Beaver

Automatic Differentiation system. (brewing...🍵)

Beaver is a library that is capable of computing derivative of given expression on fly automatically.

Build instruction.

windows (x64) 🪟

• git clone https://github.com/coderboyisongithub/Beaver.git
• cd Beaver
• mkdir build; cd build
• cmake .. -DCMAKE_BUILD_TYPE=Release will have optimization or cmake .. -DCMAKE_BUILD_TYPE=Debug

Linux (x64/clang compiler only) 💽

Getting your system ready first.

sudo apt install cmake zip wget curl ninja-build build-essential pkg-config autoconf

sudo apt install clang libc++-dev libc++abi-dev

Then

• git clone https://github.com/coderboyisongithub/Beaver.git
• cd Beaver
• mkdir build; cd build
• export CC=clang
• export CXX=clang++
• cmake .. -DCMAKE_BUILD_TYPE=Release will have optimization or cmake .. -DCMAKE_BUILD_TYPE=Debug

Example

This example will be compiled when the build is complete and program will compute the derivative and print the result.

int main()
{
    
   // Example: derivative of sin(x)+cos(x)
    dual x1(0.3f), x2(10.0f);
    dual res =sin(x1) + cos(x1);
    std::cout<<"at x=0.3" << "value:" << res.value << " partial:" << res.partial;
    

  // Example: obtain partial derivative for sin(x1)+cos(x2);
	variable x1(2.00), x2(5.0), x3(3.50f), x4(3.213);

	variable expression = sin(x1) + cos(x2);

	variable dx1 = expression.differentiate(x1);
	variable dx2 = expression.differentiate(x2);

	variable gradient = dx1 + dx2;


// We verify our result by evaluating: sum of partial shall be equal to gradient of expression evaluated here
std::cout << "sum of partial:" << gradient.value() << "actual gradient" << expression.partial(); 



    return 0;
}