internal static ndarray FromPythonScalar(object src, dtype descr)
{
int itemsize = descr.ElementSize;
NPY_TYPES type = descr.TypeNum;
if (itemsize == 0 && NpyDefs.IsExtended(type))
{
int n = PythonOps.Length(src);
if (type == NPY_TYPES.NPY_UNICODE)
{
n *= 4;
}
descr = new dtype(descr);
descr.ElementSize = n;
}
ndarray result = NpyCoreApi.AllocArray(descr, 0, null, false);
if (result.ndim > 0)
{
throw new ArgumentException("shape-mismatch on array construction");
}
result.Dtype.f.setitem(0, src, result.Array);
return(result);
}
private static ndarray FromScalar(object src, dtype descr, object context)
{
npy_intp[] dims = new npy_intp[1] {
1
};
ndarray result = NpyCoreApi.AllocArray(descr, 1, dims, false);
if (result.ndim != 1)
{
throw new ArgumentException("shape-mismatch on array construction");
}
result.Dtype.f.setitem(0, src, result.Array);
return(result);
}
internal static ndarray FromNestedList(object src, dtype descr, bool fortran)
{
npy_intp[] dims = new npy_intp[NpyDefs.NPY_MAXDIMS];
int nd = ObjectDepthAndDimension(src, dims, 0, NpyDefs.NPY_MAXDIMS);
if (nd == 0)
{
return(FromPythonScalar(src, descr));
}
ndarray result = NpyCoreApi.AllocArray(descr, nd, dims, fortran);
AssignToArray(src, result);
return(result);
}
/// <summary>
/// Builds an array from a sequence of objects. The elements of the sequence
/// can also be sequences in which case this function recursively walks the
/// nested sequences and builds an n dimentional array.
///
/// IronPython tuples and lists work as sequences.
/// </summary>
/// <param name="src">Input sequence</param>
/// <param name="descr">Desired array element type or null to determine automatically</param>
/// <param name="fortran">True if array should be Fortran layout, false for C</param>
/// <param name="minDepth"></param>
/// <param name="maxDepth"></param>
/// <returns>New array instance</returns>
internal static ndarray FromIEnumerable(IEnumerable <Object> src, dtype descr,
bool fortran, int minDepth, int maxDepth)
{
ndarray result = null;
if (descr == null)
{
descr = FindArrayType(src, null, NpyDefs.NPY_MAXDIMS);
}
int itemsize = descr.ElementSize;
NPY_TYPES type = descr.TypeNum;
bool checkIt = true;
bool stopAtString =
type != NPY_TYPES.NPY_STRING ||
descr.Type == (char)NPY_TYPECHAR.NPY_STRINGLTR;
bool stopAtTuple = false;
int numDim = DiscoverDepth(src, NpyDefs.NPY_MAXDIMS + 1, stopAtString, stopAtTuple);
if (numDim == 0)
{
return(FromPythonScalar(src, descr));
}
else
{
if (maxDepth > 0 && type == NPY_TYPES.NPY_OBJECT &&
numDim > maxDepth)
{
numDim = maxDepth;
}
if (maxDepth > 0 && numDim > maxDepth ||
minDepth > 0 && numDim < minDepth)
{
throw new ArgumentException("Invalid number of dimensions.");
}
npy_intp[] dims = new npy_intp[numDim];
DiscoverDimensions(src, numDim, dims, 0, checkIt);
result = NpyCoreApi.AllocArray(descr, numDim, dims, fortran);
AssignToArray(src, result);
}
return(result);
}
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>
/// Builds an array from a sequence of objects. The elements of the sequence
/// can also be sequences in which case this function recursively walks the
/// nested sequences and builds an n dimentional array.
///
/// IronPython tuples and lists work as sequences.
/// </summary>
/// <param name="src">Input sequence</param>
/// <param name="descr">Desired array element type or null to determine automatically</param>
/// <param name="fortran">True if array should be Fortran layout, false for C</param>
/// <param name="minDepth"></param>
/// <param name="maxDepth"></param>
/// <returns>New array instance</returns>
internal static ndarray FromIEnumerable(IEnumerable <Object> src, dtype descr,
bool fortran, int minDepth, int maxDepth)
{
ndarray result = null;
if (descr == null)
{
descr = FindArrayType(src, null, NpyDefs.NPY_MAXDIMS);
}
int itemsize = descr.ElementSize;
NPY_TYPES type = descr.TypeNum;
bool checkIt = (descr.Type != NPY_TYPECHAR.NPY_CHARLTR);
bool stopAtString =
type != NPY_TYPES.NPY_STRING ||
descr.Type == NPY_TYPECHAR.NPY_STRINGLTR;
bool stopAtTuple =
type == NPY_TYPES.NPY_VOID &&
(descr.HasNames || descr.HasSubarray);
int numDim = DiscoverDepth(src, NpyDefs.NPY_MAXDIMS + 1, stopAtString, stopAtTuple);
if (numDim == 0)
{
return(FromPythonScalar(src, descr));
}
else
{
if (maxDepth > 0 && type == NPY_TYPES.NPY_OBJECT &&
numDim > maxDepth)
{
numDim = maxDepth;
}
if (maxDepth > 0 && numDim > maxDepth ||
minDepth > 0 && numDim < minDepth)
{
throw new ArgumentException("Invalid number of dimensions.");
}
npy_intp[] dims = new npy_intp[numDim];
DiscoverDimensions(src, numDim, dims, 0, checkIt);
if (descr.Type == NPY_TYPECHAR.NPY_CHARLTR &&
numDim > 0 && dims[numDim - 1] == 1)
{
numDim--;
}
if (itemsize == 0 && NpyDefs.IsExtended(descr.TypeNum))
{
itemsize = DiscoverItemsize(src, numDim, 0);
if (descr.TypeNum == NPY_TYPES.NPY_UNICODE)
{
itemsize *= 4;
}
descr = new dtype(descr);
descr.ElementSize = itemsize;
}
result = NpyCoreApi.AllocArray(descr, numDim, dims, fortran);
AssignToArray(src, result);
}
return(result);
}