rssn 0.2.9

A comprehensive scientific computing library for Rust, aiming for feature parity with NumPy and SymPy.
Documentation 
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use crate::ffi_apis::common::BincodeBuffer;
use crate::ffi_apis::common::from_bincode_buffer;
use crate::ffi_apis::common::to_bincode_buffer;
use crate::symbolic::tensor::Tensor;

/// Performs tensor addition.
/// Takes two bincode-serialized `Tensor` objects as input,
/// and returns a bincode-serialized `Tensor` representing their sum.
#[unsafe(no_mangle)]
pub extern "C" fn rssn_bincode_tensor_add(
    t1_buf: BincodeBuffer,
    t2_buf: BincodeBuffer,
) -> BincodeBuffer {
    let t1: Option<Tensor> = from_bincode_buffer(&t1_buf);

    let t2: Option<Tensor> = from_bincode_buffer(&t2_buf);

    match (t1, t2) {
        | (Some(tensor1), Some(tensor2)) => {
            match tensor1.add(&tensor2) {
                | Ok(result) => to_bincode_buffer(&result),
                | Err(_) => BincodeBuffer::empty(),
            }
        },
        | _ => BincodeBuffer::empty(),
    }
}

/// Performs scalar multiplication on a tensor.
/// Takes a bincode-serialized `Tensor` and a bincode-serialized `Expr` (scalar).
/// Returns a bincode-serialized `Tensor` representing the result.
#[unsafe(no_mangle)]
pub extern "C" fn rssn_bincode_tensor_scalar_mul(
    t_buf: BincodeBuffer,
    scalar_buf: BincodeBuffer,
) -> BincodeBuffer {
    let t: Option<Tensor> = from_bincode_buffer(&t_buf);

    let scalar: Option<crate::symbolic::core::Expr> = from_bincode_buffer(&scalar_buf);

    match (t, scalar) {
        | (Some(tensor), Some(s)) => {
            match tensor.scalar_mul(&s) {
                | Ok(result) => to_bincode_buffer(&result),
                | Err(_) => BincodeBuffer::empty(),
            }
        },
        | _ => BincodeBuffer::empty(),
    }
}

/// Computes the outer product of two tensors.
/// Takes two bincode-serialized `Tensor` objects as input,
/// and returns a bincode-serialized `Tensor` representing their outer product.
#[unsafe(no_mangle)]
pub extern "C" fn rssn_bincode_tensor_outer_product(
    t1_buf: BincodeBuffer,
    t2_buf: BincodeBuffer,
) -> BincodeBuffer {
    let t1: Option<Tensor> = from_bincode_buffer(&t1_buf);

    let t2: Option<Tensor> = from_bincode_buffer(&t2_buf);

    match (t1, t2) {
        | (Some(tensor1), Some(tensor2)) => {
            match tensor1.outer_product(&tensor2) {
                | Ok(result) => to_bincode_buffer(&result),
                | Err(_) => BincodeBuffer::empty(),
            }
        },
        | _ => BincodeBuffer::empty(),
    }
}