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);
}