# xarray.DataArray.dot

#### DataArray.dot(other, dim=None)[[source]](https://github.com/pydata/xarray/blob/main/xarray/core/dataarray.py#L5285-L5351)

Perform dot product of two DataArrays along their shared dims.

Equivalent to taking taking tensordot over all shared dims.

* **Parameters:**
  * **other** ([`DataArray`](xarray.DataArray.html.md#xarray.DataArray)) – The other array with which the dot product is performed.
  * **dim** ([`...`](https://docs.python.org/3/builtins/constants.html#Ellipsis), [`str`](xarray.DataArray.str.html.md#xarray.DataArray.str), `Iterable` of `Hashable` or [`None`](https://docs.python.org/3/builtins/constants.html#None), *optional*) – Which dimensions to sum over. Ellipsis (…) sums over all dimensions.
    If not specified, then all the common dimensions are summed over.
* **Returns:**
  **result** ([`DataArray`](xarray.DataArray.html.md#xarray.DataArray)) – Array resulting from the dot product over all shared dimensions.

#### SEE ALSO
[`dot`](xarray.dot.html.md#xarray.dot), [`numpy.tensordot`](https://numpy.org/doc/stable/reference/generated/numpy.tensordot.html#numpy.tensordot)

### Notes

This method automatically aligns coordinates by their values (not their order).
See [Automatic alignment](../user-guide/computation.html.md#math-automatic-alignment) and [`xarray.dot()`](xarray.dot.html.md#xarray.dot) for more details.

### Examples

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```pycon
>>> da_vals = np.arange(6 * 5 * 4).reshape((6, 5, 4))
>>> da = xr.DataArray(da_vals, dims=["x", "y", "z"])
>>> dm_vals = np.arange(4)
>>> dm = xr.DataArray(dm_vals, dims=["z"])
```

```pycon
>>> dm.dims
('z',)
```

```pycon
>>> da.dims
('x', 'y', 'z')
```

```pycon
>>> dot_result = da.dot(dm)
>>> dot_result.dims
('x', 'y')
```

Coordinates are aligned by their values:

```pycon
>>> x = xr.DataArray([1, 10], coords=[("foo", ["a", "b"])])
>>> y = xr.DataArray([2, 20], coords=[("foo", ["b", "a"])])
>>> x.dot(y)
<xarray.DataArray ()> Size: 8B
array(40)
```

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