15%. + Furthermore, error bars suggest significant variability, especially with more threads.

+ 3D FFTs are the least efficient to parallelize in this benchmark. + The complex memory access patterns and increased communication overhead likely degrade performance. + Efficiency grows with size, but remains far from ideal. + For this workload and hardware, using 2-4 threads is more effective, while 8 threads yield diminishing returns. +
+ +To conclude, the benchmarks demonstrate that: +- 1D FFT is the most parallel-friendly on this Intel i7-3632QM, + showing strong speedup and high efficiency, especially with 2-4 threads. +- 2D FFT gains from parallelism for larger inputs, but memory usage and thread overhead limit its full potential. +- 3D FFT suffers from poor cache locality and higher overhead, + making it the least efficient and least scalable among the three. + + +--- + + +#### HP Pavilion 15-cx0xxx + +We benchmarked the performance of our FFT implementation on an HP Pavilion 15-cx0xxx: +- **CPU**: Intel(R) Core(TM) i7-8750H CPU @ 2.20GHz + - Thread(s) per core: 2 + - Core(s) per socket: 6 + - Socket(s): 1 + - Stepping: 10 + - CPU(s) scaling MHz: 40% + - CPU max MHz: 4100.0000 + - CPU min MHz: 800.0000 + - Caches (sum of all): + - L1d: 192 KiB (6 instances) + - L1i: 192 KiB (6 instances) + - L2: 1.5 MiB (6 instances) + - L3: 9 MiB (1 instance) +- **RAM**: 2 x 8 GB DDR4 2667 MHz +- **OS**: Ubuntu 24.04 LTS + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
1D FFT Speedup
1D FFT Speedup
+
    +
  • 2 threads: consistent growth, saturates around 1.55x, good baseline performance.
  • +
  • 4 threads: achieves the best overall speedup, peaking just above 2.1x, with solid early scaling.
  • +
  • 8 threads: slightly trails 4 threads; maxes around 2.1-2.2x, then flattens, + possibly hitting memory or cache bottlenecks.
  • +
  • 12 threads: lags behind all others at small sizes, starts catching up only after $\log_{2}(N) \ge 16$, + and finally approaches 2x.
  • +
+ The i7-8750H scales best with 4–8 threads for 1D FFT workloads. + 12 threads underperform due to hyperthreading limitations, physical cores are likely saturated beyond 6 threads. + Parallel overhead is more significant at small input sizes, especially with higher thread counts. +
1D FFT Efficiency
1D FFT Efficiency
+
    +
  • 2 threads perform best, reaching up to ~78% efficiency, and maintaining it across large inputs.
  • +
  • 4 threads achieve good efficiency (~53% max), with consistent scaling after $\log_{2}(N) \approx 12$.
  • +
  • 8 threads stay below 30% efficiency, suggesting increasing overhead and resource contention.
  • +
  • 12 threads peak at ~18%, showing the weakest efficiency due to hyperthreading saturation and memory bottlenecks.
  • +
+ This 6-core/12-thread CPU handles 1D FFTs most efficiently at 2-4 threads. + Beyond 6 threads, efficiency drops sharply due to shared core resources and diminishing returns. + Overall, efficiency trends are similar to the ThinkPad results, + but this CPU handles higher thread counts slightly better, thanks to higher core/thread availability. +
2D FFT Speedup
2D FFT Speedup
+ All configurations show increasing speedup with input size, starting around $\log_{2}(N) \approx 10$. +
    +
  • 2 threads scale gradually, maxing at ~0.95x.
  • +
  • 8 threads and 4 threads scale more stably, peaking near 1.8x and 1.55x, respectively.
  • +
  • 12 threads outperform other configurations at large sizes, reaching up to ~2x speedup, but with large variance.
  • +
+ 12 threads perform well for large 2D FFTs, + but variability increases due to likely cache pressure, memory contention, or thread migration. + 8 threads appear to be a sweet spot between speedup and stability. + Scaling is sublinear, typical of 2D workloads, but overall better than on the ThinkPad. +
2D FFT Efficiency
2D FFT Efficiency
+ Efficiency grows steadily with input size across all thread counts. +
    +
  • 2 threads achieve the highest efficiency (~0.5-0.7 at large sizes), with low variance.
  • +
  • 4 threads also scale well, reaching ~0.6 efficiency, though with more variability.
  • +
  • 8 threads and especially 12 threads have significantly lower efficiency (max ~0.25 and ~0.17, respectively), + reflecting diminishing returns from oversubscription. + Oversubscription occurs when the number of active threads in a process + exceeds the number of available logical cores in the system. + In other words, + adding more threads provides diminishing returns and may even harm performance beyond a certain point.
  • +
+ Higher thread counts introduce greater variability, likely from contention in memory access and shared hardware resources. +

+ Best efficiency is achieved using 2-4 threads. + Efficiency drops substantially with 8 or more threads, + suggesting parallel overhead outweighs benefits on this CPU beyond 6 physical cores. +

+ Compared to the ThinkPad, this system scales better with more threads, + but still struggles to maintain high efficiency at 12 threads. +
3D FFT Speedup
3D FFT Speedup
+ Speedup increases consistently with input size, but remains modest overall. +
    +
  • 2 threads exhibit the lowest speedup (max ~0.35x), showing limited benefit from parallelization.
  • +
  • 8 and 4 threads scale more gradually, peaking at ~0.65x and ~0.58x, respectively.
  • +
  • 12 threads perform best for large inputs, reaching ~0.85x speedup, but with high variability.
  • +
+ 3D FFT remains challenging to parallelize efficiently on this CPU. + The CPU scales better than the ThinkPad, especially at higher thread counts, + but still doesn’t exceed 1x speedup, meaning parallelization hasn’t yet outperformed sequential execution. +
3D FFT Efficiency
3D FFT Efficiency
+ Efficiency is low across all thread counts, even for large inputs. +
    +
  • 2 threads provide the highest efficiency, gradually rising to ~18% at $\log_{2}(N) = 23$.
  • +
  • 4 and 8 threads follow with efficiency peaking at ~15% and 10%, respectively.
  • +
  • 12 threads perform the worst, peaking at ~7% efficiency, a clear sign of oversubscription and poor scalability.
  • +
+ Growth is linear but slow, and none of the configurations exceed 20% efficiency. + 3D FFT is extremely inefficient to parallelize on this CPU under OpenMP. + Best results are achieved with fewer threads, confirming that hyperthreading and high parallelism do not help for this workload. +
+ +In conclusion, the CPU scales well with 4 to 8 threads, depending on the dimensionality of the FFT. +However, 12 threads (via Hyper-Threading) yield diminishing returns, often increasing variance and lowering efficiency. +However, efficiency consistently improves with input size but never reaches ideal (100%) scaling, +especially in higher-dimensional FFTs. + +Compared to the ThinkPad T430, the HP Pavilion 15-cx0xxx has a higher raw speed, +especially for larger input sizes and 1D/2D FFTs. +However, the ThinkPad is more efficient at low thread counts, while the HP offers higher parallel capacity. +Finally, both devices remain inefficient with 3D FFTs, though the HP handles it slightly better. + + +--- + + +#### Dell Inspiron 14 Plus + +We benchmarked the performance of our FFT implementation on a Dell Inspiron 14 Plus: +- **CPU**: Intel(R) Core(TM) Ultra 7 155H CPU @ 1.40GHz (up to 4.80 GHz) + - Thread(s) per core: 2 + - Core(s) per socket: 11 + - Socket(s): 1 + - Stepping: 4 + - CPU max MHz: 4800.0000 + - CPU min MHz: 700.0000 + - Caches (sum of all): + - L1d: 528 KiB (11 instances) + - L1i: 704 KiB (11 instances) + - L2: 22 MiB (11 instances) + - L3: 24 MiB (1 instance) +- **RAM**: 2 x 16 GB [LPDDR5X](https://semiconductor.samsung.com/dram/lpddr/lpddr5x/) 6.400 MT/s integrated memory +- **OS**: Windows 11 with WSL2 (Ubuntu 24.04 LTS) + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
1D FFT Speedup
1D FFT Speedup
+ Nearly 3.9x with 16 threads at the largest input sizes, very high speedup. +
    +
  • 2-8 threads show strong and consistent speedup curves, with 8 threads peaking ~3.6x, + indicating very effective utilization of physical cores.
  • +
  • 16 threads start slow but scale rapidly, overtaking 8 threads at large sizes.
  • +
  • 22 threads perform poorly on small inputs, but improve significantly at the end, reaching ~1.6x speedup, + still much lower than 16 threads.
  • +
+ All configurations suffer from low speedup below $\log_{2}(N) = 13$, + typical of small workloads being dominated by overhead. +

+ As expected, the Ultra 7 155H demonstrates impressive scalability, particularly with 8-16 threads. + This likely corresponds to its performance and efficiency core hybrid layout. + This CPU demonstrates real parallel potential with large FFT workloads. + This is perhaps also expected given the high number of physical cores (11) and large L3 cache (24 MiB). +
1D FFT Efficiency
1D FFT Efficiency
+
    +
  • 2 threads achieve exceptional efficiency, peaking at ~92%, near-perfect scaling.
  • +
  • 4 threads follow with a strong peak of ~73%, indicating very good per-core utilization.
  • +
  • 8 threads maintain decent scaling, reaching ~47% efficiency.
  • +
  • 16 threads drop to around 27%, still respectable given how far it’s stretching the thread pool.
  • +
  • 22 threads show very low efficiency (<10%), confirming oversubscription and SMT (Simultaneous Multi-Threading) overhead.
  • +
+ The efficiency increases gradually with input size across all thread counts, + as larger workloads help amortize overhead. + This CPU exhibits exceptional scaling up to 4-8 threads. +
2D FFT Speedup
2D FFT Speedup
+ Error bars indicate increased variability at higher thread counts (especially 22T), + likely due to scheduling complexity, memory contention, and thread imbalance. +
    +
  • 2 threads perform modestly, maxing near 1.4x, consistent with Thinkpad/HP FFT benchmarks.
  • +
  • 4 threads are solid but limited, peaking at ~2.7x, with little gain beyond mid-sized inputs.
  • +
  • 8 threads scale well, achieving ~3.6x speedup with good stability.
  • +
  • 16 threads consistently provide the highest speedup, peaking at ~5.0x on large input sizes.
  • +
  • 22 threads start slowly but ramp up very rapidly from $\log_{2}(N) = 18$, + eventually approaching 5.4x, the highest speedup recorded here.
  • +
+ This CPU handles large 2D FFTs extremely well, especially with 16-22 threads. + 22 threads, despite low early performance, scale aggressively for large inputs, + suitable for throughput-intensive batch processing. + However, variability and efficiency loss at high thread counts means 16 threads might be a safer + balance between performance and stability for most workloads. +
2D FFT Efficiency
2D FFT Efficiency
+ Across all thread counts, efficiency steadily increases with input size, as expected. +
    +
  • 2 threads and 4 threads show very high efficiency, peaking around: ~77% for 2 threads, + ~100% for 4 threads at the largest input size (possibly benefiting from L3 cache and thread affinity).
  • +
  • 8 threads also perform well, reaching ~60% efficiency, excellent for this level of parallelism.
  • +
  • 16 threads top out at ~32%, which is still reasonable given the total core count.
  • +
  • 22 threads peak at ~20%, but with noticeable variance, + suggesting oversubscription and scheduler-induced instability.
  • +
+ The CPU demonstrates outstanding scaling and resource utilization for 2D FFTs, especially up to 8 threads. + Thread efficiency remains strong up to 16 threads, + validating the strength of the hybrid architecture and large L3 cache. + 22 threads should be reserved for massive workloads where raw speedup is more important than efficiency. + As previous benchmarks have shown, + few CPUs in the laptop class achieve this level of 2D FFT efficiency with low or medium thread counts. +
3D FFT Speedup
3D FFT Speedup
+ All configurations show steady improvement with input size, crucial for workloads with significant data volume. + High thread counts (16T, 22T) begin to pay off only after $\log_{2}(N) \ge 18$, + where the computation-to-overhead ratio becomes favorable. +
    +
  • 4 threads and 2 threads offer moderate gains, peaking at ~1.6x and 0.9x, respectively.
  • +
  • 8 threads perform solidly, reaching ~2.4x speedup at large input sizes.
  • +
  • 16 threads show the strongest and most consistent scaling, peaking at ~3.3x speedup at $\log_{2}(N) \approx 23$.
  • +
  • 22 threads start slow but scale aggressively, reaching nearly 3.5x, the highest recorded in this 3D benchmark.
  • +
+ The Ultra 7 155H demonstrates excellent scalability even in 3D FFTs, traditionally the most difficult to parallelize. + 16 threads appear to offer the best performance/stability trade-off. + Finally, 22 threads are viable for very large inputs where raw throughput is critical, + though they bring higher variance due to contention, synchronization, and core heterogeneity. +
3D FFT Efficiency
3D FFT Efficiency
+ Efficiency is modest overall, as expected for 3D FFTs, which are the hardest to scale. +
    +
  • 2 threads peak at ~45% efficiency, the best among all thread counts.
  • +
  • 4 threads follow closely, approaching ~43%, showing great scaling at low concurrency.
  • +
  • 8 threads max out at ~28%, while 16 threads settle around 17%, and 22 threads remain low (~13%) even at the largest input sizes.
  • +
+ While speedup results were excellent, the efficiency plot highlights diminishing returns as threads increase. +
+ +This hardware demonstrates excellent scaling, particularly for 1D and 2D FFTs. It even achieved strong 3D FFT throughput. +The best results are obtained with 8 to 16 threads, where a balance between raw speed and stability is maintained. +Using 22 threads provides a significant speed boost for very large data sets, but it results in diminished per-thread +efficiency and increased variability. + +In conclusion, **Dell leads in scalability and peak performance**, HP offers a balanced middle ground, and the ThinkPad, +though limited in raw computing power, excels at small, efficient workloads. +Each system demonstrates the direct impact of core count, cache size, and architectural design on the success +of FFT parallelization. + +#### Reflections on the FFT Algorithm + +- ✅ **Highly scalable in 1D**: + The Cooley-Tukey radix-2 algorithm used here parallelizes well in 1D. + With proper workload size and cache locality, it can achieve near-linear speedup, + particularly when each thread has sufficient independent work to avoid contention. + +- ❌ **Diminishing returns with thread count**: + As thread count grows beyond physical cores, **synchronization**, **false sharing**, and **cache thrashing** + begin to erode efficiency, particularly visible in 3D FFTs and with 22-thread runs. + +- ❌ **3D FFTs are much harder to scale**: + The increase in data dimensionality introduces more complex memory access and greater working set sizes. + +- ❌ **Sequential bottlenecks remain**: + Some stages inherently require coordination or are not fully parallelizable with "simple" loop-level OpenMP. + + +The FFT algorithm itself is **inherently parallel**, especially in its **divide-and-conquer form** like Cooley-Tukey. +However, the **real-world scalability** depends heavily on: input size, dimensionality, hardware cache structure, +and the balance between thread granularity and workload size. + + +[OpenMP]: https://www.openmp.org/ +[CK-FFT]: https://en.wikipedia.org/wiki/Cooley%E2%80%93Tukey_FFT_algorithm +[bit-reversal]: https://en.wikipedia.org/wiki/Bit-reversal_permutation +[butterfly]: https://en.wikipedia.org/wiki/Butterfly_diagram +[quantization]: https://en.wikipedia.org/wiki/Quantization_(image_processing) +[zigzag]: https://en.wikipedia.org/wiki/Color_layout_descriptor#Zigzag_scanning +[rle]: https://en.wikipedia.org/wiki/Run-length_encoding +[Huffman]: https://en.wikipedia.org/wiki/Huffman_coding \ No newline at end of file diff --git a/benchmarks/CMakeLists.txt b/benchmarks/CMakeLists.txt new file mode 100644 index 0000000..cf5b408 --- /dev/null +++ b/benchmarks/CMakeLists.txt @@ -0,0 +1,15 @@ +if (NOT BUILD_BENCHMARKS) + message(STATUS "Google Benchmark not found: benchmarks will not be built") + return() +endif () + +find_package(benchmark REQUIRED) +if (NOT benchmark_FOUND) + message( + FATAL_ERROR + "Google Benchmark not found. Please install it following the instructions at " + "https://github.com/google/benchmark?tab=readme-ov-file#installation" + ) +endif () + +add_subdirectory(fourier_transform) diff --git a/benchmarks/fourier_transform/CMakeLists.txt b/benchmarks/fourier_transform/CMakeLists.txt new file mode 100644 index 0000000..0c25b6a --- /dev/null +++ b/benchmarks/fourier_transform/CMakeLists.txt @@ -0,0 +1,10 @@ +add_executable( + benchmark-fourier_transform + fourier_transform.cpp + utils.hpp +) +target_link_libraries( + benchmark-fourier_transform + PRIVATE benchmark::benchmark + PRIVATE signal_processing +) diff --git a/benchmarks/fourier_transform/dell.py b/benchmarks/fourier_transform/dell.py new file mode 100644 index 0000000..4d2583d --- /dev/null +++ b/benchmarks/fourier_transform/dell.py @@ -0,0 +1,348 @@ +from plot_performance import * + + +_specs = "(Dell, Intel Ultra 7 155H, 700 MHz to 4.8 GHz)" + + +def _one_d_benchmark(files): + df_seq = load_benchmark(files["1D_Sequential"], "Sequential") + df_omp_2 = load_benchmark(files["1D_OpenMP_2"], "OpenMP 2 threads") + df_omp_4 = load_benchmark(files["1D_OpenMP_4"], "OpenMP 4 threads") + df_omp_8 = load_benchmark(files["1D_OpenMP_8"], "OpenMP 8 threads") + df_omp_16 = load_benchmark(files["1D_OpenMP_16"], "OpenMP 16 threads") + df_omp_22 = load_benchmark(files["1D_OpenMP_22"], "OpenMP 22 threads") + +# plot_execution_time( +# pd.concat([df_seq, df_omp_2, df_omp_4, df_omp_8]), +# "1D FFT Execution Time (All threads)", +# output_files=[ +# "./dell/results/1D_fft_execution_time_all_threads.pdf", +# "./dell/results/1D_fft_execution_time_all_threads.png" +# ] +# ) +# plot_multi_thread_speedup( +# pd.concat([df_seq, df_omp_2, df_omp_4, df_omp_8]), +# "Sequential", +# "1D FFT Speedup (All threads)", +# output_files=[ +# "./dell/results/1D_fft_speedup_all_threads.pdf", +# "./dell/results/1D_fft_speedup_all_threads.png" +# ] +# ) +# plot_speedup_bar( +# df_seq, +# df_omp_2, +# "1D FFT Speedup Bar Chart (2 threads)", +# output_files=[ +# "./dell/results/1D_fft_speedup_bar_2_threads.pdf", +# "./dell/results/1D_fft_speedup_bar_2_threads.png" +# ] +# ) +# plot_speedup_bar( +# df_seq, +# df_omp_4, +# "1D FFT Speedup Bar Chart (4 threads)", +# output_files=[ +# "./dell/results/1D_fft_speedup_bar_4_threads.pdf", +# "./dell/results/1D_fft_speedup_bar_4_threads.png" +# ] +# ) +# plot_speedup_bar( +# df_seq, +# df_omp_8, +# "1D FFT Speedup Bar Chart (8 threads)", +# output_files=[ +# "./dell/results/1D_fft_speedup_bar_8_threads.pdf", +# "./dell/results/1D_fft_speedup_bar_8_threads.png" +# ] +# ) +# plot_efficiency_bar( +# df_seq, +# df_omp_2, +# 2, +# "1D FFT Efficiency Bar Chart (2 threads)", +# output_files=[ +# "./dell/results/1D_fft_efficiency_bar_2_threads.pdf", +# "./dell/results/1D_fft_efficiency_bar_2_threads.png" +# ] +# ) +# plot_efficiency_bar( +# df_seq, +# df_omp_4, +# 4, +# "1D FFT Efficiency Bar Chart (4 threads)", +# output_files=[ +# "./dell/results/1D_fft_efficiency_bar_4_threads.pdf", +# "./dell/results/1D_fft_efficiency_bar_4_threads.png" +# ] +# ) +# plot_efficiency_bar( +# df_seq, +# df_omp_8, +# 8, +# "1D FFT Efficiency Bar Chart (8 threads)", +# output_files=[ +# "./dell/results/1D_fft_efficiency_bar_8_threads.pdf", +# "./dell/results/1D_fft_efficiency_bar_8_threads.png" +# ] +# ) + df_omp_dict = { + 2: df_omp_2, + 4: df_omp_4, + 8: df_omp_8, + 16: df_omp_16, + 22: df_omp_22 + } + plot_speedup_vs_threads( + df_seq, + df_omp_dict, + f"1D FFT Speedup vs Threads {_specs}", + output_files=[ + "./dell/results/1D_fft_speedup_vs_threads.pdf", + "./dell/results/1D_fft_speedup_vs_threads.png" + ] + ) + plot_efficiency_vs_threads( + df_seq, + df_omp_dict, + f"1D FFT Efficiency vs Threads {_specs}", + output_files=[ + "./dell/results/1D_fft_efficiency_vs_threads.pdf", + "./dell/results/1D_fft_efficiency_vs_threads.png" + ] + ) + + +def _two_d_benchmark(files): + df_seq = load_benchmark(files["2D_Sequential"], "Sequential") + df_omp_2 = load_benchmark(files["2D_OpenMP_2"], "OpenMP 2 threads") + df_omp_4 = load_benchmark(files["2D_OpenMP_4"], "OpenMP 4 threads") + df_omp_8 = load_benchmark(files["2D_OpenMP_8"], "OpenMP 8 threads") + df_omp_16 = load_benchmark(files["2D_OpenMP_16"], "OpenMP 16 threads") + df_omp_22 = load_benchmark(files["2D_OpenMP_22"], "OpenMP 22 threads") + +# plot_execution_time_binned( +# pd.concat([df_seq, df_omp_2, df_omp_4, df_omp_8]), +# "2D FFT Execution Time (All threads)", +# output_files=[ +# "./dell/results/2D_fft_execution_time_binned_all_threads.pdf", +# "./dell/results/2D_fft_execution_time_binned_all_threads.png" +# ] +# ) +# plot_speedup_binned_with_counts( +# df_seq, +# df_omp_2, +# f"2D FFT Speedup Bar Chart (2 threads)", +# output_files=[ +# "./dell/results/2D_fft_speedup_binned_with_counts_2_threads.pdf", +# "./dell/results/2D_fft_speedup_binned_with_counts_2_threads.png" +# ] +# ) +# plot_speedup_binned_with_counts( +# df_seq, +# df_omp_4, +# f"2D FFT Speedup Bar Chart (4 threads)", +# output_files=[ +# "./dell/results/2D_fft_speedup_binned_with_counts_4_threads.pdf", +# "./dell/results/2D_fft_speedup_binned_with_counts_4_threads.png" +# ] +# ) +# plot_speedup_binned_with_counts( +# df_seq, +# df_omp_8, +# f"2D FFT Speedup Bar Chart (8 threads)", +# output_files=[ +# "./dell/results/2D_fft_speedup_binned_with_counts_8_threads.pdf", +# "./dell/results/2D_fft_speedup_binned_with_counts_8_threads.png" +# ] +# ) +# plot_efficiency_bar_binned( +# df_seq, +# df_omp_2, +# 2, +# "2D FFT Efficiency Bar Chart (2 threads)", +# output_files=[ +# "./dell/results/2D_fft_efficiency_bar_binned_2_threads.pdf", +# "./dell/results/2D_fft_efficiency_bar_binned_2_threads.png" +# ] +# ) +# plot_efficiency_bar_binned( +# df_seq, +# df_omp_4, +# 4, +# "2D FFT Efficiency Bar Chart (4 threads)", +# output_files=[ +# "./dell/results/2D_fft_efficiency_bar_binned_4_threads.pdf", +# "./dell/results/2D_fft_efficiency_bar_binned_4_threads.png" +# ] +# ) +# plot_efficiency_bar_binned( +# df_seq, +# df_omp_8, +# 8, +# "2D FFT Efficiency Bar Chart (8 threads)", +# output_files=[ +# "./dell/results/2D_fft_efficiency_bar_binned_8_threads.pdf", +# "./dell/results/2D_fft_efficiency_bar_binned_8_threads.png" +# ] +# ) + df_omp_dict = { + 2: df_omp_2, + 4: df_omp_4, + 8: df_omp_8, + 16: df_omp_16, + 22: df_omp_22 + } + plot_speedup_vs_threads( + df_seq, + df_omp_dict, + f"2D FFT Speedup vs Threads {_specs}", + output_files=[ + "./dell/results/2D_fft_speedup_vs_threads.pdf", + "./dell/results/2D_fft_speedup_vs_threads.png" + ] + ) + plot_efficiency_vs_threads( + df_seq, + df_omp_dict, + f"2D FFT Efficiency vs Threads {_specs}", + output_files=[ + "./dell/results/2D_fft_efficiency_vs_threads.pdf", + "./dell/results/2D_fft_efficiency_vs_threads.png" + ] + ) + + +def _three_d_benchmark(files): + df_seq = load_benchmark(files["3D_Sequential"], "Sequential") + df_omp_2 = load_benchmark(files["3D_OpenMP_2"], "OpenMP 2 threads") + df_omp_4 = load_benchmark(files["3D_OpenMP_4"], "OpenMP 4 threads") + df_omp_8 = load_benchmark(files["3D_OpenMP_8"], "OpenMP 8 threads") + df_omp_16 = load_benchmark(files["3D_OpenMP_16"], "OpenMP 16 threads") + df_omp_22 = load_benchmark(files["3D_OpenMP_22"], "OpenMP 22 threads") + +# plot_execution_time( +# pd.concat([df_seq, df_omp_2, df_omp_4, df_omp_8]), +# "3D FFT Execution Time (All threads)", +# output_files=[ +# "./dell/results/3D_fft_execution_time_all_threads.pdf", +# "./dell/results/3D_fft_execution_time_all_threads.png" +# ] +# ) +# plot_speedup_binned_with_counts( +# df_seq, +# df_omp_2, +# f"3D FFT Speedup Bar Chart (2 threads)", +# output_files=[ +# "./dell/results/3D_fft_speedup_binned_with_counts_2_threads.pdf", +# "./dell/results/3D_fft_speedup_binned_with_counts_2_threads.png" +# ] +# ) +# plot_speedup_binned_with_counts( +# df_seq, +# df_omp_4, +# f"3D FFT Speedup Bar Chart (4 threads)", +# output_files=[ +# "./dell/results/3D_fft_speedup_binned_with_counts_4_threads.pdf", +# "./dell/results/3D_fft_speedup_binned_with_counts_4_threads.png" +# ] +# ) +# plot_speedup_binned_with_counts( +# df_seq, +# df_omp_8, +# f"3D FFT Speedup Bar Chart (8 threads)", +# output_files=[ +# "./dell/results/3D_fft_speedup_binned_with_counts_8_threads.pdf", +# "./dell/results/3D_fft_speedup_binned_with_counts_8_threads.png" +# ] +# ) +# plot_efficiency_bar_binned( +# df_seq, +# df_omp_2, +# 2, +# "3D FFT Efficiency Bar Chart (2 threads)", +# output_files=[ +# "./dell/results/3D_fft_efficiency_bar_binned_2_threads.pdf", +# "./dell/results/3D_fft_efficiency_bar_binned_2_threads.png" +# ] +# ) +# plot_efficiency_bar_binned( +# df_seq, +# df_omp_4, +# 4, +# "3D FFT Efficiency Bar Chart (4 threads)", +# output_files=[ +# "./dell/results/3D_fft_efficiency_bar_binned_4_threads.pdf", +# "./dell/results/3D_fft_efficiency_bar_binned_4_threads.png" +# ] +# ) +# plot_efficiency_bar_binned( +# df_seq, +# df_omp_8, +# 8, +# "3D FFT Efficiency Bar Chart (8 threads)", +# output_files=[ +# "./dell/results/3D_fft_efficiency_bar_binned_8_threads.pdf", +# "./dell/results/3D_fft_efficiency_bar_binned_8_threads.png" +# ] +# ) + df_omp_dict = { + 2: df_omp_2, + 4: df_omp_4, + 8: df_omp_8, + 16: df_omp_16, + 22: df_omp_22 + } + plot_speedup_vs_threads( + df_seq, + df_omp_dict, + f"3D FFT Speedup vs Threads {_specs}", + output_files=[ + "./dell/results/3D_fft_speedup_vs_threads.pdf", + "./dell/results/3D_fft_speedup_vs_threads.png" + ] + ) + plot_efficiency_vs_threads( + df_seq, + df_omp_dict, + f"3D FFT Efficiency vs Threads {_specs}", + output_files=[ + "./dell/results/3D_fft_efficiency_vs_threads.pdf", + "./dell/results/3D_fft_efficiency_vs_threads.png" + ] + ) + + + +def main(): + files = { + "1D_Sequential": "./dell/dell-1D_results_sequential_2025-05-25_10-19-35.json", + "1D_OpenMP_22": "./dell/dell-1D_results_openmp_threads_22_2025-05-25_10-24-16.json", + "1D_OpenMP_16": "./dell/dell-1D_results_openmp_threads_16_2025-05-25_12-57-14.json", + "1D_OpenMP_8": "./dell/dell-1D_results_openmp_threads_8_2025-05-25_12-59-09.json", + "1D_OpenMP_4": "./dell/dell-1D_results_openmp_threads_4_2025-05-25_13-01-19.json", + "1D_OpenMP_2": "./dell/dell-1D_results_openmp_threads_2_2025-05-25_13-08-14.json", + + "2D_Sequential": "./dell/dell-2D_results_sequential_2025-05-25_10-25-58.json", + "2D_OpenMP_22": "./dell/dell-2D_results_openmp_threads_22_2025-05-25_10-42-51.json", + "2D_OpenMP_16": "./dell/dell-2D_results_openmp_threads_16_2025-05-25_13-15-11.json", + "2D_OpenMP_8": "./dell/dell-2D_results_openmp_threads_8_2025-05-25_13-20-48.json", + "2D_OpenMP_4": "./dell/dell-2D_results_openmp_threads_4_2025-05-25_13-51-23.json", + "2D_OpenMP_2": "./dell/dell-2D_results_openmp_threads_2_2025-05-25_14-19-12.json", + + "3D_Sequential": "./dell/dell-3D_results_sequential_2025-05-25_11-02-19.json", + "3D_OpenMP_22": "./dell/dell-3D_results_openmp_threads_22_2025-05-25_11-43-35.json", + "3D_OpenMP_16": "./dell/dell-3D_results_openmp_threads_16_2025-05-25_14-31-26.json", + "3D_OpenMP_8": "./dell/dell-3D_results_openmp_threads_8_2025-05-25_15-01-18.json", + "3D_OpenMP_4": "./dell/dell-3D_results_openmp_threads_4_2025-05-25_15-37-30.json", + "3D_OpenMP_2": "./dell/dell-3D_results_openmp_threads_2_2025-05-25_16-07-27.json" + } + + ### 1D FFT Performance Analysis + _one_d_benchmark(files) + + #### 2D FFT Performance Analysis + _two_d_benchmark(files) + + #### 3D FFT Performance Analysis + _three_d_benchmark(files) \ No newline at end of file diff --git a/benchmarks/fourier_transform/dell/dell-1D_results_openmp_threads_16_2025-05-25_12-57-14.json b/benchmarks/fourier_transform/dell/dell-1D_results_openmp_threads_16_2025-05-25_12-57-14.json new file mode 100644 index 0000000..2cbc138 --- /dev/null +++ b/benchmarks/fourier_transform/dell/dell-1D_results_openmp_threads_16_2025-05-25_12-57-14.json @@ -0,0 +1,351 @@ +{ + "context": { + "date": "2025-05-25T12:57:14+02:00", + "host_name": "andre", + "executable": "./build/ninja-dev-benchmark/benchmarks/fourier_transform/benchmark-fourier_transform", + "num_cpus": 22, + "mhz_per_cpu": 2995, + "cpu_scaling_enabled": false, + "aslr_enabled": true, + "caches": [ + { + "type": "Data", + "level": 1, + "size": 49152, + "num_sharing": 2 + }, + { + "type": "Instruction", + "level": 1, + "size": 65536, + "num_sharing": 2 + }, + { + "type": "Unified", + "level": 2, + "size": 2097152, + "num_sharing": 2 + }, + { + "type": "Unified", + "level": 3, + "size": 25165824, + "num_sharing": 22 + } + ], + "load_avg": [0,0,0.978516], + "library_version": "v1.9.3-3-g4995099c", + "library_build_type": "release", + "json_schema_version": 1 + }, + "benchmarks": [ + { + "name": "1D/2x", + "family_index": 0, + "per_family_instance_index": 0, + "run_name": "1D/2x", + "run_type": "iteration", + "repetitions": 1, + "repetition_index": 0, + "threads": 1, + "iterations": 504, + "real_time": 1.9455699424587882e+06, + "cpu_time": 1.3462470238095238e+06, + "time_unit": "ns" + }, + { + "name": "1D/4x", + "family_index": 1, + "per_family_instance_index": 0, + "run_name": "1D/4x", + "run_type": "iteration", + "repetitions": 1, + "repetition_index": 0, + "threads": 1, + "iterations": 383, + "real_time": 2.9523127049627299e+06, + "cpu_time": 2.0489409921671022e+06, + "time_unit": "ns" + }, + { + "name": "1D/8x", + "family_index": 2, + "per_family_instance_index": 0, + "run_name": "1D/8x", + "run_type": "iteration", + "repetitions": 1, + "repetition_index": 0, + "threads": 1, + "iterations": 240, + "real_time": 4.2914691499997089e+06, + "cpu_time": 3.0440691666666665e+06, + "time_unit": "ns" + }, + { + "name": "1D/16x", + "family_index": 3, + "per_family_instance_index": 0, + "run_name": "1D/16x", + "run_type": "iteration", + "repetitions": 1, + "repetition_index": 0, + "threads": 1, + "iterations": 197, + "real_time": 4.7624530862929085e+06, + "cpu_time": 3.2283568527918798e+06, + "time_unit": "ns" + }, + { + "name": "1D/32x", + "family_index": 4, + 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b/benchmarks/fourier_transform/dell/results/3D_fft_speedup_vs_threads.png differ diff --git a/benchmarks/fourier_transform/fourier_transform.cpp b/benchmarks/fourier_transform/fourier_transform.cpp new file mode 100644 index 0000000..d6e656f --- /dev/null +++ b/benchmarks/fourier_transform/fourier_transform.cpp @@ -0,0 +1,194 @@ +#include +#include +#include +#include + +#include "signal_processing/signal_processing.hpp" + +#include "utils.hpp" + +using namespace sp::fft::solver; + +constexpr size_t MAX_TOTAL_SIZE = 8388608; + +/** + * Combinatorial benchmark for the Fast Fourier Transform (FFT) in N dimensions. + * + * This function generates all valid shapes for the FFT solver + * and registers a benchmark for each shape. + * + * Since it is combinatorial, it will generate all possible shapes + * for the given maximum total size. This means that it will + * generate shapes unbalanced in terms of dimensions, e.g.: <2, 4194304> + * @tparam N Number of dimensions for the FFT solver. + * @param mode The computation mode to be used (SEQUENTIAL, OPENMP). + * @param min Optional minimum value for the dimensions. + */ +template +void combinatorialBenchmark(ComputationMode mode, const int min) { + auto shapes = generateValidShapes(MAX_TOTAL_SIZE, min); + for (const auto& dims : shapes) { + // create a benchmark name based on the dimensions + // e.g. "2D/4x4x4" + std::ostringstream name; + name << N << "D/"; + for (const size_t d : dims) + name << d << "x"; + // remove the last 'x' + name.seekp(-1, std::ios_base::end); + + // ReSharper disable once CppDFAUnusedValue + benchmark::RegisterBenchmark(name.str().c_str(), [=](benchmark::State& state) { + FastFourierTransform fft(dims); + auto input = generateInput(dims); + + for (auto _ : state) { + auto copy = input; + fft.compute(copy, mode); + benchmark::DoNotOptimize(copy); + } + }); + } +} + +/** + * Combinatorial benchmark for the Fast Fourier Transform (FFT) in N dimensions. + * + * This function generates all valid shapes for the FFT solver + * and registers a benchmark for each shape. + * + * Since it is combinatorial, it will generate all possible shapes + * for the given maximum total size. This means that it will + * generate shapes unbalanced in terms of dimensions, e.g.: <2, 4194304> + * @tparam N Number of dimensions for the FFT solver. + * @param mode The computation mode to be used (SEQUENTIAL, OPENMP). + */ +template +void combinatorialBenchmark(ComputationMode mode) { + auto shapes = generateValidShapes(MAX_TOTAL_SIZE); + for (const auto& dims : shapes) { + // create a benchmark name based on the dimensions + // e.g. "2D/4x4x4" + std::ostringstream name; + name << N << "D/"; + for (const size_t d : dims) + name << d << "x"; + // remove the last 'x' + name.seekp(-1, std::ios_base::end); + + // ReSharper disable once CppDFAUnusedValue + benchmark::RegisterBenchmark(name.str().c_str(), [=](benchmark::State& state) { + FastFourierTransform fft(dims); + auto input = generateInput(dims); + + for (auto _ : state) { + auto copy = input; + fft.compute(copy, mode); + benchmark::DoNotOptimize(copy); + } + }); + } +} + +int main(const int argc, char** argv) { + if ( + getArgValue(argc, argv, "h", false, false) != "" || + getArgValue(argc, argv, "help", true, false) != "" + ) { + printf( + "Usage: ./program -dim=<1|2|3> -type= -mode= -threads=<1|2|4|...>\n" + " -dim: Dimension of the FFT (1, 2, or 3)\n" + " -type: Type of benchmark (combinatorial or balanced)\n" + " -mode: Computation mode (sequential or openmp)\n" + " -threads: Number of threads to use (only for openmp mode)\n" + " -h or --help: Show this help message\n" + ); + return 0; + } + + const auto dim_opt = getArgValue(argc, argv, "dim"); + const auto type_opt = getArgValue(argc, argv, "type"); + const auto mode_opt = getArgValue(argc, argv, "mode"); + + if (dim_opt == "" || type_opt == "" || mode_opt == "") { + std::cerr << "Usage: ./program -dim=<1|2|3> -type= -mode= -threads=<1|2|4|...>\n" + << " -dim: Dimension of the FFT (1, 2, or 3)\n" + << " -type: Type of benchmark (combinatorial or balanced)\n" + << " -mode: Computation mode (sequential or openmp)\n" + << " -threads: Number of threads to use (only for openmp mode)\n" + << " -h or --help: Show this help message\n"; + return 1; + } + + const size_t dim = std::stoi(dim_opt); + const std::string& type = type_opt; + const std::string& rawMode = mode_opt; + + if (dim < 1 || dim > 3) { + std::cerr << "Invalid dimension. Must be 1, 2, or 3.\n"; + return 1; + } + + if (type != "combinatorial" && type != "balanced") { + std::cerr << "Invalid type. Must be 'combinatorial' or 'balanced'.\n"; + return 1; + } + + if (rawMode != "sequential" && rawMode != "openmp") { + std::cerr << "Invalid mode. Must be 'sequential', 'openmp'.\n"; + return 1; + } + + const ComputationMode mode = (rawMode == "sequential") ? ComputationMode::SEQUENTIAL : ComputationMode::OPENMP; + + // set number of threads if in openmp mode + if (mode == ComputationMode::OPENMP) { + const auto threads_opt = getArgValue(argc, argv, "threads"); + omp_set_num_threads(threads_opt != "" ? std::stoi(threads_opt) : omp_get_max_threads()); + } + + std::ostringstream oss; + // use the format provided by the user + oss << "--benchmark_out=" << dim << "D_results_" << rawMode << "_" + << "threads" << "_" << omp_get_max_threads() << "_" + << sp::utils::timestamp::createReadableTimestamp("%Y-%m-%d_%H-%M-%S") + << ".json"; + const std::string benchmark_out = oss.str(); + + const char* args[] = { + argv[0], // keep program name + argc > 1 ? argv[1] : nullptr, + benchmark_out.c_str(), + "--benchmark_out_format=json" + }; + int custom_argc = sizeof(args) / sizeof(char*); + + if (type == "balanced") { + if (dim == 1) { + combinatorialBenchmark<1>(mode, 256); + } else if (dim == 2) { + combinatorialBenchmark<2>(mode, 256); + } else { + combinatorialBenchmark<3>(mode, 256); + } + } else { + if (dim == 1) { + combinatorialBenchmark<1>(mode); + } else if (dim == 2) { + combinatorialBenchmark<2>(mode); + } else { + combinatorialBenchmark<3>(mode); + } + } + + printf("Running benchmarks with the following parameters:\n"); + printf(" Dimension: %zu\n", dim); + printf(" Type: %s\n", type.c_str()); + printf(" Mode: %s\n", rawMode.c_str()); + printf(" Output file: %s\n", benchmark_out.c_str()); + printf(" Threads: %d\n", omp_get_max_threads()); + + // Initialize with overridden args + benchmark::Initialize(&custom_argc, const_cast(args)); + benchmark::RunSpecifiedBenchmarks(); +} diff --git a/benchmarks/fourier_transform/hp.py b/benchmarks/fourier_transform/hp.py new file mode 100644 index 0000000..e3eaf51 --- /dev/null +++ b/benchmarks/fourier_transform/hp.py @@ -0,0 +1,338 @@ +from plot_performance import * + + +_specs = "(HP Pavilion 15-cx0xxx, i7-8750H CPU @ 2.20GHz)" + +def _one_d_benchmark(files): + df_seq = load_benchmark(files["1D_Sequential"], "Sequential") + df_omp_2 = load_benchmark(files["1D_OpenMP_2"], "OpenMP 2 threads") + df_omp_4 = load_benchmark(files["1D_OpenMP_4"], "OpenMP 4 threads") + df_omp_8 = load_benchmark(files["1D_OpenMP_8"], "OpenMP 8 threads") + df_omp_12 = load_benchmark(files["1D_OpenMP_12"], "OpenMP 12 threads") + +# plot_execution_time( +# pd.concat([df_seq, df_omp_2, df_omp_4, df_omp_8]), +# "1D FFT Execution Time (All threads)", +# output_files=[ +# "./hp/results/1D_fft_execution_time_all_threads.pdf", +# "./hp/results/1D_fft_execution_time_all_threads.png" +# ] +# ) +# plot_multi_thread_speedup( +# pd.concat([df_seq, df_omp_2, df_omp_4, df_omp_8]), +# "Sequential", +# "1D FFT Speedup (All threads)", +# output_files=[ +# "./hp/results/1D_fft_speedup_all_threads.pdf", +# "./hp/results/1D_fft_speedup_all_threads.png" +# ] +# ) +# plot_speedup_bar( +# df_seq, +# df_omp_2, +# "1D FFT Speedup Bar Chart (2 threads)", +# output_files=[ +# "./hp/results/1D_fft_speedup_bar_2_threads.pdf", +# "./hp/results/1D_fft_speedup_bar_2_threads.png" +# ] +# ) +# plot_speedup_bar( +# df_seq, +# df_omp_4, +# "1D FFT Speedup Bar Chart (4 threads)", +# output_files=[ +# "./hp/results/1D_fft_speedup_bar_4_threads.pdf", +# "./hp/results/1D_fft_speedup_bar_4_threads.png" +# ] +# ) +# plot_speedup_bar( +# df_seq, +# df_omp_8, +# "1D FFT Speedup Bar Chart (8 threads)", +# output_files=[ +# "./hp/results/1D_fft_speedup_bar_8_threads.pdf", +# "./hp/results/1D_fft_speedup_bar_8_threads.png" +# ] +# ) +# plot_efficiency_bar( +# df_seq, +# df_omp_2, +# 2, +# "1D FFT Efficiency Bar Chart (2 threads)", +# output_files=[ +# "./hp/results/1D_fft_efficiency_bar_2_threads.pdf", +# "./hp/results/1D_fft_efficiency_bar_2_threads.png" +# ] +# ) +# plot_efficiency_bar( +# df_seq, +# df_omp_4, +# 4, +# "1D FFT Efficiency Bar Chart (4 threads)", +# output_files=[ +# "./hp/results/1D_fft_efficiency_bar_4_threads.pdf", +# "./hp/results/1D_fft_efficiency_bar_4_threads.png" +# ] +# ) +# plot_efficiency_bar( +# df_seq, +# df_omp_8, +# 8, +# "1D FFT Efficiency Bar Chart (8 threads)", +# output_files=[ +# "./hp/results/1D_fft_efficiency_bar_8_threads.pdf", +# "./hp/results/1D_fft_efficiency_bar_8_threads.png" +# ] +# ) + df_omp_dict = { + 2: df_omp_2, + 4: df_omp_4, + 8: df_omp_8, + 12: df_omp_12 + } + plot_speedup_vs_threads( + df_seq, + df_omp_dict, + f"1D FFT Speedup vs Threads {_specs}", + output_files=[ + "./hp/results/1D_fft_speedup_vs_threads.pdf", + "./hp/results/1D_fft_speedup_vs_threads.png" + ] + ) + plot_efficiency_vs_threads( + df_seq, + df_omp_dict, + f"1D FFT Efficiency vs Threads {_specs}", + output_files=[ + "./hp/results/1D_fft_efficiency_vs_threads.pdf", + "./hp/results/1D_fft_efficiency_vs_threads.png" + ] + ) + + +def _two_d_benchmark(files): + df_seq = load_benchmark(files["2D_Sequential"], "Sequential") + df_omp_2 = load_benchmark(files["2D_OpenMP_2"], "OpenMP 2 threads") + df_omp_4 = load_benchmark(files["2D_OpenMP_4"], "OpenMP 4 threads") + df_omp_8 = load_benchmark(files["2D_OpenMP_8"], "OpenMP 8 threads") + df_omp_12 = load_benchmark(files["2D_OpenMP_12"], "OpenMP 12 threads") + +# plot_execution_time_binned( +# pd.concat([df_seq, df_omp_2, df_omp_4, df_omp_8]), +# "2D FFT Execution Time (All threads)", +# output_files=[ +# "./hp/results/2D_fft_execution_time_binned_all_threads.pdf", +# "./hp/results/2D_fft_execution_time_binned_all_threads.png" +# ] +# ) +# plot_speedup_binned_with_counts( +# df_seq, +# df_omp_2, +# f"2D FFT Speedup Bar Chart (2 threads)", +# output_files=[ +# "./hp/results/2D_fft_speedup_binned_with_counts_2_threads.pdf", +# "./hp/results/2D_fft_speedup_binned_with_counts_2_threads.png" +# ] +# ) +# plot_speedup_binned_with_counts( +# df_seq, +# df_omp_4, +# f"2D FFT Speedup Bar Chart (4 threads)", +# output_files=[ +# "./hp/results/2D_fft_speedup_binned_with_counts_4_threads.pdf", +# "./hp/results/2D_fft_speedup_binned_with_counts_4_threads.png" +# ] +# ) +# plot_speedup_binned_with_counts( +# df_seq, +# df_omp_8, +# f"2D FFT Speedup Bar Chart (8 threads)", +# output_files=[ +# "./hp/results/2D_fft_speedup_binned_with_counts_8_threads.pdf", +# "./hp/results/2D_fft_speedup_binned_with_counts_8_threads.png" +# ] +# ) +# plot_efficiency_bar_binned( +# df_seq, +# df_omp_2, +# 2, +# "2D FFT Efficiency Bar Chart (2 threads)", +# output_files=[ +# "./hp/results/2D_fft_efficiency_bar_binned_2_threads.pdf", +# "./hp/results/2D_fft_efficiency_bar_binned_2_threads.png" +# ] +# ) +# plot_efficiency_bar_binned( +# df_seq, +# df_omp_4, +# 4, +# "2D FFT Efficiency Bar Chart (4 threads)", +# output_files=[ +# "./hp/results/2D_fft_efficiency_bar_binned_4_threads.pdf", +# "./hp/results/2D_fft_efficiency_bar_binned_4_threads.png" +# ] +# ) +# plot_efficiency_bar_binned( +# df_seq, +# df_omp_8, +# 8, +# "2D FFT Efficiency Bar Chart (8 threads)", +# output_files=[ +# "./hp/results/2D_fft_efficiency_bar_binned_8_threads.pdf", +# "./hp/results/2D_fft_efficiency_bar_binned_8_threads.png" +# ] +# ) + df_omp_dict = { + 2: df_omp_2, + 4: df_omp_4, + 8: df_omp_8, + 12: df_omp_12 + } + plot_speedup_vs_threads( + df_seq, + df_omp_dict, + f"2D FFT Speedup vs Threads {_specs}", + output_files=[ + "./hp/results/2D_fft_speedup_vs_threads.pdf", + "./hp/results/2D_fft_speedup_vs_threads.png" + ] + ) + plot_efficiency_vs_threads( + df_seq, + df_omp_dict, + f"2D FFT Efficiency vs Threads {_specs}", + output_files=[ + "./hp/results/2D_fft_efficiency_vs_threads.pdf", + "./hp/results/2D_fft_efficiency_vs_threads.png" + ] + ) + + +def _three_d_benchmark(files): + df_seq = load_benchmark(files["3D_Sequential"], "Sequential") + df_omp_2 = load_benchmark(files["3D_OpenMP_2"], "OpenMP 2 threads") + df_omp_4 = load_benchmark(files["3D_OpenMP_4"], "OpenMP 4 threads") + df_omp_8 = load_benchmark(files["3D_OpenMP_8"], "OpenMP 8 threads") + df_omp_12 = load_benchmark(files["3D_OpenMP_12"], "OpenMP 12 threads") + +# plot_execution_time( +# pd.concat([df_seq, df_omp_2, df_omp_4, df_omp_8]), +# "3D FFT Execution Time (All threads)", +# output_files=[ +# "./hp/results/3D_fft_execution_time_all_threads.pdf", +# "./hp/results/3D_fft_execution_time_all_threads.png" +# ] +# ) +# plot_speedup_binned_with_counts( +# df_seq, +# df_omp_2, +# f"3D FFT Speedup Bar Chart (2 threads)", +# output_files=[ +# "./hp/results/3D_fft_speedup_binned_with_counts_2_threads.pdf", +# "./hp/results/3D_fft_speedup_binned_with_counts_2_threads.png" +# ] +# ) +# plot_speedup_binned_with_counts( +# df_seq, +# df_omp_4, +# f"3D FFT Speedup Bar Chart (4 threads)", +# output_files=[ +# "./hp/results/3D_fft_speedup_binned_with_counts_4_threads.pdf", +# "./hp/results/3D_fft_speedup_binned_with_counts_4_threads.png" +# ] +# ) +# plot_speedup_binned_with_counts( +# df_seq, +# df_omp_8, +# f"3D FFT Speedup Bar Chart (8 threads)", +# output_files=[ +# "./hp/results/3D_fft_speedup_binned_with_counts_8_threads.pdf", +# "./hp/results/3D_fft_speedup_binned_with_counts_8_threads.png" +# ] +# ) +# plot_efficiency_bar_binned( +# df_seq, +# df_omp_2, +# 2, +# "3D FFT Efficiency Bar Chart (2 threads)", +# output_files=[ +# "./hp/results/3D_fft_efficiency_bar_binned_2_threads.pdf", +# "./hp/results/3D_fft_efficiency_bar_binned_2_threads.png" +# ] +# ) +# plot_efficiency_bar_binned( +# df_seq, +# df_omp_4, +# 4, +# "3D FFT Efficiency Bar Chart (4 threads)", +# output_files=[ +# "./hp/results/3D_fft_efficiency_bar_binned_4_threads.pdf", +# "./hp/results/3D_fft_efficiency_bar_binned_4_threads.png" +# ] +# ) +# plot_efficiency_bar_binned( +# df_seq, +# df_omp_8, +# 8, +# "3D FFT Efficiency Bar Chart (8 threads)", +# output_files=[ +# "./hp/results/3D_fft_efficiency_bar_binned_8_threads.pdf", +# "./hp/results/3D_fft_efficiency_bar_binned_8_threads.png" +# ] +# ) + df_omp_dict = { + 2: df_omp_2, + 4: df_omp_4, + 8: df_omp_8, + 12: df_omp_12 + } + plot_speedup_vs_threads( + df_seq, + df_omp_dict, + f"3D FFT Speedup vs Threads {_specs}", + output_files=[ + "./hp/results/3D_fft_speedup_vs_threads.pdf", + "./hp/results/3D_fft_speedup_vs_threads.png" + ] + ) + plot_efficiency_vs_threads( + df_seq, + df_omp_dict, + f"3D FFT Efficiency vs Threads {_specs}", + output_files=[ + "./hp/results/3D_fft_efficiency_vs_threads.pdf", + "./hp/results/3D_fft_efficiency_vs_threads.png" + ] + ) + + + +def main(): + files = { + "1D_Sequential": "./hp/hp-1D_results_sequential_2025-05-18_13-18-05.json", + "1D_OpenMP_12": "./hp/hp-1D_results_openmp_threads_12_2025-05-20_17-30-27.json", + "1D_OpenMP_8": "./hp/hp-1D_results_openmp_threads_8_2025-05-25_12-14-36.json", + "1D_OpenMP_4": "./hp/hp-1D_results_openmp_threads_4_2025-05-25_12-51-23.json", + "1D_OpenMP_2": "./hp/hp-1D_results_openmp_threads_2_2025-05-25_12-57-05.json", + + "2D_Sequential": "./hp/hp-2D_results_sequential_2025-05-18_13-19-45.json", + "2D_OpenMP_12": "./hp/hp-2D_results_openmp_threads_12_2025-05-20_17-33-41.json", + "2D_OpenMP_8": "./hp/hp-2D_results_openmp_threads_8_2025-05-25_12-58-57.json", + "2D_OpenMP_4": "./hp/hp-2D_results_openmp_threads_4_2025-05-25_13-08-24.json", + "2D_OpenMP_2": "./hp/hp-2D_results_openmp_threads_2_2025-05-25_13-14-52.json", + + "3D_Sequential": "./hp/hp-3D_results_sequential_2025-05-18_16-06-44.json", + "3D_OpenMP_12": "./hp/hp-3D_results_openmp_threads_12_2025-05-20_17-38-20.json", + "3D_OpenMP_8": "./hp/hp-3D_results_openmp_threads_8_2025-05-25_13-21-06.json", + "3D_OpenMP_4": "./hp/hp-3D_results_openmp_threads_4_2025-05-25_14-19-48.json", + "3D_OpenMP_2": "./hp/hp-3D_results_openmp_threads_2_2025-05-25_15-01-28.json" + } + + ### 1D FFT Performance Analysis + _one_d_benchmark(files) + + #### 2D FFT Performance Analysis + _two_d_benchmark(files) + + #### 3D FFT Performance Analysis + _three_d_benchmark(files) \ No newline at end of file diff --git a/benchmarks/fourier_transform/hp/hp-1D_results_openmp_threads_12_2025-05-20_17-30-27.json b/benchmarks/fourier_transform/hp/hp-1D_results_openmp_threads_12_2025-05-20_17-30-27.json new file mode 100644 index 0000000..ad3563b --- /dev/null +++ b/benchmarks/fourier_transform/hp/hp-1D_results_openmp_threads_12_2025-05-20_17-30-27.json @@ -0,0 +1,351 @@ +{ + "context": { + "date": "2025-05-20T17:30:27+02:00", + "host_name": "hp", + "executable": "./build/ninja-dev-benchmark/benchmarks/fourier_transform/benchmark-fourier_transform", + "num_cpus": 12, + "mhz_per_cpu": 4100, + "cpu_scaling_enabled": true, + "aslr_enabled": true, + "caches": [ + { + "type": "Data", + "level": 1, + "size": 32768, + "num_sharing": 2 + }, + { + "type": "Instruction", + "level": 1, + "size": 32768, + "num_sharing": 2 + }, + { + "type": "Unified", + "level": 2, + "size": 262144, + "num_sharing": 2 + }, + { + "type": "Unified", + "level": 3, + "size": 9437184, + "num_sharing": 12 + } + ], + "load_avg": 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milliseconds, and label. + """ + with open(file_path, 'r') as f: + raw = json.load(f) + data = [] + for b in raw["benchmarks"]: + name = b["name"] + size_str: list[str] = name.split("/")[1].split("x") + # size_str is a list of strings like ['1024', '1024', ''] + size = 1 + for s in size_str: + if s.isdigit(): + size *= int(s) + else: + # if the string is not a digit, we skip it + continue + # convert time from nanoseconds to milliseconds + time_ms = b["real_time"] / 1e6 + data.append({"size": size, "time_ms": time_ms, "label": label}) + return pd.DataFrame(data) + + +def plot_execution_time(df, title, output_files: list | None = None): + """ + Plot execution time for different benchmarks. + The DataFrame should contain columns for size, time_ms, and label. + :param df: DataFrame containing benchmark results with columns 'size', 'time_ms', and 'label'. + :param title: Title for the plot. + :param output_files: Optional; if provided, the plot will be saved to this file. + """ + plt.figure(figsize=(10, 5)) + for label, group in df.groupby("label"): + group_sorted = group.sort_values("size") + plt.plot(group_sorted["size"], group_sorted["time_ms"], marker='o', label=label) + plt.xlabel("Input Size") + plt.ylabel("Execution Time (ms)") + plt.title(title) + plt.grid(True) + plt.legend() + if output_files: + for output_file in output_files: + plt.savefig(output_file) + plt.show() + + +def plot_speedup(df_seq, df_omp, title, output_files: list | None = None): + """ + Plot speedup of OpenMP over Sequential implementation. + The DataFrame should contain columns for size, time_ms_seq, and time_ms_omp. + :param df_seq: DataFrame containing sequential benchmark results with columns 'size' and 'time_ms'. + :param df_omp: DataFrame containing OpenMP benchmark results with columns 'size' and 'time_ms'. + :param title: Title for the plot. + :param output_files: Optional; if provided, the plot will be saved to this file. + """ + merged = pd.merge(df_seq, df_omp, on="size", suffixes=("_seq", "_omp")) + merged["speedup"] = merged["time_ms_seq"] / merged["time_ms_omp"] + + plt.figure(figsize=(10, 5)) + plt.plot( + merged["size"], merged["speedup"], + marker='o', markersize=8, linewidth=2, + markerfacecolor='white', markeredgecolor='green', + color='green', label="Speedup" + ) + plt.axhline(1.0, color='red', linestyle='--', linewidth=1) + + # Highlight max and min points with text + max_row = merged.loc[merged["speedup"].idxmax()] + min_row = merged.loc[merged["speedup"].idxmin()] + for row in [max_row, min_row]: + plt.annotate( + f'{row["speedup"]:.2f}', + xy=(row["size"], row["speedup"]), + xytext=(0, 10), + textcoords='offset points', + ha='center', + fontsize=9, + color='black', + bbox=dict(boxstyle="round,pad=0.2", fc="yellow", alpha=0.3) + ) + + plt.xlabel("Input Size") + plt.ylabel("Speedup (Sequential / OpenMP)") + plt.title(title) + plt.grid(True) + plt.legend() + if output_files: + for output_file in output_files: + plt.savefig(output_file) + plt.show() + + +def plot_speedup_bar(df_seq, df_omp, title, output_files: list | None = None): + sns.set(style="whitegrid") + + merged = pd.merge(df_seq, df_omp, on="size", suffixes=("_seq", "_omp")) + merged["speedup"] = merged["time_ms_seq"] / merged["time_ms_omp"] + merged = merged.sort_values("size") + + # Color mapping based on speedup value + def color_map(s): + if s < 1.0: + return 'red' + elif s < 1.5: + return 'orange' + else: + return 'green' + colors = merged["speedup"].apply(color_map) + + plt.figure(figsize=(12, 6)) + bars = plt.bar(merged["size"].astype(str), merged["speedup"], color=colors) + + # Annotate bars with speedup value + for bar, val in zip(bars, merged["speedup"]): + height = bar.get_height() + plt.text(bar.get_x() + bar.get_width()/2., height + 0.05, + f'{val:.2f}', ha='center', va='bottom', fontsize=8) + + plt.axhline(1.0, color='black', linestyle='--', linewidth=1) + plt.xlabel("Input Size") + plt.ylabel("Speedup (Sequential / OpenMP)") + plt.title(title) + # plt.xticks(rotation=45, ha='right') + step = max(1, len(merged) // 20) + plt.xticks( + ticks=range(0, len(merged), step), + labels=merged["size"].astype(str).values[::step], + rotation=45, + ha='right', + fontsize=8 + ) + plt.tight_layout() + if output_files: + for output_file in output_files: + plt.savefig(output_file) + plt.show() + + +def plot_speedup_binned(df_seq, df_omp, title, output_files: list | None = None): + # Merge and compute speedup + merged = pd.merge(df_seq, df_omp, on="size", suffixes=("_seq", "_omp")) + merged["speedup"] = merged["time_ms_seq"] / merged["time_ms_omp"] + merged["log2_size"] = np.log2(merged["size"]).astype(int) + + # Group by log2 bins + binned = merged.groupby("log2_size").agg( + avg_speedup=("speedup", "mean"), + max_speedup=("speedup", "max"), + min_speedup=("speedup", "min"), + count=("speedup", "count") + ).reset_index() + + # Plot average speedup bar + plt.figure(figsize=(10, 6)) + plt.bar(binned["log2_size"], binned["avg_speedup"], color='steelblue', alpha=0.8) + plt.axhline(1.0, color='red', linestyle='--') + plt.xlabel("log2(Input Size)") + plt.ylabel("Average Speedup") + plt.title(title) + plt.grid(True) + plt.tight_layout() + if output_files: + for output_file in output_files: + plt.savefig(output_file) + plt.show() + + +def plot_speedup_binned_with_counts(df_seq, df_omp, title, output_files: list | None = None): + # Merge and compute speedup + merged = pd.merge(df_seq, df_omp, on="size", suffixes=("_seq", "_omp")) + merged["speedup"] = merged["time_ms_seq"] / merged["time_ms_omp"] + merged["log2_size"] = np.log2(merged["size"]).astype(int) + + # Group by log2 bins + binned = merged.groupby("log2_size").agg( + avg_speedup=("speedup", "mean"), + max_speedup=("speedup", "max"), + std_speedup=("speedup", "std"), + count=("speedup", "count") + ).reset_index() + + # Plot dual bars (avg + max speedup) + x = binned["log2_size"] + width = 0.4 + + fig, ax1 = plt.subplots(figsize=(12, 6)) + + ax1.errorbar( + binned["log2_size"], + binned["avg_speedup"], + yerr=binned["std_speedup"], + fmt='none', + ecolor='black', + elinewidth=1.2, + capsize=4, + label="Std Dev" + ) + ax1.bar(x - width/2, binned["avg_speedup"], width=width, label='Avg Speedup', color='steelblue') + ax1.bar(x + width/2, binned["max_speedup"], width=width, label='Max Speedup', color='orange') + ax1.axhline(1.0, color='red', linestyle='--') + ax1.set_xlabel("log2(Input Size)") + ax1.set_ylabel("Speedup (Sequential / OpenMP)") + ax1.set_title(title) + ax1.grid(True) + + # Add sample count on secondary axis + ax2 = ax1.twinx() + ax2.plot(x, binned["count"], color='gray', marker='o', linestyle='-', label='Sample Count') + ax2.set_ylabel("Number of Samples per Bin", color='gray') + ax2.tick_params(axis='y', labelcolor='gray') + + # Combine legends from both axes + lines_1, labels_1 = ax1.get_legend_handles_labels() + lines_2, labels_2 = ax2.get_legend_handles_labels() + ax1.legend(lines_1 + lines_2, labels_1 + labels_2, loc='upper left') + + plt.tight_layout() + if output_files: + for output_file in output_files: + plt.savefig(output_file) + plt.show() + + +def plot_efficiency_bar(df_seq, df_omp, num_threads, title, output_files: list | None = None): + merged = pd.merge(df_seq, df_omp, on="size", suffixes=("_seq", "_omp")) + merged["speedup"] = merged["time_ms_seq"] / merged["time_ms_omp"] + merged["efficiency"] = merged["speedup"] / num_threads + + plt.figure(figsize=(10, 6)) + bars = plt.bar(merged["size"].astype(str), merged["efficiency"], color='skyblue') + + # Annotate each bar + for bar, val in zip(bars, merged["efficiency"]): + plt.text(bar.get_x() + bar.get_width()/2, val + 0.01, f'{val:.2f}', ha='center', va='bottom', fontsize=8) + + plt.axhline(1.0, linestyle="--", color="red", label="100% Efficiency") + plt.xlabel("Input Size") + plt.ylabel("Efficiency (Speedup / Threads)") + plt.title(title) + plt.ylim(0, 1.0) + plt.xticks(rotation=45, ha='right') + plt.grid(True) + plt.tight_layout() + if output_files: + for output_file in output_files: + plt.savefig(output_file) + plt.show() + + +def plot_efficiency_bar_binned(df_seq, df_omp, num_threads, title, output_files: list | None = None): + merged = pd.merge(df_seq, df_omp, on="size", suffixes=("_seq", "_omp")) + merged["speedup"] = merged["time_ms_seq"] / merged["time_ms_omp"] + merged["efficiency"] = merged["speedup"] / num_threads + merged["log2_size"] = np.log2(merged["size"]).astype(int) + + # Aggregate by log2_size + binned = merged.groupby("log2_size").agg( + avg_efficiency=("efficiency", "mean"), + std_efficiency=("efficiency", "std"), + count=("efficiency", "count") + ).reset_index() + + plt.figure(figsize=(10, 6)) + plt.bar(binned["log2_size"], binned["avg_efficiency"], yerr=binned["std_efficiency"], + color='skyblue', capsize=4) + plt.axhline(1.0, linestyle="--", color="red", label="100% Efficiency") + plt.xlabel("log2(Input Size)") + plt.ylabel("Average Efficiency (Speedup / Threads)") + plt.title(title) + plt.ylim(0, 1.0) + plt.grid(True) + plt.tight_layout() + if output_files: + for output_file in output_files: + plt.savefig(output_file) + plt.show() + + +def plot_multi_thread_speedup(df_all, baseline_label="Sequential", title="Speedup Across Threads", output_files=None): + """ + Plot speedup curves for multiple OpenMP thread configurations against a baseline (e.g., Sequential). + + :param df_all: DataFrame containing all runs, with columns 'size', 'time_ms', and 'label'. + :param baseline_label: Label used for the sequential baseline. + :param title: Plot title. + :param output_files: Optional list of output filenames to save. + """ + # Separate baseline and parallel versions + df_base = df_all[df_all["label"] == baseline_label][["size", "time_ms"]].rename(columns={"time_ms": "time_ms_base"}) + + plt.figure(figsize=(12, 6)) + for label, group in df_all[df_all["label"] != baseline_label].groupby("label"): + merged = pd.merge(df_base, group, on="size") + merged["speedup"] = merged["time_ms_base"] / merged["time_ms"] + merged_sorted = merged.sort_values("size") + plt.plot(merged_sorted["size"], merged_sorted["speedup"], marker='o', label=label) + + plt.axhline(1.0, color='gray', linestyle='--') + plt.xlabel("Input Size") + plt.ylabel("Speedup (vs Sequential)") + plt.title(title) + plt.grid(True) + plt.legend(title="Threads") + plt.tight_layout() + + if output_files: + for output_file in output_files: + plt.savefig(output_file) + plt.show() + + +def plot_speedup_vs_threads(df_seq, df_omp_dict, title, output_files: list | None = None): + """ + Compare binned average speedup for different thread counts on a single plot, with error bars. + """ + plt.figure(figsize=(12, 6)) + for threads, df_omp in sorted(df_omp_dict.items()): + merged = pd.merge(df_seq, df_omp, on="size", suffixes=("_seq", f"_omp_{threads}")) + merged["speedup"] = merged["time_ms_seq"] / merged[f"time_ms_omp_{threads}"] + merged["log2_size"] = np.log2(merged["size"]).astype(int) + binned = merged.groupby("log2_size").agg( + avg_speedup=("speedup", "mean"), + std_speedup=("speedup", "std"), + count=("speedup", "count") + ).reset_index() + plt.errorbar( + binned["log2_size"], binned["avg_speedup"], yerr=binned["std_speedup"], + marker='o', capsize=4, label=f"{threads} threads" + ) + plt.axhline(1.0, color='gray', linestyle='--') + plt.xlabel("log2(Input Size)", fontsize=16+2) + plt.ylabel("Average Speedup (Sequential / OpenMP)", fontsize=16+2) + plt.title(title, fontsize=18+2) + plt.grid(True) + plt.legend(title="Threads", fontsize=14+2, title_fontsize=15+2) + plt.xticks(fontsize=14+2) + plt.yticks(fontsize=14+2) + plt.tight_layout() + if output_files: + for output_file in output_files: + plt.savefig(output_file) + plt.show() + + +def plot_efficiency_vs_threads(df_seq, df_omp_dict, title, output_files: list | None = None): + """ + Compare binned average efficiency for different thread counts on a single plot, with error bars. + """ + plt.figure(figsize=(12, 6)) + for threads, df_omp in sorted(df_omp_dict.items()): + merged = pd.merge(df_seq, df_omp, on="size", suffixes=("_seq", f"_omp_{threads}")) + merged["speedup"] = merged["time_ms_seq"] / merged[f"time_ms_omp_{threads}"] + merged["efficiency"] = merged["speedup"] / threads + merged["log2_size"] = np.log2(merged["size"]).astype(int) + binned = merged.groupby("log2_size").agg( + avg_efficiency=("efficiency", "mean"), + std_efficiency=("efficiency", "std"), + count=("efficiency", "count") + ).reset_index() + plt.errorbar( + binned["log2_size"], binned["avg_efficiency"], yerr=binned["std_efficiency"], + marker='o', capsize=4, label=f"{threads} threads" + ) + plt.axhline(1.0, color='red', linestyle='--', label="100% Efficiency") + plt.xlabel("log2(Input Size)", fontsize=16+2) + plt.ylabel("Average Efficiency (Speedup / Threads)", fontsize=16+2) + plt.title(title, fontsize=18+2) + plt.ylim(0, 1.0) + plt.grid(True) + plt.legend(title="Threads", fontsize=14+2, title_fontsize=15+2) + plt.xticks(fontsize=14+2) + plt.yticks(fontsize=14+2) + plt.tight_layout() + if output_files: + for output_file in output_files: + plt.savefig(output_file) + plt.show() + + +def plot_execution_time_binned(df, title, output_files: list | None = None): + """ + Plot binned average execution time for different benchmarks. + Bins by log2(size) and shows mean and std per label. + """ + df = df.copy() + df["log2_size"] = np.log2(df["size"]).astype(int) + binned = df.groupby(["label", "log2_size"]).agg( + avg_time_ms=("time_ms", "mean"), + std_time_ms=("time_ms", "std"), + count=("time_ms", "count") + ).reset_index() + + plt.figure(figsize=(10, 5)) + for label, group in binned.groupby("label"): + plt.errorbar( + group["log2_size"], group["avg_time_ms"], yerr=group["std_time_ms"], + marker='o', capsize=4, label=label + ) + plt.xlabel("log2(Input Size)") + plt.ylabel("Average Execution Time (ms)") + plt.title(title) + plt.grid(True) + plt.legend() + plt.tight_layout() + if output_files: + for output_file in output_files: + plt.savefig(output_file) + plt.show() + + +if __name__ == "__main__": + import thinkpad, hp, dell + import tkinter as tk + + def run_benchmark(selection): + root.destroy() + if selection == "Thinkpad": + thinkpad.main() + elif selection == "HP": + hp.main() + elif selection == "Dell": + dell.main() + + root = tk.Tk() + root.title("Select Benchmark") + tk.Label(root, text="Which benchmark do you want to show?", font=("Arial", 14)).pack(pady=10) + for bench in ["Thinkpad", "HP", "Dell"]: + tk.Button(root, text=bench, width=20, font=("Arial", 12), + command=lambda b=bench: run_benchmark(b)).pack(pady=5) + root.mainloop() diff --git a/benchmarks/fourier_transform/requirements.txt b/benchmarks/fourier_transform/requirements.txt new file mode 100644 index 0000000..1a4ccbe --- /dev/null +++ b/benchmarks/fourier_transform/requirements.txt @@ -0,0 +1,4 @@ +pandas +numpy +matplotlib +seaborn diff --git a/benchmarks/fourier_transform/thinkpad.py b/benchmarks/fourier_transform/thinkpad.py new file mode 100644 index 0000000..f7d4353 --- /dev/null +++ b/benchmarks/fourier_transform/thinkpad.py @@ -0,0 +1,330 @@ +from plot_performance import * + + +_specs = "(Thinkpad, i7-3632QM CPU @ 2.20GHz)" + + +def _one_d_benchmark(files): + df_seq = load_benchmark(files["1D_Sequential"], "Sequential") + df_omp_2 = load_benchmark(files["1D_OpenMP_2"], "OpenMP 2 threads") + df_omp_4 = load_benchmark(files["1D_OpenMP_4"], "OpenMP 4 threads") + df_omp_8 = load_benchmark(files["1D_OpenMP_8"], "OpenMP 8 threads") + +# plot_execution_time( +# pd.concat([df_seq, df_omp_2, df_omp_4, df_omp_8]), +# "1D FFT Execution Time (All threads)", +# output_files=[ +# "./thinkpad/results/1D_fft_execution_time_all_threads.pdf", +# "./thinkpad/results/1D_fft_execution_time_all_threads.png" +# ] +# ) +# plot_multi_thread_speedup( +# pd.concat([df_seq, df_omp_2, df_omp_4, df_omp_8]), +# "Sequential", +# "1D FFT Speedup (All threads)", +# output_files=[ +# "./thinkpad/results/1D_fft_speedup_all_threads.pdf", +# "./thinkpad/results/1D_fft_speedup_all_threads.png" +# ] +# ) +# plot_speedup_bar( +# df_seq, +# df_omp_2, +# "1D FFT Speedup Bar Chart (2 threads)", +# output_files=[ +# "./thinkpad/results/1D_fft_speedup_bar_2_threads.pdf", +# "./thinkpad/results/1D_fft_speedup_bar_2_threads.png" +# ] +# ) +# plot_speedup_bar( +# df_seq, +# df_omp_4, +# "1D FFT Speedup Bar Chart (4 threads)", +# output_files=[ +# "./thinkpad/results/1D_fft_speedup_bar_4_threads.pdf", +# "./thinkpad/results/1D_fft_speedup_bar_4_threads.png" +# ] +# ) +# plot_speedup_bar( +# df_seq, +# df_omp_8, +# "1D FFT Speedup Bar Chart (8 threads)", +# output_files=[ +# "./thinkpad/results/1D_fft_speedup_bar_8_threads.pdf", +# "./thinkpad/results/1D_fft_speedup_bar_8_threads.png" +# ] +# ) +# plot_efficiency_bar( +# df_seq, +# df_omp_2, +# 2, +# "1D FFT Efficiency Bar Chart (2 threads)", +# output_files=[ +# "./thinkpad/results/1D_fft_efficiency_bar_2_threads.pdf", +# "./thinkpad/results/1D_fft_efficiency_bar_2_threads.png" +# ] +# ) +# plot_efficiency_bar( +# df_seq, +# df_omp_4, +# 4, +# "1D FFT Efficiency Bar Chart (4 threads)", +# output_files=[ +# "./thinkpad/results/1D_fft_efficiency_bar_4_threads.pdf", +# "./thinkpad/results/1D_fft_efficiency_bar_4_threads.png" +# ] +# ) +# plot_efficiency_bar( +# df_seq, +# df_omp_8, +# 8, +# "1D FFT Efficiency Bar Chart (8 threads)", +# output_files=[ +# "./thinkpad/results/1D_fft_efficiency_bar_8_threads.pdf", +# "./thinkpad/results/1D_fft_efficiency_bar_8_threads.png" +# ] +# ) + df_omp_dict = { + 2: df_omp_2, + 4: df_omp_4, + 8: df_omp_8, + } + plot_speedup_vs_threads( + df_seq, + df_omp_dict, + f"1D FFT Speedup vs Threads {_specs}", + output_files=[ + "./thinkpad/results/1D_fft_speedup_vs_threads.pdf", + "./thinkpad/results/1D_fft_speedup_vs_threads.png" + ] + ) + plot_efficiency_vs_threads( + df_seq, + df_omp_dict, + f"1D FFT Efficiency vs Threads {_specs}", + output_files=[ + "./thinkpad/results/1D_fft_efficiency_vs_threads.pdf", + "./thinkpad/results/1D_fft_efficiency_vs_threads.png" + ] + ) + + +def _two_d_benchmark(files): + df_seq = load_benchmark(files["2D_Sequential"], "Sequential") + df_omp_2 = load_benchmark(files["2D_OpenMP_2"], "OpenMP 2 threads") + df_omp_4 = load_benchmark(files["2D_OpenMP_4"], "OpenMP 4 threads") + df_omp_8 = load_benchmark(files["2D_OpenMP_8"], "OpenMP 8 threads") + +# plot_execution_time_binned( +# pd.concat([df_seq, df_omp_2, df_omp_4, df_omp_8]), +# "2D FFT Execution Time (All threads)", +# output_files=[ +# "./thinkpad/results/2D_fft_execution_time_binned_all_threads.pdf", +# "./thinkpad/results/2D_fft_execution_time_binned_all_threads.png" +# ] +# ) +# plot_speedup_binned_with_counts( +# df_seq, +# df_omp_2, +# f"2D FFT Speedup Bar Chart (2 threads)", +# output_files=[ +# "./thinkpad/results/2D_fft_speedup_binned_with_counts_2_threads.pdf", +# "./thinkpad/results/2D_fft_speedup_binned_with_counts_2_threads.png" +# ] +# ) +# plot_speedup_binned_with_counts( +# df_seq, +# df_omp_4, +# f"2D FFT Speedup Bar Chart (4 threads)", +# output_files=[ +# "./thinkpad/results/2D_fft_speedup_binned_with_counts_4_threads.pdf", +# "./thinkpad/results/2D_fft_speedup_binned_with_counts_4_threads.png" +# ] +# ) +# plot_speedup_binned_with_counts( +# df_seq, +# df_omp_8, +# f"2D FFT Speedup Bar Chart (8 threads)", +# output_files=[ +# "./thinkpad/results/2D_fft_speedup_binned_with_counts_8_threads.pdf", +# "./thinkpad/results/2D_fft_speedup_binned_with_counts_8_threads.png" +# ] +# ) +# plot_efficiency_bar_binned( +# df_seq, +# df_omp_2, +# 2, +# "2D FFT Efficiency Bar Chart (2 threads)", +# output_files=[ +# "./thinkpad/results/2D_fft_efficiency_bar_binned_2_threads.pdf", +# "./thinkpad/results/2D_fft_efficiency_bar_binned_2_threads.png" +# ] +# ) +# plot_efficiency_bar_binned( +# df_seq, +# df_omp_4, +# 4, +# "2D FFT Efficiency Bar Chart (4 threads)", +# output_files=[ +# "./thinkpad/results/2D_fft_efficiency_bar_binned_4_threads.pdf", +# "./thinkpad/results/2D_fft_efficiency_bar_binned_4_threads.png" +# ] +# ) +# plot_efficiency_bar_binned( +# df_seq, +# df_omp_8, +# 8, +# "2D FFT Efficiency Bar Chart (8 threads)", +# output_files=[ +# "./thinkpad/results/2D_fft_efficiency_bar_binned_8_threads.pdf", +# "./thinkpad/results/2D_fft_efficiency_bar_binned_8_threads.png" +# ] +# ) + df_omp_dict = { + 2: df_omp_2, + 4: df_omp_4, + 8: df_omp_8, + } + plot_speedup_vs_threads( + df_seq, + df_omp_dict, + f"2D FFT Speedup vs Threads {_specs}", + output_files=[ + "./thinkpad/results/2D_fft_speedup_vs_threads.pdf", + "./thinkpad/results/2D_fft_speedup_vs_threads.png" + ] + ) + plot_efficiency_vs_threads( + df_seq, + df_omp_dict, + f"2D FFT Efficiency vs Threads {_specs}", + output_files=[ + "./thinkpad/results/2D_fft_efficiency_vs_threads.pdf", + "./thinkpad/results/2D_fft_efficiency_vs_threads.png" + ] + ) + + +def _three_d_benchmark(files): + df_seq = load_benchmark(files["3D_Sequential"], "Sequential") + df_omp_2 = load_benchmark(files["3D_OpenMP_2"], "OpenMP 2 threads") + df_omp_4 = load_benchmark(files["3D_OpenMP_4"], "OpenMP 4 threads") + df_omp_8 = load_benchmark(files["3D_OpenMP_8"], "OpenMP 8 threads") + +# plot_execution_time( +# pd.concat([df_seq, df_omp_2, df_omp_4, df_omp_8]), +# "3D FFT Execution Time (All threads)", +# output_files=[ +# "./thinkpad/results/3D_fft_execution_time_all_threads.pdf", +# "./thinkpad/results/3D_fft_execution_time_all_threads.png" +# ] +# ) +# plot_speedup_binned_with_counts( +# df_seq, +# df_omp_2, +# f"3D FFT Speedup Bar Chart (2 threads)", +# output_files=[ +# "./thinkpad/results/3D_fft_speedup_binned_with_counts_2_threads.pdf", +# "./thinkpad/results/3D_fft_speedup_binned_with_counts_2_threads.png" +# ] +# ) +# plot_speedup_binned_with_counts( +# df_seq, +# df_omp_4, +# f"3D FFT Speedup Bar Chart (4 threads)", +# output_files=[ +# "./thinkpad/results/3D_fft_speedup_binned_with_counts_4_threads.pdf", +# "./thinkpad/results/3D_fft_speedup_binned_with_counts_4_threads.png" +# ] +# ) +# plot_speedup_binned_with_counts( +# df_seq, +# df_omp_8, +# f"3D FFT Speedup Bar Chart (8 threads)", +# output_files=[ +# "./thinkpad/results/3D_fft_speedup_binned_with_counts_8_threads.pdf", +# "./thinkpad/results/3D_fft_speedup_binned_with_counts_8_threads.png" +# ] +# ) +# plot_efficiency_bar_binned( +# df_seq, +# df_omp_2, +# 2, +# "3D FFT Efficiency Bar Chart (2 threads)", +# output_files=[ +# "./thinkpad/results/3D_fft_efficiency_bar_binned_2_threads.pdf", +# "./thinkpad/results/3D_fft_efficiency_bar_binned_2_threads.png" +# ] +# ) +# plot_efficiency_bar_binned( +# df_seq, +# df_omp_4, +# 4, +# "3D FFT Efficiency Bar Chart (4 threads)", +# output_files=[ +# "./thinkpad/results/3D_fft_efficiency_bar_binned_4_threads.pdf", +# "./thinkpad/results/3D_fft_efficiency_bar_binned_4_threads.png" +# ] +# ) +# plot_efficiency_bar_binned( +# df_seq, +# df_omp_8, +# 8, +# "3D FFT Efficiency Bar Chart (8 threads)", +# output_files=[ +# "./thinkpad/results/3D_fft_efficiency_bar_binned_8_threads.pdf", +# "./thinkpad/results/3D_fft_efficiency_bar_binned_8_threads.png" +# ] +# ) + df_omp_dict = { + 2: df_omp_2, + 4: df_omp_4, + 8: df_omp_8, + } + plot_speedup_vs_threads( + df_seq, + df_omp_dict, + f"3D FFT Speedup vs Threads {_specs}", + output_files=[ + "./thinkpad/results/3D_fft_speedup_vs_threads.pdf", + "./thinkpad/results/3D_fft_speedup_vs_threads.png" + ] + ) + plot_efficiency_vs_threads( + df_seq, + df_omp_dict, + f"3D FFT Efficiency vs Threads {_specs}", + output_files=[ + "./thinkpad/results/3D_fft_efficiency_vs_threads.pdf", + "./thinkpad/results/3D_fft_efficiency_vs_threads.png" + ] + ) + + + +def main(): + files = { + "1D_Sequential": "./thinkpad/thinkpad-1D_results_sequential_2025-05-19_12-07-52.json", + "1D_OpenMP_8": "./thinkpad/thinkpad-1D_results_openmp_threads_8_2025-05-18_17-13-24.json", + "1D_OpenMP_4": "./thinkpad/thinkpad-1D_results_openmp_threads_4_2025-05-25_15-33-57.json", + "1D_OpenMP_2": "./thinkpad/thinkpad-1D_results_openmp_threads_2_2025-05-25_15-37-47.json", + + "2D_Sequential": "./thinkpad/thinkpad-2D_results_sequential_2025-05-26_10-21-59.json", + "2D_OpenMP_8": "./thinkpad/thinkpad-2D_results_openmp_threads_8_2025-05-19_12-41-02.json", + "2D_OpenMP_4": "./thinkpad/thinkpad-2D_results_openmp_threads_4_2025-05-25_15-13-23.json", + "2D_OpenMP_2": "./thinkpad/thinkpad-2D_results_openmp_threads_2_2025-05-25_15-19-40.json", + + "3D_Sequential": "./thinkpad/thinkpad-3D_results_sequential_2025-05-18_16-06-50.json", + "3D_OpenMP_8": "./thinkpad/thinkpad-3D_results_openmp_threads_8_2025-05-19_22-47-15.json", + "3D_OpenMP_4": "./thinkpad/thinkpad-3D_results_openmp_threads_4_2025-05-25_13-26-36.json", + "3D_OpenMP_2": "./thinkpad/thinkpad-3D_results_openmp_threads_2_2025-05-25_14-18-53.json" + } + + ### 1D FFT Performance Analysis + _one_d_benchmark(files) + + #### 2D FFT Performance Analysis + _two_d_benchmark(files) + + #### 3D FFT Performance Analysis + _three_d_benchmark(files) \ No newline at end of file diff --git a/benchmarks/fourier_transform/thinkpad/results/.gitkeep b/benchmarks/fourier_transform/thinkpad/results/.gitkeep new file mode 100644 index 0000000..e69de29 diff --git a/benchmarks/fourier_transform/thinkpad/results/1D_fft_efficiency_vs_threads.pdf b/benchmarks/fourier_transform/thinkpad/results/1D_fft_efficiency_vs_threads.pdf new file mode 100644 index 0000000..bf6f780 Binary files /dev/null and b/benchmarks/fourier_transform/thinkpad/results/1D_fft_efficiency_vs_threads.pdf differ diff --git a/benchmarks/fourier_transform/thinkpad/results/1D_fft_efficiency_vs_threads.png b/benchmarks/fourier_transform/thinkpad/results/1D_fft_efficiency_vs_threads.png new file mode 100644 index 0000000..796af52 Binary files /dev/null and b/benchmarks/fourier_transform/thinkpad/results/1D_fft_efficiency_vs_threads.png differ diff --git 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element (2^0) is not included in the returned vector. + * @param max_pow The maximum power of two to generate. Default is 22, then 4'194'304. + * @return A vector containing the powers of two. + */ +inline std::vector generatePowersOfTwo(const size_t max_pow = 22) { + // cache the powers of two to avoid recomputing them for each call + static std::unordered_map> cache; + const auto it = cache.find(max_pow); + if (it != cache.end()) { + return it->second; + } + // generate the powers of two from 2^1 to 2^max_pow + std::vector powers; + for (size_t i = 1; i <= max_pow; ++i) { + // 2^i is equivalent to shifting 1 left by i bits + // e.g., 2^3 = 1 << 3 = 8 (0...0001000) + // 2^4 = 1 << 4 = 16 (0...00010000) + // 2^5 = 1 << 5 = 32 (0...00100000) + powers.push_back(1 << i); + } + cache[max_pow] = powers; + return powers; +} + +/** + * Generates a random input vector of complex numbers. + * + * It flattens the input dimensions into a single vector of complex numbers. + * So if the input is 2x3x4, it will create a vector of size 24 (2*3*4). + * + * @tparam N The number of dimensions. + * @param dims The dimensions of the input vector. + * @param seed The seed for the random number generator (default is 42). + * @return A vector of complex numbers with the specified dimensions. + */ +template +std::vector> generateInput(const std::array& dims, const size_t seed = 42) { + // calculate the total size of the input vector + // dims is an array of size N, so we need to multiply all its elements + // to get the total size + size_t total = 1; + for (const size_t d : dims) total *= d; + + // use a random number generator to fill the vector with random complex numbers + // use a fixed seed for reproducibility + std::mt19937 gen(seed); + // uniform distribution in the range [-1.0, 1.0] + std::uniform_real_distribution<> dist(-1.0, 1.0); + + // create a vector of complex numbers with the specified size + std::vector> data(total); + for (auto& x : data) + x = {dist(gen), dist(gen)}; + return data; +} + +/** + * Generates all valid shapes for a given number of dimensions. + * + * A valid shape is defined as a combination of powers of two that do not exceed + * the specified maximum total size. + * + * The function uses backtracking to explore all combinations of powers of two + * for N dimensions, ensuring that the product of the dimensions does not exceed + * the maximum total size. + * + * @tparam N The number of dimensions. + * @param max_total_size The maximum total size for the shapes. + * @param min The minimum value for the dimensions (optional). + * @return A vector of arrays representing the valid shapes. + */ +template +std::vector> generateValidShapes( + const size_t max_total_size, + const size_t min +) { + std::vector> results; + // generate the powers of two up to the maximum total size + const std::vector powers = generatePowersOfTwo(); + + std::array current; + /** + * Backtracking function to generate all combinations of powers of two. + * + * Backtracking is a recursive search that builds a solution step-by-step, + * abandoning any path that cannot possibly lead to a valid solution. + * + * More specifically, it explores all combinations of powers of two + * for N dimensions, ensuring that the product of the dimensions + * does not exceed the maximum total size. + * + * In general, Backtracking is a general algorithmic technique for: + * 1. Building candidates for a solution incrementally; + * 2. Abandoning ("backtracking") a candidate + * as soon as it's clear it's invalid or won’t lead to a full solution. + * + * In this case, it: + * 1. Goes "depth" levels deep (from 0 to N-1); + * 2. Maintains the current product of dimensions. + * It explores a tree of possible values, + * trying all combinations of powers of two across N dimensions, + * but cuts off branches when the product exceeds max_total_size. + * + * @param depth The current depth in the recursion (dimension index). + * @param product The current product of the dimensions. + */ + std::function backtrack = [&](size_t depth, const size_t product) { + // base case: filled all N dimensions + if (depth == N) { + // current array now represents one valid shape (e.g., {256, 32, 2}) + // store it in the results + results.push_back(current); + return; + } + // recursive case: iterate over all powers of two + for (size_t p : powers) { + // skip values minus of min + if (p < min) continue; + // check if the product exceeds the maximum total size + // if it does, break the loop to avoid unnecessary calculations + if (product * p > max_total_size) break; + // try placing power p at dimension depth + // (if adding it would exceed max_total_size, prev. step, + // stop, because all future powers are larger) + current[depth] = p; + // recursively call backtrack for the next dimension + // (product is updated to include the new dimension) + // (e.g., if current is {256, 32, 2} and p is 4, + // product becomes 256 * 32 * 2 * 4) + backtrack(depth + 1, product * p); + } + }; + // start backtracking from the first dimension (0) and initial product of 1 + // (1 is the multiplicative identity, so it doesn't affect the product) + backtrack(0, 1); + return results; +} + +/** + * Generates all valid shapes for a given number of dimensions. + * + * A valid shape is defined as a combination of powers of two that do not exceed + * the specified maximum total size. + * + * The function uses backtracking to explore all combinations of powers of two + * for N dimensions, ensuring that the product of the dimensions does not exceed + * the maximum total size. + * + * @tparam N The number of dimensions. + * @param max_total_size The maximum total size for the shapes. + * @return A vector of arrays representing the valid shapes. + */ +template +std::vector> generateValidShapes( + const size_t max_total_size +) { + std::vector> results; + const std::vector powers = generatePowersOfTwo(); + + std::array current; + std::function backtrack = [&](size_t depth, const size_t product) { + if (depth == N) { + results.push_back(current); + return; + } + for (size_t p : powers) { + if (product * p > max_total_size) break; + current[depth] = p; + backtrack(depth + 1, product * p); + } + }; + backtrack(0, 1); + return results; +} + +/** + * **Naive** function to get the value of a command-line argument. + * + * The argument should be in the format "-key=value". + * If the key is found, the value is returned; otherwise, std::nullopt is returned. + * + * @param argc The number of command-line arguments. + * @param argv The command-line arguments. + * @param key The key to search for (without the leading '-'). + * @param double_dash Whether to use "--" instead of "-" for the key. + * @param equals Whether the key-value pair is separated by "=" (default is true). + * @return A string containing the value if found, or an empty string if not found. + */ +inline std::string getArgValue( + const int argc, + char** argv, + const std::string& key, + const bool double_dash = false, + const bool equals = true +) { + const std::string prefix = (double_dash ? "--" : "-") + key + (equals ? "=" : ""); + for (int i = 1; i < argc; ++i) { + std::string arg = argv[i]; + if (arg.find(prefix) == 0) { + return arg.substr(prefix.size()); + } + } + return ""; +} + + +#endif // UTILS_HPP diff --git a/build-benchmarks.sh b/build-benchmarks.sh new file mode 100755 index 0000000..4e69742 --- /dev/null +++ b/build-benchmarks.sh @@ -0,0 +1,44 @@ +#!/bin/bash + +RED='\033[0;31m' +GREEN='\033[0;32m' +YELLOW='\033[1;33m' +NC='\033[0m' # No Color + +./build-essential.sh || exit 1 + +echo -e "${GREEN}~ Install Google Benchmark ~${NC}" +if ls /usr/local/lib/libbenchmark* &> /dev/null && ls /usr/local/include/benchmark/ &> /dev/null +then + echo "Google Benchmark is already installed. Skipping installation..." +else + echo -e "${YELLOW}Google Benchmark is not installed. Installing...${NC}" + mkdir -p "tmp-google-benchmark-build" && cd "tmp-google-benchmark-build" || exit 1 + git clone https://github.com/google/benchmark.git + cd benchmark || exit 1 + cmake -DCMAKE_BUILD_TYPE=Release -DBENCHMARK_DOWNLOAD_DEPENDENCIES=ON -DBENCHMARK_ENABLE_TESTING=OFF -S . -B build + cmake --build build --config Release -j "$(nproc)" + sudo cmake --install build + cd ../.. || exit 1 + rm -rf tmp-google-benchmark-build + echo -e "${GREEN}Google Benchmark installed successfully!${NC}" +fi +echo "" + + +echo -e "${GREEN}~ Compile CMakeLists.txt in $(pwd)/build ~${NC}" +mkdir -p "build" && cd "build" || exit 1 +cmake .. --preset ninja-dev-benchmark --log-level=WARNING || exit 1 +cd ninja-dev-benchmark || exit 1 +echo "" + + +echo -e "${GREEN}~ Compile project + benchmarks ~${NC}" +start_time=$(date +%s) +ninja all || exit 1 +end_time=$(date +%s) +elapsed_time=$((end_time - start_time)) +echo "Built in ~$elapsed_time seconds" +cd ../.. || exit 1 +echo "Run examples using ./build/ninja-dev-benchmark/benchmarks/benchmark-name" +echo "" \ No newline at end of file diff --git a/build-essential.sh b/build-essential.sh new file mode 100755 index 0000000..359ecd7 --- /dev/null +++ b/build-essential.sh @@ -0,0 +1,42 @@ +#!/bin/bash + +RED='\033[0;31m' +GREEN='\033[0;32m' +YELLOW='\033[1;33m' +NC='\033[0m' # No Color + +echo -e "${GREEN}~ Build Essential for Signal Processing Library ~${NC}" +if ! dpkg -l | grep 'build-essential' &> /dev/null +then + echo -e "${YELLOW}Build Essential is not installed. Installing...${NC}" + sudo apt-get update + sudo apt-get install -y build-essential + echo -e "${GREEN}Build Essential installed successfully!${NC}" +else + echo "Build Essential is already installed." +fi +echo "" + +echo -e "${GREEN}~ Install CMake ~${NC}" +if ! dpkg -l | grep 'cmake' &> /dev/null +then + echo -e "${YELLOW}CMake is not installed. Installing...${NC}" + sudo apt-get update + sudo apt-get install -y cmake + echo -e "${GREEN}CMake installed successfully!${NC}" +else + echo "CMake is already installed." +fi +echo "" + +echo -e "${GREEN}~ Install Ninja ~${NC}" +if ! dpkg -l | grep 'ninja-build' &> /dev/null +then + echo -e "${YELLOW}Ninja is not installed. Installing...${NC}" + sudo apt-get update + sudo apt-get install -y ninja-build + echo -e "${GREEN}Ninja installed successfully!${NC}" +else + echo "Ninja is already installed." +fi +echo "" diff --git a/build-examples.sh b/build-examples.sh new file mode 100755 index 0000000..95c0c2e --- /dev/null +++ b/build-examples.sh @@ -0,0 +1,64 @@ +#!/bin/bash + +RED='\033[0;31m' +GREEN='\033[0;32m' +YELLOW='\033[1;33m' +NC='\033[0m' # No Color + +./build-essential.sh || exit 1 + +echo -e "${GREEN}~ Install OpenCV ~${NC}" +if ! dpkg -l | grep 'libopencv-dev' &> /dev/null +then + echo -e "${YELLOW}OpenCV is not installed. Installing...${NC}" + sudo apt update || exit 1 + sudo apt install -y libopencv-dev || exit 1 +else + echo "OpenCV is already installed." +fi +echo "" + + +echo -e "${GREEN} ~ Install gnuplot ~${NC}" +if ! dpkg -l | grep 'gnuplot' &> /dev/null +then + echo -e "${YELLOW}Gnuplot is not installed. Installing...${NC}" + sudo apt-get update + sudo apt-get install -y gnuplot + echo -e "${GREEN}Gnuplot installed successfully!${NC}" +else + echo "Gnuplot is already installed." +fi +echo "" + + +echo -e "${GREEN}~ Checking for Matplot++ ~${NC}" +if ! test -e "$(pwd)/examples/external/matplotplusplus/CMakeLists.txt"; then + echo -e "${YELLOW}Matplot++ was not found. Cloning...${NC}" + git submodule update --init --recursive + if [ $? -ne 0 ]; then + echo -e "${RED}Failed to clone Matplot++. Please check your internet connection.${NC}" + exit 1 + fi + echo -e "${GREEN}Matplot++ cloned successfully!${NC}" +else + echo "Matplot++ is already cloned." +fi +echo "" + + +echo -e "${GREEN}~ Compile CMakeLists.txt in $(pwd)/build ~${NC}" +mkdir -p "build" && cd "build" || exit 1 +cmake .. --preset ninja-dev --log-level=WARNING || exit 1 +cd ninja-dev || exit 1 +echo "" + + +echo -e "${GREEN}~ Compile project + examples ~${NC}" +start_time=$(date +%s) +ninja all || exit 1 +end_time=$(date +%s) +elapsed_time=$((end_time - start_time)) +echo "Built in ~$elapsed_time seconds" +echo "Run examples using ./build/ninja-dev/examples/example-name" +echo "" diff --git a/clean-all.sh b/clean-all.sh new file mode 100755 index 0000000..4476ac1 --- /dev/null +++ b/clean-all.sh @@ -0,0 +1,38 @@ +#!/bin/bash + +RED='\033[0;31m' +GREEN='\033[0;32m' +YELLOW='\033[1;33m' +NC='\033[0m' # No Color + +if [ -e ./build/make-dev/Makefile ]; then + cd build/make-dev || exit 1 + make -f ./Makefile -C . clean + cd ../.. +fi + +if [ -e ./build/make-lib/Makefile ]; then + cd build/make-lib || exit 1 + make -f ./Makefile -C . clean + cd ../.. +fi + +if [ -e ./build/ninja-dev/build.ninja ]; then + cd build/ninja-dev || exit 1 + ninja clean + cd ../.. +fi + +if [ -e ./build/ninja-lib/build.ninja ]; then + cd build/ninja-lib || exit 1 + ninja clean + cd ../.. +fi + +if [ -e ./build/ninja-dev-benchmark/build.ninja ]; then + cd build/ninja-dev-benchmark || exit 1 + ninja clean + cd ../.. +fi + +echo -e "${GREEN}All cleaned up, good!${NC}" \ No newline at end of file diff --git a/A_Parallel_Implementation_of_the_Fast_Fourier_Transform_Algorithm.pdf b/docs/A_Parallel_Implementation_of_the_Fast_Fourier_Transform_Algorithm.pdf similarity index 100% rename from A_Parallel_Implementation_of_the_Fast_Fourier_Transform_Algorithm.pdf rename to docs/A_Parallel_Implementation_of_the_Fast_Fourier_Transform_Algorithm.pdf diff --git a/Description_FFT.pdf b/docs/Description_FFT.pdf similarity index 100% rename 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b/docs/reconstructed-dog-bn-threshold-0.5.png differ diff --git a/summer_project_gillian_smith.pdf b/docs/summer_project_gillian_smith.pdf similarity index 100% rename from summer_project_gillian_smith.pdf rename to docs/summer_project_gillian_smith.pdf diff --git a/examples/CMakeLists.txt b/examples/CMakeLists.txt new file mode 100644 index 0000000..e2093c9 --- /dev/null +++ b/examples/CMakeLists.txt @@ -0,0 +1,137 @@ +########## +# OpenCV # +########## +find_package(OpenCV) +if (NOT OpenCV_FOUND) + message(WARNING "OpenCV not found. Please install it with 'sudo apt-get install libopencv-dev'.") +else () + include_directories( ${OpenCV_INCLUDE_DIRS} ) + message(STATUS "OpenCV found: ${OpenCV_VERSION}") +endif () + +############# +# Matplot++ # +############# +# Detect if gnuplot is installed (required by matplot++) +find_program(GNUPLOT_EXECUTABLE gnuplot) +if (NOT GNUPLOT_EXECUTABLE) + message(FATAL_ERROR "Gnuplot not found. Please install it with 'sudo apt-get install gnuplot'.") +endif() +# Detect if matplot++ is installed +if (NOT EXISTS "${CMAKE_SOURCE_DIR}/examples/external/matplotplusplus") + message(FATAL_ERROR "Matplot++ not found. Please clone it with 'git submodule update --init --recursive'.") +endif() +add_subdirectory(external/matplotplusplus) +message(STATUS "Matplot++ found: ${MATPLOT_VERSION}") + + +################################### +# Fast Fourier Transform Examples # +################################### +# Basic 1D FFT example with matplot++ +add_executable( + example-fourier_transform_solver + fourier_transform_solver.cpp +) + +# 1D FFT example to compare performance of different FFT libraries +add_executable( + example-fourier_transform_solver_performance + fourier_transform_solver_performance.cpp +) + +# Application of 2D FFT to image processing +add_executable( + example-fourier_transform_solver_image + fourier_transform_solver_image.cpp +) + +target_link_libraries(example-fourier_transform_solver_performance + PRIVATE signal_processing +) +target_link_libraries(example-fourier_transform_solver + PRIVATE matplot + PRIVATE signal_processing +) +target_link_libraries(example-fourier_transform_solver_image + PRIVATE signal_processing +) +if (OpenCV_FOUND) + # Application of 3D FFT to video processing + add_executable( + example-fourier_transform_solver_video + fourier_transform_solver_video.cpp + ) + # Application of 3D FFT to video processing (RGB) + add_executable( + example-fourier_transform_solver_video_rgb + fourier_transform_solver_video_rgb.cpp + ) + target_link_libraries(example-fourier_transform_solver_video + PRIVATE ${OpenCV_LIBS} + PRIVATE signal_processing + ) + target_link_libraries(example-fourier_transform_solver_video_rgb + PRIVATE ${OpenCV_LIBS} + PRIVATE signal_processing + ) +else () + message(WARNING "OpenCV not found. Skipping video processing examples.") +endif () + + +################################### +# Haar Wavelet Transform Examples # +################################### +# Basic 1D Haar Wavelet Transform example +add_executable( + example-haar_wavelet_transform_solver_1d + haar_wavelet_transform_1d.cpp +) +target_link_libraries( + example-haar_wavelet_transform_solver_1d + PRIVATE signal_processing +) +# Basic 2D Haar Wavelet Transform example +add_executable( + example-haar_wavelet_transform_solver_2d + haar_wavelet_transform_2d.cpp +) +target_link_libraries( + example-haar_wavelet_transform_solver_2d + PRIVATE signal_processing +) +# Harr Wavelet Transform +add_executable( + example-haar_wavelet_transform_solver + haar_wavelet_transform.cpp +) +target_link_libraries( + example-haar_wavelet_transform_solver + PRIVATE signal_processing +) + + +################################### +# JPEG Image Compression Examples # +################################### +# Basic JPEG image compression example +add_executable( + example-jpeg_compression + jpeg_compression.cpp +) +target_link_libraries( + example-jpeg_compression + PRIVATE matplot + PRIVATE signal_processing +) +# 1D DCT example to compare performance of different DCT libraries +add_executable( + example-dct_solver_performance + dct_solver_performance.cpp +) +target_link_libraries( + example-dct_solver_performance + PRIVATE signal_processing + PRIVATE matplot +) \ No newline at end of file diff --git a/examples/dct_solver_performance.cpp b/examples/dct_solver_performance.cpp new file mode 100644 index 0000000..346710e --- /dev/null +++ b/examples/dct_solver_performance.cpp @@ -0,0 +1,265 @@ +/** + * @file dct_solver_performance.cpp + * @brief A simple demo to measure the performance of the DCT solver in sequential and parallel modes. + * + * @details The demo generates a signal in time or space domain, computes the DCT and IDCT of the signal, + * and measures the time taken for each operation. + * It is not intended to be a comprehensive performance test, but rather a simple demonstration of the + * performance of the DCT solver. + */ + +#include +#include +#include +#include +#include "matplot/matplot.h" + +#include "signal_processing/signal_processing.hpp" + +/** + * This demo measures the performance of the DCT solver in sequential and parallel modes. + */ +void sequential_vs_parallel_dct(const std::vector& signal, std::vector& sequential_dct, std::vector& parallel_dct){ + // Prepare the solver + sp::dct::solver::DiscreteCosineTransform dct_solver= sp::dct::solver::DiscreteCosineTransform(); + // you can use the solver in two modes: + // 1. in-place computation (default): the input vector is modified in place and + // the result is stored in the same vector + // 2. out-of-place computation: the input vector is not modified and the result is stored in a new vector + + // ================================================ Sequential DCT ================================================ + const auto start_time_seq = std::chrono::high_resolution_clock::now(); + dct_solver.compute(signal, sequential_dct, sp::dct::solver::ComputationMode::SEQUENTIAL); + const auto end_time_seq = std::chrono::high_resolution_clock::now(); + + printf( + "Time taken for sequential DCT: %ld ms\n", + std::chrono::duration_cast(end_time_seq - start_time_seq).count() + ); + + // ================================================= Parallel DCT ================================================= + const auto start_time_par = std::chrono::high_resolution_clock::now(); + dct_solver.compute(signal, parallel_dct, sp::dct::solver::ComputationMode::OPENMP); + const auto end_time_par = std::chrono::high_resolution_clock::now(); + + printf( + "Time taken for parallel (OpenMP, CPU) DCT: %ld ms\n", + std::chrono::duration_cast(end_time_par - start_time_par).count() + ); + printf( + "With %d threads (CPU), the speedup is: %ld\n", + omp_get_max_threads(), + (std::chrono::duration_cast(end_time_seq - start_time_seq).count()) / + (std::chrono::duration_cast(end_time_par - start_time_par).count()) + ); + + // uncomment the following lines to save the result to a file + // const CsvSignalSaver csv_signal_saver; + // csv_signal_saver.saveToFile(sequential_dct, "examples/output/sequential_dct_signal"); + // csv_signal_saver.saveToFile(parallel_dct, "examples/output/parallel_dct_signal"); +} + +/** + * This demo measures the performance of the Inverse DCT solver in sequential and parallel modes. + */ +void sequential_vs_parallel_inverse_dct(const std::vector& sequential_dct, const std::vector& parallel_dct, std::vector& sequential_idct, std::vector& parallel_idct){ + // Prepare the solver + sp::dct::solver::InverseDiscreteCosineTransform idct_solver= sp::dct::solver::InverseDiscreteCosineTransform(); + + // ============================================ Sequential Inverse DCT ============================================ + const auto start_time_seq = std::chrono::high_resolution_clock::now(); + idct_solver.compute( + sequential_dct, sequential_idct, sp::dct::solver::ComputationMode::SEQUENTIAL + ); + const auto end_time_seq = std::chrono::high_resolution_clock::now(); + + printf( + "Time taken for sequential Inverse DCT: %ld ms\n", + std::chrono::duration_cast(end_time_seq - start_time_seq).count() + ); + + // ============================================= Parallel Inverse DCT ============================================= + const auto start_time_par = std::chrono::high_resolution_clock::now(); + idct_solver.compute( + parallel_dct, parallel_idct, sp::dct::solver::ComputationMode::OPENMP + ); + const auto end_time_par = std::chrono::high_resolution_clock::now(); + + printf( + "Time taken for parallel (OpenMP, CPU) Inverse DCT: %ld ms\n", + std::chrono::duration_cast(end_time_par - start_time_par).count() + ); + printf( + "With %d threads (CPU), the speedup is: %ld\n\n", + omp_get_max_threads(), + (std::chrono::duration_cast(end_time_seq - start_time_seq).count()) / + (std::chrono::duration_cast(end_time_par - start_time_par).count()) + ); + + // uncomment the following lines to save the result to a file + // const CsvSignalSaver csv_signal_saver; + // csv_signal_saver.saveToFile(sequential_idct, "examples/output/sequential_idct_signal"); + // csv_signal_saver.saveToFile(parallel_idct, "examples/output/parallel_idct_signal"); +} + +// Function that scales DCT coefficients to frequency +std::vector scale_dct_frequencies(int num_coefficients, double sampling_rate, double signal_duration) { + std::vector scaled_freq(num_coefficients); + for (int i = 0; i < num_coefficients; ++i) { + scaled_freq[i] = static_cast(i) * (sampling_rate / (2.0 * (sampling_rate * signal_duration))); + } + return scaled_freq; +} + +int main() { + // Set parameters for signal generation + double signal_duration = 1.0; // signal duration in seconds + double sampling_rate = 500.0; // sampling rate in Hz + // Calculate the number of samples + int signal_length = static_cast(signal_duration * sampling_rate); + + //Generate signal(t) = sin(2*pi*10*t) + sin(2*pi*20*t) + sin(2*pi*30*t)+sin(2*pi*50*t)+2 + std::vector signal(signal_length); + for (int i = 0; i < signal_length; ++i) { + double t = static_cast(i) / sampling_rate; // calculate the time at each sample + signal[i] = std::sin(2.0 * M_PI * 10.0 * t) + std::sin(2.0 * M_PI * 20.0 * t) + std::sin(2.0 * M_PI * 30.0 * t) + std::sin(2.0 * M_PI * 50.0 * t) + 2.0; + } + + std::vector sequential_dct(signal_length); + std::vector parallel_dct(signal_length); + std::vector sequential_idct(signal_length); + std::vector parallel_idct(signal_length); + +/* + // ============================================= Configuration Loading ============================================= + // load the configuration from the sample file + // print number of threads used by OpenMP + const std::string file_path = "examples/resources/performance_fft_config.json"; + // load the configuration from the file + const auto loader = new sp::config::JSONConfigurationLoader(); + loader->loadConfigurationFromFile(file_path); + const auto json_loaded = new sp::config::JsonFieldHandler(loader->getConfigurationData()); + // get the simulation parameters + const int signal_length = json_loaded->getSignalLength(); + const double *frequency = new double(json_loaded->getHzFrequency()); + const double *phase = new double(json_loaded->getPhase()); + const double *noise = new double(json_loaded->getNoise()); + const std::string signal_domain = json_loaded->getSignalDomain(); + // get the seed if it exists, otherwise set it to nullopt + const std::optional seed = json_loaded->hasSeed() ? std::optional(json_loaded->getSeed()) : std::nullopt; + // prepare the signal saver and use the unique pointer to manage the memory + const auto csv_signal_saver = sp::saver::CsvSignalSaver(); + // free unused memory + delete loader; + delete json_loaded; + + + // ================================================ Generate Signal ================================================ + // generate the signal + std::vector signal(signal_length); + if (signal_domain == "time") { + // time domain + printf("Generating time domain signal of length: %d.\n", signal_length); + sp::signal_gen::TimeDomainSignalGenerator domain_signal_generator( + json_loaded->hasSeed() ? json_loaded->getSeed() : 0 + ); + signal = domain_signal_generator.generateReal1DSignal(signal_length, *frequency, *phase, *noise); + } else { + // space domain + printf("Generating space domain signal of length: %d.\n", signal_length); + sp::signal_gen::SpaceDomainSignalGenerator domain_signal_generator( + json_loaded->hasSeed() ? json_loaded->getSeed() : 0 + ); + signal = domain_signal_generator.generateReal1DSignal(signal_length, *frequency, *phase, *noise); + } +*/ + + // uncomment the following line to save the generated signal to a file + // csv_signal_saver->saveToFile(signal, "examples/output/input_signal"); + + + // ========================================== Sequential vs. Parallel DCT ========================================== + printf("\n\nSequential vs. Parallel DCT\n"); + sequential_vs_parallel_dct(signal, sequential_dct, parallel_dct); + + + // ====================================== Sequential vs. Parallel Inverse DCT ====================================== + printf("\n\nSequential vs. Parallel Inverse DCT\n"); + sequential_vs_parallel_inverse_dct(sequential_dct, parallel_dct, sequential_idct, parallel_idct); + + + + // =================================================== Plotting =================================================== + // Linear space for time axis + std::vector t = matplot::linspace(0, signal_duration, signal_length); + // Calculate scaled frequency axis for DCT + std::vector scaled_freq = scale_dct_frequencies(signal_length, sampling_rate, signal_duration); + + // create the plot for magnitude comparison + auto magnitude_figure = matplot::figure(); + // title of the window + magnitude_figure->name("Magnitude 1D DCT Signal Comparison"); + // title of the plot + magnitude_figure->title("Magnitude Comparison"); + // size of the window (width, height) + magnitude_figure->size(1300, 900); + // position of the window (x, y) + magnitude_figure->x_position(0); + magnitude_figure->y_position(0); + // plot + auto plot = magnitude_figure->add_subplot(6,1,1); + plot->height(0.17); + matplot::plot(t, signal); + matplot::title("Original Signal"); + matplot::ylabel("Amplitude"); + matplot::xlabel("Time [s]"); + plot = magnitude_figure->add_subplot(6,1,3); + plot->height(0.17); + matplot::plot(scaled_freq, sequential_dct); + matplot::title("Sequential DCT"); + matplot::ylabel("Magnitude"); + matplot::xlabel("Frequency [Hz]"); + plot = magnitude_figure->add_subplot(6,1,5); + plot->height(0.17); + matplot::plot(scaled_freq, parallel_dct); + matplot::title("Parallel DCT"); + matplot::ylabel("Magnitude"); + matplot::xlabel("Frequency [Hz]"); + // show the plot and block the execution + magnitude_figure->show(); + + // create the plot for original signal comparison + auto comparison_idct_figure = matplot::figure(); + // title of the window + comparison_idct_figure->name("Plot 1D FFT Signal Comparison"); + // title of the plot + comparison_idct_figure->title("Original Signal vs. Inverse FFT Signal"); + // size of the window (width, height) + comparison_idct_figure->size(1300, 900); + // position of the window (x, y) + comparison_idct_figure->x_position(0); + comparison_idct_figure->y_position(0); + // plot + plot = comparison_idct_figure->add_subplot(3,1,0); + plot->height(0.17); + matplot::plot(t, signal); + matplot::title("Original Signal"); + matplot::xlabel("Time [s]"); + matplot::ylabel("Amplitude"); + plot = comparison_idct_figure->add_subplot(3,1,1); + plot->height(0.17); + matplot::plot(t, sequential_idct); + matplot::title("Sequential IDCT"); + matplot::xlabel("Time [s]"); + matplot::ylabel("Amplitude"); + plot = comparison_idct_figure->add_subplot(3,1,2); + plot->height(0.17); + matplot::plot(t, parallel_idct); + matplot::title("Parallel IDCT"); + matplot::xlabel("Time [s]"); + matplot::ylabel("Amplitude"); + // show the plot and block the execution + comparison_idct_figure->show(); + + return 0; +} \ No newline at end of file diff --git a/examples/external/matplotplusplus b/examples/external/matplotplusplus new file mode 160000 index 0000000..5d01eb3 --- /dev/null +++ b/examples/external/matplotplusplus @@ -0,0 +1 @@ +Subproject commit 5d01eb3695b07634a2b6642fd423740dea9b026c diff --git a/examples/fourier_transform_solver.cpp b/examples/fourier_transform_solver.cpp new file mode 100644 index 0000000..f80f8b6 --- /dev/null +++ b/examples/fourier_transform_solver.cpp @@ -0,0 +1,285 @@ +/** + * @file fourier_transform_solver.cpp + * @brief This file demonstrates the use of the FFT and IFFT algorithms + * to compute the FFT and IFFT of a signal. + * + * @details It uses the FFT algorithm (Cooley-Tukey) to compute the FFT of a signal. + */ + +#include +#include +#include "matplot/matplot.h" +#include "signal_processing/signal_processing.hpp" + +/** + * This demo illustrates the difference between sequential and parallel FFTs. + * + * It uses the FFT algorithm (Cooley-Tukey) to compute the FFT of a signal. + * + * It computes the FFT in both sequential and parallel modes and measures the time taken for each computation. + * + * The FFT library allows you to modify the input vector in place or perform an out-of-place computation. + * Also, you don't need to create a solver for each mode + * because you can select a mode when calling the compute function. + * @param signal The input signal to be transformed. + */ +void sequential_vs_parallel_fft(const std::vector>& signal) { + const int signal_length = signal.size(); + // prepare the vectors for the FFT + std::vector> sequential_fft(signal_length); + std::vector> parallel_fft(signal_length); + std::array V1{static_cast(signal_length)}; + sp::fft::solver::FastFourierTransform<1> solver(V1); + // you can use the solver in two modes: + // 1. in-place computation (default): the input vector is modified in place and + // the result is stored in the same vector + // 2. out-of-place computation: the input vector is not modified and the result is stored in a new vector + const auto start_time_seq = std::chrono::high_resolution_clock::now(); + solver.compute(signal, sequential_fft, sp::fft::solver::ComputationMode::SEQUENTIAL); + const auto end_time_seq = std::chrono::high_resolution_clock::now(); + printf( + "Time taken for sequential FFT: %ld ms\n", + std::chrono::duration_cast(end_time_seq - start_time_seq).count() + ); + const auto start_time_par = std::chrono::high_resolution_clock::now(); + solver.compute(signal, parallel_fft, sp::fft::solver::ComputationMode::OPENMP); + const auto end_time_par = std::chrono::high_resolution_clock::now(); + printf( + "Time taken for parallel FFT: %ld ms\n", + std::chrono::duration_cast(end_time_par - start_time_par).count() + ); + // save the result to a file + const sp::saver::CsvSignalSaver csv_signal_saver; + csv_signal_saver.saveToFile(sequential_fft, "examples/output/sequential_fft_signal"); + csv_signal_saver.saveToFile(parallel_fft, "examples/output/parallel_fft_signal"); +} + +/** + * This demo illustrates the difference between sequential and parallel Inverse FFTs. + * + * It uses the Inverse FFT algorithm (Cooley-Tukey) to compute the Inverse FFT of a signal. + * + * It computes the Inverse FFT in both sequential and parallel modes and measures the time taken for each computation. + * + * The Inverse FFT library allows you to modify the input vector in place or perform an out-of-place computation. + * Also, you don't need to create a solver for each mode + * because you can select a mode when calling the compute function. + * @param signal The input signal to be transformed. + */ +void sequential_vs_parallel_inverse_fft(const std::vector>& signal) { + const int signal_length = signal.size(); + // prepare the vectors for the Inverse FFT + std::vector> sequential_ifft(signal_length); + std::vector> parallel_ifft(signal_length); + // prepare the solver + std::array V2{static_cast(signal_length)}; + sp::fft::solver::InverseFastFourierTransform<1> inverse_solver(V2); + // sequential Inverse FFT + const auto start_time_seq = std::chrono::high_resolution_clock::now(); + inverse_solver.compute( + signal, sequential_ifft, sp::fft::solver::ComputationMode::SEQUENTIAL + ); + const auto end_time_seq = std::chrono::high_resolution_clock::now(); + printf( + "Time taken for sequential Inverse FFT: %ld ms\n", + std::chrono::duration_cast(end_time_seq - start_time_seq).count() + ); + const auto start_time_par = std::chrono::high_resolution_clock::now(); + inverse_solver.compute( + signal, parallel_ifft, sp::fft::solver::ComputationMode::OPENMP + ); + const auto end_time_par = std::chrono::high_resolution_clock::now(); + printf( + "Time taken for parallel Inverse FFT: %ld ms\n", + std::chrono::duration_cast(end_time_par - start_time_par).count() + ); + + // save the result to a file + const sp::saver::CsvSignalSaver csv_signal_saver; + csv_signal_saver.saveToFile(sequential_ifft, "examples/output/sequential_ifft_signal"); + csv_signal_saver.saveToFile(parallel_ifft, "examples/output/parallel_ifft_signal"); +} + +/** + * This demo plots the original signal, the FFT and the Inverse FFT. + * + * It uses the Matplot++ library to plot the signals. + * @param signal The input signal to be transformed. + * @param signal_domain The domain of the signal (time or space). + * @param frequency The frequency of the signal. + * @param phase The phase of the signal. + * @param noise The noise of the signal. + */ +void plot_signal_fft_and_ifft( + const std::vector>& signal, + const std::string &signal_domain, + const double frequency, const double phase, const double noise +) { + const int signal_length = signal.size(); + // prepare the data for plotting + std::vector plot_magnitude(signal_length), + plot_magnitude_fft(signal_length), + plot_magnitude_ifft(signal_length); + std::vector plot_phase(signal_length), + plot_phase_fft(signal_length), + plot_phase_ifft(signal_length); + // copy the original signal into the fft_signal + std::vector> fft_signal = signal; + std::vector> inverse_fft_signal(signal_length); + // prepare the solver + std::array V3{static_cast(signal_length)}; + sp::fft::solver::FastFourierTransform<1> solver(V3); + std::array V4{static_cast(signal_length)}; + sp::fft::solver::InverseFastFourierTransform<1> inverse_solver(V4); + // compute the FFT + // note: the solver is used in place, so the input vector is modified; + // the result of the FFT is then used to compute the inverse FFT; + // this demonstrates the solver's versatility + solver.compute(fft_signal, sp::fft::solver::ComputationMode::SEQUENTIAL); + inverse_solver.compute( + fft_signal, inverse_fft_signal, sp::fft::solver::ComputationMode::SEQUENTIAL + ); + + // check if the inverse_fft_signal is the same of signal + // if not, print the difference + for (int i = 0; i < signal_length; ++i) { + if (signal[i].real() - inverse_fft_signal[i].real() > 1e-6) { + printf( + "Difference between original signal and inverse FFT signal at index %d: %f\n", + i, std::abs(signal[i] - inverse_fft_signal[i]) + ); + } + if (signal[i].imag() - inverse_fft_signal[i].imag() > 1e-6) { + printf( + "(Imag) Difference between original signal and inverse FFT signal at index %d: %f\n", + i, std::abs(signal[i] - inverse_fft_signal[i]) + ); + } + } + + // plot the comparison + const std::vector x = matplot::linspace(0, signal_length - 1, signal_length); + // convert to real values + for (int i = 0; i < signal_length; ++i) { + plot_magnitude[i] = std::abs(signal[i]); + plot_magnitude_fft[i] = std::abs(fft_signal[i]); + plot_magnitude_ifft[i] = std::abs(inverse_fft_signal[i]); + plot_phase[i] = std::arg(signal[i]); + plot_phase_fft[i] = std::arg(fft_signal[i]); + plot_phase_ifft[i] = std::arg(inverse_fft_signal[i]); + } + + const auto comparison_figure = matplot::figure(); + // title of the window + comparison_figure->name("Plot 1D FFT Signal Comparison"); + // title of the plot + std::ostringstream title; + title << "Original 1D Signal vs. IFFT and FFT (" << signal_domain << " domain, L = " + << signal_length << ", f = " + << std::fixed << std::setprecision(2) << frequency << " Hz, phase = " + << std::fixed << std::setprecision(2) << phase << ", noise = " + << std::fixed << std::setprecision(2) << noise << ")"; + comparison_figure->title(title.str()); + // size of the window (width, height) + comparison_figure->size(1200, 1200); + // position of the window (x, y) + comparison_figure->x_position(0); + comparison_figure->y_position(0); + // plot + comparison_figure->add_subplot(3,2,0); + matplot::title("Original Signal (Magnitude)"); + matplot::plot(x, plot_magnitude); + comparison_figure->add_subplot(3,2, 1); + matplot::title("Original Signal (Phase)"); + matplot::plot(x, plot_phase); + + comparison_figure->add_subplot(3,2, 2); + matplot::title("Inverse FFT (Magnitude)"); + matplot::plot(x, plot_magnitude_ifft); + comparison_figure->add_subplot(3,2, 3); + matplot::title("Inverse FFT (Phase)"); + matplot::plot(x, plot_phase_ifft); + + comparison_figure->add_subplot(3,2, 4); + matplot::title("FFT (Magnitude)"); + matplot::plot(x, plot_magnitude_fft); + comparison_figure->add_subplot(3,2, 5); + matplot::title("FFT (Phase)"); + matplot::plot(x, plot_phase_fft); + + comparison_figure->save( + "examples/output/fft_signal_comparison_" + + sp::utils::timestamp::createReadableTimestamp("%Y%m%d_%H%M%S") + + ".png" + ); + comparison_figure->save( + "examples/output/fft_signal_comparison_" + + sp::utils::timestamp::createReadableTimestamp("%Y%m%d_%H%M%S") + + ".svg" + ); + comparison_figure->show(); +} + + +int main() { + // ============================================= Configuration Loading ============================================= + // load the configuration from the sample file + const std::string file_path = "examples/resources/fft_config.json"; + // load the configuration from the file + const auto loader = new sp::config::JSONConfigurationLoader(); + loader->loadConfigurationFromFile(file_path); + const auto json_loaded = new sp::config::JsonFieldHandler(loader->getConfigurationData()); + // get the simulation parameters + const int signal_length = json_loaded->getSignalLength(); + const double *frequency = new double(json_loaded->getHzFrequency()); + const double *phase = new double(json_loaded->getPhase()); + const double *noise = new double(json_loaded->getNoise()); + const std::string *signal_domain = new std::string(json_loaded->getSignalDomain()); + // prepare the signal saver and use the unique pointer to manage the memory + const auto csv_signal_saver = std::make_unique(); + // free unused memory + delete loader; + + + // ================================================ Generate Signal ================================================ + // generate the signal + std::vector> signal(signal_length); + if (*signal_domain == "time") { + // time domain + printf("Generating time domain signal of length: %d.\n", signal_length); + sp::signal_gen::TimeDomainSignalGenerator domain_signal_generator( + json_loaded->hasSeed() ? json_loaded->getSeed() : 0 + ); + signal = domain_signal_generator.generate1DSignal(signal_length, *frequency, *phase, *noise); + } else { + // space domain + printf("Generating space domain signal of length: %d.\n", signal_length); + sp::signal_gen::SpaceDomainSignalGenerator domain_signal_generator( + json_loaded->hasSeed() ? json_loaded->getSeed() : 0 + ); + signal = domain_signal_generator.generate1DSignal(signal_length, *frequency, *phase, *noise); + } + // and save it to a file + csv_signal_saver->saveToFile(signal, "examples/output/input_signal"); + + + // ========================================== Sequential vs. Parallel FFT ========================================== + printf("\n\nSequential vs. Parallel FFT\n"); + sequential_vs_parallel_fft(signal); + + + // ====================================== Sequential vs. Parallel Inverse FFT ====================================== + printf("\n\nSequential vs. Parallel Inverse FFT\n"); + // pass the fft result as input + std::vector> fft_res(signal_length); + std::array V5{static_cast(signal_length)}; + sp::fft::solver::FastFourierTransform<1> tmp_solver(V5); + tmp_solver.compute(signal, fft_res, sp::fft::solver::ComputationMode::OPENMP); + sequential_vs_parallel_inverse_fft(fft_res); + + + // =================================================== Plotting =================================================== + plot_signal_fft_and_ifft(signal, *signal_domain, *frequency, *phase, *noise); + + return 0; +} diff --git a/examples/fourier_transform_solver_image.cpp b/examples/fourier_transform_solver_image.cpp new file mode 100644 index 0000000..b6b5d19 --- /dev/null +++ b/examples/fourier_transform_solver_image.cpp @@ -0,0 +1,117 @@ +/** + * @file fourier_transform_solver_image.cpp + * @brief This file demonstrates the correctness of the FFT and IFFT algorithms (2D) + * by applying them to an image. + */ + +#include +#include +#include +#include + +#include "stb/stb_image.h" + +#include "signal_processing/signal_processing.hpp" + + +int main() { + /** + * Ask the user to choose between the dog image and the eiffel-tower image. + */ + printf("Do you want to use the dog image or the eiffel-tower image? (d/e) "); + char choice; + std::cin >> choice; + if (choice != 'd' && choice != 'e') { + std::cerr << "Invalid choice. Please enter 'd' for dog image or 'e' for eiffel-tower image." << std::endl; + return 1; + } + printf("You chose %s image\n", choice == 'd' ? "dog" : "eiffel-tower"); + + /** + * Load the image using stb_image.h + */ + int width, height, channels; + const std::string filepath_in = choice == 'd' ? "examples/resources/dog.png" : "examples/resources/eiffel-tower.png"; + std::ostringstream filepath_out_oss; + filepath_out_oss << "examples/output/fft-" << choice + << sp::utils::timestamp::createReadableTimestamp("_%Y%m%d_%H%M%S") + << ".png"; + // check if the output folder exists + struct stat info; + if (stat("examples/output", &info) != 0 || !(info.st_mode & S_IFDIR)) { + std::cerr << "Output folder does not exist. Creating it..." << std::endl; + mkdir("examples/output", 0755); + } + // create the output file path + const std::string filepath_out = filepath_out_oss.str(); + // load the image + unsigned char* image = sp::img::loadImage( + filepath_in.c_str(), + width, height, channels + ); + printf("Image loaded successfully: (h: %d, w: %d), %d channel(s)\n", height, width, channels); + + /** + * Convert the image to a vector of complex numbers. + */ + std::vector> R, G, B; + R.reserve(width * height); + G.reserve(width * height); + B.reserve(width * height); + + for (int y = 0; y < height; ++y) + for (int x = 0; x < width; ++x) { + const int idx = (y * width + x) * 3; + R.emplace_back(image[idx + 0], 0.0); + G.emplace_back(image[idx + 1], 0.0); + B.emplace_back(image[idx + 2], 0.0); + } + printf("Image converted to complex numbers\n"); + + + /** + * Core: Compute the FFT and IFFT of the image. + */ + printf("Starting FFT computation...\n"); + + const auto start_time = std::chrono::high_resolution_clock::now(); + sp::fft::solver::FastFourierTransform<2> solver( + std::array{static_cast(height), static_cast(width)} + ); + sp::fft::solver::InverseFastFourierTransform<2> inverse_solver( + std::array{static_cast(height), static_cast(width)} + ); + auto computation_mode = sp::fft::solver::ComputationMode::OPENMP; + solver.compute(R, computation_mode); + printf("R FFT computed\n"); + solver.compute(G, computation_mode); + printf("G FFT computed\n"); + solver.compute(B, computation_mode); + printf("B FFT computed\n"); + inverse_solver.compute(R, computation_mode); + printf("R IFFT computed\n"); + inverse_solver.compute(G, computation_mode); + printf("G IFFT computed\n"); + inverse_solver.compute(B, computation_mode); + printf("B IFFT computed\n"); + const auto end_time = std::chrono::high_resolution_clock::now(); + const auto duration = std::chrono::duration_cast(end_time - start_time).count(); + + printf("FFT computation completed. Time taken %ld ms\n", duration); + + /** + * Save the FFT result to a file. + */ + std::vector output(width * height * 3); + for (size_t i = 0; i < R.size(); ++i) { + output[i * 3 + 0] = static_cast(R[i].real() > 255.0 ? 255 : (R[i].real() < 0.0 ? 0 : R[i].real())); + output[i * 3 + 1] = static_cast(G[i].real() > 255.0 ? 255 : (G[i].real() < 0.0 ? 0 : G[i].real())); + output[i * 3 + 2] = static_cast(B[i].real() > 255.0 ? 255 : (B[i].real() < 0.0 ? 0 : B[i].real())); + } + printf("Image converted back to unsigned char\n"); + // check if the image was saved successfully + sp::img::saveRGBImage(filepath_out.c_str(), output, width, height); + printf("Image saved successfully in %s\n", filepath_out.c_str()); + + return 0; +} diff --git a/examples/fourier_transform_solver_performance.cpp b/examples/fourier_transform_solver_performance.cpp new file mode 100644 index 0000000..a3b9c84 --- /dev/null +++ b/examples/fourier_transform_solver_performance.cpp @@ -0,0 +1,157 @@ +/** + * @file fourier_transform_solver_performance.cpp + * @brief A simple demo to measure the performance of the FFT solver in sequential and parallel modes. + * + * @details The demo generates a signal in time or space domain, computes the FFT and IFFT of the signal, + * and measures the time taken for each operation. + * It is not intended to be a comprehensive performance test, but rather a simple demonstration of the + * performance of the FFT solver. + */ + +#include +#include +#include +#include + +#include "signal_processing/signal_processing.hpp" + +/** + * This demo measures the performance of the FFT solver in sequential and parallel modes. + */ +void sequential_vs_parallel_fft(const std::vector>& signal){ + const int signal_length = signal.size(); + // prepare the vectors for the FFT + std::vector> sequential_fft(signal_length); + std::vector> parallel_fft(signal_length); + sp::fft::solver::FastFourierTransform<1> solver(std::array{static_cast(signal_length)}); + // you can use the solver in two modes: + // 1. in-place computation (default): the input vector is modified in place and + // the result is stored in the same vector + // 2. out-of-place computation: the input vector is not modified and the result is stored in a new vector + const auto start_time_seq = std::chrono::high_resolution_clock::now(); + solver.compute(signal, sequential_fft, sp::fft::solver::ComputationMode::SEQUENTIAL); + const auto end_time_seq = std::chrono::high_resolution_clock::now(); + printf( + "Time taken for sequential FFT: %ld ms\n", + std::chrono::duration_cast(end_time_seq - start_time_seq).count() + ); + const auto start_time_par = std::chrono::high_resolution_clock::now(); + solver.compute(signal, parallel_fft, sp::fft::solver::ComputationMode::OPENMP); + const auto end_time_par = std::chrono::high_resolution_clock::now(); + printf( + "Time taken for parallel (OpenMP, CPU) FFT: %ld ms\n", + std::chrono::duration_cast(end_time_par - start_time_par).count() + ); + printf( + "With %d threads (CPU), the speedup is: %ld\n", + omp_get_max_threads(), + std::chrono::duration_cast(end_time_seq - start_time_seq).count() / + std::chrono::duration_cast(end_time_par - start_time_par).count() + ); + // uncomment the following lines to save the result to a file + // const CsvSignalSaver csv_signal_saver; + // csv_signal_saver.saveToFile(sequential_fft, "examples/output/sequential_fft_signal"); + // csv_signal_saver.saveToFile(parallel_fft, "examples/output/parallel_fft_signal"); +} + +/** + * This demo measures the performance of the Inverse FFT solver in sequential and parallel modes. + */ +void sequential_vs_parallel_inverse_fft(const std::vector>& signal){ + const int signal_length = signal.size(); + // prepare the vectors for the Inverse FFT + std::vector> sequential_ifft(signal_length); + std::vector> parallel_ifft(signal_length); + // prepare the solver + sp::fft::solver::InverseFastFourierTransform<1> inverse_solver( + std::array{static_cast(signal_length)} + ); + // sequential Inverse FFT + const auto start_time_seq = std::chrono::high_resolution_clock::now(); + inverse_solver.compute( + signal, sequential_ifft, sp::fft::solver::ComputationMode::SEQUENTIAL + ); + const auto end_time_seq = std::chrono::high_resolution_clock::now(); + printf( + "Time taken for sequential Inverse FFT: %ld ms\n", + std::chrono::duration_cast(end_time_seq - start_time_seq).count() + ); + const auto start_time_par = std::chrono::high_resolution_clock::now(); + inverse_solver.compute( + signal, parallel_ifft, sp::fft::solver::ComputationMode::OPENMP + ); + const auto end_time_par = std::chrono::high_resolution_clock::now(); + printf( + "Time taken for parallel (OpenMP, CPU) Inverse FFT: %ld ms\n", + std::chrono::duration_cast(end_time_par - start_time_par).count() + ); + printf( + "With %d threads (CPU), the speedup is: %ld\n", + omp_get_max_threads(), + std::chrono::duration_cast(end_time_seq - start_time_seq).count() / + std::chrono::duration_cast(end_time_par - start_time_par).count() + ); + // uncomment the following lines to save the result to a file + // const CsvSignalSaver csv_signal_saver; + // csv_signal_saver.saveToFile(sequential_ifft, "examples/output/sequential_ifft_signal"); + // csv_signal_saver.saveToFile(parallel_ifft, "examples/output/parallel_ifft_signal"); +} + + +int main() { + // ============================================= Configuration Loading ============================================= + // load the configuration from the sample file + // print number of threads used by OpenMP + const std::string file_path = "examples/resources/performance_fft_config.json"; + // load the configuration from the file + const auto loader = new sp::config::JSONConfigurationLoader(); + loader->loadConfigurationFromFile(file_path); + const auto json_loaded = new sp::config::JsonFieldHandler(loader->getConfigurationData()); + // get the simulation parameters + const int signal_length = json_loaded->getSignalLength(); + const double *frequency = new double(json_loaded->getHzFrequency()); + const double *phase = new double(json_loaded->getPhase()); + const double *noise = new double(json_loaded->getNoise()); + const std::string signal_domain = json_loaded->getSignalDomain(); + // prepare the signal saver and use the unique pointer to manage the memory + const auto csv_signal_saver = sp::saver::CsvSignalSaver(); + // free unused memory + delete loader; + + + // ================================================ Generate Signal ================================================ + // generate the signal + std::vector> signal(signal_length); + if (signal_domain == "time") { + // time domain + printf("Generating time domain signal of length: %d.\n", signal_length); + sp::signal_gen::TimeDomainSignalGenerator domain_signal_generator( + json_loaded->hasSeed() ? json_loaded->getSeed() : 0 + ); + signal = domain_signal_generator.generate1DSignal(signal_length, *frequency, *phase, *noise); + } else { + // space domain + printf("Generating space domain signal of length: %d.\n", signal_length); + sp::signal_gen::SpaceDomainSignalGenerator domain_signal_generator( + json_loaded->hasSeed() ? json_loaded->getSeed() : 0 + ); + signal = domain_signal_generator.generate1DSignal(signal_length, *frequency, *phase, *noise); + } + // uncomment the following line to save the generated signal to a file + // csv_signal_saver->saveToFile(signal, "examples/output/input_signal"); + + + // ========================================== Sequential vs. Parallel FFT ========================================== + printf("\n\nSequential vs. Parallel FFT\n"); + sequential_vs_parallel_fft(signal); + + + // ====================================== Sequential vs. Parallel Inverse FFT ====================================== + printf("\n\nSequential vs. Parallel Inverse FFT\n"); + // pass the fft result as input + const std::vector> fft_res(signal_length); + sp::fft::solver::FastFourierTransform<1> tmp_solver(std::array{static_cast(signal_length)}); + sequential_vs_parallel_inverse_fft(fft_res); + + return 0; +} diff --git a/examples/fourier_transform_solver_video.cpp b/examples/fourier_transform_solver_video.cpp new file mode 100644 index 0000000..15f974d --- /dev/null +++ b/examples/fourier_transform_solver_video.cpp @@ -0,0 +1,132 @@ +/** + * @file fourier_transform_solver_video.cpp + * @brief This program demonstrates how to apply 3D FFT and IFFT + * on a video using OpenCV and the Fast Fourier Transform (FFT) library. + * + * @details This example uses the Cooley-Tukey algorithm to perform FFT and IFFT + * on a 3D volume of frames extracted from a video. + */ + +#include +#include +#include +#include + +#include "opencv2/videoio.hpp" +#include "opencv2/imgproc.hpp" +#include "opencv2/core/mat.hpp" +#include "opencv2/core/types.hpp" +#include "opencv2/core/hal/interface.h" + +#include "signal_processing/signal_processing.hpp" + +int main() { + /** + * 1. Load the Video using OpenCV + */ + std::ostringstream filepath_out_oss; + filepath_out_oss << "examples/output/fft-" + << sp::utils::timestamp::createReadableTimestamp("%Y%m%d_%H%M%S") + << ".avi"; + // check if the output folder exists + struct stat info; + if (stat("examples/output", &info) != 0 || !(info.st_mode & S_IFDIR)) { + std::cerr << "Output folder does not exist. Creating it..." << std::endl; + mkdir("examples/output", 0755); + } + cv::VideoCapture cap("examples/resources/cats-resize.mp4"); + if (!cap.isOpened()) { + std::cerr << "Error opening video file." << std::endl; + return -1; + } + printf("Video loaded successfully.\n"); + + /** + * 2. Extract and Store Frames + */ + std::vector frames; + cv::Mat frame; + for (int i = 0; i < 256; ++i) + { + if (!cap.read(frame)) { + std::cerr << "Error reading frame " << i << std::endl; + break; + } + cv::cvtColor(frame, frame, cv::COLOR_BGR2GRAY); // Optional: use grayscale for simplicity + + // crop to 1024*1024 + // int x = (frame.cols - 1024) / 2; + // int y = (frame.rows - 1024) / 2; + // cv::Rect roi(x, y, 1024, 1024); + // frame = frame(roi); + + frame.convertTo(frame, CV_64F); // Ensure double precision for FFT + frames.push_back(frame); + } + int depth = frames.size(); // Number of frames + int height = frames[0].rows; + int width = frames[0].cols; + printf("Extracted %d frames of size %dx%d.\n", depth, height, width); + + + /** + * 3. Create an array to give to FFT; Row-Major order! + */ + std::vector> volume_data(depth * height * width); + for (int z = 0; z < depth; ++z) + for (int y = 0; y < height; ++y) + for (int x = 0; x < width; ++x) { + int idx = z * height * width + y * width + x; + volume_data[idx] = std::complex(frames[z].at(y, x), 0.0); + } + printf("Volume data flattened for FFT.\n"); + + + /** + * 4. Apply Cooley-Tukey 3D FFT + */ + auto start_time = std::chrono::high_resolution_clock::now(); + sp::fft::solver::FastFourierTransform<3> solver( + {static_cast(depth), static_cast(height), static_cast(width)} + ); + sp::fft::solver::InverseFastFourierTransform<3> i_solver( + {static_cast(depth), static_cast(height), static_cast(width)} + ); + solver.compute(volume_data, sp::fft::solver::ComputationMode::OPENMP); + i_solver.compute(volume_data, sp::fft::solver::ComputationMode::OPENMP); + auto end_time = std::chrono::high_resolution_clock::now(); + std::chrono::duration elapsed = end_time - start_time; + printf("FFT and IFFT applied.\n"); + printf("FFT computation time: %.2f seconds\n", elapsed.count()); + + /** + * 5. Reconstruct the frames from the FFT output + */ + std::vector reconstructed_frames; + for (int z = 0; z < depth; ++z) { + cv::Mat frame(height, width, CV_64F); + for (int y = 0; y < height; ++y) + for (int x = 0; x < width; ++x) { + int idx = z * height * width + y * width + x; + frame.at(y, x) = volume_data[idx].real(); + } + frame.convertTo(frame, CV_8U); + reconstructed_frames.push_back(frame); + } + printf("Reconstructed frames from FFT.\n"); + + /** + * 6. Save the reconstructed frames as a video + */ + cv::VideoWriter writer( + filepath_out_oss.str(), + cv::VideoWriter::fourcc('M','J','P','G'), + 60, + cv::Size(width, height), + false + ); + for (const auto& f : reconstructed_frames) + writer.write(f); + writer.release(); + printf("Reconstructed video saved as %s.\n", filepath_out_oss.str().c_str()); +} diff --git a/examples/fourier_transform_solver_video_rgb.cpp b/examples/fourier_transform_solver_video_rgb.cpp new file mode 100644 index 0000000..7db812b --- /dev/null +++ b/examples/fourier_transform_solver_video_rgb.cpp @@ -0,0 +1,188 @@ +/** + * @file fourier_transform_solver_video_rgb.cpp + * @brief This program demonstrates how to apply 3D FFT and IFFT + * on a video using OpenCV and the Fast Fourier Transform (FFT) library. + * + * @details The program extracts frames from a video, applies FFT and IFFT + * on the RGB channels separately, and reconstructs the video. + */ + +#include +#include +#include +#include + +#include "opencv2/videoio.hpp" +#include "opencv2/imgproc.hpp" +#include "opencv2/core/mat.hpp" +#include "opencv2/core/types.hpp" +#include "opencv2/core/hal/interface.h" + +#include "signal_processing/signal_processing.hpp" + +int main() { + /** + * 1. Load the Video using OpenCV + */ + const std::string input_file = "examples/resources/cats-resize.mp4"; + std::ostringstream filepath_out_oss; + filepath_out_oss << "examples/output/fft-" + << sp::utils::timestamp::createReadableTimestamp("%Y%m%d_%H%M%S") + << ".avi"; + // check if the output folder exists + struct stat info; + if (stat("examples/output", &info) != 0 || !(info.st_mode & S_IFDIR)) { + std::cerr << "Output folder does not exist. Creating it..." << std::endl; + mkdir("examples/output", 0755); + } + cv::VideoCapture cap(input_file); + if (!cap.isOpened()) { + std::cerr << "Error opening video file." << std::endl; + return -1; + } + printf("Video loaded successfully.\n"); + + /** + * 2. Extract and Store Frames + */ + cv::Mat frame; + std::vector frames_r, frames_g, frames_b; + for (int i = 0; i < 256; ++i) + { + if (!cap.read(frame)) break; + + // crop to 1024*1024 + // int x = (frame.cols - 1024) / 2; + // int y = (frame.rows - 1024) / 2; + // cv::Rect roi(x, y, 1024, 1024); + // frame = frame(roi); + + std::vector channels(3); + cv::split(frame, channels); // BGR + + for (int c = 0; c < 3; ++c) + channels[c].convertTo(channels[c], CV_64F); + + frames_b.push_back(channels[0]); + frames_g.push_back(channels[1]); + frames_r.push_back(channels[2]); + } + int depth = frames_b.size(); // Number of frames + int height = frames_b[0].rows; + int width = frames_b[0].cols; + printf("Extracted %d frames of size %dx%d.\n", depth, height, width); + + + /** + * 3. Create a 3D Array and Apply FFT + */ + std::vector> volume_r(depth * height * width); + std::vector> volume_g(depth * height * width); + std::vector> volume_b(depth * height * width); + + # pragma omp parallel for + for (int z = 0; z < depth; ++z) + for (int y = 0; y < height; ++y) + for (int x = 0; x < width; ++x) { + int idx = z * height * width + y * width + x; + volume_r[idx] = std::complex(frames_r[z].at(y, x), 0.0); + volume_g[idx] = std::complex(frames_g[z].at(y, x), 0.0); + volume_b[idx] = std::complex(frames_b[z].at(y, x), 0.0); + } + printf("Volume data flattened for FFT.\n"); + + /** + * 4. Apply Cooley-Tukey 3D FFT + */ + sp::fft::solver::FastFourierTransform<3> solver( + {static_cast(depth), static_cast(height), static_cast(width)} + ); + sp::fft::solver::InverseFastFourierTransform<3> i_solver( + {static_cast(depth), static_cast(height), static_cast(width)} + ); + + auto start_time = std::chrono::high_resolution_clock::now(); + solver.compute(volume_r, sp::fft::solver::ComputationMode::OPENMP); + auto end_time = std::chrono::high_resolution_clock::now(); + std::chrono::duration elapsed = end_time - start_time; + printf("R FFT: %f seconds\n", elapsed.count()); + + + start_time = std::chrono::high_resolution_clock::now(); + i_solver.compute(volume_r, sp::fft::solver::ComputationMode::OPENMP); + end_time = std::chrono::high_resolution_clock::now(); + elapsed = end_time - start_time; + printf("R IFFT: %f seconds\n", elapsed.count()); + + + start_time = std::chrono::high_resolution_clock::now(); + solver.compute(volume_g, sp::fft::solver::ComputationMode::OPENMP); + end_time = std::chrono::high_resolution_clock::now(); + elapsed = end_time - start_time; + printf("G FFT: %f seconds\n", elapsed.count()); + + + start_time = std::chrono::high_resolution_clock::now(); + i_solver.compute(volume_g, sp::fft::solver::ComputationMode::OPENMP); + end_time = std::chrono::high_resolution_clock::now(); + elapsed = end_time - start_time; + printf("G IFFT: %f seconds\n", elapsed.count()); + + + start_time = std::chrono::high_resolution_clock::now(); + solver.compute(volume_b, sp::fft::solver::ComputationMode::OPENMP); + end_time = std::chrono::high_resolution_clock::now(); + elapsed = end_time - start_time; + printf("B FFT: %f seconds\n", elapsed.count()); + + + start_time = std::chrono::high_resolution_clock::now(); + i_solver.compute(volume_b, sp::fft::solver::ComputationMode::OPENMP); + end_time = std::chrono::high_resolution_clock::now(); + elapsed = end_time - start_time; + printf("B IFFT: %f seconds\n", elapsed.count()); + + + /** + * 5. Reconstruct Frames + */ + std::vector reconstructed_frames; + for (int z = 0; z < depth; ++z) { + cv::Mat r(height, width, CV_64F); + cv::Mat g(height, width, CV_64F); + cv::Mat b(height, width, CV_64F); + + for (int y = 0; y < height; ++y) + for (int x = 0; x < width; ++x) { + int idx = z * height * width + y * width + x; + r.at(y, x) = volume_r[idx].real(); + g.at(y, x) = volume_g[idx].real(); + b.at(y, x) = volume_b[idx].real(); + } + + cv::Mat r8u, g8u, b8u; + r.convertTo(r8u, CV_8U); + g.convertTo(g8u, CV_8U); + b.convertTo(b8u, CV_8U); + + std::vector channels = {b8u, g8u, r8u}; // OpenCV = BGR + cv::Mat color; + cv::merge(channels, color); + + reconstructed_frames.push_back(color); + } + printf("Reconstructed frames from FFT.\n"); + + /** + * 6. Save the Reconstructed Video + */ + cv::VideoWriter writer( + filepath_out_oss.str(), + cv::VideoWriter::fourcc('M','J','P','G'), + 60, cv::Size(width, height), true + ); + for (const auto& f : reconstructed_frames) + writer.write(f); + writer.release(); + printf("Reconstructed video saved to %s\n", filepath_out_oss.str().c_str()); +} diff --git a/examples/haar_wavelet_transform.cpp b/examples/haar_wavelet_transform.cpp new file mode 100644 index 0000000..d86e45b --- /dev/null +++ b/examples/haar_wavelet_transform.cpp @@ -0,0 +1,213 @@ +#include +#include +#include +#include + +#include "stb/stb_image.h" +#include "stb/stb_image_write.h" + +#include "signal_processing/signal_processing.hpp" + +void show(std::vector> matrix){ + + std::cout << "Matrix: " << std::endl << std::endl << "\t"; + for(int i = 0; i < 8; i++){ + for(int j = 0; j < 8; j++){ + std::cout << matrix[i][j] << "\t"; + } + std::cout << std::endl << "\t"; + } + std::cout << std::endl << std::endl; +} + +void compare(std::vector> A, std::vector> B){ + if(A.size() != B.size() || A[0].size() != B[0].size()){ + std::cout << "incompatible\n"; + return; + } + + for(int i = 0; i < A.size(); i++){ + for(int j = 0; j < A[0].size(); j++){ + if(A[i][j] != B[i][j]) std::cout << "row: " << i << " col: " << j << " A: " << A[i][j] << " B: " << B[i][j] <<"\n"; + } + } +} + +void proportions(std::vector> mat){ + + int rows = mat.size(); + int cols = mat[0].size(); + int nonzero = 0; + + for(int i = 0; i < rows; i++) + for(int j = 0; j < cols; j++) if(mat[i][j] != 0) nonzero++; + + std::cout << "total elements: " << rows*cols << ", nonzero elemts: " << nonzero << ", proportion: " << (rows*cols)/nonzero << std::endl; +} + +int main(){ + + //==================================================1D Haar wavelet transform example================================================== + + /*std::vector input = { 1.0, 2.0, 3.0, 1.0, 2.0, 3.0, 4.0, 0.0}; //example input for 1D transform + //std::vector input = { 9.0, 7.0, 3.0, 5.0}; //test vector + + std::cout << "1D Haar wavelet transform example: " << std::endl; + std::cout << "Input vector: ["; + for(int i = 0; i < input.size(); i++) + std::cout << input[i] << " "; + std::cout << "]" << std::endl; + + //create object for 1D transform + sp::hwt::solver::HaarWaveletTransform1D waveletT1D(input); + //compute the transform + waveletT1D.compute(); + //get the solution + std::vector vecSolution = waveletT1D.getSolution(); + + std::cout << "Solution vector: ["; + for(int i = 0; i < input.size(); i++) + std::cout << vecSolution[i] << " "; + std::cout << "]" << std::endl << std::endl;*/ + + + //==================================================2D Haar wavelet transform example================================================== + + /*alternative test matrix + std::vector> matrix = {{0, 1, 1, 0}, {1, 0, 0,1}, {1, 0, 0,1}, {0, 1, 1, 0}};*/ + + // Example 2D input matrix (8x8 square) + /*std::vector> matrix = {{64, 2, 3, 61, 60, 6, 7, 57}, + {9, 55, 54, 12, 13, 51, 50, 16}, + + + + std::cout << "2D Haar wavelet transform example: " << std::endl; + std::cout << "Input matrix: " << std::endl << std::endl << "\t"; + for(int i = 0; i < matrix.size(); i++){ + for(int j = 0; j < matrix[0].size(); j++){ + std::cout << matrix[i][j] << "\t"; + } + std::cout << std::endl << "\t"; + } + std::cout << std::endl; + + sp::hwt::solver::HaarWaveletTransform2D waveletT2D(matrix); //create object for 2D transform + waveletT2D.compute(); //compute the transform + std::vector> matSolution = waveletT2D.getSolution(); //get the solution + std::vector> Hn = waveletT2D.getHnMatrix(); //get Hn matrix + + std::cout << "Corresponding Hn matrix: " << std::endl << std::endl << "\t"; + for(int i = 0; i < matrix.size(); i++){ + for(int j = 0; j < matrix[0].size(); j++){ + std::cout << Hn[i][j] << "\t"; + } + std::cout << std::endl << "\t"; + } + std::cout << std::endl << std::endl; + + std::cout << "Solution matrix: " << std::endl << std::endl << "\t"; + for(int i = 0; i < matrix.size(); i++){ + for(int j = 0; j < matrix[0].size(); j++){ + std::cout << matSolution[i][j] << "\t"; + } + std::cout << std::endl << "\t"; + } + std::cout << std::endl << std::endl;*/ + + //=======================================2D Haar wavelet transform for image compression example======================================= + + // ask user for threshold + std::cout << "Enter threshold for image compression (0.0 - 5.0): "; + std::string threshold; + std::getline(std::cin, threshold); + if (threshold.empty()) { + std::cout << "No threshold provided, using default value of 0.5" << std::endl; + threshold = "0.5"; //default value + } + + int w, h, channels; + const std::string path = "examples/resources/"; + const std::string name = "dog-bw"; + const std::string ext = ".png"; + const std::string img_path= path + name + ext; + // load image + const unsigned char* image_data = stbi_load(img_path.c_str(), &w, &h, &channels, 0); + + if(!image_data){ + std::cout << "could not load image " << img_path << std::endl; + return 1; //if loading fails, terminate program + } + + std::vector> image(h, std::vector(w)); //vector to hold the image + std::cout << "Image compression through Haar wavelet transform example:" << std::endl; + + //copy image pixels to double vector + for(int i = 0; i(image_data[(i*w+j)*channels]); + + std::cout << "Image: " << img_path << " loaded" << std::endl; + + sp::hwt::ImgWLComp imgWL; //create object for image compression + + // get compressed image + // measure time for compression + const auto start = std::chrono::high_resolution_clock::now(); + const std::vector> solution = imgWL.compress(image, std::stod(threshold)); + const auto end = std::chrono::high_resolution_clock::now(); + const std::chrono::duration duration = end - start; + printf("Image compressed in %.2f seconds\n", duration.count()); + + //prepare vector to save compressed image + std::vector outputImage(h*w); + for(int i = 0; i < h; i++) + for(int j = 0; j < w; j++) + outputImage[j + i*w] = static_cast(solution[i][j]); + + //save compressed image + const std::string compressed_path = "examples/output/compressed-" + name + "-threshold-" + threshold + ext; + if (stbi_write_png(compressed_path.c_str(), w, h, channels, outputImage.data(), w) == 0) { + std::cerr << "Error: Could not save image to " << compressed_path << std::endl; + return 1; + } + + // TODO: bug with threshold 1 + /* + std::string binary_path = "examples/output/compressed-" + name + ".bin"; + imgWL.save_as_binary(solution, binary_path); + + std::cout << "Image compressed and saved as " << binary_path << std::endl; + std::cout << "Reconstructing image" << std::endl; + + std::vector> reconstructed = imgWL.load_img_from_binary(binary_path); + reconstructed = imgWL.reconstruct(reconstructed); + */ + + // measure time for reconstruction + printf("Reconstructing image...\n"); + const auto start_reconstruct = std::chrono::high_resolution_clock::now(); + std::vector> reconstructed = imgWL.reconstruct(solution); + const auto end_reconstruct = std::chrono::high_resolution_clock::now(); + const std::chrono::duration duration_reconstruct = end_reconstruct - start_reconstruct; + printf("Image reconstructed in %.2f seconds\n", duration_reconstruct.count()); + + //prepare vector to save decompressed image + for(int i = 0; i < h; i++) + for(int j = 0; j < w; j++){ + //clamp values to [0, 255] range + reconstructed[i][j] = reconstructed[i][j] > 255.0 ? 255.0 : (reconstructed[i][j] < 0.0 ? 0.0 : reconstructed[i][j]); + outputImage[j + i*w] = static_cast(reconstructed[i][j]); + } + + //save decompressed image + const std::string reconstructed_path = "examples/output/reconstructed-" + name + "-threshold-" + threshold + ext; + if (stbi_write_png(reconstructed_path.c_str(), w, h, channels, outputImage.data(), w) == 0) { + std::cerr << "Error: Could not save image to " << reconstructed_path << std::endl; + return 1; + } + + std::cout << "Image reconstructed and saved as " << reconstructed_path << std::endl; + + return 0; +} diff --git a/examples/haar_wavelet_transform_1d.cpp b/examples/haar_wavelet_transform_1d.cpp new file mode 100644 index 0000000..f5812ca --- /dev/null +++ b/examples/haar_wavelet_transform_1d.cpp @@ -0,0 +1,32 @@ +#include +#include +#include +#include + +#include "signal_processing/signal_processing.hpp" + +int main() { + std::random_device rd; + std::mt19937 gen(rd()); + std::uniform_int_distribution<> power_dist(3, 6); // 2^3 = 8 ... 2^6 = 64 + std::uniform_real_distribution<> val_dist(-10.0, 10.0); + + int N = std::pow(2, power_dist(gen)); + std::vector input(N); + for (int i = 0; i < N; ++i) + input[i] = val_dist(gen); + + std::cout << "Input vector (" << N << " elements): "; + for (double v : input) std::cout << v << " "; + std::cout << "\n\n"; + + sp::hwt::solver::HaarWaveletTransform1D wavelet(input); + wavelet.compute(); + auto output = wavelet.getSolution(); + + std::cout << "Haar Transform output:\n"; + for (double v : output) std::cout << v << " "; + std::cout << "\n"; + + return 0; +} diff --git a/examples/haar_wavelet_transform_2d.cpp b/examples/haar_wavelet_transform_2d.cpp new file mode 100644 index 0000000..488be6a --- /dev/null +++ b/examples/haar_wavelet_transform_2d.cpp @@ -0,0 +1,38 @@ +#include +#include +#include +#include + +#include "signal_processing/signal_processing.hpp" + +int main() { + std::random_device rd; + std::mt19937 gen(rd()); + std::uniform_int_distribution<> power_dist(2, 5); // N = 4 ... 32 + std::uniform_real_distribution<> val_dist(-10.0, 10.0); + + int N = std::pow(2, power_dist(gen)); + std::vector> matrix(N, std::vector(N)); + + for (int i = 0; i < N; ++i) + for (int j = 0; j < N; ++j) + matrix[i][j] = val_dist(gen); + + std::cout << "Input matrix (" << N << "x" << N << "):\n"; + for (const auto& row : matrix) { + for (double val : row) std::cout << val << "\t"; + std::cout << "\n"; + } + + sp::hwt::solver::HaarWaveletTransform2D transform(matrix); + transform.compute(); + auto result = transform.getSolution(); + + std::cout << "\nHaar Transform matrix:\n"; + for (const auto& row : result) { + for (double val : row) std::cout << val << "\t"; + std::cout << "\n"; + } + + return 0; +} diff --git a/examples/jpeg_compression.cpp b/examples/jpeg_compression.cpp new file mode 100644 index 0000000..9309e95 --- /dev/null +++ b/examples/jpeg_compression.cpp @@ -0,0 +1,130 @@ +#include +#include + +#include "signal_processing/signal_processing.hpp" + +/** + * Environment variable name for the file path for the configuration file. + */ +#define ENV_FILE_PATH "CONFIG_FILE_PATH_FFT" + +void print_vector(const std::vector& vec) { + for (int i=0; i>& mat) { + for (int i=0; i> matrix = { + {1,1,1,4,5,6,7,0}, + {1,1,1,12,13,14,0,16}, + {1,18,19,20,21,0,23,24}, + {25,26,27,28,0,30,31,32}, + {33,34,35,0,37,38,39,40}, + {41,42,0,44,45,46,47,62}, + {49,0,51,52,53,54,62,56}, + {0,58,59,60,61,62,63,64} + }; + + std::cout<<"\nInput matrix to ZigZag scan: "< zz = sp::utils::zigzag::ZigZagScan::scan(matrix); + std::cout<<"\nOutput ZigZag scan: "<> reverse_zz = sp::utils::zigzag::ZigZagScan::inverse_scan(zz,8,8); + print_matrix(reverse_zz); +} + +// RLE_COMPRESSOR TEST +void rle_compression_demo(){ + std::cout<<"\n================================================= RLE COMPRESSION demo ================================================="< vector = {2, 0, 0, 0, 0, 34, 17, 45, 45, 45, 12, 7, 9, 9, 9, 9, 9, 9, 5}; + std::cout << "\nIutput vector for RLE compression: "<> rle_vector = sp::utils::rle::RLECompressor::compress(vector); + std::cout << "\nOutput RLE compression: "< rle_reverse = sp::utils::rle::RLECompressor::decompress(rle_vector); + std::cout << "\nOutput RLE compression: "< vect = {1,2,3,4}; + std::cout<<"Input vector: "; + print_vector(vect); + + // Compute the direct DCT in place and in parallel mode + sp::dct::solver::DiscreteCosineTransform dct_solver= sp::dct::solver::DiscreteCosineTransform(); + sp::dct::solver::ComputationMode cm = sp::dct::solver::ComputationMode::OPENMP; + dct_solver.compute(vect, cm); + std::cout<<"Output DCT (parallel mode): "; + print_vector(vect); + + // Compute the inverse DCT in place and in parallel mode + sp::dct::solver::InverseDiscreteCosineTransform idct_solver= sp::dct::solver::InverseDiscreteCosineTransform(); + dct_solver.compute(vect, cm); + std::cout<<"Output IDCT (parallel mode): "; + print_vector(vect); +} + +void jpeg_compression_demo(){ + std::cout<<"\n================================================= JPEG COMPRESSION demo ================================================="< +// SPDX-License-Identifier: MIT + +/****************************************************************************\ + * Note on documentation: The source files contain links to the online * + * documentation of the public API at https://json.nlohmann.me. This URL * + * contains the most recent documentation and should also be applicable to * + * previous versions; documentation for deprecated functions is not * + * removed, but marked deprecated. See "Generate documentation" section in * + * file docs/README.md. * +\****************************************************************************/ + +#ifndef INCLUDE_NLOHMANN_JSON_HPP_ +#define INCLUDE_NLOHMANN_JSON_HPP_ + +#include // all_of, find, for_each +#include // nullptr_t, ptrdiff_t, size_t +#include // hash, less +#include // initializer_list +#ifndef JSON_NO_IO + #include // istream, ostream +#endif // JSON_NO_IO +#include // random_access_iterator_tag +#include // unique_ptr +#include // string, stoi, to_string +#include // declval, forward, move, pair, swap +#include // vector + +// #include +// __ _____ _____ _____ +// __| | __| | | | JSON for Modern C++ +// | | |__ | | | | | | version 3.11.3 +// |_____|_____|_____|_|___| https://github.com/nlohmann/json +// +// SPDX-FileCopyrightText: 2013 - 2024 Niels Lohmann +// SPDX-License-Identifier: MIT + + + +#include + +// #include +// __ _____ _____ _____ +// __| | __| | | | JSON for Modern C++ +// | | |__ | | | | | | version 3.11.3 +// |_____|_____|_____|_|___| https://github.com/nlohmann/json +// +// SPDX-FileCopyrightText: 2013 - 2024 Niels Lohmann +// SPDX-License-Identifier: MIT + + + +// This file contains all macro definitions affecting or depending on the ABI + +#ifndef JSON_SKIP_LIBRARY_VERSION_CHECK + #if defined(NLOHMANN_JSON_VERSION_MAJOR) && defined(NLOHMANN_JSON_VERSION_MINOR) && defined(NLOHMANN_JSON_VERSION_PATCH) + #if NLOHMANN_JSON_VERSION_MAJOR != 3 || NLOHMANN_JSON_VERSION_MINOR != 11 || NLOHMANN_JSON_VERSION_PATCH != 3 + #warning "Already included a different version of the library!" + #endif + #endif +#endif + +#define NLOHMANN_JSON_VERSION_MAJOR 3 // NOLINT(modernize-macro-to-enum) +#define NLOHMANN_JSON_VERSION_MINOR 11 // NOLINT(modernize-macro-to-enum) +#define NLOHMANN_JSON_VERSION_PATCH 3 // NOLINT(modernize-macro-to-enum) + +#ifndef JSON_DIAGNOSTICS + #define JSON_DIAGNOSTICS 0 +#endif + +#ifndef JSON_USE_LEGACY_DISCARDED_VALUE_COMPARISON + #define JSON_USE_LEGACY_DISCARDED_VALUE_COMPARISON 0 +#endif + +#if JSON_DIAGNOSTICS + #define NLOHMANN_JSON_ABI_TAG_DIAGNOSTICS _diag +#else + #define NLOHMANN_JSON_ABI_TAG_DIAGNOSTICS +#endif + +#if JSON_USE_LEGACY_DISCARDED_VALUE_COMPARISON + #define NLOHMANN_JSON_ABI_TAG_LEGACY_DISCARDED_VALUE_COMPARISON _ldvcmp +#else + #define NLOHMANN_JSON_ABI_TAG_LEGACY_DISCARDED_VALUE_COMPARISON +#endif + +#ifndef NLOHMANN_JSON_NAMESPACE_NO_VERSION + #define NLOHMANN_JSON_NAMESPACE_NO_VERSION 0 +#endif + +// Construct the namespace ABI tags component +#define NLOHMANN_JSON_ABI_TAGS_CONCAT_EX(a, b) json_abi ## a ## b +#define NLOHMANN_JSON_ABI_TAGS_CONCAT(a, b) \ + NLOHMANN_JSON_ABI_TAGS_CONCAT_EX(a, b) + +#define NLOHMANN_JSON_ABI_TAGS \ + NLOHMANN_JSON_ABI_TAGS_CONCAT( \ + NLOHMANN_JSON_ABI_TAG_DIAGNOSTICS, \ + NLOHMANN_JSON_ABI_TAG_LEGACY_DISCARDED_VALUE_COMPARISON) + +// Construct the namespace version component +#define NLOHMANN_JSON_NAMESPACE_VERSION_CONCAT_EX(major, minor, patch) \ + _v ## major ## _ ## minor ## _ ## patch +#define NLOHMANN_JSON_NAMESPACE_VERSION_CONCAT(major, minor, patch) \ + NLOHMANN_JSON_NAMESPACE_VERSION_CONCAT_EX(major, minor, patch) + +#if NLOHMANN_JSON_NAMESPACE_NO_VERSION +#define NLOHMANN_JSON_NAMESPACE_VERSION +#else +#define NLOHMANN_JSON_NAMESPACE_VERSION \ + NLOHMANN_JSON_NAMESPACE_VERSION_CONCAT(NLOHMANN_JSON_VERSION_MAJOR, \ + NLOHMANN_JSON_VERSION_MINOR, \ + NLOHMANN_JSON_VERSION_PATCH) +#endif + +// Combine namespace components +#define NLOHMANN_JSON_NAMESPACE_CONCAT_EX(a, b) a ## b +#define NLOHMANN_JSON_NAMESPACE_CONCAT(a, b) \ + NLOHMANN_JSON_NAMESPACE_CONCAT_EX(a, b) + +#ifndef NLOHMANN_JSON_NAMESPACE +#define NLOHMANN_JSON_NAMESPACE \ + nlohmann::NLOHMANN_JSON_NAMESPACE_CONCAT( \ + NLOHMANN_JSON_ABI_TAGS, \ + NLOHMANN_JSON_NAMESPACE_VERSION) +#endif + +#ifndef NLOHMANN_JSON_NAMESPACE_BEGIN +#define NLOHMANN_JSON_NAMESPACE_BEGIN \ + namespace nlohmann \ + { \ + inline namespace NLOHMANN_JSON_NAMESPACE_CONCAT( \ + NLOHMANN_JSON_ABI_TAGS, \ + NLOHMANN_JSON_NAMESPACE_VERSION) \ + { +#endif + +#ifndef NLOHMANN_JSON_NAMESPACE_END +#define NLOHMANN_JSON_NAMESPACE_END \ + } /* namespace (inline namespace) NOLINT(readability/namespace) */ \ + } // namespace nlohmann +#endif + +// #include +// __ _____ _____ _____ +// __| | __| | | | JSON for Modern C++ +// | | |__ | | | | | | version 3.11.3 +// |_____|_____|_____|_|___| https://github.com/nlohmann/json +// +// SPDX-FileCopyrightText: 2013 - 2024 Niels Lohmann +// SPDX-License-Identifier: MIT + + + +#include // transform +#include // array +#include // forward_list +#include // inserter, front_inserter, end +#include // map +#ifdef JSON_HAS_CPP_17 + #include // optional +#endif +#include // string +#include // tuple, make_tuple +#include // is_arithmetic, is_same, is_enum, underlying_type, is_convertible +#include // unordered_map +#include // pair, declval +#include // valarray + + +// #include +// __ _____ _____ _____ +// __| | __| | | | JSON for Modern C++ +// | | |__ | | | | | | version 3.11.3 +// |_____|_____|_____|_|___| https://github.com/nlohmann/json +// +// SPDX-FileCopyrightText: 2013 - 2024 Niels Lohmann +// SPDX-License-Identifier: MIT + + + +#include // nullptr_t +#include // exception +#if JSON_DIAGNOSTICS + #include // accumulate +#endif +#include // runtime_error +#include // to_string +#include // vector + +// #include +// __ _____ _____ _____ +// __| | __| | | | JSON for Modern C++ +// | | |__ | | | | | | version 3.11.3 +// |_____|_____|_____|_|___| https://github.com/nlohmann/json +// +// SPDX-FileCopyrightText: 2013 - 2024 Niels Lohmann +// SPDX-License-Identifier: MIT + + + +#include // array +#include // size_t +#include // uint8_t +#include // string + +// #include +// __ _____ _____ _____ +// __| | __| | | | JSON for Modern C++ +// | | |__ | | | | | | version 3.11.3 +// |_____|_____|_____|_|___| https://github.com/nlohmann/json +// +// SPDX-FileCopyrightText: 2013 - 2024 Niels Lohmann +// SPDX-License-Identifier: MIT + + + +#include // declval, pair +// #include +// __ _____ _____ _____ +// __| | __| | | | JSON for Modern C++ +// | | |__ | | | | | | version 3.11.3 +// |_____|_____|_____|_|___| https://github.com/nlohmann/json +// +// SPDX-FileCopyrightText: 2013 - 2024 Niels Lohmann +// SPDX-License-Identifier: MIT + + + +#include + +// #include +// __ _____ _____ _____ +// __| | __| | | | JSON for Modern C++ +// | | |__ | | | | | | version 3.11.3 +// |_____|_____|_____|_|___| https://github.com/nlohmann/json +// +// SPDX-FileCopyrightText: 2013 - 2024 Niels Lohmann +// SPDX-License-Identifier: MIT + + + +// #include + + +NLOHMANN_JSON_NAMESPACE_BEGIN +namespace detail +{ + +template struct make_void +{ + using type = void; +}; +template using void_t = typename make_void::type; + +} // namespace detail +NLOHMANN_JSON_NAMESPACE_END + + +NLOHMANN_JSON_NAMESPACE_BEGIN +namespace detail +{ + +// https://en.cppreference.com/w/cpp/experimental/is_detected +struct nonesuch +{ + nonesuch() = delete; + ~nonesuch() = delete; + nonesuch(nonesuch const&) = delete; + nonesuch(nonesuch const&&) = delete; + void operator=(nonesuch const&) = delete; + void operator=(nonesuch&&) = delete; +}; + +template class Op, + class... Args> +struct detector +{ + using value_t = std::false_type; + using type = Default; +}; + +template class Op, class... Args> +struct detector>, Op, Args...> +{ + using value_t = std::true_type; + using type = Op; +}; + +template class Op, class... Args> +using is_detected = typename detector::value_t; + +template class Op, class... Args> +struct is_detected_lazy : is_detected { }; + +template class Op, class... Args> +using detected_t = typename detector::type; + +template class Op, class... Args> +using detected_or = detector; + +template class Op, class... Args> +using detected_or_t = typename detected_or::type; + +template class Op, class... Args> +using is_detected_exact = std::is_same>; + +template class Op, class... Args> +using is_detected_convertible = + std::is_convertible, To>; + +} // namespace detail +NLOHMANN_JSON_NAMESPACE_END + +// #include + + +// __ _____ _____ _____ +// __| | __| | | | JSON for Modern C++ +// | | |__ | | | | | | version 3.11.3 +// |_____|_____|_____|_|___| https://github.com/nlohmann/json +// +// SPDX-FileCopyrightText: 2013 - 2024 Niels Lohmann +// SPDX-FileCopyrightText: 2016 - 2021 Evan Nemerson +// SPDX-License-Identifier: MIT + +/* Hedley - https://nemequ.github.io/hedley + * Created by Evan Nemerson + */ + +#if !defined(JSON_HEDLEY_VERSION) || (JSON_HEDLEY_VERSION < 15) +#if defined(JSON_HEDLEY_VERSION) + #undef JSON_HEDLEY_VERSION +#endif +#define JSON_HEDLEY_VERSION 15 + +#if defined(JSON_HEDLEY_STRINGIFY_EX) + #undef JSON_HEDLEY_STRINGIFY_EX +#endif +#define JSON_HEDLEY_STRINGIFY_EX(x) #x + +#if defined(JSON_HEDLEY_STRINGIFY) + #undef JSON_HEDLEY_STRINGIFY +#endif +#define JSON_HEDLEY_STRINGIFY(x) JSON_HEDLEY_STRINGIFY_EX(x) + +#if defined(JSON_HEDLEY_CONCAT_EX) + #undef JSON_HEDLEY_CONCAT_EX +#endif +#define JSON_HEDLEY_CONCAT_EX(a,b) a##b + +#if defined(JSON_HEDLEY_CONCAT) + #undef JSON_HEDLEY_CONCAT +#endif +#define JSON_HEDLEY_CONCAT(a,b) JSON_HEDLEY_CONCAT_EX(a,b) + +#if defined(JSON_HEDLEY_CONCAT3_EX) + #undef JSON_HEDLEY_CONCAT3_EX +#endif +#define JSON_HEDLEY_CONCAT3_EX(a,b,c) a##b##c + +#if defined(JSON_HEDLEY_CONCAT3) + #undef JSON_HEDLEY_CONCAT3 +#endif +#define JSON_HEDLEY_CONCAT3(a,b,c) JSON_HEDLEY_CONCAT3_EX(a,b,c) + +#if defined(JSON_HEDLEY_VERSION_ENCODE) + #undef JSON_HEDLEY_VERSION_ENCODE +#endif +#define JSON_HEDLEY_VERSION_ENCODE(major,minor,revision) (((major) * 1000000) + ((minor) * 1000) + (revision)) + +#if defined(JSON_HEDLEY_VERSION_DECODE_MAJOR) + #undef JSON_HEDLEY_VERSION_DECODE_MAJOR +#endif +#define JSON_HEDLEY_VERSION_DECODE_MAJOR(version) ((version) / 1000000) + +#if defined(JSON_HEDLEY_VERSION_DECODE_MINOR) + #undef JSON_HEDLEY_VERSION_DECODE_MINOR +#endif +#define JSON_HEDLEY_VERSION_DECODE_MINOR(version) (((version) % 1000000) / 1000) + +#if defined(JSON_HEDLEY_VERSION_DECODE_REVISION) + #undef JSON_HEDLEY_VERSION_DECODE_REVISION +#endif +#define JSON_HEDLEY_VERSION_DECODE_REVISION(version) ((version) % 1000) + +#if defined(JSON_HEDLEY_GNUC_VERSION) + #undef JSON_HEDLEY_GNUC_VERSION +#endif +#if defined(__GNUC__) && defined(__GNUC_PATCHLEVEL__) + #define JSON_HEDLEY_GNUC_VERSION JSON_HEDLEY_VERSION_ENCODE(__GNUC__, __GNUC_MINOR__, __GNUC_PATCHLEVEL__) +#elif defined(__GNUC__) + #define JSON_HEDLEY_GNUC_VERSION JSON_HEDLEY_VERSION_ENCODE(__GNUC__, __GNUC_MINOR__, 0) +#endif + +#if defined(JSON_HEDLEY_GNUC_VERSION_CHECK) + #undef JSON_HEDLEY_GNUC_VERSION_CHECK +#endif +#if defined(JSON_HEDLEY_GNUC_VERSION) + #define JSON_HEDLEY_GNUC_VERSION_CHECK(major,minor,patch) (JSON_HEDLEY_GNUC_VERSION >= JSON_HEDLEY_VERSION_ENCODE(major, minor, patch)) +#else + #define JSON_HEDLEY_GNUC_VERSION_CHECK(major,minor,patch) (0) +#endif + +#if defined(JSON_HEDLEY_MSVC_VERSION) + #undef JSON_HEDLEY_MSVC_VERSION +#endif +#if defined(_MSC_FULL_VER) && (_MSC_FULL_VER >= 140000000) && !defined(__ICL) + #define JSON_HEDLEY_MSVC_VERSION JSON_HEDLEY_VERSION_ENCODE(_MSC_FULL_VER / 10000000, (_MSC_FULL_VER % 10000000) / 100000, (_MSC_FULL_VER % 100000) / 100) +#elif defined(_MSC_FULL_VER) && !defined(__ICL) + #define JSON_HEDLEY_MSVC_VERSION JSON_HEDLEY_VERSION_ENCODE(_MSC_FULL_VER / 1000000, (_MSC_FULL_VER % 1000000) / 10000, (_MSC_FULL_VER % 10000) / 10) +#elif defined(_MSC_VER) && !defined(__ICL) + #define JSON_HEDLEY_MSVC_VERSION JSON_HEDLEY_VERSION_ENCODE(_MSC_VER / 100, _MSC_VER % 100, 0) +#endif + +#if defined(JSON_HEDLEY_MSVC_VERSION_CHECK) + #undef JSON_HEDLEY_MSVC_VERSION_CHECK +#endif +#if !defined(JSON_HEDLEY_MSVC_VERSION) + #define JSON_HEDLEY_MSVC_VERSION_CHECK(major,minor,patch) (0) +#elif defined(_MSC_VER) && (_MSC_VER >= 1400) + #define JSON_HEDLEY_MSVC_VERSION_CHECK(major,minor,patch) (_MSC_FULL_VER >= ((major * 10000000) + (minor * 100000) + (patch))) +#elif defined(_MSC_VER) && (_MSC_VER >= 1200) + #define JSON_HEDLEY_MSVC_VERSION_CHECK(major,minor,patch) (_MSC_FULL_VER >= ((major * 1000000) + (minor * 10000) + (patch))) +#else + #define JSON_HEDLEY_MSVC_VERSION_CHECK(major,minor,patch) (_MSC_VER >= ((major * 100) + (minor))) +#endif + +#if defined(JSON_HEDLEY_INTEL_VERSION) + #undef JSON_HEDLEY_INTEL_VERSION +#endif +#if defined(__INTEL_COMPILER) && defined(__INTEL_COMPILER_UPDATE) && !defined(__ICL) + #define JSON_HEDLEY_INTEL_VERSION JSON_HEDLEY_VERSION_ENCODE(__INTEL_COMPILER / 100, __INTEL_COMPILER % 100, __INTEL_COMPILER_UPDATE) +#elif defined(__INTEL_COMPILER) && !defined(__ICL) + #define JSON_HEDLEY_INTEL_VERSION JSON_HEDLEY_VERSION_ENCODE(__INTEL_COMPILER / 100, __INTEL_COMPILER % 100, 0) +#endif + +#if defined(JSON_HEDLEY_INTEL_VERSION_CHECK) + #undef JSON_HEDLEY_INTEL_VERSION_CHECK +#endif +#if defined(JSON_HEDLEY_INTEL_VERSION) + #define JSON_HEDLEY_INTEL_VERSION_CHECK(major,minor,patch) (JSON_HEDLEY_INTEL_VERSION >= JSON_HEDLEY_VERSION_ENCODE(major, minor, patch)) +#else + #define JSON_HEDLEY_INTEL_VERSION_CHECK(major,minor,patch) (0) +#endif + +#if defined(JSON_HEDLEY_INTEL_CL_VERSION) + #undef JSON_HEDLEY_INTEL_CL_VERSION +#endif +#if defined(__INTEL_COMPILER) && defined(__INTEL_COMPILER_UPDATE) && defined(__ICL) + #define JSON_HEDLEY_INTEL_CL_VERSION JSON_HEDLEY_VERSION_ENCODE(__INTEL_COMPILER, __INTEL_COMPILER_UPDATE, 0) +#endif + +#if defined(JSON_HEDLEY_INTEL_CL_VERSION_CHECK) + #undef JSON_HEDLEY_INTEL_CL_VERSION_CHECK +#endif +#if defined(JSON_HEDLEY_INTEL_CL_VERSION) + #define JSON_HEDLEY_INTEL_CL_VERSION_CHECK(major,minor,patch) (JSON_HEDLEY_INTEL_CL_VERSION >= JSON_HEDLEY_VERSION_ENCODE(major, minor, patch)) +#else + #define JSON_HEDLEY_INTEL_CL_VERSION_CHECK(major,minor,patch) (0) +#endif + +#if defined(JSON_HEDLEY_PGI_VERSION) + #undef JSON_HEDLEY_PGI_VERSION +#endif +#if defined(__PGI) && defined(__PGIC__) && defined(__PGIC_MINOR__) && defined(__PGIC_PATCHLEVEL__) + #define JSON_HEDLEY_PGI_VERSION JSON_HEDLEY_VERSION_ENCODE(__PGIC__, __PGIC_MINOR__, __PGIC_PATCHLEVEL__) +#endif + +#if defined(JSON_HEDLEY_PGI_VERSION_CHECK) + #undef JSON_HEDLEY_PGI_VERSION_CHECK +#endif +#if defined(JSON_HEDLEY_PGI_VERSION) + #define JSON_HEDLEY_PGI_VERSION_CHECK(major,minor,patch) (JSON_HEDLEY_PGI_VERSION >= JSON_HEDLEY_VERSION_ENCODE(major, minor, patch)) +#else + #define JSON_HEDLEY_PGI_VERSION_CHECK(major,minor,patch) (0) +#endif + +#if defined(JSON_HEDLEY_SUNPRO_VERSION) + #undef JSON_HEDLEY_SUNPRO_VERSION +#endif +#if defined(__SUNPRO_C) && (__SUNPRO_C > 0x1000) + #define JSON_HEDLEY_SUNPRO_VERSION JSON_HEDLEY_VERSION_ENCODE((((__SUNPRO_C >> 16) & 0xf) * 10) + ((__SUNPRO_C >> 12) & 0xf), (((__SUNPRO_C >> 8) & 0xf) * 10) + ((__SUNPRO_C >> 4) & 0xf), (__SUNPRO_C & 0xf) * 10) +#elif defined(__SUNPRO_C) + #define JSON_HEDLEY_SUNPRO_VERSION JSON_HEDLEY_VERSION_ENCODE((__SUNPRO_C >> 8) & 0xf, (__SUNPRO_C >> 4) & 0xf, (__SUNPRO_C) & 0xf) +#elif defined(__SUNPRO_CC) && (__SUNPRO_CC > 0x1000) + #define JSON_HEDLEY_SUNPRO_VERSION JSON_HEDLEY_VERSION_ENCODE((((__SUNPRO_CC >> 16) & 0xf) * 10) + ((__SUNPRO_CC >> 12) & 0xf), (((__SUNPRO_CC >> 8) & 0xf) * 10) + ((__SUNPRO_CC >> 4) & 0xf), (__SUNPRO_CC & 0xf) * 10) +#elif defined(__SUNPRO_CC) + #define JSON_HEDLEY_SUNPRO_VERSION JSON_HEDLEY_VERSION_ENCODE((__SUNPRO_CC >> 8) & 0xf, (__SUNPRO_CC >> 4) & 0xf, (__SUNPRO_CC) & 0xf) +#endif + +#if defined(JSON_HEDLEY_SUNPRO_VERSION_CHECK) + #undef JSON_HEDLEY_SUNPRO_VERSION_CHECK +#endif +#if defined(JSON_HEDLEY_SUNPRO_VERSION) + #define JSON_HEDLEY_SUNPRO_VERSION_CHECK(major,minor,patch) (JSON_HEDLEY_SUNPRO_VERSION >= JSON_HEDLEY_VERSION_ENCODE(major, minor, patch)) +#else + #define JSON_HEDLEY_SUNPRO_VERSION_CHECK(major,minor,patch) (0) +#endif + +#if defined(JSON_HEDLEY_EMSCRIPTEN_VERSION) + #undef JSON_HEDLEY_EMSCRIPTEN_VERSION +#endif +#if defined(__EMSCRIPTEN__) + #define JSON_HEDLEY_EMSCRIPTEN_VERSION JSON_HEDLEY_VERSION_ENCODE(__EMSCRIPTEN_major__, __EMSCRIPTEN_minor__, __EMSCRIPTEN_tiny__) +#endif + +#if defined(JSON_HEDLEY_EMSCRIPTEN_VERSION_CHECK) + #undef JSON_HEDLEY_EMSCRIPTEN_VERSION_CHECK +#endif +#if defined(JSON_HEDLEY_EMSCRIPTEN_VERSION) + #define JSON_HEDLEY_EMSCRIPTEN_VERSION_CHECK(major,minor,patch) (JSON_HEDLEY_EMSCRIPTEN_VERSION >= JSON_HEDLEY_VERSION_ENCODE(major, minor, patch)) +#else + #define JSON_HEDLEY_EMSCRIPTEN_VERSION_CHECK(major,minor,patch) (0) +#endif + +#if defined(JSON_HEDLEY_ARM_VERSION) + #undef JSON_HEDLEY_ARM_VERSION +#endif +#if defined(__CC_ARM) && defined(__ARMCOMPILER_VERSION) + #define JSON_HEDLEY_ARM_VERSION JSON_HEDLEY_VERSION_ENCODE(__ARMCOMPILER_VERSION / 1000000, (__ARMCOMPILER_VERSION % 1000000) / 10000, (__ARMCOMPILER_VERSION % 10000) / 100) +#elif defined(__CC_ARM) && defined(__ARMCC_VERSION) + #define JSON_HEDLEY_ARM_VERSION JSON_HEDLEY_VERSION_ENCODE(__ARMCC_VERSION / 1000000, (__ARMCC_VERSION % 1000000) / 10000, (__ARMCC_VERSION % 10000) / 100) +#endif + +#if defined(JSON_HEDLEY_ARM_VERSION_CHECK) + #undef JSON_HEDLEY_ARM_VERSION_CHECK +#endif +#if defined(JSON_HEDLEY_ARM_VERSION) + #define JSON_HEDLEY_ARM_VERSION_CHECK(major,minor,patch) (JSON_HEDLEY_ARM_VERSION >= JSON_HEDLEY_VERSION_ENCODE(major, minor, patch)) +#else + #define JSON_HEDLEY_ARM_VERSION_CHECK(major,minor,patch) (0) +#endif + +#if defined(JSON_HEDLEY_IBM_VERSION) + #undef JSON_HEDLEY_IBM_VERSION +#endif +#if defined(__ibmxl__) + #define JSON_HEDLEY_IBM_VERSION JSON_HEDLEY_VERSION_ENCODE(__ibmxl_version__, __ibmxl_release__, __ibmxl_modification__) +#elif defined(__xlC__) && defined(__xlC_ver__) + #define JSON_HEDLEY_IBM_VERSION JSON_HEDLEY_VERSION_ENCODE(__xlC__ >> 8, __xlC__ & 0xff, (__xlC_ver__ >> 8) & 0xff) +#elif defined(__xlC__) + #define JSON_HEDLEY_IBM_VERSION JSON_HEDLEY_VERSION_ENCODE(__xlC__ >> 8, __xlC__ & 0xff, 0) +#endif + +#if defined(JSON_HEDLEY_IBM_VERSION_CHECK) + #undef JSON_HEDLEY_IBM_VERSION_CHECK +#endif +#if defined(JSON_HEDLEY_IBM_VERSION) + #define JSON_HEDLEY_IBM_VERSION_CHECK(major,minor,patch) (JSON_HEDLEY_IBM_VERSION >= JSON_HEDLEY_VERSION_ENCODE(major, minor, patch)) +#else + #define JSON_HEDLEY_IBM_VERSION_CHECK(major,minor,patch) (0) +#endif + +#if defined(JSON_HEDLEY_TI_VERSION) + #undef JSON_HEDLEY_TI_VERSION +#endif +#if \ + defined(__TI_COMPILER_VERSION__) && \ + ( \ + defined(__TMS470__) || defined(__TI_ARM__) || \ + defined(__MSP430__) || \ + defined(__TMS320C2000__) \ + ) +#if (__TI_COMPILER_VERSION__ >= 16000000) + #define JSON_HEDLEY_TI_VERSION JSON_HEDLEY_VERSION_ENCODE(__TI_COMPILER_VERSION__ / 1000000, (__TI_COMPILER_VERSION__ % 1000000) / 1000, (__TI_COMPILER_VERSION__ % 1000)) +#endif +#endif + +#if defined(JSON_HEDLEY_TI_VERSION_CHECK) + #undef JSON_HEDLEY_TI_VERSION_CHECK +#endif +#if defined(JSON_HEDLEY_TI_VERSION) + #define JSON_HEDLEY_TI_VERSION_CHECK(major,minor,patch) (JSON_HEDLEY_TI_VERSION >= JSON_HEDLEY_VERSION_ENCODE(major, minor, patch)) +#else + #define JSON_HEDLEY_TI_VERSION_CHECK(major,minor,patch) (0) +#endif + +#if defined(JSON_HEDLEY_TI_CL2000_VERSION) + #undef JSON_HEDLEY_TI_CL2000_VERSION +#endif +#if defined(__TI_COMPILER_VERSION__) && defined(__TMS320C2000__) + #define JSON_HEDLEY_TI_CL2000_VERSION JSON_HEDLEY_VERSION_ENCODE(__TI_COMPILER_VERSION__ / 1000000, (__TI_COMPILER_VERSION__ % 1000000) / 1000, (__TI_COMPILER_VERSION__ % 1000)) +#endif + +#if defined(JSON_HEDLEY_TI_CL2000_VERSION_CHECK) + #undef JSON_HEDLEY_TI_CL2000_VERSION_CHECK +#endif +#if defined(JSON_HEDLEY_TI_CL2000_VERSION) + #define JSON_HEDLEY_TI_CL2000_VERSION_CHECK(major,minor,patch) (JSON_HEDLEY_TI_CL2000_VERSION >= JSON_HEDLEY_VERSION_ENCODE(major, minor, patch)) +#else + #define JSON_HEDLEY_TI_CL2000_VERSION_CHECK(major,minor,patch) (0) +#endif + +#if defined(JSON_HEDLEY_TI_CL430_VERSION) + #undef JSON_HEDLEY_TI_CL430_VERSION +#endif +#if defined(__TI_COMPILER_VERSION__) && defined(__MSP430__) + #define JSON_HEDLEY_TI_CL430_VERSION JSON_HEDLEY_VERSION_ENCODE(__TI_COMPILER_VERSION__ / 1000000, (__TI_COMPILER_VERSION__ % 1000000) / 1000, (__TI_COMPILER_VERSION__ % 1000)) +#endif + +#if defined(JSON_HEDLEY_TI_CL430_VERSION_CHECK) + #undef JSON_HEDLEY_TI_CL430_VERSION_CHECK +#endif +#if defined(JSON_HEDLEY_TI_CL430_VERSION) + #define JSON_HEDLEY_TI_CL430_VERSION_CHECK(major,minor,patch) (JSON_HEDLEY_TI_CL430_VERSION >= JSON_HEDLEY_VERSION_ENCODE(major, minor, patch)) +#else + #define JSON_HEDLEY_TI_CL430_VERSION_CHECK(major,minor,patch) (0) +#endif + +#if defined(JSON_HEDLEY_TI_ARMCL_VERSION) + #undef JSON_HEDLEY_TI_ARMCL_VERSION +#endif +#if defined(__TI_COMPILER_VERSION__) && (defined(__TMS470__) || defined(__TI_ARM__)) + #define JSON_HEDLEY_TI_ARMCL_VERSION JSON_HEDLEY_VERSION_ENCODE(__TI_COMPILER_VERSION__ / 1000000, (__TI_COMPILER_VERSION__ % 1000000) / 1000, (__TI_COMPILER_VERSION__ % 1000)) +#endif + +#if defined(JSON_HEDLEY_TI_ARMCL_VERSION_CHECK) + #undef JSON_HEDLEY_TI_ARMCL_VERSION_CHECK +#endif +#if defined(JSON_HEDLEY_TI_ARMCL_VERSION) + #define JSON_HEDLEY_TI_ARMCL_VERSION_CHECK(major,minor,patch) (JSON_HEDLEY_TI_ARMCL_VERSION >= JSON_HEDLEY_VERSION_ENCODE(major, minor, patch)) +#else + #define JSON_HEDLEY_TI_ARMCL_VERSION_CHECK(major,minor,patch) (0) +#endif + +#if defined(JSON_HEDLEY_TI_CL6X_VERSION) + #undef JSON_HEDLEY_TI_CL6X_VERSION +#endif +#if defined(__TI_COMPILER_VERSION__) && defined(__TMS320C6X__) + #define JSON_HEDLEY_TI_CL6X_VERSION JSON_HEDLEY_VERSION_ENCODE(__TI_COMPILER_VERSION__ / 1000000, (__TI_COMPILER_VERSION__ % 1000000) / 1000, (__TI_COMPILER_VERSION__ % 1000)) +#endif + +#if defined(JSON_HEDLEY_TI_CL6X_VERSION_CHECK) + #undef JSON_HEDLEY_TI_CL6X_VERSION_CHECK +#endif +#if defined(JSON_HEDLEY_TI_CL6X_VERSION) + #define JSON_HEDLEY_TI_CL6X_VERSION_CHECK(major,minor,patch) (JSON_HEDLEY_TI_CL6X_VERSION >= JSON_HEDLEY_VERSION_ENCODE(major, minor, patch)) +#else + #define JSON_HEDLEY_TI_CL6X_VERSION_CHECK(major,minor,patch) (0) +#endif + +#if defined(JSON_HEDLEY_TI_CL7X_VERSION) + #undef JSON_HEDLEY_TI_CL7X_VERSION +#endif +#if defined(__TI_COMPILER_VERSION__) && defined(__C7000__) + #define JSON_HEDLEY_TI_CL7X_VERSION JSON_HEDLEY_VERSION_ENCODE(__TI_COMPILER_VERSION__ / 1000000, (__TI_COMPILER_VERSION__ % 1000000) / 1000, (__TI_COMPILER_VERSION__ % 1000)) +#endif + +#if defined(JSON_HEDLEY_TI_CL7X_VERSION_CHECK) + #undef JSON_HEDLEY_TI_CL7X_VERSION_CHECK +#endif +#if defined(JSON_HEDLEY_TI_CL7X_VERSION) + #define JSON_HEDLEY_TI_CL7X_VERSION_CHECK(major,minor,patch) (JSON_HEDLEY_TI_CL7X_VERSION >= JSON_HEDLEY_VERSION_ENCODE(major, minor, patch)) +#else + #define JSON_HEDLEY_TI_CL7X_VERSION_CHECK(major,minor,patch) (0) +#endif + +#if defined(JSON_HEDLEY_TI_CLPRU_VERSION) + #undef JSON_HEDLEY_TI_CLPRU_VERSION +#endif +#if defined(__TI_COMPILER_VERSION__) && defined(__PRU__) + #define JSON_HEDLEY_TI_CLPRU_VERSION JSON_HEDLEY_VERSION_ENCODE(__TI_COMPILER_VERSION__ / 1000000, (__TI_COMPILER_VERSION__ % 1000000) / 1000, (__TI_COMPILER_VERSION__ % 1000)) +#endif + +#if defined(JSON_HEDLEY_TI_CLPRU_VERSION_CHECK) + #undef JSON_HEDLEY_TI_CLPRU_VERSION_CHECK +#endif +#if defined(JSON_HEDLEY_TI_CLPRU_VERSION) + #define JSON_HEDLEY_TI_CLPRU_VERSION_CHECK(major,minor,patch) (JSON_HEDLEY_TI_CLPRU_VERSION >= JSON_HEDLEY_VERSION_ENCODE(major, minor, patch)) +#else + #define JSON_HEDLEY_TI_CLPRU_VERSION_CHECK(major,minor,patch) (0) +#endif + +#if defined(JSON_HEDLEY_CRAY_VERSION) + #undef JSON_HEDLEY_CRAY_VERSION +#endif +#if defined(_CRAYC) + #if defined(_RELEASE_PATCHLEVEL) + #define JSON_HEDLEY_CRAY_VERSION JSON_HEDLEY_VERSION_ENCODE(_RELEASE_MAJOR, _RELEASE_MINOR, _RELEASE_PATCHLEVEL) + #else + #define JSON_HEDLEY_CRAY_VERSION JSON_HEDLEY_VERSION_ENCODE(_RELEASE_MAJOR, _RELEASE_MINOR, 0) + #endif +#endif + +#if defined(JSON_HEDLEY_CRAY_VERSION_CHECK) + #undef JSON_HEDLEY_CRAY_VERSION_CHECK +#endif +#if defined(JSON_HEDLEY_CRAY_VERSION) + #define JSON_HEDLEY_CRAY_VERSION_CHECK(major,minor,patch) (JSON_HEDLEY_CRAY_VERSION >= JSON_HEDLEY_VERSION_ENCODE(major, minor, patch)) +#else + #define JSON_HEDLEY_CRAY_VERSION_CHECK(major,minor,patch) (0) +#endif + +#if defined(JSON_HEDLEY_IAR_VERSION) + #undef JSON_HEDLEY_IAR_VERSION +#endif +#if defined(__IAR_SYSTEMS_ICC__) + #if __VER__ > 1000 + #define JSON_HEDLEY_IAR_VERSION JSON_HEDLEY_VERSION_ENCODE((__VER__ / 1000000), ((__VER__ / 1000) % 1000), (__VER__ % 1000)) + #else + #define JSON_HEDLEY_IAR_VERSION JSON_HEDLEY_VERSION_ENCODE(__VER__ / 100, __VER__ % 100, 0) + #endif +#endif + +#if defined(JSON_HEDLEY_IAR_VERSION_CHECK) + #undef JSON_HEDLEY_IAR_VERSION_CHECK +#endif +#if defined(JSON_HEDLEY_IAR_VERSION) + #define JSON_HEDLEY_IAR_VERSION_CHECK(major,minor,patch) (JSON_HEDLEY_IAR_VERSION >= JSON_HEDLEY_VERSION_ENCODE(major, minor, patch)) +#else + #define JSON_HEDLEY_IAR_VERSION_CHECK(major,minor,patch) (0) +#endif + +#if defined(JSON_HEDLEY_TINYC_VERSION) + #undef JSON_HEDLEY_TINYC_VERSION +#endif +#if defined(__TINYC__) + #define JSON_HEDLEY_TINYC_VERSION JSON_HEDLEY_VERSION_ENCODE(__TINYC__ / 1000, (__TINYC__ / 100) % 10, __TINYC__ % 100) +#endif + +#if defined(JSON_HEDLEY_TINYC_VERSION_CHECK) + #undef JSON_HEDLEY_TINYC_VERSION_CHECK +#endif +#if defined(JSON_HEDLEY_TINYC_VERSION) + #define JSON_HEDLEY_TINYC_VERSION_CHECK(major,minor,patch) (JSON_HEDLEY_TINYC_VERSION >= JSON_HEDLEY_VERSION_ENCODE(major, minor, patch)) +#else + #define JSON_HEDLEY_TINYC_VERSION_CHECK(major,minor,patch) (0) +#endif + +#if defined(JSON_HEDLEY_DMC_VERSION) + #undef JSON_HEDLEY_DMC_VERSION +#endif +#if defined(__DMC__) + #define JSON_HEDLEY_DMC_VERSION JSON_HEDLEY_VERSION_ENCODE(__DMC__ >> 8, (__DMC__ >> 4) & 0xf, __DMC__ & 0xf) +#endif + +#if defined(JSON_HEDLEY_DMC_VERSION_CHECK) + #undef JSON_HEDLEY_DMC_VERSION_CHECK +#endif +#if defined(JSON_HEDLEY_DMC_VERSION) + #define JSON_HEDLEY_DMC_VERSION_CHECK(major,minor,patch) (JSON_HEDLEY_DMC_VERSION >= JSON_HEDLEY_VERSION_ENCODE(major, minor, patch)) +#else + #define JSON_HEDLEY_DMC_VERSION_CHECK(major,minor,patch) (0) +#endif + +#if defined(JSON_HEDLEY_COMPCERT_VERSION) + #undef JSON_HEDLEY_COMPCERT_VERSION +#endif +#if defined(__COMPCERT_VERSION__) + #define JSON_HEDLEY_COMPCERT_VERSION JSON_HEDLEY_VERSION_ENCODE(__COMPCERT_VERSION__ / 10000, (__COMPCERT_VERSION__ / 100) % 100, __COMPCERT_VERSION__ % 100) +#endif + +#if defined(JSON_HEDLEY_COMPCERT_VERSION_CHECK) + #undef JSON_HEDLEY_COMPCERT_VERSION_CHECK +#endif +#if defined(JSON_HEDLEY_COMPCERT_VERSION) + #define JSON_HEDLEY_COMPCERT_VERSION_CHECK(major,minor,patch) (JSON_HEDLEY_COMPCERT_VERSION >= JSON_HEDLEY_VERSION_ENCODE(major, minor, patch)) +#else + #define JSON_HEDLEY_COMPCERT_VERSION_CHECK(major,minor,patch) (0) +#endif + +#if defined(JSON_HEDLEY_PELLES_VERSION) + #undef JSON_HEDLEY_PELLES_VERSION +#endif +#if defined(__POCC__) + #define JSON_HEDLEY_PELLES_VERSION JSON_HEDLEY_VERSION_ENCODE(__POCC__ / 100, __POCC__ % 100, 0) +#endif + +#if defined(JSON_HEDLEY_PELLES_VERSION_CHECK) + #undef JSON_HEDLEY_PELLES_VERSION_CHECK +#endif +#if defined(JSON_HEDLEY_PELLES_VERSION) + #define JSON_HEDLEY_PELLES_VERSION_CHECK(major,minor,patch) (JSON_HEDLEY_PELLES_VERSION >= JSON_HEDLEY_VERSION_ENCODE(major, minor, patch)) +#else + #define JSON_HEDLEY_PELLES_VERSION_CHECK(major,minor,patch) (0) +#endif + +#if defined(JSON_HEDLEY_MCST_LCC_VERSION) + #undef JSON_HEDLEY_MCST_LCC_VERSION +#endif +#if defined(__LCC__) && defined(__LCC_MINOR__) + #define JSON_HEDLEY_MCST_LCC_VERSION JSON_HEDLEY_VERSION_ENCODE(__LCC__ / 100, __LCC__ % 100, __LCC_MINOR__) +#endif + +#if defined(JSON_HEDLEY_MCST_LCC_VERSION_CHECK) + #undef JSON_HEDLEY_MCST_LCC_VERSION_CHECK +#endif +#if defined(JSON_HEDLEY_MCST_LCC_VERSION) + #define JSON_HEDLEY_MCST_LCC_VERSION_CHECK(major,minor,patch) (JSON_HEDLEY_MCST_LCC_VERSION >= JSON_HEDLEY_VERSION_ENCODE(major, minor, patch)) +#else + #define JSON_HEDLEY_MCST_LCC_VERSION_CHECK(major,minor,patch) (0) +#endif + +#if defined(JSON_HEDLEY_GCC_VERSION) + #undef JSON_HEDLEY_GCC_VERSION +#endif +#if \ + defined(JSON_HEDLEY_GNUC_VERSION) && \ + !defined(__clang__) && \ + !defined(JSON_HEDLEY_INTEL_VERSION) && \ + !defined(JSON_HEDLEY_PGI_VERSION) && \ + !defined(JSON_HEDLEY_ARM_VERSION) && \ + !defined(JSON_HEDLEY_CRAY_VERSION) && \ + !defined(JSON_HEDLEY_TI_VERSION) && \ + !defined(JSON_HEDLEY_TI_ARMCL_VERSION) && \ + !defined(JSON_HEDLEY_TI_CL430_VERSION) && \ + !defined(JSON_HEDLEY_TI_CL2000_VERSION) && \ + !defined(JSON_HEDLEY_TI_CL6X_VERSION) && \ + !defined(JSON_HEDLEY_TI_CL7X_VERSION) && \ + !defined(JSON_HEDLEY_TI_CLPRU_VERSION) && \ + !defined(__COMPCERT__) && \ + !defined(JSON_HEDLEY_MCST_LCC_VERSION) + #define JSON_HEDLEY_GCC_VERSION JSON_HEDLEY_GNUC_VERSION +#endif + +#if defined(JSON_HEDLEY_GCC_VERSION_CHECK) + #undef JSON_HEDLEY_GCC_VERSION_CHECK +#endif +#if defined(JSON_HEDLEY_GCC_VERSION) + #define JSON_HEDLEY_GCC_VERSION_CHECK(major,minor,patch) (JSON_HEDLEY_GCC_VERSION >= JSON_HEDLEY_VERSION_ENCODE(major, minor, patch)) +#else + #define JSON_HEDLEY_GCC_VERSION_CHECK(major,minor,patch) (0) +#endif + +#if defined(JSON_HEDLEY_HAS_ATTRIBUTE) + #undef JSON_HEDLEY_HAS_ATTRIBUTE +#endif +#if \ + defined(__has_attribute) && \ + ( \ + (!defined(JSON_HEDLEY_IAR_VERSION) || JSON_HEDLEY_IAR_VERSION_CHECK(8,5,9)) \ + ) +# define JSON_HEDLEY_HAS_ATTRIBUTE(attribute) __has_attribute(attribute) +#else +# define JSON_HEDLEY_HAS_ATTRIBUTE(attribute) (0) +#endif + +#if defined(JSON_HEDLEY_GNUC_HAS_ATTRIBUTE) + #undef JSON_HEDLEY_GNUC_HAS_ATTRIBUTE +#endif +#if defined(__has_attribute) + #define JSON_HEDLEY_GNUC_HAS_ATTRIBUTE(attribute,major,minor,patch) JSON_HEDLEY_HAS_ATTRIBUTE(attribute) +#else + #define JSON_HEDLEY_GNUC_HAS_ATTRIBUTE(attribute,major,minor,patch) JSON_HEDLEY_GNUC_VERSION_CHECK(major,minor,patch) +#endif + +#if defined(JSON_HEDLEY_GCC_HAS_ATTRIBUTE) + #undef JSON_HEDLEY_GCC_HAS_ATTRIBUTE +#endif +#if defined(__has_attribute) + #define JSON_HEDLEY_GCC_HAS_ATTRIBUTE(attribute,major,minor,patch) JSON_HEDLEY_HAS_ATTRIBUTE(attribute) +#else + #define JSON_HEDLEY_GCC_HAS_ATTRIBUTE(attribute,major,minor,patch) JSON_HEDLEY_GCC_VERSION_CHECK(major,minor,patch) +#endif + +#if defined(JSON_HEDLEY_HAS_CPP_ATTRIBUTE) + #undef JSON_HEDLEY_HAS_CPP_ATTRIBUTE +#endif +#if \ + defined(__has_cpp_attribute) && \ + defined(__cplusplus) && \ + (!defined(JSON_HEDLEY_SUNPRO_VERSION) || JSON_HEDLEY_SUNPRO_VERSION_CHECK(5,15,0)) + #define JSON_HEDLEY_HAS_CPP_ATTRIBUTE(attribute) __has_cpp_attribute(attribute) +#else + #define JSON_HEDLEY_HAS_CPP_ATTRIBUTE(attribute) (0) +#endif + +#if defined(JSON_HEDLEY_HAS_CPP_ATTRIBUTE_NS) + #undef JSON_HEDLEY_HAS_CPP_ATTRIBUTE_NS +#endif +#if !defined(__cplusplus) || !defined(__has_cpp_attribute) + #define JSON_HEDLEY_HAS_CPP_ATTRIBUTE_NS(ns,attribute) (0) +#elif \ + !defined(JSON_HEDLEY_PGI_VERSION) && \ + !defined(JSON_HEDLEY_IAR_VERSION) && \ + (!defined(JSON_HEDLEY_SUNPRO_VERSION) || JSON_HEDLEY_SUNPRO_VERSION_CHECK(5,15,0)) && \ + (!defined(JSON_HEDLEY_MSVC_VERSION) || JSON_HEDLEY_MSVC_VERSION_CHECK(19,20,0)) + #define JSON_HEDLEY_HAS_CPP_ATTRIBUTE_NS(ns,attribute) JSON_HEDLEY_HAS_CPP_ATTRIBUTE(ns::attribute) +#else + #define JSON_HEDLEY_HAS_CPP_ATTRIBUTE_NS(ns,attribute) (0) +#endif + +#if defined(JSON_HEDLEY_GNUC_HAS_CPP_ATTRIBUTE) + #undef JSON_HEDLEY_GNUC_HAS_CPP_ATTRIBUTE +#endif +#if defined(__has_cpp_attribute) && defined(__cplusplus) + #define JSON_HEDLEY_GNUC_HAS_CPP_ATTRIBUTE(attribute,major,minor,patch) __has_cpp_attribute(attribute) +#else + #define JSON_HEDLEY_GNUC_HAS_CPP_ATTRIBUTE(attribute,major,minor,patch) JSON_HEDLEY_GNUC_VERSION_CHECK(major,minor,patch) +#endif + +#if defined(JSON_HEDLEY_GCC_HAS_CPP_ATTRIBUTE) + #undef JSON_HEDLEY_GCC_HAS_CPP_ATTRIBUTE +#endif +#if defined(__has_cpp_attribute) && defined(__cplusplus) + #define JSON_HEDLEY_GCC_HAS_CPP_ATTRIBUTE(attribute,major,minor,patch) __has_cpp_attribute(attribute) +#else + #define JSON_HEDLEY_GCC_HAS_CPP_ATTRIBUTE(attribute,major,minor,patch) JSON_HEDLEY_GCC_VERSION_CHECK(major,minor,patch) +#endif + +#if defined(JSON_HEDLEY_HAS_BUILTIN) + #undef JSON_HEDLEY_HAS_BUILTIN +#endif +#if defined(__has_builtin) + #define JSON_HEDLEY_HAS_BUILTIN(builtin) __has_builtin(builtin) +#else + #define JSON_HEDLEY_HAS_BUILTIN(builtin) (0) +#endif + +#if defined(JSON_HEDLEY_GNUC_HAS_BUILTIN) + #undef JSON_HEDLEY_GNUC_HAS_BUILTIN +#endif +#if defined(__has_builtin) + #define JSON_HEDLEY_GNUC_HAS_BUILTIN(builtin,major,minor,patch) __has_builtin(builtin) +#else + #define JSON_HEDLEY_GNUC_HAS_BUILTIN(builtin,major,minor,patch) JSON_HEDLEY_GNUC_VERSION_CHECK(major,minor,patch) +#endif + +#if defined(JSON_HEDLEY_GCC_HAS_BUILTIN) + #undef JSON_HEDLEY_GCC_HAS_BUILTIN +#endif +#if defined(__has_builtin) + #define JSON_HEDLEY_GCC_HAS_BUILTIN(builtin,major,minor,patch) __has_builtin(builtin) +#else + #define JSON_HEDLEY_GCC_HAS_BUILTIN(builtin,major,minor,patch) JSON_HEDLEY_GCC_VERSION_CHECK(major,minor,patch) +#endif + +#if defined(JSON_HEDLEY_HAS_FEATURE) + #undef JSON_HEDLEY_HAS_FEATURE +#endif +#if defined(__has_feature) + #define JSON_HEDLEY_HAS_FEATURE(feature) __has_feature(feature) +#else + #define JSON_HEDLEY_HAS_FEATURE(feature) (0) +#endif + +#if defined(JSON_HEDLEY_GNUC_HAS_FEATURE) + #undef JSON_HEDLEY_GNUC_HAS_FEATURE +#endif +#if defined(__has_feature) + #define JSON_HEDLEY_GNUC_HAS_FEATURE(feature,major,minor,patch) __has_feature(feature) +#else + #define JSON_HEDLEY_GNUC_HAS_FEATURE(feature,major,minor,patch) JSON_HEDLEY_GNUC_VERSION_CHECK(major,minor,patch) +#endif + +#if defined(JSON_HEDLEY_GCC_HAS_FEATURE) + #undef JSON_HEDLEY_GCC_HAS_FEATURE +#endif +#if defined(__has_feature) + #define JSON_HEDLEY_GCC_HAS_FEATURE(feature,major,minor,patch) __has_feature(feature) +#else + #define JSON_HEDLEY_GCC_HAS_FEATURE(feature,major,minor,patch) JSON_HEDLEY_GCC_VERSION_CHECK(major,minor,patch) +#endif + +#if defined(JSON_HEDLEY_HAS_EXTENSION) + #undef JSON_HEDLEY_HAS_EXTENSION +#endif +#if defined(__has_extension) + #define JSON_HEDLEY_HAS_EXTENSION(extension) __has_extension(extension) +#else + #define JSON_HEDLEY_HAS_EXTENSION(extension) (0) +#endif + +#if defined(JSON_HEDLEY_GNUC_HAS_EXTENSION) + #undef JSON_HEDLEY_GNUC_HAS_EXTENSION +#endif +#if defined(__has_extension) + #define JSON_HEDLEY_GNUC_HAS_EXTENSION(extension,major,minor,patch) __has_extension(extension) +#else + #define JSON_HEDLEY_GNUC_HAS_EXTENSION(extension,major,minor,patch) JSON_HEDLEY_GNUC_VERSION_CHECK(major,minor,patch) +#endif + +#if defined(JSON_HEDLEY_GCC_HAS_EXTENSION) + #undef JSON_HEDLEY_GCC_HAS_EXTENSION +#endif +#if defined(__has_extension) + #define JSON_HEDLEY_GCC_HAS_EXTENSION(extension,major,minor,patch) __has_extension(extension) +#else + #define JSON_HEDLEY_GCC_HAS_EXTENSION(extension,major,minor,patch) JSON_HEDLEY_GCC_VERSION_CHECK(major,minor,patch) +#endif + +#if defined(JSON_HEDLEY_HAS_DECLSPEC_ATTRIBUTE) + #undef JSON_HEDLEY_HAS_DECLSPEC_ATTRIBUTE +#endif +#if defined(__has_declspec_attribute) + #define JSON_HEDLEY_HAS_DECLSPEC_ATTRIBUTE(attribute) __has_declspec_attribute(attribute) +#else + #define JSON_HEDLEY_HAS_DECLSPEC_ATTRIBUTE(attribute) (0) +#endif + +#if defined(JSON_HEDLEY_GNUC_HAS_DECLSPEC_ATTRIBUTE) + #undef JSON_HEDLEY_GNUC_HAS_DECLSPEC_ATTRIBUTE +#endif +#if defined(__has_declspec_attribute) + #define JSON_HEDLEY_GNUC_HAS_DECLSPEC_ATTRIBUTE(attribute,major,minor,patch) __has_declspec_attribute(attribute) +#else + #define JSON_HEDLEY_GNUC_HAS_DECLSPEC_ATTRIBUTE(attribute,major,minor,patch) JSON_HEDLEY_GNUC_VERSION_CHECK(major,minor,patch) +#endif + +#if defined(JSON_HEDLEY_GCC_HAS_DECLSPEC_ATTRIBUTE) + #undef JSON_HEDLEY_GCC_HAS_DECLSPEC_ATTRIBUTE +#endif +#if defined(__has_declspec_attribute) + #define JSON_HEDLEY_GCC_HAS_DECLSPEC_ATTRIBUTE(attribute,major,minor,patch) __has_declspec_attribute(attribute) +#else + #define JSON_HEDLEY_GCC_HAS_DECLSPEC_ATTRIBUTE(attribute,major,minor,patch) JSON_HEDLEY_GCC_VERSION_CHECK(major,minor,patch) +#endif + +#if defined(JSON_HEDLEY_HAS_WARNING) + #undef JSON_HEDLEY_HAS_WARNING +#endif +#if defined(__has_warning) + #define JSON_HEDLEY_HAS_WARNING(warning) __has_warning(warning) +#else + #define JSON_HEDLEY_HAS_WARNING(warning) (0) +#endif + +#if defined(JSON_HEDLEY_GNUC_HAS_WARNING) + #undef JSON_HEDLEY_GNUC_HAS_WARNING +#endif +#if defined(__has_warning) + #define JSON_HEDLEY_GNUC_HAS_WARNING(warning,major,minor,patch) __has_warning(warning) +#else + #define JSON_HEDLEY_GNUC_HAS_WARNING(warning,major,minor,patch) JSON_HEDLEY_GNUC_VERSION_CHECK(major,minor,patch) +#endif + +#if defined(JSON_HEDLEY_GCC_HAS_WARNING) + #undef JSON_HEDLEY_GCC_HAS_WARNING +#endif +#if defined(__has_warning) + #define JSON_HEDLEY_GCC_HAS_WARNING(warning,major,minor,patch) __has_warning(warning) +#else + #define JSON_HEDLEY_GCC_HAS_WARNING(warning,major,minor,patch) JSON_HEDLEY_GCC_VERSION_CHECK(major,minor,patch) +#endif + +#if \ + (defined(__STDC_VERSION__) && (__STDC_VERSION__ >= 199901L)) || \ + defined(__clang__) || \ + JSON_HEDLEY_GCC_VERSION_CHECK(3,0,0) || \ + JSON_HEDLEY_INTEL_VERSION_CHECK(13,0,0) || \ + JSON_HEDLEY_IAR_VERSION_CHECK(8,0,0) || \ + JSON_HEDLEY_PGI_VERSION_CHECK(18,4,0) || \ + JSON_HEDLEY_ARM_VERSION_CHECK(4,1,0) || \ + JSON_HEDLEY_TI_VERSION_CHECK(15,12,0) || \ + JSON_HEDLEY_TI_ARMCL_VERSION_CHECK(4,7,0) || \ + JSON_HEDLEY_TI_CL430_VERSION_CHECK(2,0,1) || \ + JSON_HEDLEY_TI_CL2000_VERSION_CHECK(6,1,0) || \ + JSON_HEDLEY_TI_CL6X_VERSION_CHECK(7,0,0) || \ + JSON_HEDLEY_TI_CL7X_VERSION_CHECK(1,2,0) || \ + JSON_HEDLEY_TI_CLPRU_VERSION_CHECK(2,1,0) || \ + JSON_HEDLEY_CRAY_VERSION_CHECK(5,0,0) || \ + JSON_HEDLEY_TINYC_VERSION_CHECK(0,9,17) || \ + JSON_HEDLEY_SUNPRO_VERSION_CHECK(8,0,0) || \ + (JSON_HEDLEY_IBM_VERSION_CHECK(10,1,0) && defined(__C99_PRAGMA_OPERATOR)) + #define JSON_HEDLEY_PRAGMA(value) _Pragma(#value) +#elif JSON_HEDLEY_MSVC_VERSION_CHECK(15,0,0) + #define JSON_HEDLEY_PRAGMA(value) __pragma(value) +#else + #define JSON_HEDLEY_PRAGMA(value) +#endif + +#if defined(JSON_HEDLEY_DIAGNOSTIC_PUSH) + #undef JSON_HEDLEY_DIAGNOSTIC_PUSH +#endif +#if defined(JSON_HEDLEY_DIAGNOSTIC_POP) + #undef JSON_HEDLEY_DIAGNOSTIC_POP +#endif +#if defined(__clang__) + #define JSON_HEDLEY_DIAGNOSTIC_PUSH _Pragma("clang diagnostic push") + #define JSON_HEDLEY_DIAGNOSTIC_POP _Pragma("clang diagnostic pop") +#elif JSON_HEDLEY_INTEL_VERSION_CHECK(13,0,0) + #define JSON_HEDLEY_DIAGNOSTIC_PUSH _Pragma("warning(push)") + #define JSON_HEDLEY_DIAGNOSTIC_POP _Pragma("warning(pop)") +#elif JSON_HEDLEY_GCC_VERSION_CHECK(4,6,0) + #define JSON_HEDLEY_DIAGNOSTIC_PUSH _Pragma("GCC diagnostic push") + #define JSON_HEDLEY_DIAGNOSTIC_POP _Pragma("GCC diagnostic pop") +#elif \ + JSON_HEDLEY_MSVC_VERSION_CHECK(15,0,0) || \ + JSON_HEDLEY_INTEL_CL_VERSION_CHECK(2021,1,0) + #define JSON_HEDLEY_DIAGNOSTIC_PUSH __pragma(warning(push)) + #define JSON_HEDLEY_DIAGNOSTIC_POP __pragma(warning(pop)) +#elif JSON_HEDLEY_ARM_VERSION_CHECK(5,6,0) + #define JSON_HEDLEY_DIAGNOSTIC_PUSH _Pragma("push") + #define JSON_HEDLEY_DIAGNOSTIC_POP _Pragma("pop") +#elif \ + JSON_HEDLEY_TI_VERSION_CHECK(15,12,0) || \ + JSON_HEDLEY_TI_ARMCL_VERSION_CHECK(5,2,0) || \ + JSON_HEDLEY_TI_CL430_VERSION_CHECK(4,4,0) || \ + JSON_HEDLEY_TI_CL6X_VERSION_CHECK(8,1,0) || \ + JSON_HEDLEY_TI_CL7X_VERSION_CHECK(1,2,0) || \ + JSON_HEDLEY_TI_CLPRU_VERSION_CHECK(2,1,0) + #define JSON_HEDLEY_DIAGNOSTIC_PUSH _Pragma("diag_push") + #define JSON_HEDLEY_DIAGNOSTIC_POP _Pragma("diag_pop") +#elif JSON_HEDLEY_PELLES_VERSION_CHECK(2,90,0) + #define JSON_HEDLEY_DIAGNOSTIC_PUSH _Pragma("warning(push)") + #define JSON_HEDLEY_DIAGNOSTIC_POP _Pragma("warning(pop)") +#else + #define JSON_HEDLEY_DIAGNOSTIC_PUSH + #define JSON_HEDLEY_DIAGNOSTIC_POP +#endif + +/* JSON_HEDLEY_DIAGNOSTIC_DISABLE_CPP98_COMPAT_WRAP_ is for + HEDLEY INTERNAL USE ONLY. API subject to change without notice. */ +#if defined(JSON_HEDLEY_DIAGNOSTIC_DISABLE_CPP98_COMPAT_WRAP_) + #undef JSON_HEDLEY_DIAGNOSTIC_DISABLE_CPP98_COMPAT_WRAP_ +#endif +#if defined(__cplusplus) +# if JSON_HEDLEY_HAS_WARNING("-Wc++98-compat") +# if JSON_HEDLEY_HAS_WARNING("-Wc++17-extensions") +# if JSON_HEDLEY_HAS_WARNING("-Wc++1z-extensions") +# define JSON_HEDLEY_DIAGNOSTIC_DISABLE_CPP98_COMPAT_WRAP_(xpr) \ + JSON_HEDLEY_DIAGNOSTIC_PUSH \ + _Pragma("clang diagnostic ignored \"-Wc++98-compat\"") \ + _Pragma("clang diagnostic ignored \"-Wc++17-extensions\"") \ + _Pragma("clang diagnostic ignored \"-Wc++1z-extensions\"") \ + xpr \ + JSON_HEDLEY_DIAGNOSTIC_POP +# else +# define JSON_HEDLEY_DIAGNOSTIC_DISABLE_CPP98_COMPAT_WRAP_(xpr) \ + JSON_HEDLEY_DIAGNOSTIC_PUSH \ + _Pragma("clang diagnostic ignored \"-Wc++98-compat\"") \ + _Pragma("clang diagnostic ignored \"-Wc++17-extensions\"") \ + xpr \ + JSON_HEDLEY_DIAGNOSTIC_POP +# endif +# else +# define JSON_HEDLEY_DIAGNOSTIC_DISABLE_CPP98_COMPAT_WRAP_(xpr) \ + JSON_HEDLEY_DIAGNOSTIC_PUSH \ + _Pragma("clang diagnostic ignored \"-Wc++98-compat\"") \ + xpr \ + JSON_HEDLEY_DIAGNOSTIC_POP +# endif +# endif +#endif +#if !defined(JSON_HEDLEY_DIAGNOSTIC_DISABLE_CPP98_COMPAT_WRAP_) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_CPP98_COMPAT_WRAP_(x) x +#endif + +#if defined(JSON_HEDLEY_CONST_CAST) + #undef JSON_HEDLEY_CONST_CAST +#endif +#if defined(__cplusplus) +# define JSON_HEDLEY_CONST_CAST(T, expr) (const_cast(expr)) +#elif \ + JSON_HEDLEY_HAS_WARNING("-Wcast-qual") || \ + JSON_HEDLEY_GCC_VERSION_CHECK(4,6,0) || \ + JSON_HEDLEY_INTEL_VERSION_CHECK(13,0,0) +# define JSON_HEDLEY_CONST_CAST(T, expr) (__extension__ ({ \ + JSON_HEDLEY_DIAGNOSTIC_PUSH \ + JSON_HEDLEY_DIAGNOSTIC_DISABLE_CAST_QUAL \ + ((T) (expr)); \ + JSON_HEDLEY_DIAGNOSTIC_POP \ + })) +#else +# define JSON_HEDLEY_CONST_CAST(T, expr) ((T) (expr)) +#endif + +#if defined(JSON_HEDLEY_REINTERPRET_CAST) + #undef JSON_HEDLEY_REINTERPRET_CAST +#endif +#if defined(__cplusplus) + #define JSON_HEDLEY_REINTERPRET_CAST(T, expr) (reinterpret_cast(expr)) +#else + #define JSON_HEDLEY_REINTERPRET_CAST(T, expr) ((T) (expr)) +#endif + +#if defined(JSON_HEDLEY_STATIC_CAST) + #undef JSON_HEDLEY_STATIC_CAST +#endif +#if defined(__cplusplus) + #define JSON_HEDLEY_STATIC_CAST(T, expr) (static_cast(expr)) +#else + #define JSON_HEDLEY_STATIC_CAST(T, expr) ((T) (expr)) +#endif + +#if defined(JSON_HEDLEY_CPP_CAST) + #undef JSON_HEDLEY_CPP_CAST +#endif +#if defined(__cplusplus) +# if JSON_HEDLEY_HAS_WARNING("-Wold-style-cast") +# define JSON_HEDLEY_CPP_CAST(T, expr) \ + JSON_HEDLEY_DIAGNOSTIC_PUSH \ + _Pragma("clang diagnostic ignored \"-Wold-style-cast\"") \ + ((T) (expr)) \ + JSON_HEDLEY_DIAGNOSTIC_POP +# elif JSON_HEDLEY_IAR_VERSION_CHECK(8,3,0) +# define JSON_HEDLEY_CPP_CAST(T, expr) \ + JSON_HEDLEY_DIAGNOSTIC_PUSH \ + _Pragma("diag_suppress=Pe137") \ + JSON_HEDLEY_DIAGNOSTIC_POP +# else +# define JSON_HEDLEY_CPP_CAST(T, expr) ((T) (expr)) +# endif +#else +# define JSON_HEDLEY_CPP_CAST(T, expr) (expr) +#endif + +#if defined(JSON_HEDLEY_DIAGNOSTIC_DISABLE_DEPRECATED) + #undef JSON_HEDLEY_DIAGNOSTIC_DISABLE_DEPRECATED +#endif +#if JSON_HEDLEY_HAS_WARNING("-Wdeprecated-declarations") + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_DEPRECATED _Pragma("clang diagnostic ignored \"-Wdeprecated-declarations\"") +#elif JSON_HEDLEY_INTEL_VERSION_CHECK(13,0,0) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_DEPRECATED _Pragma("warning(disable:1478 1786)") +#elif JSON_HEDLEY_INTEL_CL_VERSION_CHECK(2021,1,0) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_DEPRECATED __pragma(warning(disable:1478 1786)) +#elif JSON_HEDLEY_PGI_VERSION_CHECK(20,7,0) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_DEPRECATED _Pragma("diag_suppress 1215,1216,1444,1445") +#elif JSON_HEDLEY_PGI_VERSION_CHECK(17,10,0) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_DEPRECATED _Pragma("diag_suppress 1215,1444") +#elif JSON_HEDLEY_GCC_VERSION_CHECK(4,3,0) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_DEPRECATED _Pragma("GCC diagnostic ignored \"-Wdeprecated-declarations\"") +#elif JSON_HEDLEY_MSVC_VERSION_CHECK(15,0,0) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_DEPRECATED __pragma(warning(disable:4996)) +#elif JSON_HEDLEY_MCST_LCC_VERSION_CHECK(1,25,10) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_DEPRECATED _Pragma("diag_suppress 1215,1444") +#elif \ + JSON_HEDLEY_TI_VERSION_CHECK(15,12,0) || \ + (JSON_HEDLEY_TI_ARMCL_VERSION_CHECK(4,8,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_ARMCL_VERSION_CHECK(5,2,0) || \ + (JSON_HEDLEY_TI_CL2000_VERSION_CHECK(6,0,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_CL2000_VERSION_CHECK(6,4,0) || \ + (JSON_HEDLEY_TI_CL430_VERSION_CHECK(4,0,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_CL430_VERSION_CHECK(4,3,0) || \ + (JSON_HEDLEY_TI_CL6X_VERSION_CHECK(7,2,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_CL6X_VERSION_CHECK(7,5,0) || \ + JSON_HEDLEY_TI_CL7X_VERSION_CHECK(1,2,0) || \ + JSON_HEDLEY_TI_CLPRU_VERSION_CHECK(2,1,0) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_DEPRECATED _Pragma("diag_suppress 1291,1718") +#elif JSON_HEDLEY_SUNPRO_VERSION_CHECK(5,13,0) && !defined(__cplusplus) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_DEPRECATED _Pragma("error_messages(off,E_DEPRECATED_ATT,E_DEPRECATED_ATT_MESS)") +#elif JSON_HEDLEY_SUNPRO_VERSION_CHECK(5,13,0) && defined(__cplusplus) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_DEPRECATED _Pragma("error_messages(off,symdeprecated,symdeprecated2)") +#elif JSON_HEDLEY_IAR_VERSION_CHECK(8,0,0) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_DEPRECATED _Pragma("diag_suppress=Pe1444,Pe1215") +#elif JSON_HEDLEY_PELLES_VERSION_CHECK(2,90,0) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_DEPRECATED _Pragma("warn(disable:2241)") +#else + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_DEPRECATED +#endif + +#if defined(JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNKNOWN_PRAGMAS) + #undef JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNKNOWN_PRAGMAS +#endif +#if JSON_HEDLEY_HAS_WARNING("-Wunknown-pragmas") + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNKNOWN_PRAGMAS _Pragma("clang diagnostic ignored \"-Wunknown-pragmas\"") +#elif JSON_HEDLEY_INTEL_VERSION_CHECK(13,0,0) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNKNOWN_PRAGMAS _Pragma("warning(disable:161)") +#elif JSON_HEDLEY_INTEL_CL_VERSION_CHECK(2021,1,0) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNKNOWN_PRAGMAS __pragma(warning(disable:161)) +#elif JSON_HEDLEY_PGI_VERSION_CHECK(17,10,0) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNKNOWN_PRAGMAS _Pragma("diag_suppress 1675") +#elif JSON_HEDLEY_GCC_VERSION_CHECK(4,3,0) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNKNOWN_PRAGMAS _Pragma("GCC diagnostic ignored \"-Wunknown-pragmas\"") +#elif JSON_HEDLEY_MSVC_VERSION_CHECK(15,0,0) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNKNOWN_PRAGMAS __pragma(warning(disable:4068)) +#elif \ + JSON_HEDLEY_TI_VERSION_CHECK(16,9,0) || \ + JSON_HEDLEY_TI_CL6X_VERSION_CHECK(8,0,0) || \ + JSON_HEDLEY_TI_CL7X_VERSION_CHECK(1,2,0) || \ + JSON_HEDLEY_TI_CLPRU_VERSION_CHECK(2,3,0) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNKNOWN_PRAGMAS _Pragma("diag_suppress 163") +#elif JSON_HEDLEY_TI_CL6X_VERSION_CHECK(8,0,0) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNKNOWN_PRAGMAS _Pragma("diag_suppress 163") +#elif JSON_HEDLEY_IAR_VERSION_CHECK(8,0,0) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNKNOWN_PRAGMAS _Pragma("diag_suppress=Pe161") +#elif JSON_HEDLEY_MCST_LCC_VERSION_CHECK(1,25,10) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNKNOWN_PRAGMAS _Pragma("diag_suppress 161") +#else + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNKNOWN_PRAGMAS +#endif + +#if defined(JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNKNOWN_CPP_ATTRIBUTES) + #undef JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNKNOWN_CPP_ATTRIBUTES +#endif +#if JSON_HEDLEY_HAS_WARNING("-Wunknown-attributes") + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNKNOWN_CPP_ATTRIBUTES _Pragma("clang diagnostic ignored \"-Wunknown-attributes\"") +#elif JSON_HEDLEY_GCC_VERSION_CHECK(4,6,0) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNKNOWN_CPP_ATTRIBUTES _Pragma("GCC diagnostic ignored \"-Wdeprecated-declarations\"") +#elif JSON_HEDLEY_INTEL_VERSION_CHECK(17,0,0) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNKNOWN_CPP_ATTRIBUTES _Pragma("warning(disable:1292)") +#elif JSON_HEDLEY_INTEL_CL_VERSION_CHECK(2021,1,0) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNKNOWN_CPP_ATTRIBUTES __pragma(warning(disable:1292)) +#elif JSON_HEDLEY_MSVC_VERSION_CHECK(19,0,0) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNKNOWN_CPP_ATTRIBUTES __pragma(warning(disable:5030)) +#elif JSON_HEDLEY_PGI_VERSION_CHECK(20,7,0) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNKNOWN_CPP_ATTRIBUTES _Pragma("diag_suppress 1097,1098") +#elif JSON_HEDLEY_PGI_VERSION_CHECK(17,10,0) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNKNOWN_CPP_ATTRIBUTES _Pragma("diag_suppress 1097") +#elif JSON_HEDLEY_SUNPRO_VERSION_CHECK(5,14,0) && defined(__cplusplus) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNKNOWN_CPP_ATTRIBUTES _Pragma("error_messages(off,attrskipunsup)") +#elif \ + JSON_HEDLEY_TI_VERSION_CHECK(18,1,0) || \ + JSON_HEDLEY_TI_CL6X_VERSION_CHECK(8,3,0) || \ + JSON_HEDLEY_TI_CL7X_VERSION_CHECK(1,2,0) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNKNOWN_CPP_ATTRIBUTES _Pragma("diag_suppress 1173") +#elif JSON_HEDLEY_IAR_VERSION_CHECK(8,0,0) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNKNOWN_CPP_ATTRIBUTES _Pragma("diag_suppress=Pe1097") +#elif JSON_HEDLEY_MCST_LCC_VERSION_CHECK(1,25,10) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNKNOWN_CPP_ATTRIBUTES _Pragma("diag_suppress 1097") +#else + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNKNOWN_CPP_ATTRIBUTES +#endif + +#if defined(JSON_HEDLEY_DIAGNOSTIC_DISABLE_CAST_QUAL) + #undef JSON_HEDLEY_DIAGNOSTIC_DISABLE_CAST_QUAL +#endif +#if JSON_HEDLEY_HAS_WARNING("-Wcast-qual") + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_CAST_QUAL _Pragma("clang diagnostic ignored \"-Wcast-qual\"") +#elif JSON_HEDLEY_INTEL_VERSION_CHECK(13,0,0) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_CAST_QUAL _Pragma("warning(disable:2203 2331)") +#elif JSON_HEDLEY_GCC_VERSION_CHECK(3,0,0) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_CAST_QUAL _Pragma("GCC diagnostic ignored \"-Wcast-qual\"") +#else + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_CAST_QUAL +#endif + +#if defined(JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNUSED_FUNCTION) + #undef JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNUSED_FUNCTION +#endif +#if JSON_HEDLEY_HAS_WARNING("-Wunused-function") + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNUSED_FUNCTION _Pragma("clang diagnostic ignored \"-Wunused-function\"") +#elif JSON_HEDLEY_GCC_VERSION_CHECK(3,4,0) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNUSED_FUNCTION _Pragma("GCC diagnostic ignored \"-Wunused-function\"") +#elif JSON_HEDLEY_MSVC_VERSION_CHECK(1,0,0) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNUSED_FUNCTION __pragma(warning(disable:4505)) +#elif JSON_HEDLEY_MCST_LCC_VERSION_CHECK(1,25,10) + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNUSED_FUNCTION _Pragma("diag_suppress 3142") +#else + #define JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNUSED_FUNCTION +#endif + +#if defined(JSON_HEDLEY_DEPRECATED) + #undef JSON_HEDLEY_DEPRECATED +#endif +#if defined(JSON_HEDLEY_DEPRECATED_FOR) + #undef JSON_HEDLEY_DEPRECATED_FOR +#endif +#if \ + JSON_HEDLEY_MSVC_VERSION_CHECK(14,0,0) || \ + JSON_HEDLEY_INTEL_CL_VERSION_CHECK(2021,1,0) + #define JSON_HEDLEY_DEPRECATED(since) __declspec(deprecated("Since " # since)) + #define JSON_HEDLEY_DEPRECATED_FOR(since, replacement) __declspec(deprecated("Since " #since "; use " #replacement)) +#elif \ + (JSON_HEDLEY_HAS_EXTENSION(attribute_deprecated_with_message) && !defined(JSON_HEDLEY_IAR_VERSION)) || \ + JSON_HEDLEY_GCC_VERSION_CHECK(4,5,0) || \ + JSON_HEDLEY_INTEL_VERSION_CHECK(13,0,0) || \ + JSON_HEDLEY_ARM_VERSION_CHECK(5,6,0) || \ + JSON_HEDLEY_SUNPRO_VERSION_CHECK(5,13,0) || \ + JSON_HEDLEY_PGI_VERSION_CHECK(17,10,0) || \ + JSON_HEDLEY_TI_VERSION_CHECK(18,1,0) || \ + JSON_HEDLEY_TI_ARMCL_VERSION_CHECK(18,1,0) || \ + JSON_HEDLEY_TI_CL6X_VERSION_CHECK(8,3,0) || \ + JSON_HEDLEY_TI_CL7X_VERSION_CHECK(1,2,0) || \ + JSON_HEDLEY_TI_CLPRU_VERSION_CHECK(2,3,0) || \ + JSON_HEDLEY_MCST_LCC_VERSION_CHECK(1,25,10) + #define JSON_HEDLEY_DEPRECATED(since) __attribute__((__deprecated__("Since " #since))) + #define JSON_HEDLEY_DEPRECATED_FOR(since, replacement) __attribute__((__deprecated__("Since " #since "; use " #replacement))) +#elif defined(__cplusplus) && (__cplusplus >= 201402L) + #define JSON_HEDLEY_DEPRECATED(since) JSON_HEDLEY_DIAGNOSTIC_DISABLE_CPP98_COMPAT_WRAP_([[deprecated("Since " #since)]]) + #define JSON_HEDLEY_DEPRECATED_FOR(since, replacement) JSON_HEDLEY_DIAGNOSTIC_DISABLE_CPP98_COMPAT_WRAP_([[deprecated("Since " #since "; use " #replacement)]]) +#elif \ + JSON_HEDLEY_HAS_ATTRIBUTE(deprecated) || \ + JSON_HEDLEY_GCC_VERSION_CHECK(3,1,0) || \ + JSON_HEDLEY_ARM_VERSION_CHECK(4,1,0) || \ + JSON_HEDLEY_TI_VERSION_CHECK(15,12,0) || \ + (JSON_HEDLEY_TI_ARMCL_VERSION_CHECK(4,8,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_ARMCL_VERSION_CHECK(5,2,0) || \ + (JSON_HEDLEY_TI_CL2000_VERSION_CHECK(6,0,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_CL2000_VERSION_CHECK(6,4,0) || \ + (JSON_HEDLEY_TI_CL430_VERSION_CHECK(4,0,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_CL430_VERSION_CHECK(4,3,0) || \ + (JSON_HEDLEY_TI_CL6X_VERSION_CHECK(7,2,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_CL6X_VERSION_CHECK(7,5,0) || \ + JSON_HEDLEY_TI_CL7X_VERSION_CHECK(1,2,0) || \ + JSON_HEDLEY_TI_CLPRU_VERSION_CHECK(2,1,0) || \ + JSON_HEDLEY_MCST_LCC_VERSION_CHECK(1,25,10) || \ + JSON_HEDLEY_IAR_VERSION_CHECK(8,10,0) + #define JSON_HEDLEY_DEPRECATED(since) __attribute__((__deprecated__)) + #define JSON_HEDLEY_DEPRECATED_FOR(since, replacement) __attribute__((__deprecated__)) +#elif \ + JSON_HEDLEY_MSVC_VERSION_CHECK(13,10,0) || \ + JSON_HEDLEY_PELLES_VERSION_CHECK(6,50,0) || \ + JSON_HEDLEY_INTEL_CL_VERSION_CHECK(2021,1,0) + #define JSON_HEDLEY_DEPRECATED(since) __declspec(deprecated) + #define JSON_HEDLEY_DEPRECATED_FOR(since, replacement) __declspec(deprecated) +#elif JSON_HEDLEY_IAR_VERSION_CHECK(8,0,0) + #define JSON_HEDLEY_DEPRECATED(since) _Pragma("deprecated") + #define JSON_HEDLEY_DEPRECATED_FOR(since, replacement) _Pragma("deprecated") +#else + #define JSON_HEDLEY_DEPRECATED(since) + #define JSON_HEDLEY_DEPRECATED_FOR(since, replacement) +#endif + +#if defined(JSON_HEDLEY_UNAVAILABLE) + #undef JSON_HEDLEY_UNAVAILABLE +#endif +#if \ + JSON_HEDLEY_HAS_ATTRIBUTE(warning) || \ + JSON_HEDLEY_GCC_VERSION_CHECK(4,3,0) || \ + JSON_HEDLEY_INTEL_VERSION_CHECK(13,0,0) || \ + JSON_HEDLEY_MCST_LCC_VERSION_CHECK(1,25,10) + #define JSON_HEDLEY_UNAVAILABLE(available_since) __attribute__((__warning__("Not available until " #available_since))) +#else + #define JSON_HEDLEY_UNAVAILABLE(available_since) +#endif + +#if defined(JSON_HEDLEY_WARN_UNUSED_RESULT) + #undef JSON_HEDLEY_WARN_UNUSED_RESULT +#endif +#if defined(JSON_HEDLEY_WARN_UNUSED_RESULT_MSG) + #undef JSON_HEDLEY_WARN_UNUSED_RESULT_MSG +#endif +#if \ + JSON_HEDLEY_HAS_ATTRIBUTE(warn_unused_result) || \ + JSON_HEDLEY_GCC_VERSION_CHECK(3,4,0) || \ + JSON_HEDLEY_INTEL_VERSION_CHECK(13,0,0) || \ + JSON_HEDLEY_TI_VERSION_CHECK(15,12,0) || \ + (JSON_HEDLEY_TI_ARMCL_VERSION_CHECK(4,8,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_ARMCL_VERSION_CHECK(5,2,0) || \ + (JSON_HEDLEY_TI_CL2000_VERSION_CHECK(6,0,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_CL2000_VERSION_CHECK(6,4,0) || \ + (JSON_HEDLEY_TI_CL430_VERSION_CHECK(4,0,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_CL430_VERSION_CHECK(4,3,0) || \ + (JSON_HEDLEY_TI_CL6X_VERSION_CHECK(7,2,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_CL6X_VERSION_CHECK(7,5,0) || \ + JSON_HEDLEY_TI_CL7X_VERSION_CHECK(1,2,0) || \ + JSON_HEDLEY_TI_CLPRU_VERSION_CHECK(2,1,0) || \ + (JSON_HEDLEY_SUNPRO_VERSION_CHECK(5,15,0) && defined(__cplusplus)) || \ + JSON_HEDLEY_PGI_VERSION_CHECK(17,10,0) || \ + JSON_HEDLEY_MCST_LCC_VERSION_CHECK(1,25,10) + #define JSON_HEDLEY_WARN_UNUSED_RESULT __attribute__((__warn_unused_result__)) + #define JSON_HEDLEY_WARN_UNUSED_RESULT_MSG(msg) __attribute__((__warn_unused_result__)) +#elif (JSON_HEDLEY_HAS_CPP_ATTRIBUTE(nodiscard) >= 201907L) + #define JSON_HEDLEY_WARN_UNUSED_RESULT JSON_HEDLEY_DIAGNOSTIC_DISABLE_CPP98_COMPAT_WRAP_([[nodiscard]]) + #define JSON_HEDLEY_WARN_UNUSED_RESULT_MSG(msg) JSON_HEDLEY_DIAGNOSTIC_DISABLE_CPP98_COMPAT_WRAP_([[nodiscard(msg)]]) +#elif JSON_HEDLEY_HAS_CPP_ATTRIBUTE(nodiscard) + #define JSON_HEDLEY_WARN_UNUSED_RESULT JSON_HEDLEY_DIAGNOSTIC_DISABLE_CPP98_COMPAT_WRAP_([[nodiscard]]) + #define JSON_HEDLEY_WARN_UNUSED_RESULT_MSG(msg) JSON_HEDLEY_DIAGNOSTIC_DISABLE_CPP98_COMPAT_WRAP_([[nodiscard]]) +#elif defined(_Check_return_) /* SAL */ + #define JSON_HEDLEY_WARN_UNUSED_RESULT _Check_return_ + #define JSON_HEDLEY_WARN_UNUSED_RESULT_MSG(msg) _Check_return_ +#else + #define JSON_HEDLEY_WARN_UNUSED_RESULT + #define JSON_HEDLEY_WARN_UNUSED_RESULT_MSG(msg) +#endif + +#if defined(JSON_HEDLEY_SENTINEL) + #undef JSON_HEDLEY_SENTINEL +#endif +#if \ + JSON_HEDLEY_HAS_ATTRIBUTE(sentinel) || \ + JSON_HEDLEY_GCC_VERSION_CHECK(4,0,0) || \ + JSON_HEDLEY_INTEL_VERSION_CHECK(13,0,0) || \ + JSON_HEDLEY_ARM_VERSION_CHECK(5,4,0) || \ + JSON_HEDLEY_MCST_LCC_VERSION_CHECK(1,25,10) + #define JSON_HEDLEY_SENTINEL(position) __attribute__((__sentinel__(position))) +#else + #define JSON_HEDLEY_SENTINEL(position) +#endif + +#if defined(JSON_HEDLEY_NO_RETURN) + #undef JSON_HEDLEY_NO_RETURN +#endif +#if JSON_HEDLEY_IAR_VERSION_CHECK(8,0,0) + #define JSON_HEDLEY_NO_RETURN __noreturn +#elif \ + JSON_HEDLEY_INTEL_VERSION_CHECK(13,0,0) || \ + JSON_HEDLEY_MCST_LCC_VERSION_CHECK(1,25,10) + #define JSON_HEDLEY_NO_RETURN __attribute__((__noreturn__)) +#elif defined(__STDC_VERSION__) && __STDC_VERSION__ >= 201112L + #define JSON_HEDLEY_NO_RETURN _Noreturn +#elif defined(__cplusplus) && (__cplusplus >= 201103L) + #define JSON_HEDLEY_NO_RETURN JSON_HEDLEY_DIAGNOSTIC_DISABLE_CPP98_COMPAT_WRAP_([[noreturn]]) +#elif \ + JSON_HEDLEY_HAS_ATTRIBUTE(noreturn) || \ + JSON_HEDLEY_GCC_VERSION_CHECK(3,2,0) || \ + JSON_HEDLEY_SUNPRO_VERSION_CHECK(5,11,0) || \ + JSON_HEDLEY_ARM_VERSION_CHECK(4,1,0) || \ + JSON_HEDLEY_IBM_VERSION_CHECK(10,1,0) || \ + JSON_HEDLEY_TI_VERSION_CHECK(15,12,0) || \ + (JSON_HEDLEY_TI_ARMCL_VERSION_CHECK(4,8,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_ARMCL_VERSION_CHECK(5,2,0) || \ + (JSON_HEDLEY_TI_CL2000_VERSION_CHECK(6,0,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_CL2000_VERSION_CHECK(6,4,0) || \ + (JSON_HEDLEY_TI_CL430_VERSION_CHECK(4,0,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_CL430_VERSION_CHECK(4,3,0) || \ + (JSON_HEDLEY_TI_CL6X_VERSION_CHECK(7,2,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_CL6X_VERSION_CHECK(7,5,0) || \ + JSON_HEDLEY_TI_CL7X_VERSION_CHECK(1,2,0) || \ + JSON_HEDLEY_TI_CLPRU_VERSION_CHECK(2,1,0) || \ + JSON_HEDLEY_IAR_VERSION_CHECK(8,10,0) + #define JSON_HEDLEY_NO_RETURN __attribute__((__noreturn__)) +#elif JSON_HEDLEY_SUNPRO_VERSION_CHECK(5,10,0) + #define JSON_HEDLEY_NO_RETURN _Pragma("does_not_return") +#elif \ + JSON_HEDLEY_MSVC_VERSION_CHECK(13,10,0) || \ + JSON_HEDLEY_INTEL_CL_VERSION_CHECK(2021,1,0) + #define JSON_HEDLEY_NO_RETURN __declspec(noreturn) +#elif JSON_HEDLEY_TI_CL6X_VERSION_CHECK(6,0,0) && defined(__cplusplus) + #define JSON_HEDLEY_NO_RETURN _Pragma("FUNC_NEVER_RETURNS;") +#elif JSON_HEDLEY_COMPCERT_VERSION_CHECK(3,2,0) + #define JSON_HEDLEY_NO_RETURN __attribute((noreturn)) +#elif JSON_HEDLEY_PELLES_VERSION_CHECK(9,0,0) + #define JSON_HEDLEY_NO_RETURN __declspec(noreturn) +#else + #define JSON_HEDLEY_NO_RETURN +#endif + +#if defined(JSON_HEDLEY_NO_ESCAPE) + #undef JSON_HEDLEY_NO_ESCAPE +#endif +#if JSON_HEDLEY_HAS_ATTRIBUTE(noescape) + #define JSON_HEDLEY_NO_ESCAPE __attribute__((__noescape__)) +#else + #define JSON_HEDLEY_NO_ESCAPE +#endif + +#if defined(JSON_HEDLEY_UNREACHABLE) + #undef JSON_HEDLEY_UNREACHABLE +#endif +#if defined(JSON_HEDLEY_UNREACHABLE_RETURN) + #undef JSON_HEDLEY_UNREACHABLE_RETURN +#endif +#if defined(JSON_HEDLEY_ASSUME) + #undef JSON_HEDLEY_ASSUME +#endif +#if \ + JSON_HEDLEY_MSVC_VERSION_CHECK(13,10,0) || \ + JSON_HEDLEY_INTEL_VERSION_CHECK(13,0,0) || \ + JSON_HEDLEY_INTEL_CL_VERSION_CHECK(2021,1,0) + #define JSON_HEDLEY_ASSUME(expr) __assume(expr) +#elif JSON_HEDLEY_HAS_BUILTIN(__builtin_assume) + #define JSON_HEDLEY_ASSUME(expr) __builtin_assume(expr) +#elif \ + JSON_HEDLEY_TI_CL2000_VERSION_CHECK(6,2,0) || \ + JSON_HEDLEY_TI_CL6X_VERSION_CHECK(4,0,0) + #if defined(__cplusplus) + #define JSON_HEDLEY_ASSUME(expr) std::_nassert(expr) + #else + #define JSON_HEDLEY_ASSUME(expr) _nassert(expr) + #endif +#endif +#if \ + (JSON_HEDLEY_HAS_BUILTIN(__builtin_unreachable) && (!defined(JSON_HEDLEY_ARM_VERSION))) || \ + JSON_HEDLEY_GCC_VERSION_CHECK(4,5,0) || \ + JSON_HEDLEY_PGI_VERSION_CHECK(18,10,0) || \ + JSON_HEDLEY_INTEL_VERSION_CHECK(13,0,0) || \ + JSON_HEDLEY_IBM_VERSION_CHECK(13,1,5) || \ + JSON_HEDLEY_CRAY_VERSION_CHECK(10,0,0) || \ + JSON_HEDLEY_MCST_LCC_VERSION_CHECK(1,25,10) + #define JSON_HEDLEY_UNREACHABLE() __builtin_unreachable() +#elif defined(JSON_HEDLEY_ASSUME) + #define JSON_HEDLEY_UNREACHABLE() JSON_HEDLEY_ASSUME(0) +#endif +#if !defined(JSON_HEDLEY_ASSUME) + #if defined(JSON_HEDLEY_UNREACHABLE) + #define JSON_HEDLEY_ASSUME(expr) JSON_HEDLEY_STATIC_CAST(void, ((expr) ? 1 : (JSON_HEDLEY_UNREACHABLE(), 1))) + #else + #define JSON_HEDLEY_ASSUME(expr) JSON_HEDLEY_STATIC_CAST(void, expr) + #endif +#endif +#if defined(JSON_HEDLEY_UNREACHABLE) + #if \ + JSON_HEDLEY_TI_CL2000_VERSION_CHECK(6,2,0) || \ + JSON_HEDLEY_TI_CL6X_VERSION_CHECK(4,0,0) + #define JSON_HEDLEY_UNREACHABLE_RETURN(value) return (JSON_HEDLEY_STATIC_CAST(void, JSON_HEDLEY_ASSUME(0)), (value)) + #else + #define JSON_HEDLEY_UNREACHABLE_RETURN(value) JSON_HEDLEY_UNREACHABLE() + #endif +#else + #define JSON_HEDLEY_UNREACHABLE_RETURN(value) return (value) +#endif +#if !defined(JSON_HEDLEY_UNREACHABLE) + #define JSON_HEDLEY_UNREACHABLE() JSON_HEDLEY_ASSUME(0) +#endif + +JSON_HEDLEY_DIAGNOSTIC_PUSH +#if JSON_HEDLEY_HAS_WARNING("-Wpedantic") + #pragma clang diagnostic ignored "-Wpedantic" +#endif +#if JSON_HEDLEY_HAS_WARNING("-Wc++98-compat-pedantic") && defined(__cplusplus) + #pragma clang diagnostic ignored "-Wc++98-compat-pedantic" +#endif +#if JSON_HEDLEY_GCC_HAS_WARNING("-Wvariadic-macros",4,0,0) + #if defined(__clang__) + #pragma clang diagnostic ignored "-Wvariadic-macros" + #elif defined(JSON_HEDLEY_GCC_VERSION) + #pragma GCC diagnostic ignored "-Wvariadic-macros" + #endif +#endif +#if defined(JSON_HEDLEY_NON_NULL) + #undef JSON_HEDLEY_NON_NULL +#endif +#if \ + JSON_HEDLEY_HAS_ATTRIBUTE(nonnull) || \ + JSON_HEDLEY_GCC_VERSION_CHECK(3,3,0) || \ + JSON_HEDLEY_INTEL_VERSION_CHECK(13,0,0) || \ + JSON_HEDLEY_ARM_VERSION_CHECK(4,1,0) + #define JSON_HEDLEY_NON_NULL(...) __attribute__((__nonnull__(__VA_ARGS__))) +#else + #define JSON_HEDLEY_NON_NULL(...) +#endif +JSON_HEDLEY_DIAGNOSTIC_POP + +#if defined(JSON_HEDLEY_PRINTF_FORMAT) + #undef JSON_HEDLEY_PRINTF_FORMAT +#endif +#if defined(__MINGW32__) && JSON_HEDLEY_GCC_HAS_ATTRIBUTE(format,4,4,0) && !defined(__USE_MINGW_ANSI_STDIO) + #define JSON_HEDLEY_PRINTF_FORMAT(string_idx,first_to_check) __attribute__((__format__(ms_printf, string_idx, first_to_check))) +#elif defined(__MINGW32__) && JSON_HEDLEY_GCC_HAS_ATTRIBUTE(format,4,4,0) && defined(__USE_MINGW_ANSI_STDIO) + #define JSON_HEDLEY_PRINTF_FORMAT(string_idx,first_to_check) __attribute__((__format__(gnu_printf, string_idx, first_to_check))) +#elif \ + JSON_HEDLEY_HAS_ATTRIBUTE(format) || \ + JSON_HEDLEY_GCC_VERSION_CHECK(3,1,0) || \ + JSON_HEDLEY_INTEL_VERSION_CHECK(13,0,0) || \ + JSON_HEDLEY_ARM_VERSION_CHECK(5,6,0) || \ + JSON_HEDLEY_IBM_VERSION_CHECK(10,1,0) || \ + JSON_HEDLEY_TI_VERSION_CHECK(15,12,0) || \ + (JSON_HEDLEY_TI_ARMCL_VERSION_CHECK(4,8,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_ARMCL_VERSION_CHECK(5,2,0) || \ + (JSON_HEDLEY_TI_CL2000_VERSION_CHECK(6,0,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_CL2000_VERSION_CHECK(6,4,0) || \ + (JSON_HEDLEY_TI_CL430_VERSION_CHECK(4,0,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_CL430_VERSION_CHECK(4,3,0) || \ + (JSON_HEDLEY_TI_CL6X_VERSION_CHECK(7,2,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_CL6X_VERSION_CHECK(7,5,0) || \ + JSON_HEDLEY_TI_CL7X_VERSION_CHECK(1,2,0) || \ + JSON_HEDLEY_TI_CLPRU_VERSION_CHECK(2,1,0) || \ + JSON_HEDLEY_MCST_LCC_VERSION_CHECK(1,25,10) + #define JSON_HEDLEY_PRINTF_FORMAT(string_idx,first_to_check) __attribute__((__format__(__printf__, string_idx, first_to_check))) +#elif JSON_HEDLEY_PELLES_VERSION_CHECK(6,0,0) + #define JSON_HEDLEY_PRINTF_FORMAT(string_idx,first_to_check) __declspec(vaformat(printf,string_idx,first_to_check)) +#else + #define JSON_HEDLEY_PRINTF_FORMAT(string_idx,first_to_check) +#endif + +#if defined(JSON_HEDLEY_CONSTEXPR) + #undef JSON_HEDLEY_CONSTEXPR +#endif +#if defined(__cplusplus) + #if __cplusplus >= 201103L + #define JSON_HEDLEY_CONSTEXPR JSON_HEDLEY_DIAGNOSTIC_DISABLE_CPP98_COMPAT_WRAP_(constexpr) + #endif +#endif +#if !defined(JSON_HEDLEY_CONSTEXPR) + #define JSON_HEDLEY_CONSTEXPR +#endif + +#if defined(JSON_HEDLEY_PREDICT) + #undef JSON_HEDLEY_PREDICT +#endif +#if defined(JSON_HEDLEY_LIKELY) + #undef JSON_HEDLEY_LIKELY +#endif +#if defined(JSON_HEDLEY_UNLIKELY) + #undef JSON_HEDLEY_UNLIKELY +#endif +#if defined(JSON_HEDLEY_UNPREDICTABLE) + #undef JSON_HEDLEY_UNPREDICTABLE +#endif +#if JSON_HEDLEY_HAS_BUILTIN(__builtin_unpredictable) + #define JSON_HEDLEY_UNPREDICTABLE(expr) __builtin_unpredictable((expr)) +#endif +#if \ + (JSON_HEDLEY_HAS_BUILTIN(__builtin_expect_with_probability) && !defined(JSON_HEDLEY_PGI_VERSION)) || \ + JSON_HEDLEY_GCC_VERSION_CHECK(9,0,0) || \ + JSON_HEDLEY_MCST_LCC_VERSION_CHECK(1,25,10) +# define JSON_HEDLEY_PREDICT(expr, value, probability) __builtin_expect_with_probability( (expr), (value), (probability)) +# define JSON_HEDLEY_PREDICT_TRUE(expr, probability) __builtin_expect_with_probability(!!(expr), 1 , (probability)) +# define JSON_HEDLEY_PREDICT_FALSE(expr, probability) __builtin_expect_with_probability(!!(expr), 0 , (probability)) +# define JSON_HEDLEY_LIKELY(expr) __builtin_expect (!!(expr), 1 ) +# define JSON_HEDLEY_UNLIKELY(expr) __builtin_expect (!!(expr), 0 ) +#elif \ + (JSON_HEDLEY_HAS_BUILTIN(__builtin_expect) && !defined(JSON_HEDLEY_INTEL_CL_VERSION)) || \ + JSON_HEDLEY_GCC_VERSION_CHECK(3,0,0) || \ + JSON_HEDLEY_INTEL_VERSION_CHECK(13,0,0) || \ + (JSON_HEDLEY_SUNPRO_VERSION_CHECK(5,15,0) && defined(__cplusplus)) || \ + JSON_HEDLEY_ARM_VERSION_CHECK(4,1,0) || \ + JSON_HEDLEY_IBM_VERSION_CHECK(10,1,0) || \ + JSON_HEDLEY_TI_VERSION_CHECK(15,12,0) || \ + JSON_HEDLEY_TI_ARMCL_VERSION_CHECK(4,7,0) || \ + JSON_HEDLEY_TI_CL430_VERSION_CHECK(3,1,0) || \ + JSON_HEDLEY_TI_CL2000_VERSION_CHECK(6,1,0) || \ + JSON_HEDLEY_TI_CL6X_VERSION_CHECK(6,1,0) || \ + JSON_HEDLEY_TI_CL7X_VERSION_CHECK(1,2,0) || \ + JSON_HEDLEY_TI_CLPRU_VERSION_CHECK(2,1,0) || \ + JSON_HEDLEY_TINYC_VERSION_CHECK(0,9,27) || \ + JSON_HEDLEY_CRAY_VERSION_CHECK(8,1,0) || \ + JSON_HEDLEY_MCST_LCC_VERSION_CHECK(1,25,10) +# define JSON_HEDLEY_PREDICT(expr, expected, probability) \ + (((probability) >= 0.9) ? __builtin_expect((expr), (expected)) : (JSON_HEDLEY_STATIC_CAST(void, expected), (expr))) +# define JSON_HEDLEY_PREDICT_TRUE(expr, probability) \ + (__extension__ ({ \ + double hedley_probability_ = (probability); \ + ((hedley_probability_ >= 0.9) ? __builtin_expect(!!(expr), 1) : ((hedley_probability_ <= 0.1) ? __builtin_expect(!!(expr), 0) : !!(expr))); \ + })) +# define JSON_HEDLEY_PREDICT_FALSE(expr, probability) \ + (__extension__ ({ \ + double hedley_probability_ = (probability); \ + ((hedley_probability_ >= 0.9) ? __builtin_expect(!!(expr), 0) : ((hedley_probability_ <= 0.1) ? __builtin_expect(!!(expr), 1) : !!(expr))); \ + })) +# define JSON_HEDLEY_LIKELY(expr) __builtin_expect(!!(expr), 1) +# define JSON_HEDLEY_UNLIKELY(expr) __builtin_expect(!!(expr), 0) +#else +# define JSON_HEDLEY_PREDICT(expr, expected, probability) (JSON_HEDLEY_STATIC_CAST(void, expected), (expr)) +# define JSON_HEDLEY_PREDICT_TRUE(expr, probability) (!!(expr)) +# define JSON_HEDLEY_PREDICT_FALSE(expr, probability) (!!(expr)) +# define JSON_HEDLEY_LIKELY(expr) (!!(expr)) +# define JSON_HEDLEY_UNLIKELY(expr) (!!(expr)) +#endif +#if !defined(JSON_HEDLEY_UNPREDICTABLE) + #define JSON_HEDLEY_UNPREDICTABLE(expr) JSON_HEDLEY_PREDICT(expr, 1, 0.5) +#endif + +#if defined(JSON_HEDLEY_MALLOC) + #undef JSON_HEDLEY_MALLOC +#endif +#if \ + JSON_HEDLEY_HAS_ATTRIBUTE(malloc) || \ + JSON_HEDLEY_GCC_VERSION_CHECK(3,1,0) || \ + JSON_HEDLEY_INTEL_VERSION_CHECK(13,0,0) || \ + JSON_HEDLEY_SUNPRO_VERSION_CHECK(5,11,0) || \ + JSON_HEDLEY_ARM_VERSION_CHECK(4,1,0) || \ + JSON_HEDLEY_IBM_VERSION_CHECK(12,1,0) || \ + JSON_HEDLEY_TI_VERSION_CHECK(15,12,0) || \ + (JSON_HEDLEY_TI_ARMCL_VERSION_CHECK(4,8,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_ARMCL_VERSION_CHECK(5,2,0) || \ + (JSON_HEDLEY_TI_CL2000_VERSION_CHECK(6,0,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_CL2000_VERSION_CHECK(6,4,0) || \ + (JSON_HEDLEY_TI_CL430_VERSION_CHECK(4,0,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_CL430_VERSION_CHECK(4,3,0) || \ + (JSON_HEDLEY_TI_CL6X_VERSION_CHECK(7,2,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_CL6X_VERSION_CHECK(7,5,0) || \ + JSON_HEDLEY_TI_CL7X_VERSION_CHECK(1,2,0) || \ + JSON_HEDLEY_TI_CLPRU_VERSION_CHECK(2,1,0) || \ + JSON_HEDLEY_MCST_LCC_VERSION_CHECK(1,25,10) + #define JSON_HEDLEY_MALLOC __attribute__((__malloc__)) +#elif JSON_HEDLEY_SUNPRO_VERSION_CHECK(5,10,0) + #define JSON_HEDLEY_MALLOC _Pragma("returns_new_memory") +#elif \ + JSON_HEDLEY_MSVC_VERSION_CHECK(14,0,0) || \ + JSON_HEDLEY_INTEL_CL_VERSION_CHECK(2021,1,0) + #define JSON_HEDLEY_MALLOC __declspec(restrict) +#else + #define JSON_HEDLEY_MALLOC +#endif + +#if defined(JSON_HEDLEY_PURE) + #undef JSON_HEDLEY_PURE +#endif +#if \ + JSON_HEDLEY_HAS_ATTRIBUTE(pure) || \ + JSON_HEDLEY_GCC_VERSION_CHECK(2,96,0) || \ + JSON_HEDLEY_INTEL_VERSION_CHECK(13,0,0) || \ + JSON_HEDLEY_SUNPRO_VERSION_CHECK(5,11,0) || \ + JSON_HEDLEY_ARM_VERSION_CHECK(4,1,0) || \ + JSON_HEDLEY_IBM_VERSION_CHECK(10,1,0) || \ + JSON_HEDLEY_TI_VERSION_CHECK(15,12,0) || \ + (JSON_HEDLEY_TI_ARMCL_VERSION_CHECK(4,8,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_ARMCL_VERSION_CHECK(5,2,0) || \ + (JSON_HEDLEY_TI_CL2000_VERSION_CHECK(6,0,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_CL2000_VERSION_CHECK(6,4,0) || \ + (JSON_HEDLEY_TI_CL430_VERSION_CHECK(4,0,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_CL430_VERSION_CHECK(4,3,0) || \ + (JSON_HEDLEY_TI_CL6X_VERSION_CHECK(7,2,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_CL6X_VERSION_CHECK(7,5,0) || \ + JSON_HEDLEY_TI_CL7X_VERSION_CHECK(1,2,0) || \ + JSON_HEDLEY_TI_CLPRU_VERSION_CHECK(2,1,0) || \ + JSON_HEDLEY_PGI_VERSION_CHECK(17,10,0) || \ + JSON_HEDLEY_MCST_LCC_VERSION_CHECK(1,25,10) +# define JSON_HEDLEY_PURE __attribute__((__pure__)) +#elif JSON_HEDLEY_SUNPRO_VERSION_CHECK(5,10,0) +# define JSON_HEDLEY_PURE _Pragma("does_not_write_global_data") +#elif defined(__cplusplus) && \ + ( \ + JSON_HEDLEY_TI_CL430_VERSION_CHECK(2,0,1) || \ + JSON_HEDLEY_TI_CL6X_VERSION_CHECK(4,0,0) || \ + JSON_HEDLEY_TI_CL7X_VERSION_CHECK(1,2,0) \ + ) +# define JSON_HEDLEY_PURE _Pragma("FUNC_IS_PURE;") +#else +# define JSON_HEDLEY_PURE +#endif + +#if defined(JSON_HEDLEY_CONST) + #undef JSON_HEDLEY_CONST +#endif +#if \ + JSON_HEDLEY_HAS_ATTRIBUTE(const) || \ + JSON_HEDLEY_GCC_VERSION_CHECK(2,5,0) || \ + JSON_HEDLEY_INTEL_VERSION_CHECK(13,0,0) || \ + JSON_HEDLEY_SUNPRO_VERSION_CHECK(5,11,0) || \ + JSON_HEDLEY_ARM_VERSION_CHECK(4,1,0) || \ + JSON_HEDLEY_IBM_VERSION_CHECK(10,1,0) || \ + JSON_HEDLEY_TI_VERSION_CHECK(15,12,0) || \ + (JSON_HEDLEY_TI_ARMCL_VERSION_CHECK(4,8,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_ARMCL_VERSION_CHECK(5,2,0) || \ + (JSON_HEDLEY_TI_CL2000_VERSION_CHECK(6,0,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_CL2000_VERSION_CHECK(6,4,0) || \ + (JSON_HEDLEY_TI_CL430_VERSION_CHECK(4,0,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_CL430_VERSION_CHECK(4,3,0) || \ + (JSON_HEDLEY_TI_CL6X_VERSION_CHECK(7,2,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_CL6X_VERSION_CHECK(7,5,0) || \ + JSON_HEDLEY_TI_CL7X_VERSION_CHECK(1,2,0) || \ + JSON_HEDLEY_TI_CLPRU_VERSION_CHECK(2,1,0) || \ + JSON_HEDLEY_PGI_VERSION_CHECK(17,10,0) || \ + JSON_HEDLEY_MCST_LCC_VERSION_CHECK(1,25,10) + #define JSON_HEDLEY_CONST __attribute__((__const__)) +#elif \ + JSON_HEDLEY_SUNPRO_VERSION_CHECK(5,10,0) + #define JSON_HEDLEY_CONST _Pragma("no_side_effect") +#else + #define JSON_HEDLEY_CONST JSON_HEDLEY_PURE +#endif + +#if defined(JSON_HEDLEY_RESTRICT) + #undef JSON_HEDLEY_RESTRICT +#endif +#if defined(__STDC_VERSION__) && (__STDC_VERSION__ >= 199901L) && !defined(__cplusplus) + #define JSON_HEDLEY_RESTRICT restrict +#elif \ + JSON_HEDLEY_GCC_VERSION_CHECK(3,1,0) || \ + JSON_HEDLEY_MSVC_VERSION_CHECK(14,0,0) || \ + JSON_HEDLEY_INTEL_VERSION_CHECK(13,0,0) || \ + JSON_HEDLEY_INTEL_CL_VERSION_CHECK(2021,1,0) || \ + JSON_HEDLEY_ARM_VERSION_CHECK(4,1,0) || \ + JSON_HEDLEY_IBM_VERSION_CHECK(10,1,0) || \ + JSON_HEDLEY_PGI_VERSION_CHECK(17,10,0) || \ + JSON_HEDLEY_TI_CL430_VERSION_CHECK(4,3,0) || \ + JSON_HEDLEY_TI_CL2000_VERSION_CHECK(6,2,4) || \ + JSON_HEDLEY_TI_CL6X_VERSION_CHECK(8,1,0) || \ + JSON_HEDLEY_TI_CL7X_VERSION_CHECK(1,2,0) || \ + (JSON_HEDLEY_SUNPRO_VERSION_CHECK(5,14,0) && defined(__cplusplus)) || \ + JSON_HEDLEY_IAR_VERSION_CHECK(8,0,0) || \ + defined(__clang__) || \ + JSON_HEDLEY_MCST_LCC_VERSION_CHECK(1,25,10) + #define JSON_HEDLEY_RESTRICT __restrict +#elif JSON_HEDLEY_SUNPRO_VERSION_CHECK(5,3,0) && !defined(__cplusplus) + #define JSON_HEDLEY_RESTRICT _Restrict +#else + #define JSON_HEDLEY_RESTRICT +#endif + +#if defined(JSON_HEDLEY_INLINE) + #undef JSON_HEDLEY_INLINE +#endif +#if \ + (defined(__STDC_VERSION__) && (__STDC_VERSION__ >= 199901L)) || \ + (defined(__cplusplus) && (__cplusplus >= 199711L)) + #define JSON_HEDLEY_INLINE inline +#elif \ + defined(JSON_HEDLEY_GCC_VERSION) || \ + JSON_HEDLEY_ARM_VERSION_CHECK(6,2,0) + #define JSON_HEDLEY_INLINE __inline__ +#elif \ + JSON_HEDLEY_MSVC_VERSION_CHECK(12,0,0) || \ + JSON_HEDLEY_INTEL_CL_VERSION_CHECK(2021,1,0) || \ + JSON_HEDLEY_ARM_VERSION_CHECK(4,1,0) || \ + JSON_HEDLEY_TI_ARMCL_VERSION_CHECK(5,1,0) || \ + JSON_HEDLEY_TI_CL430_VERSION_CHECK(3,1,0) || \ + JSON_HEDLEY_TI_CL2000_VERSION_CHECK(6,2,0) || \ + JSON_HEDLEY_TI_CL6X_VERSION_CHECK(8,0,0) || \ + JSON_HEDLEY_TI_CL7X_VERSION_CHECK(1,2,0) || \ + JSON_HEDLEY_TI_CLPRU_VERSION_CHECK(2,1,0) || \ + JSON_HEDLEY_MCST_LCC_VERSION_CHECK(1,25,10) + #define JSON_HEDLEY_INLINE __inline +#else + #define JSON_HEDLEY_INLINE +#endif + +#if defined(JSON_HEDLEY_ALWAYS_INLINE) + #undef JSON_HEDLEY_ALWAYS_INLINE +#endif +#if \ + JSON_HEDLEY_HAS_ATTRIBUTE(always_inline) || \ + JSON_HEDLEY_GCC_VERSION_CHECK(4,0,0) || \ + JSON_HEDLEY_INTEL_VERSION_CHECK(13,0,0) || \ + JSON_HEDLEY_SUNPRO_VERSION_CHECK(5,11,0) || \ + JSON_HEDLEY_ARM_VERSION_CHECK(4,1,0) || \ + JSON_HEDLEY_IBM_VERSION_CHECK(10,1,0) || \ + JSON_HEDLEY_TI_VERSION_CHECK(15,12,0) || \ + (JSON_HEDLEY_TI_ARMCL_VERSION_CHECK(4,8,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_ARMCL_VERSION_CHECK(5,2,0) || \ + (JSON_HEDLEY_TI_CL2000_VERSION_CHECK(6,0,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_CL2000_VERSION_CHECK(6,4,0) || \ + (JSON_HEDLEY_TI_CL430_VERSION_CHECK(4,0,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_CL430_VERSION_CHECK(4,3,0) || \ + (JSON_HEDLEY_TI_CL6X_VERSION_CHECK(7,2,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_CL6X_VERSION_CHECK(7,5,0) || \ + JSON_HEDLEY_TI_CL7X_VERSION_CHECK(1,2,0) || \ + JSON_HEDLEY_TI_CLPRU_VERSION_CHECK(2,1,0) || \ + JSON_HEDLEY_MCST_LCC_VERSION_CHECK(1,25,10) || \ + JSON_HEDLEY_IAR_VERSION_CHECK(8,10,0) +# define JSON_HEDLEY_ALWAYS_INLINE __attribute__((__always_inline__)) JSON_HEDLEY_INLINE +#elif \ + JSON_HEDLEY_MSVC_VERSION_CHECK(12,0,0) || \ + JSON_HEDLEY_INTEL_CL_VERSION_CHECK(2021,1,0) +# define JSON_HEDLEY_ALWAYS_INLINE __forceinline +#elif defined(__cplusplus) && \ + ( \ + JSON_HEDLEY_TI_ARMCL_VERSION_CHECK(5,2,0) || \ + JSON_HEDLEY_TI_CL430_VERSION_CHECK(4,3,0) || \ + JSON_HEDLEY_TI_CL2000_VERSION_CHECK(6,4,0) || \ + JSON_HEDLEY_TI_CL6X_VERSION_CHECK(6,1,0) || \ + JSON_HEDLEY_TI_CL7X_VERSION_CHECK(1,2,0) || \ + JSON_HEDLEY_TI_CLPRU_VERSION_CHECK(2,1,0) \ + ) +# define JSON_HEDLEY_ALWAYS_INLINE _Pragma("FUNC_ALWAYS_INLINE;") +#elif JSON_HEDLEY_IAR_VERSION_CHECK(8,0,0) +# define JSON_HEDLEY_ALWAYS_INLINE _Pragma("inline=forced") +#else +# define JSON_HEDLEY_ALWAYS_INLINE JSON_HEDLEY_INLINE +#endif + +#if defined(JSON_HEDLEY_NEVER_INLINE) + #undef JSON_HEDLEY_NEVER_INLINE +#endif +#if \ + JSON_HEDLEY_HAS_ATTRIBUTE(noinline) || \ + JSON_HEDLEY_GCC_VERSION_CHECK(4,0,0) || \ + JSON_HEDLEY_INTEL_VERSION_CHECK(13,0,0) || \ + JSON_HEDLEY_SUNPRO_VERSION_CHECK(5,11,0) || \ + JSON_HEDLEY_ARM_VERSION_CHECK(4,1,0) || \ + JSON_HEDLEY_IBM_VERSION_CHECK(10,1,0) || \ + JSON_HEDLEY_TI_VERSION_CHECK(15,12,0) || \ + (JSON_HEDLEY_TI_ARMCL_VERSION_CHECK(4,8,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_ARMCL_VERSION_CHECK(5,2,0) || \ + (JSON_HEDLEY_TI_CL2000_VERSION_CHECK(6,0,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_CL2000_VERSION_CHECK(6,4,0) || \ + (JSON_HEDLEY_TI_CL430_VERSION_CHECK(4,0,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_CL430_VERSION_CHECK(4,3,0) || \ + (JSON_HEDLEY_TI_CL6X_VERSION_CHECK(7,2,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_CL6X_VERSION_CHECK(7,5,0) || \ + JSON_HEDLEY_TI_CL7X_VERSION_CHECK(1,2,0) || \ + JSON_HEDLEY_TI_CLPRU_VERSION_CHECK(2,1,0) || \ + JSON_HEDLEY_MCST_LCC_VERSION_CHECK(1,25,10) || \ + JSON_HEDLEY_IAR_VERSION_CHECK(8,10,0) + #define JSON_HEDLEY_NEVER_INLINE __attribute__((__noinline__)) +#elif \ + JSON_HEDLEY_MSVC_VERSION_CHECK(13,10,0) || \ + JSON_HEDLEY_INTEL_CL_VERSION_CHECK(2021,1,0) + #define JSON_HEDLEY_NEVER_INLINE __declspec(noinline) +#elif JSON_HEDLEY_PGI_VERSION_CHECK(10,2,0) + #define JSON_HEDLEY_NEVER_INLINE _Pragma("noinline") +#elif JSON_HEDLEY_TI_CL6X_VERSION_CHECK(6,0,0) && defined(__cplusplus) + #define JSON_HEDLEY_NEVER_INLINE _Pragma("FUNC_CANNOT_INLINE;") +#elif JSON_HEDLEY_IAR_VERSION_CHECK(8,0,0) + #define JSON_HEDLEY_NEVER_INLINE _Pragma("inline=never") +#elif JSON_HEDLEY_COMPCERT_VERSION_CHECK(3,2,0) + #define JSON_HEDLEY_NEVER_INLINE __attribute((noinline)) +#elif JSON_HEDLEY_PELLES_VERSION_CHECK(9,0,0) + #define JSON_HEDLEY_NEVER_INLINE __declspec(noinline) +#else + #define JSON_HEDLEY_NEVER_INLINE +#endif + +#if defined(JSON_HEDLEY_PRIVATE) + #undef JSON_HEDLEY_PRIVATE +#endif +#if defined(JSON_HEDLEY_PUBLIC) + #undef JSON_HEDLEY_PUBLIC +#endif +#if defined(JSON_HEDLEY_IMPORT) + #undef JSON_HEDLEY_IMPORT +#endif +#if defined(_WIN32) || defined(__CYGWIN__) +# define JSON_HEDLEY_PRIVATE +# define JSON_HEDLEY_PUBLIC __declspec(dllexport) +# define JSON_HEDLEY_IMPORT __declspec(dllimport) +#else +# if \ + JSON_HEDLEY_HAS_ATTRIBUTE(visibility) || \ + JSON_HEDLEY_GCC_VERSION_CHECK(3,3,0) || \ + JSON_HEDLEY_SUNPRO_VERSION_CHECK(5,11,0) || \ + JSON_HEDLEY_INTEL_VERSION_CHECK(13,0,0) || \ + JSON_HEDLEY_ARM_VERSION_CHECK(4,1,0) || \ + JSON_HEDLEY_IBM_VERSION_CHECK(13,1,0) || \ + ( \ + defined(__TI_EABI__) && \ + ( \ + (JSON_HEDLEY_TI_CL6X_VERSION_CHECK(7,2,0) && defined(__TI_GNU_ATTRIBUTE_SUPPORT__)) || \ + JSON_HEDLEY_TI_CL6X_VERSION_CHECK(7,5,0) \ + ) \ + ) || \ + JSON_HEDLEY_MCST_LCC_VERSION_CHECK(1,25,10) +# define JSON_HEDLEY_PRIVATE __attribute__((__visibility__("hidden"))) +# define JSON_HEDLEY_PUBLIC __attribute__((__visibility__("default"))) +# else +# define JSON_HEDLEY_PRIVATE +# define JSON_HEDLEY_PUBLIC +# endif +# define JSON_HEDLEY_IMPORT extern +#endif + +#if defined(JSON_HEDLEY_NO_THROW) + #undef JSON_HEDLEY_NO_THROW +#endif +#if \ + JSON_HEDLEY_HAS_ATTRIBUTE(nothrow) || \ + JSON_HEDLEY_GCC_VERSION_CHECK(3,3,0) || \ + JSON_HEDLEY_INTEL_VERSION_CHECK(13,0,0) || \ + JSON_HEDLEY_MCST_LCC_VERSION_CHECK(1,25,10) + #define JSON_HEDLEY_NO_THROW __attribute__((__nothrow__)) +#elif \ + JSON_HEDLEY_MSVC_VERSION_CHECK(13,1,0) || \ + JSON_HEDLEY_INTEL_CL_VERSION_CHECK(2021,1,0) || \ + JSON_HEDLEY_ARM_VERSION_CHECK(4,1,0) + #define JSON_HEDLEY_NO_THROW __declspec(nothrow) +#else + #define JSON_HEDLEY_NO_THROW +#endif + +#if defined(JSON_HEDLEY_FALL_THROUGH) + #undef JSON_HEDLEY_FALL_THROUGH +#endif +#if \ + JSON_HEDLEY_HAS_ATTRIBUTE(fallthrough) || \ + JSON_HEDLEY_GCC_VERSION_CHECK(7,0,0) || \ + JSON_HEDLEY_MCST_LCC_VERSION_CHECK(1,25,10) + #define JSON_HEDLEY_FALL_THROUGH __attribute__((__fallthrough__)) +#elif JSON_HEDLEY_HAS_CPP_ATTRIBUTE_NS(clang,fallthrough) + #define JSON_HEDLEY_FALL_THROUGH JSON_HEDLEY_DIAGNOSTIC_DISABLE_CPP98_COMPAT_WRAP_([[clang::fallthrough]]) +#elif JSON_HEDLEY_HAS_CPP_ATTRIBUTE(fallthrough) + #define JSON_HEDLEY_FALL_THROUGH JSON_HEDLEY_DIAGNOSTIC_DISABLE_CPP98_COMPAT_WRAP_([[fallthrough]]) +#elif defined(__fallthrough) /* SAL */ + #define JSON_HEDLEY_FALL_THROUGH __fallthrough +#else + #define JSON_HEDLEY_FALL_THROUGH +#endif + +#if defined(JSON_HEDLEY_RETURNS_NON_NULL) + #undef JSON_HEDLEY_RETURNS_NON_NULL +#endif +#if \ + JSON_HEDLEY_HAS_ATTRIBUTE(returns_nonnull) || \ + JSON_HEDLEY_GCC_VERSION_CHECK(4,9,0) || \ + JSON_HEDLEY_MCST_LCC_VERSION_CHECK(1,25,10) + #define JSON_HEDLEY_RETURNS_NON_NULL __attribute__((__returns_nonnull__)) +#elif defined(_Ret_notnull_) /* SAL */ + #define JSON_HEDLEY_RETURNS_NON_NULL _Ret_notnull_ +#else + #define JSON_HEDLEY_RETURNS_NON_NULL +#endif + +#if defined(JSON_HEDLEY_ARRAY_PARAM) + #undef JSON_HEDLEY_ARRAY_PARAM +#endif +#if \ + defined(__STDC_VERSION__) && (__STDC_VERSION__ >= 199901L) && \ + !defined(__STDC_NO_VLA__) && \ + !defined(__cplusplus) && \ + !defined(JSON_HEDLEY_PGI_VERSION) && \ + !defined(JSON_HEDLEY_TINYC_VERSION) + #define JSON_HEDLEY_ARRAY_PARAM(name) (name) +#else + #define JSON_HEDLEY_ARRAY_PARAM(name) +#endif + +#if defined(JSON_HEDLEY_IS_CONSTANT) + #undef JSON_HEDLEY_IS_CONSTANT +#endif +#if defined(JSON_HEDLEY_REQUIRE_CONSTEXPR) + #undef JSON_HEDLEY_REQUIRE_CONSTEXPR +#endif +/* JSON_HEDLEY_IS_CONSTEXPR_ is for + HEDLEY INTERNAL USE ONLY. API subject to change without notice. */ +#if defined(JSON_HEDLEY_IS_CONSTEXPR_) + #undef JSON_HEDLEY_IS_CONSTEXPR_ +#endif +#if \ + JSON_HEDLEY_HAS_BUILTIN(__builtin_constant_p) || \ + JSON_HEDLEY_GCC_VERSION_CHECK(3,4,0) || \ + JSON_HEDLEY_INTEL_VERSION_CHECK(13,0,0) || \ + JSON_HEDLEY_TINYC_VERSION_CHECK(0,9,19) || \ + JSON_HEDLEY_ARM_VERSION_CHECK(4,1,0) || \ + JSON_HEDLEY_IBM_VERSION_CHECK(13,1,0) || \ + JSON_HEDLEY_TI_CL6X_VERSION_CHECK(6,1,0) || \ + (JSON_HEDLEY_SUNPRO_VERSION_CHECK(5,10,0) && !defined(__cplusplus)) || \ + JSON_HEDLEY_CRAY_VERSION_CHECK(8,1,0) || \ + JSON_HEDLEY_MCST_LCC_VERSION_CHECK(1,25,10) + #define JSON_HEDLEY_IS_CONSTANT(expr) __builtin_constant_p(expr) +#endif +#if !defined(__cplusplus) +# if \ + JSON_HEDLEY_HAS_BUILTIN(__builtin_types_compatible_p) || \ + JSON_HEDLEY_GCC_VERSION_CHECK(3,4,0) || \ + JSON_HEDLEY_INTEL_VERSION_CHECK(13,0,0) || \ + JSON_HEDLEY_IBM_VERSION_CHECK(13,1,0) || \ + JSON_HEDLEY_CRAY_VERSION_CHECK(8,1,0) || \ + JSON_HEDLEY_ARM_VERSION_CHECK(5,4,0) || \ + JSON_HEDLEY_TINYC_VERSION_CHECK(0,9,24) +#if defined(__INTPTR_TYPE__) + #define JSON_HEDLEY_IS_CONSTEXPR_(expr) __builtin_types_compatible_p(__typeof__((1 ? (void*) ((__INTPTR_TYPE__) ((expr) * 0)) : (int*) 0)), int*) +#else + #include + #define JSON_HEDLEY_IS_CONSTEXPR_(expr) __builtin_types_compatible_p(__typeof__((1 ? (void*) ((intptr_t) ((expr) * 0)) : (int*) 0)), int*) +#endif +# elif \ + ( \ + defined(__STDC_VERSION__) && (__STDC_VERSION__ >= 201112L) && \ + !defined(JSON_HEDLEY_SUNPRO_VERSION) && \ + !defined(JSON_HEDLEY_PGI_VERSION) && \ + !defined(JSON_HEDLEY_IAR_VERSION)) || \ + (JSON_HEDLEY_HAS_EXTENSION(c_generic_selections) && !defined(JSON_HEDLEY_IAR_VERSION)) || \ + JSON_HEDLEY_GCC_VERSION_CHECK(4,9,0) || \ + JSON_HEDLEY_INTEL_VERSION_CHECK(17,0,0) || \ + JSON_HEDLEY_IBM_VERSION_CHECK(12,1,0) || \ + JSON_HEDLEY_ARM_VERSION_CHECK(5,3,0) +#if defined(__INTPTR_TYPE__) + #define JSON_HEDLEY_IS_CONSTEXPR_(expr) _Generic((1 ? (void*) ((__INTPTR_TYPE__) ((expr) * 0)) : (int*) 0), int*: 1, void*: 0) +#else + #include + #define JSON_HEDLEY_IS_CONSTEXPR_(expr) _Generic((1 ? (void*) ((intptr_t) * 0) : (int*) 0), int*: 1, void*: 0) +#endif +# elif \ + defined(JSON_HEDLEY_GCC_VERSION) || \ + defined(JSON_HEDLEY_INTEL_VERSION) || \ + defined(JSON_HEDLEY_TINYC_VERSION) || \ + defined(JSON_HEDLEY_TI_ARMCL_VERSION) || \ + JSON_HEDLEY_TI_CL430_VERSION_CHECK(18,12,0) || \ + defined(JSON_HEDLEY_TI_CL2000_VERSION) || \ + defined(JSON_HEDLEY_TI_CL6X_VERSION) || \ + defined(JSON_HEDLEY_TI_CL7X_VERSION) || \ + defined(JSON_HEDLEY_TI_CLPRU_VERSION) || \ + defined(__clang__) +# define JSON_HEDLEY_IS_CONSTEXPR_(expr) ( \ + sizeof(void) != \ + sizeof(*( \ + 1 ? \ + ((void*) ((expr) * 0L) ) : \ +((struct { char v[sizeof(void) * 2]; } *) 1) \ + ) \ + ) \ + ) +# endif +#endif +#if defined(JSON_HEDLEY_IS_CONSTEXPR_) + #if !defined(JSON_HEDLEY_IS_CONSTANT) + #define JSON_HEDLEY_IS_CONSTANT(expr) JSON_HEDLEY_IS_CONSTEXPR_(expr) + #endif + #define JSON_HEDLEY_REQUIRE_CONSTEXPR(expr) (JSON_HEDLEY_IS_CONSTEXPR_(expr) ? (expr) : (-1)) +#else + #if !defined(JSON_HEDLEY_IS_CONSTANT) + #define JSON_HEDLEY_IS_CONSTANT(expr) (0) + #endif + #define JSON_HEDLEY_REQUIRE_CONSTEXPR(expr) (expr) +#endif + +#if defined(JSON_HEDLEY_BEGIN_C_DECLS) + #undef JSON_HEDLEY_BEGIN_C_DECLS +#endif +#if defined(JSON_HEDLEY_END_C_DECLS) + #undef JSON_HEDLEY_END_C_DECLS +#endif +#if defined(JSON_HEDLEY_C_DECL) + #undef JSON_HEDLEY_C_DECL +#endif +#if defined(__cplusplus) + #define JSON_HEDLEY_BEGIN_C_DECLS extern "C" { + #define JSON_HEDLEY_END_C_DECLS } + #define JSON_HEDLEY_C_DECL extern "C" +#else + #define JSON_HEDLEY_BEGIN_C_DECLS + #define JSON_HEDLEY_END_C_DECLS + #define JSON_HEDLEY_C_DECL +#endif + +#if defined(JSON_HEDLEY_STATIC_ASSERT) + #undef JSON_HEDLEY_STATIC_ASSERT +#endif +#if \ + !defined(__cplusplus) && ( \ + (defined(__STDC_VERSION__) && (__STDC_VERSION__ >= 201112L)) || \ + (JSON_HEDLEY_HAS_FEATURE(c_static_assert) && !defined(JSON_HEDLEY_INTEL_CL_VERSION)) || \ + JSON_HEDLEY_GCC_VERSION_CHECK(6,0,0) || \ + JSON_HEDLEY_INTEL_VERSION_CHECK(13,0,0) || \ + defined(_Static_assert) \ + ) +# define JSON_HEDLEY_STATIC_ASSERT(expr, message) _Static_assert(expr, message) +#elif \ + (defined(__cplusplus) && (__cplusplus >= 201103L)) || \ + JSON_HEDLEY_MSVC_VERSION_CHECK(16,0,0) || \ + JSON_HEDLEY_INTEL_CL_VERSION_CHECK(2021,1,0) +# define JSON_HEDLEY_STATIC_ASSERT(expr, message) JSON_HEDLEY_DIAGNOSTIC_DISABLE_CPP98_COMPAT_WRAP_(static_assert(expr, message)) +#else +# define JSON_HEDLEY_STATIC_ASSERT(expr, message) +#endif + +#if defined(JSON_HEDLEY_NULL) + #undef JSON_HEDLEY_NULL +#endif +#if defined(__cplusplus) + #if __cplusplus >= 201103L + #define JSON_HEDLEY_NULL JSON_HEDLEY_DIAGNOSTIC_DISABLE_CPP98_COMPAT_WRAP_(nullptr) + #elif defined(NULL) + #define JSON_HEDLEY_NULL NULL + #else + #define JSON_HEDLEY_NULL JSON_HEDLEY_STATIC_CAST(void*, 0) + #endif +#elif defined(NULL) + #define JSON_HEDLEY_NULL NULL +#else + #define JSON_HEDLEY_NULL ((void*) 0) +#endif + +#if defined(JSON_HEDLEY_MESSAGE) + #undef JSON_HEDLEY_MESSAGE +#endif +#if JSON_HEDLEY_HAS_WARNING("-Wunknown-pragmas") +# define JSON_HEDLEY_MESSAGE(msg) \ + JSON_HEDLEY_DIAGNOSTIC_PUSH \ + JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNKNOWN_PRAGMAS \ + JSON_HEDLEY_PRAGMA(message msg) \ + JSON_HEDLEY_DIAGNOSTIC_POP +#elif \ + JSON_HEDLEY_GCC_VERSION_CHECK(4,4,0) || \ + JSON_HEDLEY_INTEL_VERSION_CHECK(13,0,0) +# define JSON_HEDLEY_MESSAGE(msg) JSON_HEDLEY_PRAGMA(message msg) +#elif JSON_HEDLEY_CRAY_VERSION_CHECK(5,0,0) +# define JSON_HEDLEY_MESSAGE(msg) JSON_HEDLEY_PRAGMA(_CRI message msg) +#elif JSON_HEDLEY_IAR_VERSION_CHECK(8,0,0) +# define JSON_HEDLEY_MESSAGE(msg) JSON_HEDLEY_PRAGMA(message(msg)) +#elif JSON_HEDLEY_PELLES_VERSION_CHECK(2,0,0) +# define JSON_HEDLEY_MESSAGE(msg) JSON_HEDLEY_PRAGMA(message(msg)) +#else +# define JSON_HEDLEY_MESSAGE(msg) +#endif + +#if defined(JSON_HEDLEY_WARNING) + #undef JSON_HEDLEY_WARNING +#endif +#if JSON_HEDLEY_HAS_WARNING("-Wunknown-pragmas") +# define JSON_HEDLEY_WARNING(msg) \ + JSON_HEDLEY_DIAGNOSTIC_PUSH \ + JSON_HEDLEY_DIAGNOSTIC_DISABLE_UNKNOWN_PRAGMAS \ + JSON_HEDLEY_PRAGMA(clang warning msg) \ + JSON_HEDLEY_DIAGNOSTIC_POP +#elif \ + JSON_HEDLEY_GCC_VERSION_CHECK(4,8,0) || \ + JSON_HEDLEY_PGI_VERSION_CHECK(18,4,0) || \ + JSON_HEDLEY_INTEL_VERSION_CHECK(13,0,0) +# define JSON_HEDLEY_WARNING(msg) JSON_HEDLEY_PRAGMA(GCC warning msg) +#elif \ + JSON_HEDLEY_MSVC_VERSION_CHECK(15,0,0) || \ + JSON_HEDLEY_INTEL_CL_VERSION_CHECK(2021,1,0) +# define JSON_HEDLEY_WARNING(msg) JSON_HEDLEY_PRAGMA(message(msg)) +#else +# define JSON_HEDLEY_WARNING(msg) JSON_HEDLEY_MESSAGE(msg) +#endif + +#if defined(JSON_HEDLEY_REQUIRE) + #undef JSON_HEDLEY_REQUIRE +#endif +#if defined(JSON_HEDLEY_REQUIRE_MSG) + #undef JSON_HEDLEY_REQUIRE_MSG +#endif +#if JSON_HEDLEY_HAS_ATTRIBUTE(diagnose_if) +# if JSON_HEDLEY_HAS_WARNING("-Wgcc-compat") +# define JSON_HEDLEY_REQUIRE(expr) \ + JSON_HEDLEY_DIAGNOSTIC_PUSH \ + _Pragma("clang diagnostic ignored \"-Wgcc-compat\"") \ + __attribute__((diagnose_if(!(expr), #expr, "error"))) \ + JSON_HEDLEY_DIAGNOSTIC_POP +# define JSON_HEDLEY_REQUIRE_MSG(expr,msg) \ + JSON_HEDLEY_DIAGNOSTIC_PUSH \ + _Pragma("clang diagnostic ignored \"-Wgcc-compat\"") \ + __attribute__((diagnose_if(!(expr), msg, "error"))) \ + JSON_HEDLEY_DIAGNOSTIC_POP +# else +# define JSON_HEDLEY_REQUIRE(expr) __attribute__((diagnose_if(!(expr), #expr, "error"))) +# define JSON_HEDLEY_REQUIRE_MSG(expr,msg) __attribute__((diagnose_if(!(expr), msg, "error"))) +# endif +#else +# define JSON_HEDLEY_REQUIRE(expr) +# define JSON_HEDLEY_REQUIRE_MSG(expr,msg) +#endif + +#if defined(JSON_HEDLEY_FLAGS) + #undef JSON_HEDLEY_FLAGS +#endif +#if JSON_HEDLEY_HAS_ATTRIBUTE(flag_enum) && (!defined(__cplusplus) || JSON_HEDLEY_HAS_WARNING("-Wbitfield-enum-conversion")) + #define JSON_HEDLEY_FLAGS __attribute__((__flag_enum__)) +#else + #define JSON_HEDLEY_FLAGS +#endif + +#if defined(JSON_HEDLEY_FLAGS_CAST) + #undef JSON_HEDLEY_FLAGS_CAST +#endif +#if JSON_HEDLEY_INTEL_VERSION_CHECK(19,0,0) +# define JSON_HEDLEY_FLAGS_CAST(T, expr) (__extension__ ({ \ + JSON_HEDLEY_DIAGNOSTIC_PUSH \ + _Pragma("warning(disable:188)") \ + ((T) (expr)); \ + JSON_HEDLEY_DIAGNOSTIC_POP \ + })) +#else +# define JSON_HEDLEY_FLAGS_CAST(T, expr) JSON_HEDLEY_STATIC_CAST(T, expr) +#endif + +#if defined(JSON_HEDLEY_EMPTY_BASES) + #undef JSON_HEDLEY_EMPTY_BASES +#endif +#if \ + (JSON_HEDLEY_MSVC_VERSION_CHECK(19,0,23918) && !JSON_HEDLEY_MSVC_VERSION_CHECK(20,0,0)) || \ + JSON_HEDLEY_INTEL_CL_VERSION_CHECK(2021,1,0) + #define JSON_HEDLEY_EMPTY_BASES __declspec(empty_bases) +#else + #define JSON_HEDLEY_EMPTY_BASES +#endif + +/* Remaining macros are deprecated. */ + +#if defined(JSON_HEDLEY_GCC_NOT_CLANG_VERSION_CHECK) + #undef JSON_HEDLEY_GCC_NOT_CLANG_VERSION_CHECK +#endif +#if defined(__clang__) + #define JSON_HEDLEY_GCC_NOT_CLANG_VERSION_CHECK(major,minor,patch) (0) +#else + #define JSON_HEDLEY_GCC_NOT_CLANG_VERSION_CHECK(major,minor,patch) JSON_HEDLEY_GCC_VERSION_CHECK(major,minor,patch) +#endif + +#if defined(JSON_HEDLEY_CLANG_HAS_ATTRIBUTE) + #undef JSON_HEDLEY_CLANG_HAS_ATTRIBUTE +#endif +#define JSON_HEDLEY_CLANG_HAS_ATTRIBUTE(attribute) JSON_HEDLEY_HAS_ATTRIBUTE(attribute) + +#if defined(JSON_HEDLEY_CLANG_HAS_CPP_ATTRIBUTE) + #undef JSON_HEDLEY_CLANG_HAS_CPP_ATTRIBUTE +#endif +#define JSON_HEDLEY_CLANG_HAS_CPP_ATTRIBUTE(attribute) JSON_HEDLEY_HAS_CPP_ATTRIBUTE(attribute) + +#if defined(JSON_HEDLEY_CLANG_HAS_BUILTIN) + #undef JSON_HEDLEY_CLANG_HAS_BUILTIN +#endif +#define JSON_HEDLEY_CLANG_HAS_BUILTIN(builtin) JSON_HEDLEY_HAS_BUILTIN(builtin) + +#if defined(JSON_HEDLEY_CLANG_HAS_FEATURE) + #undef JSON_HEDLEY_CLANG_HAS_FEATURE +#endif +#define JSON_HEDLEY_CLANG_HAS_FEATURE(feature) JSON_HEDLEY_HAS_FEATURE(feature) + +#if defined(JSON_HEDLEY_CLANG_HAS_EXTENSION) + #undef JSON_HEDLEY_CLANG_HAS_EXTENSION +#endif +#define JSON_HEDLEY_CLANG_HAS_EXTENSION(extension) JSON_HEDLEY_HAS_EXTENSION(extension) + +#if defined(JSON_HEDLEY_CLANG_HAS_DECLSPEC_DECLSPEC_ATTRIBUTE) + #undef JSON_HEDLEY_CLANG_HAS_DECLSPEC_DECLSPEC_ATTRIBUTE +#endif +#define JSON_HEDLEY_CLANG_HAS_DECLSPEC_ATTRIBUTE(attribute) JSON_HEDLEY_HAS_DECLSPEC_ATTRIBUTE(attribute) + +#if defined(JSON_HEDLEY_CLANG_HAS_WARNING) + #undef JSON_HEDLEY_CLANG_HAS_WARNING +#endif +#define JSON_HEDLEY_CLANG_HAS_WARNING(warning) JSON_HEDLEY_HAS_WARNING(warning) + +#endif /* !defined(JSON_HEDLEY_VERSION) || (JSON_HEDLEY_VERSION < X) */ + + +// This file contains all internal macro definitions (except those affecting ABI) +// You MUST include macro_unscope.hpp at the end of json.hpp to undef all of them + +// #include + + +// exclude unsupported compilers +#if !defined(JSON_SKIP_UNSUPPORTED_COMPILER_CHECK) + #if defined(__clang__) + #if (__clang_major__ * 10000 + __clang_minor__ * 100 + __clang_patchlevel__) < 30400 + #error "unsupported Clang version - see https://github.com/nlohmann/json#supported-compilers" + #endif + #elif defined(__GNUC__) && !(defined(__ICC) || defined(__INTEL_COMPILER)) + #if (__GNUC__ * 10000 + __GNUC_MINOR__ * 100 + __GNUC_PATCHLEVEL__) < 40800 + #error "unsupported GCC version - see https://github.com/nlohmann/json#supported-compilers" + #endif + #endif +#endif + +// C++ language standard detection +// if the user manually specified the used c++ version this is skipped +#if !defined(JSON_HAS_CPP_20) && !defined(JSON_HAS_CPP_17) && !defined(JSON_HAS_CPP_14) && !defined(JSON_HAS_CPP_11) + #if (defined(__cplusplus) && __cplusplus >= 202002L) || (defined(_MSVC_LANG) && _MSVC_LANG >= 202002L) + #define JSON_HAS_CPP_20 + #define JSON_HAS_CPP_17 + #define JSON_HAS_CPP_14 + #elif (defined(__cplusplus) && __cplusplus >= 201703L) || (defined(_HAS_CXX17) && _HAS_CXX17 == 1) // fix for issue #464 + #define JSON_HAS_CPP_17 + #define JSON_HAS_CPP_14 + #elif (defined(__cplusplus) && __cplusplus >= 201402L) || (defined(_HAS_CXX14) && _HAS_CXX14 == 1) + #define JSON_HAS_CPP_14 + #endif + // the cpp 11 flag is always specified because it is the minimal required version + #define JSON_HAS_CPP_11 +#endif + +#ifdef __has_include + #if __has_include() + #include + #endif +#endif + +#if !defined(JSON_HAS_FILESYSTEM) && !defined(JSON_HAS_EXPERIMENTAL_FILESYSTEM) + #ifdef JSON_HAS_CPP_17 + #if defined(__cpp_lib_filesystem) + #define JSON_HAS_FILESYSTEM 1 + #elif defined(__cpp_lib_experimental_filesystem) + #define JSON_HAS_EXPERIMENTAL_FILESYSTEM 1 + #elif !defined(__has_include) + #define JSON_HAS_EXPERIMENTAL_FILESYSTEM 1 + #elif __has_include() + #define JSON_HAS_FILESYSTEM 1 + #elif __has_include() + #define JSON_HAS_EXPERIMENTAL_FILESYSTEM 1 + #endif + + // std::filesystem does not work on MinGW GCC 8: https://sourceforge.net/p/mingw-w64/bugs/737/ + #if defined(__MINGW32__) && defined(__GNUC__) && __GNUC__ == 8 + #undef JSON_HAS_FILESYSTEM + #undef JSON_HAS_EXPERIMENTAL_FILESYSTEM + #endif + + // no filesystem support before GCC 8: https://en.cppreference.com/w/cpp/compiler_support + #if defined(__GNUC__) && !defined(__clang__) && __GNUC__ < 8 + #undef JSON_HAS_FILESYSTEM + #undef JSON_HAS_EXPERIMENTAL_FILESYSTEM + #endif + + // no filesystem support before Clang 7: https://en.cppreference.com/w/cpp/compiler_support + #if defined(__clang_major__) && __clang_major__ < 7 + #undef JSON_HAS_FILESYSTEM + #undef JSON_HAS_EXPERIMENTAL_FILESYSTEM + #endif + + // no filesystem support before MSVC 19.14: https://en.cppreference.com/w/cpp/compiler_support + #if defined(_MSC_VER) && _MSC_VER < 1914 + #undef JSON_HAS_FILESYSTEM + #undef JSON_HAS_EXPERIMENTAL_FILESYSTEM + #endif + + // no filesystem support before iOS 13 + #if defined(__IPHONE_OS_VERSION_MIN_REQUIRED) && __IPHONE_OS_VERSION_MIN_REQUIRED < 130000 + #undef JSON_HAS_FILESYSTEM + #undef JSON_HAS_EXPERIMENTAL_FILESYSTEM + #endif + + // no filesystem support before macOS Catalina + #if defined(__MAC_OS_X_VERSION_MIN_REQUIRED) && __MAC_OS_X_VERSION_MIN_REQUIRED < 101500 + #undef JSON_HAS_FILESYSTEM + #undef JSON_HAS_EXPERIMENTAL_FILESYSTEM + #endif + #endif +#endif + +#ifndef JSON_HAS_EXPERIMENTAL_FILESYSTEM + #define JSON_HAS_EXPERIMENTAL_FILESYSTEM 0 +#endif + +#ifndef JSON_HAS_FILESYSTEM + #define JSON_HAS_FILESYSTEM 0 +#endif + +#ifndef JSON_HAS_THREE_WAY_COMPARISON + #if defined(__cpp_impl_three_way_comparison) && __cpp_impl_three_way_comparison >= 201907L \ + && defined(__cpp_lib_three_way_comparison) && __cpp_lib_three_way_comparison >= 201907L + #define JSON_HAS_THREE_WAY_COMPARISON 1 + #else + #define JSON_HAS_THREE_WAY_COMPARISON 0 + #endif +#endif + +#ifndef JSON_HAS_RANGES + // ranges header shipping in GCC 11.1.0 (released 2021-04-27) has syntax error + #if defined(__GLIBCXX__) && __GLIBCXX__ == 20210427 + #define JSON_HAS_RANGES 0 + #elif defined(__cpp_lib_ranges) + #define JSON_HAS_RANGES 1 + #else + #define JSON_HAS_RANGES 0 + #endif +#endif + +#ifndef JSON_HAS_STATIC_RTTI + #if !defined(_HAS_STATIC_RTTI) || _HAS_STATIC_RTTI != 0 + #define JSON_HAS_STATIC_RTTI 1 + #else + #define JSON_HAS_STATIC_RTTI 0 + #endif +#endif + +#ifdef JSON_HAS_CPP_17 + #define JSON_INLINE_VARIABLE inline +#else + #define JSON_INLINE_VARIABLE +#endif + +#if JSON_HEDLEY_HAS_ATTRIBUTE(no_unique_address) + #define JSON_NO_UNIQUE_ADDRESS [[no_unique_address]] +#else + #define JSON_NO_UNIQUE_ADDRESS +#endif + +// disable documentation warnings on clang +#if defined(__clang__) + #pragma clang diagnostic push + #pragma clang diagnostic ignored "-Wdocumentation" + #pragma clang diagnostic ignored "-Wdocumentation-unknown-command" +#endif + +// allow disabling exceptions +#if (defined(__cpp_exceptions) || defined(__EXCEPTIONS) || defined(_CPPUNWIND)) && !defined(JSON_NOEXCEPTION) + #define JSON_THROW(exception) throw exception + #define JSON_TRY try + #define JSON_CATCH(exception) catch(exception) + #define JSON_INTERNAL_CATCH(exception) catch(exception) +#else + #include + #define JSON_THROW(exception) std::abort() + #define JSON_TRY if(true) + #define JSON_CATCH(exception) if(false) + #define JSON_INTERNAL_CATCH(exception) if(false) +#endif + +// override exception macros +#if defined(JSON_THROW_USER) + #undef JSON_THROW + #define JSON_THROW JSON_THROW_USER +#endif +#if defined(JSON_TRY_USER) + #undef JSON_TRY + #define JSON_TRY JSON_TRY_USER +#endif +#if defined(JSON_CATCH_USER) + #undef JSON_CATCH + #define JSON_CATCH JSON_CATCH_USER + #undef JSON_INTERNAL_CATCH + #define JSON_INTERNAL_CATCH JSON_CATCH_USER +#endif +#if defined(JSON_INTERNAL_CATCH_USER) + #undef JSON_INTERNAL_CATCH + #define JSON_INTERNAL_CATCH JSON_INTERNAL_CATCH_USER +#endif + +// allow overriding assert +#if !defined(JSON_ASSERT) + #include // assert + #define JSON_ASSERT(x) assert(x) +#endif + +// allow to access some private functions (needed by the test suite) +#if defined(JSON_TESTS_PRIVATE) + #define JSON_PRIVATE_UNLESS_TESTED public +#else + #define JSON_PRIVATE_UNLESS_TESTED private +#endif + +/*! +@brief macro to briefly define a mapping between an enum and JSON +@def NLOHMANN_JSON_SERIALIZE_ENUM +@since version 3.4.0 +*/ +#define NLOHMANN_JSON_SERIALIZE_ENUM(ENUM_TYPE, ...) \ + template \ + inline void to_json(BasicJsonType& j, const ENUM_TYPE& e) \ + { \ + /* NOLINTNEXTLINE(modernize-type-traits) we use C++11 */ \ + static_assert(std::is_enum::value, #ENUM_TYPE " must be an enum!"); \ + /* NOLINTNEXTLINE(modernize-avoid-c-arrays) we don't want to depend on */ \ + static const std::pair m[] = __VA_ARGS__; \ + auto it = std::find_if(std::begin(m), std::end(m), \ + [e](const std::pair& ej_pair) -> bool \ + { \ + return ej_pair.first == e; \ + }); \ + j = ((it != std::end(m)) ? it : std::begin(m))->second; \ + } \ + template \ + inline void from_json(const BasicJsonType& j, ENUM_TYPE& e) \ + { \ + /* NOLINTNEXTLINE(modernize-type-traits) we use C++11 */ \ + static_assert(std::is_enum::value, #ENUM_TYPE " must be an enum!"); \ + /* NOLINTNEXTLINE(modernize-avoid-c-arrays) we don't want to depend on */ \ + static const std::pair m[] = __VA_ARGS__; \ + auto it = std::find_if(std::begin(m), std::end(m), \ + [&j](const std::pair& ej_pair) -> bool \ + { \ + return ej_pair.second == j; \ + }); \ + e = ((it != std::end(m)) ? it : std::begin(m))->first; \ + } + +// Ugly macros to avoid uglier copy-paste when specializing basic_json. They +// may be removed in the future once the class is split. + +#define NLOHMANN_BASIC_JSON_TPL_DECLARATION \ + template class ObjectType, \ + template class ArrayType, \ + class StringType, class BooleanType, class NumberIntegerType, \ + class NumberUnsignedType, class NumberFloatType, \ + template class AllocatorType, \ + template class JSONSerializer, \ + class BinaryType, \ + class CustomBaseClass> + +#define NLOHMANN_BASIC_JSON_TPL \ + basic_json + +// Macros to simplify conversion from/to types + +#define NLOHMANN_JSON_EXPAND( x ) x +#define NLOHMANN_JSON_GET_MACRO(_1, _2, _3, _4, _5, _6, _7, _8, _9, _10, _11, _12, _13, _14, _15, _16, _17, _18, _19, _20, _21, _22, _23, _24, _25, _26, _27, _28, _29, _30, _31, _32, _33, _34, _35, _36, _37, _38, _39, _40, _41, _42, _43, _44, _45, _46, _47, _48, _49, _50, _51, _52, _53, _54, _55, _56, _57, _58, _59, _60, _61, _62, _63, _64, NAME,...) NAME +#define NLOHMANN_JSON_PASTE(...) NLOHMANN_JSON_EXPAND(NLOHMANN_JSON_GET_MACRO(__VA_ARGS__, \ + NLOHMANN_JSON_PASTE64, \ + NLOHMANN_JSON_PASTE63, \ + NLOHMANN_JSON_PASTE62, \ + NLOHMANN_JSON_PASTE61, \ + NLOHMANN_JSON_PASTE60, \ + NLOHMANN_JSON_PASTE59, \ + NLOHMANN_JSON_PASTE58, \ + NLOHMANN_JSON_PASTE57, \ + NLOHMANN_JSON_PASTE56, \ + NLOHMANN_JSON_PASTE55, \ + NLOHMANN_JSON_PASTE54, \ + NLOHMANN_JSON_PASTE53, \ + NLOHMANN_JSON_PASTE52, \ + NLOHMANN_JSON_PASTE51, \ + NLOHMANN_JSON_PASTE50, \ + NLOHMANN_JSON_PASTE49, \ + NLOHMANN_JSON_PASTE48, \ + NLOHMANN_JSON_PASTE47, \ + NLOHMANN_JSON_PASTE46, \ + NLOHMANN_JSON_PASTE45, \ + NLOHMANN_JSON_PASTE44, \ + NLOHMANN_JSON_PASTE43, \ + NLOHMANN_JSON_PASTE42, \ + NLOHMANN_JSON_PASTE41, \ + NLOHMANN_JSON_PASTE40, \ + NLOHMANN_JSON_PASTE39, \ + NLOHMANN_JSON_PASTE38, \ + NLOHMANN_JSON_PASTE37, \ + NLOHMANN_JSON_PASTE36, \ + NLOHMANN_JSON_PASTE35, \ + NLOHMANN_JSON_PASTE34, \ + NLOHMANN_JSON_PASTE33, \ + NLOHMANN_JSON_PASTE32, \ + NLOHMANN_JSON_PASTE31, \ + NLOHMANN_JSON_PASTE30, \ + NLOHMANN_JSON_PASTE29, \ + NLOHMANN_JSON_PASTE28, \ + NLOHMANN_JSON_PASTE27, \ + NLOHMANN_JSON_PASTE26, \ + NLOHMANN_JSON_PASTE25, \ + NLOHMANN_JSON_PASTE24, \ + NLOHMANN_JSON_PASTE23, \ + NLOHMANN_JSON_PASTE22, \ + NLOHMANN_JSON_PASTE21, \ + NLOHMANN_JSON_PASTE20, \ + NLOHMANN_JSON_PASTE19, \ + NLOHMANN_JSON_PASTE18, \ + NLOHMANN_JSON_PASTE17, \ + NLOHMANN_JSON_PASTE16, \ + NLOHMANN_JSON_PASTE15, \ + NLOHMANN_JSON_PASTE14, \ + NLOHMANN_JSON_PASTE13, \ + NLOHMANN_JSON_PASTE12, \ + NLOHMANN_JSON_PASTE11, \ + NLOHMANN_JSON_PASTE10, \ + NLOHMANN_JSON_PASTE9, \ + NLOHMANN_JSON_PASTE8, \ + NLOHMANN_JSON_PASTE7, \ + NLOHMANN_JSON_PASTE6, \ + NLOHMANN_JSON_PASTE5, \ + NLOHMANN_JSON_PASTE4, \ + NLOHMANN_JSON_PASTE3, \ + NLOHMANN_JSON_PASTE2, \ + NLOHMANN_JSON_PASTE1)(__VA_ARGS__)) +#define NLOHMANN_JSON_PASTE2(func, v1) func(v1) +#define NLOHMANN_JSON_PASTE3(func, v1, v2) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE2(func, v2) +#define NLOHMANN_JSON_PASTE4(func, v1, v2, v3) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE3(func, v2, v3) +#define NLOHMANN_JSON_PASTE5(func, v1, v2, v3, v4) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE4(func, v2, v3, v4) +#define NLOHMANN_JSON_PASTE6(func, v1, v2, v3, v4, v5) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE5(func, v2, v3, v4, v5) +#define NLOHMANN_JSON_PASTE7(func, v1, v2, v3, v4, v5, v6) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE6(func, v2, v3, v4, v5, v6) +#define NLOHMANN_JSON_PASTE8(func, v1, v2, v3, v4, v5, v6, v7) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE7(func, v2, v3, v4, v5, v6, v7) +#define NLOHMANN_JSON_PASTE9(func, v1, v2, v3, v4, v5, v6, v7, v8) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE8(func, v2, v3, v4, v5, v6, v7, v8) +#define NLOHMANN_JSON_PASTE10(func, v1, v2, v3, v4, v5, v6, v7, v8, v9) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE9(func, v2, v3, v4, v5, v6, v7, v8, v9) +#define NLOHMANN_JSON_PASTE11(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE10(func, v2, v3, v4, v5, v6, v7, v8, v9, v10) +#define NLOHMANN_JSON_PASTE12(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE11(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11) +#define NLOHMANN_JSON_PASTE13(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE12(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12) +#define NLOHMANN_JSON_PASTE14(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE13(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13) +#define NLOHMANN_JSON_PASTE15(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE14(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14) +#define NLOHMANN_JSON_PASTE16(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE15(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15) +#define NLOHMANN_JSON_PASTE17(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE16(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16) +#define NLOHMANN_JSON_PASTE18(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE17(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17) +#define NLOHMANN_JSON_PASTE19(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE18(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18) +#define NLOHMANN_JSON_PASTE20(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE19(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19) +#define NLOHMANN_JSON_PASTE21(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE20(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20) +#define NLOHMANN_JSON_PASTE22(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE21(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21) +#define NLOHMANN_JSON_PASTE23(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE22(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22) +#define NLOHMANN_JSON_PASTE24(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE23(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23) +#define NLOHMANN_JSON_PASTE25(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE24(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24) +#define NLOHMANN_JSON_PASTE26(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE25(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25) +#define NLOHMANN_JSON_PASTE27(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE26(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26) +#define NLOHMANN_JSON_PASTE28(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE27(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27) +#define NLOHMANN_JSON_PASTE29(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE28(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28) +#define NLOHMANN_JSON_PASTE30(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE29(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29) +#define NLOHMANN_JSON_PASTE31(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE30(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30) +#define NLOHMANN_JSON_PASTE32(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE31(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31) +#define NLOHMANN_JSON_PASTE33(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE32(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32) +#define NLOHMANN_JSON_PASTE34(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE33(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33) +#define NLOHMANN_JSON_PASTE35(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE34(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34) +#define NLOHMANN_JSON_PASTE36(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE35(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35) +#define NLOHMANN_JSON_PASTE37(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE36(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36) +#define NLOHMANN_JSON_PASTE38(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE37(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37) +#define NLOHMANN_JSON_PASTE39(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE38(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38) +#define NLOHMANN_JSON_PASTE40(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE39(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39) +#define NLOHMANN_JSON_PASTE41(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE40(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40) +#define NLOHMANN_JSON_PASTE42(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE41(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41) +#define NLOHMANN_JSON_PASTE43(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE42(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42) +#define NLOHMANN_JSON_PASTE44(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE43(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43) +#define NLOHMANN_JSON_PASTE45(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE44(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44) +#define NLOHMANN_JSON_PASTE46(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE45(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45) +#define NLOHMANN_JSON_PASTE47(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE46(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46) +#define NLOHMANN_JSON_PASTE48(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE47(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47) +#define NLOHMANN_JSON_PASTE49(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE48(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48) +#define NLOHMANN_JSON_PASTE50(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48, v49) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE49(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48, v49) +#define NLOHMANN_JSON_PASTE51(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48, v49, v50) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE50(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48, v49, v50) +#define NLOHMANN_JSON_PASTE52(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48, v49, v50, v51) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE51(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48, v49, v50, v51) +#define NLOHMANN_JSON_PASTE53(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48, v49, v50, v51, v52) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE52(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48, v49, v50, v51, v52) +#define NLOHMANN_JSON_PASTE54(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48, v49, v50, v51, v52, v53) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE53(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48, v49, v50, v51, v52, v53) +#define NLOHMANN_JSON_PASTE55(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48, v49, v50, v51, v52, v53, v54) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE54(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48, v49, v50, v51, v52, v53, v54) +#define NLOHMANN_JSON_PASTE56(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48, v49, v50, v51, v52, v53, v54, v55) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE55(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48, v49, v50, v51, v52, v53, v54, v55) +#define NLOHMANN_JSON_PASTE57(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48, v49, v50, v51, v52, v53, v54, v55, v56) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE56(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48, v49, v50, v51, v52, v53, v54, v55, v56) +#define NLOHMANN_JSON_PASTE58(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48, v49, v50, v51, v52, v53, v54, v55, v56, v57) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE57(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48, v49, v50, v51, v52, v53, v54, v55, v56, v57) +#define NLOHMANN_JSON_PASTE59(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48, v49, v50, v51, v52, v53, v54, v55, v56, v57, v58) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE58(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48, v49, v50, v51, v52, v53, v54, v55, v56, v57, v58) +#define NLOHMANN_JSON_PASTE60(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48, v49, v50, v51, v52, v53, v54, v55, v56, v57, v58, v59) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE59(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48, v49, v50, v51, v52, v53, v54, v55, v56, v57, v58, v59) +#define NLOHMANN_JSON_PASTE61(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48, v49, v50, v51, v52, v53, v54, v55, v56, v57, v58, v59, v60) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE60(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48, v49, v50, v51, v52, v53, v54, v55, v56, v57, v58, v59, v60) +#define NLOHMANN_JSON_PASTE62(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48, v49, v50, v51, v52, v53, v54, v55, v56, v57, v58, v59, v60, v61) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE61(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48, v49, v50, v51, v52, v53, v54, v55, v56, v57, v58, v59, v60, v61) +#define NLOHMANN_JSON_PASTE63(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48, v49, v50, v51, v52, v53, v54, v55, v56, v57, v58, v59, v60, v61, v62) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE62(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48, v49, v50, v51, v52, v53, v54, v55, v56, v57, v58, v59, v60, v61, v62) +#define NLOHMANN_JSON_PASTE64(func, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48, v49, v50, v51, v52, v53, v54, v55, v56, v57, v58, v59, v60, v61, v62, v63) NLOHMANN_JSON_PASTE2(func, v1) NLOHMANN_JSON_PASTE63(func, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31, v32, v33, v34, v35, v36, v37, v38, v39, v40, v41, v42, v43, v44, v45, v46, v47, v48, v49, v50, v51, v52, v53, v54, v55, v56, v57, v58, v59, v60, v61, v62, v63) + +#define NLOHMANN_JSON_TO(v1) nlohmann_json_j[#v1] = nlohmann_json_t.v1; +#define NLOHMANN_JSON_FROM(v1) nlohmann_json_j.at(#v1).get_to(nlohmann_json_t.v1); +#define NLOHMANN_JSON_FROM_WITH_DEFAULT(v1) nlohmann_json_t.v1 = nlohmann_json_j.value(#v1, nlohmann_json_default_obj.v1); + +/*! +@brief macro +@def NLOHMANN_DEFINE_TYPE_INTRUSIVE +@since version 3.9.0 +*/ +#define NLOHMANN_DEFINE_TYPE_INTRUSIVE(Type, ...) \ + friend void to_json(nlohmann::json& nlohmann_json_j, const Type& nlohmann_json_t) { NLOHMANN_JSON_EXPAND(NLOHMANN_JSON_PASTE(NLOHMANN_JSON_TO, __VA_ARGS__)) } \ + friend void from_json(const nlohmann::json& nlohmann_json_j, Type& nlohmann_json_t) { NLOHMANN_JSON_EXPAND(NLOHMANN_JSON_PASTE(NLOHMANN_JSON_FROM, __VA_ARGS__)) } + +#define NLOHMANN_DEFINE_TYPE_INTRUSIVE_WITH_DEFAULT(Type, ...) \ + friend void to_json(nlohmann::json& nlohmann_json_j, const Type& nlohmann_json_t) { NLOHMANN_JSON_EXPAND(NLOHMANN_JSON_PASTE(NLOHMANN_JSON_TO, __VA_ARGS__)) } \ + friend void from_json(const nlohmann::json& nlohmann_json_j, Type& nlohmann_json_t) { const Type nlohmann_json_default_obj{}; NLOHMANN_JSON_EXPAND(NLOHMANN_JSON_PASTE(NLOHMANN_JSON_FROM_WITH_DEFAULT, __VA_ARGS__)) } + +#define NLOHMANN_DEFINE_TYPE_INTRUSIVE_ONLY_SERIALIZE(Type, ...) \ + friend void to_json(nlohmann::json& nlohmann_json_j, const Type& nlohmann_json_t) { NLOHMANN_JSON_EXPAND(NLOHMANN_JSON_PASTE(NLOHMANN_JSON_TO, __VA_ARGS__)) } + +/*! +@brief macro +@def NLOHMANN_DEFINE_TYPE_NON_INTRUSIVE +@since version 3.9.0 +*/ +#define NLOHMANN_DEFINE_TYPE_NON_INTRUSIVE(Type, ...) \ + inline void to_json(nlohmann::json& nlohmann_json_j, const Type& nlohmann_json_t) { NLOHMANN_JSON_EXPAND(NLOHMANN_JSON_PASTE(NLOHMANN_JSON_TO, __VA_ARGS__)) } \ + inline void from_json(const nlohmann::json& nlohmann_json_j, Type& nlohmann_json_t) { NLOHMANN_JSON_EXPAND(NLOHMANN_JSON_PASTE(NLOHMANN_JSON_FROM, __VA_ARGS__)) } + +#define NLOHMANN_DEFINE_TYPE_NON_INTRUSIVE_ONLY_SERIALIZE(Type, ...) \ + inline void to_json(nlohmann::json& nlohmann_json_j, const Type& nlohmann_json_t) { NLOHMANN_JSON_EXPAND(NLOHMANN_JSON_PASTE(NLOHMANN_JSON_TO, __VA_ARGS__)) } + +#define NLOHMANN_DEFINE_TYPE_NON_INTRUSIVE_WITH_DEFAULT(Type, ...) \ + inline void to_json(nlohmann::json& nlohmann_json_j, const Type& nlohmann_json_t) { NLOHMANN_JSON_EXPAND(NLOHMANN_JSON_PASTE(NLOHMANN_JSON_TO, __VA_ARGS__)) } \ + inline void from_json(const nlohmann::json& nlohmann_json_j, Type& nlohmann_json_t) { const Type nlohmann_json_default_obj{}; NLOHMANN_JSON_EXPAND(NLOHMANN_JSON_PASTE(NLOHMANN_JSON_FROM_WITH_DEFAULT, __VA_ARGS__)) } + +/*! +@brief macro +@def NLOHMANN_DEFINE_DERIVED_TYPE_INTRUSIVE +@since version 3.11.x +*/ +#define NLOHMANN_DEFINE_DERIVED_TYPE_INTRUSIVE(Type, BaseType, ...) \ + friend void to_json(nlohmann::json& nlohmann_json_j, const Type& nlohmann_json_t) { nlohmann::to_json(nlohmann_json_j, static_cast(nlohmann_json_t)); NLOHMANN_JSON_EXPAND(NLOHMANN_JSON_PASTE(NLOHMANN_JSON_TO, __VA_ARGS__)) } \ + friend void from_json(const nlohmann::json& nlohmann_json_j, Type& nlohmann_json_t) { nlohmann::from_json(nlohmann_json_j, static_cast(nlohmann_json_t)); NLOHMANN_JSON_EXPAND(NLOHMANN_JSON_PASTE(NLOHMANN_JSON_FROM, __VA_ARGS__)) } + +#define NLOHMANN_DEFINE_DERIVED_TYPE_INTRUSIVE_WITH_DEFAULT(Type, BaseType, ...) \ + friend void to_json(nlohmann::json& nlohmann_json_j, const Type& nlohmann_json_t) { nlohmann::to_json(nlohmann_json_j, static_cast(nlohmann_json_t)); NLOHMANN_JSON_EXPAND(NLOHMANN_JSON_PASTE(NLOHMANN_JSON_TO, __VA_ARGS__)) } \ + friend void from_json(const nlohmann::json& nlohmann_json_j, Type& nlohmann_json_t) { nlohmann::from_json(nlohmann_json_j, static_cast(nlohmann_json_t)); const Type nlohmann_json_default_obj{}; NLOHMANN_JSON_EXPAND(NLOHMANN_JSON_PASTE(NLOHMANN_JSON_FROM_WITH_DEFAULT, __VA_ARGS__)) } + +/*! +@brief macro +@def NLOHMANN_DEFINE_DERIVED_TYPE_NON_INTRUSIVE +@since version 3.11.x +*/ +#define NLOHMANN_DEFINE_DERIVED_TYPE_NON_INTRUSIVE(Type, BaseType, ...) \ + inline void to_json(nlohmann::json& nlohmann_json_j, const Type& nlohmann_json_t) { nlohmann::to_json(nlohmann_json_j, static_cast(nlohmann_json_t)); NLOHMANN_JSON_EXPAND(NLOHMANN_JSON_PASTE(NLOHMANN_JSON_TO, __VA_ARGS__)) } \ + inline void from_json(const nlohmann::json& nlohmann_json_j, Type& nlohmann_json_t) { nlohmann::from_json(nlohmann_json_j, static_cast(nlohmann_json_t)); NLOHMANN_JSON_EXPAND(NLOHMANN_JSON_PASTE(NLOHMANN_JSON_FROM, __VA_ARGS__)) } + +#define NLOHMANN_DEFINE_DERIVED_TYPE_NON_INTRUSIVE_WITH_DEFAULT(Type, BaseType, ...) \ + inline void to_json(nlohmann::json& nlohmann_json_j, const Type& nlohmann_json_t) { nlohmann::to_json(nlohmann_json_j, static_cast(nlohmann_json_t)); NLOHMANN_JSON_EXPAND(NLOHMANN_JSON_PASTE(NLOHMANN_JSON_TO, __VA_ARGS__)) } \ + inline void from_json(const nlohmann::json& nlohmann_json_j, Type& nlohmann_json_t) { nlohmann::from_json(nlohmann_json_j, static_cast(nlohmann_json_t)); const Type nlohmann_json_default_obj{}; NLOHMANN_JSON_EXPAND(NLOHMANN_JSON_PASTE(NLOHMANN_JSON_FROM_WITH_DEFAULT, __VA_ARGS__)) } + +// inspired from https://stackoverflow.com/a/26745591 +// allows to call any std function as if (e.g. with begin): +// using std::begin; begin(x); +// +// it allows using the detected idiom to retrieve the return type +// of such an expression +#define NLOHMANN_CAN_CALL_STD_FUNC_IMPL(std_name) \ + namespace detail { \ + using std::std_name; \ + \ + template \ + using result_of_##std_name = decltype(std_name(std::declval()...)); \ + } \ + \ + namespace detail2 { \ + struct std_name##_tag \ + { \ + }; \ + \ + template \ + std_name##_tag std_name(T&&...); \ + \ + template \ + using result_of_##std_name = decltype(std_name(std::declval()...)); \ + \ + template \ + struct would_call_std_##std_name \ + { \ + static constexpr auto const value = ::nlohmann::detail:: \ + is_detected_exact::value; \ + }; \ + } /* namespace detail2 */ \ + \ + template \ + struct would_call_std_##std_name : detail2::would_call_std_##std_name \ + { \ + } + +#ifndef JSON_USE_IMPLICIT_CONVERSIONS + #define JSON_USE_IMPLICIT_CONVERSIONS 1 +#endif + +#if JSON_USE_IMPLICIT_CONVERSIONS + #define JSON_EXPLICIT +#else + #define JSON_EXPLICIT explicit +#endif + +#ifndef JSON_DISABLE_ENUM_SERIALIZATION + #define JSON_DISABLE_ENUM_SERIALIZATION 0 +#endif + +#ifndef JSON_USE_GLOBAL_UDLS + #define JSON_USE_GLOBAL_UDLS 1 +#endif + +#if JSON_HAS_THREE_WAY_COMPARISON + #include // partial_ordering +#endif + +NLOHMANN_JSON_NAMESPACE_BEGIN +namespace detail +{ + +/////////////////////////// +// JSON type enumeration // +/////////////////////////// + +/*! +@brief the JSON type enumeration + +This enumeration collects the different JSON types. It is internally used to +distinguish the stored values, and the functions @ref basic_json::is_null(), +@ref basic_json::is_object(), @ref basic_json::is_array(), +@ref basic_json::is_string(), @ref basic_json::is_boolean(), +@ref basic_json::is_number() (with @ref basic_json::is_number_integer(), +@ref basic_json::is_number_unsigned(), and @ref basic_json::is_number_float()), +@ref basic_json::is_discarded(), @ref basic_json::is_primitive(), and +@ref basic_json::is_structured() rely on it. + +@note There are three enumeration entries (number_integer, number_unsigned, and +number_float), because the library distinguishes these three types for numbers: +@ref basic_json::number_unsigned_t is used for unsigned integers, +@ref basic_json::number_integer_t is used for signed integers, and +@ref basic_json::number_float_t is used for floating-point numbers or to +approximate integers which do not fit in the limits of their respective type. + +@sa see @ref basic_json::basic_json(const value_t value_type) -- create a JSON +value with the default value for a given type + +@since version 1.0.0 +*/ +enum class value_t : std::uint8_t +{ + null, ///< null value + object, ///< object (unordered set of name/value pairs) + array, ///< array (ordered collection of values) + string, ///< string value + boolean, ///< boolean value + number_integer, ///< number value (signed integer) + number_unsigned, ///< number value (unsigned integer) + number_float, ///< number value (floating-point) + binary, ///< binary array (ordered collection of bytes) + discarded ///< discarded by the parser callback function +}; + +/*! +@brief comparison operator for JSON types + +Returns an ordering that is similar to Python: +- order: null < boolean < number < object < array < string < binary +- furthermore, each type is not smaller than itself +- discarded values are not comparable +- binary is represented as a b"" string in python and directly comparable to a + string; however, making a binary array directly comparable with a string would + be surprising behavior in a JSON file. + +@since version 1.0.0 +*/ +#if JSON_HAS_THREE_WAY_COMPARISON + inline std::partial_ordering operator<=>(const value_t lhs, const value_t rhs) noexcept // *NOPAD* +#else + inline bool operator<(const value_t lhs, const value_t rhs) noexcept +#endif +{ + static constexpr std::array order = {{ + 0 /* null */, 3 /* object */, 4 /* array */, 5 /* string */, + 1 /* boolean */, 2 /* integer */, 2 /* unsigned */, 2 /* float */, + 6 /* binary */ + } + }; + + const auto l_index = static_cast(lhs); + const auto r_index = static_cast(rhs); +#if JSON_HAS_THREE_WAY_COMPARISON + if (l_index < order.size() && r_index < order.size()) + { + return order[l_index] <=> order[r_index]; // *NOPAD* + } + return std::partial_ordering::unordered; +#else + return l_index < order.size() && r_index < order.size() && order[l_index] < order[r_index]; +#endif +} + +// GCC selects the built-in operator< over an operator rewritten from +// a user-defined spaceship operator +// Clang, MSVC, and ICC select the rewritten candidate +// (see GCC bug https://gcc.gnu.org/bugzilla/show_bug.cgi?id=105200) +#if JSON_HAS_THREE_WAY_COMPARISON && defined(__GNUC__) +inline bool operator<(const value_t lhs, const value_t rhs) noexcept +{ + return std::is_lt(lhs <=> rhs); // *NOPAD* +} +#endif + +} // namespace detail +NLOHMANN_JSON_NAMESPACE_END + +// #include +// __ _____ _____ _____ +// __| | __| | | | JSON for Modern C++ +// | | |__ | | | | | | version 3.11.3 +// |_____|_____|_____|_|___| https://github.com/nlohmann/json +// +// SPDX-FileCopyrightText: 2013 - 2024 Niels Lohmann +// SPDX-License-Identifier: MIT + + + +// #include + + +NLOHMANN_JSON_NAMESPACE_BEGIN +namespace detail +{ + +/*! +@brief replace all occurrences of a substring by another string + +@param[in,out] s the string to manipulate; changed so that all + occurrences of @a f are replaced with @a t +@param[in] f the substring to replace with @a t +@param[in] t the string to replace @a f + +@pre The search string @a f must not be empty. **This precondition is +enforced with an assertion.** + +@since version 2.0.0 +*/ +template +inline void replace_substring(StringType& s, const StringType& f, + const StringType& t) +{ + JSON_ASSERT(!f.empty()); + for (auto pos = s.find(f); // find first occurrence of f + pos != StringType::npos; // make sure f was found + s.replace(pos, f.size(), t), // replace with t, and + pos = s.find(f, pos + t.size())) // find next occurrence of f + {} +} + +/*! + * @brief string escaping as described in RFC 6901 (Sect. 4) + * @param[in] s string to escape + * @return escaped string + * + * Note the order of escaping "~" to "~0" and "/" to "~1" is important. + */ +template +inline StringType escape(StringType s) +{ + replace_substring(s, StringType{"~"}, StringType{"~0"}); + replace_substring(s, StringType{"/"}, StringType{"~1"}); + return s; +} + +/*! + * @brief string unescaping as described in RFC 6901 (Sect. 4) + * @param[in] s string to unescape + * @return unescaped string + * + * Note the order of escaping "~1" to "/" and "~0" to "~" is important. + */ +template +static void unescape(StringType& s) +{ + replace_substring(s, StringType{"~1"}, StringType{"/"}); + replace_substring(s, StringType{"~0"}, StringType{"~"}); +} + +} // namespace detail +NLOHMANN_JSON_NAMESPACE_END + +// #include +// __ _____ _____ _____ +// __| | __| | | | JSON for Modern C++ +// | | |__ | | | | | | version 3.11.3 +// |_____|_____|_____|_|___| https://github.com/nlohmann/json +// +// SPDX-FileCopyrightText: 2013 - 2024 Niels Lohmann +// SPDX-License-Identifier: MIT + + + +#include // size_t + +// #include + + +NLOHMANN_JSON_NAMESPACE_BEGIN +namespace detail +{ + +/// struct to capture the start position of the current token +struct position_t +{ + /// the total number of characters read + std::size_t chars_read_total = 0; + /// the number of characters read in the current line + std::size_t chars_read_current_line = 0; + /// the number of lines read + std::size_t lines_read = 0; + + /// conversion to size_t to preserve SAX interface + constexpr operator size_t() const + { + return chars_read_total; + } +}; + +} // namespace detail +NLOHMANN_JSON_NAMESPACE_END + +// #include + +// #include +// __ _____ _____ _____ +// __| | __| | | | JSON for Modern C++ +// | | |__ | | | | | | version 3.11.3 +// |_____|_____|_____|_|___| https://github.com/nlohmann/json +// +// SPDX-FileCopyrightText: 2013 - 2024 Niels Lohmann +// SPDX-FileCopyrightText: 2018 The Abseil Authors +// SPDX-License-Identifier: MIT + + + +#include // array +#include // size_t +#include // conditional, enable_if, false_type, integral_constant, is_constructible, is_integral, is_same, remove_cv, remove_reference, true_type +#include // index_sequence, make_index_sequence, index_sequence_for + +// #include + + +NLOHMANN_JSON_NAMESPACE_BEGIN +namespace detail +{ + +template +using uncvref_t = typename std::remove_cv::type>::type; + +#ifdef JSON_HAS_CPP_14 + +// the following utilities are natively available in C++14 +using std::enable_if_t; +using std::index_sequence; +using std::make_index_sequence; +using std::index_sequence_for; + +#else + +// alias templates to reduce boilerplate +template +using enable_if_t = typename std::enable_if::type; + +// The following code is taken from https://github.com/abseil/abseil-cpp/blob/10cb35e459f5ecca5b2ff107635da0bfa41011b4/absl/utility/utility.h +// which is part of Google Abseil (https://github.com/abseil/abseil-cpp), licensed under the Apache License 2.0. + +//// START OF CODE FROM GOOGLE ABSEIL + +// integer_sequence +// +// Class template representing a compile-time integer sequence. An instantiation +// of `integer_sequence` has a sequence of integers encoded in its +// type through its template arguments (which is a common need when +// working with C++11 variadic templates). `absl::integer_sequence` is designed +// to be a drop-in replacement for C++14's `std::integer_sequence`. +// +// Example: +// +// template< class T, T... Ints > +// void user_function(integer_sequence); +// +// int main() +// { +// // user_function's `T` will be deduced to `int` and `Ints...` +// // will be deduced to `0, 1, 2, 3, 4`. +// user_function(make_integer_sequence()); +// } +template +struct integer_sequence +{ + using value_type = T; + static constexpr std::size_t size() noexcept + { + return sizeof...(Ints); + } +}; + +// index_sequence +// +// A helper template for an `integer_sequence` of `size_t`, +// `absl::index_sequence` is designed to be a drop-in replacement for C++14's +// `std::index_sequence`. +template +using index_sequence = integer_sequence; + +namespace utility_internal +{ + +template +struct Extend; + +// Note that SeqSize == sizeof...(Ints). It's passed explicitly for efficiency. +template +struct Extend, SeqSize, 0> +{ + using type = integer_sequence < T, Ints..., (Ints + SeqSize)... >; +}; + +template +struct Extend, SeqSize, 1> +{ + using type = integer_sequence < T, Ints..., (Ints + SeqSize)..., 2 * SeqSize >; +}; + +// Recursion helper for 'make_integer_sequence'. +// 'Gen::type' is an alias for 'integer_sequence'. +template +struct Gen +{ + using type = + typename Extend < typename Gen < T, N / 2 >::type, N / 2, N % 2 >::type; +}; + +template +struct Gen +{ + using type = integer_sequence; +}; + +} // namespace utility_internal + +// Compile-time sequences of integers + +// make_integer_sequence +// +// This template alias is equivalent to +// `integer_sequence`, and is designed to be a drop-in +// replacement for C++14's `std::make_integer_sequence`. +template +using make_integer_sequence = typename utility_internal::Gen::type; + +// make_index_sequence +// +// This template alias is equivalent to `index_sequence<0, 1, ..., N-1>`, +// and is designed to be a drop-in replacement for C++14's +// `std::make_index_sequence`. +template +using make_index_sequence = make_integer_sequence; + +// index_sequence_for +// +// Converts a typename pack into an index sequence of the same length, and +// is designed to be a drop-in replacement for C++14's +// `std::index_sequence_for()` +template +using index_sequence_for = make_index_sequence; + +//// END OF CODE FROM GOOGLE ABSEIL + +#endif + +// dispatch utility (taken from ranges-v3) +template struct priority_tag : priority_tag < N - 1 > {}; +template<> struct priority_tag<0> {}; + +// taken from ranges-v3 +template +struct static_const +{ + static JSON_INLINE_VARIABLE constexpr T value{}; +}; + +#ifndef JSON_HAS_CPP_17 + template + constexpr T static_const::value; +#endif + +template +constexpr std::array make_array(Args&& ... args) +{ + return std::array {{static_cast(std::forward(args))...}}; +} + +} // namespace detail +NLOHMANN_JSON_NAMESPACE_END + +// #include +// __ _____ _____ _____ +// __| | __| | | | JSON for Modern C++ +// | | |__ | | | | | | version 3.11.3 +// |_____|_____|_____|_|___| https://github.com/nlohmann/json +// +// SPDX-FileCopyrightText: 2013 - 2024 Niels Lohmann +// SPDX-License-Identifier: MIT + + + +#include // numeric_limits +#include // char_traits +#include // tuple +#include // false_type, is_constructible, is_integral, is_same, true_type +#include // declval + +// #include +// __ _____ _____ _____ +// __| | __| | | | JSON for Modern C++ +// | | |__ | | | | | | version 3.11.3 +// |_____|_____|_____|_|___| https://github.com/nlohmann/json +// +// SPDX-FileCopyrightText: 2013 - 2024 Niels Lohmann +// SPDX-License-Identifier: MIT + + + +#include // random_access_iterator_tag + +// #include + +// #include + +// #include + + +NLOHMANN_JSON_NAMESPACE_BEGIN +namespace detail +{ + +template +struct iterator_types {}; + +template +struct iterator_types < + It, + void_t> +{ + using difference_type = typename It::difference_type; + using value_type = typename It::value_type; + using pointer = typename It::pointer; + using reference = typename It::reference; + using iterator_category = typename It::iterator_category; +}; + +// This is required as some compilers implement std::iterator_traits in a way that +// doesn't work with SFINAE. See https://github.com/nlohmann/json/issues/1341. +template +struct iterator_traits +{ +}; + +template +struct iterator_traits < T, enable_if_t < !std::is_pointer::value >> + : iterator_types +{ +}; + +template +struct iterator_traits::value>> +{ + using iterator_category = std::random_access_iterator_tag; + using value_type = T; + using difference_type = ptrdiff_t; + using pointer = T*; + using reference = T&; +}; + +} // namespace detail +NLOHMANN_JSON_NAMESPACE_END + +// #include + +// #include +// __ _____ _____ _____ +// __| | __| | | | JSON for Modern C++ +// | | |__ | | | | | | version 3.11.3 +// |_____|_____|_____|_|___| https://github.com/nlohmann/json +// +// SPDX-FileCopyrightText: 2013 - 2024 Niels Lohmann +// SPDX-License-Identifier: MIT + + + +// #include + + +NLOHMANN_JSON_NAMESPACE_BEGIN + +NLOHMANN_CAN_CALL_STD_FUNC_IMPL(begin); + +NLOHMANN_JSON_NAMESPACE_END + +// #include +// __ _____ _____ _____ +// __| | __| | | | JSON for Modern C++ +// | | |__ | | | | | | version 3.11.3 +// |_____|_____|_____|_|___| https://github.com/nlohmann/json +// +// SPDX-FileCopyrightText: 2013 - 2024 Niels Lohmann +// SPDX-License-Identifier: MIT + + + +// #include + + +NLOHMANN_JSON_NAMESPACE_BEGIN + +NLOHMANN_CAN_CALL_STD_FUNC_IMPL(end); + +NLOHMANN_JSON_NAMESPACE_END + +// #include + +// #include + +// #include +// __ _____ _____ _____ +// __| | __| | | | JSON for Modern C++ +// | | |__ | | | | | | version 3.11.3 +// |_____|_____|_____|_|___| https://github.com/nlohmann/json +// +// SPDX-FileCopyrightText: 2013 - 2024 Niels Lohmann +// SPDX-License-Identifier: MIT + +#ifndef INCLUDE_NLOHMANN_JSON_FWD_HPP_ + #define INCLUDE_NLOHMANN_JSON_FWD_HPP_ + + #include // int64_t, uint64_t + #include // map + #include // allocator + #include // string + #include // vector + + // #include + + + /*! + @brief namespace for Niels Lohmann + @see https://github.com/nlohmann + @since version 1.0.0 + */ + NLOHMANN_JSON_NAMESPACE_BEGIN + + /*! + @brief default JSONSerializer template argument + + This serializer ignores the template arguments and uses ADL + ([argument-dependent lookup](https://en.cppreference.com/w/cpp/language/adl)) + for serialization. + */ + template + struct adl_serializer; + + /// a class to store JSON values + /// @sa https://json.nlohmann.me/api/basic_json/ + template class ObjectType = + std::map, + template class ArrayType = std::vector, + class StringType = std::string, class BooleanType = bool, + class NumberIntegerType = std::int64_t, + class NumberUnsignedType = std::uint64_t, + class NumberFloatType = double, + template class AllocatorType = std::allocator, + template class JSONSerializer = + adl_serializer, + class BinaryType = std::vector, // cppcheck-suppress syntaxError + class CustomBaseClass = void> + class basic_json; + + /// @brief JSON Pointer defines a string syntax for identifying a specific value within a JSON document + /// @sa https://json.nlohmann.me/api/json_pointer/ + template + class json_pointer; + + /*! + @brief default specialization + @sa https://json.nlohmann.me/api/json/ + */ + using json = basic_json<>; + + /// @brief a minimal map-like container that preserves insertion order + /// @sa https://json.nlohmann.me/api/ordered_map/ + template + struct ordered_map; + + /// @brief specialization that maintains the insertion order of object keys + /// @sa https://json.nlohmann.me/api/ordered_json/ + using ordered_json = basic_json; + + NLOHMANN_JSON_NAMESPACE_END + +#endif // INCLUDE_NLOHMANN_JSON_FWD_HPP_ + + +NLOHMANN_JSON_NAMESPACE_BEGIN +/*! +@brief detail namespace with internal helper functions + +This namespace collects functions that should not be exposed, +implementations of some @ref basic_json methods, and meta-programming helpers. + +@since version 2.1.0 +*/ +namespace detail +{ + +///////////// +// helpers // +///////////// + +// Note to maintainers: +// +// Every trait in this file expects a non CV-qualified type. +// The only exceptions are in the 'aliases for detected' section +// (i.e. those of the form: decltype(T::member_function(std::declval()))) +// +// In this case, T has to be properly CV-qualified to constraint the function arguments +// (e.g. to_json(BasicJsonType&, const T&)) + +template struct is_basic_json : std::false_type {}; + +NLOHMANN_BASIC_JSON_TPL_DECLARATION +struct is_basic_json : std::true_type {}; + +// used by exceptions create() member functions +// true_type for pointer to possibly cv-qualified basic_json or std::nullptr_t +// false_type otherwise +template +struct is_basic_json_context : + std::integral_constant < bool, + is_basic_json::type>::type>::value + || std::is_same::value > +{}; + +////////////////////// +// json_ref helpers // +////////////////////// + +template +class json_ref; + +template +struct is_json_ref : std::false_type {}; + +template +struct is_json_ref> : std::true_type {}; + +////////////////////////// +// aliases for detected // +////////////////////////// + +template +using mapped_type_t = typename T::mapped_type; + +template +using key_type_t = typename T::key_type; + +template +using value_type_t = typename T::value_type; + +template +using difference_type_t = typename T::difference_type; + +template +using pointer_t = typename T::pointer; + +template +using reference_t = typename T::reference; + +template +using iterator_category_t = typename T::iterator_category; + +template +using to_json_function = decltype(T::to_json(std::declval()...)); + +template +using from_json_function = decltype(T::from_json(std::declval()...)); + +template +using get_template_function = decltype(std::declval().template get()); + +// trait checking if JSONSerializer::from_json(json const&, udt&) exists +template +struct has_from_json : std::false_type {}; + +// trait checking if j.get is valid +// use this trait instead of std::is_constructible or std::is_convertible, +// both rely on, or make use of implicit conversions, and thus fail when T +// has several constructors/operator= (see https://github.com/nlohmann/json/issues/958) +template +struct is_getable +{ + static constexpr bool value = is_detected::value; +}; + +template +struct has_from_json < BasicJsonType, T, enable_if_t < !is_basic_json::value >> +{ + using serializer = typename BasicJsonType::template json_serializer; + + static constexpr bool value = + is_detected_exact::value; +}; + +// This trait checks if JSONSerializer::from_json(json const&) exists +// this overload is used for non-default-constructible user-defined-types +template +struct has_non_default_from_json : std::false_type {}; + +template +struct has_non_default_from_json < BasicJsonType, T, enable_if_t < !is_basic_json::value >> +{ + using serializer = typename BasicJsonType::template json_serializer; + + static constexpr bool value = + is_detected_exact::value; +}; + +// This trait checks if BasicJsonType::json_serializer::to_json exists +// Do not evaluate the trait when T is a basic_json type, to avoid template instantiation infinite recursion. +template +struct has_to_json : std::false_type {}; + +template +struct has_to_json < BasicJsonType, T, enable_if_t < !is_basic_json::value >> +{ + using serializer = typename BasicJsonType::template json_serializer; + + static constexpr bool value = + is_detected_exact::value; +}; + +template +using detect_key_compare = typename T::key_compare; + +template +struct has_key_compare : std::integral_constant::value> {}; + +// obtains the actual object key comparator +template +struct actual_object_comparator +{ + using object_t = typename BasicJsonType::object_t; + using object_comparator_t = typename BasicJsonType::default_object_comparator_t; + using type = typename std::conditional < has_key_compare::value, + typename object_t::key_compare, object_comparator_t>::type; +}; + +template +using actual_object_comparator_t = typename actual_object_comparator::type; + +///////////////// +// char_traits // +///////////////// + +// Primary template of char_traits calls std char_traits +template +struct char_traits : std::char_traits +{}; + +// Explicitly define char traits for unsigned char since it is not standard +template<> +struct char_traits : std::char_traits +{ + using char_type = unsigned char; + using int_type = uint64_t; + + // Redefine to_int_type function + static int_type to_int_type(char_type c) noexcept + { + return static_cast(c); + } + + static char_type to_char_type(int_type i) noexcept + { + return static_cast(i); + } + + static constexpr int_type eof() noexcept + { + return static_cast(std::char_traits::eof()); + } +}; + +// Explicitly define char traits for signed char since it is not standard +template<> +struct char_traits : std::char_traits +{ + using char_type = signed char; + using int_type = uint64_t; + + // Redefine to_int_type function + static int_type to_int_type(char_type c) noexcept + { + return static_cast(c); + } + + static char_type to_char_type(int_type i) noexcept + { + return static_cast(i); + } + + static constexpr int_type eof() noexcept + { + return static_cast(std::char_traits::eof()); + } +}; + +/////////////////// +// is_ functions // +/////////////////// + +// https://en.cppreference.com/w/cpp/types/conjunction +template struct conjunction : std::true_type { }; +template struct conjunction : B { }; +template +struct conjunction +: std::conditional(B::value), conjunction, B>::type {}; + +// https://en.cppreference.com/w/cpp/types/negation +template struct negation : std::integral_constant < bool, !B::value > { }; + +// Reimplementation of is_constructible and is_default_constructible, due to them being broken for +// std::pair and std::tuple until LWG 2367 fix (see https://cplusplus.github.io/LWG/lwg-defects.html#2367). +// This causes compile errors in e.g. clang 3.5 or gcc 4.9. +template +struct is_default_constructible : std::is_default_constructible {}; + +template +struct is_default_constructible> + : conjunction, is_default_constructible> {}; + +template +struct is_default_constructible> + : conjunction, is_default_constructible> {}; + +template +struct is_default_constructible> + : conjunction...> {}; + +template +struct is_default_constructible> + : conjunction...> {}; + +template +struct is_constructible : std::is_constructible {}; + +template +struct is_constructible> : is_default_constructible> {}; + +template +struct is_constructible> : is_default_constructible> {}; + +template +struct is_constructible> : is_default_constructible> {}; + +template +struct is_constructible> : is_default_constructible> {}; + +template +struct is_iterator_traits : std::false_type {}; + +template +struct is_iterator_traits> +{ + private: + using traits = iterator_traits; + + public: + static constexpr auto value = + is_detected::value && + is_detected::value && + is_detected::value && + is_detected::value && + is_detected::value; +}; + +template +struct is_range +{ + private: + using t_ref = typename std::add_lvalue_reference::type; + + using iterator = detected_t; + using sentinel = detected_t; + + // to be 100% correct, it should use https://en.cppreference.com/w/cpp/iterator/input_or_output_iterator + // and https://en.cppreference.com/w/cpp/iterator/sentinel_for + // but reimplementing these would be too much work, as a lot of other concepts are used underneath + static constexpr auto is_iterator_begin = + is_iterator_traits>::value; + + public: + static constexpr bool value = !std::is_same::value && !std::is_same::value && is_iterator_begin; +}; + +template +using iterator_t = enable_if_t::value, result_of_begin())>>; + +template +using range_value_t = value_type_t>>; + +// The following implementation of is_complete_type is taken from +// https://blogs.msdn.microsoft.com/vcblog/2015/12/02/partial-support-for-expression-sfinae-in-vs-2015-update-1/ +// and is written by Xiang Fan who agreed to using it in this library. + +template +struct is_complete_type : std::false_type {}; + +template +struct is_complete_type : std::true_type {}; + +template +struct is_compatible_object_type_impl : std::false_type {}; + +template +struct is_compatible_object_type_impl < + BasicJsonType, CompatibleObjectType, + enable_if_t < is_detected::value&& + is_detected::value >> +{ + using object_t = typename BasicJsonType::object_t; + + // macOS's is_constructible does not play well with nonesuch... + static constexpr bool value = + is_constructible::value && + is_constructible::value; +}; + +template +struct is_compatible_object_type + : is_compatible_object_type_impl {}; + +template +struct is_constructible_object_type_impl : std::false_type {}; + +template +struct is_constructible_object_type_impl < + BasicJsonType, ConstructibleObjectType, + enable_if_t < is_detected::value&& + is_detected::value >> +{ + using object_t = typename BasicJsonType::object_t; + + static constexpr bool value = + (is_default_constructible::value && + (std::is_move_assignable::value || + std::is_copy_assignable::value) && + (is_constructible::value && + std::is_same < + typename object_t::mapped_type, + typename ConstructibleObjectType::mapped_type >::value)) || + (has_from_json::value || + has_non_default_from_json < + BasicJsonType, + typename ConstructibleObjectType::mapped_type >::value); +}; + +template +struct is_constructible_object_type + : is_constructible_object_type_impl {}; + +template +struct is_compatible_string_type +{ + static constexpr auto value = + is_constructible::value; +}; + +template +struct is_constructible_string_type +{ + // launder type through decltype() to fix compilation failure on ICPC +#ifdef __INTEL_COMPILER + using laundered_type = decltype(std::declval()); +#else + using laundered_type = ConstructibleStringType; +#endif + + static constexpr auto value = + conjunction < + is_constructible, + is_detected_exact>::value; +}; + +template +struct is_compatible_array_type_impl : std::false_type {}; + +template +struct is_compatible_array_type_impl < + BasicJsonType, CompatibleArrayType, + enable_if_t < + is_detected::value&& + is_iterator_traits>>::value&& +// special case for types like std::filesystem::path whose iterator's value_type are themselves +// c.f. https://github.com/nlohmann/json/pull/3073 + !std::is_same>::value >> +{ + static constexpr bool value = + is_constructible>::value; +}; + +template +struct is_compatible_array_type + : is_compatible_array_type_impl {}; + +template +struct is_constructible_array_type_impl : std::false_type {}; + +template +struct is_constructible_array_type_impl < + BasicJsonType, ConstructibleArrayType, + enable_if_t::value >> + : std::true_type {}; + +template +struct is_constructible_array_type_impl < + BasicJsonType, ConstructibleArrayType, + enable_if_t < !std::is_same::value&& + !is_compatible_string_type::value&& + is_default_constructible::value&& +(std::is_move_assignable::value || + std::is_copy_assignable::value)&& +is_detected::value&& +is_iterator_traits>>::value&& +is_detected::value&& +// special case for types like std::filesystem::path whose iterator's value_type are themselves +// c.f. https://github.com/nlohmann/json/pull/3073 +!std::is_same>::value&& + is_complete_type < + detected_t>::value >> +{ + using value_type = range_value_t; + + static constexpr bool value = + std::is_same::value || + has_from_json::value || + has_non_default_from_json < + BasicJsonType, + value_type >::value; +}; + +template +struct is_constructible_array_type + : is_constructible_array_type_impl {}; + +template +struct is_compatible_integer_type_impl : std::false_type {}; + +template +struct is_compatible_integer_type_impl < + RealIntegerType, CompatibleNumberIntegerType, + enable_if_t < std::is_integral::value&& + std::is_integral::value&& + !std::is_same::value >> +{ + // is there an assert somewhere on overflows? + using RealLimits = std::numeric_limits; + using CompatibleLimits = std::numeric_limits; + + static constexpr auto value = + is_constructible::value && + CompatibleLimits::is_integer && + RealLimits::is_signed == CompatibleLimits::is_signed; +}; + +template +struct is_compatible_integer_type + : is_compatible_integer_type_impl {}; + +template +struct is_compatible_type_impl: std::false_type {}; + +template +struct is_compatible_type_impl < + BasicJsonType, CompatibleType, + enable_if_t::value >> +{ + static constexpr bool value = + has_to_json::value; +}; + +template +struct is_compatible_type + : is_compatible_type_impl {}; + +template +struct is_constructible_tuple : std::false_type {}; + +template +struct is_constructible_tuple> : conjunction...> {}; + +template +struct is_json_iterator_of : std::false_type {}; + +template +struct is_json_iterator_of : std::true_type {}; + +template +struct is_json_iterator_of : std::true_type +{}; + +// checks if a given type T is a template specialization of Primary +template