*Last updated: 2023-03-16.*
# tf_quant_finance.math.pde.grids.rectangular_grid
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Specifies parameters for an axis-wise non-uniform grid in n-dimensions.
```python
tf_quant_finance.math.pde.grids.rectangular_grid(
axis_locations, dtype=None, name=None
)
```
This specifies rectangular grids formed by taking the cartesian product
of points along each axis. For example, in two dimensions, one may specify
a grid by specifying points along the x-axis as [0.0, 1.0, 1.3] and along the
y-axis by [3.0, 3.6, 4.3, 7.0]. Taking the cartesian product of the two,
produces a 3 x 4 grid which is rectangular but non-uniform along each axis.
The points along each axis should be in ascending order and there must be at
least two points specified along each axis. If `validate_args` is set to
True, both these conditions are explicitly verified.
#### Args:
* `axis_locations`: A Python iterable of rank 1 real `Tensor`s. The number of
`Tensor`s in the list is the dimension of the grid. The i'th element
specifies the coordinates of the points of the grid along that axis. Each
`Tensor` must have at least two elements.
* `dtype`: Optional tf.dtype. The default dtype to use for the grid..
* `name`: Python str. The name prefixed to the ops created by this class. If not
supplied, the default name 'rectangular_grid' is used.
#### Returns:
The grid locations as projected along each axis. One `Tensor` of shape
`[..., n]`, where `n` is the number of points along that axis. The first
dimensions are the batch shape. The grid itself can be seen as a cartesian
product of the locations array.
#### Raises:
ValueError if `axis_locations` is empty.