private static void AssignFromSeq(IEnumerable <Object> seq, ndarray result,
int dim, long offset)
{
if (dim >= result.ndim)
{
throw new RuntimeException(String.Format("Source dimensions ({0}) exceeded target array dimensions ({1}).", dim, result.ndim));
}
if (seq is ndarray && seq.GetType() != typeof(ndarray))
{
// Convert to an array to ensure the dimensionality reduction
// assumption works.
ndarray array = NpyCoreApi.FromArray((ndarray)seq, null, NPYARRAYFLAGS.NPY_ENSUREARRAY);
seq = (IEnumerable <object>)array;
}
if (seq.Count() != result.Dim(dim))
{
throw new RuntimeException("AssignFromSeq: sequence/array shape mismatch.");
}
long stride = result.Stride(dim);
if (dim < result.ndim - 1)
{
// Sequence elements should be additional sequences
seq.Iteri((o, i) =>
AssignFromSeq((IEnumerable <Object>)o, result, dim + 1, offset + stride * i));
}
else
{
seq.Iteri((o, i) => result.Dtype.f.setitem(offset + i * stride, o, result.Array));
}
}
internal static ndarray EnsureArray(this NpyArray a, object o)
{
if (o == null)
{
return(null);
}
if (o.GetType() == typeof(ndarray))
{
return((ndarray)o);
}
if (o is ndarray)
{
return(NpyCoreApi.FromArray((ndarray)o, null, NPYARRAYFLAGS.NPY_ENSUREARRAY));
}
return(np.FromAny(o, flags: NPYARRAYFLAGS.NPY_ENSUREARRAY));
}
private static ndarray Concatenate(IEnumerable <ndarray> arrays, int?axis = 0)
{
int i;
bool MustFlatten = false;
if (axis == null)
{
MustFlatten = true;
axis = 0;
}
try
{
arrays.First();
}
catch (InvalidOperationException)
{
throw new ArgumentException("concatenation of zero-length sequence is impossible");
}
ndarray[] mps = NpyUtil_ArgProcessing.ConvertToCommonType(arrays);
int n = mps.Length;
if (MustFlatten)
{
// Flatten the arrays
for (i = 0; i < n; i++)
{
mps[i] = mps[i].Ravel(NPY_ORDER.NPY_CORDER);
}
axis = 0;
}
else if (axis != 0)
{
// Swap to make the axis 0
for (i = 0; i < n; i++)
{
mps[i] = NpyCoreApi.FromArray(mps[i].SwapAxes(axis.Value, 0), null, NPYARRAYFLAGS.NPY_C_CONTIGUOUS);
}
}
npy_intp[] dims = mps[0].dims;
if (dims.Length == 0)
{
throw new ArgumentException("0-d arrays can't be concatenated");
}
npy_intp new_dim = dims[0];
for (i = 1; i < n; i++)
{
npy_intp[] dims2 = mps[i].dims;
if (dims.Length != dims2.Length)
{
throw new ArgumentException("arrays must have same number of dimensions");
}
bool eq = Enumerable.Zip(dims.Skip(1), dims2.Skip(1), (a1, b) => (a1 == b)).All(x => x);
if (!eq)
{
throw new ArgumentException("array dimensions do not agree");
}
new_dim += dims2[0];
}
dims[0] = new_dim;
ndarray result = NpyCoreApi.AllocArray(mps[0].Dtype, dims.Length, dims, false);
if (NpyCoreApi.CombineInto(result, mps) < 0)
{
throw new ArgumentException("unable to concatenate these arrays");
}
if (0 < axis && axis < NpyDefs.NPY_MAXDIMS || axis < 0)
{
result = result.SwapAxes(axis.Value, 0);
}
return(result);
}
/// <summary>
/// Constructs a new array from multiple input types, like lists, arrays, etc.
/// </summary>
/// <param name="src"></param>
/// <param name="descr"></param>
/// <param name="minDepth"></param>
/// <param name="maxDepth"></param>
/// <param name="requires"></param>
/// <param name="context"></param>
/// <returns></returns>
internal static ndarray FromAny(Object src, dtype descr = null, int minDepth = 0,
int maxDepth = 0, NPYARRAYFLAGS flags = 0, Object context = null)
{
ndarray result = null;
if (src == null)
{
return(np.empty(new shape(0), NpyCoreApi.DescrFromType(NPY_TYPES.NPY_OBJECT)));
}
Type t = src.GetType();
if (t != typeof(PythonTuple))
{
if (src is ndarray)
{
result = NpyCoreApi.FromArray((ndarray)src, descr, flags);
return(FromAnyReturn(result, minDepth, maxDepth));
}
if (t.IsArray)
{
result = asanyarray(src);
}
dtype newtype = (descr ?? FindScalarType(src));
if (descr == null && newtype != null)
{
if ((flags & NPYARRAYFLAGS.NPY_UPDATEIFCOPY) != 0)
{
throw UpdateIfCopyError();
}
result = FromPythonScalar(src, newtype);
return(FromAnyReturn(result, minDepth, maxDepth));
}
//result = FromScalar(src, descr, context);
if (result != null)
{
if (descr != null && !NpyCoreApi.EquivTypes(descr, result.Dtype) || flags != 0)
{
result = NpyCoreApi.FromArray(result, descr, flags);
return(FromAnyReturn(result, minDepth, maxDepth));
}
}
}
bool is_object = false;
if ((flags & NPYARRAYFLAGS.NPY_UPDATEIFCOPY) != 0)
{
throw UpdateIfCopyError();
}
if (descr == null)
{
descr = FindArrayType(src, null);
}
else if (descr.TypeNum == NPY_TYPES.NPY_OBJECT)
{
is_object = true;
}
if (result == null)
{
bool seq = false;
if (src is IEnumerable <object> )
{
try
{
result = FromIEnumerable((IEnumerable <object>)src, descr, (flags & NPYARRAYFLAGS.NPY_FORTRAN) != 0, minDepth, maxDepth);
seq = true;
}
catch (InsufficientMemoryException)
{
throw;
}
catch
{
if (is_object)
{
result = FromNestedList(src, descr, (flags & NPYARRAYFLAGS.NPY_FORTRAN) != 0);
seq = true;
}
}
}
if (!seq)
{
result = FromScalar(src, descr, null);
}
}
return(FromAnyReturn(result, minDepth, maxDepth));
}
/// <summary>
/// Constructs a new array from multiple input types, like lists, arrays, etc.
/// </summary>
/// <param name="src"></param>
/// <param name="descr"></param>
/// <param name="minDepth"></param>
/// <param name="maxDepth"></param>
/// <param name="requires"></param>
/// <param name="context"></param>
/// <returns></returns>
public static ndarray FromAny(Object src, dtype descr = null, int minDepth = 0,
int maxDepth = 0, NPYARRAYFLAGS flags = 0, Object context = null)
{
ndarray result = null;
if (src == null)
{
return(np.empty(new shape(0), NpyCoreApi.DescrFromType(NPY_TYPES.NPY_OBJECT)));
}
Type t = src.GetType();
if (t != typeof(PythonTuple))
{
if (src is ndarray)
{
result = NpyCoreApi.FromArray((ndarray)src, descr, flags);
return(FromAnyReturn(result, minDepth, maxDepth));
}
if (t.IsArray)
{
result = asanyarray(src);
}
if (src is ScalarGeneric)
{
if ((flags & NPYARRAYFLAGS.NPY_UPDATEIFCOPY) != 0)
{
throw UpdateIfCopyError();
}
result = FromScalar((ScalarGeneric)src, descr);
return(FromAnyReturn(result, minDepth, maxDepth));
}
dtype newtype = (descr ?? FindScalarType(src));
if (descr == null && newtype != null)
{
if ((flags & NPYARRAYFLAGS.NPY_UPDATEIFCOPY) != 0)
{
throw UpdateIfCopyError();
}
result = FromPythonScalar(src, newtype);
return(FromAnyReturn(result, minDepth, maxDepth));
}
//result = FromScalar(src, descr, context);
if (result != null)
{
if (descr != null && !NpyCoreApi.EquivTypes(descr, result.Dtype) || flags != 0)
{
result = NpyCoreApi.FromArray(result, descr, flags);
return(FromAnyReturn(result, minDepth, maxDepth));
}
}
}
bool is_object = false;
if ((flags & NPYARRAYFLAGS.NPY_UPDATEIFCOPY) != 0)
{
throw UpdateIfCopyError();
}
if (descr == null)
{
descr = FindArrayType(src, null);
}
else if (descr.TypeNum == NPY_TYPES.NPY_OBJECT)
{
is_object = true;
}
if (result == null)
{
// Hack required because in C# strings are enumerations of chars, not objects.
// However, we want to keep src as a string if we are building a string or object array.
if (!is_object &&
(descr.TypeNum != NPY_TYPES.NPY_STRING || descr.Type == NPY_TYPECHAR.NPY_CHARLTR) &&
descr.TypeNum != NPY_TYPES.NPY_UNICODE && src is string && ((string)src).Length > 1)
{
src = ((string)src).Cast <object>();
}
bool seq = false;
if (src is IEnumerable <object> )
{
try
{
result = FromIEnumerable((IEnumerable <object>)src, descr, (flags & NPYARRAYFLAGS.NPY_FORTRAN) != 0, minDepth, maxDepth);
seq = true;
}
catch (InsufficientMemoryException)
{
throw;
}
catch
{
if (is_object)
{
result = FromNestedList(src, descr, (flags & NPYARRAYFLAGS.NPY_FORTRAN) != 0);
seq = true;
}
}
}
if (!seq)
{
result = FromScalar(src, descr, null);
}
}
return(FromAnyReturn(result, minDepth, maxDepth));
}
