IncliArray

Minimal N-dimensional float array library in C++.

Checkout the documentation: https://inclinedadarsh.github.io/incliarray/.

Highlights

• Tiny, readable implementation (single header + single source) focused on concepts
• Explicit shapes/strides and careful ownership rules (base vs view)
• Lightweight reverse‑mode autograd for core ops

Features

• N‑dimensional float arrays with row‑major layout
• Safe, stride‑aware indexing:
  • get(std::vector<int>), set(std::vector<int>, float)
  • Flat get(int), set(int) on contiguous, owning arrays only
• Introspection and layout helpers: metadata, isContiguous, print (data or grads)
• Initialization/fill:
  • zeros, ones, fill, fillSequential
  • randint(low, high), rand() in [0,1), rand(low, high)
• Views and materialization:
  • slice returns a detached, non‑owning view (shares data, no autograd linkage)
  • clone() creates a contiguous, owning copy (detached)
• Reshape: reshape(newShape) for contiguous, owning arrays
• Broadcasting arithmetic (array ⊕ array): +, -, /, element_wise_multiply
• Scalar arithmetic (array ⊕ scalar): + float, - float, / float, element_wise_multiply(float)
• Element‑wise power with scalar exponent: operator^(float)
• 2D matrix multiplication: operator* (no broadcasting)
• Reductions:
  • sum() reduces all elements to a 1‑element array
  • sum(axis) keeps reduced dimension as size 1, supports negative axes
• Autograd:
  • Results from core ops capture prev, op, label
  • backward() builds a topological order and accumulates gradients
  • Implemented grads for add/sub (array & scalar), div (array & scalar), element‑wise multiply (array & scalar), matrix multiply, and power (scalar exponent)
• Safety/constraints:
  • Flat indexing and reshape are allowed only on contiguous, owning arrays
  • Views are non‑owning; fill operations are disallowed on non‑owning arrays
  • Division warns on divisor 0; gradient contributions on zero divisors are skipped

Build and run examples (development flow)

mkdir build && cd build
cmake ..
make
./examples/basic_scalars

Examples are built from examples/ when BUILD_EXAMPLES is ON (default). You can also run ./examples/basic_vectors if present.

See examples/README.md for details about each example.

Install the library system‑wide

mkdir build && cd build
cmake .. -DBUILD_EXAMPLES=OFF
sudo make install

This installs headers to /usr/local/include and the library to /usr/local/lib by default.

Use in your project

With CMake

In your project's CMakeLists.txt:

find_package(NDArray REQUIRED)
add_executable(myapp myapp.cpp)
target_link_libraries(myapp PRIVATE NDArray)

Then include it in code as:

#include <NDArray.h>

With a plain compiler (no CMake)

If installed to default prefixes, this typically works:

g++ -std=c++17 myapp.cpp -lNDArray -o myapp

And in your code:

#include <NDArray.h>

If you installed to a custom prefix, add -I<include_dir> and -L<lib_dir> accordingly.

Doxygen documentation

1) Install Doxygen and graphviz:

sudo apt-get install -y doxygen graphviz

2) Generate docs:

./build-docs.sh

Open html/index.html in your browser.

Project structure

.
├── CMakeLists.txt       // Library build + install rules
├── Doxyfile             // Doxygen configuration
├── include/
│   ├── NDArray.h        // NDArray class declaration
│   └── utils.h          // Internal helpers (strides, offsets, broadcasting)
├── src/
│   ├── NDArray.cpp      // NDArray implementation
│   └── utils.cpp        // Helper implementations
├── examples/
│   ├── CMakeLists.txt   // Example build targets
│   ├── basic_scalars.cpp
│   └── basic_vectors.cpp
├── LICENSE
└── README.md

Quickstart demo

#include <NDArray.h>
#include <iostream>
 
int main() {
  NDArray A({2, 3});
  A.fillSequential();
 
  NDArray B({1, 3});
  B.ones();
 
  NDArray C = A + B;                        // broadcast add
  NDArray D = C.element_wise_multiply(2.0f);
  NDArray E = D - 3.0f;                     // scalar sub
 
  NDArray W({3, 2});
  W.randint(1, 5);
  NDArray G = A * W;                        // 2D matmul (2x3) * (3x2)
 
  NDArray S = G.sum();                      // reduce to scalar (1)
  S.backward();
 
  std::cout << "Grad A:" << std::endl;
  A.print(NDArray::PrintType::Grad);
}

Author

Built with some neovim and some maths by Adarsh Dubey.

License

MIT License. Do whatever you want, just don’t sue me.