namespace NumSharp

{

public partial class NDArray

{

/// <summary>

/// Dot product of two arrays. See remarks.

/// </summary>

/// <param name="b">Rhs, Second argument.</param>

/// <returns>Returns the dot product of a and b. If a and b are both scalars or both 1-D arrays then a scalar is returned; otherwise an array is returned. If out is given, then it is returned.</returns>

/// <remarks>

/// https://docs.scipy.org/doc/numpy/reference/generated/numpy.dot.html<br></br>

/// Specifically,<br></br>

/// - If both a and b are 1-D arrays, it is inner product of vectors (without complex conjugation).<br></br>

/// - If both a and b are 2-D arrays, it is matrix multiplication, but using matmul or a @ b is preferred.<br></br>

/// - If either a or b is 0-D(scalar), it is equivalent to multiply and using numpy.multiply(a, b) or a* b is preferred.<br></br>

/// - If a is an N-D array and b is a 1-D array, it is a sum product over the last axis of a and b.<br></br>

/// - If a is an N-D array and b is an M-D array(where M>=2), it is a sum product over the last axis of a and the second-to-last axis of b:<br></br>

/// dot(a, b)[i,j,k,m] = sum(a[i,j,:] * b[k,:,m])

/// </remarks>

public NDArray dot(in NDArray b)

=> TensorEngine.Dot(this, b);

}

}