Pros of Unity.Mathematics

• Designed specifically for Unity, ensuring seamless integration with the game engine
• Utilizes SIMD intrinsics for improved performance on supported platforms
• Offers a more comprehensive set of mathematical functions tailored for game development

Cons of Unity.Mathematics

• Limited to C# and Unity ecosystem, reducing portability to other platforms
• May have a steeper learning curve for developers not familiar with Unity's conventions

Code Comparison

MathFu (C++):

vec3 result = vec3::CrossProduct(vec1, vec2);
float dot = vec1.DotProduct(vec2);

Unity.Mathematics (C#):

float3 result = math.cross(vec1, vec2);
float dot = math.dot(vec1, vec2);

Both libraries provide similar functionality, but Unity.Mathematics uses a more functional approach with static methods, while MathFu uses object-oriented member functions.

MathFu is written in C++ and focuses on being lightweight and portable, making it suitable for various platforms and projects. Unity.Mathematics, on the other hand, is tailored specifically for Unity development in C#, offering optimizations and features that align closely with Unity's ecosystem.

Pros of GLM

• More comprehensive, supporting a wider range of mathematical operations and types
• Better documentation and examples
• Closer adherence to GLSL syntax, making it easier for OpenGL developers

Cons of GLM

• Larger codebase, potentially leading to longer compile times
• Header-only library, which may increase build times for large projects
• Steeper learning curve due to its extensive feature set

Code Comparison

MathFu:

#include "mathfu/vector.h"
using namespace mathfu;
Vector<float, 3> v1(1.0f, 2.0f, 3.0f);
Vector<float, 3> v2(4.0f, 5.0f, 6.0f);
Vector<float, 3> result = v1 + v2;

GLM:

#include <glm/glm.hpp>
glm::vec3 v1(1.0f, 2.0f, 3.0f);
glm::vec3 v2(4.0f, 5.0f, 6.0f);
glm::vec3 result = v1 + v2;

Both libraries provide similar functionality for basic vector operations, but GLM offers a syntax closer to GLSL. MathFu uses templates for vector dimensions, while GLM provides specific types like vec3. GLM's extensive feature set and GLSL-like syntax make it popular among graphics programmers, while MathFu's simplicity and performance focus appeal to game developers and other performance-critical applications.

Pros of Bullet3

• Comprehensive physics simulation library with advanced features
• Active development and large community support
• Extensive documentation and examples

Cons of Bullet3

• Steeper learning curve due to complexity
• Larger codebase and potentially higher resource usage
• May be overkill for simple math operations

Code Comparison

MathFu (Vector3 addition):

Vector<float, 3> a(1, 2, 3);
Vector<float, 3> b(4, 5, 6);
Vector<float, 3> result = a + b;

Bullet3 (Vector3 addition):

btVector3 a(1, 2, 3);
btVector3 b(4, 5, 6);
btVector3 result = a + b;

Summary

MathFu is a lightweight math library focused on game development and computer graphics, while Bullet3 is a full-featured physics engine. MathFu is simpler and more suitable for basic math operations, whereas Bullet3 offers advanced physics simulation capabilities at the cost of increased complexity. The choice between the two depends on the specific requirements of your project, with MathFu being ideal for simple math tasks and Bullet3 better suited for complex physics simulations.

Pros of DirectXMath

• Optimized for DirectX and Windows platforms
• Extensive documentation and support from Microsoft
• Wider range of mathematical functions and utilities

Cons of DirectXMath

• Platform-specific (primarily for Windows)
• Steeper learning curve due to its comprehensive nature
• Less portable compared to MathFu

Code Comparison

MathFu:

#include "mathfu/vector.h"
using namespace mathfu;
Vector<float, 3> v1(1.0f, 2.0f, 3.0f);
Vector<float, 3> v2(4.0f, 5.0f, 6.0f);
Vector<float, 3> result = v1 + v2;

DirectXMath:

#include <DirectXMath.h>
using namespace DirectX;
XMVECTOR v1 = XMVectorSet(1.0f, 2.0f, 3.0f, 0.0f);
XMVECTOR v2 = XMVectorSet(4.0f, 5.0f, 6.0f, 0.0f);
XMVECTOR result = XMVectorAdd(v1, v2);

Both libraries provide efficient vector math operations, but MathFu offers a more straightforward syntax with operator overloading. DirectXMath uses SIMD-optimized functions, which may provide better performance on supported hardware but requires explicit function calls for operations.

Pros of fmt

• More active development with frequent updates and releases
• Broader functionality, focusing on string formatting and I/O operations
• Extensive documentation and examples

Cons of fmt

• Larger codebase and potentially higher memory footprint
• May have a steeper learning curve for basic usage

Code Comparison

fmt:

#include <fmt/core.h>

std::string result = fmt::format("Hello, {}!", "world");
fmt::print("The answer is {}.", 42);

MathFu:

#include "mathfu/vector.h"

mathfu::Vector<float, 3> vec(1.0f, 2.0f, 3.0f);
float length = vec.Length();

Key Differences

• MathFu focuses on mathematical operations and linear algebra, while fmt specializes in string formatting and I/O
• MathFu is tailored for game development and 3D graphics, whereas fmt has broader applications in general-purpose programming
• fmt offers more flexibility in string manipulation, while MathFu provides optimized math operations

Use Cases

• Choose MathFu for projects requiring efficient vector and matrix calculations, especially in game development
• Opt for fmt when working with string formatting, logging, or general I/O operations in C++ applications

Community and Support

• fmt has a larger community and more frequent updates
• MathFu, being a Google project, has strong backing but less frequent updates