/// <summary>
/// An N-dimensional iterator object to index arrays.
/// </summary>
public ndindex(object oshape)
{
shape newshape = NumpyExtensions.ConvertTupleToShape(oshape);
var x = np.as_strided(np.zeros(1), shape: newshape.iDims, strides: np.zeros_like(newshape.iDims, dtype: np.intp).ToArray <npy_intp>());
core = new nditer(x);
}
public bool MoveNext()
{
if (current == null)
{
current = core;
}
return(core.MoveNext());
}
/// <summary>
/// Produce an object that mimics broadcasting.
/// </summary>
/// <param name="aobjects">Input parameters.</param>
/// <returns></returns>
public static broadcast broadcast(params object[] aobjects)
{
ndarray[] arrays = new ndarray[aobjects.Length];
for (int i = 0; i < aobjects.Length; i++)
{
arrays[i] = asanyarray(aobjects[i]);
}
var nditer = new nditer(arrays);
broadcast bcast = new broadcast(nditer);
return(bcast);
}
public broadcast(nditer iter)
{
core = iter;
}
