scipp.concatenate

scipp.concatenate(x, y, dim)

Concatenate input arrays along the given dimension.

Concatenation can happen in two ways:

  • Along an existing dimension, yielding a new dimension extent given by the sum of the input’s extents.

  • Along a new dimension that is not contained in either of the inputs, yielding an output with one extra dimensions.

In the case of a data array or dataset, the coords, and masks are also concatenated. Coords, and masks for any but the given dimension are required to match and are copied to the output without changes.

Parameters

  • x (VariableLike) – Left hand side input.

  • y (VariableLike) – Right hand side input.

  • dim (str) – Dimension along which to concatenate.

Raises

If the dtype or unit does not match, or if the dimensions and shapes are incompatible.

Returns

The absolute values of the input.

Return type

VariableLike

Examples:

>>> a = sc.arange('x', 3)
>>> b = 100 * sc.arange('x', 3)
>>> c = sc.concatenate(a, b, dim='x')
>>> c
<scipp.Variable> (x: 6)      int64  [dimensionless]  [0, 1, ..., 100, 200]
>>> c.values
array([  0,   1,   2,   0, 100, 200])

>>> d = sc.concatenate(a, b, dim='y')
>>> d
<scipp.Variable> (y: 2, x: 3)      int64  [dimensionless]  [0, 1, ..., 100, 200]
>>> d.values
array([[  0,   1,   2],
       [  0, 100, 200]])

>>> x = sc.DataArray(sc.arange('x', 3), coords={'x': sc.arange('x', 3)})
>>> y = sc.DataArray(100 * sc.arange('x', 3), coords={'x': 100 * sc.arange('x', 3)})
>>> z = sc.concatenate(x, y, dim='x')
>>> z
<scipp.DataArray>
Dimensions: Sizes[x:6, ]
Coordinates:
  x                           int64  [dimensionless]  (x)  [0, 1, ..., 100, 200]
Data:
                              int64  [dimensionless]  (x)  [0, 1, ..., 100, 200]
>>> z.values
array([  0,   1,   2,   0, 100, 200])