private void PrettyPrint(StringBuilder s, bool flat = false)
{
if (Shape.Dimensions.Length == 0)
{
s.Append($"{GetValue(0)}");
return;
}
if (Shape.Dimensions.Length == 1)
{
s.Append("[");
s.Append(string.Join(", ", this.GetData().OfType <object>().Select(x => x == null ? "null" : x.ToString())));
s.Append("]");
return;
}
var last_dim = Shape.Dimensions.Last();
var slices = new Slice[Shape.Dimensions.Length];
s.Append("[");
for (int i = 0; i < last_dim; i++)
{
slices[0] = Slice.Index(i);
var n_minus_one_dim_slice = new ViewStorage(this, slices);
n_minus_one_dim_slice.PrettyPrint(s, flat);
if (i < last_dim - 1)
{
s.Append(", ");
if (!flat)
{
s.AppendLine();
}
}
}
s.Append("]");
}
private void PrettyPrint(StringBuilder s, bool flat = false)
{
if (shape.Length == 0)
{
s.Append($"{Storage.GetData().GetValue(0)}");
return;
}
if (shape.Length == 1)
{
s.Append("[");
s.Append(string.Join(", ", this.Array.OfType <object>().Select(x => x == null ? "null" : x.ToString())));
s.Append("]");
return;
}
var size = shape[0];
s.Append("[");
for (int i = 0; i < size; i++)
{
var n_minus_one_dim_slice = this[Slice.Index(i)];
n_minus_one_dim_slice.PrettyPrint(s, flat);
if (i < size - 1)
{
s.Append(", ");
if (!flat)
{
s.AppendLine();
}
}
}
s.Append("]");
}
protected void SetIndices(object[] indicesObjects, NDArray values)
{
var indicesLen = indicesObjects.Length;
if (indicesLen == 1)
{
switch (indicesObjects[0])
{
case NDArray nd:
SetIndices(this, new NDArray[] {nd}, values);
return;
case int i:
Storage.SetData(values, i);
return;
case bool boolean:
if (boolean == false)
return; //do nothing
SetData(values);
return; // np.expand_dims(this, 0); //equivalent to [np.newaxis]
case int[] coords:
SetData(values, coords);
return;
case NDArray[] nds:
this[nds] = values;
return;
case object[] objs:
this[objs] = values;
return;
case string slicesStr:
new NDArray(Storage.GetView(Slice.ParseSlices(slicesStr))).SetData(values);
return;
case null:
throw new ArgumentNullException($"The 1th dimension in given indices is null.");
//no default
}
}
int ints = 0;
int bools = 0;
for (var i = 0; i < indicesObjects.Length; i++)
{
switch (indicesObjects[i])
{
case NDArray _:
case int[] _:
goto _NDArrayFound;
case int _:
ints++;
continue;
case bool @bool:
bools++;
continue;
case string _:
case Slice _:
continue;
case null: throw new ArgumentNullException($"The {i}th dimension in given indices is null.");
default: throw new ArgumentException($"Unsupported indexing type: '{(indicesObjects[i]?.GetType()?.Name ?? "null")}'");
}
}
//handle all ints
if (ints == indicesLen)
{
Storage.SetData(values, indicesObjects.Cast<int>().ToArray());
return;
}
//handle all booleans
if (bools == indicesLen)
{
this[np.array(indicesObjects.Cast<bool>().ToArray(), false).MakeGeneric<bool>()] = values;
return;
}
Slice[] slices;
//handle regular slices
try
{
slices = indicesObjects.Select(x =>
{
switch (x)
{
case Slice o: return o;
case int o: return Slice.Index(o);
case string o: return new Slice(o);
case bool o: return o ? Slice.NewAxis : throw new NumSharpException("false bool detected"); //TODO: verify this
case IConvertible o: return Slice.Index((int)o.ToInt32(CultureInfo.InvariantCulture));
default: throw new ArgumentException($"Unsupported slice type: '{(x?.GetType()?.Name ?? "null")}'");
}
}).ToArray();
}
catch (NumSharpException e) when (e.Message.Contains("false bool detected"))
{
//handle rare case of false bool
return;
}
new NDArray(Storage.GetView(slices)).SetData(values);
//handle complex ndarrays indexing
_NDArrayFound:
var @this = this;
var indices = new List<NDArray>();
bool foundNewAxis = false;
int countNewAxes = 0;
//handle ndarray indexing
bool hasCustomExpandedSlice = false; //use for premature slicing detection
for (int i = 0; i < indicesLen; i++)
{
var idx = indicesObjects[i];
_recuse:
switch (idx)
{
case Slice o:
if (o.IsEllipsis)
{
indicesObjects = ExpandEllipsis(indicesObjects, @this.ndim).ToArray();
//TODO: i think we need to set here indicesLen = indicesObjects.Length
continue;
}
if (o.IsNewAxis)
{
//TODO: whats the approach to handling a newaxis in setter, findout.
countNewAxes++;
foundNewAxis = true;
continue;
}
hasCustomExpandedSlice = true;
indices.Add(GetIndicesFromSlice(@this.Shape.dimensions, o, i - countNewAxes));
continue;
case int o:
indices.Add(NDArray.Scalar<int>(o));
continue;
case string o:
indicesObjects[i] = idx = new Slice(o);
goto _recuse;
case bool o:
if (o)
{
indicesObjects[i] = idx = Slice.NewAxis;
goto _recuse;
}
else
return; //false bool causes nullification of return.
case IConvertible o:
indices.Add(NDArray.Scalar<int>(o.ToInt32(CultureInfo.InvariantCulture)));
continue;
case int[] o:
indices.Add(np.array(o, copy: false)); //we dont copy, pinning will be freed automatically after we done indexing.
continue;
case NDArray nd:
if (nd.typecode == NPTypeCode.Boolean)
{
//TODO: mask only specific axis??? find a unit test to check it against.
throw new Exception("if (nd.typecode == NPTypeCode.Boolean)");
}
indices.Add(nd);
continue;
default: throw new ArgumentException($"Unsupported slice type: '{(idx?.GetType()?.Name ?? "null")}'");
}
}
NDArray[] indicesArray = indices.ToArray();
//handle premature slicing when the shapes cant be broadcasted together
if (hasCustomExpandedSlice && !np.are_broadcastable(indicesArray))
{
var ndim = indicesObjects.Length;
var prematureSlices = new Slice[ndim];
var dims = @this.shape;
for (int i = 0; i < ndim; i++)
{
if (indicesObjects[i] is Slice slice)
{
prematureSlices[i] = slice;
//todo: we might need this in the future indicesObjects[i] = Slice.All;
}
else
{
prematureSlices[i] = Slice.All;
}
}
@this = @this[prematureSlices];
//updated premature axes
dims = @this.shape;
for (int i = 0; i < ndim; i++)
{
if (prematureSlices[i] != Slice.All)
{
indicesArray[i] = GetIndicesFromSlice(dims, Slice.All, i);
}
}
}
//TODO: we can use a slice as null indice instead of expanding it, then we use PrepareIndexGetters to actually simulate that.
SetIndices(@this, indicesArray, values);
//TODO: this is valid code for getter, we need to impl a similar technique before passing @this.
//if (foundNewAxis)
//{
// //TODO: This is not the behavior when setting with new axis, is it even possible?
// var targettedAxis = indices.Count - 1;
// var axisOffset = this.ndim - targettedAxis;
// var retShape = ret.Shape;
// for (int i = 0; i < indicesLen; i++)
// {
// if (!(indicesObjects[i] is Slice slc) || !slc.IsNewAxis)
// continue;
//
// var axis = Math.Max(0, Math.Min(i - axisOffset, ret.ndim));
// retShape = retShape.ExpandDimension(axis);
// }
//
// ret = ret.reshape(retShape);
//}
//
//return ret;
}
/// <summary>
/// Join a sequence of arrays along an existing axis.
/// </summary>
/// <param name="axis">The axis along which the arrays will be joined. If axis is None, arrays are flattened before use. Default is 0.</param>
/// <param name="arrays">The arrays must have the same shape, except in the dimension corresponding to axis (the first, by default).</param>
/// <returns>The concatenated array.</returns>
/// <remarks>https://docs.scipy.org/doc/numpy/reference/generated/numpy.concatenate.html</remarks>
public static NDArray concatenate(NDArray[] arrays, int axis = 0)
{
//What we do is we have the axis which is the only dimension that is allowed to be different
//We need to perform a check if the dimensions actually match.
//After we have the axis ax=1 where shape is (3,ax,3) - ax is the only dimension that can vary.
//So if we got input of (3,5,3) and (3,1,3), we create a return shape of (3,6,3).
//We perform the assignment by iterating a slice: (:,n,:) on src and dst where dst while n of dst grows as we iterate all arrays.
if (arrays == null)
{
throw new ArgumentNullException(nameof(arrays));
}
if (arrays.Length == 0)
{
throw new ArgumentException("Value cannot be an empty collection.", nameof(arrays));
}
if (arrays.Length == 1)
{
return(arrays[0]);
}
var first = arrays[0];
var firstShape = (int[])first.shape.Clone();
while (axis < 0)
{
axis = first.ndim + axis; //translate negative axis
}
int i, j;
int axisSize = 0; //accumulated shape[axis] size for return shape.
NPTypeCode retType = first.GetTypeCode;
foreach (var src in arrays)
{
//accumulate the concatenated axis
var shape = src.shape;
axisSize += shape[axis];
if (ReferenceEquals(src, first))
{
continue;
}
var srcType = src.GetTypeCode;
//resolve what the return type should be and should we perform casting.
if (first.GetTypeCode != srcType)
{
if (srcType.CompareTo(retType) == 1)
{
retType = srcType;
}
}
if (shape.Length != first.ndim)
{
throw new IncorrectShapeException("all the input arrays must have same number of dimensions.");
}
//verify the shapes are equal
for (j = 0; j < shape.Length; j++)
{
if (axis == j)
{
continue;
}
if (shape[j] != firstShape[j])
{
throw new IncorrectShapeException("all the input array dimensions except for the concatenation axis must match exactly.");
}
}
}
//prepare return shape
firstShape[axis] = axisSize;
var retShape = new Shape(firstShape);
var dst = new NDArray(retType, retShape);
var accessorDst = new Slice[retShape.NDim];
var accessorSrc = new Slice[retShape.NDim];
for (i = 0; i < accessorDst.Length; i++)
{
accessorSrc[i] = accessorDst[i] = Slice.All;
}
accessorSrc[axis] = Slice.Index(0);
accessorDst[axis] = Slice.Index(0);
foreach (var src in arrays)
{
var len = src.shape[axis];
for (i = 0; i < len; i++)
{
var writeTo = dst[accessorDst];
var writeFrom = src[accessorSrc];
MultiIterator.Assign(writeTo.Storage, writeFrom.Storage);
accessorSrc[axis]++;
accessorDst[axis]++; //increment every step
}
accessorSrc[axis] = Slice.Index(0); //reset src
}
return(dst);
}
/// <summary>
/// Get n-th dimension data
/// </summary>
/// <param name="indices">indexes</param>
/// <returns>NDArray</returns>
private NDArray GetData(params int[] indices)
{
if (indices.Length == 0)
{
return(this);
}
if (Storage.SupportsSpan)
{
Shape s1 = shape.Skip(indices.Length).ToArray();
var nd = new NDArray(dtype, s1);
//nd.Storage.Slice = new Slice($"{}");
switch (Type.GetTypeCode(dtype))
{
case TypeCode.Boolean:
nd.Array = Storage.GetSpanData <bool>(slice, indices).ToArray();
break;
case TypeCode.Byte:
nd.Array = Storage.GetSpanData <byte>(slice, indices).ToArray();
break;
case TypeCode.Int16:
nd.Array = Storage.GetSpanData <short>(slice, indices).ToArray();
break;
case TypeCode.Int32:
nd.Array = Storage.GetSpanData <int>(slice, indices).ToArray();
break;
case TypeCode.Int64:
nd.Array = Storage.GetSpanData <long>(slice, indices).ToArray();
break;
case TypeCode.Single:
nd.Array = Storage.GetSpanData <float>(slice, indices).ToArray();
break;
case TypeCode.Double:
nd.Array = Storage.GetSpanData <double>(slice, indices).ToArray();
break;
case TypeCode.Decimal:
nd.Array = Storage.GetSpanData <decimal>(slice, indices).ToArray();
break;
case TypeCode.String:
nd.Array = Storage.GetSpanData <string>(slice, indices).ToArray();
break;
default:
return(Storage.GetSpanData <NDArray>(slice, indices).ToArray()[0]);
}
return(nd);
}
if (indices.Length < Storage.Shape.NDim)
{
// a slice was requested
return(this[indices.Select(i => Slice.Index(i)).ToArray()]);
}
else if (indices.Length == Storage.Shape.NDim)
{
// a scalar was indexed
var nd = new NDArray(this.dtype, new Shape());
switch (Type.GetTypeCode(dtype))
{
case TypeCode.Boolean:
nd.Array = new [] { Storage.GetData <bool>(indices) };
break;
case TypeCode.Byte:
nd.Array = new[] { Storage.GetData <byte>(indices) };
break;
case TypeCode.Int16:
nd.Array = new[] { Storage.GetData <short>(indices) };
break;
case TypeCode.Int32:
nd.Array = new[] { Storage.GetData <int>(indices) };
break;
case TypeCode.Int64:
nd.Array = new[] { Storage.GetData <long>(indices) };
break;
case TypeCode.Single:
nd.Array = new[] { Storage.GetData <float>(indices) };
break;
case TypeCode.Double:
nd.Array = new[] { Storage.GetData <double>(indices) };
break;
case TypeCode.Decimal:
nd.Array = new[] { Storage.GetData <decimal>(indices) };
break;
case TypeCode.String:
nd.Array = new[] { Storage.GetData <string>(indices) };
break;
default:
return(Storage.GetData <NDArray>(indices));
}
return(nd);
}
else
{
throw new ArgumentException("Too many index dimensions for shape " + Storage.Shape);
}
}