public void FromMultiDimArray(Array dotNetArray)
{
if (dotNetArray.GetType().GetElementType().IsArray)
{
throw new Exception("Jagged arrays are not allowed here!");
}
int[] dims = new int[dotNetArray.Rank];
for (int idx = 0; idx < dims.Length; idx++)
{
dims[idx] = dotNetArray.GetLength(idx);
}
Storage = new NDStorage();
Storage.Allocate(dotNetArray.GetType().GetElementType(), new Shape(dims), 1);
Array internalStrg = Storage.GetData();
var pufferShape = new Shape(dims);
pufferShape.ChangeTensorLayout(2);
int[] idxDims = null;
object valueIdx = null;
for (int idx = 0; idx < Storage.Shape.Size; idx++)
{
idxDims = pufferShape.GetDimIndexOutShape(idx);
valueIdx = dotNetArray.GetValue(pufferShape.GetDimIndexOutShape(idx));
internalStrg.SetValue(valueIdx, Storage.Shape.GetIndexInShape(idxDims));
}
}
public void FromJaggedArray(Array dotNetArray)
{
if (!dotNetArray.GetType().GetElementType().IsArray)
{
throw new Exception("Multi dim arrays are not allowed here!");
}
List <int> dimList = new List <int>();
dimList.Add(dotNetArray.Length);
object currentArr = dotNetArray;
while (currentArr.GetType().GetElementType().IsArray)
{
Array child = (Array)((Array)currentArr).GetValue(0);
dimList.Add(child.Length);
currentArr = child;
}
Type elementType = currentArr.GetType().GetElementType();
int[] dims = dimList.ToArray();
Shape shape = new Shape(dims);
shape.ChangeTensorLayout(1);
NDArray nd = new NDArray(elementType, shape);
Array ndStrg = nd.Storage.GetData();
if (dims.Length == 1)
{
throw new NotImplementedException("FromJaggedArray dims.Length == 1");
}
else if (dims.Length == 2)
{
switch (dotNetArray)
{
case double[][] array:
for (int i = 0; i < dims[0]; i++)
{
for (int j = 0; j < dims[1]; j++)
{
nd[i, j] = array[i][j];
}
}
break;
}
}
this.Storage = nd.Storage;
}
/// <summary>
/// Clone the whole NDArray
/// internal storage is also cloned into 2nd memory area
/// </summary>
/// <returns>Cloned NDArray</returns>
public object Clone()
{
var puffer = new NDArray(this.dtype);
var shapePuffer = new Shape(this.shape);
shapePuffer.ChangeTensorLayout(this.Storage.Shape.TensorLayout);
puffer.Storage.Allocate(this.dtype, shapePuffer, this.Storage.TensorLayout);
puffer.Storage.SetData(this.Storage.CloneData());
return(puffer);
}
public void Reshape(params int[] dimensions)
{
if (_TensorLayout == 2)
{
_Shape = new Shape(dimensions);
}
else
{
ChangeTensorLayout(2);
_Shape = new Shape(dimensions);
_Shape.ChangeTensorLayout(2);
ChangeTensorLayout(1);
}
}
/// <summary>
/// Allocate memory by dtype, shape, tensororder (default column wise)
/// </summary>
/// <param name="dtype">storage data type</param>
/// <param name="shape">storage data shape</param>
/// <param name="tensorOrder">row or column wise</param>
public void Allocate(Type dtype, Shape shape, int tensorOrder = 1)
{
_DType = dtype;
_Shape = shape;
_Shape.ChangeTensorLayout(tensorOrder);
int elementNumber = 1;
for (int idx = 0; idx < shape.Dimensions.Length; idx++)
{
elementNumber *= shape.Dimensions[idx];
}
_values = Array.CreateInstance(dtype, elementNumber);
_TensorLayout = tensorOrder;
}
public void FromJaggedArray(Array dotNetArray)
{
if (!dotNetArray.GetType().GetElementType().IsArray)
{
throw new Exception("Multi dim arrays are not allowed here!");
}
List <int> dimList = new List <int>();
dimList.Add(dotNetArray.Length);
object currentArr = dotNetArray;
while (currentArr.GetType().GetElementType().IsArray)
{
Array child = (Array)((Array)currentArr).GetValue(0);
dimList.Add(child.Length);
currentArr = child;
}
Type elementType = currentArr.GetType().GetElementType();
int[] dims = dimList.ToArray();
Shape shape = new Shape(dims);
shape.ChangeTensorLayout(1);
NDArray nd = new NDArray(elementType, shape);
Array ndStrg = nd.Storage.GetData();
for (int idx = 0; idx < shape.Size; idx++)
{
int[] indexes = shape.GetDimIndexOutShape(idx);
Array puffer = (Array)dotNetArray.GetValue(indexes[0]);
for (int jdx = 1; jdx < indexes.Length - 1; jdx++)
{
puffer = (Array)puffer.GetValue(indexes[jdx]);
}
ndStrg.SetValue(puffer.GetValue(indexes[indexes.Length - 1]), nd.Storage.Shape.GetIndexInShape(indexes));
}
this.Storage = nd.Storage;
}
public Array ToMuliDimArray <T>()
{
Array dotNetArray = Array.CreateInstance(typeof(T), this.shape);
var pufferShape = new Shape(shape);
pufferShape.ChangeTensorLayout(2);
int[] indexes = null;
object idxValue = null;
T[] array = Storage.GetData <T>();
for (int idx = 0; idx < this.size; idx++)
{
indexes = pufferShape.GetDimIndexOutShape(idx);
idxValue = array[Storage.Shape.GetIndexInShape(indexes)];
dotNetArray.SetValue(idxValue, indexes);
}
return(dotNetArray);
}
protected void _ChangeColumnToRowLayout()
{
if (_Shape.NDim == 1)
{
}
else if (_Shape.NDim == 2)
{
var puffer = Array.CreateInstance(_values.GetType().GetElementType(), _values.Length);
var pufferShape = new Shape(_Shape.Dimensions);
pufferShape.ChangeTensorLayout(1);
for (int idx = 0; idx < _values.Length; idx++)
{
puffer.SetValue(_values.GetValue(idx), pufferShape.GetIndexInShape(Shape.GetDimIndexOutShape(idx)));
}
_values = puffer;
}
else
{
var puffer = Array.CreateInstance(_values.GetType().GetElementType(), _values.Length);
var pufferShape = new Shape(_Shape.Dimensions);
pufferShape.ChangeTensorLayout(1);
for (int idx = 0; idx < _values.Length; idx++)
{
puffer.SetValue(_values.GetValue(idx), pufferShape.GetIndexInShape(Shape.GetDimIndexOutShape(idx)));
}
_values = puffer;
}
_TensorLayout = 1;
Shape.ChangeTensorLayout(1);
}
public NDArray hstack <T>(params NDArray[] nps)
{
if (nps == null || nps.Length == 0)
{
throw new Exception("Input arrays can not be empty");
}
var npAll = new NDArray[nps.Length + 1];
npAll[0] = this;
for (int idx = 0; idx < nps.Length; idx++)
{
if (nps[0].Storage.Shape != nps[idx].Storage.Shape)
{
throw new Exception("Arrays mush have same shapes");
}
else
{
npAll[idx + 1] = nps[idx];
}
}
NDArray nd = new NDArray(dtype);
// easy 1D case
if (this.ndim == 1)
{
var list1D = new List <T>();
for (int idx = 0; idx < npAll.Length; idx++)
{
list1D.AddRange(npAll[idx].Storage.GetData <T>().ToList());
}
nd = np.array(list1D.ToArray(), this.dtype);
}
else
{
for (int idx = 0; idx < npAll.Length; idx++)
{
npAll[idx].Storage.ChangeTensorLayout(2);
}
int total = npAll[0].ndim == 1 ? 1 : npAll[0].shape[0];
var list = new List <T>();
for (int i = 0; i < total; i++)
{
for (int k = 0; k < npAll.Length; k++)
{
var pufferShape = new Shape(npAll[k].shape);
pufferShape.ChangeTensorLayout(this.Storage.Shape.TensorLayout);
int pageSize = npAll[k].ndim == 1 ? npAll[k].shape[0] : pufferShape.DimOffset[0];
for (int j = i * pageSize; j < (i + 1) * pageSize; j++)
{
var ele = npAll[k].Storage.GetData <T>()[j];
list.Add(ele);
}
}
}
int[] shapes = new int[npAll[0].shape.Length];
npAll[0].shape.CopyTo(shapes, 0);
if (shapes.Length == 1)
{
shapes[0] *= npAll.Length;
}
else
{
shapes[1] = npAll.Sum(x => x.shape[1]);
}
nd.Storage.Allocate(nd.Storage.DType, new Shape(shapes), 2);
nd.Storage.SetData(list.ToArray());
nd.Storage.ChangeTensorLayout(1);
}
return(nd);
}