public static ndarray as_strided(ndarray x, object oshape = null, object ostrides = null, bool subok = false, bool writeable = false)
{
npy_intp[] shape = null;
npy_intp[] strides = null;
if (oshape != null)
{
shape newshape = NumpyExtensions.ConvertTupleToShape(oshape);
if (newshape == null)
{
throw new Exception("Unable to convert shape object");
}
shape = newshape.iDims;
}
if (ostrides != null)
{
shape newstrides = NumpyExtensions.ConvertTupleToShape(ostrides);
if (newstrides == null)
{
throw new Exception("Unable to convert strides object");
}
strides = newstrides.iDims;
}
return(as_strided(x, shape, strides, subok, writeable));
}
private static ndarray _broadcast_to(object oarray, object oshape, bool subok, bool _readonly)
{
shape newshape = NumpyExtensions.ConvertTupleToShape(oshape);
if (newshape == null)
{
throw new Exception("Unable to convert shape object");
}
if (newshape.iDims == null || newshape.iDims.Length == 0)
{
newshape = new shape(asanyarray(oarray).shape);
}
ndarray array = np.array(asanyarray(oarray), copy: false, subok: subok);
if (array.dims == null)
{
throw new ValueError("cannot broadcast a non-scalar to a scalar array");
}
if (np.anyb(np.array(newshape.iDims) < 0))
{
throw new ValueError("all elements of broadcast shape must be non-negative");
}
var toshape = NpyCoreApi.BroadcastToShape(array, newshape.iDims, newshape.iDims.Length);
var newStrides = new npy_intp[toshape.nd_m1 + 1];
Array.Copy(toshape.strides, 0, newStrides, 0, newStrides.Length);
var result = np.as_strided(array, shape: newshape.iDims, strides: newStrides);
return(result);
}
/// <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 static ndarray reshape(this ndarray a, object oshape, NPY_ORDER order = NPY_ORDER.NPY_CORDER)
{
shape newshape = ConvertTupleToShape(oshape);
if (newshape == null)
{
throw new Exception("Unable to convert shape object");
}
return(np.reshape(a, newshape, order));
}
/// <summary>
/// returns true of the shapes are equivalent
/// </summary>
/// <param name="o2"></param>
/// <returns></returns>
public override bool Equals(object o2)
{
shape s2 = o2 as shape;
if (this.iDims.Length == s2.iDims.Length)
{
for (int i = 0; i < this.iDims.Length; i++)
{
if (this.iDims[i] != s2.iDims[i])
{
return(false);
}
}
return(true);
}
return(false);
}
public static ndarray upscale_to(ndarray a, object oshape)
{
shape newshape = NumpyExtensions.ConvertTupleToShape(oshape);
if (newshape == null)
{
throw new Exception("Unable to convert shape object");
}
if (!broadcastable(a, newshape.iDims, newshape.iDims.Length))
{
throw new Exception(string.Format("operands could not be broadcast together with shapes ({0}),({1})", a.shape.ToString(), newshape.ToString()));
}
ndarray ret = NpyCoreApi.NpyArray_UpscaleSourceArray(a, newshape);
return(ret.reshape(newshape));
}
/// <summary>
/// create a new shape, copied from existing shape
/// </summary>
/// <param name="s"></param>
public shape(shape s)
{
iDims = new npy_intp[s.iDims.Length];
Array.Copy(s.iDims, iDims, s.iDims.Length);
}
public static ndarray reshape(this ndarray a, shape newshape, NPY_ORDER order = NPY_ORDER.NPY_CORDER)
{
return(np.reshape(a, newshape, order));
}
